Indeterminate lesions on prostate-specific membrane antigen (PSMA)-PET are challenging to address. We aimed to develop, implement, and evaluate a multidisciplinary consensus algorithm that integrates existing interpretation systems with multimodality imaging and clinicopathological information for interpreting indeterminate bone and lymph node lesions on PSMA-PET. This was a retrospective single-center study on a prospectively implemented algorithm. We included all consecutive prostate cancer patients whose PSMA-PET findings for indeterminate bone lesions or lymph nodes were discussed at a multidisciplinary tumor board (MDT) in 2024–2025. An algorithm determining the level of suspicion for metastasis was developed in a multidisciplinary fashion, incorporating lesion location, conventional imaging features, PSMA-PET characteristics, and clinicopathological information. The application of the algorithm and outcomes were documented, compared against a composite reference standard. Comparisons were made with PSMA-RADS and PROMISE V2 PSMA-expression scores. 81 patients (median age 68, interquartile range 64–75) were included. Algorithm results were benign (48.1

INTRODUCTION:Focal dose intensification strategies targeting the dominant intra-prostatic lesion (DIL) improve outcomes of patients with prostate cancer. The purpose was to determine whether the 6-month multiparametric (mp)MRI response of the DIL is associated with post-treatment prostate-specific antigen (PSA) kinetics after MRI linear accelerator (LINAC) guided stereotactic body radiotherapy (SBRT) with focal dose intensification. METHODS:Retrospective, single-center study including 72 patients with localized prostate cancer treated with MRI-LINAC SBRT with focal dose intensification and without androgen deprivation therapy. Patients were followed up at 6 months after SBRT with mpMRI and PSA. mpMRI complete response (CR) was defined as no residual lesion on diffusion-weighted imaging and dynamic contrast-enhanced MRI. This was correlated with PSA responses including PSA reduction (%), PSA reduction ≥ 50.0% (PSA50), and PSA ≤ 1.0 ng/mL. RESULTS:mpMRI CR was achieved in 37 patients (51.4%) at 6 months. Patients with mpMRI CR had greater PSA reduction (81.8% vs 66.1%, p < 0.001), and more commonly had PSA50 (100.0% vs 82.9%, p = 0.010) and PSA ≤ 1.0 ng/mL (45.9% vs 11.4%, p = 0.001) compared to those without mpMRI CR. In 10 patients without 6-month mpMRI CR but had further MRI follow-up (median 13 months), DILs either further decreased in size (30.0%) or resolved (70.0%). CONCLUSION:Initial 6-month mpMRI response correlates with PSA kinetics, which is associated with important clinical outcomes. mpMRI can be used for post-SBRT evaluation to gauge local tumor response of the DIL, where most recurrences occur.

Various imaging modalities play key roles throughout the different stages of prostate cancer. Each imaging modality has different strengths and weaknesses and various scoring systems or frameworks are used to interpret their findings. Discordances between imaging modalities or interpretation frameworks, and even with clinicopathological findings are not uncommon. Discordances often lead to challenges in the decision-making process, especially with dynamically changing indications for newer imaging modalities. While more research is needed on harmonizing interpretations across different modalities, multidisciplinary team discussion is key to optimizing management of patients with prostate cancer when such discordances are present. In this comprehensive review, we take a deep dive in to these various discordances seen in clinical practice and explore their clinical implications.

Postradiation therapy erectile dysfunction can significantly impact the quality of life of patients with prostate cancer (PCa). Critical anatomic structures, such as the neurovascular bundles (NVBs), internal pudendal arteries (IPAs), penile bulb, and corporal tissues track near the prostate, making them susceptible to radiation-related damage. This study aimed to evaluate the anatomic patterns of these structures and their relationship with the prostate and to provide comprehensive illustrative examples on magnetic resonance imaging (MRI) scans. Consecutive patients with PCa who underwent MRI-linear accelerator-based stereotactic body radiation therapy from January 2024 until December 2024 were included. NVB patterns were classified into 3 categories: (1) "classical" with discrete NVB elements, (2) "adherent," dispersed and adherent to prostatic capsule, and (3) "absent." The smallest distance between the IPA and the prostate capsule and the membranous urethral length, serving as a surrogate for the distance between corporal tissue and prostatic apex, were also measured. These MRI scan findings were compared between prostate volumes >40 and <40 mL and between MRI scan findings and pathologic features of the dominant intraprostatic lesion. A total of 160 men (median age 70 years, interquartile range [IQR], 64-76) were included. The most common NVB pattern was "classic" (80.0%-85.0%), followed by the "adherent" NVB pattern (13.8%-18.1%). The median smallest distance between the IPA and prostate was 2.3 cm (IQR, 1.8-2.8 cm), with 3.1% to 3.8% <1.0 cm. The median membranous urethral length was 1.5 cm (IQR, 1.2-1.8 cm), with 2.5% of patients <1.0 cm. No significant association was found between these MRI scan features and prostate volume or other variables (P = .09-.99). In conclusion, most patients with PCa demonstrated favorable anatomy for potential dose sparing of critical structures. Comprehensive MRI scan illustrations are provided to help radiation oncologists recognize the location, trajectory, and relationship of these structures, facilitating their contouring and ultimately aiding in achieving meaningful dose reductions to these erectile function structures.

