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Sun H, Wang L, Daskivich T, Qiu S, Han F, D'Agnolo A, Saouaf R, Christodoulou AG, Kim H, Li D, Xie Y. Retrospective T2 quantification from conventional weighted MRI of the prostate based on deep learning. FRONTIERS IN RADIOLOGY 2023; 3:1223377. [PMID: 37886239 PMCID: PMC10598780 DOI: 10.3389/fradi.2023.1223377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 09/28/2023] [Indexed: 10/28/2023]
Abstract
Purpose To develop a deep learning-based method to retrospectively quantify T2 from conventional T1- and T2-weighted images. Methods Twenty-five subjects were imaged using a multi-echo spin-echo sequence to estimate reference prostate T2 maps. Conventional T1- and T2-weighted images were acquired as the input images. A U-Net based neural network was developed to directly estimate T2 maps from the weighted images using a four-fold cross-validation training strategy. The structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), mean percentage error (MPE), and Pearson correlation coefficient were calculated to evaluate the quality of network-estimated T2 maps. To explore the potential of this approach in clinical practice, a retrospective T2 quantification was performed on a high-risk prostate cancer cohort (Group 1) and a low-risk active surveillance cohort (Group 2). Tumor and non-tumor T2 values were evaluated by an experienced radiologist based on region of interest (ROI) analysis. Results The T2 maps generated by the trained network were consistent with the corresponding reference. Prostate tissue structures and contrast were well preserved, with a PSNR of 26.41 ± 1.17 dB, an SSIM of 0.85 ± 0.02, and a Pearson correlation coefficient of 0.86. Quantitative ROI analyses performed on 38 prostate cancer patients revealed estimated T2 values of 80.4 ± 14.4 ms and 106.8 ± 16.3 ms for tumor and non-tumor regions, respectively. ROI measurements showed a significant difference between tumor and non-tumor regions of the estimated T2 maps (P < 0.001). In the two-timepoints active surveillance cohort, patients defined as progressors exhibited lower estimated T2 values of the tumor ROIs at the second time point compared to the first time point. Additionally, the T2 difference between two time points for progressors was significantly greater than that for non-progressors (P = 0.010). Conclusion A deep learning method was developed to estimate prostate T2 maps retrospectively from clinically acquired T1- and T2-weighted images, which has the potential to improve prostate cancer diagnosis and characterization without requiring extra scans.
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Affiliation(s)
- Haoran Sun
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, United States
| | - Lixia Wang
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Timothy Daskivich
- Minimal Invasive Urology, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Shihan Qiu
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, United States
| | - Fei Han
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Alessandro D'Agnolo
- Imaging/Nuclear Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Rola Saouaf
- Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Anthony G. Christodoulou
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, United States
| | - Hyung Kim
- Minimal Invasive Urology, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Debiao Li
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, United States
| | - Yibin Xie
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
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Midya A, Hiremath A, Huber J, Sankar Viswanathan V, Omil-Lima D, Mahran A, Bittencourt LK, Harsha Tirumani S, Ponsky L, Shiradkar R, Madabhushi A. Delta radiomic patterns on serial bi-parametric MRI are associated with pathologic upgrading in prostate cancer patients on active surveillance: preliminary findings. Front Oncol 2023; 13:1166047. [PMID: 37731630 PMCID: PMC10508842 DOI: 10.3389/fonc.2023.1166047] [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: 02/14/2023] [Accepted: 07/24/2023] [Indexed: 09/22/2023] Open
Abstract
Objective The aim of this study was to quantify radiomic changes in prostate cancer (PCa) progression on serial MRI among patients on active surveillance (AS) and evaluate their association with pathologic progression on biopsy. Methods This retrospective study comprised N = 121 biopsy-proven PCa patients on AS at a single institution, of whom N = 50 at baseline conformed to the inclusion criteria. ISUP Gleason Grade Groups (GGG) were obtained from 12-core TRUS-guided systematic biopsies at baseline and follow-up. A biopsy upgrade (AS+) was defined as an increase in GGG (or in number of positive cores) and no upgrade (AS-) was defined when GGG remained the same during a median period of 18 months. Of N = 50 patients at baseline, N = 30 had MRI scans available at follow-up (median interval = 18 months) and were included for delta radiomic analysis. A total of 252 radiomic features were extracted from the PCa region of interest identified by board-certified radiologists on 3T bi-parametric MRI [T2-weighted (T2W) and apparent diffusion coefficient (ADC)]. Delta radiomic features were computed as the difference of radiomic feature between baseline and follow-up scans. The association of AS+ with age, prostate-specific antigen (PSA), Prostate Imaging Reporting and Data System (PIRADS v2.1) score, and tumor size was evaluated at baseline and follow-up. Various prediction models were built using random forest (RF) classifier within a threefold cross-validation framework leveraging baseline radiomics (Cbr), baseline radiomics + baseline clinical (Cbrbcl), delta radiomics (CΔr), delta radiomics + baseline clinical (CΔrbcl), and delta radiomics + delta clinical (CΔrΔcl). Results An AUC of 0.64 ± 0.09 was obtained for Cbr, which increased to 0.70 ± 0.18 with the integration of clinical variables (Cbrbcl). CΔr yielded an AUC of 0.74 ± 0.15. Integrating delta radiomics with baseline clinical variables yielded an AUC of 0.77 ± 0.23. CΔrΔclresulted in the best AUC of 0.84 ± 0.20 (p < 0.05) among all combinations. Conclusion Our preliminary findings suggest that delta radiomics were more strongly associated with upgrade events compared to PIRADS and other clinical variables. Delta radiomics on serial MRI in combination with changes in clinical variables (PSA and tumor volume) between baseline and follow-up showed the strongest association with biopsy upgrade in PCa patients on AS. Further independent multi-site validation of these preliminary findings is warranted.
