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Banchini F, Capelli P, Hasnaoui A, Palmieri G, Romboli A, Giuffrida M. 3-D reconstruction in liver surgery: a systematic review. HPB (Oxford) 2024; 26:1205-1215. [PMID: 38960762 DOI: 10.1016/j.hpb.2024.06.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2024] [Revised: 05/27/2024] [Accepted: 06/12/2024] [Indexed: 07/05/2024]
Abstract
BACKGROUND Three-dimensional reconstruction of the liver offers several advantages to the surgeon before and during liver resection. This review discusses the factors behind the use of liver 3-D reconstruction. METHODS Systematic electronic search, according to PRISMA criteria, was performed. A literature search of scientific papers was performed until October 2023. Articles were chosen based on reference to 3-D liver reconstruction and their use in liver surgery. GRADE methodology and the modified Newcastle-Ottawa scale were used to assess the quality of the studies. RESULTS The research included 47 articles and 7724 patients were analyzed. Preoperative planning was performed with 3-D liver reconstruction in the 87.2% of the studies. Most of preoperative 3-D liver reconstructions were performed in the planning of complex or major hepatectomies. Complex hepatectomies were performed in 64.3% patients. The 55.3% of the studies reported an improved navigation and accuracy during liver resection. Four studies (8.6%) on living donor liver transplant (LDLT) concluded that 3-D liver reconstruction is useful for graft selection and vascular preservation. Nine papers (19.1%) reported an accurate measurement of future liver remnant. CONCLUSION Liver 3-D reconstruction helps surgeons in the planning of liver surgery, especially in liver graft and complex liver resections, increasing the accuracy of the surgical resection.
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Affiliation(s)
- Filippo Banchini
- Department of General Surgery, Ospedale Guglielmo da Saliceto, 29100 Piacenza, Italy
| | - Patrizio Capelli
- Department of General Surgery, Ospedale Guglielmo da Saliceto, 29100 Piacenza, Italy
| | - Anis Hasnaoui
- Department of General Surgery, Menzel Bourguiba Hospital, Tunis El Manar University, Tunis, Tunisia
| | - Gerardo Palmieri
- Department of General Surgery, Ospedale Guglielmo da Saliceto, 29100 Piacenza, Italy
| | - Andrea Romboli
- Department of General Surgery, Ospedale Guglielmo da Saliceto, 29100 Piacenza, Italy
| | - Mario Giuffrida
- Department of General Surgery, Ospedale Guglielmo da Saliceto, 29100 Piacenza, Italy.
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Yan Y, Chen Q, Dai X, Xiang Z, Long Z, Wu Y, Jiang H, Zou J, Wang M, Zhu Z. Amino acid metabolomics and machine learning for assessment of post-hepatectomy liver regeneration. Front Pharmacol 2024; 15:1345099. [PMID: 38855741 PMCID: PMC11157015 DOI: 10.3389/fphar.2024.1345099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 05/06/2024] [Indexed: 06/11/2024] Open
Abstract
Objective Amino acid (AA) metabolism plays a vital role in liver regeneration. However, its measuring utility for post-hepatectomy liver regeneration under different conditions remains unclear. We aimed to combine machine learning (ML) models with AA metabolomics to assess liver regeneration in health and non-alcoholic steatohepatitis (NASH). Methods The liver index (liver weight/body weight) was calculated following 70% hepatectomy in healthy and NASH mice. The serum levels of 39 amino acids were measured using ultra-high performance liquid chromatography-tandem mass spectrometry analysis. We used orthogonal partial least squares discriminant analysis to determine differential AAs and disturbed metabolic pathways during liver regeneration. The SHapley Additive exPlanations algorithm was performed to identify potential AA signatures, and five ML models including least absolute shrinkage and selection operator, random forest, K-nearest neighbor (KNN), support vector regression, and extreme gradient boosting were utilized to assess the liver index. Results Eleven and twenty-two differential AAs were identified in the healthy and NASH groups, respectively. Among these metabolites, arginine and proline metabolism were commonly disturbed metabolic pathways related to liver regeneration in both groups. Five AA signatures were identified, including hydroxylysine, L-serine, 3-methylhistidine, L-tyrosine, and homocitrulline in healthy group, and L-arginine, 2-aminobutyric acid, sarcosine, beta-alanine, and L-cysteine in NASH group. The KNN model demonstrated the best evaluation performance with mean absolute error, root mean square error, and coefficient of determination values of 0.0037, 0.0047, 0.79 and 0.0028, 0.0034, 0.71 for the healthy and NASH groups, respectively. Conclusion The KNN model based on five AA signatures performed best, which suggests that it may be a valuable tool for assessing post-hepatectomy liver regeneration in health and NASH.
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Affiliation(s)
- Yuqing Yan
- School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
- Department of Clinical Pharmacology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Qianping Chen
- School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
- Department of Clinical Pharmacology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Xiaoming Dai
- The First Affiliated Hospital, Department of Hepatobiliary Surgery, Hengyang Medical School, University of South China, Hengyang, Hunan, China
| | - Zhiqiang Xiang
- The First Affiliated Hospital, Department of Hepatobiliary Surgery, Hengyang Medical School, University of South China, Hengyang, Hunan, China
| | - Zhangtao Long
- The First Affiliated Hospital, Department of Hepatobiliary Surgery, Hengyang Medical School, University of South China, Hengyang, Hunan, China
| | - Yachen Wu
- The First Affiliated Hospital, Department of Hepatobiliary Surgery, Hengyang Medical School, University of South China, Hengyang, Hunan, China
| | - Hui Jiang
- Hengyang Medical School, University of South China, Hengyang, Hunan, China
| | - Jianjun Zou
- Department of Clinical Pharmacology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
- Department of Pharmacy, Nanjing First Hospital, China Pharmaceutical University, Nanjing, China
| | - Mu Wang
- The NanHua Affiliated Hospital, Clinical Research Institute, Hengyang Medical School, University of South China, Hengyang, Hunan, China
| | - Zhu Zhu
- The First Affiliated Hospital, Department of Hepatobiliary Surgery, Hengyang Medical School, University of South China, Hengyang, Hunan, China
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Haddad A, Lendoire M, Maki H, Kang HC, Habibollahi P, Odisio BC, Huang SY, Vauthey JN. Liver volumetry and liver-regenerative interventions: history, rationale, and emerging tools. J Gastrointest Surg 2024; 28:766-775. [PMID: 38519362 DOI: 10.1016/j.gassur.2024.02.020] [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: 12/16/2023] [Revised: 01/26/2024] [Accepted: 02/08/2024] [Indexed: 03/24/2024]
Abstract
BACKGROUND Postoperative hepatic insufficiency (PHI) is the most feared complication after hepatectomy. Volume of the future liver remnant (FLR) is one objectively measurable indicator to identify patients at risk of PHI. In this review, we summarized the development and rationale for the use of liver volumetry and liver-regenerative interventions and highlighted emerging tools that could yield new advancements in liver volumetry. METHODS A review of MEDLINE/PubMed, Embase, and Cochrane Library databases was conducted to identify literature related to liver volumetry. The references of relevant articles were reviewed to identify additional publications. RESULTS Liver volumetry based on radiologic imaging was developed in the 1980s to identify patients at risk of PHI and later used in the 1990s to evaluate grafts for living donor living transplantation. The field evolved in the 2000s by the introduction of standardized FLR based on the hepatic metabolic demands and in the 2010s by the introduction of the degree of hypertrophy and kinetic growth rate as measures of the FLR regenerative and functional capacity. Several liver-regenerative interventions, most notably portal vein embolization, are used to increase resectability and reduce the risk of PHI. In parallel with the increase in automation and machine assistance to physicians, many semi- and fully automated tools are being developed to facilitate liver volumetry. CONCLUSION Liver volumetry is the most reliable tool to detect patients at risk of PHI. Advances in imaging analysis technologies, newly developed functional measures, and liver-regenerative interventions have been improving our ability to perform safe hepatectomy.
