Whole-orbit-based multiparametric assessment of disease activity of thyroid eye disease on Dixon MRI.

PURPOSE: This study aimed to explore the diagnostic value of whole-orbit-based multiparametric assessment on Dixon MRI for the evaluation of the thyroid eye disease (TED) activity. METHODS: The retrospective study enrolled patients diagnosed as TED and obtained their axial and coronal Dixon MRI scans. Multiparameters were assessed, including water fraction (WF), fat fraction (FF) of extraocular muscles (EOMs), orbital fat (OF), and lacrimal gland (LG). The thickness of OF and herniation of LG were also measured. Univariable and multivariable logistic regression was applied to construct prediction models based on single or multiple structures. Receiver operating characteristic (ROC) curve analysis was also implemented. RESULTS: Univariable logistic analysis revealed significant differences in water fraction (WF) of the superior rectus (P = 0.018), fat fraction (FF) of the medial rectus (P = 0.029), WF of OF (P = 0.004), and herniation of LG (P = 0.012) between the active and inactive TED phases. Multivariable logistic analysis and corresponding receiver operating characteristic curve (ROC) analysis of each structure attained the area under the curve (AUC) values of 0.774, 0.771, and 0.729 for EOMs, OF, and LG, respectively, while the combination of the four imaging parameters generated a final AUC of 0.909. CONCLUSIONS: Dixon MRI may be used for fine multiparametric assessment of multiple orbital structures. The whole-orbit-based model improves the diagnostic performance of TED activity evaluation.

Elucidating the need for prostate cancer risk calculators in conjunction with mpMRI in initial risk assessment before prostate biopsy at a tertiary prostate cancer center.

OBJECTIVE: Utilizing personalized risk assessment for clinically significant prostate cancer (csPCa) incorporating multiparametric magnetic resonance imaging (mpMRI) reduces biopsies and overdiagnosis. We validated both multi- and univariate risk models in biopsy-naïve men, with and without the inclusion of mpMRI data for csPCa detection. METHODS: N = 565 men underwent mpMRI-targeted prostate biopsy, and the diagnostic performance of risk calculators (RCs), mpMRI alone, and clinical measures were compared using receiver operating characteristic curve (ROC) analysis and decision curve analysis (DCA). Subgroups were stratified based on mpMRI findings and quality. RESULTS: csPCa was detected in 56.3%. PI-RADS score achieved the highest area under the curve (AUC) when comparing univariate risk models (AUC 0.82, p < 0.001). Multivariate RCs showed only marginal improvement in csPCa detection compared to PI-RADS score alone, with just one of four RCs showing significant superiority. In mpMRI-negative cases, the non-MRI-based RC performed best (AUC 0.80, p = 0.016), with the potential to spare biopsies for 23%. PSA-density and multivariate RCs demonstrated comparable performance for PI-RADS 3 constellation (AUC 0.65 vs. 0.60-0.65, p > 0.5; saved biopsies 16%). In men with suspicious mpMRI, both mpMRI-based RCs and the PI-RADS score predicted csPCa excellently (AUC 0.82-0.79 vs. 0.80, p > 0.05), highlighting superior performance compared to non-MRI-based models (all p < 0.002). Quality-assured imaging consistently improved csPCa risk stratification across all subgroups. CONCLUSION: In tertiary centers serving a high-risk population, high-quality mpMRI provides a simple yet effective way to assess the risk of csPCa. Using multivariate RCs reduces multiple biopsies, especially in mpMRI-negative and PI-RADS 3 constellation.

Systematic Review and Metanalysis on the Role of Prostate-Specific Membrane Antigen Positron Emission Tomography/Magnetic Resonance Imaging for Intraprostatic Tumour Assessment.

The present systematic review and meta-analysis are focused on the diagnostic accuracy of PSMA PET/MRI in primary prostate cancer assessment. A literature search was conducted on the PubMed database using the terms "PSMA" AND "prostate cancer" or "prostate" AND "PET/MRI" or "PET MRI" or "PET-MRI" or "PET-MR" AND "primary" or "staging." Ten articles were eligible for analysis after applying the exclusion criteria. PET/MRI showed better diagnostic accuracy in detecting primary PCa compared to multiparametric (mp) MRI and PET alone. The pooled sensitivity and specificity of 68Ga-PSMA PET/MRI at the per-patient level were 0.976 (CI: 0.943-0.991) and 0.739 (CI: 0.437-0.912); respectively. PSMA PET/MRI has good sensitivity in detecting primary PCa, especially in patients with PIRADS 3 PCa.