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Affiliation(s)
- Abhishek Midya
- Department of Biomedical Engineering, Emory University, Atlanta, GA, United States
| | | | - Jacob Huber
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
| | | | | | - Amr Mahran
- Department of Urology, Assiut University, Asyut, Egypt
| | - Leonardo K. Bittencourt
- Department of Radiology, University Hospitals, Cleveland Medical Center, Cleveland, OH, United States
| | - Sree Harsha Tirumani
- Department of Radiology, University Hospitals, Cleveland Medical Center, Cleveland, OH, United States
| | - Lee Ponsky
- Department of Urology, University Hospitals, Cleveland Medical Center, Cleveland, OH, United States
| | - Rakesh Shiradkar
- Department of Biomedical Engineering, Emory University, Atlanta, GA, United States
| | - Anant Madabhushi
- Department of Biomedical Engineering, Emory University, Atlanta, GA, United States
- Atlanta Veterans Administration Medical Center, Atlanta, GA, United States
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Chan VWS, Asif A, Koe JSE, Ng A, Ng CF, Teoh JYC. Implications and effects of COVID-19 on diagnosis and management of prostate cancer. Curr Opin Urol 2022; 32:311-317. [PMID: 35142745 DOI: 10.1097/mou.0000000000000973] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
PURPOSE OF REVIEW The Coronavirus disease 2019 (COVID-19) pandemic has led to uncertainty on the optimal management for prostate cancer (PCa). This narrative review aims to shed light on the optimal diagnosis and management of patients with or suspected to have PCa. RECENT FINDINGS Faecal-oral or aerosol transmission is possible during prostate procedures; caution must be in place when performing digital rectal examinations, transrectal ultrasound-guided prostate biopsies and prostate surgeries requiring general anaesthesia. Patients must also be triaged using preoperative polymerase chain reaction tests for COVID-19. COVID-19 has accelerated the adoption of multiparametric Magnetic Resonance Imaging (MRI), reducing the need for prostate biopsy unless when absolutely indicated, and the risk of COVID-19 spread can be reduced. Combined with prostate-specific antigen (PSA) density, amongst other factors, multiparametric MRI could reduce unnecessary biopsies in patients with little chance of clinically significant PCa. Treatment of PCa should be stratified by the risk level and preferences of the patient. COVID-19 has accelerated the development of telemedicine and clinicians should utilise safe and effective teleconsultations to protect themselves and their patients. SUMMARY COVID-19 transmission during prostate procedures is possible. Patients with a Prostate Imaging-Reporting and Data System (PI-RADS) of <3 and PSA density <0.15 ng/ml/ml are deemed low-risk and are safe to undergo surveillance without MRI-targeted biopsy. Intermediate- or high-risk patients should be offered definitive treatment within four months or 30days of diagnosis to avoid compromising treatment outcomes; three-month courses of neoadjuvant androgen deprivation therapy can be considered when a delay of surgery is anticipated.