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Affiliation(s)
- Antony Haddad
- Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States
| | - Mateo Lendoire
- Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States
| | - Harufumi Maki
- Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States
| | - Hyunseon Christine Kang
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States
| | - Peiman Habibollahi
- Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States
| | - Bruno C Odisio
- Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States
| | - Steven Y Huang
- Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States
| | - Jean-Nicolas Vauthey
- Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States.
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Entezari P, Toskich BB, Kim E, Padia S, Christopher D, Sher A, Thornburg B, Hohlastos ES, Salem R, Collins JD, Lewandowski RJ. Promoting Surgical Resection through Future Liver Remnant Hypertrophy. Radiographics 2022; 42:2166-2183. [PMID: 36206182 DOI: 10.1148/rg.220050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
An inadequate future liver remnant (FLR) can preclude curative-intent surgical resection for patients with primary or secondary hepatic malignancies. For patients with normal baseline liver function and without risk factors, an FLR of 20% is needed to maintain postsurgical hepatic function. However, the FLR requirement is higher for patients who are exposed to systemic chemotherapy (FLR, >30%) or have cirrhosis (FLR, >40%). Interventional radiologic and surgical methods to achieve FLR hypertrophy are evolving, including portal vein ligation, portal vein embolization, radiation lobectomy, hepatic venous deprivation, and associating liver partition and portal vein ligation for staged hepatectomy. Each technique offers particular advantages and disadvantages. Knowledge of these procedures can help clinicians to choose the suitable technique for each patient. The authors review the techniques used to develop FLR hypertrophy, focusing on technical considerations, outcomes, and the advantages and disadvantages of each approach. Online supplemental material is available for this article. ©RSNA, 2022.
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Affiliation(s)
- Pouya Entezari
- From the Department of Radiology, Section of Interventional Radiology (P.E., B.T., E.S.H., R.S., R.J.L.), and Department of Surgery, Division of Transplant Surgery (D.C.), Northwestern University, 676 N Saint Clair St, Chicago, IL 60611-2927; Department of Radiology, Section of Interventional Radiology, Mayo Clinic Florida, Jacksonville, Fla (B.B.T.); Department of Radiology, Section of Interventional Radiology, Mount Sinai University Hospitals, New York, NY (E.K., A.S.); Department of Radiology, Section of Interventional Radiology, University of California-Los Angeles, Los Angeles, Calif (S.P.); and Department of Radiology, Mayo Clinic Rochester, Rochester, Minn (J.D.C.)
| | - Beau B Toskich
- From the Department of Radiology, Section of Interventional Radiology (P.E., B.T., E.S.H., R.S., R.J.L.), and Department of Surgery, Division of Transplant Surgery (D.C.), Northwestern University, 676 N Saint Clair St, Chicago, IL 60611-2927; Department of Radiology, Section of Interventional Radiology, Mayo Clinic Florida, Jacksonville, Fla (B.B.T.); Department of Radiology, Section of Interventional Radiology, Mount Sinai University Hospitals, New York, NY (E.K., A.S.); Department of Radiology, Section of Interventional Radiology, University of California-Los Angeles, Los Angeles, Calif (S.P.); and Department of Radiology, Mayo Clinic Rochester, Rochester, Minn (J.D.C.)
| | - Edward Kim
- From the Department of Radiology, Section of Interventional Radiology (P.E., B.T., E.S.H., R.S., R.J.L.), and Department of Surgery, Division of Transplant Surgery (D.C.), Northwestern University, 676 N Saint Clair St, Chicago, IL 60611-2927; Department of Radiology, Section of Interventional Radiology, Mayo Clinic Florida, Jacksonville, Fla (B.B.T.); Department of Radiology, Section of Interventional Radiology, Mount Sinai University Hospitals, New York, NY (E.K., A.S.); Department of Radiology, Section of Interventional Radiology, University of California-Los Angeles, Los Angeles, Calif (S.P.); and Department of Radiology, Mayo Clinic Rochester, Rochester, Minn (J.D.C.)
| | - Siddharth Padia
- From the Department of Radiology, Section of Interventional Radiology (P.E., B.T., E.S.H., R.S., R.J.L.), and Department of Surgery, Division of Transplant Surgery (D.C.), Northwestern University, 676 N Saint Clair St, Chicago, IL 60611-2927; Department of Radiology, Section of Interventional Radiology, Mayo Clinic Florida, Jacksonville, Fla (B.B.T.); Department of Radiology, Section of Interventional Radiology, Mount Sinai University Hospitals, New York, NY (E.K., A.S.); Department of Radiology, Section of Interventional Radiology, University of California-Los Angeles, Los Angeles, Calif (S.P.); and Department of Radiology, Mayo Clinic Rochester, Rochester, Minn (J.D.C.)
| | - Derrick Christopher
- From the Department of Radiology, Section of Interventional Radiology (P.E., B.T., E.S.H., R.S., R.J.L.), and Department of Surgery, Division of Transplant Surgery (D.C.), Northwestern University, 676 N Saint Clair St, Chicago, IL 60611-2927; Department of Radiology, Section of Interventional Radiology, Mayo Clinic Florida, Jacksonville, Fla (B.B.T.); Department of Radiology, Section of Interventional Radiology, Mount Sinai University Hospitals, New York, NY (E.K., A.S.); Department of Radiology, Section of Interventional Radiology, University of California-Los Angeles, Los Angeles, Calif (S.P.); and Department of Radiology, Mayo Clinic Rochester, Rochester, Minn (J.D.C.)
| | - Alex Sher
- From the Department of Radiology, Section of Interventional Radiology (P.E., B.T., E.S.H., R.S., R.J.L.), and Department of Surgery, Division of Transplant Surgery (D.C.), Northwestern University, 676 N Saint Clair St, Chicago, IL 60611-2927; Department of Radiology, Section of Interventional Radiology, Mayo Clinic Florida, Jacksonville, Fla (B.B.T.); Department of Radiology, Section of Interventional Radiology, Mount Sinai University Hospitals, New York, NY (E.K., A.S.); Department of Radiology, Section of Interventional Radiology, University of California-Los Angeles, Los Angeles, Calif (S.P.); and Department of Radiology, Mayo Clinic Rochester, Rochester, Minn (J.D.C.)
| | - Bartley Thornburg
- From the Department of Radiology, Section of Interventional Radiology (P.E., B.T., E.S.H., R.S., R.J.L.), and Department of Surgery, Division of Transplant Surgery (D.C.), Northwestern University, 676 N Saint Clair St, Chicago, IL 60611-2927; Department of Radiology, Section of Interventional Radiology, Mayo Clinic Florida, Jacksonville, Fla (B.B.T.); Department of Radiology, Section of Interventional Radiology, Mount Sinai University Hospitals, New York, NY (E.K., A.S.); Department of Radiology, Section of Interventional Radiology, University of California-Los Angeles, Los Angeles, Calif (S.P.); and Department of Radiology, Mayo Clinic Rochester, Rochester, Minn (J.D.C.)
