Citations

Abstract Purpose To assess if PSA density (PSAD) velocity is a predictor of clinically significant prostate cancer (csPCa). Methods Patients undergoing prostate MR for suspected csPCa between 2017 and 2023 were included. Of these, patients who underwent two or more MR exams within 0.3 to 2 years to each other and pathological confirmation within 1 year after the last MR were identified. PI-RADS score, patient age, screening or active surveillance (AS), PSA, PSAD, PSA-velocity and PSAD-velocity were assessed if they were predictor of csPCa. For univariate analysis, all variables were assessed using student t or chi-square tests. When variables were considered significant, variables were entered into multivariate logistic regression model. Results 23,244 MRs were performed (17,703 screening, 5,541AS). 1,174 patients (mean age: 65.9) met the inclusion criteria, and 550 patients (47%) were diagnosed with csPCa. On univariate analysis, PI-RADS score (p<.0001), age (67.0 vs 64.9, p<.0001), AS exam (67% vs 59%, p = 0.004), PSA (7.5 vs 6.6, p<.001 ), PSAD (0.16 vs 0.12, p<.0001) and PSAD-velocity (0.023 vs 0.012, p = 0.005 ) were predictors of csPCa but PSA-velocity (1.4 vs 1.2, p=.4) was not. On multivariate analysis, PI-RADS score (p<.0001), age (p<.0001), AS exam (p<.0001), PSA (p<.0001) and PSAD (p<.0001) remained significant predictors, but PSAD-velocity was not (p=.1). Conclusions Higher PSAD-velocity was associated with presence of csPCa on univariate analysis but not on multivariate analysis when combined with other predictors such PI-RADS score, age, and PSAD.

Imaging is integral to detection and characterization of complications after prostate interventions, including vascular, infectious, urinary, and radiation-related complications, and facilitates timely diagnosis and management.

ABSTRACT Background Clinical T 2 ‐weighted (T2W) MRI of prostate cancer (PCa) usually implements a 2D fast‐spin‐echo (FSE) sequence, but understanding the echo‐time‐dependent contrast behavior is not straightforward due to the complicated FSE signal evolution. Consequently, consensus‐based recommendations on the optimal effective echo time (TE eff ) to maximize contrast are lacking. Purpose To investigate the effect of TE eff on PCa lesion contrast in prostate T2W MRI. Study Type Phantom and in vivo prospective study. Subjects A standard MRI phantom and 53 prostate cancer patients (29 for image evaluation and 24 for quantitative lesion analysis). Field Strength and Sequence Multi‐slice T2W FSE sequence at 3 T acquired at multiple TE eff values. Assessment Three readers (13, 25, and 27 years' experience) evaluated TE eff = 100 ms versus 150 ms on diagnostic quality and reader preference. The effective T 2 relaxation rates ( T 2,eff ) were measured using FSE sequences in the phantom and used to predict the optimal TE eff maximizing T2W contrasts. From multi‐TE eff scans of subjects with suspected PCa, T 2,eff values of PCa lesions and healthy tissue were measured and used to calculate the optimal TE eff maximizing the lesion contrast. In vivo contrast metrics were measured as a function of TE eff . Statistical Tests Wilcoxon test of reader scores, with p < 0.05 defining statistical significance. Results No statistically significant difference was found in diagnostic quality between TE eff = 150 ms and 100 ms images, but all three readers significantly favored TE eff = 150 ms. Phantom experiments demonstrated that TE eff ‐dependent FSE signal progression can be characterized by T 2,eff values typically 40% longer than actual T 2 values, allowing accurate prediction of optimal TE eff within 2%–5%. Applied to PCa imaging, in vivo measurements indicated that effective T 2 relaxation times of the prostate are on average 1.5× longer than published T 2 values. Data Conclusion The benefits of TE eff = 150 ms versus 100 ms in prostate T2W FSE were supported by reader preference, phantom experiments, in vivo measurements, and analytic optimizations. Evidence Level 2. Technical Efficacy 2.

