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Fathi M, Taher HJ, Al-Rubiae SJ, Yaghoobpoor S, Bahrami A, Eshraghi R, Sadri H, Asadi Anar M, Gholamrezanezhad A. Role of molecular imaging in prognosis, diagnosis, and treatment of gastrointestinal cancers: An update on new therapeutic methods. World J Methodol 2024; 14:93461. [PMID: 39712556 PMCID: PMC11287540 DOI: 10.5662/wjm.v14.i4.93461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 05/31/2024] [Accepted: 07/15/2024] [Indexed: 07/26/2024] Open
Abstract
One of the leading causes of cancer-related death is gastrointestinal cancer, which has a significant morbidity and mortality rate. Although preoperative risk assessment is essential for directing patient care, its biological behavior cannot be accurately predicted by conventional imaging investigations. Potential pathophysiological information in anatomical imaging that cannot be visually identified can now be converted into high-dimensional quantitative image features thanks to the developing discipline of molecular imaging. In order to enable molecular tissue profile in vivo, molecular imaging has most recently been utilized to phenotype the expression of single receptors and targets of biological therapy. It is expected that molecular imaging will become increasingly important in the near future, driven by the expanding range of biological therapies for cancer. With this live molecular fingerprinting, molecular imaging can be utilized to drive expression-tailored customized therapy. The technical aspects of molecular imaging are first briefly discussed in this review, followed by an examination of the most recent research on the diagnosis, prognosis, and potential future clinical methods of molecular imaging for GI tract malignancies.
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Affiliation(s)
- Mobina Fathi
- Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran 1983969411, Iran
| | | | | | - Shirin Yaghoobpoor
- Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran 1983969411, Iran
| | - Ashkan Bahrami
- Faculty of Medicine, Kashan University of Medical Sciences, Kashan 1617768911, Iran
| | - Reza Eshraghi
- Faculty of Medicine, Kashan University of Medical Sciences, Kashan 1617768911, Iran
| | - Hossein Sadri
- Faculty of Medicine, Kashan University of Medical Sciences, Kashan 1617768911, Iran
| | - Mahsa Asadi Anar
- Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran 1983969411, Iran
| | - Ali Gholamrezanezhad
- Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States
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Fajemisin JA, Gonzalez G, Rosenberg SA, Ullah G, Redler G, Latifi K, Moros EG, El Naqa I. Magnetic Resonance-Guided Cancer Therapy Radiomics and Machine Learning Models for Response Prediction. Tomography 2024; 10:1439-1454. [PMID: 39330753 PMCID: PMC11435563 DOI: 10.3390/tomography10090107] [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: 08/08/2024] [Revised: 08/27/2024] [Accepted: 08/28/2024] [Indexed: 09/28/2024] Open
Abstract
Magnetic resonance imaging (MRI) is known for its accurate soft tissue delineation of tumors and normal tissues. This development has significantly impacted the imaging and treatment of cancers. Radiomics is the process of extracting high-dimensional features from medical images. Several studies have shown that these extracted features may be used to build machine-learning models for the prediction of treatment outcomes of cancer patients. Various feature selection techniques and machine models interrogate the relevant radiomics features for predicting cancer treatment outcomes. This study aims to provide an overview of MRI radiomics features used in predicting clinical treatment outcomes with machine learning techniques. The review includes examples from different disease sites. It will also discuss the impact of magnetic field strength, sample size, and other characteristics on outcome prediction performance.
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Affiliation(s)
- Jesutofunmi Ayo Fajemisin
- Department of Physics, University of South Florida, Tampa, FL 33620, USA
- Machine Learning Department, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA
| | - Glebys Gonzalez
- Machine Learning Department, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA
| | - Stephen A Rosenberg
- Machine Learning Department, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA
- Radiation Oncology Department, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA
| | - Ghanim Ullah
- Department of Physics, University of South Florida, Tampa, FL 33620, USA
| | - Gage Redler
- Radiation Oncology Department, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA
| | - Kujtim Latifi
- Radiation Oncology Department, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA
| | - Eduardo G Moros
- Department of Physics, University of South Florida, Tampa, FL 33620, USA
- Machine Learning Department, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA
- Radiation Oncology Department, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA
| | - Issam El Naqa
- Department of Physics, University of South Florida, Tampa, FL 33620, USA
- Machine Learning Department, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA
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Baranwal J, Barse B, Di Petrillo A, Gatto G, Pilia L, Kumar A. Nanoparticles in Cancer Diagnosis and Treatment. MATERIALS (BASEL, SWITZERLAND) 2023; 16:5354. [PMID: 37570057 PMCID: PMC10420054 DOI: 10.3390/ma16155354] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 07/10/2023] [Accepted: 07/28/2023] [Indexed: 08/13/2023]
Abstract
The use of tailored medication delivery in cancer treatment has the potential to increase efficacy while decreasing unfavourable side effects. For researchers looking to improve clinical outcomes, chemotherapy for cancer continues to be the most challenging topic. Cancer is one of the worst illnesses despite the limits of current cancer therapies. New anticancer medications are therefore required to treat cancer. Nanotechnology has revolutionized medical research with new and improved materials for biomedical applications, with a particular focus on therapy and diagnostics. In cancer research, the application of metal nanoparticles as substitute chemotherapy drugs is growing. Metals exhibit inherent or surface-induced anticancer properties, making metallic nanoparticles extremely useful. The development of metal nanoparticles is proceeding rapidly and in many directions, offering alternative therapeutic strategies and improving outcomes for many cancer treatments. This review aimed to present the most commonly used nanoparticles for cancer applications.
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Affiliation(s)
- Jaya Baranwal
- DBT-ICGEB Centre for Advanced Bioenergy Research, International Centre for Genetic Engineering & Biotechnology, Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Brajesh Barse
- US India Business Council|US Chamber of Commerce, DLF Centre, Sansad Marg, New Delhi 110001, India
| | - Amalia Di Petrillo
- Department of Medical Sciences and Public Health, University of Cagliari, Monserrato, 09042 Cagliari, Italy;
| | - Gianluca Gatto
- Department of Electrical and Electronic Engineering, University of Cagliari, Via Marengo 2, 09123 Cagliari, Italy;
| | - Luca Pilia
- Department of Mechanical, Chemical and Material Engineering, University of Cagliari, Via Marengo 2, 09123 Cagliari, Italy
| | - Amit Kumar
- Department of Electrical and Electronic Engineering, University of Cagliari, Via Marengo 2, 09123 Cagliari, Italy;
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Chiu FY, Yen Y. Imaging biomarkers for clinical applications in neuro-oncology: current status and future perspectives. Biomark Res 2023; 11:35. [PMID: 36991494 DOI: 10.1186/s40364-023-00476-7] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 03/16/2023] [Indexed: 03/31/2023] Open
Abstract
Biomarker discovery and development are popular for detecting the subtle diseases. However, biomarkers are needed to be validated and approved, and even fewer are ever used clinically. Imaging biomarkers have a crucial role in the treatment of cancer patients because they provide objective information on tumor biology, the tumor's habitat, and the tumor's signature in the environment. Tumor changes in response to an intervention complement molecular and genomic translational diagnosis as well as quantitative information. Neuro-oncology has become more prominent in diagnostics and targeted therapies. The classification of tumors has been actively updated, and drug discovery, and delivery in nanoimmunotherapies are advancing in the field of target therapy research. It is important that biomarkers and diagnostic implements be developed and used to assess the prognosis or late effects of long-term survivors. An improved realization of cancer biology has transformed its management with an increasing emphasis on a personalized approach in precision medicine. In the first part, we discuss the biomarker categories in relation to the courses of a disease and specific clinical contexts, including that patients and specimens should both directly reflect the target population and intended use. In the second part, we present the CT perfusion approach that provides quantitative and qualitative data that has been successfully applied to the clinical diagnosis, treatment and application. Furthermore, the novel and promising multiparametric MR imageing approach will provide deeper insights regarding the tumor microenvironment in the immune response. Additionally, we briefly remark new tactics based on MRI and PET for converging on imaging biomarkers combined with applications of bioinformatics in artificial intelligence. In the third part, we briefly address new approaches based on theranostics in precision medicine. These sophisticated techniques merge achievable standardizations into an applicatory apparatus for primarily a diagnostic implementation and tracking radioactive drugs to identify and to deliver therapies in an individualized medicine paradigm. In this article, we describe the critical principles for imaging biomarker characterization and discuss the current status of CT, MRI and PET in finiding imaging biomarkers of early disease.
