Application of high-density 2D receiver coil arrays for improved SNR in prostate MRI.

PURPOSE: To 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. METHODS: An 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. RESULTS: SNR 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. CONCLUSION: AIR 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.

Fully Automated Deep Learning Model to Detect Clinically Significant Prostate Cancer at MRI.

Background Multiparametric MRI can help identify clinically significant prostate cancer (csPCa) (Gleason score ≥7) but is limited by reader experience and interobserver variability. In contrast, deep learning (DL) produces deterministic outputs. Purpose To develop a DL model to predict the presence of csPCa by using patient-level labels without information about tumor location and to compare its performance with that of radiologists. Materials and Methods Data from patients without known csPCa who underwent MRI from January 2017 to December 2019 at one of multiple sites of a single academic institution were retrospectively reviewed. A convolutional neural network was trained to predict csPCa from T2-weighted images, diffusion-weighted images, apparent diffusion coefficient maps, and T1-weighted contrast-enhanced images. The reference standard was pathologic diagnosis. Radiologist performance was evaluated as follows: Radiology reports were used for the internal test set, and four radiologists' PI-RADS ratings were used for the external (ProstateX) test set. The performance was compared using areas under the receiver operating characteristic curves (AUCs) and the DeLong test. Gradient-weighted class activation maps (Grad-CAMs) were used to show tumor localization. Results Among 5735 examinations in 5215 patients (mean age, 66 years ± 8 [SD]; all male), 1514 examinations (1454 patients) showed csPCa. In the internal test set (400 examinations), the AUC was 0.89 and 0.89 for the DL classifier and radiologists, respectively (P = .88). In the external test set (204 examinations), the AUC was 0.86 and 0.84 for the DL classifier and radiologists, respectively (P = .68). DL classifier plus radiologists had an AUC of 0.89 (P < .001). Grad-CAMs demonstrated activation over the csPCa lesion in 35 of 38 and 56 of 58 true-positive examinations in internal and external test sets, respectively. Conclusion The performance of a DL model was not different from that of radiologists in the detection of csPCa at MRI, and Grad-CAMs localized the tumor. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Johnson and Chandarana in this issue.

Natural language processing pipeline to extract prostate cancer-related information from clinical notes.

OBJECTIVES: To develop an automated pipeline for extracting prostate cancer-related information from clinical notes. MATERIALS AND METHODS: This retrospective study included 23,225 patients who underwent prostate MRI between 2017 and 2022. Cancer risk factors (family history of cancer and digital rectal exam findings), pre-MRI prostate pathology, and treatment history of prostate cancer were extracted from free-text clinical notes in English as binary or multi-class classification tasks. Any sentence containing pre-defined keywords was extracted from clinical notes within one year before the MRI. After manually creating sentence-level datasets with ground truth, Bidirectional Encoder Representations from Transformers (BERT)-based sentence-level models were fine-tuned using the extracted sentence as input and the category as output. The patient-level output was determined by compilation of multiple sentence-level outputs using tree-based models. Sentence-level classification performance was evaluated using the area under the receiver operating characteristic curve (AUC) on 15% of the sentence-level dataset (sentence-level test set). The patient-level classification performance was evaluated on the patient-level test set created by radiologists by reviewing the clinical notes of 603 patients. Accuracy and sensitivity were compared between the pipeline and radiologists. RESULTS: Sentence-level AUCs were ≥ 0.94. The pipeline showed higher patient-level sensitivity for extracting cancer risk factors (e.g., family history of prostate cancer, 96.5% vs. 77.9%, p < 0.001), but lower accuracy in classifying pre-MRI prostate pathology (92.5% vs. 95.9%, p = 0.002) and treatment history of prostate cancer (95.5% vs. 97.7%, p = 0.03) than radiologists, respectively. CONCLUSION: The proposed pipeline showed promising performance, especially for extracting cancer risk factors from patient's clinical notes. CLINICAL RELEVANCE STATEMENT: The natural language processing pipeline showed a higher sensitivity for extracting prostate cancer risk factors than radiologists and may help efficiently gather relevant text information when interpreting prostate MRI. KEY POINTS: When interpreting prostate MRI, it is necessary to extract prostate cancer-related information from clinical notes. This pipeline extracted the presence of prostate cancer risk factors with higher sensitivity than radiologists. Natural language processing may help radiologists efficiently gather relevant prostate cancer-related text information.