Association between urology practice use of multiparametric MRI and genomic testing and treatment of men with newly diagnosed prostate cancer.

INTRODUCTION: Biomarkers for prostate cancer, such as multiparametric MRI (mpMRI) and tissue-based genomics, are increasingly used for treatment decision-making. Using biomarkers indiscriminately and thus ignoring competing risks of mortality may lead to treatment in some men who derive little clinical benefit. We assessed the relationship between urology practice use of biomarkers and subsequent treatment in men with newly diagnosed prostate cancer. METHODS: We used a 20% random sample of national Medicare data to perform a retrospective cohort study of men with newly diagnosed prostate cancer diagnosed from 2015 through 2019. Urology practice-level use of biomarkers was characterized based on urology practice propensity to use either biomarker after diagnosis (never, below median, above the median). Noncancer mortality risk within 10 years of diagnosis was calculated for all men. Multilevel models were used to assess the relationship between practice-level biomarker use and treatment by noncancer mortality risk. RESULTS: Between 2015 and 2019, 1,764 (65%) urology practices used mpMRI and 897 (33%) used genomic testing for prostate cancer. Compared with urology practices never using each biomarker, those using mpMRI above the median (56% vs. 47%, P = 0.003) and tissue-based genomics below the median (56% vs. 50%, P = 0.03) were more likely to treat men with >75% risk of noncancer mortality. Additionally, compared with urology practices never using either biomarker, use of mpMRI (72% vs. 69%, P = 0.07) or tissue-based genomics (71% vs. 70%, P = 0.65) did not impact treatment in the healthiest group (i.e., those with <25% risk of noncancer mortality). CONCLUSIONS: Compared to practices that do not use each biomarker in men with newly diagnosed prostate cancer, urology practices using mpMRI, and tissue-based genomics to a lesser extent, are more likely to treat men at very high risk of dying from competing risks of mortality within 10 years of prostate cancer diagnosis.

Adding automated decision-tree models to multiparametric MRI for parotid tumours improves clinical performance.

PURPOSE: Therapeutic management of parotid gland tumours depends on their histological type. To aid its characterisation, we sought to develop automated decision-tree models based on multiparametric magnetic resonance imaging (MRI) parameters and to evaluate their added diagnostic value compared with morphological sequences. METHODS: 206 MRIs from 206 patients with histologically proven parotid gland tumours were included from January 2009 to January 2018. Multiparametric MRI findings (including parameters derived from diffusion-weighted imaging [DWI] and dynamic contrast-enhanced [DCE]) were used to build predictive classification and regression tree (CART) models for each histological type. All MRIs were read twice: first, based on morphological sequence findings only, and second, with the addition of multiparametric sequences and CART findings. The diagnostic performance between these two readings was compared using ROC curves. RESULTS: Compared to morphological sequences alone, the addition of multiparametric analysis significantly increased the diagnostic performance for all histological types (p < 0.001 to p = 0.011), except for lymphomas, where the increase was not significant (AUC 1.00 vs. 0.99, p = 0.066). ADCmean was the best parameter to identify pleomorphic adenomas, carcinomas and lymphomas with respective cut-offs of 1.292 × 10-3 mm2/s, 1.181 × 10-3 mm2/s and 0.611 × 10-3 mm2/s, respectively. × 10-3 mm2/s. The mean extracellular-extravascular space coefficient was the best parameter to Warthin tumours from the others, with a cut-off of 0.07. CONCLUSIONS: The addition of decision tree prediction models based on multiparametric sequences improves the non-invasive diagnostic performance of parotid gland tumours. ADC and extracellular-extravascular space coefficient are the two best parameters for decision making.

Assessment of treatment response to dendritic cell vaccine in patients with glioblastoma using a multiparametric MRI-based prediction model.

