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Ahn H, Kim JK, Hwang SI, Hong SK, Byun SS, Song SH, Choe G, Jee HM, Park SW. Exploring the potential of ex-vivo 7-T magnetic resonance imaging on patients with clinically significant prostate cancer: visibility and size perspective. Prostate Int 2024; 12:79-85. [PMID: 39036759 PMCID: PMC11255944 DOI: 10.1016/j.prnil.2024.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 02/13/2024] [Accepted: 02/19/2024] [Indexed: 07/23/2024] Open
Abstract
Background Despite progress in multiparametric magnetic resonance imaging (MRI), issues of prostate cancer invisibility and underestimated tumor burden persist. This study investigates the potential of an ultra-high field MRI at 7-T in an ex-vivo setting to address these limitations. Methods This prospective study included 54 tumors from 20 treatment-naïve clinically significant prostate cancer patients, confirmed by biopsy, despite negative findings on preoperative 3-T MRI. Ex-vivo 7-T MRI of resected prostates was performed, with assessment on tumor visibility and size. Factors influencing visibility were analyzed using logistic regression analyses. Results Tumor visibility was confirmed in 80% of patients, and 48% of all tumors on ex-vivo imaging. Gleason pattern 4 percentage (odds ratio 1.09) and tumor size on pathology (odds ratio 1.36) were significantly associated with visibility (P < 0.05). Mean MRI-visible and invisible tumor sizes were 10.5 mm and 5.3 mm, respectively. The size discrepancy between MRI and pathology was 2.7 mm. Conclusion Tumor visibility on ex-vivo 7-T MRI was influenced by tumor grade and size. The notable tumor visibility initially overlooked on 3-T MRI, along with small size discrepancy with pathology, suggests potential improvements in resolution.
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Affiliation(s)
- Hyungwoo Ahn
- Department of Radiology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Jung Kwon Kim
- Department of Urology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Sung Il Hwang
- Department of Radiology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Sung Kyu Hong
- Department of Urology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Seok-Soo Byun
- Department of Urology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Sang Hun Song
- Department of Urology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Gheeyoung Choe
- Department of Pathology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Hye Mi Jee
- Preclinical Research Center, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Sung Woo Park
- Department of Biomedical Engineering, Seoul National University Hospital, Seoul, Korea
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Lehto TPK, Pylväläinen J, Sandeman K, Kenttämies A, Nordling S, Mills IG, Tang J, Mirtti T, Rannikko A. Histomic and transcriptomic features of MRI-visible and invisible clinically significant prostate cancers are associated with prognosis. Int J Cancer 2024; 154:926-939. [PMID: 37767987 DOI: 10.1002/ijc.34743] [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: 04/03/2023] [Revised: 08/27/2023] [Accepted: 09/06/2023] [Indexed: 09/29/2023]
Abstract
Magnetic resonance imaging (MRI) is increasingly used to triage patients for prostate biopsy. However, 9% to 24% of clinically significant (cs) prostate cancers (PCas) are not visible in MRI. We aimed to identify histomic and transcriptomic determinants of MRI visibility and their association to metastasis, and PCa-specific death (PCSD). We studied 45 radical prostatectomy-treated patients with csPCa (grade group [GG]2-3), including 30 with MRI-visible and 15 with MRI-invisible lesions, and 18 men without PCa. First, histological composition was quantified. Next, transcriptomic profiling was performed using NanoString technology. MRI visibility-associated differentially expressed genes (DEGs) and Reactome pathways were identified. MRI visibility was classified using publicly available genes in MSK-IMPACT and Decipher, Oncotype DX, and Prolaris. Finally, DEGs and clinical parameters were used to classify metastasis and PCSD in an external cohort, which included 76 patients with metastatic GG2-4 PCa, and 84 baseline-matched controls without progression. Luminal area was lower in MRI-visible than invisible lesions and low luminal area was associated with short metastasis-free and PCa-specific survival. We identified 67 DEGs, eight of which were associated with survival. Cell division, inflammation and transcriptional regulation pathways were upregulated in MRI-visible csPCas. Genes in Decipher, Oncotype DX and MSK-IMPACT performed well in classifying MRI visibility (AUC = 0.86-0.94). DEGs improved classification of metastasis (AUC = 0.69) and PCSD (AUC = 0.68) over clinical parameters. Our data reveals that MRI-visible csPCas harbor more aggressive histomic and transcriptomic features than MRI-invisible csPCas. Thus, targeted biopsy of visible lesions may be sufficient for risk stratification in patients with a positive MRI.