Comparison of model-based versus deep learning-based image reconstruction for thin-slice T2-weighted spin-echo prostate MRI.

PURPOSE: To compare a previous model-based image reconstruction (MBIR) with a newly developed deep learning (DL)-based image reconstruction for providing improved signal-to-noise ratio (SNR) in high through-plane resolution (1 mm) T2-weighted spin-echo (T2SE) prostate MRI. METHODS: Large-area contrast and high-contrast spatial resolution of the reconstruction methods were assessed quantitatively in experimental phantom studies. The methods were next evaluated radiologically in 17 subjects at 3.0 Tesla for whom prostate MRI was clinically indicated. For each subject, the axial T2SE raw data were directed to MBIR and to the DL reconstruction at three vendor-provided levels: (L)ow, (M)edium, and (H)igh. Thin-slice images from the four reconstructions were compared using evaluation criteria related to SNR, sharpness, contrast fidelity, and reviewer preference. Results were compared using the Wilcoxon signed-rank test using Bonferroni correction, and inter-reader comparisons were done using the Cohen and Krippendorf tests. RESULTS: Baseline contrast and resolution in phantom studies were equivalent for all four reconstruction pathways as desired. In vivo, all three DL levels (L, M, H) provided improved SNR versus MBIR. For virtually, all other evaluation criteria DL L and M were superior to MBIR. DL L and M were evaluated as superior to DL H in fidelity of contrast. For 44 of the 51 evaluations, the DL M reconstruction was preferred. CONCLUSION: The deep learning reconstruction method provides significant SNR improvement in thin-slice (1 mm) T2SE images of the prostate while retaining image contrast. However, if taken to too high a level (DL High), both radiological sharpness and fidelity of contrast diminish.

Cancer Detection Rate and Abnormal Interpretation Rate of Prostate MRI in Patients With Low-Grade Cancer.

PURPOSE: The aim of this study was to evaluate the utility of cancer detection rate (CDR) and abnormal interpretation rate (AIR) in prostate MRI for patients with low-grade prostate cancer (PCa). METHODS: This three-center retrospective study included patients who underwent prostate MRI from 2017 to 2021 with known low-grade PCa (Gleason score 6) without prior treatment. Patient-level highest Prostate Imaging Reporting & Data System (PI-RADS®) score and pathologic diagnosis within 1 year after MRI were used to evaluate the diagnostic performance of prostate MRI in detecting clinically significant PCa (csPCa; Gleason score ≥ 7). The metrics AIR, CDR, and CDR adjusted for pathologic confirmation rate were calculated. Radiologist-level AIR-CDR plots were shown. Simulation AIR-CDR lines were created to assess the effects of different diagnostic performances of prostate MRI and the prevalence of csPCa. RESULTS: A total of 3,207 examinations were interpreted by 33 radiologists. Overall AIR, CDR, and CDR adjusted for pathologic confirmation rate at PI-RADS 3 to 5 (PI-RADS 4 and 5) were 51.7% (36.5%), 22.1% (18.8%), and 30.7% (24.6%), respectively. Radiologist-level AIR and CDR at PI-RADS 3 to 5 (PI-RADS 4 and 5) were in the 36.8% to 75.6% (21.9%-57.5%) range and the 16.3%-28.7% (10.9%-26.5%) range, respectively. In the simulation, changing parameters of diagnostic performance or csPCa prevalence shifted the AIR-CDR line. CONCLUSIONS: The authors propose CDR and AIR as performance metrics in prostate MRI and report reference performance values in patients with known low-grade PCa. There was variability in radiologist-level AIR and CDR. Combined use of AIR and CDR could provide meaningful feedback for radiologists to improve their performance by showing relative performance to other radiologists.

Cancer Detection Rate and Abnormal Interpretation Rate of Prostate MRI Performed for Clinical Suspicion of Prostate Cancer.

