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Bortolotto C, Pinto A, Brero F, Messana G, Cabini RF, Postuma I, Robustelli Test A, Stella GM, Galli G, Mariani M, Figini S, Lascialfari A, Filippi AR, Bottinelli OM, Preda L. CT and MRI radiomic features of lung cancer (NSCLC): comparison and software consistency. Eur Radiol Exp 2024; 8:71. [PMID: 38880866 PMCID: PMC11180643 DOI: 10.1186/s41747-024-00468-8] [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: 01/31/2024] [Accepted: 04/10/2024] [Indexed: 06/18/2024] Open
Abstract
BACKGROUND Radiomics is a quantitative approach that allows the extraction of mineable data from medical images. Despite the growing clinical interest, radiomics studies are affected by variability stemming from analysis choices. We aimed to investigate the agreement between two open-source radiomics software for both contrast-enhanced computed tomography (CT) and contrast-enhanced magnetic resonance imaging (MRI) of lung cancers and to preliminarily evaluate the existence of radiomic features stable for both techniques. METHODS Contrast-enhanced CT and MRI images of 35 patients affected with non-small cell lung cancer (NSCLC) were manually segmented and preprocessed using three different methods. Sixty-six Image Biomarker Standardisation Initiative-compliant features common to the considered platforms, PyRadiomics and LIFEx, were extracted. The correlation among features with the same mathematical definition was analyzed by comparing PyRadiomics and LIFEx (at fixed imaging technique), and MRI with CT results (for the same software). RESULTS When assessing the agreement between LIFEx and PyRadiomics across the considered resampling, the maximum statistically significant correlations were observed to be 94% for CT features and 95% for MRI ones. When examining the correlation between features extracted from contrast-enhanced CT and MRI using the same software, higher significant correspondences were identified in 11% of features for both software. CONCLUSIONS Considering NSCLC, (i) for both imaging techniques, LIFEx and PyRadiomics agreed on average for 90% of features, with MRI being more affected by resampling and (ii) CT and MRI contained mostly non-redundant information, but there are shape features and, more importantly, texture features that can be singled out by both techniques. RELEVANCE STATEMENT Identifying and selecting features that are stable cross-modalities may be one of the strategies to pave the way for radiomics clinical translation. KEY POINTS • More than 90% of LIFEx and PyRadiomics features contain the same information. • Ten percent of features (shape, texture) are stable among contrast-enhanced CT and MRI. • Software compliance and cross-modalities stability features are impacted by the resampling method.
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Affiliation(s)
- Chandra Bortolotto
- Radiology Institute, Fondazione IRCCS Policlinico San Matteo, Pavia, 27100, Italy
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, Pavia, 27100, Italy
| | - Alessandra Pinto
- Radiology Institute, Fondazione IRCCS Policlinico San Matteo, Pavia, 27100, Italy.
| | - Francesca Brero
- Department of Physics, University of Pavia, Via Bassi 6, Pavia, 27100, Italy
- Istituto Nazionale Di Fisica Nucleare, Sezione Di Pavia, Pavia, 27100, Italy
| | - Gaia Messana
- Radiology Institute, Fondazione IRCCS Policlinico San Matteo, Pavia, 27100, Italy
| | - Raffaella Fiamma Cabini
- Istituto Nazionale Di Fisica Nucleare, Sezione Di Pavia, Pavia, 27100, Italy.
- Department of Mathematics, University of Pavia, Via Ferrata 5, Pavia, 27100, Italy.
| | - Ian Postuma
- Istituto Nazionale Di Fisica Nucleare, Sezione Di Pavia, Pavia, 27100, Italy
| | - Agnese Robustelli Test
- Department of Physics, University of Pavia, Via Bassi 6, Pavia, 27100, Italy.
- Istituto Nazionale Di Fisica Nucleare, Sezione Di Pavia, Pavia, 27100, Italy.
| | - Giulia Maria Stella
- Department of Medical Sciences and Infective Diseases, Unit of Respiratory Diseases, Fondazione IRCCS Policlinico San Matteo, Pavia, 27100, Italy
- Department of Internal Medicine and Medical Therapeutics, University of Pavia, Pavia, 27100, Italy
| | - Giulia Galli
- Department of Medical Sciences and Infective Diseases, Unit of Respiratory Diseases, Fondazione IRCCS Policlinico San Matteo, Pavia, 27100, Italy
- Department of Internal Medicine and Medical Therapeutics, University of Pavia, Pavia, 27100, Italy
| | - Manuel Mariani
- Department of Physics, University of Pavia, Via Bassi 6, Pavia, 27100, Italy
| | - Silvia Figini
- Department of Political and Social Sciences, University of Pavia, Pavia, 27100, Italy
| | - Alessandro Lascialfari
- Department of Physics, University of Pavia, Via Bassi 6, Pavia, 27100, Italy
- Istituto Nazionale Di Fisica Nucleare, Sezione Di Pavia, Pavia, 27100, Italy
| | - Andrea Riccardo Filippi
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, Pavia, 27100, Italy
- Department of Radiation Oncology, Fondazione IRCCS Policlinico San Matteo, Pavia, 27100, Italy
| | - Olivia Maria Bottinelli
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, Pavia, 27100, Italy
| | - Lorenzo Preda
- Radiology Institute, Fondazione IRCCS Policlinico San Matteo, Pavia, 27100, Italy
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, Pavia, 27100, Italy
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Miles G, Quinlan A. Improving Time to Angioembolization for Trauma Care: Novel Smartphone Application. J Trauma Nurs 2024; 31:115-120. [PMID: 38484168 DOI: 10.1097/jtn.0000000000000769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
BACKGROUND Timely angiographic embolization of abdominopelvic injuries is a hallmark of a high-functioning trauma center. Yet, the process depends on the timely mobilization of interventional radiology staff. Smartphone technology to notify and mobilize staff may be a viable option. OBJECTIVE To describe the incorporation of a smartphone application into our trauma workflow process previously developed for stroke care. METHODS In 2022, our Level I trauma center implemented a smartphone application with three simultaneously occurring functions: (a) high-definition image viewing on the phone; (b) text messaging thread for all parties; and (c) a single-call activation system for staff mobilization. The application was initially developed to notify interventional radiologists of large-vessel occlusions in victims of stroke and, at our request, was modified to fit our trauma workflow process. The smartphone application company developed a new program, installed the application on trauma service smartphones, and provided educational in-services over a 1-month period. The application was then integrated into our trauma workflow process. RESULTS The trauma surgeon and the interventional radiologist can now simultaneously view high-definition images on their smartphones. Text messages are accessible to all team members. The staff is notified and mobilized with the singlecall smartphone application, preventing the placing and returning of phone calls. CONCLUSION Smartphone technology enhances timely interventional radiology staff response for hemorrhagic patients requiring emergent angioembolization.
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Affiliation(s)
- Gayla Miles
- Author Affiliation: Texas Health Harris Methodist Ft. Worth Hospital, Ft. Worth
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Bajaj S, Khunte M, Moily NS, Payabvash S, Wintermark M, Gandhi D, Malhotra A. Value Proposition of FDA-Approved Artificial Intelligence Algorithms for Neuroimaging. J Am Coll Radiol 2023; 20:1241-1249. [PMID: 37574094 DOI: 10.1016/j.jacr.2023.06.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 06/21/2023] [Accepted: 06/30/2023] [Indexed: 08/15/2023]
Abstract
PURPOSE The number of FDA-cleared artificial intelligence (AI) algorithms for neuroimaging has grown in the past decade. The adoption of these algorithms into clinical practice depends largely on whether this technology provides value in the clinical setting. The objective of this study was to analyze trends in FDA-cleared AI algorithms for neuroimaging and understand their value proposition as advertised by the AI developers and vendors. METHODS A list of AI algorithms cleared by the FDA for neuroimaging between May 2008 and August 2022 was extracted from the ACR Data Science Institute AI Central database. Product information for each device was collected from the database. For each device, information on the advertised value as presented on the developer's website was collected. RESULTS A total of 59 AI neuroimaging algorithms were cleared by the FDA between May 2008 and August 2022. Most of these algorithms (24 of 59) were compatible with noncontrast CT, 21 with MRI, 9 with CT perfusion, 8 with CT angiography, 3 with MR perfusion, and 2 with PET. Six algorithms were compatible with multiple imaging techniques. Of the 59 algorithms, websites were located that discussed the product value for 55 algorithms. The most widely advertised value proposition was improved quality of care (38 of 55 [69.1%]). A total of 24 algorithms (43.6%) proposed saving user time, 9 (15.7%) advertised decreased costs, and 6 (10.9%) described increased revenue. Product websites for 26 algorithms (43.6%) showed user testimonials advertising the value of the technology. CONCLUSIONS The results of this study indicate a wide range of value propositions advertised by developers and vendors of AI algorithms for neuroimaging. Most vendors advertised that their products would improve patient care. Further research is necessary to determine whether the value claimed by developers is actually demonstrated in clinical practice.
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Affiliation(s)
- Suryansh Bajaj
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - Mihir Khunte
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | | | - Seyedmehdi Payabvash
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - Max Wintermark
- Chair, Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Dheeraj Gandhi
- Director, Interventional Neuroradiology, University of Maryland School of Medicine, Baltimore, Maryland
| | - Ajay Malhotra
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut.
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4
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Henning MK, Gunn C, Arenas-Jiménez J, Johansen S. Strategies for calculating contrast media dose for chest CT. Eur Radiol Exp 2023; 7:29. [PMID: 37303003 DOI: 10.1186/s41747-023-00345-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 04/13/2023] [Indexed: 06/13/2023] Open
Abstract
BACKGROUND Total body weight (TBW) is a frequently used contrast media (CM) strategy for dose calculation in enhanced CT, yet it is suboptimal as it lacks consideration of patient characteristics, such as body fat percentage (BFP) and muscle mass. Alternative CM dosage strategies are suggested by the literature. Our objectives were to analyze the CM dose impact when adjusting to body composition using methods of obtaining lean body mass (LBM) and body surface area (BSA) along with its correlation with demographic factors in contrast enhanced chest CT examinations. METHODS Eighty-nine adult patients referred for CM thoracic CT were retrospectively included, categorized as either normal, muscular, or overweight. Patient body composition data was used to calculate the CM dose according to LBM or BSA. LBM was calculated with the James method, Boer method, and bioelectric impedance (BIA). BSA was calculated using the Mostellar formula. We then correlated the corresponding CM doses with demographic factors. RESULTS BIA demonstrated the highest and lowest calculated CM dose in muscular and overweight groups respectively, compared to other strategies. For the normal group, the lowest calculated CM dose was achieved using TBW. The calculated CM dose was more closely correlated with BFP using the BIA method. CONCLUSIONS The BIA method is more adaptive to variations in patient body habitus especially in muscular and overweight patients and is most closely correlated to patient demographics. This study could support utilizing the BIA method for calculating LBM for a body-tailored CM dose protocol for enhanced chest CT examinations. RELEVANCE STATEMENT The BIA-based method is adaptive to variations in body habitus especially in muscular and overweight patients and is closely correlated to patient demographics for contrast-enhanced chest CT. KEY POINTS • Calculations based on BIA showed the largest variation in CM dose. • Lean body weight using BIA demonstrated the strongest correlation to patient demographics. • Lean body weight BIA protocol may be considered for CM dosing in chest CT.
