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Özgül HA, Akin IB, Mutlu U, Balci A. Diagnostic value of machine learning-based computed tomography texture analysis for differentiating multiple myeloma from osteolytic metastatic bone lesions in the peripheral skeleton. Skeletal Radiol 2023; 52:1703-1711. [PMID: 37014470 DOI: 10.1007/s00256-023-04333-4] [Citation(s) in RCA: 1] [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: 12/28/2022] [Revised: 03/25/2023] [Accepted: 03/26/2023] [Indexed: 04/05/2023]
Abstract
OBJECTIVES To report the diagnostic performance of machine learning-based CT texture analysis for differentiating multiple myeloma from osteolytic metastatic bone lesions in the peripheral skeleton. METHODS We retrospectively evaluated 172 patients with multiple myeloma (n = 70) and osteolytic metastatic bone lesions (n = 102) in the peripheral skeleton. Two radiologists individually used two-dimensional manual segmentation to extract texture features from non-contrast CT. In total, 762 radiomic features were extracted. Dimension reduction was performed in three stages: inter-observer agreement analysis, collinearity analysis, and feature selection. Data were randomly divided into training (n = 120) and test (n = 52) groups. Eight machine learning algorithms were used for model development. The primary performance metrics were the area under the receiver operating characteristic curve and accuracy. RESULTS In total, 476 of the 762 texture features demonstrated excellent interobserver agreement. The number of features was reduced to 22 after excluding those with strong collinearity. Of these features, six were included in the machine learning algorithms using the wrapper-based classifier-specific technique. When all eight machine learning algorithms were considered for differentiating multiple myeloma from osteolytic metastatic bone lesions in the peripheral skeleton, the area under the receiver operating characteristic curve and accuracy were 0.776-0.932 and 78.8-92.3%, respectively. The k-nearest neighbors model performed the best, with the area under the receiver operating characteristic curve and accuracy values of 0.902 and 92.3%, respectively. CONCLUSION Machine learning-based CT texture analysis is a promising method for discriminating multiple myeloma from osteolytic metastatic bone lesions.
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Affiliation(s)
- Hakan Abdullah Özgül
- Department of Radiology, Kemalpaşa State Hospital, Kırovası Küme Street, Kemalpaşa, 35730, Izmir, Turkey.
| | - Işıl Başara Akin
- Department of Radiology, Dokuz Eylul University, Faculty of Medicine, Izmir, Turkey
| | - Uygar Mutlu
- Department of Radiology, Yozgat State Hospital, Yozgat, Turkey
| | - Ali Balci
- Department of Radiology, Dokuz Eylul University, Faculty of Medicine, Izmir, Turkey
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Improving protocols for whole-body magnetic resonance imaging: oncological and inflammatory applications. Pediatr Radiol 2022:10.1007/s00247-022-05478-5. [PMID: 35982340 DOI: 10.1007/s00247-022-05478-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 06/16/2022] [Accepted: 07/29/2022] [Indexed: 10/15/2022]
Abstract
Whole-body MRI is increasingly used in the evaluation of a range of oncological and non-oncological diseases in infants, children and adolescents. Technical innovation in MRI scanners, coils and sequences have enabled whole-body MRI to be performed more rapidly, offering large field-of-view imaging suitable for multifocal and multisystem disease processes in a clinically useful timeframe. Together with a lack of ionizing radiation, this makes whole-body MRI especially attractive in the pediatric population. Indications include lesion detection in cancer predisposition syndrome surveillance and in the workup of children with known malignancies, and diagnosis and monitoring of a host of infectious and non-infectious inflammatory conditions. Choosing which patients are most likely to benefit from this technology is crucial, but so is adjusting protocols to the patient and disease to optimize lesion detection. The focus of this review is on protocols and the elements impacting image acquisition in pediatric whole-body MRI. We consider the practical aspects, from scanner and coil selection to patient positioning, single-center generic and indication-specific protocols with technical parameters, motion reduction strategies and post-processing. When optimized, collectively these lead to better standardization of whole-body MRI, and when married to systematic analysis and interpretation, they can improve diagnostic accuracy.
