Pre-biopsy MRI Research Articles

Understanding the impact of historical redlining on prostate cancer care quality and treatment patterns and the association with modern metrics of disparity.

118 Background: Sociodemographic and racial disparities persist in prostate cancer care, including associations between place-based indices and prostate cancer care quality and treatment modality. This study examines the impact of historical redlining conducted by the Home Owner’s Loan Corporation (HOLC) in 1933 on modern prostate cancer care quality. Methods: We performed a retrospective, observational cohort study utilizing Medicare claims data (2015-2019) of patients aged 66 or older with localized prostate cancer. ArcGIS was used to overlay HOLC grading to modern five-digit zip-codes and generate a weighted average HOLC grade for each zip. Data was then merged with modern metrics of social determinants of health including social vulnerability index (SVI) and dual eligibility. In order to assess historical and modern metrics of structural racism, patients across HOLC grade were compared to determine treatment modality and access to prostate cancer care quality. HOLC grade was then compared to SVI and dual eligibility in determining disparities. Results: We identified 14,630 patients with newly diagnosed prostate cancer who reside within an area that received a HOLC grade, of whom 10187 (70%) were white, 2910 (20%) were Black, and 1473 (10%) were another race or ethnicity. Patients in HOLC-graded areas were more likely to be socioeconomically disadvantaged (dual eligibility status, 11% vs. 4.1%, p<0.001; 4 th Quartile SVI; 36% vs. 24%, p<0.001) and urban residents (99.9% vs 76%, p<0.001). Multivariable logistic regression analysis of patients who resided in HOLC-graded areas indicated that those in areas with worse HOLC-grade (per 1-grade difference) had lower odds of undergoing surgery (OR 0.89, CI 0.83-0.96, p=0.003), being treated by a high-volume practitioner (OR 0.86 CI 0.81-0.92, p<0.001), or undergoing pre-biopsy MRI (OR 0.94, CI 0.89-1.0, p=0.050), but similar odds of being seen by both a radiation oncologist and urologist (OR 1.03, CI 0.96-1.11, p=0.5). No significant interactions between HOLC grade and social vulnerability were found. Conclusions: This study reveals the enduring impact of historical redlining on prostate cancer care disparities, emphasizing the need for targeted interventions and housing policy reforms to promote equitable access to care. Racially explicit policies continue to shape healthcare disparities, independent of contemporary socioeconomic factors.

Trends in pre-biopsy MRI usage for prostate cancer detection, 2007-2022.

Clinical guidelines favor MRI before prostate biopsy due to proven benefits. However, adoption patterns across the US are unclear. This study used the Merative™ Marketscan® Commercial & Medicare Databases to analyze 872,829 prostate biopsies in 726,663 men from 2007-2022. Pre-biopsy pelvic MRI within 90 days was the primary outcome. Descriptive statistics and generalized estimating equations assessed changes over time, urban-rural differences, and state-level variation. Pre-biopsy MRI utilization increased significantly from 0.5% in 2007 to 35.5% in 2022, with faster adoption in urban areas (36.1% in 2022) versus rural areas (28.3% in 2022). Geographic disparities were notable, with higher utilization in California, New York, and Minnesota, and lower rates in the Southeast and Mountain West. The study reveals a paradigm shift in prostate cancer diagnostics towards MRI-guided approaches, influenced by evolving guidelines and clinical evidence. Disparities in access, particularly in rural areas and specific regions, highlight the need for targeted interventions to ensure equitable access to advanced diagnostic techniques.

Utility of dynamic contrast enhancement for clinically significant prostate cancer detection.

