A concurrent, deep learning-based computer-aided detection system for prostate multiparametric MRI: a performance study involving experienced and less-experienced radiologists.

OBJECTIVES: To evaluate the effect of a deep learning-based computer-aided diagnosis (DL-CAD) system on experienced and less-experienced radiologists in reading prostate mpMRI. METHODS: In this retrospective, multi-reader multi-case study, a consecutive set of 184 patients examined between 01/2018 and 08/2019 were enrolled. Ground truth was combined targeted and 12-core systematic transrectal ultrasound-guided biopsy. Four radiologists, two experienced and two less-experienced, evaluated each case twice, once without (DL-CAD-) and once assisted by DL-CAD (DL-CAD+). ROC analysis, sensitivities, specificities, PPV and NPV were calculated to compare the diagnostic accuracy for the diagnosis of prostate cancer (PCa) between the two groups (DL-CAD- vs. DL-CAD+). Spearman's correlation coefficients were evaluated to assess the relationship between PI-RADS category and Gleason score (GS). Also, the median reading times were compared for the two reading groups. RESULTS: In total, 172 patients were included in the final analysis. With DL-CAD assistance, the overall AUC of the less-experienced radiologists increased significantly from 0.66 to 0.80 (p = 0.001; cutoff ISUP GG ≥ 1) and from 0.68 to 0.80 (p = 0.002; cutoff ISUP GG ≥ 2). Experienced radiologists showed an AUC increase from 0.81 to 0.86 (p = 0.146; cutoff ISUP GG ≥ 1) and from 0.81 to 0.84 (p = 0.433; cutoff ISUP GG ≥ 2). Furthermore, the correlation between PI-RADS category and GS improved significantly in the DL-CAD + group (0.45 vs. 0.57; p = 0.03), while the median reading time was reduced from 157 to 150 s (p = 0.023). CONCLUSIONS: DL-CAD assistance increased the mean detection performance, with the most significant benefit for the less-experienced radiologist; with the help of DL-CAD less-experienced radiologists reached performances comparable to that of experienced radiologists. KEY POINTS: • DL-CAD used as a concurrent reading aid helps radiologists to distinguish between benign and cancerous lesions in prostate MRI. • With the help of DL-CAD, less-experienced radiologists may achieve detection performances comparable to that of experienced radiologists. • DL-CAD assistance increases the correlation between PI-RADS category and cancer grade.

Emergency Presentations for Dizziness-Radiological Findings, Final Diagnoses, and Mortality.

Background: Dizziness is a frequent presentation in patients presenting to emergency departments (EDs), often triggering extensive work-up, including neuroimaging. Therefore, gathering knowledge on final diagnoses and outcomes is important. We aimed to describe the incidence of dizziness as primary or secondary complaint, to list final diagnoses, and to determine the use and yield of neuroimaging and outcomes in these patients. Methods: Secondary analysis of two observational cohort studies, including all patients presenting to the ED of the University Hospital of Basel from 30th January 2017-19th February 2017 and from 18th March 2019-20th May 2019. Baseline demographics, Emergency Severity Index (ESI), hospitalization, admission to Intensive Care Units (ICUs), and mortality were extracted from the electronic health record database. At presentation, patients underwent a structured interview about their symptoms, defining their primary and secondary complaints. Neuroimaging results were obtained from the picture archiving and communication system (PACS). Patients were categorized into three non-overlapping groups: dizziness as primary complaint, dizziness as secondary complaint, and absence of dizziness. Results: Of 10076 presentations, 232 (2.3%) indicated dizziness as their primary and 984 (9.8%) as their secondary complaint. In dizziness as primary complaint, the three (out of 73 main conditions defined) main diagnoses were nonspecific dizziness (47, 20.3%), dysfunction of the peripheral vestibular system (37, 15.9%), as well as somatization, depression, and anxiety (20, 8.6%). 104 of 232 patients (44.8%) underwent neuroimaging, with relevant findings in 5 (4.8%). In dizziness as primary complaint 30-day mortality was 0%. Conclusion: Work-up for dizziness in emergency presentations has to consider a broad differential diagnosis, but due to the low yield, it should include neuroimaging only in few and selected cases, particularly with additional neurological abnormalities. Presentation with primary dizziness carries a generally favorable prognosis lacking short-term mortality. .

Building Large-Scale Quantitative Imaging Databases with Multi-Scale Deep Reinforcement Learning: Initial Experience with Whole-Body Organ Volumetric Analyses.