| | - Elias S Hohlastos
- From the Department of Radiology, Section of Interventional Radiology (P.E., B.T., E.S.H., R.S., R.J.L.), and Department of Surgery, Division of Transplant Surgery (D.C.), Northwestern University, 676 N Saint Clair St, Chicago, IL 60611-2927; Department of Radiology, Section of Interventional Radiology, Mayo Clinic Florida, Jacksonville, Fla (B.B.T.); Department of Radiology, Section of Interventional Radiology, Mount Sinai University Hospitals, New York, NY (E.K., A.S.); Department of Radiology, Section of Interventional Radiology, University of California-Los Angeles, Los Angeles, Calif (S.P.); and Department of Radiology, Mayo Clinic Rochester, Rochester, Minn (J.D.C.)
| | - Riad Salem
- From the Department of Radiology, Section of Interventional Radiology (P.E., B.T., E.S.H., R.S., R.J.L.), and Department of Surgery, Division of Transplant Surgery (D.C.), Northwestern University, 676 N Saint Clair St, Chicago, IL 60611-2927; Department of Radiology, Section of Interventional Radiology, Mayo Clinic Florida, Jacksonville, Fla (B.B.T.); Department of Radiology, Section of Interventional Radiology, Mount Sinai University Hospitals, New York, NY (E.K., A.S.); Department of Radiology, Section of Interventional Radiology, University of California-Los Angeles, Los Angeles, Calif (S.P.); and Department of Radiology, Mayo Clinic Rochester, Rochester, Minn (J.D.C.)
| | - Jeremy D Collins
- From the Department of Radiology, Section of Interventional Radiology (P.E., B.T., E.S.H., R.S., R.J.L.), and Department of Surgery, Division of Transplant Surgery (D.C.), Northwestern University, 676 N Saint Clair St, Chicago, IL 60611-2927; Department of Radiology, Section of Interventional Radiology, Mayo Clinic Florida, Jacksonville, Fla (B.B.T.); Department of Radiology, Section of Interventional Radiology, Mount Sinai University Hospitals, New York, NY (E.K., A.S.); Department of Radiology, Section of Interventional Radiology, University of California-Los Angeles, Los Angeles, Calif (S.P.); and Department of Radiology, Mayo Clinic Rochester, Rochester, Minn (J.D.C.)
| | - Robert J Lewandowski
- From the Department of Radiology, Section of Interventional Radiology (P.E., B.T., E.S.H., R.S., R.J.L.), and Department of Surgery, Division of Transplant Surgery (D.C.), Northwestern University, 676 N Saint Clair St, Chicago, IL 60611-2927; Department of Radiology, Section of Interventional Radiology, Mayo Clinic Florida, Jacksonville, Fla (B.B.T.); Department of Radiology, Section of Interventional Radiology, Mount Sinai University Hospitals, New York, NY (E.K., A.S.); Department of Radiology, Section of Interventional Radiology, University of California-Los Angeles, Los Angeles, Calif (S.P.); and Department of Radiology, Mayo Clinic Rochester, Rochester, Minn (J.D.C.)
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Hagen F, Mair A, Bitzer M, Bösmüller H, Horger M. Fully automated whole-liver volume quantification on CT-image data: Comparison with manual volumetry using enhanced and unenhanced images as well as two different radiation dose levels and two reconstruction kernels. PLoS One 2021; 16:e0255374. [PMID: 34339472 PMCID: PMC8328340 DOI: 10.1371/journal.pone.0255374] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 07/15/2021] [Indexed: 11/18/2022] Open
Abstract
OBJECTIVES To evaluate the accuracy of fully automated liver volume quantification vs. manual quantification using unenhanced as well as enhanced CT-image data as well as two different radiation dose levels and also two image reconstruction kernels. MATERIAL AND METHODS The local ethics board gave its approval for retrospective data analysis. Automated liver volume quantification in 300 consecutive livers in 164 male and 103 female oncologic patients (64±12y) performed at our institution (between January 2020 and May 2020) using two different dual-energy helicals: portal-venous phase enhanced, ref. tube current 300mAs (CARE Dose4D) for tube A (100 kV) and ref. 232mAs tube current for tube B (Sn140kV), slice collimation 0.6mm, reconstruction kernel I30f/1, recon. thickness of 0.6mm and 5mm, 80-100 mL iodine contrast agent 350 mg/mL, (flow 2mL/s) and unenhanced ref. tube current 100mAs (CARE Dose4D) for tube A (100 kV) and ref. 77mAs tube current for tube B (Sn140kV), slice collimation 0.6mm (kernel Q40f) were analyzed. The post-processing tool (syngo.CT Liver Analysis) is already FDA-approved. Two resident radiologists with no and 1-year CT-experience performed both the automated measurements independently from each other. Results were compared with those of manual liver volume quantification using the same software which was supervised by a senior radiologist with 30-year CT-experience (ground truth). RESULTS In total, a correlation of 98% was obtained for liver volumetry based on enhanced and unenhanced data sets compared to the manual liver quantification. Radiologist #1 and #2 achieved an inter-reader agreement of 99.8% for manual liver segmentation (p<0.0001). Automated liver volumetry resulted in an overestimation (>5% deviation) of 3.7% for unenhanced CT-image data and 4.0% for contrast-enhanced CT-images. Underestimation (<5%) of liver volume was 2.0% for unenhanced CT-image data and 1.3% for enhanced images after automated liver volumetry. Number and distribution of erroneous volume measurements using either thin or thick slice reconstructions was exactly the same, both for the enhanced as well for the unenhanced image data sets (p> 0.05). CONCLUSION Results of fully automated liver volume quantification are accurate and comparable with those of manual liver volume quantification and the technique seems to be confident even if unenhanced lower-dose CT image data is used.
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Affiliation(s)
- Florian Hagen
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University, Tübingen, Germany
| | - Antonia Mair
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University, Tübingen, Germany
| | - Michael Bitzer
- Department of Internal Medicine I, University Hospital Tübingen, Tübingen, Germany
| | - Hans Bösmüller
- Department of Pathology and Neuropathology, University Hospital Tübingen and Eberhard Karls University Tübingen, Tübingen, Germany
| | - Marius Horger
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University, Tübingen, Germany
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Winkel DJ, Weikert TJ, Breit HC, Chabin G, Gibson E, Heye TJ, Comaniciu D, Boll DT. Validation of a fully automated liver segmentation algorithm using multi-scale deep reinforcement learning and comparison versus manual segmentation. Eur J Radiol 2020; 126:108918. [PMID: 32171914 DOI: 10.1016/j.ejrad.2020.108918] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2019] [Revised: 01/29/2020] [Accepted: 02/23/2020] [Indexed: 12/12/2022]
Abstract
PURPOSE To evaluate the performance of an artificial intelligence (AI) based software solution tested on liver volumetric analyses and to compare the results to the manual contour segmentation. MATERIALS AND METHODS We retrospectively obtained 462 multiphasic CT datasets with six series for each patient: three different contrast phases and two slice thickness reconstructions (1.5/5 mm), totaling 2772 series. AI-based liver volumes were determined using multi-scale deep-reinforcement learning for 3D body markers detection and 3D structure segmentation. The algorithm was trained for liver volumetry on approximately 5000 datasets. We computed the absolute error of each automatically- and manually-derived volume relative to the mean manual volume. The mean processing time/dataset and method was recorded. Variations of liver volumes were compared using univariate generalized linear model analyses. A subgroup of 60 datasets was manually segmented by three radiologists, with a further subgroup of 20 segmented three times by each, to compare the automatically-derived results with the ground-truth. RESULTS The mean absolute error of the automatically-derived measurement was 44.3 mL (representing 2.37 % of the averaged liver volumes). The liver volume was neither dependent on the contrast phase (p = 0.697), nor on the slice thickness (p = 0.446). The mean processing time/dataset with the algorithm was 9.94 s (sec) compared to manual segmentation with 219.34 s. We found an excellent agreement between both approaches with an ICC value of 0.996. CONCLUSION The results of our study demonstrate that AI-powered fully automated liver volumetric analyses can be done with excellent accuracy, reproducibility, robustness, speed and agreement with the manual segmentation.