PURPOSE: Autologous tumor lysate-loaded dendritic cell vaccine (DCVax-L) is a promising treatment modality for glioblastomas. The purpose of this study was to investigate the potential utility of multiparametric MRI-based prediction model in evaluating treatment response in glioblastoma patients treated with DCVax-L. METHODS: Seventeen glioblastoma patients treated with standard-of-care therapy + DCVax-L were included. When tumor progression (TP) was suspected and repeat surgery was being contemplated, we sought to ascertain the number of cases correctly classified as TP + mixed response or pseudoprogression (PsP) from multiparametric MRI-based prediction model using histopathology/mRANO criteria as ground truth. Multiparametric MRI model consisted of predictive probabilities (PP) of tumor progression computed from diffusion and perfusion MRI-derived parameters. A comparison of overall survival (OS) was performed between patients treated with standard-of-care therapy + DCVax-L and standard-of-care therapy alone (external controls). Additionally, Kaplan-Meier analyses were performed to compare OS between two groups of patients using PsP, Ki-67, and MGMT promoter methylation status as stratification variables. RESULTS: Multiparametric MRI model correctly predicted TP + mixed response in 72.7% of cases (8/11) and PsP in 83.3% (5/6) with an overall concordance rate of 76.5% with final diagnosis as determined by histopathology/mRANO criteria. There was a significant concordant correlation coefficient between PP values and histopathology/mRANO criteria (r = 0.54; p = 0.026). DCVax-L-treated patients had significantly prolonged OS than those treated with standard-of-care therapy (22.38 ± 12.8 vs. 13.8 ± 9.5 months, p = 0.040). Additionally, glioblastomas with PsP, MGMT promoter methylation status, and Ki-67 values below median had longer OS than their counterparts. CONCLUSION: Multiparametric MRI-based prediction model can assess treatment response to DCVax-L in patients with glioblastoma.

Effect of a dedicated PI-QUAL curriculum on the assessment of prostate MRI quality.

PURPOSE: The Prostate Imaging Quality (PI-QUAL) score is a metric to evaluate the diagnostic quality of multiparametric magnetic resonance imaging (MRI) of the prostate. This study evaluated the impact of a prostate MRI quality training lecture on the participant's ability to assess prostate MRI image quality. METHODS: Eighteen in-training-radiologists of varying experience in reviewing diagnostic prostate MRI assessed the image quality of ten examinations. Then, they attended a dedicated lecture on MRI quality assessment using the PI-QUAL score. After the lecture, the same participants evaluated the image quality of a new set of ten scans applying the PI-QUAL score. Results were assessed using receiver operating characteristic (ROC) analysis. The reference standard was the PI-QUAL score assessed by a fellowship trained abdominal radiologist with experience in reading prostate MRI. RESULTS: There was a significant improvement in the average area under the curve (AUC) for assessment of prostate MRI image quality from baseline (0.82; [0.576 - 0.888]) to post teaching (1.0; [0.954-1]), with an improvement of 0.18 (p < 0.03). When ROC curves were computed for different cohorts stratified based on year of training, difference ranged from 0.48 for second year residents to 0.32 for fourth year residents (p < 0.001-0.01). For abdominal imaging fellows, the pre-teaching AUC was 0.9 [0.557-1] and post teaching AUC was 1 [0.957-1], a difference of 0.1 (p = 0.20). CONCLUSIONS: A dedicated lecture on PI-QUAL improved the ability of radiologists-in-training to assess prostate MRI image quality, with variable impact depending on year of training.

[Diagnostic value of multiparametric MRI-based models in the assessment of extra-prostatic extension of prostate cancer].

