A standardized method to measure the membranous urethral length (MUL) on MRI of the prostate with high inter- and intra-observer agreement.

OBJECTIVES: The membranous urethral length (MUL), defined as the length between the apex and penile base as measured on preoperative prostate magnetic resonance imaging (MRI), is an important predictor for urinary incontinence after radical prostatectomy. Literature on inter- and intra - observer agreement of MUL measurement is limited. We studied the inter- and intra-observer agreement between radiologists using a well-defined method to measure the MUL on the prostate MRI. METHODS: Prostate cancer patients underwent a preoperative MRI and robot-assisted radical prostatectomy (RARP) at one high-volume RARP center. MUL measurement was based on well-defined landmarks on sagittal T2-weighted (anatomical) images. Three radiologists independently performed MUL measurements retrospectively in 106 patients blinded to themselves, to each other, and to clinical outcomes. The inter- and intra-observer agreement of MUL measurement between the radiologists were calculated, expressed as intra-class correlation coefficient (ICC). RESULTS: The initial inter-observer agreement was ICC 0.63; 95% confidence interval (CI) 0.28-0.81. Radiologist 3 measured the MUL mean 3.9 mm (SD 3.3) longer than the other readers, interpreting the caudal point of the MUL (penile base) differently. After discussion on the correct anatomical definition, radiologist 3 re-assessed all scans, which resulted in a high inter-observer agreement (ICC 0.84; 95% CI 0.66-0.91). After a subsequent reading by radiologists 1 and 2, the intra-observer agreements were ICC 0.93; 95% CI 0.89-0.96, and ICC 0.98; 95% CI 0.97-0.98, respectively. Limitation is the monocenter design. CONCLUSIONS: The MUL can be measured reliably with high agreement among radiologists. KEY POINTS: • After discussion on the correct anatomical definition, the inter- and intra - observer agreements of membranous urethral length (MUL) measurement on magnetic resonance imaging (MRI) were high. • A reproducible method to measure the MUL can improve the clinical usefulness of prediction models for urinary continence after RARP which may benefit patient counselling.

The value of periprostatic fascia thickness and fascia preservation as prognostic factors of erectile function after nerve-sparing robot-assisted radical prostatectomy.

PURPOSE: To determine the correlation of preoperative fascia thickness (FT) and intraoperative fascia preservation (FP) with erectile function (EF) after nerve-sparing robot-assisted radical prostatectomy (RARP). METHODS: Our analysis included 106 patients, with localized prostate cancer and no erectile dysfunction (ED) before RARP, assessed with preoperative 3 Tesla (3 T) multiparametric magnetic resonance imaging (MRI). FP score was defined as the extent of FP from the base to the apex of the prostate, quantitatively assessed by the surgeon. Median fascia thickness (MFT) per patient was defined as the sum of the median FT of 12 MRI regions. Preserved MFT (pMFT) was the sum of the saved MFT. The percentage of pFMT (ppMFT) was also calculated. Fascia surface (FS) was measured on MRI and it was combined with FP score resulting in preserved FS (pFS) and percentage of pFS (ppFS). RESULTS: FP score, pMFT, ppMFT, pFS and ppFS were significantly lower (p < 0.0001) in patients with ED. In the multivariate regression analysis, lower FP score [odds ratio (OR) 0.721, p = 0.03] and lower ppMFT (OR 0.001, p = 0.027) were independent predictors of ED. ROC analysis showed the highest area under the curve for ppMFT (0.787) and FP score (0.767) followed by pMFT (0.755) and ppFS (0.743). CONCLUSIONS: MRI-determined periprostatic FT combined with intraoperative FP score are correlated to postprostatectomy EF. Based on the hypothesis that a thicker fascia forms a protective layer for the nerves, we recommend assessing FT preoperatively to counsel men for the odds of preserving EF after RARP.

Contouring of prostate tumors on multiparametric MRI: Evaluation of clinical delineations in a multicenter radiotherapy trial.

