Assessment of the accuracy of biparametric MRI/TRUS fusion-guided biopsy for index tumor evaluation using postoperative pathology specimens.

BACKGROUND: Multiparametric MRI (mpMRI) is widely used for the diagnosis, surveillance, and staging of prostate cancer. However, it has several limitations, including higher costs, longer examination times, and the use of gadolinium-based contrast agents. This study aimed to investigate the accuracy of preoperatively assessed index tumors (ITs) using biparametric MRI (bpMRI)/transrectal ultrasound (TRUS) fusion biopsy compared with radical prostatectomy (RP) specimens. METHODS: We included 113 patients diagnosed with prostate cancer through bpMRI/TRUS fusion-guided biopsies of lesions with a Prostate Imaging Reporting and Data System (PI-RADS) category ≥ 3. These patients underwent robot-assisted laparoscopic radical prostatectomy (RARP) at our institution between July 2017 and March 2023. We examined the localization of preoperative and postoperative ITs, the highest Gleason score (GS), and tumor diameter in these patients. RESULTS: The preoperative cT stage matched the postoperative pT stage in 53 cases (47%), while 31 cases (27%) were upstaged, and 29 cases (26%) were downstaged (Weighted Kappa = 0.21). The preoperative and postoperative IT localizations were consistent in 97 cases (86%). The concordance rate between Gleason groups in targeted biopsies and RP specimens was 51%, with an upgrade in 25 cases (23%) and a downgrade in 27 cases (25%) (Weighted Kappa = 0.42). The maximum diameter of the IT and the maximum cancer core length on biopsy were correlated with the RP tumor's maximum diameter (p < 0.001 for both). CONCLUSION: The diagnostic accuracy of bpMRI/TRUS fusion biopsy is comparable to mpMRI, suggesting that it can be a cost-effective and time-saving alternative.

Biparametric magnetic resonance imaging-based radiomics features for prediction of lymphovascular invasion in rectal cancer.

BACKGROUND: Preoperative assessment of lymphovascular invasion(LVI) of rectal cancer has very important clinical significance. However, accurate preoperative imaging evaluation of LVI is highly challenging because the resolution of MRI is still limited. Relatively few studies have focused on prediction of LVI of rectal cancer with the tool of radiomics, especially in patients with negative statue of MRI-based extramural vascular invasion (mrEMVI).The purpose of this study was to explore the preoperative predictive value of biparametric MRI-based radiomics features for LVI of rectal cancer in patients with the negative statue of mrEMVI. METHODS: The data of 146 cases of rectal adenocarcinoma confirmed by postoperative pathology were retrospectively collected. In the cases, 38 had positive status of LVI. All patients were examined by MRI before the operation. The biparametric MRI protocols included T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI). We used whole-volume three-dimensional method and two feature selection methods, minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO), to extract and select the features. Logistics regression was used to construct models. The area under the receiver operating characteristic curve (AUC) and DeLong's test were used to evaluate the diagnostic performance of the radiomics based on T2WI and DWI and the combined models. RESULTS: Radiomics models based on T2WI and DWI had good predictive performance for LVI of rectal cancer in both the training cohort and the validation cohort. The AUCs of the T2WI model were 0.87 and 0.87, and the AUCs of the DWI model were 0.94 and 0.92. The combined model was better than the T2WI model, with AUCs of 0.97 and 0.95. The predictive performance of the DWI model was comparable to that of the combined model. CONCLUSIONS: The radiomics model based on biparametric MRI, especially DWI, had good predictive value for LVI of rectal cancer. This model has the potential to facilitate the clinical recognition of LVI in rectal cancer preoperatively.

Performance of Artificial Intelligence-Aided Diagnosis System for Clinically Significant Prostate Cancer with MRI: A Diagnostic Comparison Study.

BACKGROUND: The high level of expertise required for accurate interpretation of prostate MRI. PURPOSE: To develop and test an artificial intelligence (AI) system for diagnosis of clinically significant prostate cancer (CsPC) with MRI. STUDY TYPE: Retrospective. SUBJECTS: One thousand two hundred thirty patients from derivation cohort between Jan 2012 and Oct 2019, and 169 patients from a publicly available data (U-Net: 423 for training/validation and 49 for test and TrumpeNet: 820 for training/validation and 579 for test). FIELD STRENGTH/SEQUENCE: 3.0T/scanners, T2 -weighted imaging (T2 WI), diffusion-weighted imaging, and apparent diffusion coefficient map. ASSESSMENT: Close-loop AI system was trained with an Unet for prostate segmentation and a TrumpetNet for CsPC detection. Performance of AI was tested in 410 internal and 169 external sets against 24 radiologists categorizing into junior, general and subspecialist group. Gleason score >6 was identified as CsPC at pathology. STATISTICAL TESTS: Area under the receiver operating characteristic curve (AUC-ROC); Delong test; Meta-regression I2 analysis. RESULTS: In average, for internal test, AI had lower AUC-ROC than subspecialists (0.85 vs. 0.92, P < 0.05), and was comparable to junior (0.84, P = 0.76) and general group (0.86, P = 0.35). For external test, both AI (0.86) and subspecialist (0.86) had higher AUC than junior (0.80, P < 0.05) and general reader (0.83, P < 0.05). In individual, it revealed moderate diagnostic heterogeneity in 24 readers (Mantel-Haenszel I2  = 56.8%, P < 0.01), and AI outperformed 54.2% (13/24) of readers in summary ROC analysis. In multivariate test, Gleason score, zonal location, PI-RADS score and lesion size significantly impacted the accuracy of AI; while effect of data source, MR device and parameter settings on AI performance is insignificant (P > 0.05). DATA CONCLUSION: Our AI system can match and to some case exceed clinicians for the diagnosis of CsPC with prostate MRI. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Diagnostic Accuracy of MRI for Solid Renal Masses: A Systematic Review and Meta-analysis.

