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Jager A, Oddens JR, Postema AW, Miclea RL, Schoots IG, Nooijen PGTA, van der Linden H, Barentsz JO, Heijmink SWTPJ, Wijkstra H, Mischi M, Turco S. Is There an Added Value of Quantitative DCE-MRI by Magnetic Resonance Dispersion Imaging for Prostate Cancer Diagnosis? Cancers (Basel) 2024; 16:2431. [PMID: 39001493 PMCID: PMC11240399 DOI: 10.3390/cancers16132431] [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: 05/23/2024] [Revised: 06/25/2024] [Accepted: 06/26/2024] [Indexed: 07/16/2024] Open
Abstract
In this multicenter, retrospective study, we evaluated the added value of magnetic resonance dispersion imaging (MRDI) to standard multiparametric MRI (mpMRI) for PCa detection. The study included 76 patients, including 51 with clinically significant prostate cancer (csPCa), who underwent radical prostatectomy and had an mpMRI including dynamic contrast-enhanced MRI. Two radiologists performed three separate randomized scorings based on mpMRI, MRDI and mpMRI+MRDI. Radical prostatectomy histopathology was used as the reference standard. Imaging and histopathology were both scored according to the Prostate Imaging-Reporting and Data System V2.0 sector map. Sensitivity and specificity for PCa detection were evaluated for mpMRI, MRDI and mpMRI+MRDI. Inter- and intra-observer variability for both radiologists was evaluated using Cohen's Kappa. On a per-patient level, sensitivity for csPCa for radiologist 1 (R1) for mpMRI, MRDI and mpMRI+MRDI was 0.94, 0.82 and 0.94, respectively. For the second radiologist (R2), these were 0.78, 0.94 and 0.96. R1 detected 4% additional csPCa cases using MRDI compared to mpMRI, and R2 detected 20% extra csPCa cases using MRDI. Inter-observer agreement was significant only for MRDI (Cohen's Kappa = 0.4250, p = 0.004). The results of this study show the potential of MRDI to improve inter-observer variability and the detection of csPCa.
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Affiliation(s)
- Auke Jager
- Department of Urology, Amsterdam UMC, University of Amsterdam, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Jorg R Oddens
- Department of Urology, Amsterdam UMC, University of Amsterdam, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
- Department of Electrical Engineering, Eindhoven University of Technology, 5612 AP Eindhoven, The Netherlands
| | - Arnoud W Postema
- Leiden University Medical Center, Department of Urology, 2333 ZA Leiden, The Netherlands
| | - Razvan L Miclea
- Department of Radiology and Nuclear Imaging, Maastricht University Medical Centre+, 6229 HX Maastricht, The Netherlands
| | - Ivo G Schoots
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands
- Department of Radiology, Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
| | - Peet G T A Nooijen
- Department of Pathology, Jeroen Bosch Hospital, 5223 GZ 's-Hertogenbosch, The Netherlands
| | - Hans van der Linden
- Department of Pathology, Jeroen Bosch Hospital, 5223 GZ 's-Hertogenbosch, The Netherlands
| | - Jelle O Barentsz
- Department of Radiology, Radboud University Nijmegen Medical Center, 6525 GA Nijmegenfi, The Netherlands
| | - Stijn W T P J Heijmink
- Department of Radiology, Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
| | - Hessel Wijkstra
- Department of Electrical Engineering, Eindhoven University of Technology, 5612 AP Eindhoven, The Netherlands
| | - Massimo Mischi
- Department of Electrical Engineering, Eindhoven University of Technology, 5612 AP Eindhoven, The Netherlands
| | - Simona Turco
- Department of Electrical Engineering, Eindhoven University of Technology, 5612 AP Eindhoven, The Netherlands
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Hellstern M, Martinez C, Wallenhorst C, Beyersdorff D, Lüdemann L, Grimm MO, Teichgräber U, Franiel T. Optimal length and temporal resolution of dynamic contrast-enhanced MR imaging for the differentiation between prostate cancer and normal peripheral zone tissue. PLoS One 2023; 18:e0287651. [PMID: 37352312 PMCID: PMC10289347 DOI: 10.1371/journal.pone.0287651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Accepted: 06/12/2023] [Indexed: 06/25/2023] Open
Abstract
The value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in the detection of prostate cancer is controversial. There are currently insufficient peer reviewed published data or expert consensus to support routine adoption of DCE-MRI for clinical use. Thus, the objective of this study was to explore the optimal temporal resolution and measurement length for DCE-MRI to differentiate cancerous from normal prostate tissue of the peripheral zone of the prostate by non-parametric MRI analysis and to compare with a quantitative MRI analysis. Predictors of interest were onset time, relative signal intensity (RSI), wash-in slope, peak enhancement, wash-out and wash-out slope determined from non-parametric characterisation of DCE-MRI intensity-time profiles. The discriminatory power was estimated from C-statistics based on cross validation. We analyzed 54 patients with 97 prostate tissue specimens (47 prostate cancer, 50 normal prostate tissue) of the peripheral zone, mean age 63.8 years, mean prostate-specific antigen 18.9 ng/mL and mean of 10.5 days between MRI and total prostatectomy. When comparing prostate cancer tissue with normal prostate tissue, median RSI was 422% vs 330%, and wash-in slope 0.870 vs 0.539. The peak enhancement of 67 vs 42 was higher with prostate cancer tissue, while wash-out (-30% vs -23%) and wash-out slope (-0.037 vs -0.029) were lower, and the onset time (32 seconds) was comparable. The optimal C-statistics was 0.743 for temporal resolution of 8.0 seconds and measurement length of 2.5 minutes compared with 0.656 derived from a quantitative MRI analysis. This study provides evidence that the use of a non-parametric approach instead of a more established parametric approach resulted in greater precision to differentiate cancerous from normal prostate tissue of the peripheral zone of the prostate.
