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Simple Summary: MRI uses magnetic pulses to create images of the body. PET scans use radioactive chemicals to determine what kinds of processes are going on in the body. PSMA is a chemical that is abundant on prostate cancer cells, so a PET scan using a radioactive chemical that attaches to PSMA shows where prostate cancer is, but this test has drawbacks: it is not widely available, it is expensive, and it exposes patients to radiation. However, a recent study found that PSMA PET was more accurate than MRI for finding areas where prostate cancer spreads. This study looks at the "false negative" cases—the specific cases where the MRI did not find prostate cancer when PSMA PET did—and how reading MRI can be improved. Background: PSMA PET has emerged as a "gold standard" imaging modality for assessing prostate cancer metastases. However, it is not universally available, and this limits its impact. In contrast, whole-body MRI is much more widely available but misses more lesions. This study aims to improve the interpretation of whole-body MRI by comparing false negative scans retrospectively to PSMA PET. Methods: This study was a retrospective sub-analysis of a prospectively collected database of patients who participated in a clinical trial of PSMA PET/MRI comparing PSMA PET and whole-body MRI from 2018–2021. Subjects whose separately read PSMA PET and MRI diagnostic reports showed discrepancies ("false negative" MRI cases) were selected for sub-analysis. The cases were reviewed by the same attending radiologist who originally read the scans. The radiologist noted specific features on MRI indicating metastatic disease that were initially missed. Results: Of 263 cases, 38 (14%) met the inclusion criteria and were reviewed. Six classes of mpMRI false negatives were identified: anatomically normal (18, 47%), atypical MRI appearance (6, 16%), mischaracterization (1, 3%), undercall (6, 16%), obscured (4, 11%), and no abnormality on MRI (3, 8%). Considering that the atypical and undercalled cases could have been adjusted in retrospect, and that 4 additional cases had positive lesions to the same extent and 11 further cases had disease confined to the pelvis, only 11 (4%) of the original 263 would have had disease outside of a conventional radiation treatment plan. Conclusion: Notably, almost 50% of the cases, including most lymph node metastases, were anatomically normal using standard criteria. This suggests that current anatomic criteria for evaluating prostate cancer lymph node metastases are not ideal, and there is a need for improved criteria. In addition, 32% of cases involved some element of human interpretive error, and, therefore, improving reader training may lead to more accurate results. [ABSTRACT FROM AUTHOR]

Simple Summary: Prostate cancer screening has traditionally been accomplished by a blood test for prostate serum antigen (PSA) followed by biopsy. MRI is very accurate at finding cancer, but ultrasound provides real-time guidance for biopsy. Using magnetic resonance imaging (MRI) to guide the biopsy under ultrasound improves detection and, in the case that only non-aggressive cancer is found, confidence in avoiding treating cancers that are unlikely to be deadly. Different approaches can be used with many different MRI–ultrasound fusion techniques, including "cognitive" fusion using only the practitioner's reading of the scans, but also software fusion using mechanical or even pure software-aided matching of the information from MRI and ultrasound. The use of MRI–ultrasound image fusion targeted biopsy of the prostate in the face of an elevated serum PSA is now recommended by multiple societies, and results in improved detection of clinically significant cancer and, potentially, decreased detection of indolent disease. This combines the excellent sensitivity of MRI for clinically significant prostate cancer and the real-time biopsy guidance and confirmation of ultrasound. Both transperineal and transrectal approaches can be implemented using cognitive fusion, mechanical fusion with an articulated arm and electromagnetic registration, or pure software registration. The performance has been shown comparable to in-bore MRI biopsy performance. However, a number of factors influence the performance of this technique, including the quality and interpretation of the MRI, the approach used for biopsy, and experience of the practitioner, with most studies showing comparable performance of MRI–ultrasound fusion to in-bore targeted biopsy. Future improvements including artificial intelligence promise to refine the performance of all approaches. [ABSTRACT FROM AUTHOR]

In this study, we investigated the potential of the multivariate curve resolution alternating least squares (MCR‐ALS) algorithm for analyzing three‐dimensional (3D) 1H‐MRSI data of the prostate in prostate cancer (PCa) patients. MCR‐ALS generates relative intensities of components representing spectral profiles derived from a large training set of patients, providing an interpretable model. Our objectives were to classify magnetic resonance (MR) spectra, differentiating tumor lesions from benign tissue, and to assess PCa aggressiveness. We included multicenter 3D 1H‐MRSI data from 106 PCa patients across eight centers. The patient cohort was divided into a training set (N = 63) and an independent test set (N = 43). Singular value decomposition determined that MR spectra were optimally represented by five components. The profiles of these components were extracted from the training set by MCR‐ALS and assigned to specific tissue types. Using these components, MCR‐ALS was applied to the test set for a quantitative analysis to discriminate tumor lesions from benign tissue and to assess tumor aggressiveness. Relative intensity maps of the components were reconstructed and compared with histopathology reports. The quantitative analysis demonstrated a significant separation between tumor and benign voxels (t‐test, p < 0.001). This result was achieved including voxels with low‐quality MR spectra. A receiver operating characteristic analysis of the relative intensity of the tumor component revealed that low‐ and high‐risk tumor lesions could be distinguished with an area under the curve of 0.88. Maps of this component properly identified the extent of tumor lesions. Our study demonstrated that MCR‐ALS analysis of 1H‐MRSI of the prostate can reliably identify tumor lesions and assess their aggressiveness. It handled multicenter data with minimal preprocessing and without using prior knowledge or quality control. These findings indicate that MCR‐ALS can serve as an automated tool to assess the presence, extent, and aggressiveness of tumor lesions in the prostate, enhancing diagnostic capabilities and treatment planning of PCa patients. [ABSTRACT FROM AUTHOR]

Multiparametric MRI (mpMRI) of the prostate aids risk stratification of patients with elevated PSA levels. Although most clinically significant prostate cancers are detected by mpMRI, insignificant cancers are less evident. Thus, multiple international prostate cancer guidelines now endorse routine use of prostate MRI as a secondary screening test before prostate biopsy. Nonetheless, management of patients with negative mpMRI results (defined as PI-RADS category 1 or 2) remains unclear. This AJR Expert Panel Narrative Review summarizes the available literature on patients with an elevated screening PSA level and a negative prostate mpMRI result and provides guidance for these patients' management. Systematic biopsy should not be routinely performed after a negative mpMRI examination in patients at average risk but should be considered in patients at high risk. In patients who undergo PSA screening rather than systematic biopsy after negative mpMRI, clear triggers should be established for when to perform a repeat MRI examination. Patients with a negative MRI result followed by negative biopsy should follow their health care practitioners' preferred guidelines concerning subsequent PSA screening for the patient's risk level. Insufficient high-level data exist to support routine use of adjunctive serum or urine biomarkers, artificial intelligence, or PSMA PET to determine the need for prostate biopsy after a negative mpMRI examination.

Prostate magnetic resonance imaging (MRI) is increasingly being used to diagnose and stage prostate cancer. The Prostate Imaging and Data Reporting System (PI-RADS) version 2.1 is a consensus-based reporting system that provides a standardized and reproducible method for interpreting prostate MRI. This primer provides an overview of the PI-RADS system, focusing on its current role in clinical interpretation. It discusses the appropriate use of PI-RADS and how it should be applied by radiologists in clinical practice to assign and report PI-RADS assessments. We also discuss the changes from prior versions and published validation studies on PI-RADS accuracy and reproducibility., (Copyright © 2023 Elsevier Inc. All rights reserved.)