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Park SY, Woo S, Park KJ, Westphalen AC. A pictorial essay of PI-RADS pearls and pitfalls: toward less ambiguity and better practice. Abdom Radiol (NY) 2024; 49:3190-3205. [PMID: 38704782 DOI: 10.1007/s00261-024-04273-0] [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: 11/09/2023] [Revised: 03/02/2024] [Accepted: 03/03/2024] [Indexed: 05/07/2024]
Abstract
Prostate Imaging Reporting and Data System (PI-RADS) was designed to standardize the interpretation of multiparametric magnetic resonance imaging (MRI) of the prostate, aiding in assessing the probability of clinically significant prostate cancer. By providing a structured scoring system, it enables better risk stratification, guiding decisions regarding the need for biopsy and subsequent treatment options. In this article, we explore both the strengths and weaknesses of PI-RADS, offering insights into its updated diagnostic performance and clinical applications, while also addressing potential pitfalls using diverse, representative MRI cases.
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Affiliation(s)
- Sung Yoon Park
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.
- Department of Radiology, University of Washington, 1959 NE Pacific St., 2nd Floor, Seattle, WA, 98195, USA.
| | - Sungmin Woo
- Department of Radiology, NYU Langone Health, New York, NY, 10016, USA
| | - Kye Jin Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, 05505, Republic of Korea
| | - Antonio C Westphalen
- Department of Radiology, University of Washington, 1959 NE Pacific St., 2nd Floor, Seattle, WA, 98195, USA
- Department of Urology, University of Washington, 1959 NE Pacific St., 2nd Floor, Seattle, WA, 98195, USA
- Department of Radiation Oncology, University of Washington, 1959 NE Pacific St., 2nd Floor, Seattle, WA, 98195, USA
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Gao Z, Xu X, Sun H, Li T, Ding W, Duan Y, Tang L, Gu Y. The value of synthetic magnetic resonance imaging in the diagnosis and assessment of prostate cancer aggressiveness. Quant Imaging Med Surg 2024; 14:5473-5489. [PMID: 39143997 PMCID: PMC11320532 DOI: 10.21037/qims-24-291] [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: 02/18/2024] [Accepted: 05/30/2024] [Indexed: 08/16/2024]
Abstract
Background Synthetic magnetic resonance imaging (SyMRI) is a fast, standardized, and robust novel quantitative technique that has the potential to circumvent the subjectivity of interpretation in prostate multiparametric magnetic resonance imaging (mpMRI) and the limitations of existing MRI quantification techniques. Our study aimed to evaluate the potential utility of SyMRI in the diagnosis and aggressiveness assessment of prostate cancer (PCA). Methods We retrospectively analyzed 309 patients with suspected PCA who had undergone mpMRI and SyMRI, and pathologic results were obtained by biopsy or PCA radical prostatectomy (RP). Pathological types were classified as PCA, benign prostatic hyperplasia (BPH), or peripheral zone (PZ) inflammation. According to the Gleason Score (GS), PCA was divided into groups of intermediate-to-high risk (GS ≥4+3) and low-risk (GS ≤3+4). Patients with biopsy-confirmed low-risk PCA were further divided into upgraded and nonupgraded groups based on the GS changes of the RP results. The values of the apparent diffusion coefficient (ADC), T1, T2 and proton density (PD) of these lesions were measured on ADC and SyMRI parameter maps by two physicians; these values were compared between PCA and BPH or inflammation, between the intermediate-to-high-risk and low-risk PCA groups, and between the upgraded and nonupgraded PCA groups. The risk factors affecting GS grades were identified via univariate analysis. The effects of confounding factors were excluded through multivariate logistic regression analysis, and independent predictive factors were calculated. Subsequently, the ADC+Sy(T2+PD) combined models for predicting PCA risk grade or GS upgrade were constructed through data processing analysis. The diagnostic performance of each parameter and the ADC+Sy(T2+PD) model was analyzed. The calibration curve was calculated by the bootstrapping internal validation method (200 bootstrap resamples). Results The T1, T2, and PD values of PCA were