To explore the feasibility of a fully automated workflow for whole-body volumetric analyses based on deep reinforcement learning (DRL) and to investigate the influence of contrast-phase (CP) and slice thickness (ST) on the calculated organ volume. This retrospective study included 431 multiphasic CT datasets-including three CP and two ST reconstructions for abdominal organs-totaling 10,508 organ volumes (10,344 abdominal organ volumes: liver, spleen, and kidneys, 164 lung volumes). Whole-body organ volumes were determined using multi-scale DRL for 3D anatomical landmark detection and 3D organ segmentation. Total processing time for all volumes and mean calculation time per case were recorded. Repeated measures analyses of variance (ANOVA) were conducted to test for robustness considering CP and ST. The algorithm calculated organ volumes for the liver, spleen, and right and left kidney (mean volumes in milliliter (interquartile range), portal venous CP, 5 mm ST: 1868.6 (1426.9, 2157.8), 350.19 (45.46, 395.26), 186.30 (147.05, 214.99) and 181.91 (143.22, 210.35), respectively), and for the right and left lung (2363.1 (1746.3, 2851.3) and 1950.9 (1335.2, 2414.2)). We found no statistically significant effects of the variable contrast phase or the variable slice thickness on the organ volumes. Mean computational time per case was 10 seconds. The evaluated approach, using state-of-the art DRL, enables a fast processing of substantial amounts irrespective of CP and ST, allowing building up organ-specific volumetric databases. The thus derived volumes may serve as reference for quantitative imaging follow-up.

Novices in MRI-targeted prostate biopsy benefit from structured reporting of MRI findings.

PURPOSE: The aim of this study was to investigate whether structured reports (SRs) of prostate MRI results are more suitable than non-structured reports (NSRs) for promoting the more accurate assessment of the location of a single prostate cancer lesion by novices in MRI-targeted biopsy. METHODS: 50 NSRs and 50 SRs describing a single prostatic lesion were presented to 5 novices in MRI-targeted biopsy. The participants were asked to plot the tumor location in a two-dimensional prostate diagram and to answer a questionnaire on the quality of the reports. The accuracy of the plotted tumor position was evaluated with a validated 30-point scoring system that distinguished between "major" and "minor" mistakes. RESULTS: The overall mean score for the accuracy of the tumor plotting was significantly higher for SRs than for NSRs (26.4 vs. 20.7, p < 0.01). The mean numbers of major (1.4 vs. 0.48, p < 0.01) and minor (3.05 vs. 1.15, p < 0.01) mistakes were significantly higher for NSRs than for SRs. Compared with NSRs, SRs received significantly higher ratings for the perceived quality of the summary (4.0 vs. 2.4, p < 0.01) as well as for the overall satisfaction with the report (4.1 vs. 2.1, p < 0.01). CONCLUSION: Novices in MRI-targeted biopsy prefer structured reporting of prostate MRI as an information tool. SRs allow for a more accurate assessment of the location of single prostate cancer lesions. Therefore, structured reporting of prostate MRI may help to foster the learning process of novices in MRI-targeted biopsy.

High spatiotemporal resolution dynamic contrast-enhanced MRI improves the image-based discrimination of histopathology risk groups of peripheral zone prostate cancer: a supervised machine learning approach.

OBJECTIVE: To assess if adding perfusion information from dynamic contrast-enhanced (DCE MRI) acquisition schemes with high spatiotemporal resolution to T2w/DWI sequences as input features for a gradient boosting machine (GBM) machine learning (ML) classifier could better classify prostate cancer (PCa) risk groups than T2w/DWI sequences alone. MATERIALS AND METHODS: One hundred ninety patients (68 ± 9 years) were retrospectively evaluated at 3T MRI for clinical suspicion of PCa. Included were 201 peripheral zone (PZ) PCa lesions. Histopathological confirmation on fusion biopsy was matched with normal prostate parenchyma contralaterally. Biopsy results were grouped into benign tissue and low-, intermediate-, and high-risk groups (Gleason sum score 6, 7, and > 7, respectively). DCE MRI was performed using golden-angle radial sparse MRI. Perfusion maps (Ktrans, Kep, Ve), apparent diffusion coefficient (ADC), and absolute T2w signal intensity were determined and used as input features for building two ML models: GBM with/without perfusion maps. Areas under the receiver operating characteristic curve (AUC) values for correlated models were compared. RESULTS: For the classification of benign vs. malignant and intermediate- vs. high-grade PCa, perfusion information added relevant information (AUC values 1 vs. 0.953 and 0.909 vs. 0.700, p < 0.001 and p = 0.038), while no statistically significant effect was found for low- vs. intermediate- and high-grade PCa. CONCLUSION: Perfusion information from DCE MRI acquisition schemes with high spatiotemporal resolution to ML classifiers enables a superior risk stratification between benign and malignant and intermediate- and high-risk PCa in the PZ compared with classifiers based on T2w/DWI information alone. KEY POINTS: • In the recent guidelines, the role of DCE MRI has changed from a mandatory to recommended sequence. • DCE MRI acquisition schemes with high spatiotemporal resolution (e.g., GRASP) have been shown to improve the diagnostic performance compared with conventional DCE MRI sequences. • Using perfusion information acquired with GRASP in combination with ML classifiers significantly improved the prediction of benign vs. malignant and intermediate- vs. high-grade peripheral zone prostate cancer compared with non-contrast sequences.