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Affiliation(s)
- Marius Hellstern
- Bürgerhospital und Clementin Kinderhospital gGmbH, Frankfurt am Main, Germany
| | - Carlos Martinez
- Institute for Epidemiology, Statistics and Informatics GmbH, Frankfurt am Main, Germany
| | | | - Dirk Beyersdorff
- Department of Diagnostic and Interventional Radiology, University Hospital Hamburg Eppendorf, Hamburg, Germany
| | - Lutz Lüdemann
- Department of Medical Physics, Essen University Hospital, Essen, Germany
| | - Marc-Oliver Grimm
- Klinik und Poliklinik für Urologie Universitätsklinikum Jena, Jena, Germany
| | - Ulf Teichgräber
- Institut für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Jena, Jena, Germany
| | - Tobias Franiel
- Institut für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Jena, Jena, Germany
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Singla A, Deep N, Naik S, Mohakud S, Nayak P, Sable M. Correlation of multiparametric MRI with histopathological grade of peripheral zone prostate carcinoma. J Cancer Res Ther 2023; 19:S569-S576. [PMID: 38384020 DOI: 10.4103/jcrt.jcrt_280_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Accepted: 07/06/2022] [Indexed: 02/23/2024]
Abstract
BACKGROUND Prostatic cancer is the second most common malignant tumor in men. Preoperative grading of prostate cancer is important for its management. Our objective is to compare individual and combined detection rates of T2-weighted imaging (T2WI), diffusion weighted imaging (DWI), dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI), and magnetic resonance spectroscopy (MRS) for prostate cancer with histopathological diagnosis as its golden standard. METHODS Forty-four patients with positive digital rectal examination (DRE) findings and elevated prostate specific antigen (PSA), underwent multiparametric MRI (Mp-MRI). T2WI, DWI, DCE-MRI and MRS were done in all the patients. Cognitive magnetic resonance-transrectal ultrasound (MR-TRUS) fusion biopsy was done in all the patients. Sensitivity and specificity of T2WI, DWI, DCE-MRI, and Prostate Imaging - Reporting and Data System PIRADS version 2 was obtained. Apparent diffusion coefficient (ADC) value and choline/citrate ratio were obtained for each lesion and correlated with histopathological grade. RESULTS The mean age of the patients was 68.7 ± 10.1 years, and the mean serum PSA level was 58.1 ± 22.4 ng/dL. Of the 38 lesions in peripheral zone, 33 (87%) had histopathologically proven prostate cancer. T2WI had a sensitivity and specificity of 75.8% and 80% and DWI had a sensitivity and specificity of 90.9% and 80%, respectively, for detection of malignant prostatic lesion. The mean ADC values for prostate cancer, prostatitis, and normal prostatic parenchyma were 0.702 ± 0.094 × 10-3 mm2/sec, 0.959 ± 0.171 × 10-3 mm2/sec, and 1.31 ± 0.223 × 10-3 mm2/sec, respectively. Type 3 curve has lower sensitivity (45.5%) but high specificity (80%) for diagnosing prostate cancer. CONCLUSION DWI can be useful to differentiate benign from malignant prostatic lesions, and low-grade from high-grade prostate carcinoma. ADC value has a positive correlation with histopathological grade of prostate cancer.
