Objectives: To investigate the membranous urethral length (MUL) measurement and its interobserver agreement, and propose literature-based recommendations to standardize MUL measurement for increasing interobserver agreement. MUL measurements based on prostate MRI scans, for urinary incontinence risk assessment before radical prostatectomy (RP), may influence treatment decision-making in men with localised prostate cancer. Before implementation in clinical practise, MRI-based MUL measurements need standardization to improve observer agreement. Methods: Online libraries were searched up to August 5, 2022, on MUL measurements. Two reviewers performed article selection and critical appraisal. Papers reporting on preoperative MUL measurements and urinary continence correlation were selected. Extracted information included measuring procedures, MRI sequences, population mean/median values, and observer agreement. Results: Fifty papers were included. Studies that specified the MRI sequence used T2-weighted images and used either coronal images (n = 13), sagittal images (n = 18), or both (n = 12) for MUL measurements. ‘Prostatic apex’ was the most common description of the proximal membranous urethra landmark and ‘level/entry of the urethra into the penile bulb’ was the most common description of the distal landmark. Population mean (median) MUL value range was 10.4–17.1 mm (7.3–17.3 mm), suggesting either population or measurement differences. Detailed measurement technique descriptions for reproducibility were lacking. Recommendations on MRI-based MUL measurement were formulated by using anatomical landmarks and detailed descriptions and illustrations. Conclusions: In order to improve on measurement variability, a literature-based measuring method of the MUL was proposed, supported by several illustrative case studies, in an attempt to standardize MRI-based MUL measurements for appropriate urinary incontinence risk preoperatively. Clinical relevance statement: Implementation of MUL measurements into clinical practise for personalized post-prostatectomy continence prediction is hampered by lack of standardization and suboptimal interobserver agreement. Our proposed standardized MUL measurement aims to facilitate standardization and to improve the interobserver agreement. Key Points: • Variable approaches for membranous urethral length measurement are being used, without detailed description and with substantial differences in length of the membranous urethra, hampering standardization. • Limited interobserver agreement for membranous urethral length measurement was observed in several studies, while preoperative incontinence risk assessment necessitates high interobserver agreement. • Literature-based recommendations are proposed to standardize MRI-based membranous urethral length measurement for increasing interobserver agreement and improving preoperative incontinence risk assessment, using anatomical landmarks on sagittal T2-weighted images.

Occult lymph node (LN)-metastases are frequently found after upfront radical cystectomy (uRC) for bladder cancer (BC). We evaluated whether the implementation of 18F-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (FDG PET/CT) influenced nodal staging at uRC. All consecutive BC patients who underwent uRC with bilateral pelvic lymph node dissection (PLND) were identified and divided into two cohorts: cohort A consisted of patients staged with FDG PET/CT and contrast-enhanced CT (CE-CT) (2016–2021); cohort B consisted of patients staged with CE-CT only (2006–2011). The diagnostic performance of FDG PET/CT was assessed and compared with that of CE-CT. Thereafter, we calculated the occult LN metastases proportions for both cohorts. In total, 523 patients were identified (cohort A n = 237, and cohort B n = 286). Sensitivity, specificity, PPV and NPV of FDG PET/CT for detecting LN metastases were 23%, 92%, 42%, and 83%, respectively, versus 15%, 93%, 33%, 81%, respectively, for CE-CT. Occult LN metastases were found in 17% of cohort A (95% confidence interval (CI) 12.2–22.8) and 22% of cohort B (95% CI 16.9–27.1). The median size of LN metastases was 4 mm in cohort A versus 13 mm in cohort B. After introduction of FDG PET/CT, fewer and smaller occult LN metastases were present after uRC. Nevertheless, up to one-fifth of occult (micro-)metastases were still missed.

Purpose: Pleural plaques (PPs) are morphologic manifestations of long-term asbestos exposure. The relationship between PP and lung function is not well understood, whereas the time-consuming nature of PP delineation to obtain volume impedes research. To automate the laborious task of delineation, we aimed to develop automatic artificial intelligence (AI)–driven segmentation of PP. Moreover, we aimed to explore the relationship between pleural plaque volume (PPV) and pulmonary function tests. Materials and Methods: Radiologists manually delineated PPs retrospectively in computed tomography (CT) images of patients with occupational exposure to asbestos (May 2014 to November 2019). We trained an AI model with a no-new-UNet architecture. The Dice Similarity Coefficient quantified the overlap between AI and radiologists. The Spearman correlation coefficient (r) was used for the correlation between PPV and pulmonary function test metrics. When recorded, these were vital capacity (VC), forced vital capacity (FVC), and diffusing capacity for carbon monoxide (DLCO). Results: We trained the AI system on 422 CT scans in 5 folds, each time with a different fold (n = 84 to 85) as a test set. On these independent test sets combined, the correlation between the predicted volumes and the ground truth was r = 0.90, and the median overlap was 0.71 Dice Similarity Coefficient. We found weak to moderate correlations with PPV for VC (n = 80, r = −0.40) and FVC (n = 82, r = −0.38), but no correlation for DLCO (n = 84, r = −0.09). When the cohort was split on the median PPV, we observed statistically significantly lower VC (P = 0.001) and FVC (P = 0.04) values for the higher PPV patients, but not for DLCO (P = 0.19). Conclusion: We successfully developed an AI algorithm to automatically segment PP in CT images to enable fast volume extraction. Moreover, we have observed that PPV is associated with loss in VC and FVC.