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Affiliation(s)
- Mette Karen Henning
- Faculty of Health Sciences, Department of Life Sciences and Health, Oslo Metropolitan University, Oslo, Norway
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Catherine Gunn
- School of Health Sciences, Dalhousie University, Halifax, Canada
| | - Juan Arenas-Jiménez
- Department of Radiology, Dr. Balmis General University Hospital, Alicante, Spain
- Department of Pathology and Surgery, Miguel Hernández University, Alicante, Spain
- Alicante Institute for Health and Biomedical Research (ISABIAL), Alicante, Spain
| | - Safora Johansen
- Faculty of Health Sciences, Department of Life Sciences and Health, Oslo Metropolitan University, Oslo, Norway.
- Department of Cancer Treatment, Oslo University Hospital, Oslo, Norway.
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Bisson T, Franz M, Dogan O I, Romberg D, Jansen C, Hufnagl P, Zerbe N. Anonymization of whole slide images in histopathology for research and education. Digit Health 2023; 9:20552076231171475. [PMID: 37205164 PMCID: PMC10185865 DOI: 10.1177/20552076231171475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 04/06/2023] [Indexed: 05/21/2023] Open
Abstract
Objective The exchange of health-related data is subject to regional laws and regulations, such as the General Data Protection Regulation (GDPR) in the EU or the Health Insurance Portability and Accountability Act (HIPAA) in the United States, resulting in non-trivial challenges for researchers and educators when working with these data. In pathology, the digitization of diagnostic tissue samples inevitably generates identifying data that can consist of sensitive but also acquisition-related information stored in vendor-specific file formats. Distribution and off-clinical use of these Whole Slide Images (WSIs) are usually done in these formats, as an industry-wide standardization such as DICOM is yet only tentatively adopted and slide scanner vendors currently do not provide anonymization functionality. Methods We developed a guideline for the proper handling of histopathological image data particularly for research and education with regard to the GDPR. In this context, we evaluated existing anonymization methods and examined proprietary format specifications to identify all sensitive information for the most common WSI formats. This work results in a software library that enables GDPR-compliant anonymization of WSIs while preserving the native formats. Results Based on the analysis of proprietary formats, all occurrences of sensitive information were identified for file formats frequently used in clinical routine, and finally, an open-source programming library with an executable CLI tool and wrappers for different programming languages was developed. Conclusions Our analysis showed that there is no straightforward software solution to anonymize WSIs in a GDPR-compliant way while maintaining the data format. We closed this gap with our extensible open-source library that works instantaneously and offline.
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Affiliation(s)
- Tom Bisson
- Institute of Pathology, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Michael Franz
- Institute of Pathology, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Isil Dogan O
- Institute of Pathology, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Daniel Romberg
- Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany
| | - Christoph Jansen
- Institute of Pathology, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Peter Hufnagl
- Institute of Pathology, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Centrum für Biomedizinische Bild- und Informationsverarbeitung (CBMI), University of Applied Sciences (HTW) Berlin, Berlin, Germany
| | - Norman Zerbe
- Institute of Pathology, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
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6
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The potential of predictive and prognostic breast MRI (P2-bMRI). Eur Radiol Exp 2022; 6:42. [PMID: 35989400 PMCID: PMC9393116 DOI: 10.1186/s41747-022-00291-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 06/08/2022] [Indexed: 11/10/2022] Open
Abstract
Magnetic resonance imaging (MRI) is an important part of breast cancer diagnosis and multimodal workup. It provides unsurpassed soft tissue contrast to analyse the underlying pathophysiology, and it is adopted for a variety of clinical indications. Predictive and prognostic breast MRI (P2-bMRI) is an emerging application next to these indications. The general objective of P2-bMRI is to provide predictive and/or prognostic biomarkers in order to support personalisation of breast cancer treatment. We believe P2-bMRI has a great clinical potential, thanks to the in vivo examination of the whole tumour and of the surrounding tissue, establishing a link between pathophysiology and response to therapy (prediction) as well as patient outcome (prognostication). The tools used for P2-bMRI cover a wide spectrum: standard and advanced multiparametric pulse sequences; structured reporting criteria (for instance BI-RADS descriptors); artificial intelligence methods, including machine learning (with emphasis on radiomics data analysis); and deep learning that have shown compelling potential for this purpose. P2-bMRI reuses the imaging data of examinations performed in the current practice. Accordingly, P2-bMRI could optimise clinical workflow, enabling cost savings and ultimately improving personalisation of treatment. This review introduces the concept of P2-bMRI, focusing on the clinical application of P2-bMRI by using semantic criteria.
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Bockhold S, Foley SJ, Rainford LA, Corridori R, Eberstein A, Hoeschen C, Konijnenberg MW, Molyneux-Hodgson S, Paulo G, Santos J, McNulty JP. Exploring the translational challenge for medical applications of ionising radiation and corresponding radiation protection research. J Transl Med 2022; 20:137. [PMID: 35303930 PMCID: PMC8932076 DOI: 10.1186/s12967-022-03344-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 03/06/2022] [Indexed: 01/19/2023] Open
Abstract
Background Medical applications of ionising radiation and associated radiation protection research often encounter long delays and inconsistent implementation when translated into clinical practice. A coordinated effort is needed to analyse the research needs for innovation transfer in radiation-based high-quality healthcare across Europe which can inform the development of an innovation transfer framework tailored for equitable implementation of radiation research at scale. Methods Between March and September 2021 a Delphi methodology was employed to gain consensus on key translational challenges from a range of professional stakeholders. A total of three Delphi rounds were conducted using a series of electronic surveys comprised of open-ended and closed-type questions. The surveys were disseminated via the EURAMED Rocc-n-Roll consortium network and prominent medical societies in the field. Approximately 350 professionals were invited to participate. Participants’ level of agreement with each generated statement was captured using a 6-point Likert scale. Consensus was defined as median ≥ 4 with ≥ 60% of responses in the upper tertile of the scale. Additionally, the stability of responses across rounds was assessed. Results In the first Delphi round a multidisciplinary panel of 20 generated 127 unique statements. The second and third Delphi rounds recruited a broader sample of 130 individuals to rate the extent to which they agreed with each statement as a key translational challenge. A total of 60 consensus statements resulted from the iterative Delphi process of which 55 demonstrated good stability. Ten statements were identified as high priority challenges with ≥ 80% of statement ratings either ‘Agree’ or ‘Strongly Agree’. Conclusion A lack of interoperability between systems, insufficient resources, unsatisfactory education and training, and the need for greater public awareness surrounding the benefits, risks, and applications of ionising radiation were identified as principal translational challenges. These findings will help to inform a tailored innovation transfer framework for medical radiation research. Supplementary Information The online version contains supplementary material available at 10.1186/s12967-022-03344-4.
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Affiliation(s)
- Sophie Bockhold
- Radiography and Diagnostic Imaging, School of Medicine, University College Dublin, Belfield, Dublin 4, Ireland.
| | - Shane J Foley
- Radiography and Diagnostic Imaging, School of Medicine, University College Dublin, Belfield, Dublin 4, Ireland
| | - Louise A Rainford
- Radiography and Diagnostic Imaging, School of Medicine, University College Dublin, Belfield, Dublin 4, Ireland
| | | | | | - Christoph Hoeschen
- Institute of Medical Engineering, Otto Von Guericke Universität Magdeburg, Magdeburg, Germany
| | - Mark W Konijnenberg
- Department of Radiology and Nuclear Medicine, Erasmus Medical Centre, Rotterdam, Netherlands
| | | | - Graciano Paulo
- Escola Superior de Tecnologia da Saúde, Instituto Politécnico de Coimbra, Coimbra, Portugal
| | - Joana Santos
- Escola Superior de Tecnologia da Saúde, Instituto Politécnico de Coimbra, Coimbra, Portugal
| | - Jonathan P McNulty
- Radiography and Diagnostic Imaging, School of Medicine, University College Dublin, Belfield, Dublin 4, Ireland
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Coppola A, Zorzetto G, Piacentino F, Bettoni V, Pastore I, Marra P, Perani L, Esposito A, De Cobelli F, Carcano G, Fontana F, Fiorina P, Venturini M. Imaging in experimental models of diabetes. Acta Diabetol 2022; 59:147-161. [PMID: 34779949 DOI: 10.1007/s00592-021-01826-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 10/30/2021] [Indexed: 12/01/2022]
Abstract
Translational medicine, experimental medicine and experimental animal models, in particular mice and rats, represent a multidisciplinary field that has made it possible to achieve, in the last decades, important scientific progress. In this review, we have summarized the most frequently used imaging animal models, such as ultrasound (US), micro-CT, MRI and the optical imaging methods, and their main implications in diagnostic and therapeutic fields, with a particular focus on diabetes mellitus, a multifactorial disease extremely widespread among the general population.
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Affiliation(s)
- Andrea Coppola
- Diagnostic and Interventional Radiology Unit, ASST Settelaghi, Varese, Italy.
| | | | - Filippo Piacentino
- Diagnostic and Interventional Radiology Unit, ASST Settelaghi, Varese, Italy
- Insubria University, Varese, Italy
| | - Valeria Bettoni
- Diagnostic and Interventional Radiology Unit, ASST Settelaghi, Varese, Italy
| | - Ida Pastore
- Division of Endocrinology, ASST Fatebenefratelli-Sacco, Milan, Italy
| | - Paolo Marra
- Department of Diagnostic Radiology, Giovanni XXIII Hospital, Milano-Bicocca University, Bergamo, Italy
| | - Laura Perani
- Experimental Imaging Center, San Raffaele Scientific Institute, Milan, Italy
| | - Antonio Esposito
- Experimental Imaging Center, San Raffaele Scientific Institute, Milan, Italy
- Radiology Unit, San Raffaele Scientific Institute, San Raffaele Vita-Salute University, Milan, Italy
| | - Francesco De Cobelli
- Radiology Unit, San Raffaele Scientific Institute, San Raffaele Vita-Salute University, Milan, Italy
| | - Giulio Carcano
- Insubria University, Varese, Italy
- General, Emergency, and Transplant Surgery Unit, ASST Settelaghi, Varese, Italy
| | - Federico Fontana
- Diagnostic and Interventional Radiology Unit, ASST Settelaghi, Varese, Italy
- Insubria University, Varese, Italy
| | - Paolo Fiorina
- International Center for T1D, Centro di Ricerca Pediatrica Romeo ed Enrica Invernizzi, Dipartimento di Scienze Biomediche e Cliniche "L. Sacco", Università di Milano, Milan, Italy
- Nephrology Division, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Endocrinology Division, ASST Fatebenefratelli Sacco, Milan, Italy
| | - Massimo Venturini
- Diagnostic and Interventional Radiology Unit, ASST Settelaghi, Varese, Italy
- Insubria University, Varese, Italy
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Castelló Cogollos L, Perez-Girbes A, Aleixandre-Benavent R, Valderrama-Zurián JC, Martí-Bonmatí L. Mapping the scientific research on radiology departments: Global trends in publication, collaboration and trending topics. Eur J Radiol 2021; 142:109841. [PMID: 34280595 DOI: 10.1016/j.ejrad.2021.109841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Revised: 06/21/2021] [Accepted: 06/28/2021] [Indexed: 11/18/2022]
Abstract
PURPOSE To characterize the global research trend in radiology departments based on bibliometric indicators. MATERIAL AND METHOD As a source of information, Science Citation Index Expanded and Journal Citation Reports from Web of Science Core Collection (WoSCC) were used. Annual trends, journals of publication, subject categories of journals, collaboration indexes between authors and institutions, network of cowords and most cited papers were identified and analysed. The period of study was 2009-2018. RESULTS 283,587 downloaded papers were analysed. The number of articles was increasing, as well as the percentage of funded works. Papers were published in 7314 different journals, being the most productive Plos One (5077), followed by American Journal of Roentgenology (4602) and European Radiology (3644). Most productive subject categories of journals were Radiology, Nuclear Medicine & Medical Imaging (86,568 papers), Clinical Neurology (29,722) and Surgery (23,564). International collaboration has increased more than 5 points, from 15.2% in 2009 to 20.7% in 2018. CONCLUSIONS Most cited articles were published in high impact journals outside the scope of diagnostic imaging. Most influential topics included technical innovations within imaging modalities. MRI replaced conventional radiography and CT as the imaging technique of choice in imaging research.