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Affiliation(s)
- Fang-Ying Chiu
- Center for Cancer Translational Research, Tzu Chi University, Hualien City, 970374, Taiwan.
- Center for Brain and Neurobiology Research, Tzu Chi University, Hualien City, 970374, Taiwan.
- Teaching and Research Headquarters for Sustainable Development Goals, Tzu Chi University, Hualien City, 970374, Taiwan.
| | - Yun Yen
- Center for Cancer Translational Research, Tzu Chi University, Hualien City, 970374, Taiwan.
- Ph.D. Program for Cancer Biology and Drug Discovery, Taipei Medical University, Taipei City, 110301, Taiwan.
- Graduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei City, 110301, Taiwan.
- TMU Research Center of Cancer Translational Medicine, Taipei Medical University, Taipei City, 110301, Taiwan.
- Cancer Center, Taipei Municipal WanFang Hospital, Taipei City, 116081, Taiwan.
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Algani YMA, Boopalan K, Elangovan G, Santosh DT, Chanthirasekaran K, Patra I, Pughazendi N, Kiranbala B, Nikitha R, Saranya M. Autonomous service for managing real time notification in detection of COVID-19 virus. COMPUTERS & ELECTRICAL ENGINEERING : AN INTERNATIONAL JOURNAL 2022; 101:108117. [PMID: 35645427 PMCID: PMC9130642 DOI: 10.1016/j.compeleceng.2022.108117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 05/15/2022] [Accepted: 05/23/2022] [Indexed: 06/15/2023]
Abstract
In today's world, the most prominent public issue in the field of medicine is the rapid spread of viral sickness. The seriousness of the disease lies in its fast spreading nature. The main aim of the study is the proposal of a framework for the earlier detection and forecasting of the COVID-19 virus infection amongst the people to avoid the spread of the disease across the world by undertaking the precautionary measures. According to this framework, there are four stages for the proposed work. This includes the collection of necessary data followed by the classification of the collected information which is then taken in the process of mining and extraction and eventually ending with the process of decision modelling. Since the frequency of the infection is very often a prescient one, the probabilistic examination is measured as a degree of membership characterised by the fever measure related to the same. The predictions are thereby realised using the temporal RNN. The model finally provides effective outcomes in the efficiency of classification, reliability, the prediction viability etc.
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Affiliation(s)
- Yousef Methkal Abd Algani
- Department of Mathematics, Sakhnin College, Israel
- Department of Mathematics, The Arab Academic College for Education in Israel-Haifa. Israel
| | - K Boopalan
- Annamacharya Institute of Technology and Sciences, Rajampet, India
| | - G Elangovan
- Department of Artificial Intelligence, Shri Vishnu Engineering College for Women, India
| | - D Teja Santosh
- Computer Science Engineering, CVR College of Engineering, Vastunagar, Mangalpalli (V), Ibrahimpatnam, T.S.-501 510, India
| | - K Chanthirasekaran
- Department of ECE, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai 602105, India
| | | | - N Pughazendi
- Department of CSE, Panimalar Engineering, College, Tamil Nadu, India
| | - B Kiranbala
- Department of Artificial Intelligence and Data Science, K.Ramakrishnan College of Engineering, Trichy, Tamil Nadu, India
| | - R Nikitha
- Department of Information Technology, RMD Engineering College, Chennai, India
| | - M Saranya
- Department of CSE, R M K College of Engineering and Technology, Chennai, India
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6
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Ahmad F, Salem-Bekhit MM, Khan F, Alshehri S, Khan A, Ghoneim MM, Wu HF, Taha EI, Elbagory I. Unique Properties of Surface-Functionalized Nanoparticles for Bio-Application: Functionalization Mechanisms and Importance in Application. NANOMATERIALS (BASEL, SWITZERLAND) 2022; 12:1333. [PMID: 35458041 PMCID: PMC9031869 DOI: 10.3390/nano12081333] [Citation(s) in RCA: 70] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 03/30/2022] [Accepted: 03/31/2022] [Indexed: 01/09/2023]
Abstract
This review tries to summarize the purpose of steadily developing surface-functionalized nanoparticles for various bio-applications and represents a fascinating and rapidly growing field of research. Due to their unique properties-such as novel optical, biodegradable, low-toxicity, biocompatibility, size, and highly catalytic features-these materials are considered superior, and it is thus vital to study these systems in a realistic and meaningful way. However, rapid aggregation, oxidation, and other problems are encountered with functionalized nanoparticles, inhibiting their subsequent utilization. Adequate surface modification of nanoparticles with organic and inorganic compounds results in improved physicochemical properties which can overcome these barriers. This review investigates and discusses the iron oxide nanoparticles, gold nanoparticles, platinum nanoparticles, silver nanoparticles, and silica-coated nanoparticles and how their unique properties after fabrication allow for their potential use in a wide range of bio-applications such as nano-based imaging, gene delivery, drug loading, and immunoassays. The different groups of nanoparticles and the advantages of surface functionalization and their applications are highlighted here. In recent years, surface-functionalized nanoparticles have become important materials for a broad range of bio-applications.
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Affiliation(s)
- Faheem Ahmad
- Department of Botany, Aligarh Muslim University, Aligarh 202002, India; (F.K.); (A.K.)
| | - Mounir M. Salem-Bekhit
- Department of Pharmaceutics, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia; (S.A.); (E.I.T.)