PURPOSE: To date no guidelines are available for contouring prostate cancer inside the gland, as visible on multiparametric (mp-) MRI. We assessed inter-institutional differences in interpretation of mp-MRI in the multicenter phase III FLAME trial. METHODS: We analyzed clinical delineations on mp-MRI and clinical characteristics from 260 patients across three institutes. We performed a logistic regression analysis to examine each institute's weighting of T2w, ADC and Ktrans intensity maps in the delineation of the cancer. As reviewing of all delineations by an expert panel is not feasible, we made a selection based on discrepancies between a published tumor probability (TP) model and each institute's clinical delineations using Areas Under the ROC Curve (AUC) analysis. RESULTS: Regression coefficients for the three institutes were -0.07, -0.27 and -0.11 for T2w, -1.96, -0.53 and -0.65 for ADC and 0.15, 0.20 and 0.62 for Ktrans, with significant differences between institutes for ADC and Ktrans. AUC analysis showed median AUC values of 0.92, 0.80 and 0.79. Five patients with lowest AUC values were reviewed by a uroradiologist. CONCLUSION: Regression coefficients revealed considerably different interpretations of mp-MRI in tumor contouring between institutes and demonstrated the need for contouring guidelines. Based on AUC values outlying delineations could efficiently be identified for review.

Repeatability of dose painting by numbers treatment planning in prostate cancer radiotherapy based on multiparametric magnetic resonance imaging.

Dose painting by numbers (DPBN) refers to a voxel-wise prescription of radiation dose modelled from functional image characteristics, in contrast to dose painting by contours which requires delineations to define the target for dose escalation. The direct relation between functional imaging characteristics and DPBN implies that random variations in images may propagate into the dose distribution. The stability of MR-only prostate cancer treatment planning based on DPBN with respect to these variations is as yet unknown. We conducted a test-retest study to investigate the stability of DPBN for prostate cancer in a semi-automated MR-only treatment planning workflow. Twelve patients received a multiparametric MRI on two separate days prior to prostatectomy. The tumor probability (TP) within the prostate was derived from image features with a logistic regression model. Dose mapping functions were applied to acquire a DPBN prescription map that served to generate an intensity modulated radiation therapy (IMRT) treatment plan. Dose calculations were done on a pseudo-CT derived from the MRI. The TP and DPBN map and the IMRT dose distribution were compared between both MRI sessions, using the intraclass correlation coefficient (ICC) to quantify repeatability of the planning pipeline. The quality of each treatment plan was measured with a quality factor (QF). Median ICC values for the TP and DPBN map and the IMRT dose distribution were 0.82, 0.82 and 0.88, respectively, for linear dose mapping and 0.82, 0.84 and 0.94 for square root dose mapping. A median QF of 3.4% was found among all treatment plans. We demonstrated the stability of DPBN radiotherapy treatment planning in prostate cancer, with excellent overall repeatability and acceptable treatment plan quality. Using validated tumor probability modelling and simple dose mapping techniques it was shown that despite day-to-day variations in imaging data still consistent treatment plans were obtained.

Magnetic resonance imaging for prostate cancer radiotherapy.

For radiotherapy of prostate cancer, MRI is used increasingly for delineation of the prostate gland. For focal treatment of low-risk prostate cancer or focal dose escalation for intermediate and high-risk cancer, delineation of the tumor is also required. While multi-parametric MRI is well established for detection of tumors and for staging of the disease, delineation of the tumor inside the prostate is not common practice. Guidelines, such as the PI-RADS classification, exist for tumor detection and staging, but no such guidelines are available for tumor delineation. Indeed, interobserver studies show substantial variation in tumor contours. Computer-aided tumor detection and delineation may help improve the robustness of the interpretation of multi-parametric MRI data. Comparing the performance of an earlier developed model for tumor segmentation with expert delineations, we found a significant correlation between tumor probability in a voxel and the number of experts identifying this voxel as tumor. This suggests that the model agrees with 'the wisdom of the crowd', and thus could serve as a reference for individual physicians in their decision making. With multi-parametric MRI it becomes feasible to revisit the GTV-CTV concept in radiotherapy of prostate cancer. While detection of index lesions is quite reliable, contouring variability and the low sensitivity to small lesions suggest that the remainder of the prostate should be treated as CTV. Clinical trials that investigate the options for dose differentiation, for example with dose escalation to the visible tumor or dose reduction to the CTV, are therefore warranted.