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Affiliation(s)
- Lourdes Castelló Cogollos
- Departament de Sociologia i Antropologia Social. Universitat de València, Valencia, Spain; UISYS, Universitat de València, Valencia, Spain
| | - Alexandre Perez-Girbes
- Grupo de Investigación Biomédica en Imagen, Hospital Universitario y Politécnico La Fe, Valencia, Spain.
| | - Rafael Aleixandre-Benavent
- UISYS, Universitat de València, Valencia, Spain; Instituto de Gestión de la Innovación y del Conocimiento-Ingenio (CSIC-Universitat Politècnica de València), Spain
| | - Juan Carlos Valderrama-Zurián
- UISYS, Universitat de València, Valencia, Spain; Departament de Història de la Ciència I Documentació. Universitat de València, Valencia, Spain
| | - Luis Martí-Bonmatí
- Grupo de Investigación Biomédica en Imagen, Hospital Universitario y Politécnico La Fe, Valencia, Spain
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Brady AP, Bello JA, Derchi LE, Fuchsjäger M, Goergen S, Krestin GP, Lee EJY, Levin DC, Pressacco J, Rao VM, Slavotinek J, Visser JJ, Walker REA, Brink JA. Radiology in the Era of Value-Based Healthcare: A Multi Society Expert Statement From the ACR, CAR, ESR, IS3R, RANZCR, and RSNA. J Am Coll Radiol 2021; 18:877-883. [PMID: 33358108 DOI: 10.1016/j.jacr.2020.12.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 12/02/2020] [Indexed: 01/08/2023]
Abstract
BACKGROUND The Value-Based Healthcare (VBH) concept is designed to improve individual healthcare outcomes without increasing expenditure, and is increasingly being used to determine resourcing of and reimbursement for medical services. Radiology is a major contributor to patient and societal healthcare at many levels. Despite this, some VBH models do not acknowledge radiology's central role; this may have future negative consequences for resource allocation. METHODS, FINDINGS AND INTERPRETATION This multi-society paper, representing the views of Radiology Societies in Europe, the USA, Canada, Australia, and New Zealand, describes the place of radiology in VBH models and the health-care value contributions of radiology. Potential steps to objectify and quantify the value contributed by radiology to healthcare are outlined.
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Affiliation(s)
- Adrian P Brady
- Mercy University Hospital, Cork, Ireland; European Society of Radiology (ESR), Vienna, Austria.
| | - Jaqueline A Bello
- Montefiore Medical Center, New York, New York; American College of Radiology (ACR), Reston, Virginia
| | - Lorenzo E Derchi
- University of Genoa, Genoa, Italy; European Society of Radiology (ESR), Vienna, Austria
| | - Michael Fuchsjäger
- Medical University Graz, Graz, Austria; European Society of Radiology (ESR), Vienna, Austria
| | - Stacy Goergen
- Monash University, Melbourne, Australia; Royal Australian and New Zealand College of Radiologists (RANZCR), Sydney, Australia
| | - Gabriel P Krestin
- Erasmus Medical Center, Rotterdam, the Netherlands; International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria
| | - Emil J Y Lee
- Langley Memorial Hospital, Langley, Canada; Canadian Association of Radiologists (CAR), Ottawa, Canada
| | - David C Levin
- Thomas Jefferson University, Philadelphia, Pennsylvania; Radiological Society of North America (RSNA), Oak Brook, Illinois
| | - Josephine Pressacco
- McGill University, Montreal, Canada; Canadian Association of Radiologists (CAR), Ottawa, Canada
| | - Vijay M Rao
- Thomas Jefferson University, Philadelphia, Pennsylvania; Radiological Society of North America (RSNA), Oak Brook, Illinois
| | - John Slavotinek
- Flinders Medical Centre and Flinders University, Adelaide, Australia; Royal Australian and New Zealand College of Radiologists (RANZCR), Sydney, Australia
| | - Jacob J Visser
- Erasmus Medical Center, Rotterdam, the Netherlands; International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria
| | - Richard E A Walker
- University of Calgary, Calgary, Canada; Canadian Association of Radiologists (CAR), Ottawa, Canada
| | - James A Brink
- Harvard Medical School, Boston, Massachusetts; American College of Radiology (ACR), Reston, Virginia; International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria
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11
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Iqbal MJ, Javed Z, Sadia H, Qureshi IA, Irshad A, Ahmed R, Malik K, Raza S, Abbas A, Pezzani R, Sharifi-Rad J. Clinical applications of artificial intelligence and machine learning in cancer diagnosis: looking into the future. Cancer Cell Int 2021; 21:270. [PMID: 34020642 PMCID: PMC8139146 DOI: 10.1186/s12935-021-01981-1] [Citation(s) in RCA: 64] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Accepted: 05/13/2021] [Indexed: 02/06/2023] Open
Abstract
Artificial intelligence (AI) is the use of mathematical algorithms to mimic human cognitive abilities and to address difficult healthcare challenges including complex biological abnormalities like cancer. The exponential growth of AI in the last decade is evidenced to be the potential platform for optimal decision-making by super-intelligence, where the human mind is limited to process huge data in a narrow time range. Cancer is a complex and multifaced disorder with thousands of genetic and epigenetic variations. AI-based algorithms hold great promise to pave the way to identify these genetic mutations and aberrant protein interactions at a very early stage. Modern biomedical research is also focused to bring AI technology to the clinics safely and ethically. AI-based assistance to pathologists and physicians could be the great leap forward towards prediction for disease risk, diagnosis, prognosis, and treatments. Clinical applications of AI and Machine Learning (ML) in cancer diagnosis and treatment are the future of medical guidance towards faster mapping of a new treatment for every individual. By using AI base system approach, researchers can collaborate in real-time and share knowledge digitally to potentially heal millions. In this review, we focused to present game-changing technology of the future in clinics, by connecting biology with Artificial Intelligence and explain how AI-based assistance help oncologist for precise treatment.
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Affiliation(s)
- Muhammad Javed Iqbal
- Department of Biotechnology, Faculty of Sciences, University of Sialkot, Sialkot, Pakistan
| | - Zeeshan Javed
- Office for Research Innovation and Commercialization (ORIC), Lahore Garrison University, Sector-C, DHA Phase-VI, Lahore, Pakistan
| | - Haleema Sadia
- Department of Biotechnology, Balochistan University of Information Technology Engineering and Management Sciences (BUITEMS), Quetta, Pakistan
| | | | - Asma Irshad
- Department of Life Sciences, University of Management Sciences and Technology, Lahore, Pakistan
| | - Rais Ahmed
- Department of Microbiology, Cholistan University of Veterinary and Animal Sciences, Bahawalpur, Pakistan
| | - Kausar Malik
- Center for Excellence in Molecular Biology, University of the Punjab, Lahore, Pakistan
| | - Shahid Raza
- Office for Research Innovation and Commercialization (ORIC), Lahore Garrison University, Sector-C, DHA Phase-VI, Lahore, Pakistan
| | - Asif Abbas
- Department of Biotechnology, Faculty of Sciences, University of Sialkot, Sialkot, Pakistan
| | - Raffaele Pezzani
- Dept. Medicine (DIMED), OU Endocrinology, University of Padova, via Ospedale 105, 35128 Padova, Italy
- AIROB, Associazione Italiana Per La Ricerca Oncologica Di Base, Padova, Italy
| | - Javad Sharifi-Rad
- Phytochemistry Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
- Facultad de Medicina, Universidad del Azuay, Cuenca, Ecuador
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12
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Birnbacher L, Braig EM, Pfeiffer D, Pfeiffer F, Herzen J. Quantitative X-ray phase contrast computed tomography with grating interferometry : Biomedical applications of quantitative X-ray grating-based phase contrast computed tomography. Eur J Nucl Med Mol Imaging 2021; 48:4171-4188. [PMID: 33846846 PMCID: PMC8566444 DOI: 10.1007/s00259-021-05259-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 02/11/2021] [Indexed: 11/25/2022]
Abstract
The ability of biomedical imaging data to be of quantitative nature is getting increasingly important with the ongoing developments in data science. In contrast to conventional attenuation-based X-ray imaging, grating-based phase contrast computed tomography (GBPC-CT) is a phase contrast micro-CT imaging technique that can provide high soft tissue contrast at high spatial resolution. While there is a variety of different phase contrast imaging techniques, GBPC-CT can be applied with laboratory X-ray sources and enables quantitative determination of electron density and effective atomic number. In this review article, we present quantitative GBPC-CT with the focus on biomedical applications.
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Affiliation(s)
- Lorenz Birnbacher
- Physics Department, Munich School of Bioengineering, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Eva-Maria Braig
- Physics Department, Munich School of Bioengineering, Technical University of Munich, Munich, Germany
| | - Daniela Pfeiffer
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Franz Pfeiffer
- Physics Department, Munich School of Bioengineering, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Julia Herzen
- Physics Department, Munich School of Bioengineering, Technical University of Munich, Munich, Germany.
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13
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Brady AP, Bello JA, Derchi LE, Fuchsjäger M, Goergen S, Krestin GP, Lee EJY, Levin DC, Pressacco J, Rao VM, Slavotinek J, Visser JJ, Walker REA, Brink JA. Radiology in the Era of Value-Based Healthcare: A Multi-Society Expert Statement From the ACR, CAR, ESR, IS3R, RANZCR, and RSNA. Can Assoc Radiol J 2020; 72:208-214. [PMID: 33345576 DOI: 10.1177/0846537120982567] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND The Value-Based Healthcare (VBH) concept is designed to improve individual healthcare outcomes without increasing expenditure, and is increasingly being used to determine resourcing of and reimbursement for medical services. Radiology is a major contributor to patient and societal healthcare at many levels. Despite this, some VBH models do not acknowledge radiology's central role; this may have future negative consequences for resource allocation. METHODS, FINDINGS AND INTERPRETATION This multi-society paper, representing the views of Radiology Societies in Europe, the USA, Canada, Australia, and New Zealand, describes the place of radiology in VBH models and the health-care value contributions of radiology. Potential steps to objectify and quantify the value contributed by radiology to healthcare are outlined.
