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Kassavin M, Chang KJ. Computed Tomography Colonography: 2025 Update. Radiol Clin North Am 2025; 63:405-417. [PMID: 40221183 DOI: 10.1016/j.rcl.2024.09.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/14/2025]
Abstract
Colorectal cancer (CRC) is the second leading cause of cancer-related deaths in the United States. Most cases arise from polyps, which can be detected and removed before becoming cancerous. Computed tomography colonography (CTC), also known as virtual colonoscopy, was first introduced in 1994 as a minimally invasive method for CRC screening and diagnosis. This 2025 update on CTC will focus on (1) techniques and dose reduction strategies, (2) image display methods, (3) reporting and classification systems, (4) tumor staging capabilities, (5) integration of advanced imaging techniques, and (6) cost-effectiveness and reimbursement.
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Affiliation(s)
- Monica Kassavin
- Department of Radiology, Boston University Chobanian and Avedisian School of Medicine, Radiology- FGH 3, 820 Harrison Avenue, Boston, MA 02118, USA
| | - Kevin J Chang
- Department of Radiology, Boston University Chobanian and Avedisian School of Medicine, Radiology- FGH 3, 820 Harrison Avenue, Boston, MA 02118, USA.
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Wang S, Medrano MJ, Imran AAZ, Lee W, Cao JJ, Stevens GM, Tse JR, Wang AS. Automated estimation of individualized organ-specific dose and noise from clinical CT scans. Phys Med Biol 2025; 70:035014. [PMID: 39761638 DOI: 10.1088/1361-6560/ada67f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2024] [Accepted: 01/06/2025] [Indexed: 01/30/2025]
Abstract
Objective. Radiation dose and diagnostic image quality are opposing constraints in x-ray computed tomography (CT). Conventional methods do not fully account for organ-level radiation dose and noise when considering radiation risk and clinical task. In this work, we develop a pipeline to generate individualized organ-specific dose and noise at desired dose levels from clinical CT scans.Approach. To estimate organ-specific dose and noise, we compute dose maps, noise maps at desired dose levels and organ segmentations. In our pipeline, dose maps are generated using Monte Carlo simulation. The noise map is obtained by scaling the inserted noise in synthetic low-dose emulation in order to avoid anatomical structures, where the scaling coefficients are empirically calibrated. Organ segmentations are generated by a deep learning-based method (TotalSegmentator). The proposed noise model is evaluated on a clinical dataset of 12 CT scans, a phantom dataset of 3 uniform phantom scans, and a cross-site dataset of 26 scans. The accuracy of deep learning-based segmentations for organ-level dose and noise estimates was tested using a dataset of 41 cases with expert segmentations of six organs: lungs, liver, kidneys, bladder, spleen, and pancreas.Main results. The empirical noise model performs well, with an average RMSE approximately 1.5 HU and an average relative RMSE approximately 5% across different dose levels. The segmentation from TotalSegmentator yielded a mean Dice score of 0.8597 across the six organs (max = 0.9315 in liver, min = 0.6855 in pancreas). The resulting error in organ-level dose and noise estimation was less than 2% for most organs.Significance. The proposed pipeline can output individualized organ-specific dose and noise estimates accurately for personalized protocol evaluation and optimization. It is fully automated and can be scalable to large clinical datasets. This pipeline can be used to optimize image quality for specific organs and thus clinical tasks, without adversely affecting overall radiation dose.
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Affiliation(s)
- Sen Wang
- Department of Radiology, Stanford University, Stanford, CA 94305, United States of America
| | - Maria Jose Medrano
- Department of Radiology, Stanford University, Stanford, CA 94305, United States of America
| | - Abdullah Al Zubaer Imran
- Department of Radiology, Stanford University, Stanford, CA 94305, United States of America
- University of Kentucky, Lexington, KY 40506, United States of America
| | - Wonkyeong Lee
- Department of Radiology, Stanford University, Stanford, CA 94305, United States of America
| | - Jennie Jiayi Cao
- Department of Radiology, Stanford University, Stanford, CA 94305, United States of America
| | | | - Justin Ruey Tse
- Department of Radiology, Stanford University, Stanford, CA 94305, United States of America
| | - Adam S Wang
- Department of Radiology, Stanford University, Stanford, CA 94305, United States of America
- Department of Electrical Engineering, Stanford University, Stanford, CA 94305, United States of America
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McWilliams N, Perl J, McCavana J, Cournane S, Vintró LL. Development of a TOPAS Monte Carlo (MC) model extension to simulate the automatic exposure control function of a C-arm CBCT. Phys Med 2024; 125:104506. [PMID: 39197264 DOI: 10.1016/j.ejmp.2024.104506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 07/18/2024] [Accepted: 08/23/2024] [Indexed: 09/01/2024] Open
Abstract
PURPOSE Accurate simulation of organ doses in C-arm CBCT is critical for estimating personalised patient dosimetry. However, system complexities such as automatic exposure control (AEC) and the incorporation of DICOM images into simulations are challenging. The aim of this study was to develop a model for mimicking the operation of an AEC system, which maintains a constant dose to the detector through mA modulation in order to facilitate more accurate MC dosimetry models for C-arm CBCT. METHODS A Siemens Artis Q Interventional Radiology (IR) C-arm system [Siemens, Erlangen, Germany] was modelled in TOol for PArticle Simulation (TOPAS) by incorporating system specifications such as rotational speed, number of projections and exam protocol parameters. A novel threshold scorer, AECScorer, was developed to model the AEC functionality. MC simulations were performed using a variety of imaged volumes including a CTDI phantom, an anthropomorphic phantom and a patient DICOM dataset. RESULTS The AECScorer extension provides a framework for a conditional scoring function within TOPAS which allows for the simulation of an AEC system. The AECScorer successfully equalises the dose to the detector for simple phantoms and DICOM imaging datasets by adjusting the number of histories simulated at each CBCT projection. This AECSCorer tool is applicable to other medical imaging systems requiring AEC simulation. CONCLUSIONS We demonstrate a novel threshold scorer in TOPAS for a C-arm CBCT setup. The presented AECScorer is the first step towards providing a system-, patient- and protocol-specific dose estimates from CBCT dosimetry applications.
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Affiliation(s)
- Nina McWilliams
- Department of Medical Physics and Clinical Engineering, St Vincent's University Hospital, Dublin, Ireland; UCD Centre for Physics in Health and Medicine, School of Physics, University College Dublin, Dublin 4, Ireland.
| | - Joseph Perl
- The SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA 94025, United States
| | - Jackie McCavana
- Department of Medical Physics and Clinical Engineering, St Vincent's University Hospital, Dublin, Ireland; UCD Centre for Physics in Health and Medicine, School of Physics, University College Dublin, Dublin 4, Ireland
| | - Seán Cournane
- Department of Medical Physics and Clinical Engineering, St Vincent's University Hospital, Dublin, Ireland; UCD Centre for Physics in Health and Medicine, School of Physics, University College Dublin, Dublin 4, Ireland
| | - Luis León Vintró
- UCD Centre for Physics in Health and Medicine, School of Physics, University College Dublin, Dublin 4, Ireland
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Marcus RP, Nagy DA, Feuerriegel GC, Anhaus J, Nanz D, Sutter R. Photon-Counting Detector CT With Denoising for Imaging of the Osseous Pelvis at Low Radiation Doses: A Phantom Study. AJR Am J Roentgenol 2024; 222:e2329765. [PMID: 37646387 DOI: 10.2214/ajr.23.29765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
Abstract
BACKGROUND. Photon-counting detector (PCD) CT may allow lower radiation doses than used for conventional energy-integrating detector (EID) CT, with preserved image quality. OBJECTIVE. The purpose of this study was to compare PCD CT and EID CT, reconstructed with and without a denoising tool, in terms of image quality of the osseous pelvis in a phantom, with attention to low radiation doses. METHODS. A pelvic phantom comprising human bones in acrylic material mimicking soft tissue underwent PCD CT and EID CT at various tube potentials and radiation doses ranging from 0.05 to 5.00 mGy. Additional denoised reconstructions were generated using a commercial tool. Noise was measured in the acrylic material. Two readers performed independent qualitative assessments that entailed determining the denoised EID CT reconstruction with the lowest acceptable dose and then comparing this reference reconstruction with PCD CT reconstructions without and with denoising, using subjective Likert scales. RESULTS. Noise was lower for PCD CT than for EID CT. For instance, at 0.05 mGy and 100 kV with tin filter, noise was 38.4 HU for PCD CT versus 48.8 HU for EID CT. Denoising further reduced noise; for example, for PCD CT at 100 kV with tin filter at 0.25 mGy, noise was 19.9 HU without denoising versus 9.7 HU with denoising. For both readers, lowest acceptable dose for EID CT was 0.10 mGy (total score, 11 of 15 for both readers). Both readers somewhat agreed that PCD CT without denoising at 0.10 mGy (reflecting reference reconstruction dose) was relatively better than the reference reconstruction in terms of osseous structures, artifacts, and image quality. Both readers also somewhat agreed that denoised PCD CT reconstructions at 0.10 mGy and 0.05 mGy (reflecting matched and lower doses, respectively, with respect to reference reconstruction dose) were relatively better than the reference reconstruction for the image quality measures. CONCLUSION. PCD CT showed better-quality images than EID CT when performed at the lowest acceptable radiation dose for EID CT. PCD CT with denoising yielded better-quality images at a dose lower than lowest acceptable dose for EID CT. CLINICAL IMPACT. PCD CT with denoising could facilitate lower radiation doses for pelvic imaging.
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Affiliation(s)
- Roy P Marcus
- Department of Radiology, Balgrist University Hospital Zurich, Forchstrasse 340, Zurich 8008, Switzerland
- Faculty of Medicine, University of Zurich, Zurich, Switzerland
| | - Daniel A Nagy
- Department of Radiology, Balgrist University Hospital Zurich, Forchstrasse 340, Zurich 8008, Switzerland
- Faculty of Medicine, University of Zurich, Zurich, Switzerland
| | - Georg C Feuerriegel
- Department of Radiology, Balgrist University Hospital Zurich, Forchstrasse 340, Zurich 8008, Switzerland
- Faculty of Medicine, University of Zurich, Zurich, Switzerland
| | | | - Daniel Nanz
- Faculty of Medicine, University of Zurich, Zurich, Switzerland
- Swiss Center for Musculoskeletal Imaging, Balgrist Campus, Zurich, Switzerland
| | - Reto Sutter
- Department of Radiology, Balgrist University Hospital Zurich, Forchstrasse 340, Zurich 8008, Switzerland
- Faculty of Medicine, University of Zurich, Zurich, Switzerland
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Brady SL. Implementation of AI image reconstruction in CT-how is it validated and what dose reductions can be achieved. Br J Radiol 2023; 96:20220915. [PMID: 37102695 PMCID: PMC10546449 DOI: 10.1259/bjr.20220915] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 03/10/2023] [Accepted: 03/15/2023] [Indexed: 04/28/2023] Open
Abstract
CT reconstruction has undergone a substantial change over the last decade with the introduction of iterative reconstruction (IR) and now with deep learning reconstruction (DLR). In this review, DLR will be compared to IR and filtered back-projection (FBP) reconstructions. Comparisons will be made using image quality metrics such as noise power spectrum, contrast-dependent task-based transfer function, and non-prewhitening filter detectability index (dNPW'). Discussion on how DLR has impacted CT image quality, low-contrast detectability, and diagnostic confidence will be provided. DLR has shown the ability to improve in areas that IR is lacking, namely: noise magnitude reduction does not alter noise texture to the degree that IR did, and the noise texture found in DLR is more aligned with noise texture of an FBP reconstruction. Additionally, the dose reduction potential for DLR is shown to be greater than IR. For IR, the consensus was dose reduction should be limited to no more than 15-30% to preserve low-contrast detectability. For DLR, initial phantom and patient observer studies have shown acceptable dose reduction between 44 and 83% for both low- and high-contrast object detectability tasks. Ultimately, DLR is able to be used for CT reconstruction in place of IR, making it an easy "turnkey" upgrade for CT reconstruction. DLR for CT is actively being improved as more vendor options are being developed and current DLR options are being enhanced with second generation algorithms being released. DLR is still in its developmental early stages, but is shown to be a promising future for CT reconstruction.
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Dieckmeyer M, Sollmann N, Kupfer K, Löffler MT, Paprottka KJ, Kirschke JS, Baum T. Computed Tomography of the Head : A Systematic Review on Acquisition and Reconstruction Techniques to Reduce Radiation Dose. Clin Neuroradiol 2023; 33:591-610. [PMID: 36862232 PMCID: PMC10449676 DOI: 10.1007/s00062-023-01271-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 01/24/2023] [Indexed: 03/03/2023]
Abstract
In 1971, the first computed tomography (CT) scan was performed on a patient's brain. Clinical CT systems were introduced in 1974 and dedicated to head imaging only. New technological developments, broader availability, and the clinical success of CT led to a steady growth in examination numbers. Most frequent indications for non-contrast CT (NCCT) of the head include the assessment of ischemia and stroke, intracranial hemorrhage and trauma, while CT angiography (CTA) has become the standard for first-line cerebrovascular evaluation; however, resulting improvements in patient management and clinical outcomes come at the cost of radiation exposure, increasing the risk for secondary morbidity. Therefore, radiation dose optimization should always be part of technical advancements in CT imaging but how can the dose be optimized? What dose reduction can be achieved without compromising diagnostic value, and what is the potential of the upcoming technologies artificial intelligence and photon counting CT? In this article, we look for answers to these questions by reviewing dose reduction techniques with respect to the major clinical indications of NCCT and CTA of the head, including a brief perspective on what to expect from current and future developments in CT technology with respect to radiation dose optimization.
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Affiliation(s)
- Michael Dieckmeyer
- Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Nico Sollmann
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Karina Kupfer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Maximilian T. Löffler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Freiburg im Breisgau, Germany
| | - Karolin J. Paprottka
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Jan S. Kirschke
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Thomas Baum
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
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Agostini A, Borgheresi A, Mariotti F, Ottaviani L, Carotti M, Valenti M, Giovagnoni A. New Frontiers in Oncological Imaging With Computed Tomography: From Morphology to Function. Semin Ultrasound CT MR 2023; 44:214-227. [PMID: 37245886 DOI: 10.1053/j.sult.2023.03.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]
Abstract
The latest evolutions in Computed Tomography (CT) technology have several applications in oncological imaging. The innovations in hardware and software allow for the optimization of the oncological protocol. Low-kV acquisitions are possible thanks to the new powerful tubes. Iterative reconstruction algorithms and artificial intelligence are helpful for the management of image noise during image reconstruction. Functional information is provided by spectral CT (dual-energy and photon counting CT) and perfusion CT.