significantly lower than those of BPH or inflammation (P≤0.001) in both the PZ or transitional zone. Among the 178 patients with PCA, intermediate-to-high-risk PCA group had significantly higher T1, T2, and PD values but lower ADC values compared with the low-risk group (P<0.05), and the diagnostic efficacy of each single parameter was similar (P>0.05). The ADC+Sy(T2+PD) model showed the best performance, with an area under the curve (AUC) 0.110 [AUC =0.818; 95% confidence interval (CI): 0.754-0.872] higher than that of ADC alone (AUC =0.708; 95% CI: 0.635-0.774) (P=0.003). Among the 68 patients initially classified as PCA in the low-risk group by biopsy, PCA in the postoperative upgraded GS group had significantly higher T1, T2, and PD values but lower ADC values than did those in the nonupgraded group (P<0.01). In addition, the ADC+Sy(T2+PD) model better predicted the upgrade of GS, with a significant increase in AUC of 0.204 (AUC =0.947; 95% CI: 0.864-0.987) compared with ADC alone (AUC =0.743; 95% CI: 0.622-0.841) (P<0.001). Conclusions Quantitative parameters (T1, T2, and PD) derived from SyMRI can help differentiate PCA from non-PCA. Combining SyMRI parameters with ADC significantly improved the ability to differentiate between intermediate-to-high risk PCA from low-risk PCA and could predict the upgrade of low-risk PCA as confirmed by biopsy.
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Affiliation(s)
- Zhongxiu Gao
- Department of Nuclear Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xinchen Xu
- Department of Nuclear Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Han Sun
- Department of Nuclear Medicine, Central Hospital of Xuzhou, Xuzhou, China
| | - Tiannv Li
- Department of Nuclear Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Wei Ding
- Department of Nuclear Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Ying Duan
- Department of Nuclear Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Lijun Tang
- Department of Nuclear Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yingying Gu
- Department of Nuclear Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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Fernandez-Quilez A, Nordström T, Jäderling F, Kjosavik SR, Eklund M. Prostate Age Gap: An MRI Surrogate Marker of Aging for Prostate Cancer Detection. J Magn Reson Imaging 2024; 60:458-468. [PMID: 37855699 DOI: 10.1002/jmri.29090] [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: 08/10/2023] [Revised: 10/04/2023] [Accepted: 10/05/2023] [Indexed: 10/20/2023] Open
Abstract
BACKGROUND Aging is the most important risk factor for prostate cancer (PC). Imaging techniques can be useful to measure age-related changes associated with the transition to diverse pathological states. However, biomarkers of aging from prostate magnetic resonance imaging (MRI) remain to be explored. PURPOSE To develop an aging biomarker from prostate MRI and to examine its relationship with clinically significant PC (csPC, Gleason score ≥7) risk occurrence. STUDY TYPE Retrospective. POPULATION Four hundred and sixty-eight (65.97 ± 6.91 years) biopsied males, contributing 7243 prostate MRI slices. A deep learning (DL) model was trained on 3223 MRI slices from 81 low-grade PC (Gleason score ≤6) and 131 negative patients, defined as non-csPC. The model was tested on 90 negative, 52 low-grade (142 non-csPC), and 114 csPC patients. FIELD STRENGTH/SEQUENCE 3-T, axial T2-weighted spin sequence. ASSESSMENT Chronological age was defined as the age of the participant at the time of the visit. Prostate-specific antigen (PSA), prostate volume, Gleason, and Prostate Imaging-Reporting and Data System (PI-RADS) scores were also obtained. Manually annotated prostate masks were used to crop the MRI slices, and a DL model was trained with those from non-csPC patients to estimate the age of the patients. Following, we obtained the prostate age gap (PAG) on previously unseen csPC and non-csPC cropped MRI exams. PAG was defined as the estimated model age minus the patient's age. Finally, the relationship between PAG and csPC risk occurrence was assessed through an adjusted multivariate logistic regression by PSA levels, age, prostate volume, and PI-RADS ≥ 3 score. STATISTICAL TESTS T-test, Mann-Whitney U test, permutation test, receiver operating characteristics (ROC), area under the curve (AUC), and odds ratio (OR). A P value <0.05 was considered statistically significant. RESULTS After adjusting, there was a significant difference in the odds of csPC (OR = 3.78, 95% confidence interval [CI]: 2.32-6.16). Further, PAG showed a significantly larger bootstrapped AUC to discriminate between csPC and non-csPC than that of adjusted PI-RADS ≥ 3 (AUC = 0.981, 95% CI: 0.975-0.987). DATA CONCLUSION PAG may be associated with the risk of csPC and could outperform other PC risk factors. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- Alvaro Fernandez-Quilez