PURPOSE: To report cancer detection rate (CDR) and abnormal interpretation rate (AIR) in prostate MRI performed for clinical suspicion of prostate cancer (PCa). MATERIALS AND METHODS: This retrospective single-institution, three-center study included patients who underwent MRI for clinical suspicion of PCa between 2017 and 2021. Patients with known PCa were excluded. Patient-level Prostate Imaging-Reporting and Data System (PI-RADS) score was extracted from the radiology report. AIR was defined as number of abnormal MRI (PI-RADS score 3-5) / total number of MRIs. CDR was defined as number of clinically significant PCa (csPCa: Gleason score ≥7) detected at abnormal MRI / total number of MRI. AIR, CDR, and CDR adjusted for pathology confirmation rate were calculated for each of three centers and pre-MRI biopsy status (biopsy-naive and previous negative biopsy). RESULTS: A total of 9,686 examinations (8,643 unique patients) were included. AIR, CDR, and CDR adjusted for pathology confirmation rate were 45.4%, 23.8%, and 27.6% for center I; 47.2%, 20.0%, and 22.8% for center II; and 42.3%, 27.2%, and 30.1% for center III, respectively. Pathology confirmation rate ranged from 81.6% to 88.0% across three centers. AIR and CDR for biopsy-naive patients were 45.5% to 52.6% and 24.2% to 33.5% across three centers, respectively, and those for previous negative biopsy were 27.2% to 39.8% and 11.7% to 14.2% across three centers, respectively. CONCLUSION: We reported CDR and AIR in prostate MRI for clinical suspicion of PCa. CDR needs to be adjusted for pathology confirmation rate and pre-MRI biopsy status for interfacility comparison.

Decreased prostate MRI cancer detection rate due to moderate to severe susceptibility artifacts from hip prosthesis.

OBJECTIVES: To evaluate the impact of susceptibility artifacts from hip prosthesis on cancer detection rate (CDR) in prostate MRI. MATERIALS AND METHODS: This three-center retrospective study included prostate MRI studies for patients without known prostate cancer between 2017 and 2021. Exams with hip prosthesis were searched on MRI reports. The degree of susceptibility artifact on diffusion-weighted images was retrospectively categorized into mild, moderate, and severe (> 66%, 33-66%, and < 33% of the prostate volume are evaluable) by blind reviewers. CDR was defined as the number of exams with Gleason score ≥7 detected by MRI (PI-RADS ≥3) divided by the total number of exams. For each artifact grade, control exams without hip prosthesis were matched (1:6 match), and CDR was compared. The degree of CDR reduction was evaluated with ratio, and influential factors were evaluated by expanding the equation. RESULTS: Hip arthroplasty was present in 548 (4.8%) of the 11,319 MRI exams. CDR of the cases and matched control exams for each artifact grade were as follows: mild (n = 238), 0.27 vs 0.25, CDR ratio = 1.09 [95% CI: 0.87-1.37]; moderate (n = 143), 0.18 vs 0.27, CDR ratio = 0.67 [95% CI: 0.46-0.96]; severe (n = 167), 0.22 vs 0.28, CDR ratio = 0.80 [95% CI: 0.59-1.08]. When moderate and severe artifact grades were combined, CDR ratio was 0.74 [95% CI: 0.58-0.93]. CDR reduction was mostly attributed to the increased frequency of PI-RADS 1-2. CONCLUSION: With moderate to severe susceptibility artifacts from hip prosthesis, CDR was decreased to 74% compared to the matched control. CLINICAL RELEVANCE STATEMENT: Moderate to severe susceptibility artifacts from hip prosthesis may cause a non-negligible CDR reduction in prostate MRI. Expanding indications for systematic prostate biopsy may be considered when PI-RADS 1-2 was assigned. KEY POINTS: • We proposed cancer detection rate as a diagnostic performance metric in prostate MRI. • With moderate to severe susceptibility artifacts secondary to hip arthroplasty, cancer detection rate decreased to 74% compared to the matched control. • Expanding indications for systematic prostate biopsy may be considered when PI-RADS 1-2 is assigned.

ACR Appropriateness Criteria® Post-Treatment Follow-up of Prostate Cancer: 2022 Update.

Prostate cancer has a wide spectrum ranging between low-grade localized disease and castrate-resistant metastatic disease. Although whole gland and systematic therapies result in cure in the majority of patients, recurrent and metastatic prostate cancer can still occur. Imaging approaches including anatomic, functional, and molecular modalities are continuously expanding. Currently, recurrent and metastatic prostate cancer is grouped in three major categories: 1) Clinical concern for residual or recurrent disease after radical prostatectomy, 2) Clinical concern for residual or recurrent disease after nonsurgical local and pelvic treatments, and 3) Metastatic prostate cancer treated by systemic therapy (androgen deprivation therapy, chemotherapy, immunotherapy). This document is a review of the current literature regarding imaging in these settings and the resulting recommendations for imaging. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Impact of measurement method on interobserver variability of apparent diffusion coefficient of lesions in prostate MRI.