This study aimed to evaluate the association of dynamic contrast enhancement (DCE) with clinically significant prostate cancer (csPCa, Gleason Grade Group ≥2) and compare biparametric magnetic resonance imaging (bpMRI) and multiparametric MRI (mpMRI) nomograms. We identified a retrospective cohort of biopsy naïve patients who underwent pre-biopsy MRI separated by individual MRI series from 2018 to 2022. csPCa detection rates were calculated for patients with peripheral zone (PZ) lesions scored 3-5 on diffusion weighted imaging (DWI) with available DCE (annotated as - or +). bpMRI Prostate Imaging Reporting and Data System (PIRADS) (3 = 3-, 3+; 4 = 4-, 4+; 5 = 5-, 5+) and mpMRI PIRADS (3 = 3-; 4 = 3+, 4-, 4+; 5 = 5-, 5+) approaches were compared in multivariable logistic regression models. Nomograms for detection of csPCa and ≥GG3 PCa incorporating all biopsy naïve patients who underwent prostate MRI were generated based on available serum biomarkers [PHI, % free prostate-specific antigen (PSA), or total PSA] and validated with an independent cohort. Patients (n = 1010) with highest PIRADS lesion in PZ were included in initial analysis with 127 (12.6%) classified as PIRADS 3+ (PIRADS 3 on bpMRI but PIRADS 4 on mpMRI). On multivariable analysis, PIRADS 3+ lesions were associated with higher csPCa rates compared to PIRADS 3- (3+ vs. 3-: OR 1.86, p= 0.024), but lower csPCa rates compared to PIRADS DWI 4 lesions (4 vs. 3+: OR 2.39, p< 0.001). csPCa rates were 19% (3-), 31% (3+), 41.5% (4-), 65.9% (4+), 62.5% (5-), and 92.3% (5+). bpMRI nomograms were non-inferior to mpMRI nomograms in the development (n= 1410) and independent validation (n= 353) cohorts. Risk calculators available at: https://rossnm1.shinyapps.io/MynMRIskCalculator/. While DCE positivity by itself was associated with csPCa among patients with highest PIRADS lesions in the PZ, nomogram comparisons suggest that there is no significant difference in performance of bpMRI and mpMRI. bpMRI may be considered as an alternative to mpMRI for prostate cancer evaluation in many situations.

Clinically Significant Prostate Cancer Detection Following Transrectal and Transperineal Biopsy: Results of the Prostate Biopsy Efficacy and Complications Randomized Clinical Trial.

The comparative effectiveness of transrectal and transperineal prostate biopsy in detecting clinically significant prostate cancer is not well understood. We conducted a randomized clinical trial to determine whether transperineal biopsy improves the detection of clinically significant prostate cancer. Of the 840 men randomized, 93% were White, 44% had a previous biopsy, with a median age of 66 years and median PSA density of 0.14. Of these, 384 underwent transrectal and 398 underwent transperineal prostate biopsy. Prebiopsy prostate MRI was performed in 96% of men. Grade Group ≥ 2 prostate cancer was classified as clinically significant. Odds ratios were calculated using logistic regression to evaluate the effect of biopsy procedures on cancer detection rates. The detection rates of clinically significant prostate cancer were 47.1% and 43.2% (odds ratio 1.17; 95% CI, 0.88-1.55) for transrectal and transperineal biopsy, respectively. Age, PSA density, clinical stage and Prostate Imaging Reporting and Data System score were associated with the diagnosis of clinically significant cancer, whereas history of previous biopsy, anterior tumors, and biopsy procedure (transrectal or transperineal) were not. Clinically significant cancer detection rates in biopsy-naïve men undergoing MRI-targeted transrectal or transperineal biopsy were 59% and 62%, respectively. The overall cancer detection rates following transrectal and transperineal biopsy were 72.1% and 70.4%, respectively. There was no significant difference noted in the detection of clinically significant prostate cancer following transrectal or transperineal prostate biopsy. Urologists may utilize either biopsy procedure that best suits their patients' needs and practice setting.

Negative magnetic resonance imaging cannot be used to omit an initial prostate biopsy - An ambispective study

IntroductionUp to 40% of patients with suspected prostate cancer (PCa) have a negative prebiopsy magnetic resonance imaging (nMRI), and up to 15% of them may have clinically significant PCa (csPCa). The ability to predict the presence of csPCa despite nMRI may help avoid unnecessary biopsies. We aimed to determine the negative predictive value (NPV) of mpMRI, the influence of MRI reporting patterns in clinical practice, and the factors that might predict csPCa among men with an nMRI. MethodologyIn an IRB-approved, ambispective study, men who underwent prostate biopsy from 2016 to 2023 and had a prebiopsy MRI, were included to determine the presence of csPCa. The reporting patterns of institutional and noninstitutional MRI were evaluated. Age, digital rectal examination (DRE) findings, prostate specific antigen (PSA), PSA density (PSAD), and MRI reports were evaluated for their ability to predict csPCa in men with nMRI. Results1660 patients who underwent prostate biopsy were assessed for eligibility, and 685 patients were enrolled in the study. The median age, PSA and PSAD were 60 years, 11.63 ng/ml and 0.23 ng/ml/cm3, respectively. 62 (9%) men had an nMRI, among which csPCa, non-csPCa, and negative biopsy were found in 34%, 5%, and 61% of men, respectively. 61% had an institutional MRI, while 39% had a noninstitutional MRI. The sensitivity and NPV of any MRI for csPCa were 93% and 66%, respectively, which improved to 96% and 81% for institutional MRI. Univariate and multivariate analyses showed abnormal DRE and PSAD ≥0.25 ng/ml/cc as predictive factors for csPCa in men with an nMRI. Conclusion34% of men with negative MRIs were found to harbor csPCa on prostate biopsy. The NPV of institutional MRI was higher than for noninstitutional MRI. Men with an abnormal DRE or PSAD ≥0.25 ng/ml/cc had a higher incidence of csPCa despite an nMRI.