- Department of Computer Science and Electrical Engineering, University of Stavanger, Stavanger, Norway
- SMIL, Department of Radiology, Stavanger University Hospital, Stavanger, Norway
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Tobias Nordström
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, Stockholm, Sweden
| | - Fredrik Jäderling
- Department of Radiology, Capio Saint Göran Hospital, Stockholm, Sweden
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Svein Reidar Kjosavik
- General Practice and Care Coordination Research Group, Stavanger University Hospital, Stavanger, Norway
| | - Martin Eklund
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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Agrotis G, Pooch E, Abdelatty M, Benson S, Vassiou A, Vlychou M, Beets-Tan RGH, Schoots IG. Diagnostic performance of ADC and ADCratio in MRI-based prostate cancer assessment: A systematic review and meta-analysis. Eur Radiol 2024:10.1007/s00330-024-10890-6. [PMID: 38995382 DOI: 10.1007/s00330-024-10890-6] [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: 02/18/2024] [Revised: 04/26/2024] [Accepted: 05/19/2024] [Indexed: 07/13/2024]
Abstract
OBJECTIVES To identify factors influencing the diagnostic performance of the quantitative imaging biomarkers ADC and ADCratio in prostate cancer (PCa) detection. MATERIALS AND METHODS A systematic literature search was conducted in Embase, Medline and Web of Science, for studies evaluating ADC values and ADCratio for PCa diagnosis, using the same patient cohorts and using histopathological references as ground truth. Pooled sensitivities, specificities, summary ROC curves and AUCs were calculated from constructed contingency data tables. Diagnostic performance (AUC) was quantitatively pooled using a bivariate mixed effects model. For identifying influencing factors, subgroup analysis, publication bias and heterogeneity assessment were investigated. RESULTS Thirteen studies, involving 1038 patients and 1441 lesions, were included. For ADC, the pooled sensitivity and specificity was 80% (95% CI: 74-85%) and 78% (95% CI: 70-85%), respectively. For ADCratio pooled sensitivity and specificity was 80% (95% CI: 74-84%) and 80% (95% CI: 71-87%). Summary ROC analysis revealed AUCs of 0.86 (95% CI: 0.83-0.89) and 0.86 (95% CI: 0.83-0.89), respectively. Meta-regression showed heterogeneity between both imaging biomarkers. Subgroup analysis showed that ADCratio improved diagnostic performance in comparison to ADC when including both peripheral and transitional zone lesions (AUC: 0.87 [95% CI: 0.84-0.90] and 0.82 [95% CI: 0.79-0.85], respectively). CONCLUSION Both ADC and ADCratio imaging biomarkers showed good and comparable diagnostic performance in PCa diagnosis. However, ADCratio shows better diagnostic performance than ADC in diagnosing transition zone cancers. CLINICAL RELEVANCE STATEMENT In quantitative MRI-based PCa diagnosis, the imaging biomarker ADCratio is useful in challenging MRI readings of lesions. Understanding the performance of quantitative imaging biomarkers better can aid diagnostic MRI protocols, enhancing the precision of PCa assessments. KEY POINTS MRI diffusion-weighted imaging-based ADC and ADCratio have comparable diagnostic performance in PCa assessment. In contrast to ADC, the ADCratio improves diagnostic performance, when assessing whole gland lesions. Compared to ADCratio, the ADC demonstrates enhanced diagnostic performance when evaluating peripheral zone lesions.
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Affiliation(s)
- Georgios Agrotis
- Department of Radiology, University Hospital of Larissa, Larissa, Greece.