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Affiliation(s)
- Andrea Agostini
- Department of Clinical, Special and Dental Sciences. University Politecnica delle Marche, Ancona, Italy; Department of Radiological Sciences, Division of Clinical Radiology, University Hospital "Azienda Ospedaliero Universitaria delle Marche", Ancona, Italy.
| | - Alessandra Borgheresi
- Department of Clinical, Special and Dental Sciences. University Politecnica delle Marche, Ancona, Italy; Department of Radiological Sciences, Division of Clinical Radiology, University Hospital "Azienda Ospedaliero Universitaria delle Marche", Ancona, Italy
| | - Francesco Mariotti
- Department of Radiological Sciences, Division of Medical Physics, University Hospital "Azienda Ospedaliero Universitaria delle Marche", Ancona, Italy
| | - Letizia Ottaviani
- Department of Radiological Sciences, Division of Clinical Radiology, University Hospital "Azienda Ospedaliero Universitaria delle Marche", Ancona, Italy
| | - Marina Carotti
- Department of Clinical, Special and Dental Sciences. University Politecnica delle Marche, Ancona, Italy; Department of Radiological Sciences, Division of Clinical Radiology, University Hospital "Azienda Ospedaliero Universitaria delle Marche", Ancona, Italy
| | - Marco Valenti
- Department of Radiological Sciences, Division of Medical Physics, University Hospital "Azienda Ospedaliero Universitaria delle Marche", Ancona, Italy
| | - Andrea Giovagnoni
- Department of Clinical, Special and Dental Sciences. University Politecnica delle Marche, Ancona, Italy; Department of Radiological Sciences, Division of Clinical Radiology, University Hospital "Azienda Ospedaliero Universitaria delle Marche", Ancona, Italy
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Computed Tomography of the Spine. Clin Neuroradiol 2022; 33:271-291. [DOI: 10.1007/s00062-022-01227-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 10/10/2022] [Indexed: 11/24/2022]
Abstract
AbstractThe introduction of the first whole-body CT scanner in 1974 marked the beginning of cross-sectional spine imaging. In the last decades, the technological advancement, increasing availability and clinical success of CT led to a rapidly growing number of CT examinations, also of the spine. After initially being primarily used for trauma evaluation, new indications continued to emerge, such as assessment of vertebral fractures or degenerative spine disease, preoperative and postoperative evaluation, or CT-guided interventions at the spine; however, improvements in patient management and clinical outcomes come along with higher radiation exposure, which increases the risk for secondary malignancies. Therefore, technical developments in CT acquisition and reconstruction must always include efforts to reduce the radiation dose. But how exactly can the dose be reduced? What amount of dose reduction can be achieved without compromising the clinical value of spinal CT examinations and what can be expected from the rising stars in CT technology: artificial intelligence and photon counting CT? In this article, we try to answer these questions by systematically reviewing dose reduction techniques with respect to the major clinical indications of spinal CT. Furthermore, we take a concise look on the dose reduction potential of future developments in CT hardware and software.
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Klein L, Liu C, Steidel J, Enzmann L, Knaup M, Sawall S, Maier A, Lell M, Maier J, Kachelrieß M. Patient-specific radiation risk-based tube current modulation for diagnostic CT. Med Phys 2022; 49:4391-4403. [PMID: 35421263 DOI: 10.1002/mp.15673] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Revised: 03/11/2022] [Accepted: 03/29/2022] [Indexed: 11/08/2022] Open
Abstract
PURPOSE Modern CT scanners use automatic exposure control (AEC) techniques, such as tube current modulation (TCM), to reduce dose delivered to patients while maintaining image quality. In contrast to conventional approaches that minimize the tube current time product of the CT scan, referred to as mAsTCM in the following, we herein propose a new method referred to as riskTCM which aims at reducing the radiation risk to the patient by taking into account the specific radiation risk of every dose-sensitive organ. METHODS For current mAsTCM implementations, the mAs-product is used as a surrogate for the patient dose. Thus they do not take into account the varying dose sensitivity of different organs. Our riskTCM framework assumes that a coarse CT reconstruction, an organ segmentation and an estimation of the dose distribution can be provided in real time, e.g. by applying machine learning techniques. Using this information riskTCM determines a tube current curve that minimizes a patient risk measure, e.g. the effective dose, while keeping the image quality constant. We retrospectively applied riskTCM to 20 patients covering all relevant anatomical regions and tube voltages from 70 kV to 150 kV. The potential reduction of effective dose at same image noise is evaluated as a figure of merit and compared to mAsTCM and to a situation with a constant tube current referred to as noTCM. RESULTS Anatomical regions like the neck, thorax, abdomen and the pelvis benefit from the proposed riskTCM. On average, a reduction of effective dose of about 23 % for the thorax, 31 % for the abdomen, 24 % for the pelvis, and 27% for the neck have been evaluated compared to today's state-of-the-art mAsTCM. For the head, the resulting reduction of effective dose is lower, about 13 % on average compared to mAsTCM. CONCLUSIONS With a risk-minimizing tube current modulation, significant higher reduction of effective dose compared to mAs-minimizing tube current modulation is possible. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Laura Klein
- Division of X-Ray Imaging and CT, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Physics and Astronomy, Ruprecht-Karls-University Heidelberg, Heidelberg, Germany
| | - Chang Liu
- Pattern Recognition Lab, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Jörg Steidel
- Division of X-Ray Imaging and CT, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Physics and Astronomy, Ruprecht-Karls-University Heidelberg, Heidelberg, Germany
| | - Lucia Enzmann
- Division of X-Ray Imaging and CT, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Physics and Astronomy, Ruprecht-Karls-University Heidelberg, Heidelberg, Germany
| | - Michael Knaup
- Division of X-Ray Imaging and CT, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Stefan Sawall
- Division of X-Ray Imaging and CT, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Medical Faculty, Ruprecht-Karls-University Heidelberg, Heidelberg, Germany
| | - Andreas Maier
- Pattern Recognition Lab, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Michael Lell
- Department of Radiology and Nuclear Medicine, Klinikum Nürnberg, Paracelsus Medical University, Nürnberg
| | - Joscha Maier
- Division of X-Ray Imaging and CT, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Marc Kachelrieß
- Division of X-Ray Imaging and CT, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Medical Faculty, Ruprecht-Karls-University Heidelberg, Heidelberg, Germany
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Hoyoshi K, Ohmura T, Kayano S, Goto M, Muramatsu S, Homma N. [A Review of Current Knowledge for X-ray Energy in CT: Practical Guide for CT Technologist]. Nihon Hoshasen Gijutsu Gakkai Zasshi 2022; 78:449-463. [PMID: 35400711 DOI: 10.6009/jjrt.2022-1238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
In computed tomography (CT) systems, the optimal X-ray energy in imaging depends on the material composition and the subject size. Among the parameters related to the X-ray energy, we can arbitrarily change only the tube voltage. For years, the tube voltage has often been set at 120 kVp. However, since about 2000, there has been an increasing interest in reducing radiation dose, and it has led to the publication of various reports on low tube voltage. Furthermore, with the spread of dual-energy CT, virtual monochromatic X-ray images are widely used since the contrast can be adjusted by selecting the optional energy. Therefore, because of the renewed interest in X-ray energy in CT imaging, the issue of energy and imaging needs to be summarized. In this article, we describe the basics of physical characteristics of X-ray attenuation with materials and its influence on the process of CT imaging. Moreover, the relationship between X-ray energy and CT imaging is discussed for clinical applications.
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Affiliation(s)
- Kazutaka Hoyoshi
- Department of Radiology, Yamagata University Hospital.,Department of Radiological Imaging and Informatics, Tohoku University Graduate School of Medicine
| | - Tomomi Ohmura
- Department of Radiology and Nuclear Medicine, Akita Cerebrospinal and Cardiovascular Center
| | - Shingo Kayano
- Department of Radiological Technology, Tohoku University Hospital
| | - Mitsunori Goto
- Department of Radiological Technology, Miyagi Cancer Center (Current address: Department of Radiology, Fujita Health University Hospital)
| | | | - Noriyasu Homma
- Department of Radiological Imaging and Informatics, Tohoku University Graduate School of Medicine
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Maier J, Klein L, Eulig E, Sawall S, Kachelrieß M. Real-time estimation of patient-specific dose distributions for medical CT using the deep dose estimation. Med Phys 2022; 49:2259-2269. [PMID: 35107176 DOI: 10.1002/mp.15488] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 12/08/2021] [Accepted: 01/08/2022] [Indexed: 12/30/2022] Open
Abstract
PURPOSE With the rising number of computed tomography (CT) examinations and the trend toward personalized medicine, patient-specific dose estimates are becoming more and more important in CT imaging. However, current approaches are often too slow or too inaccurate to be applied routinely. Therefore, we propose the so-called deep dose estimation (DDE) to provide highly accurate patient dose distributions in real time METHODS: To combine accuracy and computational performance, the DDE algorithm uses a deep convolutional neural network to predict patient dose distributions. To do so, a U-net like architecture is trained to reproduce Monte Carlo simulations from a two-channel input consisting of a CT reconstruction and a first-order dose estimate. Here, the corresponding training data were generated using CT simulations based on 45 whole-body patient scans. For each patient, simulations were performed for different anatomies (pelvis, abdomen, thorax, head), different tube voltages (80 kV, 100 kV, 120 kV), different scan trajectories (circle, spiral), and with and without bowtie filtration and tube current modulation. Similar simulations were performed using a second set of eight whole-body CT scans from the Visual Concept Extraction Challenge in Radiology (Visceral) project to generate testing data. Finally, the DDE algorithm was evaluated with respect to the generalization to different scan parameters and the accuracy of organ dose and effective dose estimates based on an external organ segmentation. RESULTS DDE dose distributions were quantified in terms of the mean absolute percentage error (MAPE) and a gamma analysis with respect to the ground truth Monte Carlo simulation. Both measures indicate that DDE generalizes well to different scan parameters and different anatomical regions with a maximum MAPE of 6.3% and a minimum gamma passing rate of 91%. Evaluating the organ dose values for all organs listed in the International Commission on Radiological Protection (ICRP) recommendation, shows an average error of 3.1% and maximum error of 7.2% (bone surface). CONCLUSIONS The DDE algorithm provides an efficient approach to determine highly accurate dose distributions. Being able to process a whole-body CT scan in about 1.5 s, it provides a valuable alternative to Monte Carlo simulations on a graphics processing unit (GPU). Here, the main advantage of DDE is that it can be used on top of any existing Monte Carlo code such that real-time performance can be achieved without major adjustments. Thus, DDE opens up new options not only for dosimetry but also for scan and protocol optimization.
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Affiliation(s)
- Joscha Maier
- German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Laura Klein
- German Cancer Research Center (DKFZ), Heidelberg, Germany.,Ruprecht-Karls-University, Heidelberg, Germany
| | - Elias Eulig
- German Cancer Research Center (DKFZ), Heidelberg, Germany.,Ruprecht-Karls-University, Heidelberg, Germany
| | - Stefan Sawall
- German Cancer Research Center (DKFZ), Heidelberg, Germany.,Ruprecht-Karls-University, Heidelberg, Germany
| | - Marc Kachelrieß
- German Cancer Research Center (DKFZ), Heidelberg, Germany.,Ruprecht-Karls-University, Heidelberg, Germany
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Yoshida M, Nakaura T, Oda S, Kidoh M, Nagayama Y, Uetani H, Azuma M, Sakabe D, Hirai T, Funama Y. Effects of tube voltage and iodine contrast medium on radiation dose of whole-body CT. Acta Radiol 2022; 63:458-466. [PMID: 33709794 DOI: 10.1177/02841851211001539] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND The low-tube-voltage scan generally needs a higher tube current than the conventional 120 kVp to maintain the image noise. In addition, the low-tube-voltage scan increases the photoelectric effect, which increases the radiation absorption in organs. PURPOSE To compare the organ radiation dose caused by iodine contrast medium between low tube voltage with low contrast medium and that of conventional 120-kVp protocol with standard contrast medium. MATERIAL AND METHODS After the propensity-matching analysis, 66 patients were enrolled including 33 patients with 120 kVp and 600 mgI/kg and 33 patients with 80 kVp and 300 mgI/kg (50% iodine reduction). The pre- and post-contrast phases were assessed in all patients. The Monte Carlo simulation tool was used to simulate the radiation dose. The computed tomography (CT) numbers for 10 organs and the organ doses were measured. The organ doses were normalized by the volume CT dose index, and the 120-kVp protocol was compared with the 80-kVp protocol. RESULTS On contrast-enhanced CT, there were no significant differences in the mean CT numbers of the organs between 80-kVp and 120-kVp protocols except for the pancreas, kidneys, and small intestine. The normalized organ doses at 80 kVp were significantly lower than those of 120 kVp in all organs (e.g. liver, 1.6 vs. 1.9; pancreas, 1.5 vs. 1.8; spleen, 1.7 vs. 2.0) on contrast-enhanced CT. CONCLUSION The low tube voltage with low-contrast-medium protocol significantly reduces organ doses at the same volume CT dose index setting compared with conventional 120-kVp protocol with standard contrast medium on contrast-enhanced CT.