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Affiliation(s)
- Timo-Pekka K Lehto
- Department of Pathology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Department of Urology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Juho Pylväläinen
- Department of Radiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | | | - Anu Kenttämies
- Department of Radiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Stig Nordling
- Department of Pathology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Ian G Mills
- Nuffield Department of Surgical Sciences, University of Oxford, Oxfordshire, UK
- Patrik G Johnston Centre for Cancer Research, Queen's University of Belfast, Belfast, UK
| | - Jing Tang
- Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Biochemistry and Developmental Biology, University of Helsinki, Helsinki, Finland
| | - Tuomas Mirtti
- Department of Pathology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Biomedical Engineering, School of Medicine, Emory University, Atlanta, Georgia, USA
- iCAN-Digital Precision Cancer Medicine Flagship, Helsinki, Finland
| | - Antti Rannikko
- Department of Urology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- iCAN-Digital Precision Cancer Medicine Flagship, Helsinki, Finland
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Zhu M, Liang Z, Feng T, Mai Z, Jin S, Wu L, Zhou H, Chen Y, Yan W. Up-to-Date Imaging and Diagnostic Techniques for Prostate Cancer: A Literature Review. Diagnostics (Basel) 2023; 13:2283. [PMID: 37443677 DOI: 10.3390/diagnostics13132283] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 06/29/2023] [Accepted: 06/30/2023] [Indexed: 07/15/2023] Open
Abstract
Prostate cancer (PCa) faces great challenges in early diagnosis, which often leads not only to unnecessary, invasive procedures, but to over-diagnosis and treatment as well, thus highlighting the need for modern PCa diagnostic techniques. The review aims to provide an up-to-date summary of chronologically existing diagnostic approaches for PCa, as well as their potential to improve clinically significant PCa (csPCa) diagnosis and to reduce the proliferation and monitoring of PCa. Our review demonstrates the primary outcomes of the most significant studies and makes comparisons across the diagnostic efficacies of different PCa tests. Since prostate biopsy, the current mainstream PCa diagnosis, is an invasive procedure with a high risk of post-biopsy complications, it is vital we dig out specific, sensitive, and accurate diagnostic approaches in PCa and conduct more studies with milestone findings and comparable sample sizes to validate and corroborate the findings.
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Affiliation(s)
- Ming Zhu
- Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Zhen Liang
- Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Tianrui Feng
- Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Zhipeng Mai
- Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Shijie Jin
- Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Liyi Wu
- Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Huashan Zhou
- Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Yuliang Chen
- Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Weigang Yan
- Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
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Harder FN, Heming CAM, Haider MA. mpMRI Interpretation in Active Surveillance for Prostate Cancer-An overview of the PRECISE score. Abdom Radiol (NY) 2023; 48:2449-2455. [PMID: 37160473 DOI: 10.1007/s00261-023-03912-2] [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: 02/28/2023] [Revised: 03/31/2023] [Accepted: 04/05/2023] [Indexed: 05/11/2023]
Abstract
Active surveillance (AS) is now included in all major guidelines for patients with low-risk PCa and selected patients with intermediate-risk PCa. Several studies have highlighted the potential benefit of multiparametric magnetic resonance imaging (mpMRI) in AS and it has been adopted in some guidelines. However, uncertainty remains about whether serial mpMRI can help to safely reduce the number of required repeat biopsies under AS. In 2017, the European School of Oncology initiated the Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) panel which proposed the PRECISE scoring system to assess the likelihood of radiological tumor progression on serial mpMRI. The PRECISE scoring system remains the only major system evaluated in multiple publications. In this review article, we discuss the current body of literature investigating the application of PRECISE as it is not as yet an established standard in mpMRI reporting. We delineate the strengths of PRECISE and its potential added value. Also, we underline potential weaknesses of the PRECISE scoring system, which might be tackled in future versions to further increase its value in AS.