PURPOSE: To compare the inter-observer variability of apparent diffusion coefficient (ADC) values of prostate lesions measured by 2D-region of interest (ROI) with and without specific measurement instruction. METHODS: Forty lesions in 40 patients who underwent prostate MR followed by targeted prostate biopsy were evaluated. A multi-reader study (10 readers) was performed to assess the agreement of ADC values between 2D-ROI without specific instruction and 2D-ROI with specific instruction to place a 9-pixel size 2D-ROI covering the lowest ADC area. The computer script generated multiple overlapping 9-pixel 2D-ROIs within a 3D-ROI encompassing the entire lesion placed by a single reader. The lowest mean ADC values from each 2D-small-ROI were used as reference values. Inter-observer agreement was assessed using the Bland-Altman plot. Intraclass correlation coefficient (ICC) was assessed between ADC values measured by 10 readers and the computer-calculated reference values. RESULTS: Ten lesions were benign, 6 were Gleason score 6 prostate carcinoma (PCa), and 24 were clinically significant PCa. The mean±SD ADC reference value by 9-pixel-ROI was 733 ± 186 (10-6 mm2/s). The 95% limits of agreement of ADC values among readers were better with specific instruction (±112) than those without (±205). ICC between reader-measured ADC values and computer-calculated reference values ranged from 0.736-0.949 with specific instruction and 0.349-0.919 without specific instruction. CONCLUSION: Interobserver agreement of ADC values can be improved by indicating a measurement method (use of a specific ROI size covering the lowest ADC area).

Magnetic resonance imaging (MRI) helps differentiate renal cell carcinoma with sarcomatoid differentiation from renal cell carcinoma without sarcomatoid differentiation.

PURPOSE: The aim of the present study is to identify predictive imaging findings and construct a diagnostic model for differentiating renal cell carcinoma (RCC) with and without sarcomatoid dedifferentiation (sRCC and non-sRCC). METHODS: This study is a single-center retrospective study. All patients had magnetic resonance imaging (MRI) with gradient-echo T1-weighted images, single-shot T2-weighted images (T2WI), and enhanced nephrographic phase images. Forty pathologically confirmed sRCCs and 80 non-sRCCs were included in this study. Control cases were selected by matching the tumor diameter and the year of MRI. Two radiologists independently evaluated the following findings: growth pattern, presence of low-intensity area on T2WI in the tumor (T2LIA), presence of non-enhancing area, local tumor stage, and presence of regional lymphadenopathy. Two radiologists measured the diameter of the tumor, T2LIA, and the non-enhancing area. Multivariable logistic regression analysis was used to identify independent predictive factors for differentiating sRCC from non-sRCC. Selected variables were entered in the logistic regression model, and the area under the curve (AUC) was calculated for each reader with 95% confidence intervals (CIs). RESULTS: Larger T2LIA-to-tumor diameter ratio, regional lymphadenopathy, and local tumor stage 4 were associated with sRCC, and selected for the subsequent construction of a logistic regression model. With this model, the AUCs were 0.76 (95% CI, 0.66-0.85) and 0.70 (95% CI, 0.59-0.81) for prediction of sRCC. CONCLUSION: In conclusion, larger T2LIA-to-tumor diameter ratio, regional lymphadenopathy, and local tumor stage 4 are predictive findings of sRCC. As a result, the model constructed using these findings demonstrated a moderate degree of diagnostic accuracy.

Repeatability and Reproducibility Assessment of the Apparent Diffusion Coefficient in the Prostate: A Trial of the ECOG-ACRIN Research Group (ACRIN 6701).