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Affiliation(s)
- Amit Singla
- Department of Radiodiagnosis, All India Institute of Medical Sciences, Bhubaneswar, Odisha, India
| | - Nerbadyswari Deep
- Department of Radiodiagnosis, All India Institute of Medical Sciences, Bhubaneswar, Odisha, India
| | - Suprava Naik
- Department of Radiodiagnosis, All India Institute of Medical Sciences, Bhubaneswar, Odisha, India
| | - Sudipta Mohakud
- Department of Radiodiagnosis, All India Institute of Medical Sciences, Bhubaneswar, Odisha, India
| | - Prasant Nayak
- Department of Urology, All India Institute of Medical Sciences, Bhubaneswar, Odisha, India
| | - Mukund Sable
- Department of Pathology, All India Institute of Medical Sciences, Bhubaneswar, Odisha, India
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Reynolds HM, Tadimalla S, Wang YF, Montazerolghaem M, Sun Y, Williams S, Mitchell C, Finnegan ME, Murphy DG, Haworth A. Semi-quantitative and quantitative dynamic contrast-enhanced (DCE) MRI parameters as prostate cancer imaging biomarkers for biologically targeted radiation therapy. Cancer Imaging 2022; 22:71. [PMID: 36536464 PMCID: PMC9762110 DOI: 10.1186/s40644-022-00508-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Accepted: 12/07/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Biologically targeted radiation therapy treatment planning requires voxel-wise characterisation of tumours. Dynamic contrast enhanced (DCE) DCE MRI has shown promise in defining voxel-level biological characteristics. In this study we consider the relative value of qualitative, semi-quantitative and quantitative assessment of DCE MRI compared with diffusion weighted imaging (DWI) and T2-weighted (T2w) imaging to detect prostate cancer at the voxel level. METHODS Seventy prostate cancer patients had multiparametric MRI prior to radical prostatectomy, including T2w, DWI and DCE MRI. Apparent Diffusion Coefficient (ADC) maps were computed from DWI, and semi-quantitative and quantitative parameters computed from DCE MRI. Tumour location and grade were validated with co-registered whole mount histology. Kolmogorov-Smirnov tests were applied to determine whether MRI parameters in tumour and benign voxels were significantly different. Cohen's d was computed to quantify the most promising biomarkers. The Parker and Weinmann Arterial Input Functions (AIF) were compared for their ability to best discriminate between tumour and benign tissue. Classifier models were used to determine whether DCE MRI parameters improved tumour detection versus ADC and T2w alone. RESULTS All MRI parameters had significantly different data distributions in tumour and benign voxels. For low grade tumours, semi-quantitative DCE MRI parameter time-to-peak (TTP) was the most discriminating and outperformed ADC. For high grade tumours, ADC was the most discriminating followed by DCE MRI parameters Ktrans, the initial rate of enhancement (IRE), then TTP. Quantitative parameters utilising the Parker AIF better distinguished tumour and benign voxel values than the Weinmann AIF. Classifier models including DCE parameters versus T2w and ADC alone, gave detection accuracies of 78% versus 58% for low grade tumours and 85% versus 72% for high grade tumours. CONCLUSIONS Incorporating DCE MRI parameters with DWI and T2w gives improved accuracy for tumour detection at a voxel level. DCE MRI parameters should be used to spatially characterise tumour biology for biologically targeted radiation therapy treatment planning.
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Affiliation(s)
- Hayley M Reynolds
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.
| | | | - Yu-Feng Wang
- School of Physics, The University of Sydney, Sydney, NSW, Australia
| | | | - Yu Sun
- School of Physics, The University of Sydney, Sydney, NSW, Australia
| | - Scott Williams
- Division of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC, Australia
| | - Catherine Mitchell
- Department of Pathology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Mary E Finnegan
- Department of Imaging, Imperial College Healthcare NHS Trust, London, UK
- Department of Bioengineering, Imperial College London, London, UK
| | - Declan G Murphy
- Division of Cancer Surgery, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Annette Haworth
- School of Physics, The University of Sydney, Sydney, NSW, Australia
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Mikoshi A, Miyai K, Hamabe F, Edo H, Ito K, Matsukuma S, Tsuda H, Shinmoto H. MRI-detectability and histological factors of prostate cancer including intraductal carcinoma and cribriform pattern. Prostate 2022; 82:452-463. [PMID: 34964158 DOI: 10.1002/pros.24291] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 11/15/2021] [Accepted: 12/13/2021] [Indexed: 11/11/2022]
Abstract
BACKGROUND Histopathological characteristics affecting the detectability of clinically significant prostate cancer (csPCa) on magnetic resonance imaging (MRI) remain unclear. This study aimed to compare the histopathology between MRI-detectable and MRI-undetectable cancers, emphasizing intraductal carcinoma of the prostate (IDC-P) and predominant Gleason pattern 4 subtype. METHODS This single-center retrospective study enrolled 153 consecutive patients with 191 lesions who underwent preoperative multiparametric MRI and subsequent radical prostatectomy. MRI/histopathological findings and area fractions of histological components (cancer cells, stroma, and luminal spaces) of MRI-detectable and MRI-undetectable cancers were compared. Data were analyzed using Fisher's exact, independent t, or Mann-Whitney U tests. RESULTS Overall, 148 (77%) and 43 (23%) cancers were MRI-detectable and MRI-undetectable, respectively. MRI-detectable cancers were significantly larger than MRI-undetectable cancers (p = 0.03). The percentage of lesions in Grade Group 3 or higher was significantly higher among MRI-detectable cancers than among MRI-undetectable cancers (p = 0.02). MRI detectability of csPCa was associated with increases in relative area fractions of cancer cells (p < 0.001) and decreases in those of stroma (p < 0.001) and luminal spaces (p < 0.001) in prostate cancer (PCa) than the percentage of Gleason pattern 4 (p = 0.09). The percentage of lesions containing IDC-P was similar for MRI-detectable and MRI-undetectable cancers (40% vs. 33%; p = 0.48). The distribution of cribriform gland subtypes was not significantly different between MRI-detectable and MRI-undetectable Gleason pattern 4 subtype cancers (p > 0.99). Contrarily, the ratio of fused gland subtype was significantly higher in MRI-detectable than in MRI-undetectable cancers (p = 0.03). Furthermore, the ratio of poorly-formed gland subtype was significantly higher in MRI-undetectable than in MRI-detectable cancers (p = 0.01). CONCLUSIONS MRI detectability of csPCa is strongly associated with the relative area fractions of cancer cells, stroma, and luminal spaces in PCa rather than conventional histopathological parameters. Neither the presence nor the percentage of IDC-P affected MRI detectability.