- Department of Microbiology and Immunology, Faculty of Pharmacy, Al-Azhar University, Cairo 11884, Egypt
| | - Faryad Khan
- Department of Botany, Aligarh Muslim University, Aligarh 202002, India; (F.K.); (A.K.)
| | - Sultan Alshehri
- Department of Pharmaceutics, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia; (S.A.); (E.I.T.)
| | - Amir Khan
- Department of Botany, Aligarh Muslim University, Aligarh 202002, India; (F.K.); (A.K.)
| | - Mohammed M. Ghoneim
- Department of Pharmacy Practice, College of Pharmacy, AlMaarefa University, Ad Diriyah 13713, Saudi Arabia;
| | - Hui-Fen Wu
- Department of Chemistry, National Sun Yat-Sen University, Kaohsiung, 70, Lien-Hai Road, Kaohsiung 80424, Taiwan;
- School of Pharmacy, College of Pharmacy, Kaohsiung Medical University, Kaohsiung 807, Taiwan
| | - Ehab I. Taha
- Department of Pharmaceutics, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia; (S.A.); (E.I.T.)
| | - Ibrahim Elbagory
- College of Pharmacy, Northern Border University, Arar 1321, Saudi Arabia;
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7
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Infante T, Francone M, De Rimini ML, Cavaliere C, Canonico R, Catalano C, Napoli C. Machine learning and network medicine: a novel approach for precision medicine and personalized therapy in cardiomyopathies. J Cardiovasc Med (Hagerstown) 2021; 22:429-440. [PMID: 32890235 DOI: 10.2459/jcm.0000000000001103] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
The early identification of pathogenic mechanisms is essential to predict the incidence and progression of cardiomyopathies and to plan appropriate preventive interventions. Noninvasive cardiac imaging such as cardiac computed tomography, cardiac magnetic resonance, and nuclear imaging plays an important role in diagnosis and management of cardiomyopathies and provides useful prognostic information. Most molecular factors exert their functions by interacting with other cellular components, thus many diseases reflect perturbations of intracellular networks. Indeed, complex diseases and traits such as cardiomyopathies are caused by perturbations of biological networks. The network medicine approach, by integrating systems biology, aims to identify pathological interacting genes and proteins, revolutionizing the way to know cardiomyopathies and shifting the understanding of their pathogenic phenomena from a reductionist to a holistic approach. In addition, artificial intelligence tools, applied to morphological and functional imaging, could allow imaging scans to be automatically analyzed to extract new parameters and features for cardiomyopathy evaluation. The aim of this review is to discuss the tools of network medicine in cardiomyopathies that could reveal new candidate genes and artificial intelligence imaging-based features with the aim to translate into clinical practice as diagnostic, prognostic, and predictive biomarkers and shed new light on the clinical setting of cardiomyopathies. The integration and elaboration of clinical habits, molecular big data, and imaging into machine learning models could provide better disease phenotyping, outcome prediction, and novel drug targets, thus opening a new scenario for the implementation of precision medicine for cardiomyopathies.
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Affiliation(s)
- Teresa Infante
- Department of Advanced Medical and Surgical Sciences (DAMSS), University of Campania 'Luigi Vanvitelli', Naples, Italy
| | - Marco Francone
- Department of Radiological, Oncological, and Pathological Sciences, La Sapienza University, Rome
| | | | | | - Raffaele Canonico
- U.O.C. of Dietetics, Sport Medicine and Psychophysical Wellbeing, Department of Experimental Medicine, University of Campania 'Luigi Vanvitelli', Naples, Italy
| | - Carlo Catalano
- Department of Radiological, Oncological, and Pathological Sciences, La Sapienza University, Rome
| | - Claudio Napoli
- Department of Advanced Medical and Surgical Sciences (DAMSS), University of Campania 'Luigi Vanvitelli', Naples, Italy
- IRCCS SDN
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8
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Thimmapuram M, Pentakota S, Naga Chandrika H. Deep Learning for Lung Cancer Prediction: A Study on NSCLC Patients. LECTURE NOTES IN NETWORKS AND SYSTEMS 2021:41-53. [DOI: 10.1007/978-981-16-1773-7_4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2025]
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9
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Farzin A, Etesami SA, Quint J, Memic A, Tamayol A. Magnetic Nanoparticles in Cancer Therapy and Diagnosis. Adv Healthc Mater 2020; 9:e1901058. [PMID: 32196144 PMCID: PMC7482193 DOI: 10.1002/adhm.201901058] [Citation(s) in RCA: 250] [Impact Index Per Article: 50.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Revised: 01/15/2020] [Indexed: 12/16/2022]
Abstract
There is urgency for the development of nanomaterials that can meet emerging biomedical needs. Magnetic nanoparticles (MNPs) offer high magnetic moments and surface-area-to-volume ratios that make them attractive for hyperthermia therapy of cancer and targeted drug delivery. Additionally, they can function as contrast agents for magnetic resonance imaging (MRI) and can improve the sensitivity of biosensors and diagnostic tools. Recent advancements in nanotechnology have resulted in the realization of the next generation of MNPs suitable for these and other biomedical applications. This review discusses methods utilized for the fabrication and engineering of MNPs. Recent progress in the use of MNPs for hyperthermia therapy, controlling drug release, MRI, and biosensing is also critically reviewed. Finally, challenges in the field and potential opportunities for the use of MNPs toward improving their properties are discussed.
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Affiliation(s)
- A. Farzin
- Division of Engineering in Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02139, USA
| | - S. Alireza Etesami
- Department of Mechanical Engineering, The University of Memphis. Memphis, TN 38152, USA
| | - Jacob Quint
- Department of Mechanical and Materials Engineering, University of Nebraska, Lincoln, Lincoln, NE, 68588, USA
| | - Adnan Memic
- Department of Biomedical Engineering, University of Connecticut, Farmington, CT, 06030, USA
| | - Ali Tamayol
- Division of Engineering in Medicine Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02139, USA
- Department of Mechanical and Materials Engineering, University of Nebraska, Lincoln, Lincoln, NE, 68588, USA
- Department of Biomedical Engineering, University of Connecticut, Farmington, CT, 06030, USA
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10
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Dammes N, Peer D. Monoclonal antibody-based molecular imaging strategies and theranostic opportunities. Theranostics 2020; 10:938-955. [PMID: 31903161 PMCID: PMC6929980 DOI: 10.7150/thno.37443] [Citation(s) in RCA: 90] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2019] [Accepted: 09/26/2019] [Indexed: 01/13/2023] Open
Abstract
Molecular imaging modalities hold great potential as less invasive techniques for diagnosis and management of various diseases. Molecular imaging combines imaging agents with targeting moieties to specifically image diseased sites in the body. Monoclonal antibodies (mAbs) have become increasingly popular as novel therapeutics against a variety of diseases due to their specificity, affinity and serum stability. Because of the same properties, mAbs are also exploited in molecular imaging to target imaging agents such as radionuclides to the cell of interest in vivo. Many studies investigated the use of mAb-targeted imaging for a variety of purposes, for instance to monitor disease progression and to predict response to a specific therapeutic agent. Herein, we highlighted the application of mAb-targeted imaging in three different types of pathologies: autoimmune diseases, oncology and cardiovascular diseases. We also described the potential of molecular imaging strategies in theranostics and precision medicine. Due to the nearly infinite repertoire of mAbs, molecular imaging can change the future of modern medicine by revolutionizing diagnostics and response prediction in practically any disease.