BACKGROUND: Uncertainty regarding the reproducibility of the apparent diffusion coefficient (ADC) hampers the use of quantitative diffusion-weighted imaging (DWI) in evaluation of the prostate with magnetic resonance imaging MRI. The quantitative imaging biomarkers alliance (QIBA) profile for quantitative DWI claims a within-subject coefficient of variation (wCV) for prostate lesion ADC of 0.17. Improved understanding of ADC reproducibility would aid the use of quantitative diffusion in prostate MRI evaluation. PURPOSE: Evaluation of the repeatability (same-day) and reproducibility (multi-day) of whole-prostate and focal-lesion ADC assessment in a multi-site setting. STUDY TYPE: Prospective multi-institutional. SUBJECTS: Twenty-nine males, ages 53 to 80 (median 63) years, following diagnosis of prostate cancer, 10 with focal lesions. FIELD STRENGTH/SEQUENCE: 3T, single-shot spin-echo diffusion-weighted echo-planar sequence with four b-values. ASSESSMENT: Sites qualified for the study using an ice-water phantom with known ADC. Readers performed DWI analyses at visit 1 ("V1") and visit 2 ("V2," 2-14 days after V1), where V2 comprised scans before ("V2pre") and after ("V2post") a "coffee-break" interval with subject removal and repositioning. A single reader segmented the whole prostate. Two readers separately placed region-of-interests for focal lesions. STATISTICAL TESTS: Reproducibility and repeatability coefficients for whole prostate and focal lesions derived from median pixel ADC. We estimated the wCV and 95% confidence interval using a variance stabilizing transformation and assessed interreader reliability of focal lesion ADC using the intraclass correlation coefficient (ICC). RESULTS: The ADC biases from b0 -b600 and b0 -b800 phantom scans averaged 1.32% and 1.44%, respectively; mean b-value dependence was 0.188%. Repeatability and reproducibility of whole prostate median pixel ADC both yielded wCVs of 0.033 (N = 29). In 10 subjects with an evaluable focal lesion, the individual reader wCVs were 0.148 and 0.074 (repeatability) and 0.137 and 0.078 (reproducibility). All time points demonstrated good to excellent interreader reliability for focal lesion ADC (ICCV1  = 0.89; ICCV2pre  = 0.76; ICCV2post  = 0.94). DATA CONCLUSION: This study met the QIBA claim for prostate ADC. Test-retest repeatability and multi-day reproducibility were largely equivalent. Interreader reliability for focal lesion ADC was high across time points. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2 TOC CATEGORY: Pelvis.

Long-Term Risk of Clinical Progression Utilizing Magnetic Resonance Imaging Findings of Locally Recurrent Prostate Cancer in Patients with Biochemical Recurrence following Radical Prostatectomy.

PURPOSE: Our goal was to evaluate the long-term prognostic value of magnetic resonance imaging of the prostatectomy bed in patients with biochemical recurrence after radical prostatectomy for prostate cancer. MATERIALS AND METHODS: Men with biochemical recurrence after radical prostatectomy who were studied by prostatectomy bed magnetic resonance imaging for suspected local recurrence were retrospectively evaluated. Locally recurrent tumors were noted and measured from imaging reports. Patients with nodal/bone lesions at the time of imaging were excluded. Kaplan-Meier and Cox regression analyses were used to assess systemic progression-free and prostate cancer-specific survival. RESULTS: A total of 896 men were enrolled and the imaging positive and negative groups for local recurrent tumor consisted of 441 and 455 men, respectively. On univariate analysis, preoperative prostate specific antigen (p=0.02), clinical tumor stage (p=0.006), pathological Gleason score from prostatectomy (p=0.02), subsequent salvage radiotherapy (p <0.001), biochemical recurrence to magnetic resonance imaging time interval (p <0.001), age at magnetic resonance imaging (p=0.047) and prostate specific antigen at magnetic resonance imaging (p <0.001) were significantly different between magnetic resonance imaging positive and negative groups. Patients with negative magnetic resonance imaging results had worse systemic progression-free survival rates (p=0.025) and better prostate cancer-specific survival (p=0.016) than those with recurrence. Larger lesion size significantly increased risk of prostate cancer death (hazard ratio: 1.07; p <0.001). On multivariable analysis, pathological Gleason scores ≥7 were independent prognostic factors of systemic progression (p <0.05). CONCLUSIONS: Prostatectomy bed magnetic resonance imaging provides long-term prognostic information for the evaluation of patients with biochemical recurrence after prostatectomy. Post-prostatectomy patients with recurrent lesions on imaging had longer progression-free survival but shorter prostate cancer-specific survival compared to those without lesions. Additionally, those with larger lesions were associated with poorer cancer-specific survival.

Feasibility of Dual-Energy Computed Tomography Imaging of Gadolinium-Based Contrast Agents and Its Application in Computed Tomography Cystography: An Exploratory Study to Assess an Alternative Option When Iodinated Contrast Agents Are Contraindicated.