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Affiliation(s)
- Ayako Mikoshi
- Department of Radiology, National Defense Medical College, Tokorozawa, Saitama, Japan
| | - Kosuke Miyai
- Department of Basic Pathology, National Defense Medical College, Tokorozawa, Saitama, Japan
- Department of Pathology and Laboratory Medicine, National Defense Medical College, Tokorozawa, Saitama, Japan
| | - Fumiko Hamabe
- Department of Radiology, National Defense Medical College, Tokorozawa, Saitama, Japan
| | - Hiromi Edo
- Department of Radiology, National Defense Medical College, Tokorozawa, Saitama, Japan
| | - Keiichi Ito
- Department of Urology, National Defense Medical College, Tokorozawa, Saitama, Japan
| | - Susumu Matsukuma
- Department of Pathology and Laboratory Medicine, National Defense Medical College, Tokorozawa, Saitama, Japan
| | - Hitoshi Tsuda
- Department of Basic Pathology, National Defense Medical College, Tokorozawa, Saitama, Japan
| | - Hiroshi Shinmoto
- Department of Radiology, National Defense Medical College, Tokorozawa, Saitama, Japan
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Albano D, Bruno F, Agostini A, Angileri SA, Benenati M, Bicchierai G, Cellina M, Chianca V, Cozzi D, Danti G, De Muzio F, Di Meglio L, Gentili F, Giacobbe G, Grazzini G, Grazzini I, Guerriero P, Messina C, Micci G, Palumbo P, Rocco MP, Grassi R, Miele V, Barile A. Dynamic contrast-enhanced (DCE) imaging: state of the art and applications in whole-body imaging. Jpn J Radiol 2021; 40:341-366. [PMID: 34951000 DOI: 10.1007/s11604-021-01223-4] [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: 09/06/2021] [Accepted: 11/17/2021] [Indexed: 12/18/2022]
Abstract
Dynamic contrast-enhanced (DCE) imaging is a non-invasive technique used for the evaluation of tissue vascularity features through imaging series acquisition after contrast medium administration. Over the years, the study technique and protocols have evolved, seeing a growing application of this method across different imaging modalities for the study of almost all body districts. The main and most consolidated current applications concern MRI imaging for the study of tumors, but an increasing number of studies are evaluating the use of this technique also for inflammatory pathologies and functional studies. Furthermore, the recent advent of artificial intelligence techniques is opening up a vast scenario for the analysis of quantitative information deriving from DCE. The purpose of this article is to provide a comprehensive update on the techniques, protocols, and clinical applications - both established and emerging - of DCE in whole-body imaging.
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Affiliation(s)
- Domenico Albano
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- IRCCS Istituto Ortopedico Galeazzi, Milan, Italy
- Dipartimento Di Biomedicina, Neuroscienze E Diagnostica Avanzata, Sezione Di Scienze Radiologiche, Università Degli Studi Di Palermo, via Vetoio 1L'Aquila, 67100, Palermo, Italy
| | - Federico Bruno
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy.
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy.
| | - Andrea Agostini
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Department of Clinical, Special and Dental Sciences, Department of Radiology, University Politecnica delle Marche, University Hospital "Ospedali Riuniti Umberto I - G.M. Lancisi - G. Salesi", Ancona, Italy
| | - Salvatore Alessio Angileri
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Radiology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Massimo Benenati
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Dipartimento di Diagnostica per Immagini, Fondazione Policlinico Universitario A. Gemelli IRCCS, Oncologia ed Ematologia, RadioterapiaRome, Italy
| | - Giulia Bicchierai
- Diagnostic Senology Unit, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Michaela Cellina
- Department of Radiology, ASST Fatebenefratelli Sacco, Ospedale Fatebenefratelli, Milan, Italy
| | - Vito Chianca
- Ospedale Evangelico Betania, Naples, Italy
- Clinica Di Radiologia, Istituto Imaging Della Svizzera Italiana - Ente Ospedaliero Cantonale, Lugano, Switzerland
| | - Diletta Cozzi
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Department of Emergency Radiology, Careggi University Hospital, Florence, Italy
| | - Ginevra Danti
- Department of Emergency Radiology, Careggi University Hospital, Florence, Italy
| | - Federica De Muzio
- Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, Campobasso, Italy
| | - Letizia Di Meglio
- Postgraduation School in Radiodiagnostics, University of Milan, Milan, Italy
| | - Francesco Gentili
- Unit of Diagnostic Imaging, Azienda Ospedaliera Universitaria Senese, Siena, Italy
| | - Giuliana Giacobbe
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Department of Precision Medicine, University of Campania "L. Vanvitelli", Naples, Italy
| | - Giulia Grazzini
- Department of Radiology, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Irene Grazzini
- Department of Radiology, Section of Neuroradiology, San Donato Hospital, Arezzo, Italy
| | - Pasquale Guerriero
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, Campobasso, Italy
| | | | - Giuseppe Micci
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Dipartimento Di Biomedicina, Neuroscienze E Diagnostica Avanzata, Sezione Di Scienze Radiologiche, Università Degli Studi Di Palermo, via Vetoio 1L'Aquila, 67100, Palermo, Italy
| | - Pierpaolo Palumbo
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Abruzzo Health Unit 1, Department of diagnostic Imaging, Area of Cardiovascular and Interventional Imaging, L'Aquila, Italy
| | - Maria Paola Rocco
- Department of Precision Medicine, University of Campania "L. Vanvitelli", Naples, Italy