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Affiliation(s)
- Felix N Harder
- Institute of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, 600 University Avenue, Toronto, ON, M5G 1X5, Canada
- Joint Department of Medical Imaging, University Health Network, Sinai Health System and University of Toronto, Toronto, ON, M5G 1X5, Canada
| | - Carolina A M Heming
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, 600 University Avenue, Toronto, ON, M5G 1X5, Canada
- Joint Department of Medical Imaging, University Health Network, Sinai Health System and University of Toronto, Toronto, ON, M5G 1X5, Canada
- Radiology Department, Instituto Nacional do Cancer (INCa), Rio de Janeiro, Brazil
| | - Masoom A Haider
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, 600 University Avenue, Toronto, ON, M5G 1X5, Canada.
- Joint Department of Medical Imaging, University Health Network, Sinai Health System and University of Toronto, Toronto, ON, M5G 1X5, Canada.
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Zhang J, Xu L, Zhang G, Zhang X, Bai X, Sun H, Jin Z. Effects of dynamic contrast enhancement on transition zone prostate cancer in Prostate Imaging Reporting and Data System Version 2.1. Radiol Oncol 2023; 57:42-50. [PMID: 36655324 PMCID: PMC10039479 DOI: 10.2478/raon-2023-0007] [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: 10/09/2022] [Accepted: 11/18/2022] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND The aim of the study was to analyse the effects of dynamic contrast enhanced (DCE)-MRI on transitional-zone prostate cancer (tzPCa) and clinically significant transitional-zone prostate cancer (cs-tzPCa) in Prostate Imaging Reporting and Data System (PI-RADS) Version 2.1. PATIENTS AND METHODS The diagnostic efficiencies of T2-weighted imaging (T2WI) + diffusion-weighted imaging (DWI), T2WI + dynamic contrast-enhancement (DCE), and T2WI + DWI + DCE in tzPCa and cs-tzPCa were compared using the score of ≥ 4 as the positive threshold and prostate biopsy as the reference standard. RESULTS A total of 425 prostate cases were included in the study: 203 cases in the tzPCa group, and 146 in the cs-tzPCa group. The three sequence combinations had the similar areas under the curves in diagnosing tzPCa and cs-tzPCa (all P < 0.05). The sensitivity of T2WI + DCE and T2WI + DWI + DCE (84.7% and 85.7% for tzPCa; 88.4% and 89.7% for cs-tzPCa, respectively) in diagnosing tzPCa and cs-tzPCa was significantly greater than that of T2WI + DWI (79.3% for tzPCa; 82.9% for cs-tzPCa). The specificity of T2WI + DWI (86.5% for tzPCa; 74.9% for cs-tzPCa) were significantly greater than those of T2WI + DCE and T2WI + DWI + DCE (68.0% and 68.5% for tzPCa; 59.1% and 59.5% for cs-tzPCa, respectively) (all P > 0.05). The diagnostic efficacies of T2WI + DCE and T2WI + DWI + DCE had no significant differences (all P < 0.05). CONCLUSIONS DCE can improve the sensitivity of diagnosis for tzPCa and cs-tzPCa, and it is useful for small PCa lesion diagnosis.