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
| | - Eduardo Pooch
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
- GROW School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands
| | - Mohamed Abdelatty
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
- Department of Diagnostic and Interventional Radiology, Kasr Al-Ainy Hospital, Cairo University, Giza, Egypt
| | - Sean Benson
- Department of Diagnostic and Interventional Radiology, Kasr Al-Ainy Hospital, Cairo University, Giza, Egypt
| | - Aikaterini Vassiou
- Department of Radiology, University Hospital of Larissa, Larissa, Greece
| | - Marianna Vlychou
- Department of Radiology, University Hospital of Larissa, Larissa, Greece
| | - Regina G H Beets-Tan
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
- GROW School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands
| | - Ivo G Schoots
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
- Department of Radiology & Nuclear Medicine, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
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Kim B, Mathai TS, Helm K, Summers RM. AUTOMATED CLASSIFICATION OF MULTI-PARAMETRIC BODY MRI SERIES. ARXIV 2024:arXiv:2405.08247v1. [PMID: 38903740 PMCID: PMC11188138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 06/22/2024]
Abstract
Multi-parametric MRI (mpMRI) studies are widely available in clinical practice for the diagnosis of various diseases. As the volume of mpMRI exams increases yearly, there are concomitant inaccuracies that exist within the DICOM header fields of these exams. This precludes the use of the header information for the arrangement of the different series as part of the radiologist's hanging protocol, and clinician oversight is needed for correction. In this pilot work, we propose an automated framework to classify the type of 8 different series in mpMRI studies. We used 1,363 studies acquired by three Siemens scanners to train a DenseNet-121 model with 5-fold cross-validation. Then, we evaluated the performance of the DenseNet-121 ensemble on a held-out test set of 313 mpMRI studies. Our method achieved an average precision of 96.6%, sensitivity of 96.6%, specificity of 99.6%, and F 1 score of 96.6% for the MRI series classification task. To the best of our knowledge, we are the first to develop a method to classify the series type in mpMRI studies acquired at the level of the chest, abdomen, and pelvis. Our method has the capability for robust automation of hanging protocols in modern radiology practice.
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Affiliation(s)
- Boah Kim
- Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, USA
| | - Tejas Sudharshan Mathai
- Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, USA
| | - Kimberly Helm
- Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, USA
| | - Ronald M Summers
- Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, USA
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Turkbey B. Use of Molecular Imaging to Further Investigate PI-RADS 3 Lesions. Radiology 2024; 311:e240401. [PMID: 38771180 PMCID: PMC11140525 DOI: 10.1148/radiol.240401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Revised: 03/13/2024] [Accepted: 03/14/2024] [Indexed: 05/22/2024]
Affiliation(s)
- Baris Turkbey
- From the Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, 10 Center Dr, Room B3B85, Bethesda, MD 20892
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de Oliveira Correia ET, Purysko AS, Paranhos BM, Shoag JE, Padhani AR, Bittencourt LK. PI-RADS Upgrading Rules: Impact on Prostate Cancer Detection and Biopsy Avoidance of MRI-Directed Diagnostic Pathways. AJR Am J Roentgenol 2024; 222:e2330611. [PMID: 38353450 DOI: 10.2214/ajr.23.30611] [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] [Indexed: 02/22/2024]
Abstract
BACKGROUND. PI-RADS incorporates rules by which ancillary sequence findings upgrade a dominant score to a higher final category. Evidence on the upgrading rules' impact on diagnostic pathways remains scarce. OBJECTIVE. The purpose of this article was to evaluate the clinical net benefit of the PI-RADS upgrading rules in MRI-directed diagnostic pathways. METHODS. This study was a retrospective analysis of a prospectively maintained clinical registry. The study included patients without known prostate cancer who underwent prostate MRI followed by prostate biopsy from January 2016 to May 2020. Clinically significant prostate cancer (csPCa) was defined as International Society of Urological Pathology (ISUP) grade group 2 and higher. csPCa detection was compared between dominant (i.e., no upgrade rule applied) and upgraded lesions. Decision-curve analysis was used to compare the net benefit, considering the trade-off of csPCa detection and biopsy avoidance, of MRI-directed pathways in scenarios considering and disregarding PI-RADS upgrading rules. These included a biopsy-all pathway, MRI-focused pathway (no biopsy