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Affiliation(s)
- Niels Dammes
- Laboratory of Precision NanoMedicine, Tel Aviv University, Tel Aviv 69978, Israel
- School of Molecular Cell Biology and Biotechnology, George S Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel
- Department of Materials Sciences and Engineering, Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv University, Tel Aviv 69978, Israel
- Center for Nanoscience and Nanotechnology, and Tel Aviv University, Tel Aviv 69978, Israel
- Cancer Biology Research Center, Tel Aviv University, Tel Aviv 69978, Israel
| | - Dan Peer
- Laboratory of Precision NanoMedicine, Tel Aviv University, Tel Aviv 69978, Israel
- School of Molecular Cell Biology and Biotechnology, George S Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel
- Department of Materials Sciences and Engineering, Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv University, Tel Aviv 69978, Israel
- Center for Nanoscience and Nanotechnology, and Tel Aviv University, Tel Aviv 69978, Israel
- Cancer Biology Research Center, Tel Aviv University, Tel Aviv 69978, Israel
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11
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Preclinical Molecular Imaging for Precision Medicine in Breast Cancer Mouse Models. CONTRAST MEDIA & MOLECULAR IMAGING 2019; 2019:8946729. [PMID: 31598114 PMCID: PMC6778915 DOI: 10.1155/2019/8946729] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 04/28/2019] [Accepted: 07/25/2019] [Indexed: 12/18/2022]
Abstract
Precision and personalized medicine is gaining importance in modern clinical medicine, as it aims to improve diagnostic precision and to reduce consequent therapeutic failures. In this regard, prior to use in human trials, animal models can help evaluate novel imaging approaches and therapeutic strategies and can help discover new biomarkers. Breast cancer is the most common malignancy in women worldwide, accounting for 25% of cases of all cancers and is responsible for approximately 500,000 deaths per year. Thus, it is important to identify accurate biomarkers for precise stratification of affected patients and for early detection of responsiveness to the selected therapeutic protocol. This review aims to summarize the latest advancements in preclinical molecular imaging in breast cancer mouse models. Positron emission tomography (PET) imaging remains one of the most common preclinical techniques used to evaluate biomarker expression in vivo, whereas magnetic resonance imaging (MRI), particularly diffusion-weighted (DW) sequences, has been demonstrated as capable of distinguishing responders from nonresponders for both conventional and innovative chemo- and immune-therapies with high sensitivity and in a noninvasive manner. The ability to customize therapies is desirable, as this will enable early detection of diseases and tailoring of treatments to individual patient profiles. Animal models remain irreplaceable in the effort to understand the molecular mechanisms and patterns of oncologic diseases.
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Langs G, Röhrich S, Hofmanninger J, Prayer F, Pan J, Herold C, Prosch H. Machine learning: from radiomics to discovery and routine. Radiologe 2019; 58:1-6. [PMID: 29922965 PMCID: PMC6244522 DOI: 10.1007/s00117-018-0407-3] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Abstract
Machine learning is rapidly gaining importance in radiology. It allows for the exploitation of patterns in imaging data and in patient records for a more accurate and precise quantification, diagnosis, and prognosis. Here, we outline the basics of machine learning relevant for radiology, and review the current state of the art, the limitations, and the challenges faced as these techniques become an important building block of precision medicine. Furthermore, we discuss the roles machine learning can play in clinical routine and research and predict how it might change the field of radiology.
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Affiliation(s)
- G Langs
- Department of Biomedical Imaging and Image-Guided Therapy, Computational Imaging Research Lab, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.
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13
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The European Institute for Biomedical Imaging Research (EIBIR). Strategic research agenda for biomedical imaging. Insights Imaging 2019; 10:7. [PMID: 30693378 PMCID: PMC6352390 DOI: 10.1186/s13244-019-0684-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2018] [Accepted: 01/03/2019] [Indexed: 12/18/2022] Open
Abstract
This Strategic Research Agenda identifies current challenges and needs in healthcare, illustrates how biomedical imaging and derived data can help to address these, and aims to stimulate dedicated research funding efforts.Medicine is currently moving towards a more tailored, patient-centric approach by providing personalised solutions for the individual patient. Innovation in biomedical imaging plays a key role in this process as it addresses the current needs for individualised prevention, treatment, therapy response monitoring, and image-guided surgery.The use of non-invasive biomarkers facilitates better therapy prediction and monitoring, leading to improved patient outcomes. Innovative diagnostic imaging technologies provide information about disease characteristics which, coupled with biological, genetic and -omics data, will contribute to an individualised diagnosis and therapy approach.In the emerging field of theranostics, imaging tools together with therapeutic agents enable the selection of best treatments and allow tailored therapeutic interventions.For prenatal monitoring, the use of innovative imaging technologies can ensure an early detection of malfunctions or disease.The application of biomedical imaging for diagnosis and management of lifestyle-induced diseases will help to avoid disease development through lifestyle changes.Artificial intelligence and machine learning in imaging will facilitate the improvement of image interpretation and lead to better disease prediction and therapy planning.As biomedical imaging technologies and analysis of existing imaging data provide solutions to current challenges and needs in healthcare, appropriate funding for dedicated research is needed to implement the innovative approaches for the wellbeing of citizens and patients.
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Hosny A, Parmar C, Coroller TP, Grossmann P, Zeleznik R, Kumar A, Bussink J, Gillies RJ, Mak RH, Aerts HJWL. Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study. PLoS Med 2018; 15:e1002711. [PMID: 30500819 PMCID: PMC6269088 DOI: 10.1371/journal.pmed.1002711] [Citation(s) in RCA: 350] [Impact Index Per Article: 50.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Accepted: 11/05/2018] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Non-small-cell lung cancer (NSCLC) patients often demonstrate varying clinical courses and outcomes, even within the same tumor stage. This study explores deep learning applications in medical imaging allowing for the automated quantification of radiographic characteristics and potentially improving patient stratification. METHODS AND FINDINGS We performed an integrative analysis on 7 independent datasets across 5 institutions totaling 1,194 NSCLC patients (age median = 68.3 years [range 32.5-93.3], survival median = 1.7 years [range 0.0-11.7]). Using external validation in computed tomography (CT) data, we identified prognostic signatures using a 3D convolutional neural network (CNN) for patients treated with radiotherapy (n = 771, age median = 68.0 years [range 32.5-93.3], survival median = 1.3 years [range 0.0-11.7]). We then employed a transfer learning approach to achieve the same for surgery patients (n = 391, age median = 69.1 years [range 37.2-88.0], survival median = 3.1 years [range 0.0-8.8]). We found that the CNN predictions were significantly associated with 2-year overall survival from the start of respective treatment for radiotherapy (area under the receiver operating characteristic curve [AUC] = 0.70 [95% CI 0.63-0.78], p < 0.001) and surgery (AUC = 0.71 [95% CI 0.60-0.82], p < 0.001) patients. The CNN was also able to significantly stratify patients into low and high mortality risk groups in both the radiotherapy (p < 0.001) and surgery (p = 0.03) datasets. Additionally, the CNN was found to significantly outperform random forest models built on clinical parameters-including age, sex, and tumor node metastasis stage-as well as demonstrate high robustness against test-retest (intraclass correlation coefficient = 0.91) and inter-reader (Spearman's rank-order correlation = 0.88) variations. To gain a better understanding of the characteristics captured by the CNN, we identified regions with the most contribution towards predictions and highlighted the importance of tumor-surrounding tissue in patient stratification. We also present preliminary findings on the biological basis of the captured phenotypes as being linked to cell cycle and transcriptional processes. Limitations include the retrospective nature of this study as well as the opaque black box nature of deep learning networks. CONCLUSIONS Our results provide evidence that deep learning networks may be used for mortality risk stratification based on standard-of-care CT images from NSCLC patients. This evidence motivates future research into better deciphering the clinical and biological basis of deep learning networks as well as validation in prospective data.