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Affiliation(s)
| | | | - Seitaro Oda
- Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
| | - Masafumi Kidoh
- Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
| | | | - Hiroyuki Uetani
- Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
| | - M Azuma
- Faculty of Medicine, University of Miyazaki, Miyazaki, Japan
| | - Daisuke Sakabe
- Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
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Montoya JC, Zhang C, Li Y, Li K, Chen GH. Reconstruction of three-dimensional tomographic patient models for radiation dose modulation in CT from two scout views using deep learning. Med Phys 2022; 49:901-916. [PMID: 34908175 PMCID: PMC9080958 DOI: 10.1002/mp.15414] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 11/11/2021] [Accepted: 11/16/2021] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND A tomographic patient model is essential for radiation dose modulation in x-ray computed tomography (CT). Currently, two-view scout images (also known as topograms) are used to estimate patient models with relatively uniform attenuation coefficients. These patient models do not account for the detailed anatomical variations of human subjects, and thus, may limit the accuracy of intraview or organ-specific dose modulations in emerging CT technologies. PURPOSE The purpose of this work was to show that 3D tomographic patient models can be generated from two-view scout images using deep learning strategies, and the reconstructed 3D patient models indeed enable accurate prescriptions of fluence-field modulated or organ-specific dose delivery in the subsequent CT scans. METHODS CT images and the corresponding two-view scout images were retrospectively collected from 4214 individual CT exams. The collected data were curated for the training of a deep neural network architecture termed ScoutCT-NET to generate 3D tomographic attenuation models from two-view scout images. The trained network was validated using a cohort of 55 136 images from 212 individual patients. To evaluate the accuracy of the reconstructed 3D patient models, radiation delivery plans were generated using ScoutCT-NET 3D patient models and compared with plans prescribed based on true CT images (gold standard) for both fluence-field-modulated CT and organ-specific CT. Radiation dose distributions were estimated using Monte Carlo simulations and were quantitatively evaluated using the Gamma analysis method. Modulated dose profiles were compared against state-of-the-art tube current modulation schemes. Impacts of ScoutCT-NET patient model-based dose modulation schemes on universal-purpose CT acquisitions and organ-specific acquisitions were also compared in terms of overall image appearance, noise magnitude, and noise uniformity. RESULTS The results demonstrate that (1) The end-to-end trained ScoutCT-NET can be used to generate 3D patient attenuation models and demonstrate empirical generalizability. (2) The 3D patient models can be used to accurately estimate the spatial distribution of radiation dose delivered by standard helical CTs prior to the actual CT acquisition; compared to the gold-standard dose distribution, 95.0% of the voxels in the ScoutCT-NET based dose maps have acceptable gamma values for 5 mm distance-to-agreement and 10% dose difference. (3) The 3D patient models also enabled accurate prescription of fluence-field modulated CT to generate a more uniform noise distribution across the patient body compared to tube current-modulated CT. (4) ScoutCT-NET 3D patient models enabled accurate prescription of organ-specific CT to boost image quality for a given body region-of-interest under a given radiation dose constraint. CONCLUSION 3D tomographic attenuation models generated by ScoutCT-NET from two-view scout images can be used to prescribe fluence-field-modulated or organ-specific CT scans with high accuracy for the overall objective of radiation dose reduction or image quality improvement for a given imaging task.
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Affiliation(s)
- Juan C Montoya
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Chengzhu Zhang
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Yinsheng Li
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Ke Li
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Guang-Hong Chen
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
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Jeon PH, Lee CL. Improving image quality by optimizing beam width and helical pitch in CT. JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY 2022; 30:399-408. [PMID: 35095014 DOI: 10.3233/xst-211103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
BACKGROUND Expanding computed tomography (CT) detector coverage broadens the beam width, but inaccurate tube current application can reduce image quality at the boundaries between body regions with different attenuation values along the z-axis. OBJECTIVE This study aims to develop and validate a new CT scanning technique with a fixed pitch to achieve higher imaging quality. METHODS A cylindrical water phantom and an anthropomorphic chest phantom with different diameters represent a human body with different attenuation values. By optimizing the beam width and helical pitch, the pitch is fixed during scanning. The mean noise of the images and the standard deviation were calculated, and the coefficient of variation (COV) was compared to evaluate the uniformity of image noise according to the beam width. RESULTS At the boundaries between regions with different attenuation values, the 10 mm beam width (COV: 0.065) in the water phantom showed a 47.7% COV reduction of image noise compared with the 20 mm beam width (COV: 0.125). In addition, the 20 mm beam width (COV: 0.146) in the chest phantom showed a 29.3% COV reduction of image noise compared with the 40 mm beam width (COV: 0.206). Thus, as the beam was narrowed, the mean noise was similar, but the standard deviation was reduced. CONCLUSIONS The proposed CT scanning technique with a fixed pitch, optimized beam width, and helical pitch demonstrates that image quality can be improved without increasing radiation dose at the boundary between regions with different attenuation values.
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Affiliation(s)
- Pil-Hyun Jeon
- Department of Diagnostic Radiology, Yonsei University Wonju College of Medicine, Wonju Severance Christian Hospital, Wonju-si, Gangwon-do, Republic of Korea
| | - Chang-Lae Lee
- Health & Medical Equipment Business Unit, Samsung Electronics, Suwon-si, Gyeonggi-do, Republic of Korea
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15
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Comparison of 100-Kilovoltage Tin Filtration With Advanced Modeled Iterative Reconstruction Protocol to an Automated Kilovoltage Selection With Filtered Back Projection Protocol on Radiation Dose and Image Quality in Pediatric Noncontrast-Enhanced Chest Computed Tomography. J Comput Assist Tomogr 2021; 46:64-70. [DOI: 10.1097/rct.0000000000001248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Kim J, Kim HK. A NOVEL METHOD FOR ESTIMATING PATIENT-SPECIFIC PRIMARY DOSE IN CONE-BEAM COMPUTED TOMOGRAPHY. RADIATION PROTECTION DOSIMETRY 2021; 196:71-84. [PMID: 34487179 DOI: 10.1093/rpd/ncab128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 07/12/2021] [Accepted: 08/04/2021] [Indexed: 06/13/2023]
Abstract
For the purpose of real-time scan-protocol optimisation and patient-specific dose management in cone-beam computed tomography, we introduce a numerical algorithm that estimates the primary dose distributions in reconstructed images. The proposed algorithm is based on the ray-tracing technique and utilises reconstructed voxel data and scanning protocol. The algorithm is validated with the Monte Carlo (MC) and conventional model-based dose reconstruction methods for the simple cylindrical water and anthropomorphic head phantoms. The algorithm shows good agreement with both methods in terms of the zeroth-order x-ray interactions, which exclude the higher-order x-ray interactions at sites distant from the first interactions, and it consumes a significantly lower computational cost compared with the MC method. The differences between the proposed algorithm and the model-based dose reconstruction method as well as the improvement strategies of the algorithm are discussed in detail.
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Affiliation(s)
- Jinwoo Kim
- Center for Advanced Medical Engineering Research, Pusan National University, Busan 46241, Republic of Korea
| | - Ho Kyung Kim
- Center for Advanced Medical Engineering Research, Pusan National University, Busan 46241, Republic of Korea
- School of Mechanical Engineering, Pusan National University, Busan 46241, Republic of Korea
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17
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Jadick G, Abadi E, Harrawood B, Sharma S, Segars WP, Samei E. A scanner-specific framework for simulating CT images with tube current modulation. Phys Med Biol 2021; 66:10.1088/1361-6560/ac2269. [PMID: 34464942 PMCID: PMC8552241 DOI: 10.1088/1361-6560/ac2269] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 08/31/2021] [Indexed: 11/12/2022]
Abstract
Although tube current modulation (TCM) is routinely implemented in modern computed tomography (CT) scans, no existing CT simulator is capable of generating realistic images with TCM. The goal of this study was to develop such a framework to (1) facilitate patient-specific optimization of TCM parameters and (2) enable future virtual imaging trials (VITs) with more clinically realistic image quality and x-ray flux distributions. The framework was created by developing a TCM module and integrating it with an existing CT simulator (DukeSim). The developed module utilizes scanner-calibrated TCM parameters and two localizer radiographs to compute the mAs for each simulated CT projection. This simulation pipeline was validated in two parts. First, DukeSim was validated in the context of a commercial scanner with TCM (SOMATOM Force, Siemens Healthineers) by imaging a physical CT phantom (Mercury, Sun Nuclear) and its computational analogue. Second, the TCM module was validated by imaging a computational anthropomorphic phantom (ATOM, CIRS) using DukeSim with real and module-generated TCM profiles. The validation demonstrated DukeSim's realism in terms of noise magnitude, noise texture, spatial resolution, and image contrast (with average differences of 0.38%, 6.31%, 0.43%, and -9 HU, respectively). It also demonstrated the TCM module's realism in terms of projection-level mAs and resulting noise magnitude (2.86% and -2.60%, respectively). Finally, the framework was applied to a pilot VIT simulating images of three computational anthropomorphic phantoms (XCAT, with body mass indices (BMIs) of 24.3, 28.2, and 33.0) under five different TCM settings. The optimal TCM for each phantom was characterized based on various criteria, such as minimizing mAs or maximizing image quality. 'Very Weak' TCM minimized noise for the 24.3 BMI phantom, while 'Very Strong' TCM minimized noise for the 33.0 BMI phantom. This illustrates the utility of the developed framework for future optimization studies of TCM parameters and, more broadly, large-scale VITs with scanner-specific TCM.
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Affiliation(s)
- Giavanna Jadick
- Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, NC, United States of America
| | - Ehsan Abadi
- Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, NC, United States of America
- Medical Physics Graduate Program, Duke University School of Medicine, NC, United States of America
- Department of Electrical and Computer Engineering, Duke University, NC, United States of America
| | - Brian Harrawood
- Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, NC, United States of America
| | - Shobhit Sharma
- Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, NC, United States of America
- Department of Physics, Duke University, NC, United States of America
| | - W Paul Segars
- Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, NC, United States of America
- Medical Physics Graduate Program, Duke University School of Medicine, NC, United States of America
- Department of Biomedical Engineering, Duke University, NC, United States of America
| | - Ehsan Samei
- Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, NC, United States of America
- Medical Physics Graduate Program, Duke University School of Medicine, NC, United States of America
- Department of Electrical and Computer Engineering, Duke University, NC, United States of America
- Department of Physics, Duke University, NC, United States of America
- Department of Biomedical Engineering, Duke University, NC, United States of America
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Gould SM, Mackewn J, Chicklore S, Cook GJR, Mallia A, Pike L. Optimisation of CT protocols in PET-CT across different scanner models using different automatic exposure control methods and iterative reconstruction algorithms. EJNMMI Phys 2021; 8:58. [PMID: 34331602 PMCID: PMC8325723 DOI: 10.1186/s40658-021-00404-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 07/13/2021] [Indexed: 11/20/2022] Open
Abstract
Background A significant proportion of the radiation dose from a PET-CT examination is dependent on the CT protocol, which should be optimised for clinical purposes. Matching protocols on different scanners within an imaging centre is important for the consistency of image quality and dose. This paper describes our experience translating low-dose CT protocols between scanner models utilising different automatic exposure control (AEC) methods and reconstruction algorithms. Methods The scanners investigated were a newly installed Siemens Biograph mCT PET with 64-slice SOMATOM Definition AS CT using sinogram affirmed iterative reconstruction (SAFIRE) and two GE Discovery 710 PET scanners with 128-slice Optima 660 CT using adaptive statistical reconstruction (ASiR). Following exploratory phantom work, 33 adult patients of various sizes were scanned using the Siemens scanner and matched to patients scanned using our established GE protocol to give 33 patient pairs. A comparison of volumetric CT dose index (CTDIvol) and image noise within these patient pairs informed optimisation, specifically for obese patients. Another matched patient study containing 27 patient pairs was used to confirm protocol matching. Size-specific dose estimates (SSDEs) were calculated for patients in the second cohort. With the acquisition protocol for the Siemens scanner determined, clinicians visually graded the images to identify optimal reconstruction parameters. Results In the first matched patient study, the mean percentage difference in CTDIvol for Siemens compared to GE was − 10.7% (range − 41.7 to 50.1%), and the mean percentage difference in noise measured in the patients’ liver was 7.6% (range − 31.0 to 76.8%). In the second matched patient study, the mean percentage difference in CTDIvol for Siemens compared to GE was − 20.5% (range − 43.1 to 1.9%), and the mean percentage difference in noise was 19.8% (range − 27.0 to 146.8%). For these patients, the mean SSDEs for patients scanned on the Siemens and GE scanners were 3.27 (range 2.83 to 4.22) mGy and 4.09 (range 2.81 to 4.82) mGy, respectively. The analysis of the visual grading study indicated no preference for any of the SAFIRE strengths. Conclusions Given the different implementations of acquisition parameters and reconstruction algorithms between vendors, careful consideration is required to ensure optimisation and standardisation of protocols.
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Affiliation(s)
- Sarah-May Gould
- King's College London & Guy's and St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, UK.
| | - Jane Mackewn
- King's College London & Guy's and St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, UK
| | - Sugama Chicklore
- King's College London & Guy's and St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, UK
| | - Gary J R Cook
- King's College London & Guy's and St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, UK
| | - Andrew Mallia
- King's College London & Guy's and St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, UK
| | - Lucy Pike
- King's College London & Guy's and St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, UK
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Thierry-Chef I, Ferro G, Le Cornet L, Dabin J, Istad TS, Jahnen A, Lee C, Maccia C, Malchair F, Olerud HM, Harbron RW, Figuerola J, Hermen J, Moissonnier M, Bernier MO, Bosch de Basea MB, Byrnes G, Cardis E, Hauptmann M, Journy N, Kesminiene A, Meulepas JM, Pokora R, Simon SL. Dose Estimation for the European Epidemiological Study on Pediatric Computed Tomography (EPI-CT). Radiat Res 2021; 196:74-99. [PMID: 33914893 DOI: 10.1667/rade-20-00231.1] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Accepted: 03/26/2021] [Indexed: 11/03/2022]
Abstract
Within the European Epidemiological Study to Quantify Risks for Paediatric Computerized Tomography (EPI-CT study), a cohort was assembled comprising nearly one million children, adolescents and young adults who received over 1.4 million computed tomography (CT) examinations before 22 years of age in nine European countries from the late 1970s to 2014. Here we describe the methods used for, and the results of, organ dose estimations from CT scanning for the EPI-CT cohort members. Data on CT machine settings were obtained from national surveys, questionnaire data, and the Digital Imaging and Communications in Medicine (DICOM) headers of 437,249 individual CT scans. Exposure characteristics were reconstructed for patients within specific age groups who received scans of the same body region, based on categories of machines with common technology used over the time period in each of the 276 participating hospitals. A carefully designed method for assessing uncertainty combined with the National Cancer Institute Dosimetry System for CT (NCICT, a CT organ dose calculator), was employed to estimate absorbed dose to individual organs for each CT scan received. The two-dimensional Monte Carlo sampling method, which maintains a separation of shared and unshared error, allowed us to characterize uncertainty both on individual doses as well as for the entire cohort dose distribution. Provided here are summaries of estimated doses from CT imaging per scan and per examination, as well as the overall distribution of estimated doses in the cohort. Doses are provided for five selected tissues (active bone marrow, brain, eye lens, thyroid and female breasts), by body region (i.e., head, chest, abdomen/pelvis), patient age, and time period (1977-1990, 1991-2000, 2001-2014). Relatively high doses were received by the brain from head CTs in the early 1990s, with individual mean doses (mean of 200 simulated values) of up to 66 mGy per scan. Optimization strategies implemented since the late 1990s have resulted in an overall decrease in doses over time, especially at young ages. In chest CTs, active bone marrow doses dropped from over 15 mGy prior to 1991 to approximately 5 mGy per scan after 2001. Our findings illustrate patterns of age-specific doses and their temporal changes, and provide suitable dose estimates for radiation-induced risk estimation in epidemiological studies.