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Affiliation(s)
- David J Winkel
- Department of Radiology, University Hospital of Basel, Basel, Switzerland; Siemens Healthineers, Medical Imaging Technologies, Princeton, NJ, USA.
| | - Thomas J Weikert
- Department of Radiology, University Hospital of Basel, Basel, Switzerland
| | | | - Guillaume Chabin
- Siemens Healthineers, Medical Imaging Technologies, Princeton, NJ, USA
| | - Eli Gibson
- Siemens Healthineers, Medical Imaging Technologies, Princeton, NJ, USA
| | - Tobias J Heye
- Department of Radiology, University Hospital of Basel, Basel, Switzerland
| | - Dorin Comaniciu
- Siemens Healthineers, Medical Imaging Technologies, Princeton, NJ, USA
| | - Daniel T Boll
- Department of Radiology, University Hospital of Basel, Basel, Switzerland
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Bozkurt B, Emek E, Arikan T, Ceyhan O, Yazici P, Sahin T, Mammadov E, Serin A, Gurcan NI, Yuzer Y, Tokat Y. Liver Graft Volume Estimation by Manual Volumetry and Software-Aided Interactive Volumetry: Which is Better? Transplant Proc 2019; 51:2387-2390. [DOI: 10.1016/j.transproceed.2019.01.152] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2018] [Accepted: 01/21/2019] [Indexed: 02/07/2023]
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8
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Goja S, Yadav SK, Yadav A, Piplani T, Rastogi A, Bhangui P, Saigal S, Soin AS. Accuracy of preoperative CT liver volumetry in living donor hepatectomy and its clinical implications. Hepatobiliary Surg Nutr 2018; 7:167-174. [PMID: 30046567 DOI: 10.21037/hbsn.2017.08.02] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
Background An accurate preoperative volumetric assessment of donor liver is essential for successful living donor liver transplant by ensuring adequate remnant and graft recipient weight ratio (GRWR). Methods The study cohort consisted of 744 right lobe (RL), 65 left lobe (LL) and 33 left lateral sector (LLS) grafts from July 2010 to January 2014. A semi-automated interactive commercial software called AW Volume share 6 was used for volumetry. Bland Altman plot was used for assessing the agreement between estimated graft weight (EGW) and actual graft weight (AGW). Results There was no statistically significant difference between EGW and AGW for RL graft weight (722±134 vs. 717±126 gm; P=0.06). Although Bland Altman graph showed that 95% limits of agreement was more in LL (-164 to +110) than RL (-156 to +147) and LLS grafts (-137 to +239), CT scan significantly overestimated LL graft weight (EGW =460±118 gm vs. AGW =433±102 gm; P=0.003) and underestimated LLS graft weight (EGW =203±48 gm vs. AGW =254±49 gm; P<0.001). Conclusions CT volumetry overestimate LL graft and underestimate LLS graft weight. This should be factored in when selecting LL graft by taking higher GRWR.
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Affiliation(s)
- Sanjay Goja
- Institute of Liver Transplant and Regenerative Medicine, Medanta, The Medicity, Gurgaon, Delhi (NCR), India
| | - Sanjay Kumar Yadav
- Institute of Liver Transplant and Regenerative Medicine, Medanta, The Medicity, Gurgaon, Delhi (NCR), India
| | - Amardeep Yadav
- Institute of Liver Transplant and Regenerative Medicine, Medanta, The Medicity, Gurgaon, Delhi (NCR), India
| | - Tarun Piplani
- Department of Radiology and Nuclear Medicine, Medanta, The Medicity, Gurgaon, Delhi (NCR), India
| | - Amit Rastogi
- Institute of Liver Transplant and Regenerative Medicine, Medanta, The Medicity, Gurgaon, Delhi (NCR), India
| | - Prashant Bhangui
- Institute of Liver Transplant and Regenerative Medicine, Medanta, The Medicity, Gurgaon, Delhi (NCR), India
| | - Sanjiv Saigal
- Institute of Liver Transplant and Regenerative Medicine, Medanta, The Medicity, Gurgaon, Delhi (NCR), India
| | - Arvinder Singh Soin
- Institute of Liver Transplant and Regenerative Medicine, Medanta, The Medicity, Gurgaon, Delhi (NCR), India
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Comparative Evaluation of Three Software Packages for Liver and Spleen Segmentation and Volumetry. Acad Radiol 2017; 24:831-839. [PMID: 28258903 DOI: 10.1016/j.acra.2017.02.001] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2016] [Revised: 02/01/2017] [Accepted: 02/01/2017] [Indexed: 02/08/2023]
Abstract
RATIONALE AND OBJECTIVES This study aims to compare the speed and accuracy of three different software packages in segmenting the liver and the spleen. MATERIALS AND METHODS The three software packages are Advantage Workstation Solutions (AWS), Claron Technology (Claron) Liver Segmentor, and Vitrea Core Fx (Vitrea). The dataset consisted of abdominal computed tomography scans of 30 patients obtained from the portal venous phase. All but two of the patients had a cancer diagnosis. The livers of 14 patients and the spleens of 24 patients were reported as normal; the remaining livers and spleens contained one or more abnormalities. The initial segmentation times and volumes were recorded in Claron and Vitrea as these created automatic segmentations. The total segmentation times and volumes following corrections were recorded. The livers and spleens were segmented separately by two radiologists who used all three packages. Accuracy was assessed by comparing volumes measured using fully manual segmentation on the AWS. RESULTS Claron could not segment the spleen in four subjects for the first reader and in two subjects for the second reader. The final mean segmentation times for the liver for both readers were 6.5 and 5.5 minutes for AWS, 4.4 and 3.6 minutes for Claron, and 5.1 and 4.2 minutes for Vitrea. The final mean segmentation times for the spleen were 2.7 and 2.1 minutes for AWS, 2.1 and 1.4 minutes for Claron, and 1.8 and 1.2 minutes for Vitrea. No statistically significant difference was found between the organ volumes measured by the two readers when using Vitrea. The mean differences between the initial and final segmentation volumes ranged from -1.2% to 0.4% for the liver and from -4.0% to 9.8% for the spleen. The mean differences between the automated liver segmentation volumes and the AWS volumes were 2.5%-2.9% for Claron and 4.9%-6.6% for Vitrea. The mean differences between the automated splenic segmentation volumes and the AWS volumes were 5.0%-6.2% for Claron and 10.6%-12.0% for Vitrea. CONCLUSIONS Both automated packages (Claron and Vitrea) measured liver and spleen volumes that were accurate and quick before manual correction. Volumes for the liver were more accurate than those for the spleen, perhaps due to the much smaller splenic volumes compared to those of the liver. For both liver and spleen, manual corrections were time consuming and for most subjects did not significantly change the volume measurement.