BACKGROUND: Biparametric (bp)-MRI and multiparametric (mp)-MRI may improve the diagnostic accuracy of renal mass histology. PURPOSE: To evaluate the available evidence on the diagnostic accuracy of bp-MRI and mp-MRI for solid renal masses in differentiating malignant from benign, aggressive from indolent, and clear cell renal cell carcinoma (ccRCC) from other histology. STUDY TYPE: Systematic review. POPULATION: MEDLINE, EMBASE, and CENTRAL up to January 11, 2022 were searched. FIELD STRENGTH/SEQUENCE: 1.5 or 3 Tesla. ASSESSMENT: Eligible studies evaluated the accuracy of MRI (with at least two sequences: T2, T1, dynamic contrast and diffusion-weighted imaging) for diagnosis of solid renal masses in adult patients, using histology as reference standard. Risk of bias and applicability were assessed using QUADAS-2. STATISTICAL TESTS: Meta-analysis using a bivariate logitnormal random effects model. RESULTS: We included 10 studies (1239 masses from approximately 1200 patients). The risk of bias was high in three studies, unclear in five studies and low in two studies. The diagnostic accuracy of malignant (vs. benign) masses was assessed in five studies (64% [179/281] malignant). The summary estimate of sensitivity was 95% (95% confidence interval [CI]: 77%-99%), and specificity was 63% (95% CI: 46%-77%). No study assessed aggressive (vs. indolent) masses. The diagnostic accuracy of ccRCC (vs. other subtypes) was evaluated in six studies (47% [455/971] ccRCC): the summary estimate of sensitivity was 85% (95% CI: 77%-90%) and specificity was 77% (95% CI: 73%-81%). DATA CONCLUSION: Our study reveals deficits in the available evidence on MRI for diagnosis of renal mass histology. The number of studies was limited, at unclear/high risk of bias, with heterogeneous definitions of solid masses, imaging techniques, diagnostic criteria, and outcome measures. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Deep-learning prostate cancer detection and segmentation on biparametric versus multiparametric magnetic resonance imaging: Added value of dynamic contrast-enhanced imaging.

OBJECTIVES: To develop diagnostic algorithms of multisequence prostate magnetic resonance imaging for cancer detection and segmentation using deep learning and explore values of dynamic contrast-enhanced imaging in multiparametric imaging, compared with biparametric imaging. METHODS: We collected 3227 multiparametric imaging sets from 332 patients, including 218 cancer patients (291 biopsy-proven foci) and 114 noncancer patients. Diagnostic algorithms of T2-weighted, T2-weighted plus dynamic contrast-enhanced, biparametric, and multiparametric imaging were built using 2578 sets, and their performance for clinically significant cancer was evaluated using 649 sets. RESULTS: Biparametric and multiparametric imaging had following region-based performance: sensitivity of 71.9% and 74.8% (p = 0.394) and positive predictive value of 61.3% and 74.8% (p = 0.013), respectively. In side-specific analyses of cancer images, the specificity was 72.6% and 89.5% (p < 0.001) and the negative predictive value was 78.9% and 83.5% (p = 0.364), respectively. False-negative cancer on multiparametric imaging was smaller (p = 0.002) and more dominant with grade group ≤2 (p = 0.028) than true positive foci. In the peripheral zone, false-positive regions on biparametric imaging turned out to be true negative on multiparametric imaging more frequently compared with the transition zone (78.3% vs. 47.2%, p = 0.018). In contrast, T2-weighted plus dynamic contrast-enhanced imaging had lower specificity than T2-weighted imaging (41.1% vs. 51.6%, p = 0.042). CONCLUSIONS: When using deep learning, multiparametric imaging provides superior performance to biparametric imaging in the specificity and positive predictive value, especially in the peripheral zone. Dynamic contrast-enhanced imaging helps reduce overdiagnosis in multiparametric imaging.

Detection of Prostate Cancer Using Biparametric Prostate MRI, Radiomics, and Kallikreins: A Retrospective Multicenter Study of Men With a Clinical Suspicion of Prostate Cancer.