Objective: To evaluate the diagnostic value of multiparametric magnetic resonance imaging (mpMRI) based models in the assessment of extra-prostatic extension (EPE) of prostate cancer. Methods: This retrospective study included 168 consecutive men with prostate cancers [aged 48 to 82 (66.6±6.8) years] who underwent radical prostatectomy and preoperative mpMRI examinations at the First Medical Center of the PLA General Hospital from January 2021 to February 2022. According to European Society of Urogenital Radiology (ESUR) score, EPE grade and mEPE score, all cases were independently evaluated by two radiologists, with disagreement reviewed by a senior radiologist as the final result. The diagnostic performance of each MRI-based model for pathologic EPE prediction was assessed using receiver operating characteristic curve (ROC), and the differences between the corresponding area under the curve (AUC) were compared using the DeLong test. The weighted Kappa test was used to evaluate the inter-reader agreement of each MRI-based model. Results: A total of 62 (36.9%) prostate cancer patients had pathologic confirmed EPE after radical prostatectomy. The AUC of ESUR score, EPE grade and mEPE score for predicting pathologic EPE were 0.836 (95%CI: 0.771-0.888), 0.834 (95%CI: 0.769-0.887) and 0.785 (95%CI: 0.715-0.844), respectively. The AUC of ESUR score and EPE grade were both superior to that of mEPE score with significant differences (all P<0.05), while there was no significant difference between the ESUR score and EPE grade models (P=0.900). EPE grading and mEPE score had good inter-reader consistency, with weighted Kappa values of 0.65 (95%CI: 0.56-0.74) and 0.74 (95%CI: 0.64-0.84), respectively. The inter-reader consistency of ESUR score was moderate, and the weighted Kappa value was 0.52 (95%CI: 0.40-0.63). Conclusion: All MRI-based models showed good preoperative diagnostic value in predicting EPE, among which the EPE grade resulted in more reliable performance with substantial inter-reader agreement.

Diagnostic accuracy of pelvis multiparametric MRI against CT virtual hysterosalpingography: a prospective study of tubal patency through female infertility assessment.

OBJECTIVE: To evaluate the diagnostic accuracy of MRI-hysterosalpingogram (HSG) with semiquantitative dynamic contrast-enhanced perfusion, against the virtual multislice CT hysterosalpingogram (VHSG) as a reference standard. METHODS AND MATERIALS: In this prospective study, 26 women (age >18 years) searching for infertility causes and with VHSG physician request. Thereafter, the assessment performance of both techniques was determined by two reader analyses. k statistics were used for the assessment of tubal patency. Receiver operating characteristic (ROC) analysis was used to compare the capability for tubal patency assessment between both exams on a per-patient and per-tube basis. The McNemar test was used to compare the diagnostic accuracy measures. RESULTS: Tubal patency, uterine morphological, ovarian, and extrauterine abnormalities were evaluated through both exams in all 26 women. There was no significant difference between diagnostic performance measurements between the methods. The ROC curve of VHSG was 0.852 for both per-patient and per-tube analyses, and one and 0.938 for MRI-HSG. Sensitivity and specificity for per-patient and per-tube for VHSG were 95.2 and 97.7, 80 and 87.5%, and for MRI-HSG 100% for both analyses and 100 and 87.5%, respectively. CONCLUSION: This study demonstrates the feasibility of diagnosing tubal patency through MRI, using a semi-quantitative dynamic contrast-enhanced perfusion sequence, and the satisfactory diagnosing of the uterine morphology, ovarian abnormalities, and ovarian and deep endometriosis. ADVANCES IN KNOWLEDGE: Multiparametric MRI with a perfusion real-time sequence as a HSG method can be used in the evaluation not only for uterine and ovarian abnormilities but also tubal patency.

Multiparametric Magnetic Resonance Imaging With Comprehensive Assessment of Prostate Volume, Morphology, and Composition Better Reflects the Correlation With International Prostate Symptom Score.