| | - Roberto Grassi
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Department of Precision Medicine, University of Campania "L. Vanvitelli", Naples, Italy
| | - Vittorio Miele
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Department of Radiology, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Antonio Barile
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
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Li X, Wang Q, Dou Y, Zhang Y, Tao J, Yang L, Wang S. Soft tissue sarcoma: can dynamic contrast-enhanced (DCE) MRI be used to predict the histological grade? Skeletal Radiol 2020; 49:1829-1838. [PMID: 32519183 DOI: 10.1007/s00256-020-03491-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2020] [Revised: 05/25/2020] [Accepted: 05/25/2020] [Indexed: 02/02/2023]
Abstract
OBJECTIVE To determine if dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) parameters reflect histological grade of soft tissue sarcoma (STS) MATERIALS AND METHODS: The medical records of 50 patients diagnosed with pathologically confirmed STS were retrospectively reviewed. Each STS was assessed with conventional contrast-enhanced MRI and DCE-MRI using a 3.0-T MRI system. The conventional MRI characteristics of low-grade (grade 1) and high-grade (grade 2 and grade 3) tumors were analyzed. Semi-quantitative parameters, including iAUC and TTP, and quantitative parameters, including Ktrans, Kep, and Ve, were derived from DCE-MRI. The diagnostic performances and optimal thresholds of various combinations of DCE-MRI parameters for predicting histological grades of STS were investigated using receiver operator characteristic (ROC) curves. RESULTS On conventional MRI, high-grade STSs were significantly larger (≥ 5 cm) and more likely to show a heterogeneous signal intensity on T2WI (> 75%), peritumoral hyperintensity on T2WI, or tumor necrosis (> 50%) compared with low-grade STS. On DCE-MRI, iAUC, TTP, Ktrans, and Kep were significant predictors of STS histological grade. Ktrans had a high diagnostic value for differentiating between high-grade and low-grade STSs. The combination of iAUC, TTP, and Ktrans yielded a higher AUC value (0.841) than the other models. CONCLUSION High-grade STSs were usually larger than low-grade STSs, had unclear boundaries, a heterogeneous signal intensity on T2-weighted image (T2WI), and extensive necrosis. On DCE-MRI, iAUC, TTP, Ktrans, and Kep could differentiate between high-grade and low-grade STSs. The combination of iAUC, TTP, and Ktrans had a high diagnostic performance for differentiating between STS histological grades.
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Affiliation(s)
- Xiangwen Li
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, Liaoning Province, China
| | - Qimeng Wang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, Liaoning Province, China
| | - Yanping Dou
- Department of Ultrasound, The First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Yu Zhang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, Liaoning Province, China
| | - Juan Tao
- Department of Pathology, The Second Hospital, Dalian Medical University, Dalian, China
| | - Lin Yang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, Liaoning Province, China
| | - Shaowu Wang
- Department of Radiology, The Second Hospital, Dalian Medical University, Dalian, Liaoning Province, China.
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Prostatitis, the Great Mimicker of Prostate Cancer: Can We Differentiate Them Quantitatively With Multiparametric MRI? AJR Am J Roentgenol 2020; 215:1104-1112. [PMID: 32901562 DOI: 10.2214/ajr.20.22843] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
OBJECTIVE. The purpose of this study was to investigate the diagnostic performance of semiquantitative and quantitative pharmacokinetic parameters and quantitative apparent diffusion coefficient (ADC) values obtained from prostate multiparametric MRI (mpMRI) to differentiate prostate cancer (PCa) and prostatitis objectively. MATERIALS AND METHODS. We conducted a retrospective review of patients with biopsy-proven PCa or prostatitis who underwent mpMRI study between January 2015 and February 2018. Mean ADC, forward volume transfer constant (Ktrans), reverse volume transfer constant (kep), plasma volume fraction (Vp), extravascular extracellular space volume fraction (Ve), and time to peak (TTP) values were calculated for both lesions and contralateral normal prostate tissue. Signal intensity-time curves were analyzed. Lesion-to-normal prostate tissue ratios of pharmacokinetic parameters were also calculated. The diagnostic accuracy and cutoff points of all parameters were analyzed to differentiate PCa from prostatitis. RESULTS. A total of 138 patients (94 with PCa and 44 with prostatitis) were included in the study. Statistically, ADC, quantitative pharmacokinetic parameters (Ktrans, kep, Ve, and Vp), their lesion-to-normal prostate tissue ratios, and TTP values successfully differentiated PCa and prostatitis. Surprisingly, we found that Ve values were significantly higher in prostatitis lesions. The combination of these parameters had 92.7% overall diagnostic accuracy. ADC, kep, and TTP made up the most successful combination for differential diagnosis. Analysis of the signal intensity-time curves showed mostly type 2 and type 3 enhancement curve patterns for patients with PCa. Type 3 curves were not seen in any prostatitis cases. CONCLUSION. Quantitative analysis of mpMRI differentiates PCa from prostatitis with high sensitivity and specificity, appears to have significant potential, and may improve diagnostic accuracy. In addition, evaluating these parameters does not cause any extra burden to the patients.