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Mussin N, Sumo M, Lee KW, Choi Y, Choi JY, Ahn SW, Yoon KC, Kim HS, Hong SK, Yi NJ, Suh KS. The correlation between preoperative volumetry and real graft weight: comparison of two volumetry programs. Ann Surg Treat Res 2017; 92:214-220. [PMID: 28382294 PMCID: PMC5378562 DOI: 10.4174/astr.2017.92.4.214] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2016] [Revised: 11/01/2016] [Accepted: 11/01/2016] [Indexed: 12/16/2022] Open
Abstract
Purpose Liver volumetry is a vital component in living donor liver transplantation to determine an adequate graft volume that meets the metabolic demands of the recipient and at the same time ensures donor safety. Most institutions use preoperative contrast-enhanced CT image-based software programs to estimate graft volume. The objective of this study was to evaluate the accuracy of 2 liver volumetry programs (Rapidia vs. Dr. Liver) in preoperative right liver graft estimation compared with real graft weight. Methods Data from 215 consecutive right lobe living donors between October 2013 and August 2015 were retrospectively reviewed. One hundred seven patients were enrolled in Rapidia group and 108 patients were included in the Dr. Liver group. Estimated graft volumes generated by both software programs were compared with real graft weight measured during surgery, and further classified into minimal difference (≤15%) and big difference (>15%). Correlation coefficients and degree of difference were determined. Linear regressions were calculated and results depicted as scatterplots. Results Minimal difference was observed in 69.4% of cases from Dr. Liver group and big difference was seen in 44.9% of cases from Rapidia group (P = 0.035). Linear regression analysis showed positive correlation in both groups (P < 0.01). However, the correlation coefficient was better for the Dr. Liver group (R2 = 0.719), than for the Rapidia group (R2 = 0.688). Conclusion Dr. Liver can accurately predict right liver graft size better and faster than Rapidia, and can facilitate preoperative planning in living donor liver transplantation.
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Affiliation(s)
- Nadiar Mussin
- Department of Surgery, Seoul National University College of Medicine, Seoul, Korea
| | - Marco Sumo
- Department of Surgery, Seoul National University College of Medicine, Seoul, Korea.; Department of Surgery, The Medical City Hospital, Manila, Philippines
| | - Kwang-Woong Lee
- Department of Surgery, Seoul National University College of Medicine, Seoul, Korea
| | - YoungRok Choi
- Department of Surgery, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Jin Yong Choi
- Department of Surgery, Seoul National University College of Medicine, Seoul, Korea
| | - Sung-Woo Ahn
- Department of Surgery, Seoul National University College of Medicine, Seoul, Korea
| | - Kyung Chul Yoon
- Department of Surgery, Seoul National University College of Medicine, Seoul, Korea
| | - Hyo-Sin Kim
- Department of Surgery, Seoul National University College of Medicine, Seoul, Korea
| | - Suk Kyun Hong
- Department of Surgery, Seoul National University College of Medicine, Seoul, Korea
| | - Nam-Joon Yi
- Department of Surgery, Seoul National University College of Medicine, Seoul, Korea
| | - Kyung-Suk Suh
- Department of Surgery, Seoul National University College of Medicine, Seoul, Korea
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11
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Gotra A, Chartrand G, Vu KN, Vandenbroucke-Menu F, Massicotte-Tisluck K, de Guise JA, Tang A. Comparison of MRI- and CT-based semiautomated liver segmentation: a validation study. Abdom Radiol (NY) 2017; 42:478-489. [PMID: 27680014 DOI: 10.1007/s00261-016-0912-7] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
PURPOSE To compare the repeatability, agreement, and efficiency of MRI- and CT-based semiautomated liver segmentation for the assessment of total and subsegmental liver volume. METHODS This retrospective study was conducted in 31 subjects who underwent contemporaneous liver MRI and CT. Total and subsegmental liver volumes were segmented from contrast-enhanced 3D gradient-recalled echo MRI sequences and CT images. Semiautomated segmentation was based on variational interpolation and Laplacian mesh optimization. All segmentations were repeated after 2 weeks. Manual segmentation of CT images using an active contour tool was used as the reference standard. Repeatability and agreement of the methods were evaluated with intra-class correlation coefficients (ICC) and Bland-Altman analysis. Total interaction time was recorded. RESULTS Intra-reader ICC were ≥0.987 for MRI and ≥0.995 for CT. Intra-reader repeatability was 30 ± 217 ml (bias ± 1.96 SD) (95% limits of agreement: -187 to 247 ml) for MRI and -10 ± 143 ml (-153 to 133 ml) for CT. Inter-method ICC between semiautomated and manual volumetry were ≥0.995 for MRI and ≥0.986 for CT. Inter-method segmental ICC varied between 0.584 and 0.865 for MRI and between 0.596 and 0.890 for CT. Inter-method agreement was -14 ± 136 ml (-150 to 122 ml) for MRI and 50 ± 226 ml (-176 to 276 ml) for CT. Inter-method segmental agreement ranged from 10 ± 47 ml (-37 to 57 ml) to 2 ± 214 ml (-212 to 216 ml) for MRI and 9 ± 45 ml (-36 to 54 ml) to -46 ± 183 ml (-229 to 137 ml) for CT. Interaction time (mean ± SD) was significantly shorter for MRI-based semiautomated segmentation (7.2 ± 0.1 min, p < 0.001) and for CT-based semiautomated segmentation (6.5 ± 0.2 min, p < 0.001) than for CT-based manual segmentation (14.5 ± 0.4 min). CONCLUSION MRI-based semiautomated segmentation provides similar repeatability and agreement to CT-based segmentation for total liver volume.
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12
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Kaufmann D, Lauscher JC, Gröne J, zur Hausen G, Kreis ME, Hamm B, Niehues SM. CT-based measurement of the inner pelvic volume. Acta Radiol 2017; 58:218-223. [PMID: 26966146 DOI: 10.1177/0284185116637248] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Background Surgery in the lesser pelvis is associated with a high complication rate as surgeons are spatially limited by solid anatomic structures and soft tissue borders. So far, only two-dimensional (2D) parameters have been used for risk stratification. Purpose To precisely measure the inner pelvic volume a computed tomography (CT)-based three-dimensional (3D) approach was established and compared to approximations by 2D parameter combinations. Material and Methods Thin-layered multi-slice CT datasets were used retrospectively for slice by slice depiction of the inner pelvic surface. The inner pelvic volume was then automatically compounded. Combinations of two to four 2D dimensions determined in 3D volume rendered reconstructions were correlated with the inner pelvic volume. Pearson's correlation coefficient and Chi square test were used for statistical calculations. Significance level was set at P < 0.05. Results In total 142 patients (91 men, 51 women) aged 64.8 ± 10.6 years at surgery were included in the study. Mean calculated pelvic volume was 1031.13 ± 180.06 cm3 (men, 996.57 ± 172.43 cm3; women, 1093.34 ± 178.39 cm3). Best approximations were obtained by combination of the 2D measurements transverse inlet and pelvic height for men (r = 0.799, P < 0.05) as well as transverse inlet, obstetric conjugate, interspinous distance and pelvic depth for women (r = 0.855, P < 0.05). Conclusion We describe a precise and reproducible CT-based method for pelvic volumetry. A less time consuming but still reliable approximation can be achieved by combination of two to four 2D dimensions.