BACKGROUND: Accurate detection of clinically significant prostate cancer (csPCa), Gleason Grade Group ≥ 2, remains a challenge. Prostate MRI radiomics and blood kallikreins have been proposed as tools to improve the performance of biparametric MRI (bpMRI). PURPOSE: To develop and validate radiomics and kallikrein models for the detection of csPCa. STUDY TYPE: Retrospective. POPULATION: A total of 543 men with a clinical suspicion of csPCa, 411 (76%, 411/543) had kallikreins available and 360 (88%, 360/411) did not take 5-alpha-reductase inhibitors. Two data splits into training, validation (split 1: single center, n = 72; split 2: random 50% of pooled datasets from all four centers), and testing (split 1: 4 centers, n = 288; split 2: remaining 50%) were evaluated. FIELD STRENGTH/SEQUENCE: A 3 T/1.5 T, TSE T2-weighted imaging, 3x SE DWI. ASSESSMENT: In total, 20,363 radiomic features calculated from manually delineated whole gland (WG) and bpMRI suspicion lesion masks were evaluated in addition to clinical parameters, prostate-specific antigen, four kallikreins, MRI-based qualitative (PI-RADSv2.1/IMPROD bpMRI Likert) scores. STATISTICAL TESTS: For the detection of csPCa, area under receiver operating curve (AUC) was calculated using the DeLong's method. A multivariate analysis was conducted to determine the predictive power of combining variables. The values of P-value < 0.05 were considered significant. RESULTS: The highest prediction performance was achieved by IMPROD bpMRI Likert and PI-RADSv2.1 score with AUC = 0.85 and 0.85 in split 1, 0.85 and 0.83 in split 2, respectively. bpMRI WG and/or kallikreins demonstrated AUCs ranging from 0.62 to 0.73 in split 1 and from 0.68 to 0.76 in split 2. AUC of bpMRI lesion-derived radiomics model was not statistically different to IMPROD bpMRI Likert score (split 1: AUC = 0.83, P-value = 0.306; split 2: AUC = 0.83, P-value = 0.488). DATA CONCLUSION: The use of radiomics and kallikreins failed to outperform PI-RADSv2.1/IMPROD bpMRI Likert and their combination did not lead to further performance gains. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

Clinically Significant Prostate Cancer Detection After a Negative Prebiopsy MRI Examination: Comparison of Biparametric Versus Multiparametric MRI.

BACKGROUND. The frequency of clinically significant prostate cancer (csPCa) following negative biparametric MRI (bpMRI) and multiparametric MRI (mpMRI) has not been well investigated in direct comparative studies. OBJECTIVE. The purposes of this study were to compare the frequency of csPCa after negative prebiopsy bpMRI and mpMRI and to evaluate factors predictive of csPCa in the two cohorts. METHODS. This retrospective study included 232 men (mean age, 64.5 years) with negative bpMRI from August 2017 to March 2020 and 193 men (mean age, 69.0 years) with negative mpMRI from January 2018 to December 2018. PI-RADS category 1 or 2 was defined as negative. The study institution offered bpMRI as a low-cost self-pay option for patients without insurer coverage of prebiospy mpMRI. Patient characteristics and subsequent biopsy results were recorded. CsPCa was defined as Gleason score of 3 + 4 or greater. Multivariable regression analyses were performed to identify independent predictors of csPCa. The AUC of PSA density (PSAD) for csPCA was computed, and the diagnostic performance of PSAD was assessed at a clinically established threshold of 0.15 ng/mL2. RESULTS. Systematic biopsy was performed after negative bpMRI for 41.4% (96/232) of patients and after negative mpMRI for 30.5% (59/193) (p = .02). Among those undergoing biopsy, csPCa was present in 15.6% (15/96) in the bpMRI cohort versus 13.6% (8/59) in the mpMRI cohort (p = .69). The NPV for csPCa was 84% (81/96) for bpMRI and 86% (51/59) for mpMRI. In multivariable analyses, independent predictors of csPCa included smaller prostate volume (OR, 0.27; p < .001) and greater PSAD (OR, 3.09; p < .001). In multivariable models, bpMRI (compared with mpMRI) was not independently predictive of csPCa (p > .05). PSAD had an AUC for csPCa of 0.71 (95% CI, 0.56-0.87) in the bpMRI cohort versus 0.68 (95% CI, 0.42-0.93) in the mpMRI cohort. For detecting csPCa, a PSAD threshold of 0.15 ng/mL2 had NPV of 90% and PPV of 28%, in the bpMRI cohort versus NPV of 92% and PPV of 44% in the mpMRI cohort. CONCLUSION. The frequencies of csPCa were not significantly different at systematic biopsy performed after negative bpMRI and mpMRI examinations. PSAD had similar diagnostic utility for csPCa in the two cohorts. CLINICAL IMPACT. Either bpMRI or mpMRI, in combination with PSAD measurement, can help avoid negative prostate biopsies.

Biparametric prostate MRI: impact of a deep learning-based software and of quantitative ADC values on the inter-reader agreement of experienced and inexperienced readers.