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Qin J, Yao Q, Ge X, Zhu J, Yin Z, Li X, Li C. Comparative study of imaging and histology of sacroiliac joint in normal rats based on IVIM-DWI and DCE-MRI. BMC Musculoskelet Disord 2020; 21:472. [PMID: 32689978 PMCID: PMC7370526 DOI: 10.1186/s12891-020-03481-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Accepted: 07/06/2020] [Indexed: 12/03/2022] Open
Abstract
Background Currently, few studies have described the relationship between functional MRI findings and histology of normal sacroiliac joint (SIJ). Besides, due to the difficulties in access to SIJ, authentic animal models are important in providing opportunities for quantitative parameter extraction on imaging. Aims This study aimed at exploring the parameters of Intravoxel Incoherent Motion Diffusion-Weighted Imaging (IVIM-DWI) and Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) and comparing them with the histology of the SIJ in normal rats with different ages. Methods A total of thirty 7-week-old male Wistar rats were included in the study. The parameters of IVIM-DWI and DCE-MRI in the bone marrow and the joint space of SIJ were measured at 8, 13, 18, 23, 28, and 33 weeks. The histological analysis of the SIJ was examined using light microscopy. One-way ANOVA was used for statistical analysis. Results The D values in the sacral and iliac bone marrow of normal rats decreased with an increase in age. One-way ANOVA analysis indicated a significant difference in D values in different age groups (P<0.005). The normal values of D*, f, Fenh (%), Senh (%/s) in the sacral bone marrow, the iliac bone marrow, and the joint space in SIJ of normal rats were obtained. The results showed that in the six groups of rats of different ages, the histology of the SIJ surface was smooth and clear, the cartilage cells were intact, and no thickening or pannus formation was observed. Conclusions This study obtained the IVIM-DWI and DCE-MRI parameters of the sacral and iliac bone marrow and the synovial area of the joint space in normal rats. The parameters in normal rats can be used in future research to compare to similar parameters in animal models or patients with SIJ diseases. This study serves as a guide for future research in SIJ diseases.
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Affiliation(s)
- Jian Qin
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, No. 366 Taishan Street, Taian City, 271000, Shandong, China
| | - Qianqian Yao
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, No. 366 Taishan Street, Taian City, 271000, Shandong, China
| | - Xubo Ge
- Department of Radiology, The Fourth People's Hospital of Taian, Taian, 271000, Shandong, China
| | - Jianzhong Zhu
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, No. 366 Taishan Street, Taian City, 271000, Shandong, China
| | - Zhaoliang Yin
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, No. 366 Taishan Street, Taian City, 271000, Shandong, China
| | - Xiaoqian Li
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, No. 366 Taishan Street, Taian City, 271000, Shandong, China
| | - Changqin Li
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, No. 366 Taishan Street, Taian City, 271000, Shandong, China.
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10
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Preclinical Molecular Imaging for Precision Medicine in Breast Cancer Mouse Models. CONTRAST MEDIA & MOLECULAR IMAGING 2019; 2019:8946729. [PMID: 31598114 PMCID: PMC6778915 DOI: 10.1155/2019/8946729] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 04/28/2019] [Accepted: 07/25/2019] [Indexed: 12/18/2022]
Abstract
Precision and personalized medicine is gaining importance in modern clinical medicine, as it aims to improve diagnostic precision and to reduce consequent therapeutic failures. In this regard, prior to use in human trials, animal models can help evaluate novel imaging approaches and therapeutic strategies and can help discover new biomarkers. Breast cancer is the most common malignancy in women worldwide, accounting for 25% of cases of all cancers and is responsible for approximately 500,000 deaths per year. Thus, it is important to identify accurate biomarkers for precise stratification of affected patients and for early detection of responsiveness to the selected therapeutic protocol. This review aims to summarize the latest advancements in preclinical molecular imaging in breast cancer mouse models. Positron emission tomography (PET) imaging remains one of the most common preclinical techniques used to evaluate biomarker expression in vivo, whereas magnetic resonance imaging (MRI), particularly diffusion-weighted (DW) sequences, has been demonstrated as capable of distinguishing responders from nonresponders for both conventional and innovative chemo- and immune-therapies with high sensitivity and in a noninvasive manner. The ability to customize therapies is desirable, as this will enable early detection of diseases and tailoring of treatments to individual patient profiles. Animal models remain irreplaceable in the effort to understand the molecular mechanisms and patterns of oncologic diseases.