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Affiliation(s)
- Adrian P Brady
- 36860Mercy University Hospital, Cork, Ireland.,European Society of Radiology (ESR), Vienna, Austria
| | - Jaqueline A Bello
- Montefiore Medical Center, New York, USA.,American College of Radiology (ACR), Reston, VA, USA
| | - Lorenzo E Derchi
- European Society of Radiology (ESR), Vienna, Austria.,University of Genoa, Italy
| | - Michael Fuchsjäger
- European Society of Radiology (ESR), Vienna, Austria.,Medical University Graz, Austria
| | - Stacy Goergen
- Monash University, Melbourne, Victoria, Australia.,Royal Australian and New Zealand College of Radiologists (RANZCR), Sydney, New South Wales, Australia
| | - Gabriel P Krestin
- 6993Erasmus Medical Center, Rotterdam, the Netherlands.,International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria
| | - Emil J Y Lee
- 60460Langley Memorial Hospital, British Columbia, Canada.,Canadian Association of Radiologists (CAR), Ottawa, Ontario, Canada
| | - David C Levin
- 6559Thomas Jefferson University, Philadelphia, PA, USA.,Radiological Society of North America (RSNA), Oak Brook, IL, USA
| | - Josephine Pressacco
- Canadian Association of Radiologists (CAR), Ottawa, Ontario, Canada.,5620McGill University, Montreal, Quebec, Canada
| | - Vijay M Rao
- 6559Thomas Jefferson University, Philadelphia, PA, USA.,Radiological Society of North America (RSNA), Oak Brook, IL, USA
| | - John Slavotinek
- Royal Australian and New Zealand College of Radiologists (RANZCR), Sydney, New South Wales, Australia.,14351Flinders Medical Centre and Flinders University, Adelaide, South Australia, Australia
| | - Jacob J Visser
- 6993Erasmus Medical Center, Rotterdam, the Netherlands.,International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria
| | - Richard E A Walker
- Canadian Association of Radiologists (CAR), Ottawa, Ontario, Canada.,2129University of Calgary, Alberta, Canada
| | - James A Brink
- American College of Radiology (ACR), Reston, VA, USA.,International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria.,1811Harvard Medical School, Boston, MA, USA
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14
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Brady AP, Bello JA, Derchi LE, Fuchsjäger M, Goergen S, Krestin GP, Lee EJY, Levin DC, Pressacco J, Rao VM, Slavotinek J, Visser JJ, Walker REA, Brink JA. Radiology in the era of value-based healthcare: a multi-society expert statement from the ACR, CAR, ESR, IS3R, RANZCR, and RSNA. Insights Imaging 2020; 11:136. [PMID: 33345287 PMCID: PMC7750384 DOI: 10.1186/s13244-020-00941-z] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
Background The Value-Based Healthcare (VBH) concept is designed to improve individual healthcare outcomes without increasing expenditure, and is increasingly being used to determine resourcing of and reimbursement for medical services. Radiology is a major contributor to patient and societal healthcare at many levels. Despite this, some VBH models do not acknowledge radiology’s central role; this may have future negative consequences for resource allocation. Methods, findings and interpretation This multi-society paper, representing the views of Radiology Societies in Europe, the USA, Canada, Australia, and New Zealand, describes the place of radiology in VBH models and the healthcare value contributions of radiology. Potential steps to objectify and quantify the value contributed by radiology to healthcare are outlined.
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Affiliation(s)
- Adrian P Brady
- Mercy University Hospital, Cork, Ireland. .,European Society of Radiology (ESR), Vienna, Austria.
| | - Jaqueline A Bello
- Montefiore Medical Center, New York, USA.,American College of Radiology (ACR), Reston, USA
| | - Lorenzo E Derchi
- University of Genoa, Genoa, Italy.,European Society of Radiology (ESR), Vienna, Austria
| | - Michael Fuchsjäger
- Medical University Graz, Graz, Austria.,European Society of Radiology (ESR), Vienna, Austria
| | - Stacy Goergen
- Monash University, Melbourne, Australia.,Royal Australian and New Zealand College of Radiologists (RANZCR), Sydney, Australia
| | - Gabriel P Krestin
- Erasmus Medical Center, Rotterdam, The Netherlands.,International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria
| | - Emil J Y Lee
- Langley Memorial Hospital, Langley, Canada.,Canadian Association of Radiologists (CAR), Ottawa, Canada
| | - David C Levin
- Thomas Jefferson University, Philadelphia, USA.,Radiological Society of North America (RSNA), Oak Brook, USA
| | - Josephine Pressacco
- McGill University, Montreal, Canada.,Canadian Association of Radiologists (CAR), Ottawa, Canada
| | - Vijay M Rao
- Thomas Jefferson University, Philadelphia, USA.,Radiological Society of North America (RSNA), Oak Brook, USA
| | - John Slavotinek
- Flinders Medical Centre and Flinders University, Adelaide, Australia.,Royal Australian and New Zealand College of Radiologists (RANZCR), Sydney, Australia
| | - Jacob J Visser
- Erasmus Medical Center, Rotterdam, The Netherlands.,International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria
| | - Richard E A Walker
- University of Calgary, Calgary, Canada.,Canadian Association of Radiologists (CAR), Ottawa, Canada
| | - James A Brink
- Harvard Medical School, Boston, USA.,American College of Radiology (ACR), Reston, USA.,International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria
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15
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Brady AP, Bello JA, Derchi LE, Fuchsjäger M, Goergen S, Krestin GP, Lee EJ, Levin DC, Pressacco J, Rao VM, Slavotinek J, Visser JJ, Walker RE, Brink JA. Radiology in the era of value-based healthcare: A multi-society expert statement from the ACR, CAR, ESR, IS3R, RANZCR and RSNA. J Med Imaging Radiat Oncol 2020; 65:60-66. [PMID: 33345440 DOI: 10.1111/1754-9485.13125] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND The value-based healthcare (VBH) concept is designed to improve individual healthcare outcomes without increasing expenditure and is increasingly being used to determine resourcing of and reimbursement for medical services. Radiology is a major contributor to patient and societal healthcare at many levels. Despite this, some VBH models do not acknowledge radiology's central role; this may have future negative consequences for resource allocation. METHODS, FINDINGS AND INTERPRETATION This multi-society paper, representing the views of Radiology Societies in Europe, the USA, Canada, Australia and New Zealand, describes the place of radiology in VBH models and the healthcare value contributions of radiology. Potential steps to objectify and quantify the value contributed by radiology to healthcare are outlined.
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Affiliation(s)
- Adrian P Brady
- Mercy University Hospital, Cork, Ireland.,European Society of Radiology (ESR), Vienna, Austria
| | - Jaqueline A Bello
- Montefiore Medical Center, New York, New York, USA.,American College of Radiology (ACR), Reston, Virginia, USA
| | - Lorenzo E Derchi
- European Society of Radiology (ESR), Vienna, Austria.,University of Genoa, Genoa, Italy
| | - Michael Fuchsjäger
- European Society of Radiology (ESR), Vienna, Austria.,Medical University Graz, Graz, Austria
| | - Stacy Goergen
- Monash University, Melbourne, Victoria, Australia.,Royal Australian and New Zealand College of Radiologists (RANZCR), Sydney, New South Wales, Australia
| | - Gabriel P Krestin
- Erasmus Medical Center, Rotterdam, The Netherlands.,International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria
| | - Emil Jy Lee
- Langley Memorial Hospital, Langley, British Columbia, Canada.,Canadian Association of Radiologists (CAR), Ottawa, Ontario, Canada
| | - David C Levin
- Thomas Jefferson University, Philadelphia, Pennsylvania, USA.,Radiological Society of North America (RSNA), Oak Brook, Illinois, USA
| | - Josephine Pressacco
- Canadian Association of Radiologists (CAR), Ottawa, Ontario, Canada.,McGill University, Montreal, Quebec, Canada
| | - Vijay M Rao
- Thomas Jefferson University, Philadelphia, Pennsylvania, USA.,Radiological Society of North America (RSNA), Oak Brook, Illinois, USA
| | - John Slavotinek
- Royal Australian and New Zealand College of Radiologists (RANZCR), Sydney, New South Wales, Australia.,Flinders Medical Centre and Flinders University, Adelaide, South Australia, Australia
| | - Jacob J Visser
- Erasmus Medical Center, Rotterdam, The Netherlands.,International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria
| | - Richard Ea Walker
- Canadian Association of Radiologists (CAR), Ottawa, Ontario, Canada.,University of Calgary, Calgary, Alberta, Canada
| | - James A Brink
- American College of Radiology (ACR), Reston, Virginia, USA.,International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria.,Harvard Medical School, Boston, Massachusetts, USA
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16
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Brady AP, Bello JA, Derchi LE, Fuchsjäger M, Goergen S, Krestin GP, Lee EJY, Levin DC, Pressacco J, Rao VM, Slavotinek J, Visser JJ, Walker REA, Brink JA. Radiology in the Era of Value-based Healthcare: A Multi-Society Expert Statement from the ACR, CAR, ESR, IS3R, RANZCR, and RSNA. Radiology 2020; 298:486-491. [PMID: 33346696 DOI: 10.1148/radiol.2020209027] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background The Value-Based Healthcare (VBH) concept is designed to improve individual healthcare outcomes without increasing expenditure, and is increasingly being used to determine resourcing of and reimbursement for medical services. Radiology is a major contributor to patient and societal healthcare at many levels. Despite this, some VBH models do not acknowledge radiology's central role; this may have future negative consequences for resource allocation. Methods, findings and interpretation This multi-society paper, representing the views of Radiology Societies in Europe, the USA, Canada, Australia, and New Zealand, describes the place of radiology in VBH models and the health-care value contributions of radiology. Potential steps to objectify and quantify the value contributed by radiology to healthcare are outlined. Published under a CC BY 4.0 license.