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Affiliation(s)
- Jiahui Zhang
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Lili Xu
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Gumuyang Zhang
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Xiaoxiao Zhang
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Xin Bai
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Hao Sun
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
- National Center for Quality Control of Radiology, Beijing, China
| | - Zhengyu Jin
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
- National Center for Quality Control of Radiology, Beijing, China
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6
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Liu G, Pan S, Zhao R, Zhou H, Chen J, Zhou X, Xu J, Zhou Y, Xue W, Wu G. The added value of AI-based computer-aided diagnosis in classification of cancer at prostate MRI. Eur Radiol 2023:10.1007/s00330-023-09433-2. [PMID: 36725719 DOI: 10.1007/s00330-023-09433-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 10/26/2022] [Accepted: 01/05/2023] [Indexed: 02/03/2023]
Abstract
OBJECTIVES To develop an artificial intelligence (AI) model for prostate segmentation and prostate cancer (PCa) detection, and explore the added value of AI-based computer-aided diagnosis (CAD) compared to conventional PI-RADS assessment. METHODS A retrospective study was performed on multi-centers and included patients who underwent prostate biopsies and multiparametric MRI. A convolutional-neural-network-based AI model was trained and validated; the reliability of different CAD methods (concurrent read and AI-first read) were tested in an internal/external cohort. The diagnostic performance, consistency and efficiency of radiologists and AI-based CAD were compared. RESULTS The training/validation/internal test sets included 650 (400/100/150) cases from one center; the external test included 100 cases (25/25/50) from three centers. For diagnosis accuracy, AI-based CAD methods showed no significant differences and were equivalent to the radiologists in the internal test (127/150 vs. 130/150 vs. 125/150 for reader 1; 127/150 vs.132/150 vs. 131/150 for reader 2; all p > 0.05), whereas in the external test, concurrent-read methods were superior/equal to AI-first read (87/100 vs. 71/100, p < 0.001, for reader 2; 79/100 vs. 69/100, p = 0.076, for reader 1) and better than/equal to radiologists (79/100 vs. 72/100, p = 0.039, for reader 1; 87/100 vs. 86/100, p = 1.000, for reader 2). Moreover, AI-first read/concurrent read improved consistency in both internal test (κ = 1.000, 0.830) and external test (κ = 0.958, 0.713) compared to radiologists (κ = 0.747, 0.600); AI-first read method (8.54 s/7.66 s) was faster than readers (92.72 s/89.54 s) and concurrent-read method (29.15 s/28.92 s), respectively. CONCLUSION AI-based CAD could improve the consistency and efficiency for accurate diagnosis; the concurrent-read method could enhance the diagnostic capabilities of an inexperienced radiologist in unfamiliar situations. KEY POINTS • For prostate cancer segmentation, the performance of multi-small Vnet displays optimal compared to small Vnet and Vnet (DSCmsvnet vs. DSCsvnet, p = 0.021; DSCmsvnet vs. DSCvnet, p < 0.001). • For prostate gland segmentation, the mean/median DSCs for fine and coarse segmentation were 0.91/0.91 and 0.88/0.89, respectively. Fine segmentation displays superior performance compared to coarse (DSCcoarse vs. DSCfine, p < 0.001). • For PCa diagnosis, AI-based CAD methods improve consistency in internal (κ = 1.000; 0.830) and external (κ = 0.958; 0.713) tests compared to radiologists (κ = 0.747; 0.600); the AI-first read (8.54 s/7.66 s) was faster than the readers (92.72 s/89.54 s) and the concurrent-read method (29.15 s/28.92 s).