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Affiliation(s)
- Ahmed Hosny
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Chintan Parmar
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Thibaud P. Coroller
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Patrick Grossmann
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Roman Zeleznik
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Avnish Kumar
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Johan Bussink
- Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Robert J. Gillies
- Department of Cancer Physiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, United States of America
| | - Raymond H. Mak
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Hugo J. W. L. Aerts
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
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15
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Lu M, Zhan X. The crucial role of multiomic approach in cancer research and clinically relevant outcomes. EPMA J 2018; 9:77-102. [PMID: 29515689 PMCID: PMC5833337 DOI: 10.1007/s13167-018-0128-8] [Citation(s) in RCA: 155] [Impact Index Per Article: 22.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2017] [Accepted: 01/29/2018] [Indexed: 02/06/2023]
Abstract
Cancer with heavily economic and social burden is the hot point in the field of medical research. Some remarkable achievements have been made; however, the exact mechanisms of tumor initiation and development remain unclear. Cancer is a complex, whole-body disease that involves multiple abnormalities in the levels of DNA, RNA, protein, metabolite and medical imaging. Biological omics including genomics, transcriptomics, proteomics, metabolomics and radiomics aims to systematically understand carcinogenesis in different biological levels, which is driving the shift of cancer research paradigm from single parameter model to multi-parameter systematical model. The rapid development of various omics technologies is driving one to conveniently get multi-omics data, which accelerates predictive, preventive and personalized medicine (PPPM) practice allowing prediction of response with substantially increased accuracy, stratification of particular patients and eventual personalization of medicine. This review article describes the methodology, advances, and clinically relevant outcomes of different "omics" technologies in cancer research, and especially emphasizes the importance and scientific merit of integrating multi-omics in cancer research and clinically relevant outcomes.
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Affiliation(s)
- Miaolong Lu
- Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan 410008 People’s Republic of China
- Hunan Engineering Laboratory for Structural Biology and Drug Design, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan 410008 People’s Republic of China
- State Local Joint Engineering Laboratory for Anticancer Drugs, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan 410008 People’s Republic of China
| | - Xianquan Zhan
- Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan 410008 People’s Republic of China
- Hunan Engineering Laboratory for Structural Biology and Drug Design, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan 410008 People’s Republic of China
- State Local Joint Engineering Laboratory for Anticancer Drugs, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan 410008 People’s Republic of China
- The State Key Laboratory of Medical Genetics, Central South University, 88 Xiangya Road, Changsha, Hunan 410008 People’s Republic of China
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16
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Katsila T, Liontos M, Patrinos GP, Bamias A, Kardamakis D. The New Age of -omics in Urothelial Cancer - Re-wording Its Diagnosis and Treatment. EBioMedicine 2018; 28:43-50. [PMID: 29428524 PMCID: PMC5835572 DOI: 10.1016/j.ebiom.2018.01.044] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2018] [Revised: 01/31/2018] [Accepted: 01/31/2018] [Indexed: 02/06/2023] Open
Abstract
Unmet needs in urothelial cancer management represent an important challenge in our effort to improve long-term overall and disease-free survival rates with no significant compromise in quality of life. Radical cystectomy with pelvic lymph node dissection is the standard for the management of muscle-invasive, non-metastatic cancers. In spite of a 90% local disease control, up to 50% of patients ultimately die of distant metastasis. Bladder preservation using chemo-radiation is an acceptable alternative, but optimal patient selection remains elusive. Recent research is focused on the employment of tailored-made strategies in urothelial cancer exploiting the potential of theranostics in patient selection for specific therapies. Herein, we review the current knowledge on molecular theranostics in urothelial cancer and we suggest that this is the time to move toward imaging theranostics, if tailored-made disease management and patient stratification is envisaged.
Urothelial cancer management represents an important challenge. Optimum patient stratification and tailored-made theranostics remain elusive. Imaging theranostics is envisaged as a cancer roadmap.
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Affiliation(s)
- Theodora Katsila
- Department of Pharmacy, School of Health Sciences, University of Patras, Patras, Greece; Department of Radiation Oncology, University of Patras Medical School, Patras, Greece.
| | - Michalis Liontos
- Department of Clinical Therapeutics, National and Kapodistrian University of Athens, Athens, Greece
| | - George P Patrinos
- Department of Pharmacy, School of Health Sciences, University of Patras, Patras, Greece; Department of Pathology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Aristotelis Bamias
- Department of Clinical Therapeutics, National and Kapodistrian University of Athens, Athens, Greece
| | - Dimitrios Kardamakis
- Department of Radiation Oncology, University of Patras Medical School, Patras, Greece
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17
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Brix G, Salehi Ravesh M, Griebel J. Two-compartment modeling of tissue microcirculation revisited. Med Phys 2017; 44:1809-1822. [DOI: 10.1002/mp.12196] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Revised: 02/24/2017] [Accepted: 02/24/2017] [Indexed: 12/17/2022] Open
Affiliation(s)
- Gunnar Brix
- Department of Medical Radiation Protection; Federal Office for Radiation Protection; Ingolstädter Landstraße 1 D-85764 Oberschleissheim Germany
| | - Mona Salehi Ravesh
- Department of Congenital Heart Disease and Pediatric Cardiology; University Hospital Schleswig-Holstein; Arnold-Heller-Straße 3 D-24105 Kiel Germany
| | - Jürgen Griebel
- Department of Medical Radiation Protection; Federal Office for Radiation Protection; Ingolstädter Landstraße 1 D-85764 Oberschleissheim Germany
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18
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Bignotti B, Signori A, Valdora F, Rossi F, Calabrese M, Durando M, Mariscotto G, Tagliafico A. Evaluation of background parenchymal enhancement on breast MRI: a systematic review. Br J Radiol 2017; 90:20160542. [PMID: 27925480 PMCID: PMC5685112 DOI: 10.1259/bjr.20160542] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2016] [Revised: 11/18/2016] [Accepted: 12/05/2016] [Indexed: 12/30/2022] Open
Abstract
OBJECTIVE To perform a systematic review of the methods used for background parenchymal enhancement (BPE) evaluation on breast MRI. METHODS Studies dealing with BPE assessment on breast MRI were retrieved from major medical libraries independently by four reviewers up to 6 October 2015. The keywords used for database searching are "background parenchymal enhancement", "parenchymal enhancement", "MRI" and "breast". The studies were included if qualitative and/or quantitative methods for BPE assessment were described. RESULTS Of the 420 studies identified, a total of 52 articles were included in the systematic review. 28 studies performed only a qualitative assessment of BPE, 13 studies performed only a quantitative assessment and 11 studies performed both qualitative and quantitative assessments. A wide heterogeneity was found in the MRI sequences and in the quantitative methods used for BPE assessment. CONCLUSION A wide variability exists in the quantitative evaluation of BPE on breast MRI. More studies focused on a reliable and comparable method for quantitative BPE assessment are needed. Advances in knowledge: More studies focused on a quantitative BPE assessment are needed.
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Affiliation(s)
- Bianca Bignotti
- Department of Health Sciences, Institute of Statistics, University of Genoa, Genoa, Italy
| | - Alessio Signori
- Department of Experimental Medicine, Institute of Anatomy, University of Genoa, Genoa, Italy
| | | | - Federica Rossi
- Department of Health Sciences, University of Genova, Genoa, Italy
| | - Massimo Calabrese
- IRCCS AOU San Martino - IST Istituto Nazionale per la Ricerca sul Cancro, Genova, Italy
| | - Manuela Durando
- Department of Diagnostic Imaging and Radiotherapy, AOU Città della Salute e della Scienza of Turin, Breast Imaging Service, Division of Radiology, University of Turin, Turin, Italy
| | - Giovanna Mariscotto
- Department of Diagnostic Imaging and Radiotherapy, AOU Città della Salute e della Scienza of Turin, Breast Imaging Service, Division of Radiology, University of Turin, Turin, Italy
| | - Alberto Tagliafico
- Department of Experimental Medicine, Institute of Anatomy, University of Genoa, Genoa, Italy
- IRCCS AOU San Martino - IST Istituto Nazionale per la Ricerca sul Cancro, Genova, Italy
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Nano-Magnetic Resonance Imaging (Nano-MRI) Gives Personalized Medicine a New Perspective. Biomedicines 2017; 5:biomedicines5010007. [PMID: 28536350 PMCID: PMC5423496 DOI: 10.3390/biomedicines5010007] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2016] [Revised: 01/02/2017] [Accepted: 01/22/2017] [Indexed: 11/16/2022] Open
Abstract
This paper reviews some of the major and most recent advances in nanoscale-magnetic resonance imaging (nano-MRI) for personalized medicine (PM). Nano-MRI may drastically expand the capabilities of the traditional magnetic resonance images (MRI), down to the nanometer scale and possibly, in the near future, at the atomic scale. Nano-MRI is potentially able to observe structures which cannot be seen using today's molecular imaging, with sensitivities of many billions of times better than MRI as currently used in hospitals, for example. The paper briefly reports on the foremost research themes in nano-MRI.