OBJECTIVE: To investigate the impact of an artificial intelligence (AI) software and quantitative ADC (qADC) on the inter-reader agreement, diagnostic performance, and reporting times of prostate biparametric MRI (bpMRI) for experienced and inexperienced readers. MATERIALS AND METHODS: A total of 170 multiparametric MRI (mpMRI) of patients with suspicion of prostate cancer (PCa) were retrospectively reviewed by one experienced and one inexperienced reader three times, following a wash-out period. First, only the bpMRI sequences, including T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI) sequences, and apparent diffusion coefficient (ADC) maps, were used. Then, bpMRI and quantitative ADC values were used. Lastly, bpMRI and the AI software were used. Inter-reader agreement between the two readers and between each reader and the mpMRI original reports was calculated. Detection rates and reporting times were calculated for each group. RESULTS: Inter-reader agreement with respect to mpMRI was moderate for bpMRI, Quantib, and qADC for both the inexperienced (weighted k of 0.42, 0.45, and 0.41, respectively) and the experienced radiologists (weighted k of 0.44, 0.46, and 0.42, respectively). Detection rate of PCa was similar between the inexperienced (0.24, 0.26, and 0.23) and the experienced reader (0.26, 0.27 and 0.27), for bpMRI, Quantib, and qADC, respectively. Reporting times were lower for Quantib (8.23, 7.11, and 9.87 min for the inexperienced reader and 5.62, 5.07, and 6.21 min for the experienced reader, for bpMRI, Quantib, and qADC, respectively). CONCLUSIONS: AI and qADC did not have a significant impact on the diagnostic performance of both readers. The use of Quantib was associated with lower reporting times.

Optimized MRI Assessment for Clinically Significant Prostate Cancer: A STARD-Compliant Two-Center Study.

BACKGROUND: There is a requirement for a personalized strategy to make MRI more accessible to men with suspicion of clinically significant prostate cancer (CSPC). PURPOSE: To evaluate an optimized (Op)-MRI compared with biparametric (Bp)-MRI and multiparametric (Mp)-MRI for the diagnosis of CSPC. STUDY TYPE: Two-center, retrospective. SUBJECTS: A total of 346 patients from center 1 and 292 patients from center 2. FIELD STRENGTH/SEQUENCE: 3.0T scanners, T2 -weighted imaging (T2 WI), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) imaging. ASSESSMENT: Four radiologists interpreted the Bp-MRI (T2 WI and DWI) and Mp-MRI (T2 WI, DWI, and DCE) independently according to the Prostate Imaging Reporting and Data System (PI-RADS). For Op-MRI, two radiologists used an adjusted decision rule on Bp-MRI-assessed PI-RADS 3 lesions by determining early enhancement of DCE. Pathologies at biopsy and/or prostatectomy specimens were used as standard references. STATISTICAL TESTS: Performance was assessed using receiver operating characteristic (ROC) curves. Kappa statistics were used to assess interobserver variability. RESULTS: Interreader agreement was excellent for all three MRI assessments (all κ values >0.80). Op-MRI had comparable sensitivity (senior/junior: 90.9% [261/287] / 91.6% [263/287]) and higher specificity (78.1% [274/351] /74.4% [261/351]) compared with Mp-MRI (sensitivity: 92.3% [265/287] / 93.7% [269/287]; specificity: 67.8% [238/351] / 68.1% [239/351]) and Bp-MRI (sensitivity: 91.6% [263/287] / 93.4% [268/287]; specificity: 71.2% [250/351] / 70.1% [246/351]) for the diagnosis of CSPC. Compared to Mp-MRI, Op-MRI spared biopsy in 80.7% (515/638) of DCE scans with similar performance accuracy. Compared to Bp-MRI, Op-MRI downgraded 25.2% (31/123) of lesions at a cost of missing 6.5% (3/46) of malignancies, and upgraded 45.5% (56/123) of lesions with a positive predictive value of 62.5% (35/56) in 123 equivocal findings. DATA CONCLUSION: The Op-MRI, using an adjusted PI-RADS decision rule, did not compromise diagnostic accuracy with sparing biopsy in 80.7% of DCE scans compared to Mp-MRI, and outperformed Bp-MRI by regrading PI-RADS lesions. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY STAGE: 2.

Contrast Medium or No Contrast Medium for Prostate Cancer Diagnosis. That Is the Question.

The benefits and drawbacks of the dynamic contrast-enhanced MRI sequence for prostate cancer diagnosis are increasingly being recognized, with many centers adopting the biparametric (bp) MRI approach as the default initial approach. The abandonment of the routine use of contrast medium requires an assessment of the loss of diagnostic power against the gains in operational logistics, costs, time, capacity, and side effects. It is the balance of these factors weighted against the clinical priorities of patients that determines which patient groups can safely avoid dynamic contrast enhancement. Although systematic reviews and individual studies are broadly supportive of the bpMRI approach, the pathway impacts for men with suspected cancer using the bpMRI approach are still not well documented for clinical practice. Robust prospectively acquired data for bpMRI regarding biopsy avoidance, detection of clinically significant and insignificant cancers, and for increasing the precision of tumor grade and volume are needed. There is a requirement for prospective, randomized, or blinded head-to-head, multicenter studies, addressing the noninferiority of biopsy yields prompted by bpMRI and multiparametric MRI approaches. These studies should more precisely define patient groups where the benefits and harms of contrast enhancement are aligned to their clinical priorities. Only then can we be confident in recommending bpMRI as an initial diagnostic approach for prostate cancer diagnosis. Level of Evidence 1 Technical Efficacy Stage 5.