for PI-RADS ≤ 2), and risk-based pathway (use of PSA density ≥ 0.15 ng/mL2 to select patients with PI-RADS ≤ 3 for biopsy). RESULTS. The sample comprised 716 patients (mean age, 64.9 years; 93 with a PI-RADS ≤ 2 examination, 623 with total of 780 PI-RADS ≥ 3 lesions). Frequencies of csPCa were not significantly different between dominant and upgraded PI-RADS 3 transition zone lesions (20% vs 19%, respectively), dominant and upgraded PI-RADS 4 transition zone lesions (33% vs 26%), and dominant and upgraded PI-RADS 4 peripheral zone lesions (58% vs 45%) (p > .05). In the biopsy-all, per-guideline MRI-focused, MRI-focused disregarding upgrading rules, per-guideline risk-based, and risk-based disregarding upgrading rules pathways, csPCa frequency was 53%, 52%, 51%, 52%, and 48% and biopsy avoidance was 0%, 13%, 16%, 19%, and 25%, respectively. Disregarding upgrading rules yielded 5.5 and 1.9 biopsies avoided per missed csPCa for MRI-focused and risk-based pathways, respectively. At probability thresholds for biopsy selection of 7.5-30.0%, net benefit was highest for the per-guideline risk-based pathway. CONCLUSION. Disregarding PI-RADS upgrading rules reduced net clinical bene fit of the risk-based MRI-directed diagnostic pathway when considering trade-offs between csPCa detection and biopsy avoidance. CLINICAL IMPACT. This study supports the application of PI-RADS upgrading rules to optimize biopsy selection, particularly in risk-based pathways.
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Affiliation(s)
| | - Andrei S Purysko
- Department of Radiology, Abdominal Imaging Section, Cleveland Clinic, Cleveland, OH
| | - Bruno Merz Paranhos
- Department of Radiology, Diagnosticos da America S.A, Rio de Janeiro, Brazil
| | - Jonathan E Shoag
- Case Western Reserve University, Cleveland, OH
- Case Comprehensive Cancer Center, Cleveland, OH
- Department of Urology, University Hospitals Cleveland Medical Center, Cleveland, OH
- Department of Urology, Weill Cornell Medicine, New York, NY
| | - Anwar R Padhani
- Paul Strickland Scanner Centre, Mount Vernon Hospital, Middlesex, United Kingdom
| | - Leonardo K Bittencourt
- Department of Radiology, University Hospitals Cleveland Medical Center, 11100 Euclid Ave, Cleveland, Ohio 44106
- Case Western Reserve University, Cleveland, OH
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Zhang C, Tu X, Dai J, Zhang Z, Shen C, Wu Q, Liu Z, Lin T, Qiu S, Yang L, Yang L, Zhang M, Cai D, Bao Y, Zeng H, Wei Q. Utilization trend of prebiopsy multiparametric magnetic resonance imaging and its impact on prostate cancer detection: Real-world insights from a high-volume center in southwest China. Prostate 2024; 84:539-548. [PMID: 38173301 DOI: 10.1002/pros.24669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 11/24/2023] [Accepted: 12/19/2023] [Indexed: 01/05/2024]
Abstract
BACKGROUND Data on the utilization and effects of prebiopsy prostate multiparametric magnetic resonance imaging (mpMRI) to support its routine use in real-world setting are still scarce. OBJECTIVE To evaluate the change of clinical practice of prebiopsy mpMRI over time, and assess its diagnostic accuracy. DESIGN, SETTING, AND PARTICIPANTS We retrospectively analyzed data from 6168 patients who underwent primary prostate biopsy (PBx) between January 2011 and December 2021 and had prostate-specific antigen (PSA) values ranging from 3 to 100 ng/mL. INTERVENTION Prebiopsy MRI at the time of PBx. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS We performed general linear regression and to elucidate trends in the annual use of prebiopsy mpMRI and conducted multivariable logistic regression to evaluate the potential benefits of incorporating prebiopsy mpMRI for prostate cancer (PCa) detection. RESULTS AND LIMITATIONS The utilization of prebiopsy mpMRI significantly increased from 9.2% in 2011 to 75.0% in 2021 (p < 0.001). In addition, prebiopsy mpMRI significantly reduced negative PBx by 8.6% while improving the detection of clinically significant PCa (csPCa) by 7.0%. Regression analysis showed that the utilization of prebiopsy mpMRI was significantly associated with a 48% (95% confidence interval [CI]: 1.19-1.84) and 36% (95% CI: 1.12-1.66) increased PCa detection rate in the PSA 3-10 ng/mL and 10-20 ng/mL groups, respectively; and a 34% increased csPCa detection rate in the PSA 10-20 ng/mL group (95% CI: 1.09-1.64). The retrospective design and the single center cohort constituted the limitations of this study. CONCLUSIONS Our study demonstrated a notable rise in the utilization of prebiopsy mpMRI in the past decade. The adoption of this imaging technique was significantly associated with an increased probability of detecting prostate cancer. PATIENT SUMMARY From 2011 to 2021, we demonstrated a steady increase in the utilization of prebiopsy mpMRI among biopsy-naïve men. We also confirmed the positive impact of prebiopsy mpMRI utilization on the detection of prostate cancer.