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Affiliation(s)
- Adrian P Brady
- From Mercy University Hospital, Grenville Place, Centre, Cork, T12 WE28, Ireland (A.P.B.); European Society of Radiology (ESR), Vienna, Austria (A.P.B., L.E.D., M.F.); Montefiore Medical Center, New York, NY (J. Bello); American College of Radiology (ACR), Reston, Va (J. Bello, J. Brink); University of Genoa, Genoa Italy (L.E.D.); Medical University Graz, Graz, Austria (M.F.); Monash University, Melbourne, Australia (S.G.); Royal Australian and New Zealand College of Radiologists (RANZCR), Sydney, Australia (S.G., J.S.); Erasmus Medical Center, Rotterdam, the Netherlands (G.P.K., J.J.V., J. Brink); International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria (G.P.K., J.J.V.); Langley Memorial Hospital, Langley, Canada (E.J.Y.L.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Thomas Jefferson University, Philadelphia, Pa (D.C.L., V.M.R.); Radiological Society of North America (RSNA), Oak Brook, Ill (D.C.L.†, V.M.R.); McGill University, Montreal, Canada (J.P.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Flinders Medical Centre and Flinders University, Adelaide, Australia (J.S.); University of Calgary, Calgary, Canada (R.E.A.W.); Harvard Medical School, Boston, Mass (J. Brink)
| | - Jaqueline A Bello
- From Mercy University Hospital, Grenville Place, Centre, Cork, T12 WE28, Ireland (A.P.B.); European Society of Radiology (ESR), Vienna, Austria (A.P.B., L.E.D., M.F.); Montefiore Medical Center, New York, NY (J. Bello); American College of Radiology (ACR), Reston, Va (J. Bello, J. Brink); University of Genoa, Genoa Italy (L.E.D.); Medical University Graz, Graz, Austria (M.F.); Monash University, Melbourne, Australia (S.G.); Royal Australian and New Zealand College of Radiologists (RANZCR), Sydney, Australia (S.G., J.S.); Erasmus Medical Center, Rotterdam, the Netherlands (G.P.K., J.J.V., J. Brink); International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria (G.P.K., J.J.V.); Langley Memorial Hospital, Langley, Canada (E.J.Y.L.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Thomas Jefferson University, Philadelphia, Pa (D.C.L., V.M.R.); Radiological Society of North America (RSNA), Oak Brook, Ill (D.C.L., V.M.R.); McGill University, Montreal, Canada (J.P.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Flinders Medical Centre and Flinders University, Adelaide, Australia (J.S.); University of Calgary, Calgary, Canada (R.E.A.W.); Harvard Medical School, Boston, Mass (J. Brink)
| | - Lorenzo E Derchi
- From Mercy University Hospital, Grenville Place, Centre, Cork, T12 WE28, Ireland (A.P.B.); European Society of Radiology (ESR), Vienna, Austria (A.P.B., L.E.D., M.F.); Montefiore Medical Center, New York, NY (J. Bello); American College of Radiology (ACR), Reston, Va (J. Bello, J. Brink); University of Genoa, Genoa Italy (L.E.D.); Medical University Graz, Graz, Austria (M.F.); Monash University, Melbourne, Australia (S.G.); Royal Australian and New Zealand College of Radiologists (RANZCR), Sydney, Australia (S.G., J.S.); Erasmus Medical Center, Rotterdam, the Netherlands (G.P.K., J.J.V., J. Brink); International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria (G.P.K., J.J.V.); Langley Memorial Hospital, Langley, Canada (E.J.Y.L.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Thomas Jefferson University, Philadelphia, Pa (D.C.L., V.M.R.); Radiological Society of North America (RSNA), Oak Brook, Ill (D.C.L., V.M.R.); McGill University, Montreal, Canada (J.P.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Flinders Medical Centre and Flinders University, Adelaide, Australia (J.S.); University of Calgary, Calgary, Canada (R.E.A.W.); Harvard Medical School, Boston, Mass (J. Brink)
| | - Michael Fuchsjäger
- From Mercy University Hospital, Grenville Place, Centre, Cork, T12 WE28, Ireland (A.P.B.); European Society of Radiology (ESR), Vienna, Austria (A.P.B., L.E.D., M.F.); Montefiore Medical Center, New York, NY (J. Bello); American College of Radiology (ACR), Reston, Va (J. Bello, J. Brink); University of Genoa, Genoa Italy (L.E.D.); Medical University Graz, Graz, Austria (M.F.); Monash University, Melbourne, Australia (S.G.); Royal Australian and New Zealand College of Radiologists (RANZCR), Sydney, Australia (S.G., J.S.); Erasmus Medical Center, Rotterdam, the Netherlands (G.P.K., J.J.V., J. Brink); International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria (G.P.K., J.J.V.); Langley Memorial Hospital, Langley, Canada (E.J.Y.L.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Thomas Jefferson University, Philadelphia, Pa (D.C.L., V.M.R.); Radiological Society of North America (RSNA), Oak Brook, Ill (D.C.L., V.M.R.); McGill University, Montreal, Canada (J.P.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Flinders Medical Centre and Flinders University, Adelaide, Australia (J.S.); University of Calgary, Calgary, Canada (R.E.A.W.); Harvard Medical School, Boston, Mass (J. Brink)
| | - Stacy Goergen
- From Mercy University Hospital, Grenville Place, Centre, Cork, T12 WE28, Ireland (A.P.B.); European Society of Radiology (ESR), Vienna, Austria (A.P.B., L.E.D., M.F.); Montefiore Medical Center, New York, NY (J. Bello); American College of Radiology (ACR), Reston, Va (J. Bello, J. Brink); University of Genoa, Genoa Italy (L.E.D.); Medical University Graz, Graz, Austria (M.F.); Monash University, Melbourne, Australia (S.G.); Royal Australian and New Zealand College of Radiologists (RANZCR), Sydney, Australia (S.G., J.S.); Erasmus Medical Center, Rotterdam, the Netherlands (G.P.K., J.J.V., J. Brink); International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria (G.P.K., J.J.V.); Langley Memorial Hospital, Langley, Canada (E.J.Y.L.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Thomas Jefferson University, Philadelphia, Pa (D.C.L., V.M.R.); Radiological Society of North America (RSNA), Oak Brook, Ill (D.C.L., V.M.R.); McGill University, Montreal, Canada (J.P.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Flinders Medical Centre and Flinders University, Adelaide, Australia (J.S.); University of Calgary, Calgary, Canada (R.E.A.W.); Harvard Medical School, Boston, Mass (J. Brink)
| | - Gabriel P Krestin
- From Mercy University Hospital, Grenville Place, Centre, Cork, T12 WE28, Ireland (A.P.B.); European Society of Radiology (ESR), Vienna, Austria (A.P.B., L.E.D., M.F.); Montefiore Medical Center, New York, NY (J. Bello); American College of Radiology (ACR), Reston, Va (J. Bello, J. Brink); University of Genoa, Genoa Italy (L.E.D.); Medical University Graz, Graz, Austria (M.F.); Monash University, Melbourne, Australia (S.G.); Royal Australian and New Zealand College of Radiologists (RANZCR), Sydney, Australia (S.G., J.S.); Erasmus Medical Center, Rotterdam, the Netherlands (G.P.K., J.J.V., J. Brink); International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria (G.P.K., J.J.V.); Langley Memorial Hospital, Langley, Canada (E.J.Y.L.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Thomas Jefferson University, Philadelphia, Pa (D.C.L., V.M.R.); Radiological Society of North America (RSNA), Oak Brook, Ill (D.C.L., V.M.R.); McGill University, Montreal, Canada (J.P.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Flinders Medical Centre and Flinders University, Adelaide, Australia (J.S.); University of Calgary, Calgary, Canada (R.E.A.W.); Harvard Medical School, Boston, Mass (J. Brink)
| | - Emil J Y Lee
- From Mercy University Hospital, Grenville Place, Centre, Cork, T12 WE28, Ireland (A.P.B.); European Society of Radiology (ESR), Vienna, Austria (A.P.B., L.E.D., M.F.); Montefiore Medical Center, New York, NY (J. Bello); American College of Radiology (ACR), Reston, Va (J. Bello, J. Brink); University of Genoa, Genoa Italy (L.E.D.); Medical University Graz, Graz, Austria (M.F.); Monash University, Melbourne, Australia (S.G.); Royal Australian and New Zealand College of Radiologists (RANZCR), Sydney, Australia (S.G., J.S.); Erasmus Medical Center, Rotterdam, the Netherlands (G.P.K., J.J.V., J. Brink); International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria (G.P.K., J.J.V.); Langley Memorial Hospital, Langley, Canada (E.J.Y.L.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Thomas Jefferson University, Philadelphia, Pa (D.C.L., V.M.R.); Radiological Society of North America (RSNA), Oak Brook, Ill (D.C.L., V.M.R.); McGill University, Montreal, Canada (J.P.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Flinders Medical Centre and Flinders University, Adelaide, Australia (J.S.); University of Calgary, Calgary, Canada (R.E.A.W.); Harvard Medical School, Boston, Mass (J. Brink)
| | - David C Levin
- From Mercy University Hospital, Grenville Place, Centre, Cork, T12 WE28, Ireland (A.P.B.); European Society of Radiology (ESR), Vienna, Austria (A.P.B., L.E.D., M.F.); Montefiore Medical Center, New York, NY (J. Bello); American College of Radiology (ACR), Reston, Va (J. Bello, J. Brink); University of Genoa, Genoa Italy (L.E.D.); Medical University Graz, Graz, Austria (M.F.); Monash University, Melbourne, Australia (S.G.); Royal Australian and New Zealand College of Radiologists (RANZCR), Sydney, Australia (S.G., J.S.); Erasmus Medical Center, Rotterdam, the Netherlands (G.P.K., J.J.V., J. Brink); International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria (G.P.K., J.J.V.); Langley Memorial Hospital, Langley, Canada (E.J.Y.L.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Thomas Jefferson University, Philadelphia, Pa (D.C.L., V.M.R.); Radiological Society of North America (RSNA), Oak Brook, Ill (D.C.L., V.M.R.); McGill University, Montreal, Canada (J.P.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Flinders Medical Centre and Flinders University, Adelaide, Australia (J.S.); University of Calgary, Calgary, Canada (R.E.A.W.); Harvard Medical School, Boston, Mass (J. Brink)
| | - Josephine Pressacco
- From Mercy University Hospital, Grenville Place, Centre, Cork, T12 WE28, Ireland (A.P.B.); European Society of Radiology (ESR), Vienna, Austria (A.P.B., L.E.D., M.F.); Montefiore Medical Center, New York, NY (J. Bello); American College of Radiology (ACR), Reston, Va (J. Bello, J. Brink); University of Genoa, Genoa Italy (L.E.D.); Medical University Graz, Graz, Austria (M.F.); Monash University, Melbourne, Australia (S.G.); Royal Australian and New Zealand College of Radiologists (RANZCR), Sydney, Australia (S.G., J.S.); Erasmus Medical Center, Rotterdam, the Netherlands (G.P.K., J.J.V., J. Brink); International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria (G.P.K., J.J.V.); Langley Memorial Hospital, Langley, Canada (E.J.Y.L.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Thomas Jefferson University, Philadelphia, Pa (D.C.L., V.M.R.); Radiological Society of North America (RSNA), Oak Brook, Ill (D.C.L., V.M.R.); McGill University, Montreal, Canada (J.P.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Flinders Medical Centre and Flinders University, Adelaide, Australia (J.S.); University of Calgary, Calgary, Canada (R.E.A.W.); Harvard Medical School, Boston, Mass (J. Brink)
| | - Vijay M Rao