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20
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Hemmer E, Acosta-Mora P, Méndez-Ramos J, Fischer S. Optical nanoprobes for biomedical applications: shining a light on upconverting and near-infrared emitting nanoparticles for imaging, thermal sensing, and photodynamic therapy. J Mater Chem B 2017; 5:4365-4392. [DOI: 10.1039/c7tb00403f] [Citation(s) in RCA: 150] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Shining a light on spectrally converting lanthanide (Ln3+)-doped nanoparticles: progress, trends, and challenges in Ln3+-nanoprobes for near-infrared bioimaging, nanothermometry, and photodynamic therapy.
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Affiliation(s)
- E. Hemmer
- Department of Chemistry and Biomolecular Sciences
- University of Ottawa
- Ottawa (ON)
- Canada
| | - P. Acosta-Mora
- Departamento de Fíísica
- Universidad de La Laguna
- Tenerife
- Spain
| | - J. Méndez-Ramos
- Departamento de Fíísica
- Universidad de La Laguna
- Tenerife
- Spain
| | - S. Fischer
- Department of Materials Science and Engineering, University of California—Berkeley
- Berkeley
- USA
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21
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Schober O, Dössel O, Ermert H, Requardt H, Ziegler S, Adam G. [Imaging in clinic and research: contribution to individualized medicine?]. Nuklearmedizin 2017. [PMID: 29533421 DOI: 10.3413/2017-05-0002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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22
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Thrall JH. Trends and Developments Shaping the Future of Diagnostic Medical Imaging: 2015 Annual Oration in Diagnostic Radiology. Radiology 2016; 279:660-6. [PMID: 27183401 DOI: 10.1148/radiol.2016160293] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- James H Thrall
- From the Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 25 New Chardon St, Suite 400, Boston, MA 02114
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23
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Affiliation(s)
- Stella K Kang
- From the Departments of Radiology (S.K.K.), Population Health (S.K.K., R.S.B.), and Medicine (R.S.B.), NYU Langone Medical Center, 550 First Ave, New York, NY 10016; Center for Bioethics and Social Sciences in Medicine, Division of General Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich (A.F.); and VA Health Services Research and Development Center of Excellence, VA Ann Arbor Healthcare System, Ann Arbor, Mich (A.F.)
| | - Angela Fagerlin
- From the Departments of Radiology (S.K.K.), Population Health (S.K.K., R.S.B.), and Medicine (R.S.B.), NYU Langone Medical Center, 550 First Ave, New York, NY 10016; Center for Bioethics and Social Sciences in Medicine, Division of General Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich (A.F.); and VA Health Services Research and Development Center of Excellence, VA Ann Arbor Healthcare System, Ann Arbor, Mich (A.F.)
| | - R Scott Braithwaite
- From the Departments of Radiology (S.K.K.), Population Health (S.K.K., R.S.B.), and Medicine (R.S.B.), NYU Langone Medical Center, 550 First Ave, New York, NY 10016; Center for Bioethics and Social Sciences in Medicine, Division of General Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich (A.F.); and VA Health Services Research and Development Center of Excellence, VA Ann Arbor Healthcare System, Ann Arbor, Mich (A.F.)
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24
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The Role of Radiology in Personalized Medicine. Per Med 2016. [DOI: 10.1007/978-3-319-39349-0_10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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25
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Wáng YXJ, Idée JM, Corot C. Scientific and industrial challenges of developing nanoparticle-based theranostics and multiple-modality contrast agents for clinical application. NANOSCALE 2015; 7:16146-16150. [PMID: 26394746 DOI: 10.1039/c5nr03887a] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Designing of theranostics and dual or multi-modality contrast agents are currently two of the hottest topics in biotechnology and biomaterials science. However, for single entity theranostics, a right ratio of their diagnostic component and their therapeutic component may not always be realized in a composite suitable for clinical application. For dual/multiple modality molecular imaging agents, after in vivo administration, there is an optimal time window for imaging, when an agent is imaged by one modality, the pharmacokinetics of this agent may not allow imaging by another modality. Due to reticuloendothelial system clearance, efficient in vivo delivery of nanoparticles to the lesion site is sometimes difficult. The toxicity of these entities also remains poorly understood. While the medical need of theranostics is admitted, the business model remains to be established. There is an urgent need for a global and internationally harmonized re-evaluation of the approval and marketing processes of theranostics. However, a reasonable expectation exists that, in the near future, the current obstacles will be removed, thus allowing the wide use of these very promising agents.
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Affiliation(s)
- Yì Xiáng J Wáng
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong SAR, China.
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European Society of Radiology (ESR). ESR Position Paper on Imaging Biobanks. Insights Imaging 2015; 6:403-10. [PMID: 25999018 PMCID: PMC4519817 DOI: 10.1007/s13244-015-0409-x] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2015] [Accepted: 04/08/2015] [Indexed: 12/19/2022] Open
Abstract
In March 2014 the European Society of Radiology (ESR) established a dedicated working group (ESR WG on Imaging Biobanks) aimed at monitoring the existing imaging biobanks in Europe, promoting the federation of imaging biobanks and communication of their findings in a white paper. The WG provided the following statements: (1) Imaging biobanks can be defined as "organised databases of medical images and associated imaging biomarkers (radiology and beyond) shared among multiple researchers, and linked to other biorepositories". (2) The immediate purpose of imaging biobanks should be to allow the generation of imaging biomarkers for use in research studies and to support biological validation of existing and novel imaging biomarkers. (3) A long-term scope of imaging biobanks should be the creation of a network/federation of such repositories integrated with the already-existing biobanking network. The aim of the WG was to investigate the existence, consistency, geographical distribution and type of imaging biobanks in Europe. A survey among ESR members resulted in the identification of 27 imaging biobanks, mostly disease-oriented and designed for research and clinical reference. In 80 % access to imaging biobanks is restricted. Key points • Imaging biobanks are "shared databases of imaging biomarkers, linked to biorepositories".• Exploitation of traditional and imaging biobanks is meaningful for "personalised medicine".• A European imaging biobank network would significantly boost research in the imaging domain.