Direct MRI-guided In-Bore Targeted Biopsy of the Prostate: A Step-by-Step How To and Lessons Learned.

Multiparametric MRI-the most accurate imaging technique for detection of prostate cancer-has transformed the landscape of prostate cancer diagnosis by enabling targeted biopsies. In a targeted biopsy, tissue samples are obtained from suspicious regions identified at prebiopsy diagnostic MRI. The authors briefly compare the different strategies available for targeting an MRI-visible suspicious lesion, followed by a step-by-step description of the direct MRI-guided in-bore approach and an illustrated review of its application in challenging clinical scenarios. In this technique, direct visualization of the needle, needle guide, and needle trajectory during the procedure provides a precise and versatile strategy to accurately sample suspicious lesions, improving detection of clinically significant cancers. Published under a CC BY 4.0 license Test Your Knowledge questions for this article are available in the supplemental material.

The impact of pre-biopsy MRI and additional testing on prostate cancer screening outcomes: A rapid review.

This work aims to examine the latest evidence on the impact of pre-biopsy MRI, in addition to prostate-specific antigen (PSA) testing, on health outcomes and quality of life. We conducted a literature search including PubMed and Cochrane Central Register of Controlled Trials (CENTRAL) databases, with a limited scan of (i) guidelines and (ii) references from trial reports, from January 2005 to 25th January 2023. Two independent reviewers selected randomised controlled trials (RCT) and cohort studies which met our inclusion criteria. One hundred thirty-seven articles were identified, and seven trial articles were selected. Trial interventions were as follows: (i) PSA blood test, (ii) additional tests such as pre-biopsy multiparametric magnetic resonance imaging (mpMRI) and Biparametric MRI (bpMRI), and (iii) MRI targeted biopsy and standard biopsy. Compared with standard biopsy, MRI-based interventions led to increased detection of clinically significant cancers in three studies and decreased detection of clinically insignificant cancer (Gleason grade 3 + 3) in four studies. However, PROstate Magnetic resonance Imaging Study (PROMIS) and Stockholm3 with MRI (STHLM3-MRI) studies reported different trends depending on the scenario studied in PROMIS (MRI triage and MRI directed biopsy vs. MRI triage and standard biopsy) and thresholds used in STHLM3-MRI (≥0·11 and ≥0·15). MRI also helped 8%-49% of men avoid biopsy, in six out of seven studies, but not in STHLM3-MRI at ≥0.11. Interestingly, the proportion of men who experienced sepsis and UTI was low across studies. This review found that a combination of approaches, centred on the use of pre-biopsy MRI, may improve the detection of clinically significant cancers and reduce (i) the diagnosis of clinically insignificant cancers and (ii) unnecessary biopsies, compared with PSA testing and standard biopsy alone. However, the impact of such interventions on longer term outcomes such as prostate cancer-specific mortality has not yet been assessed.

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.

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. To evaluate the change of clinical practice of prebiopsy mpMRI over time, and assess its diagnostic accuracy. 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. Prebiopsy MRI at the time of PBx. 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. 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. 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. 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.

Validation of the Barcelona-MRI predictive model when PI-RADS v2.1 is used with trans-perineal prostate biopsies.

To validate the Barcelona magnetic resonance imaging predictive model (BCN-MRI PM) in men with pre-biopsy multiparametric MRI (mpMRI) reported with the Prostate Imaging Reporting and Data System (PI-RADS) v2.1, followed by transrectal and transperineal prostate biopsies. Prospective analysis of 3,264 men with PSA >3.0 ng/mL and/or abnormal digital rectal examination who were referred to ten participant centers in the csPCa early detection program of Catalonia (Spain), between 2021 and 2023. MpMRI was reported with the PI-RADS v2.1, and 2- to 4-core MRI-transrectal ultrasound (TRUS) fusion-targeted biopsy of suspected lesions and/or 12-core systematic biopsy were conducted. 2,295 (70.3%) individuals were referred to six centers for transrectal prostate biopsies, while 969 (39.7%) were referred to four centers for transperineal prostate biopsies. CsPCa was classified whenever the International Society of Urologic Pathology grade group was 2 or higher. CsPCa was detected in 41% of transrectal prostate biopsies and in 45.9% of transperineal prostate biopsies (p < 0.016). Both BCN-MRI PM calibration curves were within the ideal correlation between predicted and observed csPCa. Areas under the curve and 95% confidence intervals were 0.847 (0.830-0.857) and 0.830 (0.823-0.855), respectively (p = 0.346). Specificities corresponding to 95% sensitivity were 37.6 and 36.8%, respectively (p = 0.387). The Net benefit of the BCN-MRI PM was similar with both biopsy methods. The BCN-MRI PM has been successfully validated when mpMRI was reported with the PI-RADS v2.1 and prostate biopsies were conducted via the transrectal and transperineal route.