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Affiliation(s)
- Isabelle Thierry-Chef
- International Agency for Research on Cancer, Lyon, France
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Ciber Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Gilles Ferro
- International Agency for Research on Cancer, Lyon, France
| | - Lucian Le Cornet
- Institute of Medical Biostatistics, Epidemiology and Informatics, University Medical Center Mainz, Mainz, Germany
- German Cancer Research Center, Heidelberg, Germany
| | - Jérémie Dabin
- Belgian Nuclear Research Centre, SCK CEN, Mol, Belgium
| | - Tore S Istad
- Norwegian Radiation and Nuclear Safety Authority, NO-0213 Oslo, Norway
| | - Andreas Jahnen
- Luxembourg Institute of Science and Technology, Esch-sur-Alzette, Luxembourg
| | - Choonsik Lee
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland
| | | | | | - Hilde M Olerud
- University of South-Eastern Norway, Faculty of Health and Social Sciences, Kongsberg, Norway
| | - Richard W Harbron
- Institute of Health and Society, Newcastle University (UNEW), Newcastle upon Tyne, United Kingdom
- NIHR Health Protection Research Unit in Chemical and Radiation Threats and Hazards, Newcastle University, United Kingdom
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Ciber Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Jordi Figuerola
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Ciber Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Johannes Hermen
- Luxembourg Institute of Science and Technology, Esch-sur-Alzette, Luxembourg
| | | | - Marie-Odile Bernier
- Institut de Radioprotection et de Sûreté Nucléaire, Laboratoire d'épidémiologie des Rayonnements Ionisants, Fontenay-aux-Roses, France
| | - Magda Bosch Bosch de Basea
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Ciber Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Graham Byrnes
- International Agency for Research on Cancer, Lyon, France
| | - Elisabeth Cardis
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Ciber Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Michael Hauptmann
- Department of Epidemiology and Biostatistics, Netherlands Cancer Institute, Amsterdam, the Netherlands
- Institute of BiostatisTics and Registry Research, Medical University Brandenburg Theodor Fontane, Neuruppin, Germany
| | - Neige Journy
- Institut de Radioprotection et de Sûreté Nucléaire, Laboratoire d'épidémiologie des Rayonnements Ionisants, Fontenay-aux-Roses, France
- French National Institute of Health and Medical Research (Inserm) Unit 1018, Centre for Research in Epidemiology and Population Health (CESP), Cancer and Radiations Group, Gustave Roussy, Villejuif, France
| | | | - Johanna M Meulepas
- Department of Epidemiology and Biostatistics, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Roman Pokora
- Institute of Medical Biostatistics, Epidemiology and Informatics, University Medical Center Mainz, Mainz, Germany
| | - Steven L Simon
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland
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20
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Huck SM, Fung GSK, Parodi K, Stierstorfer K. On the potential of ROI imaging in x-ray CT - A comparison of novel dynamic beam attenuators with current technology. Med Phys 2021; 48:3479-3499. [PMID: 33838055 DOI: 10.1002/mp.14879] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 03/24/2021] [Accepted: 03/29/2021] [Indexed: 12/30/2022] Open
Abstract
PURPOSE In this work, we explore the potential of region-of-interest (ROI) imaging in x-ray computed tomography (CT). Using two dynamic beam attenuator (DBA) concepts for fluence field modulation (FFM) previously developed, we investigate and evaluate the potential dose savings in comparison with current FFM technology. METHODS ROI imaging is a special application of FFM where the bulk of x-ray radiation is propagated toward a certain anatomical target (ROI), specified by the imaging task, while the surrounding tissue is spared from radiation. We introduce a criterion suitable to quantitatively describe the balance between image quality inside an ROI and total radiation dose with respect to a given ROI imaging task. It accounts for the mean image variance at the ROI and the effective patient dose calculated from Monte Carlo simulations. The criterion is further used to compile task-specific DBA trajectories determining the primary x-ray fluence, and eventually used for comparing different FFM techniques, namely the sheet-based dynamic beam attenuator (sbDBA), the z-aligned sbDBA (z-sbDBA), and an adjustable static operation mode of the z-sbDBA. Furthermore, two static bowtie filters and the influence of tube current modulation (TCM) are included in the comparison. RESULTS Our findings demonstrate by simulations that the presented trajectory optimization method determines reasonable DBA trajectories. The influence of TCM is strongly depending on the imaging task. The narrow bowtie filter allows for dose reductions of about 10% compared to the regular bowtie filter in the considered ROI imaging tasks. The DBAs are shown to realize substantially larger dose reductions. In our cardiac imaging scenario, the DBAs can reduce the effective dose by about 30% (z-sbDBA) or 60% (sbDBA). We can further verify that the noise characteristics are not adversely affected by the DBAs. CONCLUSION Our research demonstrates that ROI imaging using the presented DBA concepts is a promising technique toward a more patient- and task-specific CT imaging requiring lower radiation dose. Both the sbDBA and the z-sbDBA are potential technical solutions for realizing ROI imaging in x-ray CT.
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Affiliation(s)
- Sascha Manuel Huck
- Siemens Healthcare GmbH, Forchheim, Germany.,Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Garching, Germany
| | | | - Katia Parodi
- Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Garching, Germany
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21
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Yang Y, Zhuo W, Chen B, Lu S, Zhou P, Ren W, Liu H. A new phantom developed to test the ATCM performance of chest CT scanners. JOURNAL OF RADIOLOGICAL PROTECTION : OFFICIAL JOURNAL OF THE SOCIETY FOR RADIOLOGICAL PROTECTION 2021; 41:349-359. [PMID: 33862608 DOI: 10.1088/1361-6498/abf900] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 04/16/2021] [Indexed: 06/12/2023]
Abstract
In this study, a new ATCM phantom was developed to test the performance of the automatic tube current modulation (ATCM) of computed tomography (CT) scanners.. Based on the Chinese reference man and Monte Carlo simulations of x-ray attenuation, a more realistic ATCM phantom made of polymethyl methacrylate was developed. The phantom has a length of 20 cm, and it can be used to measure the dose profile along the central axis using 19 real-time MOSFET detectors. The image noise can be calculated slice by slice in the phantom's center. Test experiments showed that the phantom could initiate tube current modulation under different modulation levels of CT scans, and the actual effects of ATCM could be evaluated with the aid of the dose profile measurements. Using the measured dose profiles and image noise, the preferred dose can easily be identified from a choice of different modulation levels. The new phantom developed in this study can be used to test the ATCM performance of CT scanners, and is useful for further studies of the optimization of CT scan protocols with ATCM.
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Affiliation(s)
- Yang Yang
- Institute of Radiation Medicine, Fudan University, Shanghai 200032,People's Republic of China
| | - Weihai Zhuo
- Institute of Radiation Medicine, Fudan University, Shanghai 200032,People's Republic of China
| | - Bo Chen
- Institute of Radiation Medicine, Fudan University, Shanghai 200032,People's Republic of China
| | - Shunqi Lu
- Institute of Radiation Medicine, Fudan University, Shanghai 200032,People's Republic of China
| | - Pei Zhou
- Shanghai United Imaging Healthcare, Shanghai 201807, People's Republic of China
| | - Wenliang Ren
- Shanghai United Imaging Healthcare, Shanghai 201807, People's Republic of China
| | - Haikuan Liu
- Institute of Radiation Medicine, Fudan University, Shanghai 200032,People's Republic of China
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Kim J, Jeon H, Kyung Kim H. MONTE CARLO DOSE ASSESSMENT IN DENTAL CONE-BEAM COMPUTED TOMOGRAPHY. RADIATION PROTECTION DOSIMETRY 2021; 193:190-199. [PMID: 33855365 DOI: 10.1093/rpd/ncab039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2020] [Revised: 02/09/2021] [Accepted: 02/25/2021] [Indexed: 06/12/2023]
Abstract
Most dental cone-beam computed tomography (CBCT) uses an x-ray beam field covering the maxillomandibular region and the width-truncated detector geometry. The spatial dose distribution in dental CBCT is analyzed in terms of local primary and remote secondary doses by using a list-mode analysis of x-ray interactions obtained from the Monte Carlo simulations. The patient-dose benefit due to the width-truncated detector geometry is also investigated for a wide range of detector offsets. The developed dose estimation agrees with the measurement in a relative error of 7.7%. The secondary dose outside of the irradiation field becomes larger with increasing tube voltage. The dose benefit with the width-truncated geometry linearly increases as the detector-offset width is decreased. Leaving the CT image quality out of the account, the MC results reveal that the operation of dental CBCT with a lower tube voltage and a smaller detector-offset width is beneficial to the patient dose.
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Affiliation(s)
- Jinwoo Kim
- School of Mechanical Engineering, Pusan National University, Busan 46241, Republic of Korea
| | - Hosang Jeon
- Department of Radiation Oncology, Pusan National University Yangsan Hospital, Yangsan-Si, Gyeongsangnam-do 50612, Republic of Korea
| | - Ho Kyung Kim
- School of Mechanical Engineering, Pusan National University, Busan 46241, Republic of Korea
- Center for Advanced Medical Engineering, Pusan National University, Busan 46241, Republic of Korea
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Stankovic U, Ploeger LS, Sonke JJ. Improving linac integrated cone beam computed tomography image quality using tube current modulation. Med Phys 2021; 48:1739-1749. [PMID: 33525051 DOI: 10.1002/mp.14746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 01/18/2021] [Accepted: 01/20/2021] [Indexed: 11/08/2022] Open
Abstract
PURPOSE Linac integrated cone beam CT (CBCT) scanners have become widespread tool for image guidance in radiotherapy. The current implementation uses constant imaging fluence across all the projection angles, which leads to anisotropic noise properties and suboptimal image quality for noncircular symmetric objects. Tube current modulation (TCM) is widely used in conventional CT. The purpose of this work was to implement TCM on a linac integrated CBCT scanner and evaluate its impact on image quality under varying scatter conditions and scatter correction strategies. METHODS We have implemented TCM on a nonclinical Elekta Versa HD linear accelerator with enhanced x-ray generator functionality including pulse width modulation. The pulse width was modulated using two Arduino programmable microcontrollers: one placed on the kV arm to measure the projection angle and the other connected to the kV generator control board to vary x-ray pulse width as function of gantry angle and precalculated transmission. An in-house developed phantom with a ratio of the left-right to anterior-posterior path length of 1.85:1 was scanned. Image quality was determined using the anisotropicity of the 2D noise power spectra (NPS) in the transverse plane and the contrast-to-noise ratio (CNR). In addition, to determine the impact of scatter on the applicability of the TCM method we have modified the generated scatter using three different collimators in the cranio-caudal direction as well as with and without an antiscatter grid (ASG). RESULTS Application of the TCM led to 30-78% reduction of the angular anisotropicity of the NPS in the transverse plane. The amount of reduction depended on the scatter conditions, with lower values corresponding to higher scatter conditions. The same was true for the CNR: when scatter contribution was low (presence of an ASG or very aggressive collimation) the CNR was improved by about 30%, while in high scatter conditions the CNR was improved by about 12%. CONCLUSIONS TCM has the potential to improve CBCT image quality, but this depends on the amount of detected x-ray scatter.
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Affiliation(s)
- Uros Stankovic
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, 1066CX, The Netherlands
| | - Lennert S Ploeger
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, 1066CX, The Netherlands
| | - Jan-Jakob Sonke
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, 1066CX, The Netherlands
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24
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Wang T, Lei Y, Fu Y, Wynne JF, Curran WJ, Liu T, Yang X. A review on medical imaging synthesis using deep learning and its clinical applications. J Appl Clin Med Phys 2021; 22:11-36. [PMID: 33305538 PMCID: PMC7856512 DOI: 10.1002/acm2.13121] [Citation(s) in RCA: 126] [Impact Index Per Article: 31.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 11/12/2020] [Accepted: 11/21/2020] [Indexed: 02/06/2023] Open
Abstract
This paper reviewed the deep learning-based studies for medical imaging synthesis and its clinical application. Specifically, we summarized the recent developments of deep learning-based methods in inter- and intra-modality image synthesis by listing and highlighting the proposed methods, study designs, and reported performances with related clinical applications on representative studies. The challenges among the reviewed studies were then summarized with discussion.