OBJECTIVE: To investigate the application of multiparametric magnetic resonance imaging (mp-MRI) for comprehensive evaluation of the correlation between the characteristics of the transitional zone and the International Prostate Symptom Score (IPSS) in patients with benign prostatic hyperplasia (BPH). MATERIALS AND METHODS: We retrospectively recruited 210 patients with biopsy-proven BPH who underwent preoperative mp-MRI and were assigned an IPSS. The evaluation indicators included prostate volumetric parameters (total prostate volume [TPV], transition zone volume [TZV], and transition zone index [TZI, TZI=TZV/TPV]), prostate morphological parameters (intravesical prostatic protrusion, and presumed circle area ratio) and prostate compositional parameters (apparent diffusion coefficient [ADC], and mean signal intensity of T2WI [mean-SI-T2WI]). The Pearson (r) correlation coefficient, one-way analysis of variance, and multiple linear regression analysis were used to build a regression model for evaluating the correlation between MRI-derived parameters and IPSS, IPSS-storage symptom, IPSS-voiding symptom. RESULTS: Significant correlations were found between IPSS, IPSS-storage symptom, IPSS-voiding symptom, and prostate MRI-derived parameters, including TPV (r = 0.350; r = 0.466; r = 0.225, P < .001), TZV (r = 0.374; r = 0.492; r = 0.243, P < .001), TZI (r = 0.383; r = 0.313; r = 0.354, P < .001), presumed circle area ratio (r = 0.481; r = 0.356; r = 0.469, P < .001), ADC(r = -0.198; r = -0.053; r = -0.239, P < .05) and mean-SI-T2WI (r = -0.626; r = -0.310; r = -0.687, P < .001), respectively. Based on multiple linear regression analysis, the impact of mean-SI-T2WI and TZI on total IPSS were statistically significant (P < .05), and the regression equation established with the analysis (IPSS= 39.224 + 8.469 ×TZI+ (-0.09)× (mean-SI-T2WI)) was statistically significant (F=104.995, P < .001). CONCLUSION: Mp-MRI could be used to evaluate the volume and morphology of BPH. In particular, mean-SI-T2WI and ADC could be used to describe the internal composition of the prostate. The imaging parameters were effective for evaluating BPH.

Deep Learning Radiomics for the Assessment of Telomerase Reverse Transcriptase Promoter Mutation Status in Patients With Glioblastoma Using Multiparametric MRI.

BACKGROUND: Studies have shown that magnetic resonance imaging (MRI)-based deep learning radiomics (DLR) has the potential to assess glioma grade; however, its role in predicting telomerase reverse transcriptase (TERT) promoter mutation status in patients with glioblastoma (GBM) remains unclear. PURPOSE: To evaluate the value of deep learning (DL) in multiparametric MRI-based radiomics in identifying TERT promoter mutations in patients with GBM preoperatively. STUDY TYPE: Retrospective. POPULATION: A total of 274 patients with isocitrate dehydrogenase-wildtype GBM were included in the study. The training and external validation cohorts included 156 (54.3 ± 12.7 years; 96 males) and 118 (54 .2 ± 13.4 years; 73 males) patients, respectively. FIELD STRENGTH/SEQUENCE: Axial contrast-enhanced T1-weighted spin-echo inversion recovery sequence (T1CE), T1-weighted spin-echo inversion recovery sequence (T1WI), and T2-weighted spin-echo inversion recovery sequence (T2WI) on 1.5-T and 3.0-T scanners were used in this study. ASSESSMENT: Overall tumor area regions (the tumor core and edema) were segmented, and the radiomics and DL features were extracted from preprocessed multiparameter preoperative brain MRI images-T1WI, T1CE, and T2WI. A model based on the DLR signature, clinical signature, and clinical DLR (CDLR) nomogram was developed and validated to identify TERT promoter mutation status. STATISTICAL TESTS: The Mann-Whitney U test, Pearson test, least absolute shrinkage and selection operator, and logistic regression analysis were applied for feature selection and construction of radiomics and DL signatures. Results were considered statistically significant at P-value <0.05. RESULTS: The DLR signature showed the best discriminative power for predicting TERT promoter mutations, yielding an AUC of 0.990 and 0.890 in the training and external validation cohorts, respectively. Furthermore, the DLR signature outperformed CDLR nomogram (P = 0.670) and significantly outperformed clinical models in the validation cohort. DATA CONCLUSION: The multiparameter MRI-based DLR signature exhibited a promising performance for the assessment of TERT promoter mutations in patients with GBM, which could provide information for individualized treatment. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Promoting the use of the PI-QUAL score for prostate MRI quality: results from the ESOR Nicholas Gourtsoyiannis teaching fellowship.