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27
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European Society of Radiology (ESR). The ESR Patient Advisory Group (ESR-PAG). Insights Imaging 2015; 6:167-71. [PMID: 25779591 PMCID: PMC4376811 DOI: 10.1007/s13244-015-0395-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2015] [Accepted: 02/02/2015] [Indexed: 11/25/2022] Open
Abstract
Abstract The European Society of Radiology (ESR) Patient Advisory Group addresses the issue of communication among radiologists, radiographers and their patients. Initiated in 2013, the group represents many patient groups, working together with the ESR to raise awareness of medical imaging amongst patients, improve patient knowledge about imaging procedures, liaise on policy issues of common interest, involve patient representatives in strategic decisions regarding medical imaging and ensure that a patient-centred, “human” approach is embedded in the structure of the ESR. The ESR strongly believes that close collaboration with patient organisations is beneficial for both stakeholders, helping radiologists to understand patients’ needs, to adapt their practice accordingly and to improve their communication skills. These factors are important to help radiologists find acknowledgement as clinicians and overcome the specialty’s poor visibility. Close collaboration with professionals will allow patients to obtain a better understanding of the work of everyone involved in a radiological department, of the advantages and limitations of imaging, and what to expect from a radiological examination or an imaging-guided interventional procedure. Thus, this collaborative effort is not simply limited to improving patient satisfaction; the ultimate goal is to enhance the faith and trust that patients place in the medical imaging profession and all the radiology professionals involved. Main messages • Good communication between patient and doctor is important for proper patient care. • The ESR Patient Advisory Group specifically addresses this communication issue. • The activities aim at developing a reciprocal relationship between radiologists/radiographers and patients. • Both radiologists/radiographers and patients need to be “educated” to improve communication.
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28
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European Society of Radiology (ESR). Medical imaging in personalised medicine: a white paper of the research committee of the European Society of Radiology (ESR). Insights Imaging 2015; 6:141-55. [PMID: 25763994 PMCID: PMC4376812 DOI: 10.1007/s13244-015-0394-0] [Citation(s) in RCA: 92] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2015] [Accepted: 02/02/2015] [Indexed: 02/06/2023] Open
Abstract
The future of medicine lies in early diagnosis and individually tailored treatments, a concept that has been designated 'personalised medicine' (PM), which aims to deliver the right treatment to the right patient at the right time. Medical imaging has always been personalised and is fundamental to almost all aspects of PM. It is instrumental in solving clinical differential diagnoses. Imaging procedures are tailored to the clinical problem and patient characteristics. Screening for preclinical disease is done with imaging. Stratification based on imaging biomarkers can help identify individuals suited for preventive intervention. Treatment decisions are based on the in vivo visualisation of the location and extent of an abnormality, as well as the loco-regional physiological, biochemical and biological processes using structural and molecular imaging. Image-guided biopsy provides relevant tissue specimens for genetic/molecular characterisation. In addition, radiogenomics relate imaging biomarkers to these genetic and molecular features. Furthermore, imaging is essential to patient-tailored therapy planning, therapy monitoring and follow-up of disease, as well as targeting non-invasive or minimally invasive treatments, especially with the rise of theranostics. Radiologists need to be prepared for this new paradigm as it will mean changes in training, clinical practice and in research. Key Points • Medical imaging is a key component in personalised medicine • Personalised prevention will rely on image-based screening programmes • Anatomical, functional and molecular imaging biomarkers affect decisions on the type and intensity of treatment • Treatment response assessment with imaging will improve personalised treatment • Image-based invasive intervention integrates personalised diagnosis and personalised treatment.
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29
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Agustí A, Antó JM, Auffray C, Barbé F, Barreiro E, Dorca J, Escarrabill J, Faner R, Furlong LI, Garcia-Aymerich J, Gea J, Lindmark B, Monsó E, Plaza V, Puhan MA, Roca J, Ruiz-Manzano J, Sampietro-Colom L, Sanz F, Serrano L, Sharpe J, Sibila O, Silverman EK, Sterk PJ, Sznajder JI. Personalized respiratory medicine: exploring the horizon, addressing the issues. Summary of a BRN-AJRCCM workshop held in Barcelona on June 12, 2014. Am J Respir Crit Care Med 2015; 191:391-401. [PMID: 25531178 PMCID: PMC4351599 DOI: 10.1164/rccm.201410-1935pp] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2014] [Accepted: 11/21/2014] [Indexed: 12/29/2022] Open
Abstract
This Pulmonary Perspective summarizes the content and main conclusions of an international workshop on personalized respiratory medicine coorganized by the Barcelona Respiratory Network ( www.brn.cat ) and the AJRCCM in June 2014. It discusses (1) its definition and historical, social, legal, and ethical aspects; (2) the view from different disciplines, including basic science, epidemiology, bioinformatics, and network/systems medicine; (3) the bottlenecks and opportunities identified by some currently ongoing projects; and (4) the implications for the individual, the healthcare system and the pharmaceutical industry. The authors hope that, although it is not a systematic review on the subject, this document can be a useful reference for researchers, clinicians, healthcare managers, policy-makers, and industry parties interested in personalized respiratory medicine.
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Affiliation(s)
- Alvar Agustí
- Hospital Clinic, Institut d'Investigacions Biomèdiques August Pi i Sunyer, University Barcelona, Spain
- Centro de Investigación Biomédica en Red Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - Josep Maria Antó
- Centre for Research in Environmental Epidemiology, Hospital del Mar Medical Research Institute, Universitat Pompeu Fabra, Centros de Investigación Biomédica en Red Epidemiología y Salud Pública, Barcelona, Spain
| | - Charles Auffray
- European Institute for Systems Biology and Medicine, Lyon, France
| | - Ferran Barbé
- Centro de Investigación Biomédica en Red Enfermedades Respiratorias (CIBERES), Madrid, Spain
- Institut de Recerca Biomèdica de Lleida, Lleida, Spain
| | - Esther Barreiro
- Centro de Investigación Biomédica en Red Enfermedades Respiratorias (CIBERES), Madrid, Spain
- Pulmonology Department, Hospital del Mar-Hospital del Mar Medical Research Institute, CEXS, Universitat Pompeu Fabra, Barcelona Biomedical Research Park, Barcelona, Spain
| | - Jordi Dorca
- Centro de Investigación Biomédica en Red Enfermedades Respiratorias (CIBERES), Madrid, Spain
- Hospital University Bellvitge, University Barcelona, El Institut d’Investigació Biomèdica de Bellvitge, Hospitalet Ll., Spain
| | - Joan Escarrabill
- Hospital Clinic, Institut d'Investigacions Biomèdiques August Pi i Sunyer, University Barcelona, Spain
| | - Rosa Faner
- Hospital Clinic, Institut d'Investigacions Biomèdiques August Pi i Sunyer, University Barcelona, Spain
- Centro de Investigación Biomédica en Red Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - Laura I. Furlong
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute, University Pompeu Fabra, Barcelona, Spain
| | - Judith Garcia-Aymerich
- Centre for Research in Environmental Epidemiology, Hospital del Mar Medical Research Institute, Universitat Pompeu Fabra, Centros de Investigación Biomédica en Red Epidemiología y Salud Pública, Barcelona, Spain
| | - Joaquim Gea
- Centro de Investigación Biomédica en Red Enfermedades Respiratorias (CIBERES), Madrid, Spain
- Pulmonology Department, Hospital del Mar-Hospital del Mar Medical Research Institute, CEXS, Universitat Pompeu Fabra, Barcelona Biomedical Research Park, Barcelona, Spain
| | | | - Eduard Monsó
- Centro de Investigación Biomédica en Red Enfermedades Respiratorias (CIBERES), Madrid, Spain