Automated detection of pulmonary embolism in CT pulmonary angiograms using an AI-powered algorithm.

OBJECTIVES: To evaluate the performance of an AI-powered algorithm for the automatic detection of pulmonary embolism (PE) on chest computed tomography pulmonary angiograms (CTPAs) on a large dataset. METHODS: We retrospectively identified all CTPAs conducted at our institution in 2017 (n = 1499). Exams with clinical questions other than PE were excluded from the analysis (n = 34). The remaining exams were classified into positive (n = 232) and negative (n = 1233) for PE based on the final written reports, which defined the reference standard. The fully anonymized 1-mm series in soft tissue reconstruction served as input for the PE detection prototype algorithm that was based on a deep convolutional neural network comprising a Resnet architecture. It was trained and validated on 28,000 CTPAs acquired at other institutions. The result series were reviewed using a web-based feedback platform. Measures of diagnostic performance were calculated on a per patient and a per finding level. RESULTS: The algorithm correctly identified 215 of 232 exams positive for pulmonary embolism (sensitivity 92.7%; 95% confidence interval [CI] 88.3-95.5%) and 1178 of 1233 exams negative for pulmonary embolism (specificity 95.5%; 95% CI 94.2-96.6%). On a per finding level, 1174 of 1352 findings marked as embolus by the algorithm were true emboli. Most of the false positive findings were due to contrast agent-related flow artifacts, pulmonary veins, and lymph nodes. CONCLUSION: The AI prototype algorithm we tested has a high degree of diagnostic accuracy for the detection of PE on CTPAs. Sensitivity and specificity are balanced, which is a prerequisite for its clinical usefulness. KEY POINTS: • An AI-based prototype algorithm showed a high degree of diagnostic accuracy for the detection of pulmonary embolism on CTPAs. • It can therefore help clinicians to automatically prioritize exams with a high suspection of pulmonary embolism and serve as secondary reading tool. • By complementing traditional ways of worklist prioritization in radiology departments, this can speed up the diagnostic and therapeutic workup of patients with pulmonary embolism and help to avoid false negative calls.

Gamification of Electronic Learning in Radiology Education to Improve Diagnostic Confidence and Reduce Error Rates.

OBJECTIVE. The purpose of this study is to validate an electronic learning, or e-learning, concept featuring gamification elements, rapid case reading, and instant feedback. SUBJECTS AND METHODS. An e-learning concept was devised that offered game levels for the purpose of providing training in the detection of pneumothorax in 195 cases, with questions read in rapid succession and instant feedback provided for each case. The user's task was to locate the pneumothorax on chest radiographs and indicate its presence by clicking a mouse. The game level design included an entry test consisting of 15 cases, training levels with increasing difficulty that involved 150 cases, and a final test that including 30 cases (the 15 cases from the entry test plus 15 new cases). A total of 126 candidates were invited via e-mail to participate and were asked to complete a survey before and after playing the game, which is known as RapRad. The level of diagnostic confidence and the error rate before and after playing the game were compared using a Wilcoxon signed rank test. RESULTS. Fifty-nine of 126 participants (47%) responded to the first survey and finished the game. Of these 59 participants, 29 (49%) responded to the second survey after completing the game. Diagnostic confidence in pneumothorax detection improved significantly, from a mean (± SD) score of 4.3 ± 2.1 on the entry test to a final score of 7.3 ± 2.1 (p < 0.01) after playing RapRad, with the score measured on a 10-point scale, with 10 denoting the highest possible score. Of the participants, 93% indicated that they would use the game for learning purposes again, and 87% indicated that they had fun using RapRad (7% had a neutral response and 6% had a negative response). The error rate (i.e., the number of failed attempts to answer a question correctly) significantly decreased from 39% for the entry test to 22% for the final test (p < 0.01). CONCLUSION. Our e-learning concept is capable of improving diagnostic confidence, reducing error rates in training pneumothorax detection, and offering fun in interaction with the platform.

Compressed Sensing Radial Sampling MRI of Prostate Perfusion: Utility for Detection of Prostate Cancer.