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Affiliation(s)
- Chichen Zhang
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Xiang Tu
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Jindong Dai
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Zilong Zhang
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Chenlan Shen
- Department of Laboratory Medicine, Med+X Center for Manufacturing, West China Hospital, Sichuan University, Chengdu, China
| | - Qiyou Wu
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Zhenhua Liu
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Tianhai Lin
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Shi Qiu
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
- Department of Molecular Oncology, Institute of Oncology Research (IOR), Oncology Institute of Southern Switzerland (IOSI), Bellinzona, Switzerland
| | - Lu Yang
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Ling Yang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Mengni Zhang
- Department of Pathology and Laboratory of Pathology, State Key Laboratory of Biotherapy, West China Hospital, West China Medical School, Sichuan University, Chengdu, China
| | - Diming Cai
- Department of Ultrasound, West China Hospital, Sichuan University, Chengdu, China
| | - Yige Bao
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Hao Zeng
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Qiang Wei
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
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Yilmaz EC, Lin Y, Belue MJ, Harmon SA, Phelps TE, Merriman KM, Hazen LA, Garcia C, Johnson L, Lay NS, Toubaji A, Merino MJ, Patel KR, Parnes HL, Law YM, Wood BJ, Gurram S, Choyke PL, Pinto PA, Turkbey B. PI-RADS Version 2.0 Versus Version 2.1: Comparison of Prostate Cancer Gleason Grade Upgrade and Downgrade Rates From MRI-Targeted Biopsy to Radical Prostatectomy. AJR Am J Roentgenol 2024; 222:e2329964. [PMID: 37729551 DOI: 10.2214/ajr.23.29964] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
BACKGROUND. Precise risk stratification through MRI/ultrasound (US) fusion-guided targeted biopsy (TBx) can guide optimal prostate cancer (PCa) management. OBJECTIVE. The purpose of this study was to compare PI-RADS version 2.0 (v2.0) and PI-RADS version 2.1 (v2.1) in terms of the rates of International Society of Urological Pathology (ISUP) grade group (GG) upgrade and downgrade from TBx to radical prostatectomy (RP). METHODS. This study entailed a retrospective post hoc analysis of patients who underwent 3-T prostate MRI at a single institution from May 2015 to March 2023 as part of three prospective clinical trials. Trial participants who underwent MRI followed by MRI/US fusion-guided TBx and RP within a 1-year interval were identified. A single genitourinary radiologist performed clinical interpretations of the MRI examinations using PI-RADS v2.0 from May 2015 to March 2019 and PI-RADS v2.1 from April 2019 to March 2023. Upgrade and downgrade rates from TBx to RP were compared using chi-square tests. Clinically significant cancer was defined as ISUP GG2 or greater. RESULTS. The final analysis included 308 patients (median age, 65 years; median PSA density, 0.16 ng/mL2). The v2.0 group (n = 177) and v2.1 group (n = 131) showed no significant difference in terms of upgrade rate (29% vs 22%, respectively; p = .15), downgrade rate (19% vs 21%, p = .76), clinically significant upgrade rate (14% vs 10%, p = .27), or clinically significant downgrade rate (1% vs 1%, p > .99). The upgrade rate and downgrade rate were also not significantly different between the v2.0 and v2.1 groups when stratifying by index lesion PI-RADS category or index lesion zone, as well as when assessed only in patients without a prior PCa diagnosis (all p > .01). Among patients with GG2 or GG3 at RP (n = 121 for v2.0; n = 103 for v2.1), the concordance rate between TBx and RP was not significantly different between the v2.0 and v2.1 groups (53% vs 57%, p = .51). CONCLUSION. Upgrade and downgrade rates from TBx to RP were not significantly different between patients whose MRI examinations were clinically interpreted using v2.0 or v2.1. CLINICAL IMPACT. Implementation of the most recent PI-RADS update did not improve the incongruence in PCa grade assessment between TBx and surgery.