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Affiliation(s)
- Tonghe Wang
- Department of Radiation OncologyEmory UniversityAtlantaGAUSA
- Winship Cancer InstituteEmory UniversityAtlantaGAUSA
| | - Yang Lei
- Department of Radiation OncologyEmory UniversityAtlantaGAUSA
| | - Yabo Fu
- Department of Radiation OncologyEmory UniversityAtlantaGAUSA
| | - Jacob F. Wynne
- Department of Radiation OncologyEmory UniversityAtlantaGAUSA
| | - Walter J. Curran
- Department of Radiation OncologyEmory UniversityAtlantaGAUSA
- Winship Cancer InstituteEmory UniversityAtlantaGAUSA
| | - Tian Liu
- Department of Radiation OncologyEmory UniversityAtlantaGAUSA
- Winship Cancer InstituteEmory UniversityAtlantaGAUSA
| | - Xiaofeng Yang
- Department of Radiation OncologyEmory UniversityAtlantaGAUSA
- Winship Cancer InstituteEmory UniversityAtlantaGAUSA
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Sakabe D, Nakaura T, Oda S, Kidoh M, Utsunomiya D, Masahiro Hatemura RT, Funama Y. Decreasing the radiation dose for contrast-enhanced abdominal spectral CT with a half contrast dose: a matched-pair comparison with a 120 kVp protocol. BJR Open 2020; 2:20200006. [PMID: 33367197 PMCID: PMC7749088 DOI: 10.1259/bjro.20200006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 09/18/2020] [Indexed: 12/15/2022] Open
Abstract
Objectives To compare the estimated radiation dose of 50% reduced iodine contrast medium (halfCM) for virtual monochromatic images (VMIs) with that of standard CM (stdCM) with a 120 kVp imaging protocol for contrast-enhanced CT (CECT). Methods We enrolled 30 adults with renal dysfunction who underwent abdominal CT with halfCM for spectral CT. As controls, 30 matched patients without renal dysfunction using stdCM were also enrolled. CT images were reconstructed with the VMIs at 55 keV with halfCM and 120 kVp images with stdCM and halfCM. The Monte-Carlo simulation tool was used to simulate the radiation dose. The organ doses were normalized to CTDIvol for the liver, pancreas, spleen, and kidneys and measured between halfCM and stdCM protocols. Results For the arterial phase, the mean organ doses normalized to CTDIvol for stdCM and halfCM were 1.22 and 1.29 for the liver, 1.50 and 1.35 for the spleen, 1.75 and 1.51 for the pancreas, and 1.89 and 1.53 for the kidneys. As compared with non-enhanced CT, the average increase in the organ dose was significantly lower for halfCM (13.8% ± 14.3 and 26.7% ± 16.7) than for stdCM (31.0% ± 14.3 and 38.5% ± 14.8) during the hepatic arterial and portal venous phases (p < 0.01). Conclusion As compared with stdCM with the 120 kVp imaging protocol, a 50% reduction in CM with VMIs with the 55 keV protocol allowed for a substantial reduction of the average organ dose of iodine CM while maintaining the iodine CT number for CECT. Advances in knowledge This study provides that the halfCM protocol for abdominal CT with a dual-layer-dual-energy CT can significantly reduce the increase in the average organ dose for non-enhanced CT as compared with the standard CM protocol.
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Affiliation(s)
| | - Takeshi Nakaura
- Department of Diagnostic Radiology, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
| | - Seitaro Oda
- Department of Diagnostic Radiology, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
| | - Masafumi Kidoh
- Department of Diagnostic Radiology, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
| | - Daisuke Utsunomiya
- Diagnostic Radiology, Yokohama City University Graduate School of Medicine, Yokohama, Japan
| | | | - Yoshinori Funama
- Department of Medical Physics, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
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Performance evaluation of near-real time angular tube current modulation in X-ray computed tomography using real-time dosimeter: a phantom study. HEALTH AND TECHNOLOGY 2020. [DOI: 10.1007/s12553-020-00473-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Huck SM, Fung GSK, Parodi K, Stierstorfer K. The z-sbDBA, a new concept for a dynamic sheet-based fluence field modulator in x-ray CT. Med Phys 2020; 47:4827-4837. [PMID: 32754971 DOI: 10.1002/mp.14430] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 07/20/2020] [Accepted: 07/24/2020] [Indexed: 01/28/2023] Open
Abstract
PURPOSE We present a new concept for dynamic fluence field modulation (FFM) in x-ray computed tomography (CT). The so-called z-aligned sheet-based dynamic beam attenuator (z-sbDBA) is developed to dynamically compensate variations in patient attenuation across the fan beam and the projection angle. The goal is to enhance image quality and to reduce patient radiation dose. METHODS The z-sbDBA consists of an array of attenuation sheets aligned along the z direction. In neutral position, the array is focused toward the focal spot. Tilting the z-sbDBA defocuses the sheets, thus reducing the transmission for larger fan beam angles. The structure of the z-sbDBA significantly differs from the previous sheet-based dynamic beam attenuator (sbDBA) in two features: (a) The sheets of the z-sbDBA are aligned parallel to the detector rows, and (b) the height of the sheets increases from the center toward larger fan beam angles. We built a motor actuated prototype of the z-sbDBA integrated into a clinical CT scanner. In experiments, we investigated its feasibility for FFM. We compared the z-sbDBA to common CT bowtie filters in terms of the spectral dependency of the transmission and possible image variance distribution in reconstructed phantom images. Additionally, the potential radiation dose saving using z-sbDBA for region-of-interest (ROI) imaging was studied. RESULTS Our experimental results confirm that the z-sbDBA can realize variable transmission profiles of the radiation fluence by only small tilts. Compared to the sbDBA, the z-sbDBA can mitigate some practical and mechanical issues. In comparison to bowtie filters, the spectral dependency is considerably reduced when using the z-sbDBA. Likewise, more homogeneous image variance distributions can be attained in reconstructed phantom images. The z-sbDBA allows controlling the spatial image variance distribution which makes it suitable for ROI imaging. Our comparison on ROI imaging reveals skin dose reductions of up to 35% at equal ROI image quality by using the z-sbDBA. CONCLUSION Our new concept for FFM in x-ray CT, the z-sbDBA, was experimentally validated on a clinical CT scanner. It facilitates dynamic FFM by realizing variable transmission profiles across the fan beam angle on a projection-wise basis. This key feature allows for substantial improvements in image quality, a reduction in patient radiation dose, and additionally provides a technical solution for ROI imaging.
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Affiliation(s)
- Sascha Manuel Huck
- Siemens Healthcare GmbH, Siemensstr. 3, Forchheim, 91301, Germany.,Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Am Coulombwall 1, Garching, 85748, Germany
| | - George S K Fung
- Siemens Medical Solutions USA, Inc., 40 Liberty Bouldevard, Malvern, PA, 19355, USA.,Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, 601 N Caroline St, JHOC 4253, Baltimore, MD, 21287, USA
| | - Katia Parodi
- Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Am Coulombwall 1, Garching, 85748, Germany
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Gharbi S, Labidi S, Mars M. AUTOMATIC BRAIN DOSE ESTIMATION IN COMPUTED TOMOGRAPHY USING PATIENT DICOM IMAGES. RADIATION PROTECTION DOSIMETRY 2020; 188:536-542. [PMID: 32043150 DOI: 10.1093/rpd/ncaa006] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Revised: 12/03/2019] [Accepted: 01/13/2020] [Indexed: 06/10/2023]
Abstract
This study aims to develop an Automatic Brain Dose Estimation (ABDE) methodology for head computed tomography examinations. The ABDE is to be applied first to an anthropomorphic Alderson phantom to obtain a Correction factor (Cf) between the ABDE and the direct absorbed brain dose using dosemeters positioned within the anthropomorphic phantom. Then, in order to estimate the correct brain dose for patient, the Cf was multiplied by the mean ABDE values for each patient. Results were compared to those registered with a mathematical simulation phantom using CT-Expo V 2.4 software. Results showed no significant difference between the correct ABDE values and the CT-Expo values with a mean percent difference of 2.54 ± 0.01%. In conclusion, ABDE yields a correct estimation of brain dose, taking into account the size and attenuation of the irradiated region. Thus, it is clinically recommended for accurate patient brain dose assessment.
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Affiliation(s)
- Souha Gharbi
- Université Tunis EL Manar, Institut Supérieur des Technologies Médicales de Tunis, Laboratoire de recherche de Biophysique et de Technologies Médicales, 9, Avenue du Docteur Z. Essafi, Tunis 1006, Tunisia
| | - Salam Labidi
- Université Tunis EL Manar, Institut Supérieur des Technologies Médicales de Tunis, Laboratoire de recherche de Biophysique et de Technologies Médicales, 9, Avenue du Docteur Z. Essafi, Tunis 1006, Tunisia
| | - Mokhtar Mars
- Université Tunis EL Manar, Institut Supérieur des Technologies Médicales de Tunis, Laboratoire de recherche de Biophysique et de Technologies Médicales, 9, Avenue du Docteur Z. Essafi, Tunis 1006, Tunisia
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Impact of ultra-low dose CT acquisition on semi-automated RECIST tool in the evaluation of malignant focal liver lesions. Diagn Interv Imaging 2020; 101:473-479. [DOI: 10.1016/j.diii.2020.05.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Revised: 05/05/2020] [Accepted: 05/06/2020] [Indexed: 12/21/2022]
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Kitera N, Matsubara K, Fujioka C, Yokomachi K, Nishimaru E, Kiguchi M, Morimoto A, Ishifuro M, Awai K. [Organ-based Tube-current Modulation Applied on Different MDCT Scanners: Reduction in the Radiation Dose to the Eye Lens at Head CT]. Nihon Hoshasen Gijutsu Gakkai Zasshi 2020; 76:366-374. [PMID: 32307364 DOI: 10.6009/jjrt.2020_jsrt_76.4.366] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
PURPOSE Organ-based tube current modulation (OB-TCM) techniques, which are provided by three vendors, reduces the radiation dose to the lens of the eyes by decreasing the tube current, when the X-ray tube passes over the anterior surface of critical organs. However, the characteristics of dose modulation of these techniques are different. The purpose of this study was to understand the performance characteristics of OB-TCM technique of each computed tomography (CT) vendor at head CT. METHODS We used three CT scanners (SOMATOM Definition Flash; Siemens Healthcare, Revolution CT; GE Healthcare, and Aquilion ONE Genesis Edition; Canon Medical Systems). We measured the radiation dose to the lens surface as evaluation of radiation dose reduction and measured the image noise as index of image quality. We measured the radiation dose rate in the air for analysis of the characteristics of dose modulation in each OB-TCM. RESULTS When applying OB-TCM, the radiation doses for the lens surface were decreased by 28%, 22%, and 25% for Siemens, GE, and Canon CT scanners, respectively, and the image noise level was increased by 5.6%, 8.5%, and 15.1% for Siemens, GE, and Canon CT scanners, respectively. The characteristics of dose modulation in each OB-TCM were also confirmed by measured the radiation dose rate. CONCLUSION We confirmed that each OB-TCM has different influence on image quality and radiation doses for lens surface, due to the different characteristics of dose modulation for each CT vendor.
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Affiliation(s)
- Nobuo Kitera
- Department of Radiology, Hiroshima University Hospital.,Graduate School of Medical Science, Kanazawa University
| | - Kosuke Matsubara
- Department of Quantum Medical Technology, Faculty of Health Sciences, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University
| | | | | | | | - Masao Kiguchi
- Department of Radiology, Hiroshima University Hospital
| | | | | | - Kazuo Awai
- Department of Diagnostic Radiology, Hiroshima University Hospital
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Barreto I, Verma N, Quails N, Olguin C, Correa N, Mohammed TL. Patient size matters: Effect of tube current modulation on size-specific dose estimates (SSDE) and image quality in low-dose lung cancer screening CT. J Appl Clin Med Phys 2020; 21:87-94. [PMID: 32250062 PMCID: PMC7170290 DOI: 10.1002/acm2.12857] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Revised: 02/03/2020] [Accepted: 02/21/2020] [Indexed: 11/25/2022] Open
Abstract
Purpose We compare the effect of tube current modulation (TCM) and fixed tube current (FTC) on size‐specific dose estimates (SSDE) and image quality in lung cancer screening with low‐dose CT (LDCT) for patients of all sizes. Methods Initially, 107 lung screening examinations were performed using FTC, which satisfied the Centers for Medicare & Medicaid Services' volumetric CT dose index (CTDIvol) limit of 3.0 mGy for standard‐sized patients. Following protocol modification, 287 examinations were performed using TCM. Patient size and examination parameters were collected and water‐equivalent diameter (Dw) and SSDE were determined for each patient. Regression models were used to correlate CTDIvol and SSDE with Dw. Objective and subjective image quality were measured in 20 patients who had consecutive annual screenings with both FTC and TCM. Results CTDIvol was 2.3 mGy for all FTC scans and increased exponentially with Dw (range = 0.96–4.50 mGy, R2 = 0.73) for TCM scans. As patient Dw increased, SSDE decreased for FTC examinations (R2 = 1) and increased for TCM examinations (R2 = 0.54). Image quality measurements were superior with FTC for smaller sized patients and with TCM for larger sized patients (R2 > 0.5, P < 0.005). Radiologist graded all images acceptable for diagnostic evaluation of lung cancer screening. Conclusion Although FTC protocol offered a consistently low CTDIvol for all patients, it yielded unnecessarily high SSDE for small patients and increased image noise for large patients. Lung cancer screening with LDCT using TCM produces radiation doses that are appropriately reduced for small patients and increased for large patients with diagnostic image quality for all patients.
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Affiliation(s)
- Izabella Barreto
- Department of Radiology, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Nupur Verma
- Department of Radiology, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Nathan Quails
- Department of Radiology, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Catherine Olguin
- Department of Radiology, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Nathalie Correa
- Department of Radiology, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Tan-Lucien Mohammed
- Department of Radiology, College of Medicine, University of Florida, Gainesville, FL, USA
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Wang T, Lei Y, Tian Z, Dong X, Liu Y, Jiang X, Curran WJ, Liu T, Shu HK, Yang X. Deep learning-based image quality improvement for low-dose computed tomography simulation in radiation therapy. J Med Imaging (Bellingham) 2019; 6:043504. [PMID: 31673567 PMCID: PMC6811730 DOI: 10.1117/1.jmi.6.4.043504] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Accepted: 10/03/2019] [Indexed: 01/02/2023] Open
Abstract
Low-dose computed tomography (CT) is desirable for treatment planning and simulation in radiation therapy. Multiple rescanning and replanning during the treatment course with a smaller amount of dose than a single conventional full-dose CT simulation is a crucial step in adaptive radiation therapy. We developed a machine learning-based method to improve image quality of low-dose CT for radiation therapy treatment simulation. We used a residual block concept and a self-attention strategy with a cycle-consistent adversarial network framework. A fully convolution neural network with residual blocks and attention gates (AGs) was used in the generator to enable end-to-end transformation. We have collected CT images from 30 patients treated with frameless brain stereotactic radiosurgery (SRS) for this study. These full-dose images were used to generate projection data, which were then added with noise to simulate the low-mAs scanning scenario. Low-dose CT images were reconstructed from this noise-contaminated projection data and were fed into our network along with the original full-dose CT images for training. The performance of our network was evaluated by quantitatively comparing the high-quality CT images generated by our method with the original full-dose images. When mAs is reduced to 0.5% of the original CT scan, the mean square error of the CT images obtained by our method is ∼ 1.6 % , with respect to the original full-dose images. The proposed method successfully improved the noise, contract-to-noise ratio, and nonuniformity level to be close to those of full-dose CT images and outperforms a state-of-the-art iterative reconstruction method. Dosimetric studies show that the average differences of dose-volume histogram metrics are < 0.1 Gy ( p > 0.05 ). These quantitative results strongly indicate that the denoised low-dose CT images using our method maintains image accuracy and quality and are accurate enough for dose calculation in current CT simulation of brain SRS treatment. We also demonstrate the great potential for low-dose CT in the process of simulation and treatment planning.