- Hospital University Parc Taulí, Sabadell, Spain
| | - Vicente Plaza
- Hospital de la Santa Creu i Sant Pau, IIB Sant Pau, University Autonoma de Barcelona, Barcelona, Spain
| | - Milo A. Puhan
- Epidemiology, Biostatistics & Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Josep Roca
- Hospital Clinic, Institut d'Investigacions Biomèdiques August Pi i Sunyer, University Barcelona, Spain
- Centro de Investigación Biomédica en Red Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - Juan Ruiz-Manzano
- Centro de Investigación Biomédica en Red Enfermedades Respiratorias (CIBERES), Madrid, Spain
- Hospital University Germans Trias i Pujol, University Autónoma Barcelona, Badalona, Spain
| | - Laura Sampietro-Colom
- Hospital Clinic, Institut d'Investigacions Biomèdiques August Pi i Sunyer, University Barcelona, Spain
| | - Ferran Sanz
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute, University Pompeu Fabra, Barcelona, Spain
| | - Luis Serrano
- European Molecular Biology Laboratory/Centre for Genomic Regulation Systems Biology Research Unit, Centre for Genomic Regulation, Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain
| | - James Sharpe
- European Molecular Biology Laboratory/Centre for Genomic Regulation Systems Biology Research Unit, Centre for Genomic Regulation, Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain
| | - Oriol Sibila
- Hospital de la Santa Creu i Sant Pau, IIB Sant Pau, University Autonoma de Barcelona, Barcelona, Spain
| | - Edwin K. Silverman
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Peter J. Sterk
- Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands; and
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Abstract
In view of the trend towards personalized treatment strategies for (cancer) patients, there is an increasing need to noninvasively determine individual patient characteristics. Such information enables physicians to administer to patients accurate therapy with appropriate timing. For the noninvasive visualization of disease-related features, imaging biomarkers are expected to play a crucial role. Next to the chemical development of imaging probes, this requires preclinical studies in animal tumour models. These studies provide proof-of-concept of imaging biomarkers and help determine the pharmacokinetics and target specificity of relevant imaging probes, features that provide the fundamentals for translation to the clinic. In this review we describe biological processes derived from the “hallmarks of cancer” that may serve as imaging biomarkers for diagnostic, prognostic and treatment response monitoring that are currently being studied in the preclinical setting. A number of these biomarkers are also being used for the initial preclinical assessment of new intervention strategies. Uniquely, noninvasive imaging approaches allow longitudinal assessment of changes in biological processes, providing information on the safety, pharmacokinetic profiles and target specificity of new drugs, and on the antitumour effectiveness of therapeutic interventions. Preclinical biomarker imaging can help guide translation to optimize clinical biomarker imaging and personalize (combination) therapies.
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Polivka J, Polivka J, Karlikova M, Topolcan O. Pre-graduate and post-graduate education in personalized medicine in the Czech Republic: statistics, analysis and recommendations. EPMA J 2014; 5:22. [PMID: 25904992 PMCID: PMC4406177 DOI: 10.1186/1878-5085-5-22] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2014] [Accepted: 11/17/2014] [Indexed: 11/10/2022]
Abstract
The main goal of personalized medicine is the individualized approach to the patient's treatment. It could be achieved only by the integration of the complexity of novel findings in diverse "omics" disciplines, new methods of medical imaging, as well as implementation of reliable biomarkers into the medical care. The implementation of personalized medicine into clinical practice is dependent on the adaptation of pre-graduate and post-graduate medical education to these principles. The situation in the education of personalized medicine in the Czech Republic is analyzed together with novel educational tools that are currently established in our country. The EPMA representatives in the Czech Republic in cooperation with the working group of professionals at the Faculty of Medicine in Pilsen, Charles University in Prague have implemented the survey of personalized medicine awareness among students of Faculty of Medicine in Pilsen-the "Personalized Medicine Questionnaire". The results showed lacking knowledge of personalized medicine principles and students' will of education in this domain. Therefore, several educational activities addressed particularly to medical students and young physicians were realized at our facility with very positive evaluation. These educational activities (conferences, workshops, seminars, e-learning and special courses in personalized medicine (PM)) will be a part of pre-graduate and post-graduate medical education, will be extended to other medical faculties in our country. The "Summer School of Personalized Medicine in Plzen 2015" will be organized at the Faculty of Medicine and Faculty Hospital in Pilsen as the first event on this topic in the Czech Republic.
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Affiliation(s)
- Jiri Polivka
- />Department of Histology and Embryology, Faculty of Medicine in Pilsen, Charles University in Prague, Husova 3, Pilsen, 301 66 Czech Republic
- />Biomedical Centre, Faculty of Medicine in Pilsen, Charles University in Prague, Husova 3, Pilsen, 301 66 Czech Republic
| | - Jiri Polivka
- />Department of Neurology, Faculty of Medicine in Pilsen, Charles University in Prague and Faculty Hospital in Pilsen, alej Svobody 80, Pilsen, 304 60 Czech Republic
| | - Marie Karlikova
- />Faculty Hospital in Pilsen, Central Immunoanalytical Laboratory, alej Svobody 80, Pilsen, 304 60 Czech Republic
| | - Ondrej Topolcan
- />Faculty Hospital in Pilsen, Central Immunoanalytical Laboratory, alej Svobody 80, Pilsen, 304 60 Czech Republic
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Quattrocchi CC, Giona A, Di Martino AC, Errante Y, Scarciolla L, Mallio CA, Denaro V, Zobel BB. Extra-spinal incidental findings at lumbar spine MRI in the general population: a large cohort study. Insights Imaging 2013; 4:301-8. [PMID: 23456750 PMCID: PMC3675253 DOI: 10.1007/s13244-013-0234-z] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2013] [Revised: 02/09/2013] [Accepted: 02/11/2013] [Indexed: 11/24/2022] Open
Abstract
OBJECTIVE To determine the prevalence of clinically and non-clinically relevant extra-spinal incidental findings (IF) in patients undergoing magnetic resonance imaging (MRI) of the lumbar spine and to evaluate the rate of undetected findings in archived radiological reports. METHODS A retrospective search of patients undergoing lumbar spine MRI from January 2006 to December 2010 was conducted. By means of randomisation, we retrospectively reviewed 3,000 lumbar spine MRI examinations. Extra-spinal abnormalities were classified according to a modified CT Colonography Reporting and Data System (C-RADS). We retrospectively compared our structured approach with the archived MRI reports as it regarded the detection of extra-spinal IF to estimate non-detection rates. RESULTS By means of the structured approach used, extra-spinal findings were detected in 2,060 (68.6 %) of the 3,000 lumbar spine MRI examinations; 362 (17.6 %) patients had indeterminate or clinically important findings (E3 and E4) requiring clinical correlation or further evaluation. After review of the original archived radiological reports, potentially important C-RADS E3 and E4 extra-spinal IF were respectively reported in 47 of the 265 (17.7 %) and in 8 of 74 (10.8 %) patients. CONCLUSIONS Our study shows that incidental extra-spinal findings at conventional lumbar spine MRI are common but underestimated in radiological reports.
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Affiliation(s)
- Carlo Cosimo Quattrocchi
- Diagnostic Imaging, Università Campus Bio-Medico di Roma, via Alvaro del Portillo, 21, 00128, Rome, Italy,
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Comley RA, Kallend D. Imaging in the cardiovascular and metabolic disease area. Drug Discov Today 2013; 18:185-92. [DOI: 10.1016/j.drudis.2012.09.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2012] [Revised: 09/14/2012] [Accepted: 09/24/2012] [Indexed: 01/09/2023]
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