Background: Robot-assisted radical prostatectomy (RARP) is a common treatment option for prostate cancer. A 3D model for surgical guidance can improve surgical outcomes. Manual expert radiologist segmentation of the prostate and tumor in prostate MRI to create 3D models is labor-intensive and prone to inter-observer variability, highlighting the need for automated segmentation methods. Methods: This study evaluates the performance of the prostate and tumor segmentation using a commercially available AI tool without (fully automated) and with manual adjustment (AI-assisted) compared to manual segmentations on 120 patients, using several metrics, including Dice Coefficient and Hausdorff distance. Tumor detection rates were assessed with recall and precision. Results: For the prostate, both the fully automated AI model and AI-assisted model achieved a mean Dice score of 0.88, while AI-assisted had a lower Hausdorff distance (7.22 mm) compared to the fully automated (7.40 mm). For tumor segmentations, the Dice scores were 0.53 and 0.62, with Hausdorff distances of 9.53 mm and 6.62 mm obtained for fully automated AI and AI-assisted methods, respectively. The fully automated AI method had a recall of 0.74 and a precision of 0.76 in tumor detection, while the AI-assisted method achieved 0.95 recall and 0.94 precision. Fully automated segmentation required less than 1 min, while adjustments for the AI-assisted segmentation took an additional 81 s, and manual segmentation took approximately 15–30 min. Conclusions: The fully automated AI model shows promising results, offering high tumor detection rates and acceptable segmentation metrics. The AI-assisted strategy improved the relevant metrics with minimal additional time investment. Therefore, the AI-assisted segmentation method is promising for allowing 3D-model-guided surgery for all patients undergoing RARP.

Prostate MRI has an important role in prostate cancer diagnosis and treatment, including detection, the targeting of prostate biopsies, staging and guiding radiotherapy and active surveillance. However, there are other ‘’less well-known’’ applications which are being studied and frequently used in our highly specialized medical center. In this review, we focus on two research topics that lie within the expertise of this study group: (1) anatomical parameters predicting the risk of urinary incontinence after radical prostatectomy, allowing more personalized shared decision-making, with special emphasis on the membranous urethral length (MUL); (2) the use of three-dimensional models to help the surgical planning. These models may be used for training, patient counselling, personalized estimation of nerve sparing and extracapsular extension and may help to achieve negative surgical margins and undetectable postoperative PSA values.

Purpose: The phase I induction trial (NCT04287894) assessed the feasibility and safety of induction immunotherapy (IIT) prior to concurrent chemoradiotherapy (cCRT) in patients with locally advanced non–small cell lung cancer (NSCLC). Patients and Methods: Patients with unresectable stage II/III NSCLC were eligible for inclusion. Patients received either one cycle of tremelimumab (75 mg) with two cycles of durvalumab (1,500 mg) in cohort I, one cycle of tremelimumab (300 mg) with two cycles of durvalumab in cohort II, or one cycle of tremelimumab (300 mg) with one cycle of durvalumab in cohort III. After IIT, a comprehensive radiological and pathological restaging was performed followed by cCRT. The combined primary endpoint was the feasibility and safety of IIT-cCRT. Results: Fifteen of 17 included patients were treated per protocol. IIT-cCRT was completed in 13 of the 15 patients within the predefined feasibility criteria. Grade ≥3 immune-related adverse events occurred in seven of the 15 patients, of which six were treated in the high-dose tremelimumab cohorts, thereby violating the safety criteria in cohorts II and III. The low-dose tremelimumab cohort (I) complied with safety criteria. Eleven patients had multilevel N2 or N3 disease at baseline; eight of these patients were downstaged to either N0/N1 or single-level N2 after IIT. Multiparametric MRI accurately identified nodal downstaging in all seven patients. Conclusions: Induction with high-dose tremelimumab plus durvalumab prior to cCRT in unresectable locally advanced NSCLC was associated with unacceptable toxicity, although IIT resulted in clinically relevant nodal downstaging in eight of the 11 patients with baseline multilevel N2 or N3 disease. Multiparametric MRI showed potential for evaluating treatment response.