Multiparametric MRI and T2/FLAIR mismatch complements the World Health Organization 2021 classification for the diagnosis of IDH-mutant 1p/19q non-co-deleted/ATRX-mutant astrocytoma

To investigate whether T2-weighted imaging-fluid-attenuated inversion recovery (T2/FLAIR) mismatch, T2∗ dynamic susceptibility contrast (DSC) perfusion, and magnetic resonance spectroscopy (MRS) correlated with the histological diagnosis and grading of IDH (isocitrate dehydrogenase)-mutant, 1p/19q non-co-deleted/ATRX (alpha-thalassemia mental retardation X-linked)-mutant astrocytoma. Imaging of 101 IDH-mutant diffuse glioma cases of histological grades 2-3 (2019-2021) were analysed retrospectively by two neuroradiologists blinded to the molecular diagnosis. T2/FLAIR mismatch sign is used for radio-phenotyping, and pre-biopsy multiparametric MRI images were assessed for grading purposes. Cut-off values pre-determined for radiologically high-grade lesions were relative cerebral blood volume (rCBV) ≥2, choline/creatine ratio (Cho/Cr) ≥1.5 (30 ms echo time [TE]), Cho/Cr ≥1.8 (135 ms TE). Sixteen of the 101 cases showed T2/FLAIR mismatch, all of which were histogenetically confirmed IDH-mutant 1p/19q non-co-deleted/ATRX mutant astrocytomas; 50% were grade 3 (8/16) and 50% grade 2 (8/16). None showed contrast enhancement. Nine of the 16 had adequate multiparametric MRI for analysis. Any positive value by combining rCBV ≥2 with Cho/Cr ≥1.5 (30 ms TE) or Cho/Cr ≥1.8 (135 ms TE) predicted grade 3 histology with sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 100%. The T2/FLAIR mismatch sign detected diffuse astrocytomas with 100% specificity. When combined with high Cho/Cr and raised rCBV, this predicted histological grading with high accuracy. The future direction for imaging should explore a similar integrated layered approach of 2021 classification of central nervous system (CNS) tumours combining radio-phenotyping and grading from structural and multiparametric imaging.

First population-level results of pre-biopsy prostate MRI.

First population-level results of pre-biopsy prostate MRI.

MRI-Based Surrogate Imaging Markers of Aggressiveness in Prostate Cancer: Development of a Machine Learning Model Based on Radiomic Features.

This retrospective study included 86 adult Hispanic men (60 ± 8.2 years, median prostate-specific antigen density (PSA-D) 0.15 ng/mL2) with PCa who underwent prebiopsy 3T MRI followed by targeted MRI-ultrasound fusion and systematic biopsy. Two observers performed 2D segmentation of lesions in T2WI/ADC images. We classified csPCa (GS ≥ 7) vs. non-csPCa (GS = 6). Univariate statistical tests were performed for different parameters, including prostate volume (PV), PSA-D, PI-RADS, and radiomic features. Multivariate models were built using the automatic feature selection algorithm Recursive Feature Elimination (RFE) and different classifiers. A stratified split separated the train/test (80%) and validation (20%) sets. Radiomic features derived from T2WI/ADC are associated with GS in patients with PCa. The best model found was multivariate, including image (T2WI/ADC) and clinical (PV and PSA-D) information. The validation area under the curve (AUC) was 0.80 for differentiating csPCa from non-csPCa, exhibiting better performance than PI-RADS (AUC: 0.71) and PSA-D (AUC: 0.78). Our multivariate ML model outperforms PI-RADS v2.1 and established clinical indicators like PSA-D in classifying csPCa accurately. This underscores MRI-derived radiomics' (T2WI/ADC) potential as a robust biomarker for assessing PCa aggressiveness in Hispanic patients.