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Affiliation(s)
- David Kaufmann
- Department of Radiology, Campus Benjamin Franklin, Charité Universitätsmedizin Berlin, Germany
| | - Johannes C Lauscher
- Department of Surgery, Campus Benjamin Franklin, Charité Universitätsmedizin Berlin, Germany
| | - Jörn Gröne
- Department of Surgery, Campus Benjamin Franklin, Charité Universitätsmedizin Berlin, Germany
| | - Gerrit zur Hausen
- Institute of Clinical Cancer Research, University Cancer Center, Krankenhaus Nordwest gGmbH, Frankfurt am Main, Germany
| | - Martin E Kreis
- Department of Surgery, Campus Benjamin Franklin, Charité Universitätsmedizin Berlin, Germany
| | - Bernd Hamm
- Department of Radiology, Campus Benjamin Franklin, Charité Universitätsmedizin Berlin, Germany
| | - Stefan M Niehues
- Department of Radiology, Campus Benjamin Franklin, Charité Universitätsmedizin Berlin, Germany
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Coimbra FJF, Ribeiro HSDC, Marques MC, Herman P, Chojniak R, Kalil AN, Wiermann EG, Cavallero SRDA, Coelho FF, Fernandes PHDS, Silvestrini AA, Almeida MFA, de Araújo ALE, Pitombo M, Teixeira HM, Waechter FL, Ferreira FG, Diniz AL, D'Ippolito G, D'Ippolito G, Begnami MDFDS, Prolla G, Balzan SMP, de Oliveira TB, Szultan LA, Lendoire J, Torres OJM. FIRST BRAZILIAN CONSENSUS ON MULTIMODAL TREATMENT OF COLORECTAL LIVER METASTASES. MODULE 1: PRE-TREATMENT EVALUATION. ABCD-ARQUIVOS BRASILEIROS DE CIRURGIA DIGESTIVA 2016; 28:222-30. [PMID: 26734788 PMCID: PMC4755170 DOI: 10.1590/s0102-6720201500040002] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/12/2015] [Accepted: 08/11/2015] [Indexed: 02/07/2023]
Abstract
Background : Liver metastases of colorectal cancer are frequent and potentially fatal event
in the evolution of patients with these tumors. Aim : In this module, was contextualized the clinical situations and parameterized
epidemiological data and results of the various treatment modalities established.
Method: Was realized deep discussion on detecting and staging metastatic colorectal
cancer, as well as employment of imaging methods in the evaluation of response to
instituted systemic therapy. Results : The next step was based on the definition of which patients would have their
metastases considered resectable and how to expand the amount of patients elegible
for modalities with curative intent. Conclusion : Were presented clinical, pathological and molecular prognostic factors,
validated to be taken into account in clinical practice.
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Affiliation(s)
| | | | | | - Paulo Herman
- American Hepato-Pancreato-Biliary Association, São Paulo, Brazil
| | - Rubens Chojniak
- American Hepato-Pancreato-Biliary Association, São Paulo, Brazil
| | | | | | | | | | | | | | | | | | - Marcos Pitombo
- American Hepato-Pancreato-Biliary Association, São Paulo, Brazil
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Lodewick TM, Arnoldussen CW, Lahaye MJ, van Mierlo KM, Neumann UP, Beets-Tan RG, Dejong CH, van Dam RM. Fast and accurate liver volumetry prior to hepatectomy. HPB (Oxford) 2016; 18:764-72. [PMID: 27593594 PMCID: PMC5011086 DOI: 10.1016/j.hpb.2016.06.009] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2016] [Revised: 06/05/2016] [Accepted: 06/11/2016] [Indexed: 12/12/2022]
Abstract
BACKGROUND Volumetric assessment of the liver is essential in the prevention of postresectional liver failure after partial hepatectomy. Currently used methods are accurate but time-consuming. This study aimed to test a new automated method for preoperative volumetric liver assessment. METHODS Patients who underwent a contrast enhanced portovenous phase CT-scan prior to hepatectomy in 2012 were included. Total liver volume (TLV) and future remnant liver volume (FRLV) were measured using TeraRecon Aquarius iNtuition(®) (autosegmentation) and OsiriX(®) (manual segmentation) software by two observers for each software package. Remnant liver volume percentage (RLV%) was calculated. Time needed to determine TLV and FRLV was measured. Inter-observer variability was assessed using Bland-Altman plots. RESULTS Twenty-seven patients were included. There were no significant differences in measured volumes between OsiriX(®) and iNtuition(®). Moreover, there were significant correlations between the OsiriX(®) observers, the iNtuition(®) observers and between OsiriX(®) and iNtuition(®) post-processing systems (all R(2) > 0.97). The median time needed for complete liver volumetric analysis was 18.4 ± 4.9 min with OsiriX(®) and 5.8 ± 1.7 min using iNtuition(®) (p < 0.001). CONCLUSION Both OsiriX(®) and iNtuition(®) liver volumetry are accurate and easily applicable. However, volumetric assessment of the liver with iNtuition(®) auto-segmentation is three times faster compared to manual OsiriX(®) volumetry.
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Affiliation(s)
- Toine M. Lodewick
- Department of Surgery, Maastricht University Medical Center & NUTRIM School of Nutrition & Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands,Department of Surgery, University Hospital Aachen, Division of General, Visceral and Transplantation Surgery, Aachen, Germany,Correspondence Toine M. Lodewick, Department of Surgery, Maastricht University, PO Box 616, 6200 MD, Maastricht, The Netherlands. Tel: +31 43 3881547, +31 43 3875473.Department of SurgeryMaastricht UniversityPO Box 616Maastricht6200 MDThe Netherlands
| | | | - Max J. Lahaye
- Department of Radiology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Kim M.C. van Mierlo
- Department of Surgery, Maastricht University Medical Center & NUTRIM School of Nutrition & Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
| | - Ulf P. Neumann
- Department of Surgery, Maastricht University Medical Center & NUTRIM School of Nutrition & Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands,Department of Surgery, University Hospital Aachen, Division of General, Visceral and Transplantation Surgery, Aachen, Germany
| | - Regina G. Beets-Tan
- Department of Radiology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Cornelis H.C. Dejong
- Department of Surgery, Maastricht University Medical Center & NUTRIM School of Nutrition & Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands,Department of Surgery, University Hospital Aachen, Division of General, Visceral and Transplantation Surgery, Aachen, Germany
| | - Ronald M. van Dam
- Department of Surgery, Maastricht University Medical Center & NUTRIM School of Nutrition & Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands,Department of Surgery, University Hospital Aachen, Division of General, Visceral and Transplantation Surgery, Aachen, Germany
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Monti L, Soglia G, Tomà P. Imaging in pediatric liver transplantation. Radiol Med 2016; 121:378-90. [PMID: 26909515 DOI: 10.1007/s11547-016-0628-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2016] [Accepted: 01/31/2016] [Indexed: 12/11/2022]
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Grieser C, Denecke T, Rothe JH, Geisel D, Stelter L, Cannon Walter T, Seehofer D, Steffen IG. Gd-EOB enhanced MRI T1-weighted 3D-GRE with and without elevated flip angle modulation for threshold-based liver volume segmentation. Acta Radiol 2015; 56:1419-27. [PMID: 25406435 DOI: 10.1177/0284185114558975] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2014] [Accepted: 10/16/2014] [Indexed: 12/15/2022]
Abstract
BACKGROUND Despite novel software solutions, liver volume segmentation is still a time-consuming procedure and often requires further manual optimization. With the high signal intensity of the liver parenchyma in Gd-EOB enhanced magnetic resonance imaging (MRI), liver volume segmentation may be improved. PURPOSE To evaluate the practicability of threshold-based segmentation of the liver volume using Gd-EOB-enhanced MRI including a customized three-dimensional (3D) sequence. MATERIAL AND METHODS A total of 20 patients examined with Gd-EOB MRI (hepatobiliary phase T1-weighted (T1W) 3D sequence [VIBE]; flip angle [FA], 10° and 30°) were enrolled in this retrospective study. The datasets were independently processed by two blinded observers (O1 and O2) in two ways: manual (man) and threshold-based (thresh; study method) segmentation of the liver each followed by an optimization step (man+opt and thresh+opt; man+opt [FA10°] served as reference method). Resulting liver volumes and segmentation times were compared. A liver conversion factor was calculated in percent, describing the non-hepatocellular fraction of the total liver volume, i.e. bile ducts and vessels. RESULTS Thresh+opt (FA10°) was significantly faster compared to the reference method leading to a median volume overestimation of 4%/8% (P < 0.001). Using thresh+opt (FA30°), segmentation was even faster (P < 0.001) and even reduced median volume deviation of 0%/2% (O1/O2; both P > 0.2). The liver conversion factor was found to be 10%. CONCLUSION Threshold-based liver segmentation employing Gd-EOB-enhanced hepatobiliary phase standard T1W 3D sequence is accurate and time-saving. The performance of this approach can be further improved by increasing the FA.