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Treitl KM, Ricke J, Baur-Melnyk A. Whole-body magnetic resonance imaging (WBMRI) versus whole-body computed tomography (WBCT) for myeloma imaging and staging. Skeletal Radiol 2022; 51:43-58. [PMID: 34031705 PMCID: PMC8626374 DOI: 10.1007/s00256-021-03799-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 04/19/2021] [Accepted: 04/25/2021] [Indexed: 02/02/2023]
Abstract
Myeloma-associated bone disease (MBD) develops in about 80-90% of patients and severely affects their quality of life, as it accounts for the majority of mortality and morbidity. Imaging in multiple myeloma (MM) and MBD is of utmost importance in order to detect bone and bone marrow lesions as well as extraosseous soft-tissue masses and complications before the initiation of treatment. It is required for determination of the stage of disease and aids in the assessment of treatment response. Whole-body low-dose computed tomography (WBLDCT) is the key modality to establish the initial diagnosis of MM and is now recommended as reference standard procedure for the detection of lytic destruction in MBD. In contrast, whole-body magnetic resonance imaging (WBMRI) has higher sensitivity for the detection of focal and diffuse plasma cell infiltration patterns of the bone marrow and identifies them prior to osteolytic destruction. It is recommended for the evaluation of spinal and vertebral lesions, while functional, diffusion-weighted MRI (DWI-MRI) is a promising tool for the assessment of treatment response. This review addresses the current improvements and limitations of WBCT and WBMRI for diagnosis and staging in MM, underlining the fact that both modalities offer complementary information. It further summarizes the corresponding radiological findings and novel technological aspects of both modalities.
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Affiliation(s)
- Karla M. Treitl
- grid.5252.00000 0004 1936 973XDepartment of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377 Munich, Germany
| | - Jens Ricke
- grid.5252.00000 0004 1936 973XDepartment of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377 Munich, Germany
| | - Andrea Baur-Melnyk
- grid.5252.00000 0004 1936 973XDepartment of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377 Munich, Germany
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Oprea-Lager DE, Cysouw MC, Boellaard R, Deroose CM, de Geus-Oei LF, Lopci E, Bidaut L, Herrmann K, Fournier LS, Bäuerle T, deSouza NM, Lecouvet FE. Bone Metastases Are Measurable: The Role of Whole-Body MRI and Positron Emission Tomography. Front Oncol 2021; 11:772530. [PMID: 34869009 PMCID: PMC8640187 DOI: 10.3389/fonc.2021.772530] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 11/04/2021] [Indexed: 12/14/2022] Open
Abstract
Metastatic tumor deposits in bone marrow elicit differential bone responses that vary with the type of malignancy. This results in either sclerotic, lytic, or mixed bone lesions, which can change in morphology due to treatment effects and/or secondary bone remodeling. Hence, morphological imaging is regarded unsuitable for response assessment of bone metastases and in the current Response Evaluation Criteria In Solid Tumors 1.1 (RECIST1.1) guideline bone metastases are deemed unmeasurable. Nevertheless, the advent of functional and molecular imaging modalities such as whole-body magnetic resonance imaging (WB-MRI) and positron emission tomography (PET) has improved the ability for follow-up of bone metastases, regardless of their morphology. Both these modalities not only have improved sensitivity for visual detection of bone lesions, but also allow for objective measurements of bone lesion characteristics. WB-MRI provides a global assessment of skeletal metastases and for a one-step "all-organ" approach of metastatic disease. Novel MRI techniques include diffusion-weighted imaging (DWI) targeting highly cellular lesions, dynamic contrast-enhanced MRI (DCE-MRI) for quantitative assessment of bone lesion vascularization, and multiparametric MRI (mpMRI) combining anatomical and functional sequences. Recommendations for a homogenization of MRI image acquisitions and generalizable response criteria have been developed. For PET, many metabolic and molecular radiotracers are available, some targeting tumor characteristics not confined to cancer type (e.g. 18F-FDG) while other targeted radiotracers target specific molecular characteristics, such as prostate specific membrane antigen (PSMA) ligands for prostate cancer. Supporting data on quantitative PET analysis regarding repeatability, reproducibility, and harmonization of PET/CT system performance is available. Bone metastases detected on PET and MRI can be quantitatively assessed using validated methodologies, both on a whole-body and individual lesion basis. Both have the advantage of covering not only bone lesions but visceral and nodal lesions as well. Hybrid imaging, combining PET with MRI, may provide complementary parameters on the morphologic, functional, metabolic and molecular level of bone metastases in one examination. For clinical implementation of measuring bone metastases in response assessment using WB-MRI and PET, current RECIST1.1 guidelines need to be adapted. This review summarizes available data and insights into imaging of bone metastases using MRI and PET.