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Affiliation(s)
- Tonghe Wang
- Emory University, Winship Cancer Institute, Department of Radiation Oncology, Atlanta, Georgia, United States
| | - Yang Lei
- Emory University, Winship Cancer Institute, Department of Radiation Oncology, Atlanta, Georgia, United States
| | - Zhen Tian
- Emory University, Winship Cancer Institute, Department of Radiation Oncology, Atlanta, Georgia, United States
| | - Xue Dong
- Emory University, Winship Cancer Institute, Department of Radiation Oncology, Atlanta, Georgia, United States
| | - Yingzi Liu
- Emory University, Winship Cancer Institute, Department of Radiation Oncology, Atlanta, Georgia, United States
| | - Xiaojun Jiang
- Emory University, Winship Cancer Institute, Department of Radiation Oncology, Atlanta, Georgia, United States
| | - Walter J. Curran
- Emory University, Winship Cancer Institute, Department of Radiation Oncology, Atlanta, Georgia, United States
| | - Tian Liu
- Emory University, Winship Cancer Institute, Department of Radiation Oncology, Atlanta, Georgia, United States
| | - Hui-Kuo Shu
- Emory University, Winship Cancer Institute, Department of Radiation Oncology, Atlanta, Georgia, United States
| | - Xiaofeng Yang
- Emory University, Winship Cancer Institute, Department of Radiation Oncology, Atlanta, Georgia, United States
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Yurt A, Özsoykal İ, Obuz F. Effects of the Use of Automatic Tube Current Modulation on Patient Dose and Image Quality in Computed Tomography. Mol Imaging Radionucl Ther 2019; 28:96-103. [PMID: 31507141 PMCID: PMC6746012 DOI: 10.4274/mirt.galenos.2019.83723] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Objectives: The frequency of abdominal computed tomography examinations is increasing, leading to a significant level of patient dose. This study aims to quantify and evaluate the effects of automatic tube current modulation (ATCM) technique on patient dose and image quality in contrast-enhanced biphasic abdominal examinations. Methods: Two different scan protocols, based on constant tube current and ATCM technique, were used on 64 patients who visited our radiology department periodically. For three patient groups with different patient size, results from two protocols were compared with respect to patient dose and image quality. Dosimetric evaluations were based on the Computed Tomography Dose Index, dose length product, and effective dose. For the comparison of image qualities between two protocols, Noise Index (NI) and Contrast to Noise Ratio (CNR) values were determined for each image. Additionally, the quality of each image was evaluated subjectively by an experienced radiologist, and the results were compared between the two protocols. Results: Dose reductions of 31% and 21% were achieved by the ATCM protocol in the arterial and portal phases, respectively. On the other hand, NI exhibited an increase between 9% and 46% for liver, fat and aorta. CNR values were observed to decrease between 5% and 19%. All images were evaluated by a radiologist, and no obstacle limiting a reliable diagnostic evaluation was found in any image obtained by either technique. Conclusion: These results showed that the ATCM technique reduces patient dose significantly while maintaining a certain level of image quality.
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Affiliation(s)
- Ayşegül Yurt
- Dokuz Eylül University Faculty of Medicine, Department of Medical Physics, İzmir, Turkey
| | - İsmail Özsoykal
- Dokuz Eylül University Faculty of Medicine, Department of Medical Physics, İzmir, Turkey
| | - Funda Obuz
- Dokuz Eylül University Faculty of Medicine, Department of Radiology, İzmir, Turkey
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Anam C, Budi WS, Adi K, Sutanto H, Haryanto F, Ali MH, Fujibuchi T, Dougherty G. Assessment of patient dose and noise level of clinical CT images: automated measurements. JOURNAL OF RADIOLOGICAL PROTECTION : OFFICIAL JOURNAL OF THE SOCIETY FOR RADIOLOGICAL PROTECTION 2019; 39:783-793. [PMID: 31117064 DOI: 10.1088/1361-6498/ab23cc] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
We investigated comparisons between patient dose and noise in pelvic, abdominal, thoracic and head CT images using an automatic method. 113 patient images (37 pelvis, 34 abdominal, 25 thoracic, and 17 head examinations) were retrospectively and automatically examined in this study. Water-equivalent diameter (Dw), size-specific dose estimates (SSDE) and noise were automatically calculated from the center slice for every patient image. The Dw was calculated based on auto-contouring of the patients' edges, and the SSDE was calculated as the product of the volume CT dose index (CTDIvol) extracted from the Digital Imaging and Communications in Medicine (DICOM) header and the size conversion factor based on the Dw obtained from AAPM 204. The noise was automatically measured as a minimum standard deviation in the map of standard deviations. A square region of interest of about 1 cm2 was used in the automated noise measurement. The SSDE values for the pelvis, abdomen, thorax, and head were 21.8 ± 7.3 mGy, 22.0 ± 4.5 mGy, 21.5 ± 4.7 mGy, and 65.1 ± 1.7 mGy, respectively. The SSDEs for the pelvis, abdomen, and thorax increased linearly with increasing Dw, and for the head with constant tube current, the SSDE decreased with increasing Dw. The noise in the pelvis, abdomen, thorax, and head were 5.9 ± 1.5 HU, 5.2 ± 1.4 HU, 4.9 ± 0.8 HU and 3.9 ± 0.2 HU, respectively. The noise levels for the pelvis, abdomen, and thorax of the patients were relatively constant with Dw because of tube current modulation. The noise in the head image was also relatively constant because Dw variations in the head are very small. The automated approach provides a convenient and objective tool for dose optimizations.
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Affiliation(s)
- Choirul Anam
- Department of Physics, Faculty of Mathematics and Natural Sciences, Diponegoro University, Jl. Prof. Soedarto SH, Tembalang, Semarang 50275, Central Java, Indonesia
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Larson DB, Boland GW. Imaging Quality Control in the Era of Artificial Intelligence. J Am Coll Radiol 2019; 16:1259-1266. [DOI: 10.1016/j.jacr.2019.05.048] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2019] [Revised: 05/27/2019] [Accepted: 05/29/2019] [Indexed: 12/13/2022]
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Shen C, Lou Y, Chen L, Zeng T, Ng MK, Zhu L, Jia X. Comparison of three undersampling approaches in computed tomography reconstruction. Quant Imaging Med Surg 2019; 9:1229-1241. [PMID: 31448209 DOI: 10.21037/qims.2019.07.07] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Background Projection data undersampling is an effective approach to reduce X-ray radiation dose in computed tomography (CT). In modern CT technologies, undersampling is also a favorable method to reduce projection data size to facilitate rapid CT scan and imaging. It is an intriguing question that given an undersampling ratio, what is the optimal undersampling approach that enables the best CT image reconstruction. While this is in general a challenging mathematical question, it is the motivation of this paper to compare three types of undersampling operations, which we hope to shed some light to this question. Methods We considered regular view undersampling that acquires X-ray projections at equiangular projection angles, regular ray undersampling that acquires projections at all angles but with X-ray lines blocked within each projection under a periodic pattern, and random ray undersampling that acquires each X-ray line with a certain probability. By representing the undersampling projection operators under the basis of singular vectors of full projection operator, we generated matrix representations of these undersampling operators and numerically perform singular value decomposition (SVD). Singular value spectra and singular vectors were compared. Results For a given undersampling ratio, the random ray undersampling approach preserves the properties of the full projection operator better than the other two approaches. This translates to advantages of reconstructing a CT image at a lower error, which has also been demonstrated in the numerical experiments. Conclusions We compared three undersampling strategies and found that random undersampling preserves the most information and outperforms the other two in terms of reconstruction quality.
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Affiliation(s)
- Chenyang Shen
- Innovative Technology of Radiotherapy Computations and Hardware (iTORCH) Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Yifei Lou
- Department of Mathematical Sciences, University of Texas Dallas, Richardson, TX, USA
| | - Liyuan Chen
- Innovative Technology of Radiotherapy Computations and Hardware (iTORCH) Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Tieyong Zeng
- Department of Mathematics, Chinese University of Hong Kong, Hong Kong, China
| | - Michael K Ng
- Department of Mathematics, Hong Kong Baptist University, Hong Kong, China
| | - Lei Zhu
- Department of Modern Physics, School of Physical Sciences, University of Science and Technology of China, Hefei 230026,China
| | - Xun Jia
- Innovative Technology of Radiotherapy Computations and Hardware (iTORCH) Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
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Expanding the Concept of Diagnostic Reference Levels to Noise and Dose Reference Levels in CT. AJR Am J Roentgenol 2019; 213:889-894. [PMID: 31180737 DOI: 10.2214/ajr.18.21030] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
OBJECTIVE. Diagnostic reference levels were developed as guidance for radiation dose in medical imaging and, by inference, diagnostic quality. The objective of this work was to expand the concept of diagnostic reference levels to explicitly include noise of CT examinations to simultaneously target both dose and quality through corresponding reference values. MATERIALS AND METHODS. The study consisted of 2851 adult CT examinations performed with scanners from two manufacturers and two clinical protocols: abdominopelvic CT with IV contrast administration and chest CT without IV contrast administration. An institutional informatics system was used to automatically extract protocol type, patient diameter, volume CT dose index, and noise magnitude from images. The data were divided into five reference patient size ranges. Noise reference level, noise reference range, dose reference level, and dose reference range were defined for each size range. RESULTS. The data exhibited strong dependence between dose and patient size, weak dependence between noise and patient size, and different trends for different manufacturers with differing strategies for tube current modulation. The results suggest size-based reference intervals and levels for noise and dose (e.g., noise reference level and noise reference range of 11.5-12.9 HU and 11.0-14.0 HU for chest CT and 10.1-12.1 HU and 9.4-13.7 HU for abdominopelvic CT examinations) that can be targeted to improve clinical performance consistency. CONCLUSION. New reference levels and ranges, which simultaneously consider image noise and radiation dose information across wide patient populations, were defined and determined for two clinical protocols. The methods of new quantitative constraints may provide unique and useful information about the goal of managing the variability of image quality and dose in clinical CT examinations.
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Chen B, Kobler E, Muckley MJ, Sodickson AD, O'Donnell T, Flohr T, Schmidt B, Sodickson DK, Otazo R. SparseCT: System concept and design of multislit collimators. Med Phys 2019; 46:2589-2599. [PMID: 30980728 DOI: 10.1002/mp.13544] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2018] [Revised: 02/28/2019] [Accepted: 04/04/2019] [Indexed: 12/11/2022] Open
Abstract
PURPOSE SparseCT, an undersampling scheme for compressed sensing (CS) computed tomography (CT), has been proposed to reduce radiation dose by acquiring undersampled projection data from clinical CT scanners (Koesters et al. in, SparseCT: Interrupted-Beam Acquisition and Sparse Reconstruction for Radiation Dose Reduction; 2017). SparseCT partially blocks the x-ray beam with a multislit collimator (MSC) to perform a multidimensional undersampling along the view and detector row dimensions. SparseCT undersamples the projection data within each view and moves the MSC along the z-direction during gantry rotation to change the undersampling pattern. It enables reconstruction of images from undersampled data using CS algorithms. The purpose of this work is to design the spacing and width of the MSC slits and the MSC motion patterns based on beam separation, undersampling efficiency, and image quality. The development and testing of a SparseCT prototype with the designed MSC will be described in a following paper. METHODS We chose a few initial MSC designs based on the guidance from two metrics: beam separation and undersampling efficiency. Both beam separation and undersampling efficiency were measured from numerically simulated photon distribution with MSC taken into consideration. Beam separation measures the separation between x-ray beams from consecutive slits, taking into account penumbra effects on both sides of each slit. Undersampling efficiency measures the dose-weighted similarity between penumbra undersampling and binary undersampling, in other words, the effective contribution of the incident dose to the signal to noise ratio of the projection data. We then compared the initially chosen MSC designs in terms of their reconstruction image quality. SparseCT projections were simulated from fully sampled patient projection data according to the MSC design and motion pattern, reconstructed iteratively using a sparsity-enforcing penalized weighted least squares cost function with ordered subsets/momentum algorithm, and compared visually and quantitatively. RESULTS Simulated photon distributions indicate that the size of the penumbra is dominated by the size of the focal spot. Therefore, a wider MSC slit and a smaller focal spot lead to increased beam separation and undersampling efficiency. For fourfold undersampling with a 1.2 mm focal spot, a minimum MSC slit width of three detector rows (projected to the detector surface) is needed for beam separation; for threefold undersampling, a minimum slit width of four detector rows is needed. Simulations of SparseCT projection and reconstruction indicate that the motion pattern of the MSC does not have a visible impact on image quality. An MSC slit width of three or four detector rows yields similar image quality. CONCLUSION The MSC is the key component of the SparseCT method. Simulations of MSC designs incorporating x-ray beam penumbra effects showed that for threefold and fourfold dose reductions, an MSC slit width of four detector rows provided reasonable beam separation, undersampling efficiency, and image quality.