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Affiliation(s)
- Vinson Wai-Shun Chan
- School of Medicine, Faculty of Medicine and Health, University of Leeds, Leeds, UK
- S.H. Ho Urology Centre, Department of Surgery, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China
- Division of Surgery and Interventional Science, University College London, London
| | - Aqua Asif
- Division of Surgery and Interventional Science, University College London, London
- Leicester Medical School, University of Leicester, Leicester
| | - Jasmine Sze-Ern Koe
- School of Medicine, Faculty of Medicine and Health, University of Leeds, Leeds, UK
| | - Alexander Ng
- UCL Medical School, University College London, London, UK
| | - Chi Fai Ng
- S.H. Ho Urology Centre, Department of Surgery, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China
| | - Jeremy Yuen-Chun Teoh
- S.H. Ho Urology Centre, Department of Surgery, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China
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Morote J, Borque-Fernando A, Triquell M, Celma A, Regis L, Mast R, de Torres IM, Semidey ME, Santamaría A, Planas J, Esteban LM, Trilla E. Multiparametric Magnetic Resonance Imaging Grades the Aggressiveness of Prostate Cancer. Cancers (Basel) 2022; 14:1828. [PMID: 35406600 PMCID: PMC8997549 DOI: 10.3390/cancers14071828] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 03/31/2022] [Accepted: 04/01/2022] [Indexed: 02/04/2023] Open
Abstract
We sought to find further evidence showing the increase in PCa aggressiveness as PI-RADS score increases from four surrogates of PCa aggressiveness: i. prostate biopsy GG (≤3 vs. >3), ii. type of pathology in surgical specimens (favourable vs. unfavourable), iii. clinical stage (localised vs. advanced), and risk of recurrence of localised PCa after primary treatment (low-intermediate vs. high). A group of 692 PCa patients were diagnosed after 3-T multiparametric MRI (mpMRI) and guided and/or systematic biopsies, showing csPCa (GG ≥ 2) in 547 patients (79%) and insignificant PCa (iPCa) in 145 (21%). The csPCa rate increased from 32.4% in PI-RADS < 3 to 95.5% in PI-RADS 5 (p < 0.001). GG ≥ 3 was observed in 7.6% of PCa with PI-RADS < 3 and 32.6% in those with PI-RADS > 3 (p < 0.001). Unfavourable pathology was observed in 38.9% of PCa with PI-RAD < 3 and 68.3% in those with PI-RADS > 3 (p = 0.030). Advanced disease was not observed in PCa with PI-RADS ≤ 3, while it existed in 12.7% of those with PI-RADS > 3 (p < 0.001). High-risk recurrence localised PCa was observed in 9.5% of PCa with PI-RADS < 3 and 35% in those with PI-RADS > 3 (p = 0.001). The PI-RADS score was an independent predictor of all surrogates of PCa aggressiveness as PSA density. We confirmed that mpMRI grades PCa aggressiveness.
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Affiliation(s)
- Juan Morote
- Department of Urology, Vall d’Hebron Hospital, 08035 Barcelona, Spain; (M.T.); (A.C.); (L.R.); (J.P.); (E.T.)
- Department of Surgery, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain
| | - Angel Borque-Fernando
- Department of Urology, Hospital Universitario Miguel Servet, IIS-Aragon, 50009 Zaragoza, Spain;
| | - Marina Triquell
- Department of Urology, Vall d’Hebron Hospital, 08035 Barcelona, Spain; (M.T.); (A.C.); (L.R.); (J.P.); (E.T.)
| | - Anna Celma
- Department of Urology, Vall d’Hebron Hospital, 08035 Barcelona, Spain; (M.T.); (A.C.); (L.R.); (J.P.); (E.T.)
| | - Lucas Regis
- Department of Urology, Vall d’Hebron Hospital, 08035 Barcelona, Spain; (M.T.); (A.C.); (L.R.); (J.P.); (E.T.)
| | - Richard Mast
- Department of Radiology, Vall d’Hebron Hospital, 08035 Barcelona, Spain;
| | - Inés M. de Torres
- Department of Pathology, Vall d’Hebron Hospital, 08035 Barcelona, Spain; (I.M.d.T.); (M.E.S.)
- Department of Morphological Sciences, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain
| | - María E. Semidey
- Department of Pathology, Vall d’Hebron Hospital, 08035 Barcelona, Spain; (I.M.d.T.); (M.E.S.)
- Department of Morphological Sciences, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain
| | | | - Jacques Planas
- Department of Urology, Vall d’Hebron Hospital, 08035 Barcelona, Spain; (M.T.); (A.C.); (L.R.); (J.P.); (E.T.)
| | - Luis M. Esteban
- Department of Applied Mathematics, Escuela Universitaria Politécnica La Almunia, Universidad de Zaragoza, 50100 Zaragoza, Spain;
| | - Enrique Trilla
- Department of Urology, Vall d’Hebron Hospital, 08035 Barcelona, Spain; (M.T.); (A.C.); (L.R.); (J.P.); (E.T.)
- Department of Surgery, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain
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