- From Mercy University Hospital, Grenville Place, Centre, Cork, T12 WE28, Ireland (A.P.B.); European Society of Radiology (ESR), Vienna, Austria (A.P.B., L.E.D., M.F.); Montefiore Medical Center, New York, NY (J. Bello); American College of Radiology (ACR), Reston, Va (J. Bello, J. Brink); University of Genoa, Genoa Italy (L.E.D.); Medical University Graz, Graz, Austria (M.F.); Monash University, Melbourne, Australia (S.G.); Royal Australian and New Zealand College of Radiologists (RANZCR), Sydney, Australia (S.G., J.S.); Erasmus Medical Center, Rotterdam, the Netherlands (G.P.K., J.J.V., J. Brink); International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria (G.P.K., J.J.V.); Langley Memorial Hospital, Langley, Canada (E.J.Y.L.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Thomas Jefferson University, Philadelphia, Pa (D.C.L., V.M.R.); Radiological Society of North America (RSNA), Oak Brook, Ill (D.C.L., V.M.R.); McGill University, Montreal, Canada (J.P.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Flinders Medical Centre and Flinders University, Adelaide, Australia (J.S.); University of Calgary, Calgary, Canada (R.E.A.W.); Harvard Medical School, Boston, Mass (J. Brink)
| | - John Slavotinek
- From Mercy University Hospital, Grenville Place, Centre, Cork, T12 WE28, Ireland (A.P.B.); European Society of Radiology (ESR), Vienna, Austria (A.P.B., L.E.D., M.F.); Montefiore Medical Center, New York, NY (J. Bello); American College of Radiology (ACR), Reston, Va (J. Bello, J. Brink); University of Genoa, Genoa Italy (L.E.D.); Medical University Graz, Graz, Austria (M.F.); Monash University, Melbourne, Australia (S.G.); Royal Australian and New Zealand College of Radiologists (RANZCR), Sydney, Australia (S.G., J.S.); Erasmus Medical Center, Rotterdam, the Netherlands (G.P.K., J.J.V., J. Brink); International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria (G.P.K., J.J.V.); Langley Memorial Hospital, Langley, Canada (E.J.Y.L.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Thomas Jefferson University, Philadelphia, Pa (D.C.L., V.M.R.); Radiological Society of North America (RSNA), Oak Brook, Ill (D.C.L., V.M.R.); McGill University, Montreal, Canada (J.P.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Flinders Medical Centre and Flinders University, Adelaide, Australia (J.S.); University of Calgary, Calgary, Canada (R.E.A.W.); Harvard Medical School, Boston, Mass (J. Brink)
| | - Jacob J Visser
- From Mercy University Hospital, Grenville Place, Centre, Cork, T12 WE28, Ireland (A.P.B.); European Society of Radiology (ESR), Vienna, Austria (A.P.B., L.E.D., M.F.); Montefiore Medical Center, New York, NY (J. Bello); American College of Radiology (ACR), Reston, Va (J. Bello, J. Brink); University of Genoa, Genoa Italy (L.E.D.); Medical University Graz, Graz, Austria (M.F.); Monash University, Melbourne, Australia (S.G.); Royal Australian and New Zealand College of Radiologists (RANZCR), Sydney, Australia (S.G., J.S.); Erasmus Medical Center, Rotterdam, the Netherlands (G.P.K., J.J.V., J. Brink); International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria (G.P.K., J.J.V.); Langley Memorial Hospital, Langley, Canada (E.J.Y.L.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Thomas Jefferson University, Philadelphia, Pa (D.C.L., V.M.R.); Radiological Society of North America (RSNA), Oak Brook, Ill (D.C.L., V.M.R.); McGill University, Montreal, Canada (J.P.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Flinders Medical Centre and Flinders University, Adelaide, Australia (J.S.); University of Calgary, Calgary, Canada (R.E.A.W.); Harvard Medical School, Boston, Mass (J. Brink)
| | - Richard E A Walker
- From Mercy University Hospital, Grenville Place, Centre, Cork, T12 WE28, Ireland (A.P.B.); European Society of Radiology (ESR), Vienna, Austria (A.P.B., L.E.D., M.F.); Montefiore Medical Center, New York, NY (J. Bello); American College of Radiology (ACR), Reston, Va (J. Bello, J. Brink); University of Genoa, Genoa Italy (L.E.D.); Medical University Graz, Graz, Austria (M.F.); Monash University, Melbourne, Australia (S.G.); Royal Australian and New Zealand College of Radiologists (RANZCR), Sydney, Australia (S.G., J.S.); Erasmus Medical Center, Rotterdam, the Netherlands (G.P.K., J.J.V., J. Brink); International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria (G.P.K., J.J.V.); Langley Memorial Hospital, Langley, Canada (E.J.Y.L.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Thomas Jefferson University, Philadelphia, Pa (D.C.L., V.M.R.); Radiological Society of North America (RSNA), Oak Brook, Ill (D.C.L., V.M.R.); McGill University, Montreal, Canada (J.P.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Flinders Medical Centre and Flinders University, Adelaide, Australia (J.S.); University of Calgary, Calgary, Canada (R.E.A.W.); Harvard Medical School, Boston, Mass (J. Brink)
| | - James A Brink
- From Mercy University Hospital, Grenville Place, Centre, Cork, T12 WE28, Ireland (A.P.B.); European Society of Radiology (ESR), Vienna, Austria (A.P.B., L.E.D., M.F.); Montefiore Medical Center, New York, NY (J. Bello); American College of Radiology (ACR), Reston, Va (J. Bello, J. Brink); University of Genoa, Genoa Italy (L.E.D.); Medical University Graz, Graz, Austria (M.F.); Monash University, Melbourne, Australia (S.G.); Royal Australian and New Zealand College of Radiologists (RANZCR), Sydney, Australia (S.G., J.S.); Erasmus Medical Center, Rotterdam, the Netherlands (G.P.K., J.J.V., J. Brink); International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria (G.P.K., J.J.V.); Langley Memorial Hospital, Langley, Canada (E.J.Y.L.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Thomas Jefferson University, Philadelphia, Pa (D.C.L., V.M.R.); Radiological Society of North America (RSNA), Oak Brook, Ill (D.C.L., V.M.R.); McGill University, Montreal, Canada (J.P.); Canadian Association of Radiologists (CAR), Ottawa, Canada (E.J.Y.L., J.P., R.E.A.W.); Flinders Medical Centre and Flinders University, Adelaide, Australia (J.S.); University of Calgary, Calgary, Canada (R.E.A.W.); Harvard Medical School, Boston, Mass (J. Brink)
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Shapira N, Scheuermann J, Perkins AE, Kim J, Liu LP, Karp JS, Noël PB. Quantitative positron emission tomography imaging in the presence of iodinated contrast media using electron density quantifications from dual-energy computed tomography. Med Phys 2020; 48:273-286. [PMID: 33170953 DOI: 10.1002/mp.14589] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 07/31/2020] [Accepted: 11/02/2020] [Indexed: 11/10/2022] Open
Abstract
PURPOSE As preparation for future positron emission tomography (PET)/dual-energy computed tomography (DECT)T imaging modality and new possible clinical applications, the study aimed to evaluate the utility of clinically available spectral results from a DECT system for improving attenuation corrections of PET acquisitions in the presence of iodinated contrast media. The dependence of the accuracy of PET quantification values, reconstructed with conventional and spectral-based attenuation corrections, was examined as a function of the amount of iodine content and x-ray radiation exposure. METHODS Measurements were performed on commercial PET/CT and DECT systems, using a semi-anthropomorphic phantom with seven centrifuge tubes in its bore. Five different configurations of tube contents were scanned by both PET/CT and DECT. With the aim of mimicking clinically observed concentrations, in all phantom configurations the center tube contained a high concentration of radionuclide while the peripheral tubes contained a lower concentration of radionuclide. Iodine content was incrementally increased between phantom configurations by replacing iodine-free tubes with tubes that contained the original radionuclide concentration within a 10 mg/ml iodine dilution. DECT-based attenuation correction maps were generated by scaling electron density spectral results into corresponding 511 keV photon linear attenuation coefficients. RESULTS Mean SUV values obtained from the nominal PET reconstruction, using conventional CT images as input for the attenuation correction, demonstrate a monotonic increase of 8.6% when the water and radionuclide mixtures were replaced by iodine, water, and radionuclide (same level of activity) mixture. Mean SUV values obtained from the DECT-based reconstruction, in which the attenuation correction utilizes electron density values as input, demonstrate different, more stable behavior across all iodine insert configurations, with a standard deviation to mean ratio of less than 1%. This observed behavior was independent of the area size used for measurement. A minor radiation dose dependency of the electron density values (below 0.5%) was observed. This resulted in consistent (iodine independent) PET quantification behavior, which persisted even at the lowest radiation dose levels tested in our experiment, that is, 25% of the radiation dose utilized for CT acquisition in the clinical PET/CT protocol. CONCLUSIONS Utilization of DECT-generated electron density estimations for attenuation correction benefit PET quantification consistency in the presence of iodine and at nominal and low DECT radiation exposure levels. The ability to correctly account for iodinated contrast media in PET acquisitions will allow the development of new clinical applications that rely on the quantitative capabilities of spectral CT technologies and modern PET systems.
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Affiliation(s)
- Nadav Shapira
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Joshua Scheuermann
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Johoon Kim
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Leening P Liu
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Joel S Karp
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Peter B Noël
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.,Department of Diagnostic and Interventional Radiology, School of Medicine & klinikum rechts der Isar, Technical University of Munich, München, Germany
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Zanardo M, Doniselli FM, Esseridou A, Agrò M, Panarisi NAR, Monti CB, Di Leo G, Sardanelli F. Lean body weight versus total body weight to calculate the iodinated contrast media volume in abdominal CT: a randomised controlled trial. Insights Imaging 2020; 11:132. [PMID: 33296036 PMCID: PMC7726088 DOI: 10.1186/s13244-020-00920-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Accepted: 10/07/2020] [Indexed: 12/25/2022] Open
Abstract
Objectives Iodinated contrast media (ICM) could be more appropriately dosed on patient lean body weight (LBW) than on total body weight (TBW). Methods After Ethics Committee approval, trial registration NCT03384979, patients aged ≥ 18 years scheduled for multiphasic abdominal CT were randomised for ICM dose to LBW group (0.63 gI/kg of LBW) or TBW group (0.44 gI/kg of TBW). Abdominal 64-row CT was performed using 120 kVp, 100–200 mAs, rotation time 0.5 s, pitch 1, Iopamidol (370 mgI/mL), and flow rate 3 mL/s. Levene, Mann–Whitney U, and χ2 tests were used. The primary endpoint was liver contrast enhancement (LCE). Results Of 335 enrolled patients, 17 were screening failures; 44 dropped out after randomisation; 274 patients were analysed (133 LBW group, 141 TBW group). The median age of LBW group (66 years) was slightly lower than that of TBW group (70 years). Although the median ICM-injected volume was comparable between groups, its variability was larger in the former (interquartile range 27 mL versus 21 mL, p = 0.01). The same was for unenhanced liver density (IQR 10 versus 7 HU) (p = 0.02). Median LCE was 40 (35–46) HU in the LBW group and 40 (35–44) HU in the TBW group, without significant difference for median (p = 0.41) and variability (p = 0.23). Suboptimal LCE (< 40 HU) was found in 64/133 (48%) patients in the LBW group and 69/141 (49%) in the TBW group, but no examination needed repeating. Conclusions The calculation of the ICM volume to be administered for abdominal CT based on the LBW does not imply a more consistent LCE.