Purpose To investigate the diagnostic performance of a dual-parameter approach by combining either volumetric interpolated breath-hold examination (VIBE)- or golden-angle radial sparse parallel (GRASP)-derived dynamic contrast agent-enhanced (DCE) MRI with established diffusion-weighted imaging (DWI) compared with traditional single-parameter evaluations on the basis of DWI alone. Materials and Methods Ninety-four male participants (66 years ± 7 [standard deviation]) were prospectively evaluated at 3.0-T MRI for clinical suspicion of prostate cancer. Included were 101 peripheral zone prostate cancer lesions. Histopathologic confirmation at MRI transrectal US fusion biopsy was matched with normal contralateral prostate parenchyma. MRI was performed with diffusion weighting and DCE by using GRASP (temporal resolution, 2.5 seconds) or VIBE (temporal resolution, 10 seconds). Perfusion (influx forward volume transfer constant [Ktrans] and rate constant [Kep]) and apparent diffusion coefficient (ADC) parameters were determined by tumor volume analysis. Areas under the receiver operating characteristic curve were compared for both sequences. Results Evaluated were 101 prostate cancer lesions (GRASP, 61 lesions; VIBE, 40 lesions). In a combined analysis, diffusion and perfusion parameters ADC with Ktrans or Kep acquired with GRASP had higher diagnostic performance compared with diffusion characteristics alone (area under the curve, 0.97 ± 0.02 [standard error] vs 0.93 ± 0.03; P < .006 and .021, respectively), whereas ADC with perfusion parameters acquired with VIBE had no additional benefit (area under the curve, 0.94 ± 0.03 vs 0.93 ± 0.04; P = .18and .50, respectively, for combination of ADC with Ktrans and Kep). Conclusion If used in a dual-parameter model, incorporating diffusion and perfusion characteristics, the golden-angle radial sparse parallel acquisition technique improves the diagnostic performance of multiparametric MRI examinations of the prostate. This effect could not be observed combining diffusing with perfusion parameters acquired with volumetric interpolated breath-hold examination. © RSNA, 2018.

Gadoxetate Disodium versus Gadoterate Meglumine: Quantitative Respiratory and Hemodynamic Metrics by Using Compressed-Sensing MRI.

Background Gadoxetate disodium has been associated with various respiratory irregularities at arterial imaging MRI. Purpose To measure the relationship between gadolinium-based contrast agent administration and irregularities by comparing gadoxetate disodium and gadoterate meglumine at free breathing. Materials and Methods This prospective observational cohort study (January 2015 to May 2017) included consecutive abdominal MRI performed with either gadoxetate disodium or gadoterate meglumine enhancement. Participants underwent dynamic imaging by using the golden-angle radial sparse parallel sequence at free breathing. The quantitative assessment evaluated the aortic contrast enhancement, the respiratory hepatic translation, and the k-space-derived respiratory pattern. Analyses of variance compared hemodynamic metrics, respiratory-induced hepatic motion, and respiratory parameters before and after respiratory gating. Results A total of 497 abdominal MRI examinations were included. Of these, 338 participants were administered gadoxetate disodium (mean age, 59 years ± 15; 153 women) and 159 participants were administered gadoterate meglumine (mean age, 59 years ± 17; 85 women). The arterial bolus of gadoxetate disodium arrived later than gadoterate meglumine (19.7 vs 16.3 seconds, respectively; P < .001). Evaluation of the hepatic respiratory translation showed respiratory motion occurring in 70.7% (239 of 338) of participants who underwent gadoxetate-enhanced examinations and in 28.9% (46 of 159) of participants who underwent gadoterate-enhanced examinations (P < .001). The duration of motion irregularities was longer for gadoxetate than for gadoterate (19.2 seconds vs 17.2 seconds, respectively) and the motion irregularities were more severe (P < .001). Both the respiratory frequency and amplitude were shorter for participants administered gadoxetate from the prebolus phase to the late arterial phase compared with gadoterate (P < .001). Conclusion The administration of two different gadolinium-based contrast agents, gadoxetate and gadoterate, at free-breathing conditions potentially leads to respiratory irregularities with differing intensity and onset. © RSNA, 2019 Online supplemental material is available for this article.

Comparison of image quality and radiation dose between split-filter dual-energy images and single-energy images in single-source abdominal CT.

