Andrei Saraiva Purysko

Active surveillance (AS) is an established management strategy for men with low-risk and some favorable intermediate-risk prostate cancer. Multiparametric MRI (MRI) plays an increasingly important role in AS, contributing to initial risk stratification, confirmatory evaluation, and longitudinal monitoring. However, comparing baseline and follow-up MR images is challenging because acquisition varies, readers differ, and imaging alone has limited ability to define clinically meaningful progression. The Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) scoring system was developed to standardize the assessment of interval change on serial prostate MRI. PRECISE provides a structured framework for categorizing radiologic regression, stability, and progression, thereby addressing a key limitation of Prostate Imaging – Reporting and Data System (PI-RADS), which was designed for lesion detection rather than longitudinal assessment. PRECISE version 2 further refines definitions and introduces clearer categories, including separation of stable visible and stable non-visible disease and recognition of non-diagnostic examinations. Available evidence suggests that PRECISE performs best as a rule-out tool, with consistently high negative predictive value for clinically significant progression, while radiologic progression demonstrates more limited positive predictive value for histopathologic upgrading. Although PRECISE reduces subjective interpretation through structured scoring, its application remains affected by variability in MRI quality and heterogeneity in AS protocols. To mitigate these limitations, radiologists should incorporate prostate-specific antigen kinetics, biopsy results, and clinical context into their interpretation of serial MRI. In this review, we provide a practical, radiologist-focused overview of PRECISE, summarize its evolution and evidence base, and illustrate its application in clinical practice. We also discuss key limitations, common pitfalls, and the importance of MRI quality and standardization in improving reproducibility. PRECISE represents an important step toward standardized longitudinal assessment in prostate cancer AS and supports more consistent, evidence-based multidisciplinary decision-making.

Purpose of the Report: The PRIMARY score standardizes interpretation of PSMA PET for intraprostatic assessment of clinically significant prostate cancer (csPCa). Although early studies are promising, no meta-analysis has systematically evaluated its accuracy. We aimed to assess the diagnostic performance of PRIMARY and compare it with PI-RADS. Material and Methods: A systematic review and meta-analysis were performed according to PRISMA-DTA guidelines. Studies assessing the PRIMARY score on PSMA PET/CT or PET/MRI for csPCa detection were included. The primary analysis focused on biopsy-naïve patients; secondary analyses incorporated all studies irrespective of prior histology, evaluated thresholds (≥3 vs. ≥4), compared PRIMARY with PI-RADS, and examined combined performance. Pooled sensitivity and specificity were estimated with a bivariate random-effects model. Results: Thirteen studies (n=1974) were included. In biopsy-naïve cohorts (6 studies), PRIMARY ≥3 achieved pooled sensitivity/specificity of 90% (95% CI: 86%–93%) and 63% (95% CI: 57%–69%). In an expanded analysis of 9 studies regardless of prior biopsy, values were 87% (82%–90%) and 56% (46%–65%). Across 5 studies directly comparing thresholds, raising the cutoff from ≥3 to ≥4 reduced sensitivity from 89% to 81% but increased specificity from 53% to 72%. Three head-to-head studies showed comparable accuracy between PRIMARY and PI-RADS. Conclusions: PRIMARY demonstrates high sensitivity and moderate specificity for csPCa, comparable to PI-RADS. In biopsy-naïve men it shows robust performance, and combination with mpMRI further improves sensitivity. Threshold selection should reflect clinical intent, supporting PRIMARY as a tool for pre-biopsy risk stratification and integrated diagnostic workflows.

The American College of Radiology’s Prostate MR Image Quality Improvement Collaborative identified the factors of MRI protocol optimization, patient preparation, personnel training, and performance monitoring and feedback as key drivers of prostate MR image quality and developed interventions to address these areas.

Radiologists must have a thorough understanding of seed placement, seed migration patterns, and hydrogel spacer complications to enhance interpretation of posttreatment imaging studies and improve care for patients with prostate cancer who are undergoing low-dose-rate brachytherapy.