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Affiliation(s)
- Baiyu Chen
- Department of Radiology, NYU School of Medicine, New York, NY, 10016, USA
| | - Erich Kobler
- Institute of Computer Graphics and Vision, Graz University of Technology, Graz, 8010, Austria
| | - Matthew J Muckley
- Department of Radiology, NYU School of Medicine, New York, NY, 10016, USA
| | - Aaron D Sodickson
- Department of Radiology, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | | | | | | | - Daniel K Sodickson
- Department of Radiology, NYU School of Medicine, New York, NY, 10016, USA
| | - Ricardo Otazo
- Department of Radiology, NYU School of Medicine, New York, NY, 10016, USA.,Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA.,Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
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Does the Tube Voltage Affect the Characterization of Coronary Plaques on 100- and 120-kVp Computed Tomography Scans. J Comput Assist Tomogr 2019; 43:416-422. [PMID: 30762654 DOI: 10.1097/rct.0000000000000845] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
OBJECTIVE The aim of this study was to compare the diagnostic performance of 100- and 120-kVp coronary computed tomography (CT) angiography (CCTA) scans for the identification of coronary plaque components. METHODS We included 116 patients with coronary plaques who underwent CCTA and integrated backscatter intravascular ultrasound studies. On 100-kVp scans, we observed 24 fibrous and 24 fatty/fibrofatty plaques; on 120-kVp scans, we noted 27 fibrous and 41 fatty/fibrofatty plaques. We compared the fibrous and the fatty/fibrofatty plaques, the CT number of the coronary lumen, and the radiation dose on scans obtained at 100 and 120 kVp. We also compared the area under the receiver operating characteristic (ROC) curve of the coronary plaques on 100- and 120-kVp scans with their ROC curves on integrated backscatter intravascular ultrasound images. RESULTS The mean CT numbers of fatty and fatty/fibrofatty plaques were 5.71 ± 36.5 and 76.6 ± 33.7 Hounsfield units (HU), respectively, on 100-kVp scans; on 120-kVp scans, they were 13.9 ± 29.4 and 54.5 ± 22.3 HU, respectively. The CT number of the coronary lumen was 323.1 ± 81.2 HU, and the radiation dose was 563.7 ± 81.2 mGy-cm on 100-kVp scans; these values were 279.3 ± 61.8 HU and 819.1 ± 115.1 mGy-cm on 120-kVp scans. The results of ROC curve analysis identified 30.5 HU as the optimal diagnostic cutoff value for 100-kVp scans (area under the curve = 0.93, 95% confidence interval = 0.87-0.99, sensitivity = 95.8%, specificity = 78.9%); for 120-kVp plaque images, the optimal cutoff was 37.4 HU (area under the curve = 0.87, 95% confidence interval = 0.79-0.96, sensitivity = 82.1%, specificity = 85.7%). CONCLUSIONS For the discrimination of coronary plaque components, the diagnostic performance of 100- and 120-kVp CCTA scans is comparable.
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Magnetic resonance angiography imaging of pulmonary embolism using agents with blood pool properties as an alternative to computed tomography to avoid radiation exposure. Eur J Radiol 2019; 113:165-173. [PMID: 30927943 DOI: 10.1016/j.ejrad.2019.02.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Revised: 01/30/2019] [Accepted: 02/07/2019] [Indexed: 11/22/2022]
Abstract
PURPOSE To evaluate the feasibility and accuracy of a combined magnetic resonance angiography (MRA) - magnetic resonance venography (MRV) protocol using contrast agents with blood pool properties, gadofosveset trisodium and gadobenate dimeglumine, in the evaluation of pulmonary embolus (PE) and deep venous thrombosis (DVT) as compared to the standard clinical reference imaging modalities; computed tomography pulmonary angiography (CTPA) and color-coded Duplex ultrasound (DUS). MATERIALS AND METHODS This prospective clinical study recruited patients presenting to the emergency department with clinical suspicion for PE and scheduled for a clinically indicated CTPA. We performed both MRA of the chest for the evaluation of PE as well as MRV of the pelvis and thighs to evaluate for DVT using a single contrast injection. MRA-MRV data was compared to the clinical reference standard CTPA and DUS, respectively. RESULTS A total of 40 patients were recruited. The results on a per-patient basis comparing MRA to CTPA for pulmonary embolus yielded 100% sensitivity and 97% specificity. There was a small subset of patients that underwent clinical DUS to evaluate for DVT, which demonstrated a sensitivity and specificity of 100% for MRV. CONCLUSIONS This single-center, preliminary study using contrast agents with blood pool properties to perform a relatively rapid combined MRA-MRV exam to image for PE and above knee DVT shows potential as an alternative imaging choice to CTPA. Further large-scale, multicentre studies are warranted.
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Nachabe R, Strauss K, Schueler B, Bydon M. Radiation dose and image quality comparison during spine surgery with two different, intraoperative 3D imaging navigation systems. J Appl Clin Med Phys 2019; 20:136-145. [PMID: 30677233 PMCID: PMC6370984 DOI: 10.1002/acm2.12534] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Revised: 12/07/2018] [Accepted: 12/22/2018] [Indexed: 12/20/2022] Open
Abstract
Careful protocol selection is required during intraoperative three-dimensional (3D) imaging for spine surgery to manage patient radiation dose and achieve clinical image quality. Radiation dose and image quality of a Medtronic O-arm commonly used during spine surgery, and a Philips hybrid operating room equipped with XperCT C-arm 3D cone-beam CT (hCBCT) are compared. The mobile O-arm (mCBCT) offers three different radiation dose settings (low, standard, and high), for four different patient sizes (small, medium, large, and extra large). The patient's radiation dose rate is constant during the entire 3D scan. In contrast, C-CBCT spine imaging uses three different field of views (27, 37, and 48 cm) using automatic exposure control (AEC) that modulates the patient's radiation dose rate during the 3D scan based on changing patient thickness. hCBCT uses additional x-ray beam filtration. Small, medium, and large trunk phantoms designed to mimic spine and soft tissue were imaged to assess radiation dose and image quality of the two systems. The estimated measured "patient" dose for the small, medium, and large phantoms imaged by the mCBCT considering all the dose settings ranged from 9.4-27.6 mGy, 8.9-33.3 mGy, and 13.8-40.6 mGy, respectively. The "patient" dose values for the same phantoms imaged with hCBCT were 2.8-4.6 mGy, 5.7-10.0 mGy, and 11.0-15.2 mGy. The CNR for the small, medium, and large phantoms was 2.9 to 3.7, 2.0 to 3.0, and 2.5 to 2.6 times higher with the hCBCT system, respectively. Hounsfield unit accuracy, noise, and uniformity of hCBCT exceeded the performance of the mCBCT; spatial resolution was comparable. Added x-ray beam filtration and AEC capability achieved clinical image quality for intraoperative spine surgery at reduced radiation dose to the patient in comparison to a reference O-arm system without these capabilities.
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Affiliation(s)
- Rami Nachabe
- Image Guided Therapy SystemsPhilips HealthcareBestThe Netherlands
| | - Keith Strauss
- Department of RadiologyCincinnati Children's HospitalCincinnatiOHUSA
| | - Beth Schueler
- Department of Neurologic RadiologyMayo ClinicRochesterMNUSA
| | - Mohamad Bydon
- Department of Neurologic SurgeryMayo ClinicRochesterMNUSA
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Wang W, Gang GJ, Siewerdsen JH, Stayman JW. Predicting image properties in penalized-likelihood reconstructions of flat-panel CBCT. Med Phys 2019; 46:65-80. [PMID: 30372536 PMCID: PMC6904934 DOI: 10.1002/mp.13249] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2018] [Revised: 09/17/2018] [Accepted: 10/09/2018] [Indexed: 12/18/2022] Open
Abstract
PURPOSE Model-based iterative reconstruction (MBIR) algorithms such as penalized-likelihood (PL) methods exhibit data-dependent and shift-variant properties. Image quality predictors have been derived to prospectively estimate local noise and spatial resolution, facilitating both system hardware design and tuning of reconstruction methods. However, current MBIR image quality predictors rely on idealized system models, ignoring physical blurring effects and noise correlations found in real systems. In this work, we develop and validate a new set of predictors using a physical system model specific to flat-panel cone-beam CT (FP-CBCT). METHODS Physical models appropriate for integration with MBIR analysis are developed and parameterized to represent nonidealities in FP projection data including focal spot blur, scintillator blur, detector aperture effect, and noise correlations. Flat-panel-specific predictors for local spatial resolution and local noise properties in PL reconstructions are developed based on these realistic physical models. Estimation accuracy of conventional (idealized) and FP-specific predictors is investigated and validated against experimental CBCT measurements using specialized phantoms. RESULTS Validation studies show that flat-panel-specific predictors can accurately estimate the local spatial resolution and noise properties, while conventional predictors show significant deviations in the magnitude and scale of the spatial resolution and local noise. The proposed predictors show accurate estimations over a range of imaging conditions including varying x-ray technique and regularization strength. The conventional spatial resolution prediction is sharper than ground truth. Using conventional spatial resolution predictor, the full width at half maximum (FWHM) of local point spread function (PSF) is underestimated by 0.2 mm. This mismatch is mostly eliminated in FP-specific prediction. The general shape and amplitude of local noise power spectrum (NPS) FP-specific predictions are consistent with measurement, while the conventional predictions underestimated the noise level by 70%. CONCLUSION The proposed image quality predictors permit accurate estimation of local spatial resolution and noise properties for PL reconstruction, accounting for dependencies on the system geometry, x-ray technique, and patient-specific anatomy in real FP-CBCT. Such tools enable prospective analysis of image quality for a range of goals including novel system and acquisition design, adaptive and task-driven imaging, and tuning of MBIR for robust and reliable behavior.
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Affiliation(s)
- Wenying Wang
- Department of Biomedical EngineeringJohns Hopkins UniversityBaltimoreMD21205USA
| | - Grace J. Gang
- Department of Biomedical EngineeringJohns Hopkins UniversityBaltimoreMD21205USA
| | | | - J. Webster Stayman
- Department of Biomedical EngineeringJohns Hopkins UniversityBaltimoreMD21205USA
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Kaasalainen T, Mäkelä T, Kortesniemi M. The effect of vertical centering and scout direction on automatic tube voltage selection in chest CT: a preliminary phantom study on two different CT equipments. Eur J Radiol Open 2018; 6:24-32. [PMID: 30619916 PMCID: PMC6298908 DOI: 10.1016/j.ejro.2018.12.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2018] [Revised: 12/11/2018] [Accepted: 12/11/2018] [Indexed: 12/11/2022] Open
Abstract
Purpose To determine the effect of patient's vertical off-centering and scout direction on the function of automatic tube voltage selection (ATVS) and tube current modulation (TCM) in chest computed tomography (CT). Methods Chest phantom was scanned with Siemens and GE CT systems using three clinical chest CT protocols exploiting ATVS and a fixed 120 kVp chest protocol. The scans were performed at five vertical positions of the phantom (-6 to +6 cm from the scanner isocenter). The effects of scout direction (posterior-to-anterior, anterior-to-posterior, and lateral) and vertical off-centering on the function of ATVS and TCM were studied by examining changes in selected voltage, radiation dose (volume CT dose index, CTDIvol), and image noise and contrast. Results Both scout direction and vertical off-centering affected ATVS. The effect differed between the vendors for the studied geometry, demonstrating differences in technical approaches. The greatest observed increase in CTDIvol due to off-centering was 91%. Anterior-to-posterior scout produced highest doses at the uppermost table position, whereas posterior-to-anterior scout produced highest doses at the lowermost table position. Dose varied least using lateral scouts. Vertical off-centering impacted image noise and contrast due to the combined effect of ATVS, TCM, structural noise, and bowtie filters. Conclusions Patient vertical off-centering and scout direction affected substantially the CTDIvol and image quality in chest CT examinations. Vertical off-centering caused variation also in the selected tube voltage. The function of ATVS and TCM methods differ significantly between the CT vendors, resulting in differences in CTDIvol and image noise characteristics.
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Affiliation(s)
- Touko Kaasalainen
- HUS Medical Imaging Center, Helsinki University Central Hospital, Finland.,Department of Physics, University of Helsinki, Finland
| | - Teemu Mäkelä
- HUS Medical Imaging Center, Helsinki University Central Hospital, Finland.,Department of Physics, University of Helsinki, Finland
| | - Mika Kortesniemi
- HUS Medical Imaging Center, Helsinki University Central Hospital, Finland.,Department of Physics, University of Helsinki, Finland
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Maamoun I, Khalil MM. Assessment of iterative image reconstruction on kidney and liver donors: Potential role of adaptive iterative dose reduction 3D (AIDR 3D) technology. Eur J Radiol 2018; 109:124-129. [PMID: 30527293 DOI: 10.1016/j.ejrad.2018.10.020] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2018] [Revised: 09/30/2018] [Accepted: 10/19/2018] [Indexed: 02/02/2023]
Abstract
OBJECTIVE The aim of this study was to evaluate the radiation exposure levels in two different types of subjects including liver and kidney donors in diagnostic assessment of transplant operation and also the significance of dose reduction on total effective dose. MATERIALS AND METHODS A number of Sixty subjects (40 males and 20 females, average age of 35 ± 10 years) were randomly prospectively recruited and equally divided into two distinct groups namely kidney donors (KD, 24 M and 6 F) and liver donors (LD, 21 M and 9 female). Kidney donors were divided into full dose (KFD, n = 20) group and low dose (KLD, n = 10) group. They had undergone dynamic renal scan using Tc99 m-DTPA, CT renal angiography and x-ray plain radiograph. Liver donors were divided into full dose (LFD, n = 20) and low dose (LLD, n = 10) groups and performed CT liver volumetry. The CT dose index (CTDIvol), dose length product (DLP), total milli-ampere product time mAs, effective dose and image noise index were measured in all subjects of kidney and liver donors comparing full dose and low dose protocols. RESULTS In comparison of all subjects of kidney donor groups (KFD vs KLD), the parameters (mAs = 16386.8 ± 3140.7 vs 2830.286 ± 831.676), (CTDIvol = 183.19 ± 32.58 mGy vs. 45.5 ± 13.3 mGy), DLP = 2884 ± 859.0 mGy.cm vs. 1437.5 ± 399 mGy.cm) and (effective dose = 49.0 ± 9.0 mSv vs. 18.9 mSv±5.7 mSv) were significant, p < 0.0005. Statistical evaluation of liver donors groups (LFD vs LLD) showed that (mAs = 14348.8 ± 4571.8 vs 3123.357 ± 794.5), (CTDIvol = 333.6 ± 59.5 mGy vs. 51.4 ± 13 mGy), (DLP = 3268.3 ± 604.3 mGy.cm vs 1260.5 ± 404.6 mGy.cm) and (effective dose = 43.3 mSv±12.9 mSv vs. 21.6 ± 5.9 mSv) are statistically significant, p < 0.0005. Nevertheless, the comparative evaluation of the image quality noise index of KFD vs KLD groups and LFD vs LLD showed a no statistical significance p > 0.05. CONCLUSION Renal and liver donors bear a relatively significant radiation dose due to diagnostic evaluation and patient management. The CT iterative reconstruction using AIDR3D proved very valuable tool in dose reduction such that it can reduce 37% in kidney donors and 48% in liver donors while able to maintain an acceptable image quality. Monitoring of those subjects on the clinical and radiobiological levels are recommended.