OBJECTIVES: To compare image quality and radiation dose of abdominal split-filter dual-energy CT (SF-DECT) combined with monoenergetic imaging to single-energy CT (SECT) with automatic tube voltage selection (ATVS). METHODS: Two-hundred single-source abdominal CT scans were performed as SECT with ATVS (n = 100) and SF-DECT (n = 100). SF-DECT scans were reconstructed and subdivided into composed images (SF-CI) and monoenergetic images at 55 keV (SF-MI). Objective and subjective image quality were compared among single-energy images (SEI), SF-CI and SF-MI. CNR and FOM were separately calculated for the liver (e.g. CNRliv) and the portal vein (CNRpv). Radiation dose was compared using size-specific dose estimate (SSDE). Results of the three groups were compared using non-parametric tests. RESULTS: Image noise of SF-CI was 18% lower compared to SEI and 48% lower compared to SF-MI (p < 0.001). Composed images yielded higher CNRliv over single-energy images (23.4 vs. 20.9; p < 0.001), whereas CNRpv was significantly lower (3.5 vs. 5.2; p < 0.001). Monoenergetic images overcame this inferiority in CNRpv and achieved similar results compared to single-energy images (5.1 vs. 5.2; p > 0.628). Subjective sharpness was equal between single-energy and monoenergetic images and diagnostic confidence was equal between single-energy and composed images. FOMliv was highest for SF-CI. FOMpv was equal for SEI and SF-MI (p = 0.78). SSDE was significant lower for SF-DECT compared to SECT (p < 0.022). CONCLUSIONS: The combined use of split-filter dual-energy CT images provides comparable objective and subjective image quality at lower radiation dose compared to single-energy CT with ATVS. KEY POINTS: • Split-filter dual-energy results in 18% lower noise compared to single-energy with ATVS. • Split-filter dual-energy results in 11% lower SSDE compared to single-energy with ATVS. • Spectral shaping of split-filter dual-energy leads to an increased dose-efficiency.

First Report of Evolut Pro+ Transcatheter Aortic Valve-in-Valve in a Degenerated Lotus Valve.

The increasing use of transcatheter aortic valves in patients with aortic stenosis has led to a higher number of valve-in-valve procedures due to gradual valve degeneration. We present a case of a 72-year-old woman who received transcatheter aortic valve implantation (TAVI) using a Lotus valve due to severe aortic stenosis, which showed valve degeneration several years after the initial procedure. After heart-team discussion, TAVI-in-TAVI was planned using an Evolut pro+ valve, which allowed for full coverage of the Lotus valve and maintenance of coronary flow, resulting in a well-functioning valve with no regurgitation and normal performance. Despite high-risk anatomic features, valve-in-valve using an Evolut pro+ in a degenerated Lotus valve is feasible and overcomes pitfalls such as entanglement or coronary obstruction.

Aortic root rotation: morphological analysis of the aortic root with three-dimensional computed tomography.

OBJECTIVES: The aortic root (AoR) rotation and its spatial morphology at the base of the heart were postulated but not described in every detail. AoR rotation modalities may play an important role in decision-making during AoR surgery and its outcome. The aim was to provide a detailed spatial anatomy of the AoR rotation and its relation to the vital surrounding structure. METHODS: The AoR rotation and its relation to the surrounding structure were assessed in 104 patients with tricuspid aortic valve. The interatrial septum was chosen as a reference to describe AoR rotation that marked the midline of the heart base as a landmark for the AoR rotation direction. Intermediate, clockwise and counterclockwise AoR rotations were defined based on the mentioned reference structures. RESULTS: The AoR rotation was successfully assessed in 104 patients undergoing ascending aorta and or AoR intervention by multidetector row computed tomography. AoR was positioned normally in 53.8% of cases (n = 56) and rotated counterclockwise in 5.8% (n = 6) and clockwise in 40.4% (n = 42) of cases. In clockwise AoR rotation, the right coronary sinus was positioned in proximity to the right atrium and of the tricuspid valve, whereas in a counterclockwise rotation, the noncoronary sinus was placed over the tricuspid valve just over the membranous septum. CONCLUSIONS: The AoR's rotation can be diagnosed using multidetector row computed tomography. Understanding the anatomy of the aortic valve related to rotational position helps guide surgical decision-making in performing AoR reconstruction.

The learning curve for robotic-assisted transperineal MRI/US fusion-guided prostate biopsy.

Transperineal fusion prostate biopsy has a considerable learning curve (LC). Robotic-assisted transperineal MRI/Ultrasound fusion-guided biopsy (RA-TP-FBx) may have an easier LC due to automatization. We aimed to assess the LC of RA-TP-FBx and analyze its most difficult steps. We prospectively analyzed cases randomized to a biopsy-naïve urology resident, the chief resident, and an expert urologist in RA-TP-FBx (controls). We also analyzed consecutive cases in the LC of the expert. The LC was defined by procedure time, PCa detection rate (including stratification by PI-RADS), entrustable professional activities (EPA) assessment scores, and the NASA task load index. We collectively performed 246 RA-TP-FBx with the Mona Lisa device. Procedure time for residents decreased steeply from maximum 53 min to minimum 10 min, while the mean procedure time for the expert was 9 min (range 17-5 min). PCa detection for PI-RADS-4 lesions was 57% for the naïve resident, 61% for the chief resident and 62% for the expert. There was also no difference in Pca detection for PI-RADS-4 lesions when comparing the first and second half of the experts' biopsies (p = 0.8). Maximum EPA score was registered after 22 cases. Workload steeply declined. Proficient RA-TP-FBx performance appears feasible after 22 cases regardless of previous experience.