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11
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Ioannidis GS, Maris TG, Nikiforaki K, Karantanas A, Marias K. Investigating the Correlation of Ktrans With Semi-Quantitative MRI Parameters Towards More Robust and Reproducible Perfusion Imaging Biomarkers in Three Cancer Types. IEEE J Biomed Health Inform 2019; 23:1855-1862. [DOI: 10.1109/jbhi.2018.2888979] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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12
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Bae H, Cho NH, Park SY. PI-RADS version 2: optimal time range for determining positivity of dynamic contrast-enhanced MRI in peripheral zone prostate cancer. Clin Radiol 2019; 74:895.e27-895.e34. [PMID: 31327469 DOI: 10.1016/j.crad.2019.06.014] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2019] [Accepted: 06/24/2019] [Indexed: 11/30/2022]
Abstract
AIM To analyse the optimal time cut-off for determining positivity of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in peripheral zone (PZ) prostate cancer (PCa). MATERIALS AND METHODS A consecutive series of 89 patients with PZ PCa who had undergone diffusion-weighted imaging (DWI) and subtraction DCE MRI were included. An experienced reader visually analysed the earliest time after contrast medium injection to visualise the best contrast between an index tumour and normal PZ on DCE MRI (i.e., best contrast time). The best contrast time cut-off for clinically significant cancer (csPCa) according to Epstein criteria or International Society of Urological Pathology (ISUP) grade ≥2 was analysed by an experienced reader, and applied to a less-experienced reader. For the index lesion of DWI category 3, the added value of DCE MRI (increased true positive and negative rates of PI-RADSv2 for csPCa) was evaluated using the cut-off time. RESULTS The best contrast time cut-off for csPCa was ≤72 seconds for Epstein criteria and ≤56 seconds for ISUP grade ≥2 by an experienced reader. The weighted kappa to determine positivity of DCE MRI was 0.622 for ≤72 seconds and 0.527 for ≤56 seconds between the two readers. The added value of DCE MRI was 55-75% by an experienced reader and 39.1-69.6% by a less-experienced reader. CONCLUSION For interpreting PI-RADSv2, imaging findings within 60-72 seconds following contrast media injection seem to reliably determine positivity of DCE MRI in PZ, and have added value for detecting csPCa.
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Affiliation(s)
- H Bae
- Department of Radiology, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - N H Cho
- Department of Pathology, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - S Y Park
- Department of Radiology, Yonsei University College of Medicine, Seoul, Republic of Korea; Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
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Cristel G, Esposito A, Briganti A, Damascelli A, Brembilla G, Freschi M, Ambrosi A, Montorsi F, Del Maschio A, De Cobelli F. MpMRI of the prostate: is there a role for semi-quantitative analysis of DCE-MRI and late gadolinium enhancement in the characterisation of prostate cancer? Clin Radiol 2019; 74:259-267. [PMID: 30739715 DOI: 10.1016/j.crad.2018.08.017] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2018] [Accepted: 08/13/2018] [Indexed: 01/19/2023]
Abstract
AIM To assess whether there is a significant difference in perfusion parameters between benign and malignant prostatic lesions, focusing on semi-quantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and presence of late gadolinium enhancement (LGE). MATERIAL AND METHODS Three hundred and thirteen patients who underwent multiparametric MRI (mpMRI) of the prostate and with available corresponding histology (prostatectomy or biopsy) were selected retrospectively for this study. The MRI protocol consisted of multiplanar T2-and diffusion-weighted imaging, DCE and delayed axial T1 images. Images were reviewed independently by two radiologists for LGE assessment and Prostate Imaging - Reporting and Data System (PI-RADS) scoring. For each lesion, semi-quantitative analysis of DCE-MRI was performed and the following data were evaluated: time to peak, wash-in rate, wash-out rate, brevity of enhancement, and area under the curve. The presence or absence of LGE in delayed axial T1 images was assessed qualitatively. MRI results were compared to histology. The presence of significant prostate cancer was based both on Epstein criteria (SPC) and Gleason score (GS ≥7). RESULTS SPC and Gleason score ≥7 tumours showed significant lower time to peak and brevity of enhancement (p<0.001) with higher wash-in rate (p=0.001). LGE was observed in 152/313 (49%) cases; among them 103/152 (68%) did not show SPC whereas 49/152 (32%) had SPC (p<0.001). The presence of LGE determined a risk reduction of SPC resulting as an independent predictor at multivariate analysis (logOR=-0.78, SE 0.33, p=0.02). CONCLUSION Semi-quantitative perfusion analysis and LGE may help to predict the presence/absence of a significant prostate tumour and represent a promising tool to improve mpMRI diagnostic performance.