Abstract Photon-counting detector CT (PCD-CT) directly detects individual photons and measures their energies, enabling the acquisition of multi-energy data from a single x-ray source with higher spatial resolution, thereby allowing visualization of smaller arteries and veins and other important imaging features not seen at conventional CT. It also substantially reduces calcium and stent blooming artifacts. Appropriate patient selection and task-based optimization of acquisition, reconstruction, and interpretation are critical to realize these benefits. Vascular imaging examinations for which early evidence shows that PCD-CT demonstrates higher diagnostic performance compared to conventional CT include coronary CT angiography (CTA) for evaluation of partially calcified plaques or stents, peripheral runoff CTA, detection of cerebrospinal fluid-venous fistulas, and head CTA for evaluation of small intracranial vessels and aneurysms. Current limitations include excessive image noise with the sharpest reconstruction kernels and challenges when adapting conventional CT protocols (eg, requiring sharper kernels, thinner slices, higher matrices, tailored scan modes) to achieve time-efficient image reconstruction and hanging protocols. New solutions and directions will include deep-learning-based image noise reduction, improved spectral separation, strategic triage of specific patient populations to PCD-CT systems, and subspecialty clinical practice recommendations for this new technology.

Abstract Purpose To evaluate the effectiveness of subcutaneous glucagon in reducing motion artifact during prostate MRI through intraindividual comparison. Methods At our institution patients undergoing a clinical prostate MRI exam receive 1 mg of subcutaneous glucagon before scanning. From February 15, 2024 to February 11, 2025 33 such patients were recruited to undergo an additional, research exam without glucagon. All exams were acquired at 3T. An axial T2-weighted spin-echo series (T2-WI) was acquired within both exams. Evaluation of the T2-WI series was done by three experienced radiologists using the criteria of diagnostic quality (0–3 scale), PI-QUALv2 (0–3 sum), motion artifact (significant, visible, none), and reviewer preference (five-point relative scale). Due to differences in prescribed coverage, the scan times for the two T2-WI sequences were in general different for each subject. Results were stratified using the acquisition time ratio (Trel) between the glucagon vs. non-glucagon scans. Wilcoxon tests assessed score differences. Results Across all 33 subjects, no significant differences were found between glucagon and non-glucagon scans. However, the observed negative correlation between glucagon preference and Trel (p = 0.026) led to stratification into low-Trel (n = 16) and high-Trel (n = 17) groups. In the low-Trel group the glucagon scans provided significantly improved diagnostic quality (p = 0.048), PI-QUALv2 sum (p = 0.049), motion scores (p = 0.047), and reader preference (p = 0.042). Conclusion Subcutaneous glucagon provides improved image quality in prostate T2-WI MRI when scan duration remains within 1.25× of that of a non-glucagon T2-WI series. The benefit appears to decrease with longer scan times.

Objectives: The aims of the study are to develop a prostate cancer risk prediction model that combines clinical and magnetic resonance imaging (MRI)–related findings and to assess the impact of adding Prostate Imaging-Reporting and Data System (PI-RADS) ≥3 lesions-level findings on its diagnostic performance. Methods: This 3-center retrospective study included prostate MRI examinations performed with clinical suspicion of clinically significant prostate cancer (csPCa) between 2018 and 2022. Pathological diagnosis within 1 year after the MRI was used to diagnose csPCa. Seven clinical, 3 patient-level MRI-related, and 4 lesion-level MRI-related findings were extracted. After feature selection, 2 logistic regression models with and without lesions-level findings were created using data from facility I and II (development cohort). The area under the receiver operating characteristic curve (AUC) between the 2 models was compared in the PI-RADS ≥3 population in the development cohort and Facility III (validation cohort) using the Delong test. Interfacility differences of the selected predictive variables were evaluated using the Kruskal-Wallis test or chi-squared test. Results: Selected lesion-level features included the peripheral zone involvement and apparent diffusion coefficient (ADC) values. The model with lesions-level findings had significantly higher AUC than the model without in 655 examinations in the development cohort (0.81 vs 0.79, respectively, P = 0.005), but not in 553 examinations in the validation cohort (0.77 vs 0.76, respectively). Large interfacility differences were seen in the ADC distribution (P < 0.001) and csPCa proportion in PI-RADS 3–5 (P < 0.001). Conclusions: Adding lesions-level findings improved the csPCa discrimination in the development but not the validation cohort. Interfacility differences impeded model generalization, including the distribution of reported ADC values and PI-RADS score-level csPCa proportion.