Cardiac Cine MRI Using a Commercially Available 0.55-T Scanner.

Purpose To compare parameters of left ventricular (LV) and right ventricular (RV) volume and function between a commercially available 0.55-T low-field-strength cardiac cine MRI scanner and a 1.5-T scanner. Materials and Methods In this prospective study, healthy volunteers (May 2022 to July 2022) underwent same-day cine imaging using both scanners (0.55 T, 1.5 T). Volumetric and functional parameters were assessed by two experts. After analyzing the results of a blinded crossover reader study of the healthy volunteers, 20 participants with clinically indicated cardiac MRI were prospectively included (November 2022 to February 2023). In a second blinded expert reading, parameters from clinical 1.5-T scans in these participants were compared with those same-day 0.55-T scans. Results are displayed as Bland-Altman plots. Results Eleven healthy volunteers (mean age: 33 years [95% CI: 27, 40]; four of 11 [36%] female, seven of 11 [64%] male) were included. Very strong mean correlation was observed (r = 0.98 [95% CI: 0.97, 0.98]). Average deviation between MRI systems was 1.6% (95% CI: 0.3, 2.9) for both readers. Twenty participants with clinically indicated cardiac MRI were included (mean age: 55 years [95% CI: 48, 62], six of 20 [30%] female, 14 of 20 [70%] male). Mean correlation was very strong (r = 0.98 [95% CI: 0.97, 0.98]). LV and RV parameters demonstrated an average deviation of 1.1% (95% CI: 0.1, 2.1) between MRI systems. Conclusion Cardiac cine MRI at 0.55 T yielded comparable results for quantitative biventricular volumetric and functional parameters compared with routine imaging at 1.5 T, if acquisition time is doubled. Keywords: Cardiac, Comparative Studies, Heart, Cardiovascular MRI, Cine, Myocardium Supplemental material is available for this article. ©RSNA, 2024.

Opportunistic Prostate Cancer Screening with Biparametric Magnetic Resonance Imaging (VISIONING).

BACKGROUND: This study investigates the use of biparametric magnetic resonance imaging (bpMRI) as primary opportunistic screening for prostate cancer (PCa) without using a prostate-specific antigen (PSA) cut-off. OBJECTIVE: The primary endpoint was to assess the efforts and effectiveness of identifying 20 participants with clinically significant prostate cancer (csPCa) using bpMRI. DESIGN, SETTING, AND PARTICIPANTS: Biopsy-naïve men aged over 45 yr were included. All participants underwent 3 Tesla bpMRI, PSA, and digital rectal examination (DRE). Targeted-only biopsy was performed in participants with Prostate Imaging Reporting and Data System (PI-RADS) ≥3. Men with negative bpMRI but suspicious DRE or elevated PSA/PSA density had template biopsies. Preintended protocol adjustments were made after an interim analysis for PI-RADS 3 lesions: no biopsy and follow-up MRI after 6 mo and biopsy only if lesions persisted or upgraded. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Biopsy results underwent a comparison using Fisher's exact test and univariable logistic regression to identify prognostic factors for positive biopsy. RESULTS AND LIMITATIONS: A total of 229 men were enrolled in this study, of whom 79 underwent biopsy. Among these men, 77 displayed suspicious PI-RADS lesions. PCa was detected in 29 participants (12.7%), of whom 21 had csPCa (9.2%). Biparametric MRI detected 21 csPCa cases, while PSA and DRE would have missed 38.1%. Protocol adjustment led to a 54.6% biopsy reduction in PI-RADS 3 lesions. Overall, in this cohort of men with a median PSA value of 1.26 ng/ml, 10.9 bpMRI scans were needed to identify one participant with csPCa. A major limitation of the study is the lack of a control cohort undergoing systematic biopsies. CONCLUSIONS: Opportunistic screening utilising bpMRI as a primary tool has higher sensitivity in detecting csPCa than classical screening methods. PATIENT SUMMARY: Screening with biparametric magnetic resonance imaging (bpMRI) and targeted biopsy identified clinically significant prostate cancer in every 11th man, regardless of the prostate-specific antigen (PSA) levels. Preselecting patients based on PSA >1 ng/ml and a positive family history of prostate cancer, as well as other potential blood tests may further improve the effectiveness of bpMRI in this setting.