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Affiliation(s)
- Enis C Yilmaz
- Molecular Imaging Branch, National Cancer Institute, NIH, 10 Center Dr, MSC 1182, Bldg 10, Rm B3B85, Bethesda, MD 20892
| | - Yue Lin
- Molecular Imaging Branch, National Cancer Institute, NIH, 10 Center Dr, MSC 1182, Bldg 10, Rm B3B85, Bethesda, MD 20892
| | - Mason J Belue
- Molecular Imaging Branch, National Cancer Institute, NIH, 10 Center Dr, MSC 1182, Bldg 10, Rm B3B85, Bethesda, MD 20892
| | - Stephanie A Harmon
- Molecular Imaging Branch, National Cancer Institute, NIH, 10 Center Dr, MSC 1182, Bldg 10, Rm B3B85, Bethesda, MD 20892
| | - Tim E Phelps
- Molecular Imaging Branch, National Cancer Institute, NIH, 10 Center Dr, MSC 1182, Bldg 10, Rm B3B85, Bethesda, MD 20892
| | - Katie M Merriman
- Molecular Imaging Branch, National Cancer Institute, NIH, 10 Center Dr, MSC 1182, Bldg 10, Rm B3B85, Bethesda, MD 20892
| | - Lindsey A Hazen
- Center for Interventional Oncology, National Cancer Institute, NIH, Bethesda, MD
- Department of Radiology, Clinical Center, NIH, Bethesda, MD
| | - Charisse Garcia
- Center for Interventional Oncology, National Cancer Institute, NIH, Bethesda, MD
- Department of Radiology, Clinical Center, NIH, Bethesda, MD
| | - Latrice Johnson
- Molecular Imaging Branch, National Cancer Institute, NIH, 10 Center Dr, MSC 1182, Bldg 10, Rm B3B85, Bethesda, MD 20892
| | - Nathan S Lay
- Molecular Imaging Branch, National Cancer Institute, NIH, 10 Center Dr, MSC 1182, Bldg 10, Rm B3B85, Bethesda, MD 20892
| | - Antoun Toubaji
- Laboratory of Pathology, National Cancer Institute, NIH, Bethesda, MD
| | - Maria J Merino
- Laboratory of Pathology, National Cancer Institute, NIH, Bethesda, MD
| | - Krishnan R Patel
- Radiation Oncology Branch, National Cancer Institute, NIH, Bethesda, MD
| | - Howard L Parnes
- Division of Cancer Prevention, National Cancer Institute, NIH, Bethesda, MD
| | - Yan Mee Law
- Department of Radiology, Singapore General Hospital, Singapore
| | - Bradford J Wood
- Center for Interventional Oncology, National Cancer Institute, NIH, Bethesda, MD
- Department of Radiology, Clinical Center, NIH, Bethesda, MD
| | - Sandeep Gurram
- Urologic Oncology Branch, National Cancer Institute, NIH, Bethesda, MD
| | - Peter L Choyke
- Molecular Imaging Branch, National Cancer Institute, NIH, 10 Center Dr, MSC 1182, Bldg 10, Rm B3B85, Bethesda, MD 20892
| | - Peter A Pinto
- Urologic Oncology Branch, National Cancer Institute, NIH, Bethesda, MD
| | - Baris Turkbey
- Molecular Imaging Branch, National Cancer Institute, NIH, 10 Center Dr, MSC 1182, Bldg 10, Rm B3B85, Bethesda, MD 20892
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10
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Aguirre DA, Cardona Ortegón JD. Unlocking the Benefits of Multiparametric MRI for Predicting Prostate Cancer Recurrence. Radiology 2023; 309:e232819. [PMID: 37987663 DOI: 10.1148/radiol.232819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Affiliation(s)
- Diego A Aguirre
- From the Department of Radiology, Abdominal Imaging Section, Fundación Santa Fe de Bogotá, Calle 116 # 9-02, 110111 Bogotá, Colombia
| | - José David Cardona Ortegón
- From the Department of Radiology, Abdominal Imaging Section, Fundación Santa Fe de Bogotá, Calle 116 # 9-02, 110111 Bogotá, Colombia
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11
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Turkbey B. The Potential for Deep Learning Reconstruction to Improve the Quality of T2-weighted Prostate MRI. Radiology 2023; 308:e232344. [PMID: 37750773 PMCID: PMC10546281 DOI: 10.1148/radiol.232344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Revised: 09/09/2023] [Accepted: 09/11/2023] [Indexed: 09/27/2023]