Added value of systematic biopsy in men with a clinical suspicion of prostate cancer undergoing biparametric MRI-targeted biopsy: multi-institutional external validation study.

PURPOSE: We aimed to develop and externally validate a nomogram based on MRI volumetric parameters and clinical information for deciding when SBx should be performed in addition to TBx in man with suspicious prostate MRI. MATERIALS AND METHODS: Retrospective analyses of single (IMPROD, NCT01864135) and multi-institution (MULTI-IMPROD, NCT02241122) clinical trials. All men underwent a unique rapid biparametric magnetic resonance imaging (IMPROD bpMRI) consisting of T2-weighted imaging and three separate DWI acquisitions. Men with IMPROD bpMRI Likert scores of 3-5 were included. Logistic regression models were developed using IMPROD trial (n = 122) and validated using MULTI-IMPROD trial (n = 262) data. The model's performance was evaluated in the terms of PCa detection with Gleason Grade Group 1 (clinically insignificant prostate cancer, iPCa) and > 1 (clinically significant prostate cancer, csPCa). Net benefits and decision curve analyses (DCA) were compared. Combined biopsies were used for reference. RESULTS: The developed nomogram included age, PSA, prostate volume, MRI suspicion score (IMPROD bpMRI Likert or PIRADsv2.1 score), MRI-suspicion lesion volume percentage, and lesion location. All these variables were significant predictors of csPCa in SBx in multivariable analysis. In the validation cohort (n = 262) using different nomogram cutoffs, 19-43% of men would have avoided SBx while missing 1-4% of csPCa and avoiding detection of 9-20% of iPCa. Similar performance was found for nomograms using IMPROD bpMRI Likert score or v2.1. CONCLUSIONS: The developed nomogram demonstrated potential to select men with a clinical suspicion of PCa who would benefit from performing SBx in addition to TBx. Public access to the nomogram is provided at: https://petiv.utu.fi/multiimprod/ .

PI-RADS Committee Position on MRI Without Contrast Medium in Biopsy-Naive Men With Suspected Prostate Cancer: Narrative Review.

The steadily increasing demand for diagnostic prostate MRI has led to concerns regarding the lack of access to and the availability of qualified MRI scanners and sufficiently experienced radiologists, radiographers, and technologists to meet the demand. Solutions must enhance operational benefits without compromising diagnostic performance, quality, and delivery of service. Solutions should also mitigate risks such as decreased reader confidence and referrer engagement. One approach may be the implementation of MRI without the use gadolinium-based contrast medium (bipara-metric MRI), but only if certain prerequisites such as high-quality imaging, expert interpretation quality, and availability of patient recall or on-table monitoring are mandated. Alternatively, or in combination, a clinical risk-based approach could be used for protocol selection, specifically, which biopsy-naive men need MRI with contrast medium (multiparametric MRI). There is a need for prospective studies in which biopsy decisions are made according to MRI without contrast enhancement. Such studies must define clinical and operational benefits and identify which patient groups can be scanned successfully without contrast enhancement. These higher-quality data are needed before the Prostate Imaging Reporting and Data System (PI-RADS) Committee can make evidence-based recommendations about MRI without contrast enhancement as an initial diagnostic approach for prostate cancer workup.

Noninvasive Prediction of High-Grade Prostate Cancer via Biparametric MRI Radiomics.

BACKGROUND: Gleason score (GS) is a histologic prognostic factor and the basis of treatment decision-making for prostate cancer (PCa). Treatment regimens between lower-grade (GS ≤7) and high-grade (GS >7) PCa differ largely and have great effects on cancer progression. PURPOSE: To investigate the use of different sequences in biparametric MRI (bpMRI) of the prostate gland for noninvasively distinguishing high-grade PCa. STUDY TYPE: Retrospective. POPULATION: In all, 489 patients (training cohort: N = 326; test cohort: N = 163) with PCa between June 2008 and January 2018. FIELD STRENGTH/SEQUENCE: 3.0T, pelvic phased-array coils, bpMRI including T2 -weighted imaging (T2 WI) and diffusion-weighted imaging (DWI); apparent diffusion coefficient map extracted from DWI. ASSESSMENT: The whole prostate gland was delineated. Radiomic features were extracted and selected using the Kruskal-Wallis test, the minimum redundancy-maximum relevance, and the sequential backward elimination algorithm. Two single-sequence radiomic (T2 WI, DWI) and two combined (T2 WI-DWI, T2 WI-DWI-Clinic) models were respectively constructed and validated via logistic regression. STATISTICAL TESTS: The Kruskal-Wallis test and chi-squared test were utilized to evaluate the differences among variable groups. P < 0.05 determined statistical significance. The area under the receiver operating characteristic curve (AUC), specificity, sensitivity, and accuracy were used to evaluate model performance. The Delong test was conducted to compare the differences between the AUCs of all models. RESULT: All radiomic models showed significant (P < 0.001) predictive performances. Between the single-sequence radiomic models, the DWI model achieved the most encouraging results, with AUCs of 0.801 and 0.787 in the training and test cohorts, respectively. For the combined models, the T2 WI-DWI models acquired an AUC of 0.788, which was almost the same with DWI in the test cohort, and no significant difference was found between them (training cohort: P = 0.199; test cohort: P = 0.924). DATA CONCLUSION: Radiomics based on bpMRI can noninvasively identify high-grade PCa before the operation, which is helpful for individualized diagnosis of PCa. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:1102-1109.