OBJECTIVE: The aim of this study was to compare the contrast enhancement differences between gadolinium-based and iodine-based contrast agents at different single-energy tube potentials and dual-energy-based virtual monochromatic energies. In addition, we describe the application of a gadolinium-based contrast agent in computed tomography (CT) cystography for a patient with contraindications to iodine. METHODS: A phantom study was performed using 3 iodine samples (concentrations: 5, 10, and 15 mgI/mL) and 3 gadolinium samples (concentrations: 3.3, 6.6, and 9.9 mgGd/mL). The prepared phantom was scanned by a dual-energy CT (DECT) at 80, 100, 120, and 140 kV in the single-energy mode and at 100/Sn140 kV in the dual-energy mode. Virtual monoenergetic images (VMIs) at 50 keV were generated from the DECT scan. In addition, a DECT cystogram was performed using a gadolinium-based contrast agent in a patient with contraindications to iodinated contrast. RESULTS: Strong linear correlations between mean signal of contrast enhancement and mass concentration were found for both iodine and gadolinium samples across all single-energy CT (SECT) and DECT scan conditions. The VMI at 50 keV provided the highest contrast enhancement for both types of contrast samples at each concentration level, and single-energy CT scans at low-energy beams showed higher contrast enhancement than higher beam energies. In addition, the contrast enhancement for pure gadolinium solution was constantly higher than pure iodine solution at an identical mass concentration level. The DECT cystogram was performed with excellent technical success. The urinary bladder was appropriately distended with intravesical contrast measuring 606 Hounsfield units and no evidence of bladder leak or fistula. CONCLUSIONS: Imaging of gadolinium-based contrast agents is improved using a DECT technique, with VMI at 50 keV providing the highest contrast enhancement among our tested parameters. Dual-energy CT cystography using a gadolinium-based agent can be a safe and effective alternative when iodinated agents are contraindicated.

ACR Appropriateness Criteria® Post-Treatment Surveillance of Bladder Cancer: 2021 Update.

Urothelial cancer is the second most common cancer, and cause of cancer death, related to the genitourinary tract. The goals of surveillance imaging after the treatment of urothelial cancer of the urinary bladder are to detect new or previously undetected urothelial tumors, to identify metastatic disease, and to evaluate for complications of therapy. For surveillance, patients can be stratified into one of three groups: 1) nonmuscle invasive bladder cancer with no symptoms or additional risk factors; 2) nonmuscle invasive bladder cancer with symptoms or additional risk factors; and 3) muscle invasive bladder cancer. This document is a review of the current literature for urothelial cancer and resulting recommendations for surveillance imaging. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

The prognostic value, sensitivity, and specificity of multiparametric magnetic resonance imaging before salvage radiotherapy for prostate cancer.

AIM: To determine the operational characteristics of pelvic magnetic resonance imaging (MRI) prior to salvage radiation therapy (SRT) for biochemically recurrent prostate cancer following radical prostatectomy. METHODS AND MATERIALS: We reviewed the medical records of 386 patients who underwent MRI prior to SRT. We assessed associations of pre-SRT MRI findings with biochemical recurrence (BCR), distant metastasis (DM), prostate cancer-specific mortality (PCSM), and salvage androgen deprivation therapy (ADT) use following SRT. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of MRI for detecting local recurrence were also calculated. RESULTS: Pre-SRT MRI was positive for local recurrence in 216 patients (56%), indeterminate in 46 (12%), and negative in 124 (32%). On univariate analysis, BCR following SRT was significantly less likely for patients with positive (HR: 0.58, 95% CI: 0.42-0.8) or indeterminate (HR: 0.6: 0.36-1) MRI findings, compared to patients with negative imaging (p = 0.003). These associations remained significant on multivariate analysis (p < 0.05) and across pre-SRT PSA groups. For the entire cohort, the sensitivity of MRI for local recurrence was 61.0% (53.5-68.1%), specificity 60.0% (44.3-73.0%), PPV 86.1% (78.9-91.5%) and NPV 27.6% (19.0-37.5%). Sensitivity of MRI was better in men with higher pre-SRT PSA (80.0% for PSA > 1.0), and specificity was improved with lower pre-SRT PSA (73.9% for PSA 0.1-0.5). CONCLUSIONS: Positive or indeterminate MRI findings prior to SRT were associated with improved biochemical control following SRT, across PSA levels. The sensitivity and specificity of MRI for local recurrence were 61% and 58.7%, respectively.