Affiliation(s)
- Baris Turkbey
- From the Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, 10 Center Dr, Room B3B85, Bethesda, MD 20892
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12
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Kalchev E. Evaluating the Utility of Prostate-Specific Antigen Density in Risk Stratification of PI-RADS 3 Peripheral Zone Lesions on Non-Contrast-Enhanced Prostate MRI: An Exploratory Single-Institution Study. Cureus 2023; 15:e41369. [PMID: 37546087 PMCID: PMC10399968 DOI: 10.7759/cureus.41369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/04/2023] [Indexed: 08/08/2023] Open
Abstract
Objective This study aimed to explore the potential of prostate-specific antigen density (PSAD) as a supplementary tool for defining high-risk Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions in the peripheral zone on non-contrast-enhanced MRI. This additional stratification tool could supplement the decision-making process for biopsy, potentially helping in identifying higher-risk patients more accurately, minimizing unnecessary procedures in lower-risk patients, and limiting the need for dynamic contrast-enhanced (DCE) scans. Materials and methods Between January 2019 and April 2023, 30 patients with PI-RADS 3 lesions underwent MRI-ultrasound fusion biopsies at our institution. Age and PSAD values were investigated using logistic regression and chi-square automatic interaction detection (CHAID) analysis to discern their predictive value for malignancy. Results The mean patient age was 64.7 years, and the mean PSAD was 0.13 ng/mL2. Logistic regression demonstrated PSAD to be a significant predictor of cancer (p=0.012), but not age (p=0.855). CHAID analysis further identified a PSAD cut-off value of 0.12, below which the cancer detection rate was 23.1% and above which the rate increased to 76.5%. Conclusions This exploratory study suggests that PSAD might be utilized to enhance the stratification of high-risk PI-RADS 3 lesions in the peripheral zone on non-contrast-enhanced MRI, aiding in decision-making for biopsy. While biopsy remains the gold standard for definitive diagnosis, a high PSAD value may suggest a greater need for biopsy in this specific group. Although further validation in larger cohorts is required, our findings contribute to the ongoing discourse on optimizing PI-RADS 3 lesion management. Limitations include a small sample size, the retrospective nature of the study, and the single-center setting, which may impact the generalizability of our results.
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Affiliation(s)
- Emilian Kalchev
- Diagnostic Imaging, St Marina University Hospital, Varna, BGR
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13
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Goh V. Genitourinary Imaging in 2040. Radiology 2023; 307:e230223. [PMID: 37249430 PMCID: PMC10315527 DOI: 10.1148/radiol.230223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 02/03/2023] [Accepted: 02/06/2023] [Indexed: 05/31/2023]
Affiliation(s)
- Vicky Goh
- From the Department of Cancer Imaging, School of Biomedical
Engineering and Imaging Sciences, King’s College London, SE1 7EH,
United Kingdom; and Department of Radiology, Guy’s & St
Thomas’ NHS Foundation Trust, Level 1, Lambeth Wing, St Thomas’
Hospital, Westminster Bridge Rd, London, United Kingdom
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