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Affiliation(s)
- Guiqin Liu
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Shihang Pan
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Rui Zhao
- Department of Radiology, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Huang Zhou
- Department of Radiology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
| | - Jie Chen
- Huangpu Branch, Shanghai Ninth People's Hospital, Shanghai, China
| | - Xiang Zhou
- Department of Radiology, Putuo Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jianrong Xu
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yan Zhou
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Wei Xue
- Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
| | - Guangyu Wu
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
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Pötsch N, Rainer E, Clauser P, Vatteroni G, Hübner N, Korn S, Shariat S, Helbich T, Baltzer P. Impact of PI-QUAL on PI-RADS and cancer yield in an MRI-TRUS fusion biopsy population. Eur J Radiol 2022; 154:110431. [DOI: 10.1016/j.ejrad.2022.110431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 06/21/2022] [Accepted: 06/30/2022] [Indexed: 11/26/2022]
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Diagnostic Accuracy of Abbreviated Bi-Parametric MRI (a-bpMRI) for Prostate Cancer Detection and Screening: A Multi-Reader Study. Diagnostics (Basel) 2022; 12:diagnostics12020231. [PMID: 35204322 PMCID: PMC8871361 DOI: 10.3390/diagnostics12020231] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 01/07/2022] [Accepted: 01/12/2022] [Indexed: 11/25/2022] Open
Abstract
(1) Background: There is currently limited evidence on the diagnostic accuracy of abbreviated biparametric MRI (a-bpMRI) protocols for prostate cancer (PCa) detection and screening. In the present study, we aim to investigate the performance of a-bpMRI among multiple readers and its potential application to an imaging-based screening setting. (2) Methods: A total of 151 men who underwent 3T multiparametric MRI (mpMRI) of the prostate and transperineal template prostate mapping biopsies were retrospectively selected. Corresponding bpMRI (multiplanar T2WI, DWI, ADC maps) and a-bpMRI (axial T2WI and b 2000 s/mm2 DWI only) dataset were derived from mpMRI. Three experienced radiologists scored a-bpMRI, standard biparametric MRI (bpMRI) and mpMRI in separate sessions. Diagnostic accuracy and interreader agreement of a-bpMRI was tested for different positivity thresholds and compared to bpMRI and mpMRI. Predictive values of a-bpMRI were computed for lower levels of PCa prevalence to simulate a screening setting. The primary definition of clinically significant PCa (csPCa) was Gleason ≥ 4 + 3, or cancer core length ≥ 6 mm. (3) Results: The median age was 62 years, the median PSA was 6.8 ng/mL, and the csPCa prevalence was 40%. Using a cut off of MRI score ≥ 3, the sensitivity and specificity of a-bpMRI were 92% and 48%, respectively. There was no significant difference in sensitivity compared to bpMRI and mpMRI. Interreader agreement of a-bpMRI was moderate (AC1 0.58). For a low prevalence of csPCa (e.g., <10%), higher cut offs (MRI score ≥ 4) yield a more favourable balance between the predictive values and positivity rate of MRI. (4) Conclusion: Abbreviated bpMRI protocols could match the diagnostic accuracy of bpMRI and mpMRI for the detection of csPCa. If a-bpMRI is used in low-prevalence settings, higher cut-offs for MRI positivity should be prioritised.
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Satish P, Freeman A, Kelly D, Kirkham A, Orczyk C, Simpson BS, Giganti F, Whitaker HC, Emberton M, Norris JM. Relationship of prostate cancer topography and tumour conspicuity on multiparametric magnetic resonance imaging: a protocol for a systematic review and meta-analysis. BMJ Open 2022; 12:e050376. [PMID: 34987040 PMCID: PMC8734010 DOI: 10.1136/bmjopen-2021-050376] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
INTRODUCTION Multiparametric magnetic resonance imaging (mpMRI) has improved the triage of men with suspected prostate cancer, through precision prebiopsy identification of clinically significant disease. While multiple important characteristics, including tumour grade and size have been shown to affect conspicuity on mpMRI, tumour location and association with mpMRI visibility is an underexplored facet of this field. Therefore, the objective of this systematic review and meta-analysis is to collate the extant evidence comparing MRI performance between different locations within the prostate in men with existing or suspected prostate cancer. This review will help clarify mechanisms that underpin whether a tumour is visible, and the prognostic implications of our findings. METHODS AND ANALYSIS The databases MEDLINE, PubMed, Embase and Cochrane will be systematically searched for relevant studies. Eligible studies will be full-text English-language articles that examine the effect of zonal location on mpMRI conspicuity. Two reviewers will perform study selection, data extraction and quality assessment. A third reviewer will be involved if consensus is not achieved. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines will inform the methodology and reporting of the review. Study bias will be assessed using a modified Newcastle-Ottawa scale. A thematic approach will be used to synthesise key location-based factors associated with mpMRI conspicuity. A meta-analysis will be conducted to form a pooled value of the sensitivity and specificity of mpMRI at different tumour locations. ETHICS AND DISSEMINATION Ethical approval is not required as it is a protocol for a systematic review. Findings will be disseminated through peer-reviewed publications and conference presentations. PROSPERO REGISTRATION NUMBER CRD42021228087.