Prostate MRI characteristics in patients with inflammatory bowel disease.

PURPOSE: Previous studies have indicated an increased risk of prostate carcinoma (PCa) associated with inflammatory bowel disease (IBD). Prostate MRI of IBD patients could be expected to show a mixture of inflammation as well as higher than normal rates of PCa, which could impact interpretation and MRI performance. The purpose of this study is to evaluate the characteristics of prostate MRI in patients with IBD. METHODS: 3140 patients with prostate MRI were evaluated. Coexisting IBD, PI-RADS score, and pathological results of prostate lesions (clinically significant PCa [csPCa]: Gleason score [GS] 7+, Non-csPCa: benign or GS 6) were assessed. The distribution of PI-RADS scoring and pathological result was assessed by chi-square test. RESULTS: 71 patients had IBD (IBD group), whereas the remaining 3069 patients did not (Non-IBD group). The proportion of abnormal MRI (PI-RADS 3, 4 or 5) was 51 % (36/71) in IBD group and 47 % (1436/3069) in Non-IBD groups (p = 0.513). Total of 1285 patients underwent biopsy or prostatectomy. The proportion of csPCa at pathology was 35 % (12/34) in IBD group and 56 % (699/1251) in non-IBD groups (p = 0.017). The positive predictive value of abnormal MRI for csPCa was significantly lower in IBD group (39 %, 19/31) compared to Non-IBD group (63 %, 657/1047) (p = 0.007). CONCLUSION: The proportion of csPCa at pathology and positive predictive value of abnormal MR for csPCa were lower in patients with IBD group compared to Non-IBD group.

ACR Appropriateness Criteria® Recurrent Lower Urinary Tract Infections in Females.

Urinary tract infections (UTIs) in women are common, with an overall lifetime risk over >50%. UTIs are considered recurrent when they follow complete clinical resolution of a previous UTI and are usually defined as at least three episodes of infection within the preceding 12 months. An uncomplicated UTI is classified as a UTI without structural or functional abnormalities of the urinary tract and without relevant comorbidities. Complicated UTIs are those occurring in patients with underlying structural or medical problems. In women with recurrent uncomplicated UTIs, cystoscopy and imaging are not routinely used. In women suspected of having a recurrent complicated UTI, cystoscopy and imaging should be considered. CT urography or MR urography are usually appropriate for the evaluation of recurrent complicated lower urinary tract infections or for women who are nonresponders to conventional therapy, develop frequent reinfections or relapses, or have known underlying risk factors. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Hemosiderin deposition in papillary renal cell carcinoma and its potential to mask enhancement on MRI: analysis of 110 cases.

OBJECTIVES: To evaluate the relationship between imperceptible T1 enhancement of papillary renal cell carcinoma (pRCC) on MR and intratumoral hemosiderin deposition. METHODS: One hundred ten pRCCs (≤ 7 cm) were evaluated by MR with in- and opposed-phase spoiled gradient echo (GRE) and T1-weighted spoiled GRE with fat suppression before and after contrast. Hemosiderin deposition was assessed by SIindex and Dindex on in- and opposed-phase images. SIindex and Dindex are calculated as (SIin - SIopp)/(SIin) × 100, where SIin and SIopp are tumor signal intensities on in- and opposed-phase images and (Din)/(Dopp), where Din and Dopp are tumor diameters on in- and opposed-phase images, respectively. The degree of tumor enhancement was classified as grade 1 (no), grade 2 (subtle), or grade 3 (definite). Tumor enhancement on CT was assessed when available. RESULTS: Five (5%), 10 (9%), and 95 (86%) tumors were categorized as grades 1, 2, and 3 enhancement, respectively. The mean SIindex was - 33.9, - 25.3, and 1.00, whereas the mean Dindex was 1.26, 1.05, and 1.00 in tumors with grades 1, 2, and 3 enhancement, respectively. Tumors with grade 1 enhancement had significantly lower SIindex (p = 0.001) and higher Dindex (p = 0.005) than those with grade 3 enhancement. Among six tumors with grade 1 or 2 enhancement and available CT, four tumors showed > 20 HU enhancement. CONCLUSIONS: pRCC with no subjective enhancement on contrast-enhanced MR showed hemosiderin deposition evident by lower SIindex and higher Dindex. Hemosiderin deposition might mask the tumor enhancement on MR. KEY POINTS: • 5% of papillary renal cell carcinoma showed imperceptible enhancement on contrast-enhanced MR. • Hemosiderin deposition in papillary renal cell carcinoma might mask the tumor enhancement on contrast-enhanced MR due to T2/T2*-shortening effects. • A renal lesion with extensive hemosiderin deposition but no perceptible enhancement on MR should be considered suspicious for papillary renal cell carcinoma.