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Affiliation(s)
- Daniela E. Oprea-Lager
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Matthijs C.F. Cysouw
- Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Christophe M. Deroose
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- Nuclear Medicine, University Hospitals Leuven, Leuven, Belgium
- Nuclear Medicine & Molecular Imaging, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Lioe-Fee de Geus-Oei
- Department of Radiology, Leiden University Medical Center, Leiden, Netherlands
- Biomedical Photonic Imaging Group, University of Twente, Enschede, Netherlands
| | - Egesta Lopci
- Nuclear Medicine Unit, IRCCS – Humanitas Research Hospital, Milan, Italy
| | - Luc Bidaut
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- College of Science, University of Lincoln, Lincoln, United Kingdom
| | - Ken Herrmann
- Department of Nuclear Medicine, University of Duisburg-Essen, and German Cancer Consortium (DKTK)-University Hospital Essen, Essen, Germany
| | - Laure S. Fournier
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- Paris Cardiovascular Research Center (PARCC), Institut National de la Santé et de la Recherche Médicale (INSERM), Radiology Department, Assistance Publique-Hôpitaux de Paris (AP-HP), Hopital europeen Georges Pompidou, Université de Paris, Paris, France
- European Imaging Biomarkers Alliance (EIBALL), European Society of Radiology, Vienna, Austria
| | - Tobias Bäuerle
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Nandita M. deSouza
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- European Imaging Biomarkers Alliance (EIBALL), European Society of Radiology, Vienna, Austria
- Division of Radiotherapy and Imaging, The Institute of Cancer Research and Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Frederic E. Lecouvet
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- Department of Radiology, Institut de Recherche Expérimentale et Clinique (IREC), Cliniques Universitaires Saint Luc, Université Catholique de Louvain (UCLouvain), Brussels, Belgium
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Michoux NF, Ceranka JW, Vandemeulebroucke J, Peeters F, Lu P, Absil J, Triqueneaux P, Liu Y, Collette L, Willekens I, Brussaard C, Debeir O, Hahn S, Raeymaekers H, de Mey J, Metens T, Lecouvet FE. Repeatability and reproducibility of ADC measurements: a prospective multicenter whole-body-MRI study. Eur Radiol 2021; 31:4514-4527. [PMID: 33409773 DOI: 10.1007/s00330-020-07522-0] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Revised: 08/31/2020] [Accepted: 11/13/2020] [Indexed: 12/13/2022]
Abstract
OBJECTIVES Multicenter oncology trials increasingly include MRI examinations with apparent diffusion coefficient (ADC) quantification for lesion characterization and follow-up. However, the repeatability and reproducibility (R&R) limits above which a true change in ADC can be considered relevant are poorly defined. This study assessed these limits in a standardized whole-body (WB)-MRI protocol. METHODS A prospective, multicenter study was performed at three centers equipped with the same 3.0-T scanners to test a WB-MRI protocol including diffusion-weighted imaging (DWI). Eight healthy volunteers per center were enrolled to undergo test and retest examinations in the same center and a third examination in another center. ADC variability was assessed in multiple organs by two readers using two-way mixed ANOVA, Bland-Altman plots, coefficient of variation (CoV), and the upper limit of the 95% CI on repeatability (RC) and reproducibility (RDC) coefficients. RESULTS CoV of ADC was not influenced by other factors (center, reader) than the organ. Based on the upper limit of the 95% CI on RC and RDC (from both readers), a change in ADC in an individual patient must be superior to 12% (cerebrum white matter), 16% (paraspinal muscle), 22% (renal cortex), 26% (central and peripheral zones of the prostate), 29% (renal medulla), 35% (liver), 45% (spleen), 50% (posterior iliac crest), 66% (L5 vertebra), 68% (femur), and 94% (acetabulum) to be significant. CONCLUSIONS This study proposes R&R limits above which ADC changes can be considered as a reliable quantitative endpoint to assess disease or treatment-related changes in the tissue microstructure in the setting of multicenter WB-MRI trials. KEY POINTS • The present study showed the range of R&R of ADC in WB-MRI that may be achieved in a multicenter framework when a standardized protocol is deployed. • R&R was not influenced by the site of acquisition of DW images. • Clinically significant changes in ADC measured in a multicenter WB-MRI protocol performed with the same type of MRI scanner must be superior to 12% (cerebrum white matter), 16% (paraspinal muscle), 22% (renal cortex), 26% (central zone and peripheral zone of prostate), 29% (renal medulla), 35% (liver), 45% (spleen), 50% (posterior iliac crest), 66% (L5 vertebra), 68% (femur), and 94% (acetabulum) to be detected with a 95% confidence level.