Qualitative and Quantitative Reporting of a Unique Biparametric MRI: Towards Biparametric MRI-Based Nomograms for Prediction of Prostate Biopsy Outcome in Men With a Clinical Suspicion of Prostate Cancer (IMPROD and MULTI-IMPROD Trials).

BACKGROUND: Multiparametric MRI of the prostate has been shown to improve the risk stratification of men with an elevated prostate-specific antigen (PSA). However, long acquisition time, high cost, and inter-center/reader variability of a routine prostate multiparametric MRI limit its wider adoption. PURPOSE: To develop and validate nomograms based on unique rapid biparametric MRI (bpMRI) qualitative and quantitative derived variables for prediction of clinically significant cancer (SPCa). STUDY TYPE: Retrospective analyses of single (IMPROD, NCT01864135) and multiinstitution trials (MULTI-IMPROD, NCT02241122). POPULATION: 161 and 338 prospectively enrolled men who completed the IMPROD and MULTI-IMPROD trials, respectively. FIELD STRENGTH/SEQUENCE: IMPROD bpMRI: 3T/1.5T, T2 -weighted imaging, three separate diffusion-weighted imaging (DWI) acquisitions: 1) b-values 0, 100, 200, 300, 500 s/mm2 ; 2) b values 0, 1500 s/mm2 ; 3) values 0, 2000 s/mm2 . ASSESSMENT: The primary endpoint of the combined trial analysis was the diagnostic accuracy of the combination of IMPROD bpMRI and clinical variables for detection of SPCa. STATISTICAL TESTS: Logistic regression models were developed using IMPROD trial data and validated using MULTI-IMPROD trial data. The model's performance was expressed as the area under the curve (AUC) values for the detection of SPCa, defined as ISUP Gleason Grade Group ≥2. RESULTS: A model incorporating clinical variables had an AUC (95% confidence interval) of 0.83 (0.77-0.89) and 0.80 (0.75-0.85) in the development and validation cohorts, respectively. The corresponding values for a model using IMPROD bpMRI findings were 0.93 (0.89-0.97), and 0.88 (0.84-0.92), respectively. Further addition of the quantitative DWI-based score did not improve AUC values (P < 0.05). DATA CONCLUSION: A prediction model using qualitative IMPROD bpMRI findings demonstrated high accuracy for predicting SPCa in men with an elevated PSA. Online risk calculator: http://petiv.utu.fi/multiimprod/ Level of Evidence: 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1556-1567.

Prostate Cancer Risk Stratification in Men With a Clinical Suspicion of Prostate Cancer Using a Unique Biparametric MRI and Expression of 11 Genes in Apparently Benign Tissue: Evaluation Using Machine-Learning Techniques.

BACKGROUND: Accurate risk stratification of men with a clinical suspicion of prostate cancer (cSPCa) remains challenging despite the increasing use of MRI. PURPOSE: To evaluate the diagnostic accuracy of a unique biparametric MRI protocol (IMPROD bpMRI) combined with clinical and molecular markers in men with cSPCa. STUDY TYPE: Prospective single-institutional clinical trial (NCT01864135). SUBJECTS: Eighty men with cSPCa. FIELD STRENGTH/SEQUENCE: 3T, surface array coils. Two T2 -weighted and three diffusion-weighted imaging (DWI) acquisitions: 1) b-values 0, 100, 200, 300, 500 s/mm2 ; 2) b-values 0,1500 s/mm2 ; 3) b-values 0, 2000 s/mm2 . ASSESSMENT: IMPROD bpMRI examinations were qualitatively (IMPROD bpMRI Likert score) and quantitatively (DWI-based Gleason grade score) prospectively reported. Men with IMPROD bpMRI Likert 3-5 had two targeted biopsies followed by 12-core systematic biopsies (SB); those with IMPROD bpMRI Likert 1-2 had only SB. Additionally, 2-core from normal-appearing prostate areas were obtained for the mRNA expression of ACSM1, AMACR, CACNA1D, DLX1, PCA3, PLA2G7, RHOU, SPINK1, SPON2, TMPRSS2-ERG, and TDRD1 measured by quantitative reverse-transcription polymerase chain reaction. STATISTICAL TESTS: Univariate and multivariate analysis using regularized least-squares, feature selection and tournament leave-pair-out cross-validation (TLPOCV), as well as 10 random splits of the data in training-testing sets, were used to evaluate the mRNA, clinical and IMPROD bpMRI parameters in detecting clinically significant prostate cancer (SPCa) defined as Gleason score ≥ 3 + 4. The evaluation metric was the area under the curve (AUC). RESULTS: IMPROD bpMRI Likert demonstrated the highest TLPOCV AUC of 0.92. The tested clinical variables had AUC 0.56-0.73, while the mRNA and additional IMPROD bpMRI parameters had AUC 0.50-0.67 and 0.65-0.89 respectively. The combination of clinical and mRNA biomarkers produced TLPOCV AUC of 0.87, the highest TLPOCV performance without including IMPROD bpMRI Likert. DATA CONCLUSION: The qualitative IMPROD bpMRI Likert score demonstrated the highest accuracy for SPCa detection compared with the tested clinical variables and mRNA biomarkers. LEVEL OF EVIDENCE: 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1540-1553.