Variability of the Positive Predictive Value of PI-RADS for Prostate MRI across 26 Centers: Experience of the Society of Abdominal Radiology Prostate Cancer Disease-focused Panel.

Background Prostate MRI is used widely in clinical care for guiding tissue sampling, active surveillance, and staging. The Prostate Imaging Reporting and Data System (PI-RADS) helps provide a standardized probabilistic approach for identifying clinically significant prostate cancer. Despite widespread use, the variability in performance of prostate MRI across practices remains unknown. Purpose To estimate the positive predictive value (PPV) of PI-RADS for the detection of high-grade prostate cancer across imaging centers. Materials and Methods This retrospective cross-sectional study was compliant with the HIPAA. Twenty-six centers with members in the Society of Abdominal Radiology Prostate Cancer Disease-focused Panel submitted data from men with suspected or biopsy-proven untreated prostate cancer. MRI scans were obtained between January 2015 and April 2018. This was followed with targeted biopsy. Only men with at least one MRI lesion assigned a PI-RADS score of 2-5 were included. Outcome was prostate cancer with Gleason score (GS) greater than or equal to 3+4 (International Society of Urological Pathology grade group ≥2). A mixed-model logistic regression with institution and individuals as random effects was used to estimate overall PPVs. The variability of observed PPV of PI-RADS across imaging centers was described by using the median and interquartile range. Results The authors evaluated 3449 men (mean age, 65 years ± 8 [standard deviation]) with 5082 lesions. Biopsy results showed 1698 cancers with GS greater than or equal to 3+4 (International Society of Urological Pathology grade group ≥2) in 2082 men. Across all centers, the estimated PPV was 35% (95% confidence interval [CI]: 27%, 43%) for a PI-RADS score greater than or equal to 3 and 49% (95% CI: 40%, 58%) for a PI-RADS score greater than or equal to 4. The interquartile ranges of PPV at these same PI-RADS score thresholds were 27%-44% and 27%-48%, respectively. Conclusion The positive predictive value of the Prostate Imaging and Reporting Data System was low and varied widely across centers. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Milot in this issue.

Current Imaging Techniques for and Imaging Spectrum of Prostate Cancer Recurrence and Metastasis: A Pictorial Review.

Relapsing level of prostate-specific antigen (PSA) after initial curative-intent local therapy for organ-confined prostate cancer is often the first sign of recurrence. However, PSA level recurrence does not enable accurate differentiation of locally recurrent tumor from metastatic disease or a combination of both. Metastatic prostate cancer most frequently involves bones and lymph nodes, followed by other organs such as the liver, lung, pleura, adrenal gland, ureter, peritoneum, penis, testis, and meninges. Conventional imaging including CT and bone scintigraphy has long been the standard of care but has limited sensitivity in depicting early local recurrence or metastatic disease. Multiparametric MRI has been shown to be more sensitive in detecting locally recurrent tumor in the prostatectomy bed as well as in situ recurrence in a prostate gland that has been treated with radiation therapy or thermal ablation. In addition, lesions detected with multiparametric MRI may be amenable to targeted biopsy for definitive diagnosis of recurrence. PET/CT or PET/MRI using the U.S. Food and Drug Administration (FDA)-approved tracers carbon 11 choline or fluorine 18 fluciclovine has demonstrated markedly increased sensitivity and specificity for diagnosis of early metastatic disease such as small-volume lymph node metastasis, as have a range of investigational gallium 68 prostate-specific membrane antigen (PSMA) radioactive PET tracers. With recent advances in imaging modalities and techniques, more accurate early detection, localization, and characterization of recurrent prostate cancer have become possible. The authors present a contemporary review of the strengths and limitations of conventional and advanced imaging modalities in evaluation of patients with recurrent prostate cancer and a systematic review of the clinical and imaging features of locally recurrent and metastatic disease.©RSNA, 2020See discussion on this article by Barwick and Castellucci.