Can Extraprostatic Extension Be Predicted by Tumor-Capsule Contact Length in Prostate Cancer? Relationship With International Society of Urological Pathology Grade Groups.

OBJECTIVE. The objective of our study was to evaluate the relationship between the tumor-capsule contact length, defined as tumor contact length (TCL), and extraprostatic extension (EPE) using the MRI-based TCL measurements and the real TCL measurements from pathology and to determine whether the International Society of Urological Pathology (ISUP) grade group of the tumors influenced this relationship. MATERIALS AND METHODS. In this retrospective study, we reviewed prostate multiparametric MRI (mpMRI) studies performed between 2012 and 2018 of 1576 patients and found that 134 patients also underwent radical prostatectomy (RP) after mpMRI. Finally, 86 patients with index lesions in contact with the prostate capsule in RP specimens were enrolled in the study. ROC analysis was used to evaluate the cutoff values of TCLs measured at pathology and TCLs measured on MRI in terms of EPE according to ISUP grade groups. RESULTS. There was no statistically significant cutoff value for pathology-based TCL measurements in individual ISUP grade groups and subgroups. Although not statistically significant, pathology-based TCL cutoff values decreased (from 21.0 to 11.0 mm) as ISUP grade group increased in terms of EPE positivity. When the relationship between MRI-based TCL measurements and EPE was considered, statistically significant cutoff values (range, 14.5-16.6 mm) could be determined in many groups and subgroups with low ISUP grades (sensitivity, 66.7-100%; specificity, 52.8-93.0%; p = 0.006-0.042). However, no statistically significant cutoff value was found for high ISUP grades. CONCLUSION. ISUP grade groups may have an effect on the TCL-EPE relationship. When the MRI-based TCL and EPE relationship is evaluated independent of ISUP grade group, a cutoff value around 15-16 mm may be usable to predict EPE.

Densidad de APE en pacientes PI-RADS 3: un parámetro clínico útil para su manejo / PSA density as a new approach for PIRADS 3 patient's management

Resumen: Objetivo: Analizar las biopsias realizadas en paciente categorizados PIRADS 3 en nuestra institución desde el segundo semestre del año 2016 al primer semestre del año 2018 y describir la correlación de la densidad de PSA con la incidencia de cáncer de próstata. Evaluar el rol de la densidad de PSA en la indicación de estudio histológico en pacientes PIRADS 3. Método: Trabajo autorizado por el comité de ética de nuestra institución. Se realizó búsqueda en el PACs, de todos los informes de RM multiparamétricas de próstata que incluyeran la categoría ¨PIRADS 3¨ en el periodo señalado. De ellos se calculó la densidad de PSA, con el último valor de PSA registrado en la ficha clínica previo a RM y volumen prostático en RM. Se procedió a buscar los pacientes con estudio histológico. Se correlacionó los resultados de biopsias con el valor de densidad de PSA. Realizamos análisis uni y multivariados, análisis estadísticos con sensibilidad, especificidad y uso de curva ROC. Resultados: De las 2416 RMmp de próstata realizadas en nuestra institución en las fechas ya descritas, se encontraron 424 informes catalogados con score PIRADS 3, y 267 de esos pacientes tenían estudio y seguimiento institucional, de los cuales 134 contaban con biopsia. La muestra tenía un promedio de edad de 60 años, y una mediana de densidad de PSA de 0,10 (RIC 0,07-0,14). Se encontraron 36 biopsias con cáncer clínicamente significativo (Gleason > 6), lo que corresponde a 26,8% de la muestra, valor similar al encontrado en la literuatua. En estos pacientes se obtuvo un punto de corte óptimo de densidad de PSA de 0,11, con una sensibilidad y especificidad de 67% y un AUC de 0,68. Una densidad de PSA de 0,11 presenta un OR de 4,1, con una probabilidad de 4 veces más de encontrar un cáncer de próstata por sobre este valor (IC 95% 1,3-9,8), lo cuál es estadísticamente significativo con un p igual a 0,01. Conclusión: La DAPE sobre 0,11 ng/ml/cc puede considerarse como una herramienta adicional para indicar biopsia en pacientes con RMmp PI-RADS 3, aumentando la precisión para la detección de cáncer de próstata clínicamente significativos ayudando a disminuir estudios histológicos innecesarios.