To develop a tool for the clinical hybrid imaging workflow which combines morphologic and functional measurements. And to quantify the number of clicks saved per positron emission tomography/computed tomography (PET/CT) interpretation. A tool was developed where a volume of interest (VOI) is automatically created around line distance measurements. VOI statistics for both PET and CT component, and line distances are generated and displayed. Usage data for the first two months after introduction of the tool was analyzed. Eleven radiologists and nuclear medicine physicians used the tool in 364 PET/CTs. In 19

To explore pragmatic approaches integrating MRI and PSMA-PET/CT for evaluating extraprostatic extension (EPE) of prostate cancer (PCa). Consecutive patients with newly-diagnosed PCa that underwent multiparametric MRI and PSMA-PET/CT, followed by radical prostatectomy in 2021–2024 were included. Imaging parameters assessed on both modalities were: size, length of capsular contact (LCC), Likert scales (MRI EPE grade/PSMA Likert scale), PI-RADS/PRIMARY scores, and SUVmax. Three pragmatic integrated approaches were tested: (1) Integration of Likert scales (positive if either or both MRI and PSMA-PET/CT were positive); (2) P score (framework combining PI-RADS + PRIMARY); and (3) combining MRI morphological information with PSMA-PET/CT functional information (upgrading suspicion of lesions with LCC below cutoff if SUVmax>12). Diagnostic performance was tested with receiver operating characteristic (ROC) curves and compared using DeLong and McNemar tests. 67 men (median age, 66 years) with EPE in 76.1

Radiology departments face challenges in delivering timely and accurate imaging reports, especially in high-volume, subspecialized settings. In this retrospective cohort study at a tertiary cancer center, we assessed the efficacy of an Automatic Assignment System (AAS) in improving radiology workflow efficiency by analyzing 232,022 CT examinations over a 12-month period post-implementation and compared it to a historical control period. The AAS was integrated with the hospital-wide scheduling system and set up to automatically prioritize and distribute unreported CT examinations to available radiologists based on upcoming patient appointments, coupled with an email notification system. Following this AAS implementation, despite a 9% rise in CT volume, coupled with a concurrent 8% increase in the number of available radiologists, the mean daily urgent radiology report requests (URR) significantly decreased by 60% (25 ± 12 to 10 ± 5, t = -17.6, p < 0.001), and URR during peak days (95 th quantile) was reduced by 52.2% from 46 to 22 requests. Additionally, the mean turnaround time (TAT) for reporting was significantly reduced by 440 min for patients without immediate appointments and by 86 min for those with same-day appointments. Lastly, patient waiting time sampled in one of the outpatient clinics was not negatively affected. These results demonstrate that AAS can substantially decrease workflow interruptions and improve reporting efficiency.

Purpose To investigate the accuracy and robustness of prostate segmentation using deep learning across various training data sizes, MRI vendors, prostate zones, and testing methods relative to fellowship-trained diagnostic radiologists. Materials and Methods In this systematic review, Embase, PubMed, Scopus, and Web of Science databases were queried for English-language articles using keywords and related terms for prostate MRI segmentation and deep learning algorithms dated to July 31, 2022. A total of 691 articles from the search query were collected and subsequently filtered to 48 on the basis of predefined inclusion and exclusion criteria. Multiple characteristics were extracted from selected studies, such as deep learning algorithm performance, MRI vendor, and training dataset features. The primary outcome was comparison of mean Dice similarity coefficient (DSC) for prostate segmentation for deep learning algorithms versus diagnostic radiologists. Results Forty-eight studies were included. Most published deep learning algorithms for whole prostate gland segmentation (39 of 42 [93%]) had a DSC at or above expert level (DSC ≥ 0.86). The mean DSC was 0.79 ± 0.06 (SD) for peripheral zone, 0.87 ± 0.05 for transition zone, and 0.90 ± 0.04 for whole prostate gland segmentation. For selected studies that used one major MRI vendor, the mean DSCs of each were as follows: General Electric (three of 48 studies), 0.92 ± 0.03; Philips (four of 48 studies), 0.92 ± 0.02; and Siemens (six of 48 studies), 0.91 ± 0.03. Conclusion Deep learning algorithms for prostate MRI segmentation demonstrated accuracy similar to that of expert radiologists despite varying parameters; therefore, future research should shift toward evaluating segmentation robustness and patient outcomes across diverse clinical settings. Keywords: MRI, Genital/Reproductive, Prostate Segmentation, Deep Learning Systematic review registration link: osf.io/nxaev © RSNA, 2024.

In this chapter some concepts of cybersecurity are reviewed. Common cyberattacks such as malware, botnets, and phishing are explained. The hypothetical usage of AI for attacks on healthcare systems or for defensive purposes is explored.