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Affiliation(s)
- Nicolas F Michoux
- Institut de Recherche Expérimentale & Clinique (IREC) - Radiology Department, Université Catholique de Louvain (UCLouvain) - Cliniques Universitaires Saint Luc, Avenue Hippocrate 10, B-1200, Brussels, Belgium.
| | - Jakub W Ceranka
- Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Jef Vandemeulebroucke
- Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Frank Peeters
- Institut de Recherche Expérimentale & Clinique (IREC) - Radiology Department, Université Catholique de Louvain (UCLouvain) - Cliniques Universitaires Saint Luc, Avenue Hippocrate 10, B-1200, Brussels, Belgium
| | - Pierre Lu
- Institut de Recherche Expérimentale & Clinique (IREC) - Radiology Department, Université Catholique de Louvain (UCLouvain) - Cliniques Universitaires Saint Luc, Avenue Hippocrate 10, B-1200, Brussels, Belgium
| | - Julie Absil
- Radiology Department, Université libre de Bruxelles, Hôpital Erasme, Brussels, Belgium
| | - Perrine Triqueneaux
- Institut de Recherche Expérimentale & Clinique (IREC) - Radiology Department, Université Catholique de Louvain (UCLouvain) - Cliniques Universitaires Saint Luc, Avenue Hippocrate 10, B-1200, Brussels, Belgium
| | - Yan Liu
- European Organisation for Research and Treatment of Cancer, Brussels, Belgium
| | - Laurence Collette
- European Organisation for Research and Treatment of Cancer, Brussels, Belgium
| | | | | | - Olivier Debeir
- LISA (Laboratories of Image Synthesis and Analysis), Ecole Polytechnique de Bruxelles, Université libre de Bruxelles, Brussels, Belgium
| | - Stephan Hahn
- LISA (Laboratories of Image Synthesis and Analysis), Ecole Polytechnique de Bruxelles, Université libre de Bruxelles, Brussels, Belgium
| | | | | | - Thierry Metens
- Radiology Department, Université libre de Bruxelles, Hôpital Erasme, Brussels, Belgium
| | - Frédéric E Lecouvet
- Institut de Recherche Expérimentale & Clinique (IREC) - Radiology Department, Université Catholique de Louvain (UCLouvain) - Cliniques Universitaires Saint Luc, Avenue Hippocrate 10, B-1200, Brussels, Belgium
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Latifoltojar A, Duncan MKJ, Klusmann M, Sidhu H, Bainbridge A, Neriman D, Fraioli F, Lambert J, Ardeshna KM, Punwani S. Whole Body 3.0 T Magnetic Resonance Imaging in Lymphomas: Comparison of Different Sequence Combinations for Staging Hodgkin's and Diffuse Large B Cell Lymphomas. J Pers Med 2020; 10:E284. [PMID: 33339372 PMCID: PMC7765916 DOI: 10.3390/jpm10040284] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2020] [Revised: 12/09/2020] [Accepted: 12/11/2020] [Indexed: 11/16/2022] Open
Abstract
To investigate the diagnostic value of different whole-body magnetic resonance imaging (WB-MRI) protocols for staging Hodgkin and diffuse-large B-cell lymphomas (HL and DLBCL), twenty-two patients (M/F 12/10, median age 32, range 22-87, HL/DLBCL 14/8) underwent baseline WB-MRI and 18F-2-fluoro-2-deoxy-D-glucose (18F-FDG) positron emission tomography (PET) fused with computed tomography (CT) scan 18F-FDG-PET-CT. The 3.0 T WB-MRI was performed using pre-contrast modified Dixon (mDixon), T2-weighted turbo-spin-echo (TSE), diffusion-weighted-imaging (DWI), dynamic-contrast-enhanced (DCE) liver/spleen, contrast-enhanced (CE) lung MRI and CE whole-body mDixon. WB-MRI scans were divided into: (1) "WB-MRI DWI+IP": whole-body DWI + in-phase mDixon (2) "WB-MRI T2-TSE": whole-body T2-TSE (3) "WB-MRI Post-C": whole-body CE mDixon + DCE liver/spleen and CE lung mDixon (4) "WB-MRI All ": the entire protocol. Two radiologists evaluated WB-MRIs at random, independently and then in consensus. Two nuclear-medicine-physicians reviewed 18F-FDG PET-CT in consensus. An enhanced-reference-standard (ERS) was derived using all available baseline and follow-up imaging. The sensitivity and specificity of WB-MRI protocols for nodal and extra-nodal staging was derived against the ERS. Agreement between the WB-MRI protocols and the ERS for overall staging was assessed using kappa statistic. For consensus WB-MRI, the sensitivity and specificity for nodal staging were 75%, 98% for WB-MRI DWI+IP, 76%, 98% for WB-MRI Post-C, 83%, 99% for WB-MRI T2-TSE and 87%, 100% for WB-MRI All. The sensitivity and specificity for extra-nodal staging were 67% 100% for WB-MRI DWI+IP, 89%, 100% for WB-MRI Post-C, 89%, 100% for WB-MRI T2-TSE and 100%, 100% for the WB-MRI All. The consensus WB-MRI All read had perfect agreement with the ERS for overall staging [kappa = 1.00 (95% CI: 1.00-1.00)]. The best diagnostic performance is achieved combining all available WB-MRI sequences.
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Affiliation(s)
- Arash Latifoltojar
- Centre for Medical Imaging, University College London, 2nd Floor Charles Bell House, 43-45 Foley Street, London W1W 7TS, UK; (A.L.); (H.S.)
- The Royal Marsden Hospital, Downs road, Sutton, Surrey SM2 5PT, UK
| | - Mark K. J. Duncan
- Department of Radiology, University College London Hospitals NHS Foundation Trust, 235 Euston Road, London NW1 2BU, UK; (M.K.J.D.); (M.K.)
| | - Maria Klusmann
- Department of Radiology, University College London Hospitals NHS Foundation Trust, 235 Euston Road, London NW1 2BU, UK; (M.K.J.D.); (M.K.)
| | - Harbir Sidhu
- Centre for Medical Imaging, University College London, 2nd Floor Charles Bell House, 43-45 Foley Street, London W1W 7TS, UK; (A.L.); (H.S.)
- Department of Radiology, University College London Hospitals NHS Foundation Trust, 235 Euston Road, London NW1 2BU, UK; (M.K.J.D.); (M.K.)
| | - Alan Bainbridge
- Department of Medical Physics and Biomedical Engineering, University College London Hospitals NHS Foundation Trust, 235 Euston Road, London NW1 2BU, UK;
| | - Deena Neriman
- Institute of Nuclear Medicine, University College London Hospitals NHS Foundation Trust, 235 Euston Road, London NW1 2BU, UK; (D.N.); (F.F.)
| | - Francesco Fraioli
- Institute of Nuclear Medicine, University College London Hospitals NHS Foundation Trust, 235 Euston Road, London NW1 2BU, UK; (D.N.); (F.F.)
| | - Jonathan Lambert
- Department of Haematology, University College London Hospitals NHS Foundation Trust, 235 Euston Road, London NW1 2BU, UK; (J.L.); (K.M.A.)
| | - Kirit M. Ardeshna
- Department of Haematology, University College London Hospitals NHS Foundation Trust, 235 Euston Road, London NW1 2BU, UK; (J.L.); (K.M.A.)
| | - Shonit Punwani
- Centre for Medical Imaging, University College London, 2nd Floor Charles Bell House, 43-45 Foley Street, London W1W 7TS, UK; (A.L.); (H.S.)
- Department of Radiology, University College London Hospitals NHS Foundation Trust, 235 Euston Road, London NW1 2BU, UK; (M.K.J.D.); (M.K.)
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