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Affiliation(s)
- Moreno Zanardo
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, Milan, Italy.
| | - Fabio Martino Doniselli
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, Milan, Italy.,Neuroradiology Department, Foundation IRCCS Neurological Institute "C. Besta", Via Celoria 11, 20133, Milan, Italy
| | - Anastassia Esseridou
- Radiology Unit, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy
| | - Massimiliano Agrò
- Postgraduate School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122, Milan, Italy
| | - Nicol Antonina Rita Panarisi
- Postgraduate School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122, Milan, Italy
| | - Caterina Beatrice Monti
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, Milan, Italy
| | - Giovanni Di Leo
- Radiology Unit, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy
| | - Francesco Sardanelli
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, Milan, Italy.,Radiology Unit, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese, Italy
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Trimboli RM, Giorgi Rossi P, Battisti NML, Cozzi A, Magni V, Zanardo M, Sardanelli F. Do we still need breast cancer screening in the era of targeted therapies and precision medicine? Insights Imaging 2020; 11:105. [PMID: 32975658 PMCID: PMC7519022 DOI: 10.1186/s13244-020-00905-3] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Accepted: 08/20/2020] [Indexed: 12/27/2022] Open
Abstract
Breast cancer (BC) is the most common female cancer and the second cause of death among women worldwide. The 5-year relative survival rate recently improved up to 90% due to increased population coverage and women's attendance to organised mammography screening as well as to advances in therapies, especially systemic treatments. Screening attendance is associated with a mortality reduction of at least 30% and a 40% lower risk of advanced disease. The stage at diagnosis remains the strongest predictor of recurrences. Systemic treatments evolved dramatically over the last 20 years: aromatase inhibitors improved the treatment of early-stage luminal BC; targeted monoclonal antibodies changed the natural history of anti-human epidermal growth factor receptor 2-positive (HER2) disease; immunotherapy is currently investigated in patients with triple-negative BC; gene expression profiling is now used with the aim of personalising systemic treatments. In the era of precision medicine, it is a challenging task to define the relative contribution of early diagnosis by screening mammography and systemic treatments in determining BC survival. Estimated contributions before 2000 were 46% for screening and 54% for treatment advances and after 2000, 37% and 63%, respectively. A model showed that the 10-year recurrence rate would be 30% and 25% using respectively chemotherapy or novel treatments in the absence of screening, but would drop to 19% and 15% respectively if associated with mammography screening. Early detection per se has not a curative intent and systemic treatment has limited benefit on advanced stages. Both screening mammography and systemic therapies continue to positively contribute to BC prognosis.
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Affiliation(s)
- Rubina Manuela Trimboli
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milan, Italy
| | - Paolo Giorgi Rossi
- Epidemiology Unit, Azienda USL–IRCCS di Reggio Emilia, Via Amendola 2, 42122 Reggio Emilia, Italy
| | - Nicolò Matteo Luca Battisti
- Breast Unit–Department of Medicine, The Royal Marsden NHS Foundation Trust, Downs Road, Sutton, London, SM2 5PT UK
- Breast Cancer Research Division, The Institute of Cancer Research, 15 Cotswold Road, Sutton, London, SM2 5NG UK
| | - Andrea Cozzi
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milan, Italy
| | - Veronica Magni
- Medical School, Università degli Studi di Milano, Via Festa del Perdono 7, 20122 Milan, Italy
| | - Moreno Zanardo
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milan, Italy
| | - Francesco Sardanelli
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milan, Italy
- Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097 San Donato Milanese, Italy
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Chiwome L, Okojie OM, Rahman AKMJ, Javed F, Hamid P. Artificial Intelligence: Is It Armageddon for Breast Radiologists? Cureus 2020; 12:e8923. [PMID: 32760624 PMCID: PMC7392361 DOI: 10.7759/cureus.8923] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Accepted: 06/30/2020] [Indexed: 12/22/2022] Open
Abstract
Artificial Intelligence (AI) has taken radiology by storm, in particular, mammogram interpretation, and we have seen a recent surge in the number of publications on potential uses of AI in breast radiology. Breast cancer exerts a lot of burden on the National Health Service (NHS) and is the second most common cancer in the UK as of 2018. New cases of breast cancer have been on the rise in the past decade, while the survival rate has been improving. The NHS breast cancer screening program led to an improvement in survival rate. The expansion of the screening program led to more mammograms, thereby putting more work on the hands of radiologists, and the issue of double reading further worsens the workload. The introduction of computer-aided detection (CAD) systems to help radiologists was found not to have the expected outcome of improving the performance of readers. Unreliability of CAD systems has led to the explosion of studies and development of applications with the potential use in breast imaging. The purported success recorded with the use of machine learning in breast radiology has led to people postulating ideas that AI will replace breast radiologists. Of course, AI has many applications and potential uses in radiology, but will it replace radiologists? We reviewed many articles on the use of AI in breast radiology to give future radiologists and radiologists full information on this topic. This article focuses on explaining the basic principles and terminology of AI in radiology, potential uses, and limitations of AI in radiology. We have also analysed articles and answered the question of whether AI will replace radiologists.
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Affiliation(s)
- Lawman Chiwome
- General Internal Medicine, University Hospitals of Morecambe Bay NHS Foundation Trust, Lancaster, GBR
| | - Onosetale M Okojie
- Family Medicine, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA
| | - A K M Jamiur Rahman
- Internal Medicine, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA
| | - Faheem Javed
- Anaesthesia, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA
| | - Pousettef Hamid
- Neurology, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA
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Pesapane F, Tantrige P, Patella F, Biondetti P, Nicosia L, Ianniello A, Rossi UG, Carrafiello G, Ierardi AM. Myths and facts about artificial intelligence: why machine- and deep-learning will not replace interventional radiologists. Med Oncol 2020; 37:40. [DOI: 10.1007/s12032-020-01368-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Accepted: 03/18/2020] [Indexed: 12/13/2022]
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Ooi SKG, Makmur A, Soon AYQ, Fook-Chong S, Liew C, Sia SY, Ting YH, Lim CY. Attitudes toward artificial intelligence in radiology with learner needs assessment within radiology residency programmes: a national multi-programme survey. Singapore Med J 2019; 62:126-134. [PMID: 31680181 DOI: 10.11622/smedj.2019141] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
INTRODUCTION We aimed to assess the attitudes and learner needs of radiology residents and faculty radiologists regarding artificial intelligence (AI) and machine learning (ML) in radiology. METHODS A web-based questionnaire, designed using SurveyMonkey, was sent out to residents and faculty radiologists in all three radiology residency programmes in Singapore. The questionnaire comprised four sections and aimed to evaluate respondents' current experience, attempts at self-learning, perceptions of career prospects and expectations of an AI/ML curriculum in their residency programme. Respondents' anonymity was ensured. RESULTS A total of 125 respondents (86 male, 39 female; 70 residents, 55 faculty radiologists) completed the questionnaire. The majority agreed that AI/ML will drastically change radiology practice (88.8%) and makes radiology more exciting (76.0%), and most would still choose to specialise in radiology if given a choice (80.0%). 64.8% viewed themselves as novices in their understanding of AI/ML, 76.0% planned to further advance their AI/ML knowledge and 67.2% were keen to get involved in an AI/ML research project. An overwhelming majority (84.8%) believed that AI/ML knowledge should be taught during residency, and most opined that this was as important as imaging physics and clinical skills/knowledge curricula (80.0% and 72.8%, respectively). More than half thought that their residency programme had not adequately implemented AI/ML teaching (59.2%). In subgroup analyses, male and tech-savvy respondents were more involved in AI/ML activities, leading to better technical understanding. CONCLUSION A growing optimism towards radiology undergoing technological transformation and AI/ML implementation has led to a strong demand for an AI/ML curriculum in residency education.
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Affiliation(s)
- Su Kai Gideon Ooi
- Department of Nuclear Medicine and Molecular Imaging, Division of Radiological Sciences, Singapore General Hospital, Singapore
| | - Andrew Makmur
- Department of Diagnostic Imaging, National University Hospital, Singapore
| | | | | | - Charlene Liew
- Department of Diagnostic Radiology, Changi General Hospital, Singapore
| | - Soon Yiew Sia
- Department of Diagnostic Imaging, National University Hospital, Singapore
| | - Yong Han Ting
- Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore
| | - Chee Yeong Lim
- Department of Diagnostic Radiology, Division of Radiological Sciences, Singapore General Hospital, Singapore
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Radiology workflow for RECIST assessment in clinical trials: Can we reconcile time-efficiency and quality? Eur J Radiol 2019; 118:257-263. [DOI: 10.1016/j.ejrad.2019.07.030] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2019] [Revised: 06/10/2019] [Accepted: 07/23/2019] [Indexed: 01/01/2023]
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Sardanelli F. The future of radiology is now: the first 100 articles published in European Radiology Experimental. Eur Radiol Exp 2019; 3:28. [PMID: 31350626 PMCID: PMC6660525 DOI: 10.1186/s41747-019-0106-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2019] [Accepted: 07/01/2019] [Indexed: 12/12/2022] Open
Abstract
European Radiology Experimental reached the first 100 articles published in two years. Rejection rate was 30%, publication rate increased from 3.5/month in the first 12-month period to 4.8/month in the second 12-month period. The journal metrics were: 25 days from submission to first decision, 96 days from submission to acceptance, and 69 days from acceptance to publication. At the end of May 2019, we accumulated a total of 82,367 article accesses, 541 Altmetric score, and 110 citations for 92 published articles. Europe accounted for 85% of article origin. One third of corresponding authors were not radiologists/radiology residents, but were rather mainly physicists, engineers, or computer scientists. The distribution among subspecialties/body parts was well balanced; 9% of the topics regarded patient's safety, radioprotection, or contrast media. Magnetic resonance imaging (MRI) and computed tomography (CT) accounted for 71% of the articles. Twenty-two percent of original articles/technical notes reported on animal models, 15% on phantoms, 3% on in silico, 2% on human cadavers, and 2% on cells. Nine articles regarded artificial intelligence and/or radiomics, and 2 regarded augmented reality. Of 100 articles, 57 declared funding sources. A total of 517 independent reviews were performed by 92 reviewers. The five articles quoted the most regarded augmented reality, spectral photon-counting CT, artificial intelligence, MRI radiomics, and diffusion tensor imaging of the musculoskeletal and peripheral nerve systems. The journal is complying with aims and scope of its "experimental" profile.
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Affiliation(s)
- Francesco Sardanelli
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milan, Italy. .,Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097 San Donato Milanese, Milan, Italy.
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25
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Pesapane F, Codari M, Sardanelli F. Artificial intelligence in medical imaging: threat or opportunity? Radiologists again at the forefront of innovation in medicine. Eur Radiol Exp 2018; 2:35. [PMID: 30353365 PMCID: PMC6199205 DOI: 10.1186/s41747-018-0061-6] [Citation(s) in RCA: 310] [Impact Index Per Article: 51.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2018] [Accepted: 07/31/2018] [Indexed: 02/08/2023] Open
Abstract
One of the most promising areas of health innovation is the application of artificial intelligence (AI), primarily in medical imaging. This article provides basic definitions of terms such as “machine/deep learning” and analyses the integration of AI into radiology. Publications on AI have drastically increased from about 100–150 per year in 2007–2008 to 700–800 per year in 2016–2017. Magnetic resonance imaging and computed tomography collectively account for more than 50% of current articles. Neuroradiology appears in about one-third of the papers, followed by musculoskeletal, cardiovascular, breast, urogenital, lung/thorax, and abdomen, each representing 6–9% of articles. With an irreversible increase in the amount of data and the possibility to use AI to identify findings either detectable or not by the human eye, radiology is now moving from a subjective perceptual skill to a more objective science. Radiologists, who were on the forefront of the digital era in medicine, can guide the introduction of AI into healthcare. Yet, they will not be replaced because radiology includes communication of diagnosis, consideration of patient’s values and preferences, medical judgment, quality assurance, education, policy-making, and interventional procedures. The higher efficiency provided by AI will allow radiologists to perform more value-added tasks, becoming more visible to patients and playing a vital role in multidisciplinary clinical teams.