The value of a new diagnostic strategy for adipocytic soft tissue tumors in adults: A retrospective study

IntroductionThe distinction between lipoma and well-differentiated liposarcoma (WDLPS), or “atypical lipomatous tumor” (ALT), is crucial as it impacts patient management. A group of European experts led by Benjamin Moulin recently issued a consensus report to define the role of radiology in managing these lesions. It describes an algorithm defining the criteria prompting a diagnostic biopsy of deep lipomatous tumors of the limbs and chest wall. The primary aim of this study was to evaluate the algorithm's diagnostic performance. Materials and methodsBetween 2012 and 2019, all biopsies of deep fatty tumors of the limbs or chest wall with a pre-biopsy MRI assessment were recorded at our institution. The MRI scans were reviewed by two radiologists. Each lesion was classified according to biopsy status by applying the algorithm of the European panel. The algorithm's diagnostic performance was assessed by calculating the sensitivity, specificity, positive predictive value and negative predictive value. Inter-rater agreement was also assessed. ResultsOf the 156 tumors in our study, 148 (94.9%) required a biopsy, and the algorithm's sensitivity for detecting ALT/WDLPS was 100% with specificity of 6.3% and a PPV of 20.3%. Inter-rater agreement was almost perfect with a kappa value of 0.882. ConclusionThe European algorithm demonstrates perfect sensitivity, an important criterion for a screening examination such as MRI in this setting. The algorithm's low specificity, however, emphasizes the need for further studies to redefine the optimum size cut-off value, especially for lesions without atypical criteria or an anatomical location at risk of post-surgical recurrence.

MRI of Benign Prostatic Hyperplasia: Important Pre- and Posttherapeutic Considerations

New minimally invasive techniques that reduce morbidity while improving lower urinary tract symptoms (LUTS) due to benign prostatic hypertrophy (BPH) have become attractive alternatives for patients, in comparison to traditional techniques such as transurethral resection of the prostate (TURP) and simple prostatectomy. Pre- and postprocedural MRI is not routinely performed for LUTS due to BPH treatments. However, because of the combination of rapidly evolving treatments available for LUTS due to BPH and increasing demand for prebiopsy prostate MRI for detection of clinically significant prostate cancer (PCa), an understanding of procedural techniques and expected changes are important for accurate interpretation of prostate MRI performed after treatment of BPH. The authors discuss the imaging evaluation of LUTS due to BPH and emerging predictors of treatment success. The posttreatment appearance and underlying anatomic changes in the prostate after medical, surgical, and minimally invasive treatments including TURP, simple prostatectomy, laser enucleations and ablations, prostatic urethral lift, water vapor thermal therapy, and prostate artery embolization are detailed. Most procedures reduce prostate volume, notably in the periurethral prostatic tissue. Ablations create areas of necrosis and can distort the normal zonal anatomy between the transition zone and the peripheral zone, and prostate artery embolization creates infarcts in the transition zone. Mechanical prostatic urethral lift devices open the anterior channel at the bladder base but create susceptibility artifacts that can obscure and prevent detection of a lesion in the transition zone. Also discussed are the detection of clinically significant prostate cancer in the postprocedural prostate and imaging of BPH procedure complications such as urethral strictures, abscesses, and hematuria. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material. See the invited commentary by Purysko in this issue.

MP44-10 THE VALUE OF DYNAMIC CONTRAST ENHANCEMENT FOR RISK-STRATIFICATION AND PROSTATE CANCER DETECTION ON MULTIPARAMETRIC PROSTATE MRI