Deep Learning-based Unsupervised Domain Adaptation via a Unified Model for Prostate Lesion Detection Using Multisite Biparametric MRI Datasets.

Purpose To determine whether the unsupervised domain adaptation (UDA) method with generated images improves the performance of a supervised learning (SL) model for prostate cancer (PCa) detection using multisite biparametric (bp) MRI datasets. Materials and Methods This retrospective study included data from 5150 patients (14 191 samples) collected across nine different imaging centers. A novel UDA method using a unified generative model was developed for PCa detection using multisite bpMRI datasets. This method translates diffusion-weighted imaging (DWI) acquisitions, including apparent diffusion coefficient (ADC) and individual diffusion-weighted (DW) images acquired using various b values, to align with the style of images acquired using b values recommended by Prostate Imaging Reporting and Data System (PI-RADS) guidelines. The generated ADC and DW images replace the original images for PCa detection. An independent set of 1692 test cases (2393 samples) was used for evaluation. The area under the receiver operating characteristic curve (AUC) was used as the primary metric, and statistical analysis was performed via bootstrapping. Results For all test cases, the AUC values for baseline SL and UDA methods were 0.73 and 0.79 (P < .001), respectively, for PCa lesions with PI-RADS score of 3 or greater and 0.77 and 0.80 (P < .001) for lesions with PI-RADS scores of 4 or greater. In the 361 test cases under the most unfavorable image acquisition setting, the AUC values for baseline SL and UDA were 0.49 and 0.76 (P < .001) for lesions with PI-RADS scores of 3 or greater and 0.50 and 0.77 (P < .001) for lesions with PI-RADS scores of 4 or greater. Conclusion UDA with generated images improved the performance of SL methods in PCa lesion detection across multisite datasets with various b values, especially for images acquired with significant deviations from the PI-RADS-recommended DWI protocol (eg, with an extremely high b value). Keywords: Prostate Cancer Detection, Multisite, Unsupervised Domain Adaptation, Diffusion-weighted Imaging, b Value Supplemental material is available for this article. © RSNA, 2024.

Multimodality imaging and 3D-printing of a thoraco-abdominal aortic aneurysm eroding into the spine.

A rare case of a previously treated thoraco-abdominal aortic aneurysm eroding into the thoracic spine is described. Initially, several follow-up CT angiography scans showed an increasing aneurysm sack, but no endoleak could be depicted. Then, a new rapidly developing erosion into the thoracic spine was noted. MRI imaging excluded any other underlying infectious or malignant process. Additional contrast-enhanced ultrasound excluded an endoleak. A 3D-printed model of the aneurysm and spine and cinematic renderings were created to improve visualization. She underwent relining of the thoracic stent graft. Follow-up imaging showed a stable aneurysm size and no progression of the vertebral erosions.

Assessment of hepatic function employing hepatocyte specific contrast agent concentrations to multifactorially evaluate fibrotic remodeling.

Background: Diffuse parenchymal liver diseases are contributing substantially to global morbidity and represent major causes of deaths worldwide. The aim of our study is to assess whether established hepatic fat and iron quantitation and relaxometry-based quantification of hepatocyte-specific contrast material as surrogate for liver function estimation allows to evaluate liver fibrosis. Methods: Retrospective consecutive study. Seventy-two healthy patients (mean age: 53 years) without known liver disease, 21 patients with temporary elevated liver enzymes (mean: 65 years) and 109 patients with biopsy proven liver fibrosis or cirrhosis (mean: 61 years), who underwent liver magnetic resonance imaging (MRI) with a hepatocyte-specific contrast agent [gadoxetate disodium, gadolinium ethoxybenzyl-diethylenetriaminepentaacetic acid (Gd-EOB-DTPA), 0.25 mmol/mL Primovist, Bayer AG, Leverkusen, Germany] at 1.5 T (n=133) and at 3 T (n=69), were included. Fibrosis was classified using the histopathological meta-analysis of histological data in viral hepatitis (METAVIR) and the clinical Child-Pugh scores. Gd-concentration were quantified using T1 map-based calculations. Gd-concentration mapping was performed by using a Look-Locker approach prior to and 912±159 s after intravenous administration of hepatocyte specific contrast agent. Additionally, parenchymal fat fraction, R2*, bilirubin, gender and age were defined as predicting factors. Diagnostic accuracy was calculated in a monoparametric (linear regression, predictor: Gd-concentration) and multiparametric model (predictors: age, bilirubin level, iron overload, liver fat fraction, Gd concentration in the left and right liver lobe). Results: Mean Gd-concentration in the liver parenchyma was significantly higher for healthy patients ([Gd] =0.51 µmol/L) than for those with liver fibrosis or cirrhosis ([Gd] =0.31 µmol/L; P<0.0001) and with acute liver disease ([Gd] =0.28 µmol/L), though there were no significant differences for the latter two groups. There was a significant moderate negative correlation for the mean Gd-concentration and the METAVIR score (ρ=-0.44, P<0.0001) as well as for the Child-Pugh stage (ρ=-0.35, P<0.0001). There was a significant strong correlation between the bilirubin concentration and the Gd-concentration (ρ=-0.61, P<0.0001). The diagnostic accuracy for the discrimination of healthy patients and patients with known fibrosis or cirrhosis was 0.74 (0.71/0.60 sensitivity/specificity) in a monoparametric and 0.76 (0.85/0.61 sensitivity/specificity) in a machine learning based multiparametric model. Conclusions: T1 mapping-based quantification of hepatic Gd-EOB-DTPA concentrations performed in a multiparametric model shows promising diagnostic accuracy for the detection of fibrotic changes. Liver biopsy might be replaced by imaging examinations.