Added value of diffusion-weighted images and dynamic contrast enhancement in multiparametric magnetic resonance imaging for the detection of clinically significant prostate cancer in the PICTURE trial.

OBJECTIVE: To determine the additional diagnostic value of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced imaging (DCE) in men requiring a repeat biopsy within the PICTURE study. PATIENTS AND METHODS: PICTURE was a paired-cohort confirmatory study in which 249 men who required further risk stratification after a previous non-magnetic resonance imaging (MRI)-guided transrectal ultrasonography-guided biopsy underwent a 3-Tesla (3T) multiparametic (mp)MRI consisting of T2-weighted imaging (T2W), DWI and DCE, followed by transperineal template prostate mapping biopsy. Each mpMRI was reported using a LIKERT score in a sequential blinded manner to generate scores for T2W, T2W+DWI and T2W+DWI+DCE. Area under the receiver-operating characteristic curve (AUROC) analysis was performed to compare the diagnostic accuracy of each combination. The threshold for a positive mpMRI was set at a LIKERT score ≥3. Clinically significant prostate cancer was analysed across a range of definitions including UCL/Ahmed definition 1 (primary definition), UCL/Ahmed definition 2, any Gleason ≥3 + 4 and any Gleason ≥4 + 3. RESULTS: Of 249 men, sequential MRI reporting was available for 246. There was a higher rate of equivocal lesions (44.6%) using T2W alone compared to the addition of DWI (23.9%) and DCE (19.8%). Using the primary definition of clinically significant disease, there was no significant difference in the overall accuracy between T2W, with an AUROC of 0.74 (95% confidence interval [CI] 0.68-0.80), T2W+DWI at 0.76 (95% CI 0.71-0.82), and T2W+DWI+DCE, with an AUROC of 0.77 (95% CI 0.71-0.82; P = 0.55). The AUROC values remained comparable using other definitions of clinically significant disease including UCL/Ahmed definition 2 (P = 0.79), Gleason ≥3 + 4 (P = 0.53) and Gleason ≥4 + 3 (P = 0.53). CONCLUSIONS: Using 3T MRI, a high level of diagnostic accuracy can be achieved using T2W as a single parameter in men with a prior biopsy; however, such a strategy can lead to a higher rate of equivocal lesions.

IMPROD biparametric MRI in men with a clinical suspicion of prostate cancer (IMPROD Trial): Sensitivity for prostate cancer detection in correlation with whole-mount prostatectomy sections and implications for focal therapy.

BACKGROUND: Prostate MRI is increasingly being used in men with a clinical suspicion of prostate cancer (PCa). However, development and validation of methods for focal therapy planning are still lagging. PURPOSE: To evaluate the diagnostic accuracy on lesion, region-of-interest (ROI), and voxel level of IMPROD biparametric prostate MRI (bpMRI) for PCa detection in men with a clinical suspicion of PCa who subsequently underwent radical prostatectomy. STUDY TYPE: Prospective single-institution clinical trial (NCT01864135). POPULATION: Sixty-four men who underwent radical prostatectomy after IMPROD bpMRI performed in prebiopsy settings. FIELD STRENGTH/SEQUENCE: IMPROD bpMRI consisted of T2 -weighted imaging (T2 w) and three separate diffusion-weighted imaging acquisitions with an average acquisition time of 15 minutes. ASSESSMENT: The diagnostic accuracy of prospectively reported manual cancer delineations and regions increased with 3D dilation were evaluated on the voxel level (volume of 1.17 mm3 , 1 mm3 , 125 mm3 ) as well as the 36 ROI level. Only PCa lesions with a diameter ≥ 5 mm or any Gleason Grade 4 were analyzed. All data and protocols are freely available at: http://petiv.utu.fi/improd STATISTICAL TESTS: Sensitivity, specificity, accuracy. RESULTS: In total, 99 PCa lesions were identified. Forty (40%, 40/99) had a Gleason score (GS) of >3 + 4. Twenty-eight PCa lesions (28%, 28/99) were missed by IMPROD bpMRI, three (7.5%, 3/40) with GS >3 + 4. 3D dilation of manual cancer delineations in all directions by ~10-12 mm (corresponding to the Hausdorff distance) was needed to achieve sensitivity approaching 100% on a voxel level. DATA CONCLUSION: IMPROD bpMRI had a high sensitivity on lesion level for PCa with GS >3 + 4. Increasing 3D lesion delineations by ~10-12 mm (corresponding to the Hausdorff distance) was needed to achieve high sensitivity on the voxel level. Such information may help in planning ablation therapies. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1641-1650.

Comparison of multiparametric and biparametric MRI of the prostate: are gadolinium-based contrast agents needed for routine examinations?