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Affiliation(s)
- Christian Grieser
- Klinik für Strahlenheilkunde, Campus Virchow-Klinikum, Charité – Universitätsmedizin Berlin, Germany
| | - Timm Denecke
- Klinik für Strahlenheilkunde, Campus Virchow-Klinikum, Charité – Universitätsmedizin Berlin, Germany
| | - Jan-Holger Rothe
- Klinik für Strahlenheilkunde, Campus Virchow-Klinikum, Charité – Universitätsmedizin Berlin, Germany
| | - Dominik Geisel
- Klinik für Strahlenheilkunde, Campus Virchow-Klinikum, Charité – Universitätsmedizin Berlin, Germany
| | - Lars Stelter
- Klinik für Strahlenheilkunde, Campus Virchow-Klinikum, Charité – Universitätsmedizin Berlin, Germany
| | - Thula Cannon Walter
- Klinik für Strahlenheilkunde, Campus Virchow-Klinikum, Charité – Universitätsmedizin Berlin, Germany
| | - Daniel Seehofer
- Klinik für Allgemein, Viszeral- und Transplantationschirurgie, Campus Virchow-Klinikum, Charité – Universitätsmedizin Berlin, Germany
| | - Ingo G Steffen
- Klinik für Strahlenheilkunde, Campus Virchow-Klinikum, Charité – Universitätsmedizin Berlin, Germany
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Gotra A, Chartrand G, Massicotte-Tisluck K, Morin-Roy F, Vandenbroucke-Menu F, de Guise JA, Tang A. Validation of a semiautomated liver segmentation method using CT for accurate volumetry. Acad Radiol 2015; 22:1088-98. [PMID: 25907454 DOI: 10.1016/j.acra.2015.03.010] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2014] [Revised: 03/08/2015] [Accepted: 03/10/2015] [Indexed: 02/07/2023]
Abstract
RATIONALE AND OBJECTIVES To compare the repeatability and agreement of a semiautomated liver segmentation method with manual segmentation for assessment of total liver volume on CT (computed tomography). MATERIALS AND METHODS This retrospective, institutional review board-approved study was conducted in 41 subjects who underwent liver CT for preoperative planning. The major pathologies encountered were colorectal cancer metastases, benign liver lesions and hepatocellular carcinoma. This semiautomated segmentation method is based on variational interpolation and 3D minimal path-surface segmentation. Total and subsegmental liver volumes were segmented from contrast-enhanced CT images in venous phase. Two image analysts independently performed semiautomated segmentations and two other image analysts performed manual segmentations. Repeatability and agreement of both methods were evaluated with intraclass correlation coefficients (ICC) and Bland-Altman analysis. Interaction time was recorded for both methods. RESULTS Bland-Altman analysis revealed an intrareader agreement of -1 ± 27 mL (mean ± 1.96 standard deviation) with ICC of 0.999 (P < .001) for manual segmentation and 12 ± 97 mL with ICC of 0.991 (P < .001) for semiautomated segmentation. Bland-Altman analysis revealed an interreader agreement of -4 ± 22 mL with ICC of 0.999 (P < .001) for manual segmentation and 5 ± 98 mL with ICC of 0.991 (P < .001) for semiautomated segmentation. Intermethod agreement was found to be 3 ± 120 mL with ICC of 0.988 (P < .001). Mean interaction time was 34.3 ± 16.7 minutes for the manual method and 8.0 ± 1.2 minutes for the semiautomated method (P < .001). CONCLUSIONS A semiautomated segmentation method can substantially shorten interaction time while preserving a high repeatability and agreement with manual segmentation.
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Affiliation(s)
- Akshat Gotra
- Department of Radiology, Saint-Luc Hospital, University of Montreal, 1058 rue Saint-Denis, Montreal, Quebec, Canada H2X 3J4; Department of Radiology, Montreal General Hospital, McGill University, Montreal, Quebec, Canada
| | - Gabriel Chartrand
- Imaging and Orthopaedics Research Laboratory (LIO), École de technologie supérieure, Centre de recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montreal, Quebec, Canada
| | - Karine Massicotte-Tisluck
- Department of Radiology, Saint-Luc Hospital, University of Montreal, 1058 rue Saint-Denis, Montreal, Quebec, Canada H2X 3J4
| | - Florence Morin-Roy
- Department of Radiology, Saint-Luc Hospital, University of Montreal, 1058 rue Saint-Denis, Montreal, Quebec, Canada H2X 3J4
| | - Franck Vandenbroucke-Menu
- Department of Hepato-biliary and Pancreatic Surgery, Saint-Luc Hospital, University of Montreal, Montreal, Quebec, Canada
| | - Jacques A de Guise
- Imaging and Orthopaedics Research Laboratory (LIO), École de technologie supérieure, Centre de recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montreal, Quebec, Canada
| | - An Tang
- Department of Radiology, Saint-Luc Hospital, University of Montreal, 1058 rue Saint-Denis, Montreal, Quebec, Canada H2X 3J4; Centre de recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montreal, Quebec, Canada.
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Luersen GF, Bhosale P, Szklaruk J. State-of-the-art cross-sectional liver imaging: beyond lesion detection and characterization. J Hepatocell Carcinoma 2015; 2:101-17. [PMID: 27508199 PMCID: PMC4918289 DOI: 10.2147/jhc.s85201] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Abstract
Cross-sectional imaging with computed tomography or magnetic resonance imaging is routinely used to detect and diagnose liver lesions; however, these examinations can provide additional important information. The improvement of equipment and techniques has allowed outstanding evaluation of the vascular and biliary anatomy, which is practicable in most routine examinations. Anatomical variants may exclude patients from certain therapeutic options and may be the cause of morbidity or mortality after surgery or interventional procedures. Diffuse liver disease, such as steatosis, hemochromatosis, or fibrosis, must be diagnosed and quantified. Usually these conditions are silent until the late stages, and imaging plays an important role in detecting them early. Additionally, a background of diffuse disease may interfere in a focal lesion systematic reasoning. The diagnostic probability of a particular nodule varies according to the background liver disease. Nowadays, most diffuse liver diseases can be easily and accurately quantified by imaging, which has allowed better understanding of these diseases and improved patient management. Finally, cross-sectional imaging can calculate total and partial liver volumes and estimate the future liver remnant after hepatectomy. This information helps to select patients for portal vein embolization and reduces postoperative complications. Use of a specific hepatic contrast agent on magnetic resonance imaging, in addition to improving detection and characterization of focal lesions, provides functional global and segmental information about the liver parenchyma.