You have accessJournal of UrologyCME1 Apr 2023MP44-10 THE VALUE OF DYNAMIC CONTRAST ENHANCEMENT FOR RISK-STRATIFICATION AND PROSTATE CANCER DETECTION ON MULTIPARAMETRIC PROSTATE MRI Eric Li, Mohammad Siddiqui, Jonathan Aguiar, Parth Shah, Ashorne Mahenthiran, Jasmine Lin, Moataz Soliman, Sai Kumar, Mary Kate Keeter, Clayton Neill, Xinlei Mi, Quan Mai, Edward Schaeffer, Ashley Ross, and Hiten Patel Eric LiEric Li More articles by this author , Mohammad SiddiquiMohammad Siddiqui More articles by this author , Jonathan AguiarJonathan Aguiar More articles by this author , Parth ShahParth Shah More articles by this author , Ashorne MahenthiranAshorne Mahenthiran More articles by this author , Jasmine LinJasmine Lin More articles by this author , Moataz SolimanMoataz Soliman More articles by this author , Sai KumarSai Kumar More articles by this author , Mary Kate KeeterMary Kate Keeter More articles by this author , Clayton NeillClayton Neill More articles by this author , Xinlei MiXinlei Mi More articles by this author , Quan MaiQuan Mai More articles by this author , Edward SchaefferEdward Schaeffer More articles by this author , Ashley RossAshley Ross More articles by this author , and Hiten PatelHiten Patel More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003290.10AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Positive dynamic contrast enhancement (DCE) on multiparametric prostate MRI (mpMRI) upgrades peripheral zone (PZ) lesions on diffusion weighted imaging (DWI) from PIRADS 3 to 4, whereas these lesions would remain PIRADS 3 for biparametric MRI. It remains unclear if the rate of clinically significant prostate cancer (csPCa, Gleason Grade Group [GG] ≥2) differs for patients with DCE upgraded lesions (3+) compared to lesions rated 3 by DWI with negative DCE (3-), or 4 by DWI. METHODS: Biopsy naïve men presenting with elevated PSA and pre-biopsy MRI from 2018-2022 were identified. Clinicopathologic and MRI data including highest PIRADS lesion and scoring in individual MRI series were obtained. Patients with PIRADS 1 or 2 or transitional zone lesions as their highest PIRADS lesion were excluded. Patients with multiple lesions were included, and categorized by their highest PIRADS lesion. T-test, Chi-squared, and multivariable logistic regression were performed. RESULTS: 2468 men underwent mpMRI, and 1021 patients who underwent prostate biopsy had PZ lesions as their highest PIRADS lesion. csPCa detection rates for PIRADS 3-, 3+ and 4 were 19%, 31%, and 58%, respectively (p=0.01 for 3- vs 3+; p<0.001 for 3+ vs 4). On multivariable analysis, older age, Black race, PHI>36, PSAD>0.16, and highest PIRADS were significant predictors of csPCa. There was a significant difference in csPCa detection comparing 3+ to 3- (OR 1.94, 95% CI 1.13-3.34, p<0.001) and comparing 4 to 3+ (OR 2.38, 95% CI 1.52-3.78, p<0.001). AUCs for csPCa detection were similar for models classifying patients based on biparametric or multiparametric interpretation of PIRADS (82.0% vs. 81.9%). CONCLUSIONS: Patients with PZ lesions upgraded from PIRADS 3 to 4 by DCE have a csPCa detection rate that is higher than those rated as DWI 3 with negative DCE, but lower than those rated as DWI 4. Overall discrimination for biparametric and multiparametric MRI were similar, but DCE findings may aid in individualized cancer risk-stratification and diagnostic decisions. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e614 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Eric Li More articles by this author Mohammad Siddiqui More articles by this author Jonathan Aguiar More articles by this author Parth Shah More articles by this author Ashorne Mahenthiran More articles by this author Jasmine Lin More articles by this author Moataz Soliman More articles by this author Sai Kumar More articles by this author Mary Kate Keeter More articles by this author Clayton Neill More articles by this author Xinlei Mi More articles by this author Quan Mai More articles by this author Edward Schaeffer More articles by this author Ashley Ross More articles by this author Hiten Patel More articles by this author Expand All Advertisement PDF downloadLoading ...

Direct comparison between Grade Group assessed on systematic and MRI/ultrasound fusion targeted biopsies correlated to the radical prostatectomy specimens in patients with prostate cancer.

To compare the correlation of Gleason score (GS) and ISUP grade determined by prostate biopsies (PBx) and radical prostatectomy (RP) specimens according to the biopsy technique: ultrasound randomised (RBx) vs. MRI/ultrasound fusion targeted (TBx). Between March 2013 and June 2018, we retrospectively included patients who underwent RP for prostate cancer (PCa) histopathologically proven by RBx and/or TBx. All patients had a prebiopsy MRI by a single radiologist (using PI-RADS score), then transrectal RBx (12cores, blinded to MRI lesions) and TBx (2-4 cores/target) with elastic MRI/ultrasound fusion (UroStation™, Koelis, Grenoble, France). Histological findings were compared: PBx vs. RP. One hundred and four patients underwent RP after RBx and/or TBx. ISUP concordance rate was better with the association RBx+TBx 49% (51/104) vs. 43.3% with TBx (P=0.07) and 43.3% with RBx (P=0.13). With RBx, 50% of the patients were downgraded (52/104) against 42.3% (44/104) with TBx (P=0.088). The association RBx+TBx significantly decreased the rate of downgrading of the ISUP score compared to the ISUP score of RP 35.6% (37/104) vs. RBx (50%, P=0.0001) and vs. TBx (42.3%, P=0.016). In half of cases, the ISUP score was underestimated in RBx compared to RP specimens. Adding TBx to RBx significantly reduced downgrading. The combination of both biopsy techniques appeared to be the best protocol to get closer to ISUP score and GS of the RP specimens. C.