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Affiliation(s)
- Filippo Pesapane
- Postgraduate School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122, Milan, Italy
| | - Marina Codari
- Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097 San Donato Milanese, Milan, Italy.
| | - Francesco Sardanelli
- Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097 San Donato Milanese, Milan, Italy.,Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Morandi 30, 20097 San Donato Milanese, Milan, Italy
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Birnbacher L, Willner M, Marschner M, Pfeiffer D, Pfeiffer F, Herzen J. Accurate effective atomic number determination with polychromatic grating-based phase-contrast computed tomography. OPTICS EXPRESS 2018; 26:15153-15166. [PMID: 30114766 DOI: 10.1364/oe.26.015153] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Accepted: 04/30/2018] [Indexed: 06/08/2023]
Abstract
The demand for quantitative medical imaging is increasing in the ongoing digitalization. Conventional computed tomography (CT) is energy-dependent and therefore of limited comparability. In contrast, dual-energy CT (DECT) allows for the determination of absolute image contrast quantities, namely the electron density and the effective atomic number, and is already established in clinical radiology and radiation therapy. Grating-based phase-contrast computed tomography (GBPC-CT) is an experimental X-ray technique that also allows for the measurement of the electron density and the effective atomic number. However, the determination of both quantities is challenging when dealing with polychromatic GBPC-CT setups. In this paper, we present how to calculate the effective atomic numbers with a polychromatic, laboratory GBPC-CT setup operating between 35 and 50\,kVp. First, we investigated the accuracy of the measurement of the attenuation coefficients and electron densities. For this, we performed a calibration using the concept of effective energy. With the reliable experimental quantitative values, we were able to evaluate the effective atomic numbers of the investigated materials using a method previously shown with monochromatic X-ray radiation. In detail, we first calculated the ratio of the electron density and attenuation coefficient, which were experimentally determined with our polychromatic GBPC-CT setup. Second, we compared this ratio with tabulated total attenuation cross sections from literature values to determine the effective atomic numbers. Thus, we were able to calculate two physical absolute quantities -- the electron density and effective atomic number -- that are in general independent of the specific experimental conditions like the X-ray beam spectrum or the setup design.
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27
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Building Imaging Institutes of Patient Care Outcomes: Imaging as a Nidus for Innovation in Clinical Care, Research, and Education. Acad Radiol 2018; 25:594-598. [PMID: 29729856 DOI: 10.1016/j.acra.2018.01.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2017] [Revised: 01/08/2018] [Accepted: 01/14/2018] [Indexed: 11/24/2022]
Abstract
Traditionally, radiologists have been responsible for the protocol of imaging studies, imaging acquisition, supervision of imaging technologists, and interpretation and reporting of imaging findings. In this article, we outline how radiology needs to change and adapt to a role of providing value-based, integrated health-care delivery. We believe that the way to best serve our specialty and our patients is to undertake a fundamental paradigm shift in how we practice. We describe the need for imaging institutes centered on disease entities (eg, lung cancer, multiple sclerosis) to not only optimize clinical care and patient outcomes, but also spur the development of a new educational focus, which will increase opportunities for medical trainees and other health professionals. These institutes will also serve as unique environments for testing and implementing new technologies and for generating new ideas for research and health-care delivery. We propose that the imaging institutes focus on how imaging practices-including new innovations-improve patient care outcomes within a specific disease framework. These institutes will allow our specialty to lead patient care, provide the necessary infrastructure for state-of-the art-education of trainees, and stimulate innovative and clinically relevant research.
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28
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PET/CT and urinary cancers: the message from urologists. Clin Transl Imaging 2018. [DOI: 10.1007/s40336-018-0262-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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29
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Chianca V, Albano D, Messina C, Midiri F, Mauri G, Aliprandi A, Catapano M, Pescatori LC, Monaco CG, Gitto S, Pisani Mainini A, Corazza A, Rapisarda S, Pozzi G, Barile A, Masciocchi C, Sconfienza LM. Rotator cuff calcific tendinopathy: from diagnosis to treatment. ACTA BIO-MEDICA : ATENEI PARMENSIS 2018; 89:186-196. [PMID: 29350647 PMCID: PMC6179075 DOI: 10.23750/abm.v89i1-s.7022] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Accepted: 01/12/2018] [Indexed: 12/15/2022]
Abstract
Rotator cuff calcific tendinopathy (RCCT) is a very common condition caused by the presence of calcific deposits in the rotator cuff (RC) or in the subacromial-subdeltoid (SASD) bursa when calcification spreads around the tendons. The pathogenetic mechanism of RCCT is still unclear. It seems to be related to cell-mediated disease in which metaplastic transformation of tenocytes into chondrocytes induces calcification inside the tendon of the RC. RCCT is a frequent finding in the RC that may cause significant shoulder pain and disability. It can be easily diagnosed with imaging studies as conventional radiography (CR) or ultrasound (US). Conservative management of RCCT usually involves rest, physical therapy, and oral NSAIDs administration. Imaging-guided treatments are currently considered minimally-invasive, yet effective methods to treat RCCT with about 80% success rate. Surgery remains the most invasive treatment option in chronic cases that fail to improve with other less invasive approaches. (www.actabiomedica.it)
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Arrigoni F, Bruno F, Zugaro L, Natella R, Cappabianca S, Russo U, Papapietro VR, Splendiani A, Di Cesare E, Masciocchi C, Barile A. Developments in the management of bone metastases with interventional radiology. ACTA BIO-MEDICA : ATENEI PARMENSIS 2018; 89:166-174. [PMID: 29350645 PMCID: PMC6179078 DOI: 10.23750/abm.v89i1-s.7020] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Accepted: 01/12/2018] [Indexed: 01/08/2023]
Abstract
Interventional radiology has known an exponential growth in the last years. Technological advances of the last decades, have made it possible to use new treatments on a larger scale, with safe and effective results. They could be considered as palliative treatments for painful lesions but also curative procedures, as single treatment or specially in combination with other techniques (surgery, radiation and oncology therapies, etc.).The main diffuse techniques are those of thermal ablation that destroy the target lesion through the heat; however there are also endovascular therapies that destroy the target tissue thanks to devascularization. Finally the is also the possibility to stabilize pathological fractures or impending fractures. In this paper all the most diffuse and effective techniques are reviewed and also a discussion of the main indications is done, with an analisys of the success and complications rates.
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31
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Sardanelli F, Alì M, Hunink MG, Houssami N, Sconfienza LM, Di Leo G. To share or not to share? Expected pros and cons of data sharing in radiological research. Eur Radiol 2018; 28:2328-2335. [PMID: 29349697 DOI: 10.1007/s00330-017-5165-5] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2017] [Revised: 10/06/2017] [Accepted: 10/31/2017] [Indexed: 01/20/2023]
Abstract
The aims of this paper are to illustrate the trend towards data sharing, i.e. the regulated availability of the original patient-level data obtained during a study, and to discuss the expected advantages (pros) and disadvantages (cons) of data sharing in radiological research. Expected pros include the potential for verification of original results with alternative or supplementary analyses (including estimation of reproducibility), advancement of knowledge by providing new results by testing new hypotheses (not explored by the original authors) on pre-existing databases, larger scale analyses based on individual-patient data, enhanced multidisciplinary cooperation, reduced publication of false studies, improved clinical practice, and reduced cost and time for clinical research. Expected cons are outlined as the risk that the original authors could not exploit the entire potential of the data they obtained, possible failures in patients' privacy protection, technical barriers such as the lack of standard formats, and possible data misinterpretation. Finally, open issues regarding data ownership, the role of individual patients, advocacy groups and funding institutions in decision making about sharing of data and images are discussed. KEY POINTS • Regulated availability of patient-level data of published clinical studies (data-sharing) is expected. • Expected benefits include verification/advancement of knowledge, reduced cost/time of research, clinical improvement. • Potential drawbacks include faults in patients' identity protection and data misinterpretation.
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Affiliation(s)
- Francesco Sardanelli
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via L. Mangiagalli 31, 20133, Milan, Italy. .,Radiology Unit, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese Milan, Italy.
| | - Marco Alì
- PhD Course in Integrative Biomedical Research, Università degli Studi di Milano, Via L. Mangiagalli 31, 20133, Milan, Italy
| | - Myriam G Hunink
- Departments of Radiology and Epidemiology, Erasmus University Medical Center, PO Box 2040, Rotterdam, The Netherlands.,Department of Health Policy and Medicine, Harvard School of Public Health, Harvard University, 677 Huntington Avenue, Boston, MA, 02115, USA
| | - Nehmat Houssami
- Screening and Test Evaluation Program, School of Public Health, Sydney Medical School, University of Sydney, Edward Ford Building, Room A27, Sydney, NSW, 2006, Australia
| | - Luca M Sconfienza
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via L. Mangiagalli 31, 20133, Milan, Italy.,Unit of Diagnostic and Interventional Radiology, IRCCS Istituto Ortopedico Galeazzi, Via Riccardo Galeazzi 4, 20161, Milan, Italy
| | - Giovanni Di Leo
- Radiology Unit, IRCCS Policlinico San Donato, Via Morandi 30, 20097, San Donato Milanese Milan, Italy
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Chianca V, Albano D, Messina C, Cinnante CM, Triulzi FM, Sardanelli F, Sconfienza LM. Diffusion tensor imaging in the musculoskeletal and peripheral nerve systems: from experimental to clinical applications. Eur Radiol Exp 2017; 1:12. [PMID: 29708174 PMCID: PMC5909344 DOI: 10.1186/s41747-017-0018-1] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2017] [Accepted: 08/01/2017] [Indexed: 12/14/2022] Open
Abstract
Magnetic resonance imaging (MRI) is a well-established imaging modality which is used in all districts of the musculoskeletal and peripheral nerve systems. More recently, initial studies have applied multiparametric MRI to evaluate quantitatively different aspects of musculoskeletal and peripheral nerve diseases, thus providing not only images but also numbers and clinical data. Besides 1H and 31P magnetic resonance spectroscopy, diffusion-weighted imaging (DWI) and blood oxygenation level-dependent imaging, diffusion tensor imaging (DTI) is a relatively new MRI-based technique relying on principles of DWI, which has traditionally been used mainly for evaluating the central nervous system to track fibre course. In the musculoskeletal and peripheral nerve systems, DTI has been mostly used in experimental settings, with still few indications in clinical practice. In this review, we describe the potential use of DTI to evaluate different musculoskeletal and peripheral nerve conditions, emphasising the translational aspects of this technique from the experimental to the clinical setting.
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Affiliation(s)
- Vito Chianca
- 1Department of Advanced Biomedical Sciences, Università Federico II, Via Pansini 5, 80131 11 Napoli, Italy
| | - Domenico Albano
- 2Department of Radiology, DIBIMED, Università di Palermo, Via del Vespro 127, 90127 Palermo, Italy
| | - Carmelo Messina
- 7Unit of Diagnostic and Interventional Radiology, IRCCS Istituto Ortopedico Galeazzi, Via Riccardo Galeazzi 4, 20161 Milano, Italy
| | - Claudia Maria Cinnante
- 3Unit of Neuroradiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Francesco Sforza 35, 20122 Milano, Italy
| | - Fabio Maria Triulzi
- 3Unit of Neuroradiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Francesco Sforza 35, 20122 Milano, Italy.,5Department of Pathophysiology and Transplantation, Università degli Studi di Milano, Via Festa del Perdono 7, 20122 Milano, Italy
| | - Francesco Sardanelli
- 4Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097 San Donato Milanese, Italy.,6Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, 20122 Milano, Italy
| | - Luca Maria Sconfienza
- 6Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133, 20122 Milano, Italy.,7Unit of Diagnostic and Interventional Radiology, IRCCS Istituto Ortopedico Galeazzi, Via Riccardo Galeazzi 4, 20161 Milano, Italy
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