AbstractPurposeTo study if adaptive image receive (AIR) receiver coil elements can be configured into a 2D array with high (>45% by diameter) element‐to‐element overlap, allowing improved SNR at depth (0.7–1.5× element diameter) versus conventional (20%) overlap.MethodsAn anterior array composed of twenty 10‐cm diameter elements with 45% overlap arranged into a 4 × 5 grid and a similar 3 × 7 twenty‐one‐element posterior array were constructed. SNR and g‐factor were measured in a pelvic phantom using the new high‐density (HD) arrays (41 total elements) and compared to vendor AIR‐based arrays (30 total elements) with conventional overlap. T2‐weighted fast‐spin‐echo (T2SE) images acquired using both arrays were compared in 20 subjects. SNR was estimated in vivo. Results were compared blindly by three uroradiologists using a five‐point scale. Images using the HD arrays were also compared to a set of images acquired over a range of acceleration factors (R = 2.0, 2.5, 3.0) with the conventional arrays.ResultsSNR within the phantom was on average 15% higher for R = 1.0, 1.5, and 2.0 using the HD arrays. Across the 20 subjects SNR within the prostate was 11% higher and assessed radiologically as significantly higher (p < 0.001) for the HD versus conventional arrays. At all acceleration factors the new HD arrays outperformed the conventional arrays (p ≤ 0.01), allowing increased R for similar SNR.ConclusionAIR elements can be configured into 2D arrays with high (45%) element‐to‐element overlap, consistently providing increased SNR at depth versus arrays with conventional (20%) overlap. The SNR improvement allows increased acceleration in T2SE prostate MRI.

The performance of a deep learning model was not different from that of radiologists in the detection of clinically significant prostate cancer at MRI, and gradient-weighted class activation maps localized the tumor.

PurposeThe purpose is to develop a model‐based image‐reconstruction method using wavelet sparsity regularization for maintaining restoration of through‐plane resolution but with improved retention of SNR versus linear reconstruction using Tikhonov (TK) regularization in high through‐plane resolution (1 mm) T2‐weighted spin‐echo (T2SE) images of the prostate.MethodsA wavelet sparsity (WS)–regularized image reconstruction was developed that takes as input a set of ≈80 overlapped 3‐mm‐thick slices acquired using a T2SE multislice scan and typically 30 coil elements. After testing in contrast and resolution phantoms and calibration in 6 subjects, the WS reconstruction was evaluated in 16 consecutive prostate T2SE MRI exams. Results reconstructed with nominal 1‐mm thickness were compared with those from the TK reconstruction with the same raw data. Results were evaluated radiologically. The ratio of magnitude of prostate signal to periprostatic muscle signal was used to assess the presence of noise reduction. Technical performance was also compared with a commercial 3D‐T2SE sequence.ResultsThe new WS reconstruction was assessed as superior statistically to TK for overall SNR, contrast, and multiple evaluation criteria related to sharpness while retaining the high (1 mm) through‐plane resolution. Wavelet sparsity tended to provide improved overall diagnostic quality versus TK, but not significantly so. In all 16 studies, the prostate‐to‐muscle signal ratio increased.ConclusionsModel‐based WS‐regularized reconstruction consistently provides improved SNR in high (1 mm) through‐plane resolution images of prostate T2SE MRI versus linear reconstruction using TK regularization.