MP73-12 ARTIFICIAL INTELLIGENCE-BASED CANCER MAPPING TO AID IN PROSTATE CANCER THERAPY

You have accessJournal of UrologyCME1 Apr 2023MP73-12 ARTIFICIAL INTELLIGENCE-BASED CANCER MAPPING TO AID IN PROSTATE CANCER THERAPY Wayne Brisbane, Alan Priester, Sakina Mohammed Mota, Joshua Shubert, Jeremy Bong, James Sayre, Brittany Berry-Pusey, and Shyam Natarajan Wayne BrisbaneWayne Brisbane More articles by this author , Alan PriesterAlan Priester More articles by this author , Sakina Mohammed MotaSakina Mohammed Mota More articles by this author , Joshua ShubertJoshua Shubert More articles by this author , Jeremy BongJeremy Bong More articles by this author , James SayreJames Sayre More articles by this author , Brittany Berry-PuseyBrittany Berry-Pusey More articles by this author , and Shyam NatarajanShyam Natarajan More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003341.12AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Focal therapy (FT) for prostate cancer is gaining prominence as an alternative to whole-gland treatment. FT efficacy relies on predicting disease margins, but their underestimation and patient-specific optimization remain largely unaddressed problems. An artificial intelligence (AI)-based cancer mapping and decision support tool was built using pre-biopsy MRI, targeted biopsy data, and PSA to aid urologists in identifying cancer margins. A reader study was conducted to compare this AI-based software against the standard of care (SOC) in determining the extent of clinically significant prostate cancer (csPCa). METHODS: Seven urologists and three radiologists from five institutions with 2 – 23 years of expertise each evaluated 50 prostatectomy cases (total of 1000 reads) Cases were prospectively eligible for FT, with GG 2-3 csPCa, ≥1 region of interest (ROI), and disease that appeared localized to a single hemisphere or the anterior gland. Each case included T2-weighted MRI, ROI segmentation, and pathology reports with conventional locations. Readers were asked to produce contours on each image that prioritized the inclusion of all csPCa, excluding non-csPCa tissue as a secondary objective. First, readers manually defined margins using all given data (SOC). Then, after≥4 weeks had passed, readers produced AI-assisted margins using custom software (iQuest, Avenda Health, CA) [Figure B]. Margins from each method [Figure C] were evaluated against WM pathology data [Figure D] as ground truth. Statistical tests were performed using generalized estimating equations. RESULTS: AI margins had superior sensitivity (97.4% vs. 38.2%, p<0.0001) to SOC margins in classifying csPCa [Figure A]. AI-assisted margins also had superior balanced accuracy, i.e. (specificity+sensitivity)/2, to SOC margins (84.7% vs. 67.2%, p<0.0001). On average, AI-assisted margins completely encapsulated csPCa in 72.8% of cases, compared to only 1.6% of cases with SOC methods (p<0.0001). Furthermore, the average time spent fell from 3.5 minutes (SOC) to 2.0 minutes (AI-assisted, p<0.0001). CONCLUSIONS: AI-assisted cancer mapping helps address the systematic underestimation of csPCa by SOC methods. This study establishes that AI-assisted margins greatly improve csPCa encapsulation, which could improve oncological efficacy for focal treatments. Source of Funding: Avenda Health © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e1039 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Wayne Brisbane More articles by this author Alan Priester More articles by this author Sakina Mohammed Mota More articles by this author Joshua Shubert More articles by this author Jeremy Bong More articles by this author James Sayre More articles by this author Brittany Berry-Pusey More articles by this author Shyam Natarajan More articles by this author Expand All Advertisement PDF downloadLoading ...

Radiogenomics Reveals Correlation between Quantitative Texture Radiomic Features of Biparametric MRI and Hypoxia-Related Gene Expression in Men with Localised Prostate Cancer

To perform multiscale correlation analysis between quantitative texture feature phenotypes of pre-biopsy biparametric MRI (bpMRI) and targeted sequence-based RNA expression for hypoxia-related genes. Images from pre-biopsy 3T bpMRI scans in clinically localised PCa patients of various risk categories (n = 15) were used to extract textural features. The genomic landscape of hypoxia-related gene expression was obtained using post-radical prostatectomy tissue for targeted RNA expression profiling using the TempO-sequence method. The nonparametric Games Howell test was used to correlate the differential expression of the important hypoxia-related genes with 28 radiomic texture features. Then, cBioportal was accessed, and a gene-specific query was executed to extract the Oncoprint genomic output graph of the selected hypoxia-related genes from The Cancer Genome Atlas (TCGA). Based on each selected gene profile, correlation analysis using Pearson's coefficients and survival analysis using Kaplan-Meier estimators were performed. The quantitative bpMR imaging textural features, including the histogram and grey level co-occurrence matrix (GLCM), correlated with three hypoxia-related genes (ANGPTL4, VEGFA, and P4HA1) based on RNA sequencing using the TempO-Seq method. Further radiogenomic analysis, including data accessed from the cBioportal genomic database, confirmed that overexpressed hypoxia-related genes significantly correlated with a poor survival outcomes, with a median survival ratio of 81.11:133.00 months in those with and without alterations in genes, respectively. This study found that there is a correlation between the radiomic texture features extracted from bpMRI in localised prostate cancer and the hypoxia-related genes that are differentially expressed. The analysis of expression data based on cBioportal revealed that these hypoxia-related genes, which were the focus of the study, are linked to an unfavourable survival outcomes in prostate cancer patients.