Abstract: Objective: To analyze the biopsies performed in patients categorized PIRADS 3 in our institution from the second half of 2016 to the first half of 2018 and describe the correlation of PSA density with the incidence of prostate cancer. To evaluate the role of PSA density in the indication of histological study in PIRADS 3 patients. Method: Work authorized by the ethics committee of our institution. The PACs were searched for all multiparameter prostate MRI reports that included the category "PIRADS 3" in the period indicated. The PSA density was calculated, with the last PSA value recorded in the clinical record before MRI and prostate volume in MRI. We proceeded to look for patients with the histological study. The biopsy results were correlated with the PSA density value. We perform uni and multivariate analyzes, statistical analyzes with sensitivity, specificity and use of the ROC curve. Results: Of the 2416 RMmp of the prostate performed in our institution on the dates already described, 424 reports catalogued with PIRADS 3 score were found, and 267 of those patients had study and institutional follow-up, of which 134 had a biopsy. The sample had an average age of 60 years and a median PSA density of 0.10 (RIC 0.075-0.146). We found 36 biopsies with clinically significant cancer (Gleason> 6), which corresponds to 26.8% of the sample, a value similar to that found in the literature. In these patients, an optimal cut-off point of PSA density of 0.11 was obtained, with a sensitivity and specificity of 67% and an AUC of 0.68. A PSA density of 0.11 has an OR of 4.1, with a 4-fold probability of finding prostate cancer above this value (95% CI 1.3-9.8), which It is statistically significant with a p equal to 0.01. Conclusion: DAPE over 0.11 ng/ml/cc can be considered as an additional tool to indicate biopsy in patients with RMmp PI-RADS 3, increasing the accuracy for the detection of clinically significant prostate cancer helping to reduce unnecessary histological studies.

Prebiopsy Multiparametric MRI With Cancer-Negative Findings in Men With Suspected Prostate Cancer: Evaluation Using Prostate Imaging Reporting and Data System Version 2.

OBJECTIVE: The purpose of this study is to investigate the rates and characteristics of missed cancers at prebiopsy multiparametric MRI with cancer-negative findings according to the Prostate Imaging Reporting and Data System (PI-RADS) version 2 in men with suspected prostate cancer (PCa). MATERIALS AND METHODS: A total of 584 consecutive men (biopsy naive, n = 392; repeated biopsy, n = 192) with suspected PCa who underwent prebiopsy 3-T multipara-metric MRI, followed by subsequent biopsies, were enrolled. Cancer-positive findings were confirmed at systemic biopsies and cognitive MRI-targeted biopsies, whereas cancer-negative findings were confirmed at systemic biopsies performed during subsequent follow-up. Missing and detection rates of all PCa and clinically significant cancer according to five biopsy-based definitions were determined. The likelihood of PCa at multiparametric MRI was evaluated according to PI-RADS version 2, and the results were compared. RESULTS: Pathologically confirmed cancers were found in 25% of patients. Cancer-positive MRI findings were seen in 99 men (17%) and, of these, 85.9% had PCa. Of 485 men with cancer-negative MRI findings, a total of 61 (12.6%) had PCa, including 46 men in the biopsy-naive group and 15 men in the repeated-biopsy group. For clinically significant cancers, the rate of missed cancers at MRI was 0.1-6.0%, and the detection rate was 21.2-83.5%. For detecting PCa, multiparametric MRI had 96.8% specificity, 87.2% accuracy, and 87.4% negative predictive value. CONCLUSION: Prebiopsy 3-T multiparametric MRI with cancer-negative findings missed approximately 12.6% of cases of PCa, including 0.1-6.0% of clinically significant cancers in a cohort of biopsy-naive men and those who had undergone repeated biopsy.

Risk of Clinically Significant Prostate Cancer Associated With Prostate Imaging Reporting and Data System Category 3 (Equivocal) Lesions Identified on Multiparametric Prostate MRI.