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Affiliation(s)
- Pranav Satish
- UCL Division of Surgery & Interventional Science, UCL Medical School, London, UK
| | - Alex Freeman
- Department of Pathology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Daniel Kelly
- School of Healthcare Sciences, Cardiff University, Cardiff, UK
| | - Alex Kirkham
- Department of Radiology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Clement Orczyk
- Department of Urology, University College London Hospitals NHS Foundation Trust, London, UK
| | | | - Francesco Giganti
- Department of Radiology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Hayley C Whitaker
- Division of Surgery and Interventional Science, University College London, London, UK
| | - Mark Emberton
- Department of Urology, University College London Hospitals NHS Foundation Trust, London, UK
- Division of Surgery and Interventional Science, University College London, London, UK
| | - Joseph M Norris
- Division of Surgery and Interventional Science, University College London, London, UK
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AI-enhanced simultaneous multiparametric 18F-FDG PET/MRI for accurate breast cancer diagnosis. Eur J Nucl Med Mol Imaging 2021; 49:596-608. [PMID: 34374796 PMCID: PMC8803815 DOI: 10.1007/s00259-021-05492-z] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2021] [Accepted: 07/06/2021] [Indexed: 12/17/2022]
Abstract
Purpose To assess whether a radiomics and machine learning (ML) model combining quantitative parameters and radiomics features extracted from simultaneous multiparametric 18F-FDG PET/MRI can discriminate between benign and malignant breast lesions. Methods A population of 102 patients with 120 breast lesions (101 malignant and 19 benign) detected on ultrasound and/or mammography was prospectively enrolled. All patients underwent hybrid 18F-FDG PET/MRI for diagnostic purposes. Quantitative parameters were extracted from DCE (MTT, VD, PF), DW (mean ADC of breast lesions and contralateral breast parenchyma), PET (SUVmax, SUVmean, and SUVminimum of breast lesions, as well as SUVmean of the contralateral breast parenchyma), and T2-weighted images. Radiomics features were extracted from DCE, T2-weighted, ADC, and PET images. Different diagnostic models were developed using a fine Gaussian support vector machine algorithm which explored different combinations of quantitative parameters and radiomics features to obtain the highest accuracy in discriminating between benign and malignant breast lesions using fivefold cross-validation. The performance of the best radiomics and ML model was compared with that of expert reader review using McNemar’s test. Results Eight radiomics models were developed. The integrated model combining MTT and ADC with radiomics features extracted from PET and ADC images obtained the highest accuracy for breast cancer diagnosis (AUC 0.983), although its accuracy was not significantly higher than that of expert reader review (AUC 0.868) (p = 0.508). Conclusion A radiomics and ML model combining quantitative parameters and radiomics features extracted from simultaneous multiparametric 18F-FDG PET/MRI images can accurately discriminate between benign and malignant breast lesions. Supplementary Information The online version contains supplementary material available at 10.1007/s00259-021-05492-z.
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