PURPOSE: To investigate, if and how omitting gadolinium-based contrast agents (GBCA) and dynamic contrast-enhanced imaging (DCE) influences diagnostic accuracy and tumor detection rates of prostate MRI. METHODS: In this retrospective study, 236 patients were included. The results of biparametric (bpMRI) and multiparametric magnetic resonance imaging (mpMRI) were compared using the PI-RADS version 2 scoring system. The distribution of lesions to PIRADS score levels, tumor detection rates, diagnostic accuracy and RoC analysis were calculated and compared to the results of histopathological analysis or 5-year follow-up for benign findings. RESULTS: Omitting DCE changed PI-RADS scores in 9.75% of patients, increasing the number of PI-RADS 3 scores by 8.89% when compared to mpMRI. No change of more than one score level was observed. BpMRI did not show significant differences in diagnostic accuracy or tumor detection rates. (AuC of 0.914 vs 0.917 in ROC analysis). Of 135 prostate carcinomas (PCa), 94.07% were scored identically, and 5.93% were downgraded only from PI-RADS 4 to PI-RADS 3 by bpMRI. All of them were low-grade PCa with Gleason Score 6 or 7a. No changes were observed for PCa ≥ 7b. CONCLUSION: Omitting DCE did not lead to significant differences in diagnostic accuracy or tumor detection rates when using the PI-RADS 2 scoring system. According to these data, it seems reasonable to use a biparametric approach for initial routine prostate MRI. This could decrease examination time and reduce costs without significantly lowering the diagnostic accuracy.

Abbreviated Biparametric Versus Standard Multiparametric MRI for Diagnosis of Prostate Cancer: A Systematic Review and Meta-Analysis.

OBJECTIVE: The objective of our study was to evaluate the diagnostic accuracy of abbreviated biparametric MRI (bpMRI) versus standard multiparametric MRI (mpMRI) for prostate cancer (PCa) using guided biopsy or prostatectomy histopathology results as the reference standard. MATERIALS AND METHODS: A comprehensive literature search of PubMed, Web of Science, and Cochrane Library databases was performed by two researchers independently and the relevant references were assessed. Original research studies comparing bpMRI with mpMRI in diagnosing PCa were included. The methodologic quality of eligible studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Data necessary to complete 2 × 2 contingency tables were obtained to calculate the diagnostic performance of bpMRI and mpMRI using Stata (version 14). RESULTS: Ten studies were included, and a total of 1705 patients and 3419 lesions were analyzed. Sensitivity, specificity, positive likelihood ratio (LR), negative LR, and diagnostic odds ratio (DOR) of mpMRI in diagnosing PCa were 0.79 (95% CI, 0.69-0.87), 0.89 (95% CI, 0.70-0.96), 6.9 (95% CI, 2.5-18.8), 0.24 (95% CI, 0.16-0.35), and 29 (95% CI, 10-83). Sensitivity, specificity, positive LR, negative LR, and DOR of bpMRI in diagnosing PCa were 0.79 (95% CI, 0.69-0.87), 0.88 (95% CI, 0.73-0.95), 6.4 (95% CI, 2.9-14.5), 0.24 (95% CI, 0.16-0.35), and 27 (95% CI, 11-67). Meta-analysis showed no statistically significant difference between bpMRI and mpMRI for the diagnosis of PCa, and the areas under the summary ROC (SROC) curves were 0.89 and 0.88, respectively (p = 0.9944). Results of the sensitivity analysis were consistent, and the area under the SROC curve for bpMRI and mpMRI was 0.89 for both (p = 0.9349). CONCLUSION: The available evidence indicates that bpMRI and mpMRI have similar diagnostic efficacy in diagnosing PCa.

Poor reproducibility of PIRADS score in two multiparametric MRIs before biopsy in men with elevated PSA.

PURPOSE: Since January 2015, all men referred to urologists in Norway due to elevated PSA or other suspicion of prostate cancer underwent multiparametric MRI (mpMRI) before prostate biopsy. At our hospital, patients and the initial MRI were assessed by an urologist and if deemed necessary, patients were referred to another institution for MR/US fusion biopsies. Before MR/US biopsy, patients underwent a second mpMRI. Since we noticed disagreement of these two mpMRIs before biopsy, we retrospectively assessed the level of agreement between the two mpMRIs from the two institutions. METHODS: During the first 6 months of 2015, 292 patients were referred to our outpatient clinic. We referred 126 patients of these to the other institution for MR/US fusion biopsy. The 2 mpMRIs were performed within 4 weeks. We analyzed MR reports and schematics for number of lesions and highest PIRADS score per side of the prostate and histological result of the biopsies. Bland-Altman's plot was used to compare the level of agreement between the two mpMRIs of the same patient before biopsy. RESULTS: There was a poor level of agreement between the two mpMRIs and a statistically significant difference in PIRADS scores. Regression analysis showed that there was no proportional or systematic bias. CONCLUSION: In unselected patients with elevated PSA, there seems to be a significant variation of mpMRI results across institutions. The PIRADS scoring system needs to be validated with regards to MR equipment, mpMRI protocols and inter-reader variability of radiologists.