OBJECTIVE: The objective of this study is to determine the frequency of clinically significant cancer (CSC) in Prostate Imaging Reporting and Data System (PI-RADS) category 3 (equivocal) lesions prospectively identified on multiparametric prostate MRI and to identify risk factors (RFs) for CSC that may aid in decision making. MATERIALS AND METHODS: Between January 2015 and July 2016, a total of 977 consecutively seen men underwent multiparametric prostate MRI, and 342 underwent MRI-ultrasound (US) fusion targeted biopsy. A total of 474 lesions were retrospectively reviewed, and 111 were scored as PI-RADS category 3 and were visualized using a 3-T MRI scanner. Multiparametric prostate MR images were prospectively interpreted by body subspecialty radiologists trained to use PI-RADS version 2. CSC was defined as a Gleason score of at least 7 on targeted biopsy. A multivariate logistic regression model was constructed to identify the RFs associated with CSC. RESULTS: Of the 111 PI-RADS category 3 lesions, 81 (73.0%) were benign, 11 (9.9%) were clinically insignificant (Gleason score, 6), and 19 (17.1%) were clinically significant. On multivariate analysis, three RFs were identified as significant predictors of CSC: older patient age (odds ratio [OR], 1.13; p = 0.002), smaller prostate volume (OR, 0.94; p = 0.008), and abnormal digital rectal examination (DRE) findings (OR, 3.92; p = 0.03). For PI-RADS category 3 lesions associated with zero, one, two, or three RFs, the risk of CSC was 4%, 16%, 62%, and 100%, respectively. PI-RADS category 3 lesions for which two or more RFs were noted (e.g., age ≥ 70 years, gland size ≤ 36 mL, or abnormal DRE findings) had a CSC detection rate of 67% with a sensitivity of 53%, a specificity of 95%, a positive predictive value of 67%, and a negative predictive value of 91%. CONCLUSION: Incorporating clinical parameters into risk stratification algorithms may improve the ability to detect clinically significant disease among PI-RADS category 3 lesions and may aid in the decision to perform biopsy.

Impact of an Information Technology-Enabled Initiative on the Quality of Prostate Multiparametric MRI Reports.

RATIONALE AND OBJECTIVES: Assess the impact of implementing a structured report template and a computer-aided diagnosis (CAD) tool on the quality of prostate multiparametric magnetic resonance imaging (mp-MRI) reports. MATERIALS AND METHODS: Institutional Review Board approval was obtained for this Health Insurance Portability and Accountability Act-compliant study performed at an academic medical center. The study cohort included all prostate mp-MRI reports (n = 385) finalized 6 months before and after implementation of a structured report template and a CAD tool (collectively the information technology [IT] tools) integrated into the picture archiving and communication system workstation. Primary outcome measure was quality of prostate mp-MRI reports. An expert panel of our institution's subspecialty-trained abdominal radiologists defined prostate mp-MRI report quality as optimal, satisfactory, or unsatisfactory based on documentation of nine variables. Reports were reviewed to extract the predefined quality variables and determine whether the IT tools were used to create each report. Chi-square and Student's t tests were used to compare report quality before and after implementation of IT tools. RESULTS: The overall proportion of optimal or satisfactory reports increased from 29.8% (47/158) to 53.3% (121/227) (P < .001) after implementing the IT tools. Although the proportion of optimal or satisfactory reports increased among reports generated using at least one of the IT tools (47/158 = [29.8%] vs. 105/161 = [65.2%]; P < .001), there was no change in quality among reports generated without use of the IT tools (47/158 = [29.8%] vs. 16/66 = [24.2%]; P = .404). CONCLUSIONS: The use of a structured template and CAD tool improved the quality of prostate mp-MRI reports compared to free-text report format and subjective measurement of contrast enhancement kinetic curve.

Characterization of prostate cancer using T2 mapping at 3T: a multi-scanner study.

RATIONALE AND OBJECTIVES: To assess the prostate T2 value as a predictor of malignancy on two different 3T scanners. PATIENTS AND METHODS: Eighty-three pre-prostatectomy multiparametric MRIs were retrospectively evaluated [67 obtained on a General Electric MRI (scanner 1) and 16 on a Philips MRI (scanner 2)]. After correlation with prostatectomy specimens, readers measured the T2 value of regions-of-interest categorized as "cancers", "false positive lesions", or "normal tissue". RESULTS: On scanner 1, in PZ, cancers had significantly lower T2 values than false positive lesions (P=0.02) and normal tissue (P=2×10(-9)). Gleason≥6 cancers had similar T2 values than false positive lesions and significantly higher T2 values than Gleason≥7 cancers (P=0.009). T2 values corresponding to a 25% and 75% risk of Gleason≥7 malignancy were respectively 132 ms (95% CI: 129-135 ms) and 77 ms (95% CI: 74-81 ms). In TZ, cancers had significantly lower T2 values than normal tissue (P=0.008), but not than false positive findings. Mean T2 values measured on scanner 2 were not significantly different than those measured on scanner 1 for all tissue classes. CONCLUSION: All tested tissue classes had similar mean T2 values on both scanners. In PZ, the T2 value was a significant predictor of Gleason≥7 cancers.