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Affiliation(s)
- Gustavo Felipe Luersen
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Priya Bhosale
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Janio Szklaruk
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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Vohra S, Goyal N, Gupta S. Preoperative CT evaluation of potential donors in living donor liver transplantation. Indian J Radiol Imaging 2014; 24:350-9. [PMID: 25489128 PMCID: PMC4247504 DOI: 10.4103/0971-3026.143897] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Living donor liver transplantation is an effective, life sustaining surgical treatment in patients with end-stage liver disease and a successful liver transplant requires a close working relationship between the radiologist and the transplant surgeon. There is extreme variability in hepatic vascular anatomy; therefore, preoperative imaging of potential liver donors is crucial not only in donor selection but also helps the surgeons in planning their surgical approach. In this article, we elaborate important aspects in evaluation of potential liver donors on multi-detector computed tomography (MDCT) and the utility of MDCT in presurgical assessment of the hepatic parenchyma, relevant hepatic vascular anatomy and segmental liver volumes.
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Affiliation(s)
- Sandeep Vohra
- Department of Radiology, Center for Liver and Biliary Sciences, Indraprastha Apollo Hospital, New Delhi, India
| | - Neerav Goyal
- Departments of Surgical Gastroenterology and Liver Transplant, Center for Liver and Biliary Sciences, Indraprastha Apollo Hospital, New Delhi, India
| | - Subash Gupta
- Departments of Surgical Gastroenterology and Liver Transplant, Center for Liver and Biliary Sciences, Indraprastha Apollo Hospital, New Delhi, India
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D’Onofrio M, De Robertis R, Demozzi E, Crosara S, Canestrini S, Pozzi Mucelli R. Liver volumetry: Is imaging reliable? Personal experience and review of the literature. World J Radiol 2014; 6:62-71. [PMID: 24778768 PMCID: PMC4000610 DOI: 10.4329/wjr.v6.i4.62] [Citation(s) in RCA: 50] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2013] [Revised: 01/11/2014] [Accepted: 03/14/2014] [Indexed: 02/06/2023] Open
Abstract
The amount of the future liver remnant volume is fundamental for hepato-biliary surgery, representing an important potential risk-factor for the development of post-hepatectomy liver failure. Despite this, there is no uniform consensus about the amount of hepatic parenchyma that can be safely resected, nor about the modality that should be chosen for this evaluation. The pre-operative evaluation of hepatic volume, along with a precise identification of vascular and biliar anatomy and variants, are therefore necessary to reduce surgical complications, especially for extensive resections. Some studies have tried to validate imaging methods [ultrasound, computed tomography (CT), magnetic resonance imaging] for the assessment of liver volume, but there is no clear evidence about the most accurate method for this evaluation. Furthermore, this volumetric evaluation seems to have a certain degree of error, tending to overestimate the actual hepatic volume, therefore some conversion factors, which should give a more reliable evaluation of liver volume, have been proposed. It is widespread among non-radiologists the use of independent software for an off-site volumetric analysis, performed on digital imaging and communications in medicine images with their own personal computer, but very few studies have provided a validation of these methods. Moreover, while the pre-transplantation volumetric assessment is fundamental, it remains unclear whether it should be routinely performed in all patients undergoing liver resection. In this editorial the role of imaging in the estimation of liver volume is discussed, providing a review of the most recent literature and a brief personal series of correlations between liver volumes and resection specimens’ weight, in order to assess the precision of the volumetric CT evaluation.
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Podleska LE, Poeppel T, Herbrik M, Dahlkamp L, Grabellus F, Taeger G. Drug dosage in isolated limb perfusion: evaluation of a limb volume model for extremity volume calculation. World J Surg Oncol 2014; 12:81. [PMID: 24684972 PMCID: PMC3994217 DOI: 10.1186/1477-7819-12-81] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2013] [Accepted: 03/16/2014] [Indexed: 11/22/2022] Open
Abstract
Background Exact drug dosing in isolated limb perfusion (ILP) and infusion (ILI) is essential. We developed and evaluated a model for calculating the volume of extremities and compared this model with body weight- and height-dependent parameters. Methods The extremity was modeled by a row of coupled truncated cones. The sizes of the truncated cone bases were derived from the circumference measurements of the extremity at predefined levels (5 cm). The resulting volumes were added. This extremity volume model was correlated to the computed tomography (CT) volume data of the extremity (total limb volume). The extremity volume was also correlated with the patient’s body weight, body mass index (BMI) and ideal body weight (IBW). The no-fat CT limb volume was correlated with the circumference-measured limb volume corrected by the ideal-body-weight to actual-body-weight ratio (IBW corrected-limb-volume). Results The correlation between the CT volume and the volume measured by the circumference was high and significant. There was no correlation between the limb volume and the bare body weight, BMI or IBW. The correlation between the no-fat CT volume and IBW-corrected limb volume was high and significant. Conclusions An appropriate drug dosing in ILP can be achieved by combining the limb volume with the simple circumference measurements and the IBW to body-weight ratio.
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Affiliation(s)
- Lars Erik Podleska
- Department of Trauma Surgery and Musculoskeletal Surgical Oncology, University Hospital of Essen and Sarcoma Center at the West German Cancer Center (WTZ), University of Duisburg-Essen, Hufelandstr, 55, D-45122 Essen, Germany.
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Megally HI, Badran YM, Abdelal SM, Koriem EM. Role of MDCT angiography in assessment of vascular variant in potential living liver donor transplantation. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2013. [DOI: 10.1016/j.ejrnm.2013.07.009] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
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Rerknimitr R, Angsuwatcharakon P, Ratanachu-ek T, Khor CJL, Ponnudurai R, Moon JH, Seo DW, Pantongrag-Brown L, Sangchan A, Pisespongsa P, Akaraviputh T, Reddy ND, Maydeo A, Itoi T, Pausawasdi N, Punamiya S, Attasaranya S, Devereaux B, Ramchandani M, Goh KL. Asia-Pacific consensus recommendations for endoscopic and interventional management of hilar cholangiocarcinoma. J Gastroenterol Hepatol 2013; 28:593-607. [PMID: 23350673 DOI: 10.1111/jgh.12128] [Citation(s) in RCA: 182] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/20/2012] [Indexed: 12/13/2022]
Abstract
Hilar cholangiocarcinoma (HCCA) is one of the most common types of hepatobiliary cancers reported in the world including Asia-Pacific region. Early HCCA may be completely asymptomatic. When significant hilar obstruction develops, the patient presents with jaundice, pale stools, dark urine, pruritus, abdominal pain, and sometimes fever. Because no single test can establish the definite diagnosis then, a combination of many investigations such as tumor markers, tissue acquisition, computed tomography scan, magnetic resonance imaging/magnetic resonance cholangiopancreatography, endoscopic ultrasonography/intraductal ultrasonography, and advanced cholangioscopy is required. Surgery is the only curative treatment. Unfortunately, the majority of HCCA has a poor prognosis due to their advanced stage on presentation. Although there is no survival advantage, inoperable HCCA managed by palliative drainage may benefit from symptomatic improvement. Currently, there are three techniques of biliary drainage which include endoscopic, percutaneous, and surgical approaches. For nonsurgical approaches, stent is the most preferred device and there are two types of stents i.e. plastic and metal. Type of stent and number of stent for HCCA biliary drainage are subjected to debate because the decision is made under many grounds i.e. volume of liver drainage, life expectancy, expertise of the facility, etc. Recently, radio-frequency ablation and photodynamic therapy are promising techniques that may extend drainage patency. Through a review in the literature and regional data, the Asia-Pacific Working Group for hepatobiliary cancers has developed statements to assist clinicians in diagnosing and managing of HCCA. After voting anonymously using modified Delphi method, all final statements were determined for the level of evidence quality and strength of recommendation.
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Affiliation(s)
- Rungsun Rerknimitr
- Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
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