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Affiliation(s)
- G Cristel
- Department of Radiology, Experimental Imaging Center, San Raffaele Scientific Institute, via Olgettina 60, 20132 Milan, Italy.
| | - A Esposito
- Department of Radiology, Experimental Imaging Center, San Raffaele Scientific Institute, via Olgettina 60, 20132 Milan, Italy; Vita Salute San Raffaele University, via Olgettina 60, 20132 Milan, Italy
| | - A Briganti
- Vita Salute San Raffaele University, via Olgettina 60, 20132 Milan, Italy; Department of Urology, San Raffaele Scientific Institute, via Olgettina 60, 20132 Milan, Italy
| | - A Damascelli
- Department of Radiology, Experimental Imaging Center, San Raffaele Scientific Institute, via Olgettina 60, 20132 Milan, Italy; Vita Salute San Raffaele University, via Olgettina 60, 20132 Milan, Italy
| | - G Brembilla
- Department of Radiology, Experimental Imaging Center, San Raffaele Scientific Institute, via Olgettina 60, 20132 Milan, Italy; Vita Salute San Raffaele University, via Olgettina 60, 20132 Milan, Italy
| | - M Freschi
- Department of Pathology, San Raffaele Scientific Institute, via Olgettina 60, 20132 Milan, Italy
| | - A Ambrosi
- Vita Salute San Raffaele University, via Olgettina 60, 20132 Milan, Italy
| | - F Montorsi
- Vita Salute San Raffaele University, via Olgettina 60, 20132 Milan, Italy; Department of Urology, San Raffaele Scientific Institute, via Olgettina 60, 20132 Milan, Italy
| | - A Del Maschio
- Department of Radiology, Experimental Imaging Center, San Raffaele Scientific Institute, via Olgettina 60, 20132 Milan, Italy; Vita Salute San Raffaele University, via Olgettina 60, 20132 Milan, Italy
| | - F De Cobelli
- Department of Radiology, Experimental Imaging Center, San Raffaele Scientific Institute, via Olgettina 60, 20132 Milan, Italy; Vita Salute San Raffaele University, via Olgettina 60, 20132 Milan, Italy
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14
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Tau N, Berlin A, Yeung I, Halankar J, Murphy G, Jhaveri KS, Ghai S, Metser U. Quantitative assessment of dynamic 18F-flumethycholine PET and dynamic contrast enhanced MRI in high risk prostate cancer. Br J Radiol 2018; 92:20180568. [PMID: 30383459 DOI: 10.1259/bjr.20180568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVE: To describe dynamic 18F-flumethycholine PET (dPET) and dynamic contrast enhancement MR (DCE MR) parameters in localized high-risk prostate cancer (PCa), and determine whether these differ from normal prostate. Furthermore, to determine whether a correlation exists between dPET and DCE MR parameters. METHODS: 41 consenting patients who underwent prostate DCE MR and dPET were included in this institutionally approved study. Intraprostatic lesions on MR were assigned a PI-RADS v2 score, and focal lesions on PET were documented. All lesions were correlated with pathology. Quantitative and semi-quantitative DCE MR and two-tissue compartmental model dPET parameters were determined and tumor-to-normal gland ratios (T/N) for these parameters were calculated. Finally, dPET and DCE MR correlation was estimated using Spearman correlation coefficients. RESULTS: There were 46 malignant lesions per standard of reference. On dPET, peripheral zone (PZ) tumors had higher K1 (p < 0.001), and a T/N ratio ≥2 was significant (p < 0.001). On DCE MR, the parameters in, kep, Ktrans and quantitative iAUC were higher for PZ and non-PZ tumors than corresponding normal tissue (p < 0.001); for PZ tumors, a T/N ratio ≥ 1.5 for Ktrans and pei was significant (p = 0.0019 and 0.0026, respectively). Moderate Spearman correlation (0.40 < ρ < 0.59) was found between dPET K1 and DCE MR Ktrans and pei. CONCLUSION: In patients with high-risk PCa, quantitative dPET and DCE-MR parameters in primary tumors differ from normal tissue. Only moderate correlation exists between K1 (dPET) and Ktrans and pei (DCE MR). The incremental value of any of these parameters to PI-RADS v2 warrants further investigation. ADVANCES IN KNOWLEDGE: Unique quantitative and semi-quantitative FCH PET/MR parameters in PCa differ from normal gland, and should be further investigated to determine their potential contribution to PI-RADS v2 in the detection of clinically significant PCa.
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Affiliation(s)
- Noam Tau
- 1 Joint Department of Medical Imaging, Princess Margaret Hospital, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto , Toronto, ON , Canada
| | - Alejandro Berlin
- 2 Department of Radiation Oncology, University of Toronto and Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network , Toronto, ON , Canada
| | - Ivan Yeung
- 2 Department of Radiation Oncology, University of Toronto and Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network , Toronto, ON , Canada
| | - Jaydeep Halankar
- 1 Joint Department of Medical Imaging, Princess Margaret Hospital, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto , Toronto, ON , Canada
| | - Grainne Murphy
- 1 Joint Department of Medical Imaging, Princess Margaret Hospital, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto , Toronto, ON , Canada
| | - Kartik S Jhaveri
- 1 Joint Department of Medical Imaging, Princess Margaret Hospital, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto , Toronto, ON , Canada
| | - Sangeet Ghai
- 1 Joint Department of Medical Imaging, Princess Margaret Hospital, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto , Toronto, ON , Canada
| | - Ur Metser
- 1 Joint Department of Medical Imaging, Princess Margaret Hospital, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto , Toronto, ON , Canada
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