Estimation of differential renal function on routine abdominal imaging employing compressed-sensed contrast-enhanced MR: a feasibility study referenced against dynamic renal scintigraphy in patients with deteriorating renal retention parameters.

PURPOSE: To assess whether high temporal/spatial resolution GRASP MRI acquired during routine clinical imaging can identify several degrees of renal function impairment referenced against renal dynamic scintigraphy. METHODS: This retrospective study consists of method development and method verification parts. During method development, patients subject to renal imaging using gadoterate meglumine and GRASP post-contrast MRI technique (TR/TE 3.3/1.6 ms; FoV320 × 320 mm; FA12°; Voxel1.1 × 1.1x2.5 mm) were matched into four equally-sized renal function groups (no-mild-moderate-severe impairment) according to their laboratory-determined estimated glomerular filtration rates (eGFR); 60|120 patients|kidneys were included. Regions-of-interest (ROIs) were placed on cortices, medullary pyramids and collecting systems of bilateral kidneys. Cortical perfusion, tubular concentration and collecting system excretion were determined as TimeCortex=Pyramid(sec), SlopeTubuli (sec-1), and TimeCollecting System (sec), respectively, and were measured by a combination of extraction of time intensity curves and respective quantitative parameters. For method verification, patients subject to GRASP MRI and renal dynamic scintigraphy (99mTc-MAG3, 100 MBq/patient) were matched into three renal function groups (no-mild/moderate-severe impairment). Split renal function parameters post 1.5-2.5 min as well as MAG3 TER were correlated with time intensity parameters retrieved using GRASP technique; 15|30 patients|kidneys were included. RESULTS: Method development showed differing values for TimeCortex=Pyramid(71|75|93|122 s), SlopeTubuli(2.6|2.1|1.3|0.5 s-1) and TimeCollecting System(90|111|129|139 s) for the four renal function groups with partial significant tendencies (several p-values < 0.001). In method verification, 29/30 kidneys (96.7%) were assigned to the correct renal function group. CONCLUSION: High temporal and spatial resolution GRASP MR imaging allows to identify several degrees of renal function impairment using routine clinical imaging with a high degree of accuracy.

Simultaneous assessment of vascular distensibility and vessel wall area at coronary, carotid, and aortic level in diabetic patients using CMR: detection of vascular remodeling.

AIMS: No data is available about the significance of cardiovascular magnetic resonance (CMR) derived vascular distensibility (VD) and vessel wall ratio (VWR) for risk stratification in patients with type 2 diabetes mellitus (T2DM). Therefore, this study aimed to investigate the effects of T2DM on VD and VWR using CMR in both central and peripheral territories. METHODS: Thirty-one T2DM-patients and nine controls underwent CMR. Angulation of the aorta, the common carotid, and the coronary arteries was performed to obtain cross-sectional vessel areas. RESULTS: In T2DM the Carotid-VWR and the Aortic-VWR correlated significantly. Mean values of Carotid-VWR and Aortic-VWR were significantly higher in T2DM than in controls. Coronary-VD was significantly lower in T2DM than in controls. No significant difference in Carotid-VD or Aortic-VD in T2DM vs. controls, respectively, could be observed. In a subgroup of thirteen T2DM patients with coronary artery disease (CAD), Coronary-VD was significantly lower and Aortic-VWR was significantly higher compared to T2DM patients without CAD. CONCLUSION: CMR allows a simultaneous evaluation of the structure and function of three important vascular territories to detect vascular remodeling in T2DM.