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Affiliation(s)
- I Maamoun
- Department of Intensive Care, Nuclear Cardiology Unit, Faculty of Medicine, Cairo University, Cairo, Egypt
| | - Magdy M Khalil
- Department of Physics, Faculty of Science, Helwan University, Cairo, Egypt.
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Shunhavanich P, Hsieh SS, Pelc NJ. Fluid-filled dynamic bowtie filter: Description and comparison with other modulators. Med Phys 2018; 46:127-139. [PMID: 30383310 DOI: 10.1002/mp.13272] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Revised: 09/30/2018] [Accepted: 10/22/2018] [Indexed: 11/09/2022] Open
Abstract
PURPOSE A dynamic bowtie filter can modulate flux along both fan and view angles for reduced patient dose, scatter, and required photon flux, which is especially important for photon counting detectors (PCDs). Among the proposed dynamic bowtie designs, the piecewise-linear attenuator (Hsieh and Pelc, Med Phys. 2013;40:031910) offers more flexibility than conventional filters, but relies on analog positioning of a limited number of wedges. In this work, we study our previously proposed dynamic attenuator design, the fluid-filled dynamic bowtie filter (FDBF) that has digital control. Specifically, we use computer simulations to study fluence modulation, reconstructed image noise, and radiation dose and to compare it to other attenuators. FDBF is an array of small channels each of which, if it can be filled with dense fluid or emptied quickly, has a binary effect on the flux. The cumulative attenuation from each channel along the x-ray path contributes to the FDBF total attenuation. METHODS An algorithm is proposed for selecting which FDBF channels should be filled. Two optimization metrics are considered: minimizing the maximum-count-rate for PCDs and minimizing peak-variance for energy-integrating detectors (EIDs) at fixed radiation dose (for optimizing dose efficiency). Using simulated chest, abdomen, and shoulder data, the performance is compared with a conventional bowtie and a piecewise-linear attenuator. For minimizing peak-variance, a perfect-attenuator (hypothetical filter capable of adjusting the fluence of each ray individually) and flat-variance attenuator are also included in the comparison. Two possible fluids, solutions of zinc bromide and gadolinium chloride, were tested. RESULTS To obtain the same SNR as routine clinical protocols, the proposed FDBF reduces the maximum-count-rate (across projection data, averaged over the test objects) of PCDs to 1.2 Mcps/mm2 , which is 55.8 and 3.3 times lower than the max-count-rate of the conventional bowtie and the piecewise-linear bowtie, respectively. (Averaged across objects for FDBF, the max-count-rate without object and FDBF is 2063.5 Mcps/mm2 , and the max-count-rate with object without FDBF is 749.8 Mcps/mm2 .) Moreover, for the peak-variance analysis, the FDBF can reduce entrance-energy-fluence (sum of energy incident on objects, used as a surrogate for dose) to 34% of the entrance-energy-fluence from the conventional filter on average while achieving the same peak noise level. Its entrance-energy-fluence reduction performance is only 7% worse than the perfect-attenuator on average and is 13% better than the piecewise-linear filter for chest and shoulder. Furthermore, the noise-map in reconstructed image domain from the FDBF is more uniform than the piecewise-linear filter, with 3 times less variation across the object. For the dose reduction task, the zinc bromide solution performed slightly poorer than stainless steel but was better than the gadolinium chloride solution. CONCLUSIONS The FDBF allows finer control over flux distribution compared to piecewise-linear and conventional bowtie filters. It can reduce the required maximum-count-rate for PCDs to a level achievable by current detector designs and offers a high dose reduction factor.
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Affiliation(s)
- Picha Shunhavanich
- Departments of Bioengineering and Radiology, Stanford University, Stanford, CA, 94305, USA
| | - Scott S Hsieh
- Department of Radiological Sciences, University of California, Los Angeles, Los Angeles, CA, 90024, USA
| | - Norbert J Pelc
- Departments of Bioengineering and Radiology, Stanford University, Stanford, CA, 94305, USA
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Masuda T, Funama Y, Nakaura T, Tahara M, Yamashita Y, Kiguchi M, Imada N, Sato T, Awai K. Radiation Dose Reduction with a Low-Tube Voltage Technique for Pediatric Chest Computed Tomographic Angiography Based on the Contrast-to-Noise Ratio Index. Can Assoc Radiol J 2018; 69:390-396. [DOI: 10.1016/j.carj.2018.05.004] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2017] [Revised: 03/08/2018] [Accepted: 05/16/2018] [Indexed: 10/28/2022] Open
Abstract
Introduction The aim of this study was to evaluate the radiation dose and image quality at low tube-voltage pediatric chest computed tomographic angiography (CTA) that applies the same contrast-to-noise ratio (CNR) index as the standard tube voltage technique. Materials and Methods Contrast-enhanced chest CTA scans of 100 infants were acquired on a 64-row multidetector computed tomography (MDCT) scanner. In the retrospective study, we evaluated 50 images acquired at 120 kVp; the image noise level was set at 25 Hounsfield units. In the prospective study, we used an 80-kVp protocol; the image noise level was 40 Hounsfield units because the iodine contrast was 1.6 times higher than on 120-kVp scans; the CNR was as in the 120-kVp protocol. We compared the CT number, image noise, CT dose index volume (CTDIvol), and the dose-length product on scans acquired with the 2 protocols. A diagnostic radiologist and a pediatric cardiologist visually evaluated all CTA images. Results The mean CTDIvol and the mean dose-length product were 0.5 mGy and 7.8 mGy-cm for 80- and 1.2 mGy and 20.8 mGy-cm for 120-kVp scans, respectively ( P < .001). The mean CTDIvol was 42% lower at 80 kVp than at 120 kVp, and there was no significant difference in the visual scores assigned to the CTA images ( P = .28). Conclusions With the CNR index being the same at 80-kVp and 120-kVp imaging, the radiation dose delivered to infants subjected to chest CTA can be reduced without degradation of the image quality.
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Affiliation(s)
- Takanori Masuda
- Department of Radiological Technology, Tsuchiya General Hospital, Hiroshima, Japan
- Department of Diagnostic Radiology, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima, Japan
| | - Yoshinori Funama
- Department of Medical Physics, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
| | - Takeshi Nakaura
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan
| | - Masahiro Tahara
- Department of Pediatric Cardiology, Tsuchiya General Hospital, Hiroshima, Japan
| | - Yukari Yamashita
- Department of Radiological Technology, Tsuchiya General Hospital, Hiroshima, Japan
| | - Masao Kiguchi
- Department of Diagnostic Radiology, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima, Japan
| | - Naoyuki Imada
- Department of Radiological Technology, Tsuchiya General Hospital, Hiroshima, Japan
| | - Tomoyasu Sato
- Department of Diagnostic Radiology, Tsuchiya General Hospital, Hiroshima, Japan
| | - Kazuo Awai
- Department of Diagnostic Radiology, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima, Japan
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Willemink MJ, Noël PB. The evolution of image reconstruction for CT-from filtered back projection to artificial intelligence. Eur Radiol 2018; 29:2185-2195. [PMID: 30377791 PMCID: PMC6443602 DOI: 10.1007/s00330-018-5810-7] [Citation(s) in RCA: 294] [Impact Index Per Article: 42.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Revised: 09/12/2018] [Accepted: 09/27/2018] [Indexed: 12/22/2022]
Abstract
Abstract The first CT scanners in the early 1970s already used iterative reconstruction algorithms; however, lack of computational power prevented their clinical use. In fact, it took until 2009 for the first iterative reconstruction algorithms to come commercially available and replace conventional filtered back projection. Since then, this technique has caused a true hype in the field of radiology. Within a few years, all major CT vendors introduced iterative reconstruction algorithms for clinical routine, which evolved rapidly into increasingly advanced reconstruction algorithms. The complexity of algorithms ranges from hybrid-, model-based to fully iterative algorithms. As a result, the number of scientific publications on this topic has skyrocketed over the last decade. But what exactly has this technology brought us so far? And what can we expect from future hardware as well as software developments, such as photon-counting CT and artificial intelligence? This paper will try answer those questions by taking a concise look at the overall evolution of CT image reconstruction and its clinical implementations. Subsequently, we will give a prospect towards future developments in this domain. Key Points • Advanced CT reconstruction methods are indispensable in the current clinical setting. • IR is essential for photon-counting CT, phase-contrast CT, and dark-field CT. • Artificial intelligence will potentially further increase the performance of reconstruction methods.
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Affiliation(s)
- Martin J Willemink
- Department of Radiology, Stanford University School of Medicine, 300 Pasteur Drive, Room M-039, Stanford, CA, 94305-5105, USA. .,Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Peter B Noël
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Department of Diagnostic and Interventional Radiology, Technische Universität München, Munich, Germany
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Noël PB, Engels S, Köhler T, Muenzel D, Franz D, Rasper M, Rummeny EJ, Dobritz M, Fingerle AA. Evaluation of an iterative model-based CT reconstruction algorithm by intra-patient comparison of standard and ultra-low-dose examinations. Acta Radiol 2018; 59:1225-1231. [PMID: 29320863 DOI: 10.1177/0284185117752551] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background The explosive growth of computer tomography (CT) has led to a growing public health concern about patient and population radiation dose. A recently introduced technique for dose reduction, which can be combined with tube-current modulation, over-beam reduction, and organ-specific dose reduction, is iterative reconstruction (IR). Purpose To evaluate the quality, at different radiation dose levels, of three reconstruction algorithms for diagnostics of patients with proven liver metastases under tumor follow-up. Material and Methods A total of 40 thorax-abdomen-pelvis CT examinations acquired from 20 patients in a tumor follow-up were included. All patients were imaged using the standard-dose and a specific low-dose CT protocol. Reconstructed slices were generated by using three different reconstruction algorithms: a classical filtered back projection (FBP); a first-generation iterative noise-reduction algorithm (iDose4); and a next generation model-based IR algorithm (IMR). Results The overall detection of liver lesions tended to be higher with the IMR algorithm than with FBP or iDose4. The IMR dataset at standard dose yielded the highest overall detectability, while the low-dose FBP dataset showed the lowest detectability. For the low-dose protocols, a significantly improved detectability of the liver lesion can be reported compared to FBP or iDose4 ( P = 0.01). The radiation dose decreased by an approximate factor of 5 between the standard-dose and the low-dose protocol. Conclusion The latest generation of IR algorithms significantly improved the diagnostic image quality and provided virtually noise-free images for ultra-low-dose CT imaging.
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Affiliation(s)
- Peter B Noël
- Department of Diagnostic and Interventional Radiology, Technische Universität München, Munich, Germany
- Physics Department & Munich School of BioEngineering, Technische Universität München, Garching, Germany
| | - Stephan Engels
- Department of Diagnostic and Interventional Radiology, Technische Universität München, Munich, Germany
| | | | - Daniela Muenzel
- Department of Diagnostic and Interventional Radiology, Technische Universität München, Munich, Germany
- Physics Department & Munich School of BioEngineering, Technische Universität München, Garching, Germany
| | - Daniela Franz
- Department of Diagnostic and Interventional Radiology, Technische Universität München, Munich, Germany
| | - Michael Rasper
- Department of Diagnostic and Interventional Radiology, Technische Universität München, Munich, Germany
| | - Ernst J Rummeny
- Department of Diagnostic and Interventional Radiology, Technische Universität München, Munich, Germany
| | - Martin Dobritz
- Department of Diagnostic and Interventional Radiology, Technische Universität München, Munich, Germany
| | - Alexander A Fingerle
- Department of Diagnostic and Interventional Radiology, Technische Universität München, Munich, Germany
- Physics Department & Munich School of BioEngineering, Technische Universität München, Garching, Germany
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Zhang H, Wang J, Zeng D, Tao X, Ma J. Regularization strategies in statistical image reconstruction of low-dose x-ray CT: A review. Med Phys 2018; 45:e886-e907. [PMID: 30098050 PMCID: PMC6181784 DOI: 10.1002/mp.13123] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2018] [Revised: 06/22/2018] [Accepted: 08/04/2018] [Indexed: 12/17/2022] Open
Abstract
Statistical image reconstruction (SIR) methods have shown potential to substantially improve the image quality of low-dose x-ray computed tomography (CT) as compared to the conventional filtered back-projection (FBP) method. According to the maximum a posteriori (MAP) estimation, the SIR methods are typically formulated by an objective function consisting of two terms: (a) a data-fidelity term that models imaging geometry and physical detection processes in projection data acquisition, and (b) a regularization term that reflects prior knowledge or expectations of the characteristics of the to-be-reconstructed image. SIR desires accurate system modeling of data acquisition, while the regularization term also has a strong influence on the quality of reconstructed images. A variety of regularization strategies have been proposed for SIR in the past decades, based on different assumptions, models, and prior knowledge. In this paper, we review the conceptual and mathematical bases of these regularization strategies and briefly illustrate their efficacies in SIR of low-dose CT.
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Affiliation(s)
- Hao Zhang
- Department of Radiation OncologyStanford UniversityStanfordCA94304USA
| | - Jing Wang
- Department of Radiation OncologyUT Southwestern Medical CenterDallasTX75390USA
| | - Dong Zeng
- School of Biomedical EngineeringSouthern Medical UniversityGuangzhou510515China
| | - Xi Tao
- School of Biomedical EngineeringSouthern Medical UniversityGuangzhou510515China
| | - Jianhua Ma
- School of Biomedical EngineeringSouthern Medical UniversityGuangzhou510515China
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