Machine learning-based radiomics model to predict benign and malignant PI-RADS v2.1 category 3 lesions: a retrospective multi-center study

PurposeTo develop machine learning-based radiomics models derive from different MRI sequences for distinction between benign and malignant PI-RADS 3 lesions before intervention, and to cross-institution validate the generalization ability of the models.MethodsThe pre-biopsy MRI datas of 463 patients classified as PI-RADS 3 lesions were collected from 4 medical institutions retrospectively. 2347 radiomics features were extracted from the VOI of T2WI, DWI and ADC images. The ANOVA feature ranking method and support vector machine classifier were used to construct 3 single-sequence models and 1 integrated model combined with the features of three sequences. All the models were established in the training set and independently verified in the internal test and external validation set. The AUC was used to compared the predictive performance of PSAD with each model. Hosmer–lemeshow test was used to evaluate the degree of fitting between prediction probability and pathological results. Non-inferiority test was used to check generalization performance of the integrated model.ResultsThe difference of PSAD between PCa and benign lesions was statistically significant (P = 0.006), with the mean AUC of 0.701 for predicting clinically significant prostate cancer (internal test AUC = 0.709 vs. external validation AUC = 0.692, P = 0.013) and 0.630 for predicting all cancer (internal test AUC = 0.637 vs. external validation AUC = 0.623, P = 0.036). T2WI-model with the mean AUC of 0.717 for predicting csPCa (internal test AUC = 0.738 vs. external validation AUC = 0.695, P = 0.264) and 0.634 for predicting all cancer (internal test AUC = 0.678 vs. external validation AUC = 0.589, P = 0.547). DWI-model with the mean AUC of 0.658 for predicting csPCa (internal test AUC = 0.635 vs. external validation AUC = 0.681, P = 0.086) and 0.655 for predicting all cancer (internal test AUC = 0.712 vs. external validation AUC = 0.598, P = 0.437). ADC-model with the mean AUC of 0.746 for predicting csPCa (internal test AUC = 0.767 vs. external validation AUC = 0.724, P = 0.269) and 0.645 for predicting all cancer (internal test AUC = 0.650 vs. external validation AUC = 0.640, P = 0.848). Integrated model with the mean AUC of 0.803 for predicting csPCa (internal test AUC = 0.804 vs. external validation AUC = 0.801, P = 0.019) and 0.778 for predicting all cancer (internal test AUC = 0.801 vs. external validation AUC = 0.754, P = 0.047).ConclusionsThe radiomics model based on machine learning has the potential to be a non-invasive tool to distinguish cancerous, noncancerous and csPCa in PI-RADS 3 lesions, and has relatively high generalization ability between different date set.

Prognostic significance of PI-RADS 5 lesions in patients treated by radical prostatectomy.

To analyse the pathological features and survival of patients with a PI-RADS 5 lesion on pre-biopsy MRI. We extracted from a European multicentre prospectively gathered database the data of patients with a PI-RADS 5 lesion on pre-biopsy MRI, diagnosed using both systematic and targeted biopsies and subsequently treated by radical prostatectomy. The Kaplan-Meier model was used to assess the biochemical-free survival of the whole cohort and univariable and multivariable Cox models were set up to study factors associated with survival. Between 2013 and 2019, 539 consecutive patients with a PI-RADS 5 lesion on pre-biopsy MRI were treated by radical prostatectomy and included in the analysis. Follow-up data were available for 448 patients. Radical prostatectomy and lymph node dissection specimens showed non-organ confined disease in 297/539 (55%), (including 2 patients with a locally staged pT2 lesion and lymph node involvement (LNI)). With a median follow-up of 25months (12-39), the median biochemical recurrence-free survival was 54% at 2years (95% CI 45-61) and 28% at 5years (95% CI 18-39). Among the factors studied, MRI T stage [T3a vs T2 HR 3.57 (95%CI 1.78-7.16); T3b vs T2 HR 6.17 (95% CI 2.99-12.72)] and PSA density (HR 4.47 95% CI 1.55-12.89) were significantly associated with a higher risk of biochemical recurrence in multivariable analysis. Patients with a PI-RADS 5 lesion on pre-biopsy MRI have a high risk of early biochemical recurrence after radical prostatectomy. MRI T stage and PSA density can be used to improve patient selection and counselling.