Objective Poor magnetic resonance imaging (MRI) quality can lead to missed prostate cancer diagnoses. Our institution had variability in pre-MRI patient preparation, limited collaboration between radiologists and technologists, and no formal, routine image quality auditing process. The Prostate Imaging Quality system version 1 (PI-QUAL v1) is an established framework for assessing prostate MRI quality. Our quality improvement team aimed to increase the percentage of exams that received a PI-QUALv1 score of ≥ 4 and the percentage with at least one Diffusion Weighted Imaging (DWI) sequence rated optimal. Methods In partnership with the American College of Radiology (ACR) Learning Network, we introduced numerous interventions to improve our baseline workflow. During our Intervention Phase (May– September 2023), our team standardized pre-MRI patient instructions and documentation regarding nil by mouth (NPO) status and bladder emptying. MRI technologists received image quality education and were involved in the image scoring process. Our team also used weekly PI-QUALv1 scoring criteria which was later embedded into the reporting system. Interventions were maintained during a Sustainment Phase (October 2023– January 2024). Results 1206 MRI prostate exams were audited. From the Pre-intervention to Sustainment Phase, the percentage of exams with PI-QUAL score ≥ 4 increased from 90% (95% CI: 87–94%) to 97% (95% CI: 95–99%). The percentage of exams meeting DWI criteria increased from 77% (95% CI: 74–79%) to 83% (95% CI: 78–88%). Team members reported that integrating scoring into the reporting system saved time. Patients and staff reported that standardized instructions led to a better understanding of how patient preparation improves image quality. Conclusions Consistent patient preparation, team collaboration, and standardized quality scoring led to promising quality trends without using enema. PI-QUAL scores and DWI quality reached the upper limits of performance previously described by the ACR Learning Network Prostate MR QI Collaborative. Graphical abstract

Purpose High-quality imaging is critical for accurate prostate cancer assessment using MRI. This study describes a quality improvement (QI) initiative for prostate MRI and evaluates the impact of image quality on diagnostic performance. Methods In this prospective study, 1328 patients underwent prostate MRI between March 2023 and March 2024. The QI initiative focused on patient preparation, protocol standardization, technologist education, and quality control. Image quality was prospectively scored using the Prostate Imaging Quality (PI-QUAL) system. Diagnostic performance was assessed by comparing the positive predictive value (PPV) of PI-RADS ≥ 3 lesions before and after the intervention and between exams with optimal (PI-QUAL ≥ 4) and suboptimal quality. Fisher’s exact test was used for comparisons. Clinically significant prostate cancer (csPCa) was defined as Gleason Grade Group ≥ 2. Results The proportion of PI-QUAL ≥ 4 exams increased from 67 to 84% after the intervention (p < 0.001). The PPV for any prostate cancer improved from 65 to 78% (p = 0.03), though the increase for csPCa (from 42 to 46%) was not statistically significant (p = 0.5). No significant difference in PPV was observed between optimal and suboptimal exams for any cancer (76% vs. 77%, p = 0.9) or csPCa (45% vs. 48%, p = 0.7). Conclusion The QI initiative significantly improved image quality and overall cancer detection rates. However, the association between image quality and csPCa detection was not statistically significant, possibly due to greater improvements in T2-weighted images vs. diffusion weighted images and high reader expertise.

Gastrointestinal (GI) cancers are a leading cause of cancer-related mortality worldwide. Accurate identification of lymphatic spread is essential for staging, prognosis, and treatment planning. The first metastatic lymph nodes vary depending on the primary tumor site, representing the initial echelon of nodal involvement. This pictorial essay reviews the lymphatic drainage patterns of major gastrointestinal cancers—including esophageal, gastric, pancreatic, hepatobiliary, and colorectal tumors—highlighting key nodal stations commonly involved in metastatic spread emphasizing their diagnostic and clinical relevance. By integrating multimodality imaging findings, we highlight key lymph node groups involved in metastasis, discuss their anatomical significance, and illustrate their appearance on computed tomography (CT) and magnetic resonance imaging (MRI). Understanding these patterns is critical for optimizing oncologic management.