OBJECTIVES: The Prostate Imaging Quality (PI-QUAL) score is a new metric to evaluate the diagnostic quality of multiparametric magnetic resonance imaging (MRI) of the prostate. This study assesses the impact of an intervention, namely a prostate MRI quality training lecture, on the participant's ability to apply PI-QUAL. METHODS: Sixteen participants (radiologists, urologists, physicists, and computer scientists) of varying experience in reviewing diagnostic prostate MRI all assessed the image quality of ten examinations from different vendors and machines. Then, they attended a dedicated lecture followed by a hands-on workshop on MRI quality assessment using the PI-QUAL score. Five scans assessed by the participants were evaluated in the workshop using the PI-QUAL score for teaching purposes. After the course, the same participants evaluated the image quality of a new set of ten scans applying the PI-QUAL score. Results were assessed using receiver operating characteristic analysis. The reference standard was the PI-QUAL score assessed by one of the developers of PI-QUAL. RESULTS: There was a significant improvement in average area under the curve for the evaluation of image quality from baseline (0.59 [95 % confidence intervals: 0.50-0.66]) to post-teaching (0.96 [0.92-0.98]), an improvement of 0.37 [0.21-0.41] (p < 0.001). CONCLUSIONS: A teaching course (dedicated lecture + hands-on workshop) on PI-QUAL significantly improved the application of this scoring system to assess the quality of prostate MRI examinations. KEY POINTS: • A significant improvement in the application of PI-QUAL for the assessment of prostate MR image quality was observed after an educational intervention. • Appropriate training on image quality can be delivered to those involved in the acquisition and interpretation of prostate MRI. • Further investigation will be needed to understand the impact on improving the acquisition of high-quality diagnostic prostate MR examinations.

Noninvasive Assessment of the Renal Function, Oxford Classification and Prognostic Risk Stratification of IgAN by Using Intravoxel Incoherent Motion Diffusion-Weighted Imaging and Blood Oxygenation Level-Dependent MRI.

BACKGROUND: Immunoglobulin A nephropathy (IgAN) is the most common primary glomerulonephritis worldwide. Oxford classification including mesangial hypercellularity (M), endothelial hypercellularity (E), segmental sclerosis (S), interstitial fibrosis/tubular atrophy (T), and crescent (C) were recommended to predict the prognosis of IgAN. PURPOSE: To explore whether multiparametric magnetic resonance imaging (MRI) can be applied to assess the renal function, Oxford classification, and risk of progression to end-stage kidney disease within 5 years of IgAN. STUDY TYPE: Prospective. POPULATION: A total of 46 patients with pathologically confirmed IgAN and 20 healthy volunteers. FIELD STRENGTH/SEQUENCE: A 3-T, blood oxygenation level-dependent (BOLD)-MRI, intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI). ASSESSMENT: Two radiologists measured the cortex and medulla T2*, apparent diffusion coefficient (ADC), true diffusion (Dt), pseudo-diffusion (Dp), perfusion fraction (fp). All participants were divided into three groups: group 1, healthy volunteers; group 2, patients with estimated glomerular filtration rate (eGFR) ≥60 mL/min/1.73 m2 ; group 3, patients with eGFR <60 mL/min/1.73 m2 . Or two groups: group A, 5-year risk scores ≤10% and group B, 5-year risk scores >10%. STATISTICAL TESTS: Intraclass correlation coefficient, one-way analysis of variance, least-significant difference, Student's t-test, Pearson product-moment correlation, Spearman's rank correlation, and receiver operating characteristics (ROC) with the area under the curve (AUC). A P value <0.05 was considered statistically significant. RESULTS: Except for cortical Dp, all other MRI parameters showed significant differences between group 1 and group 2. None of the MRI parameters showed a significant correlation with M, E, or C scores. Cortical T2*, Dt, fp, and medullary Dt and fp showed low-to-moderate significant correlations with S scores. Except for cortical and medullary Dp, all other MRI parameters were significantly correlated with T scores. Cortical Dt showed the largest AUC for differentiating group A from group B (AUC = 0.927) and T0 from T1/T2 (AUC = 0.963). DATA CONCLUSION: Imaging by IVIM-DWI and BOLD-MRI could facilitate noninvasive assessment of the renal function, Oxford classification, and prognostic risk of IgAN patients. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 3.

Utility of a Rule-Based Algorithm in the Assessment of Standardized Reporting in PI-RADS.

RATIONALE AND OBJECTIVES: Adoption of the Prostate Imaging Reporting & Data System (PI-RADS) has been shown to increase detection of clinically significant prostate cancer on prostate mpMRI. We propose that a rule-based algorithm based on Regular Expression (RegEx) matching can be used to automatically categorize prostate mpMRI reports into categories as a means by which to assess for opportunities for quality improvement. MATERIALS AND METHODS: All prostate mpMRIs performed in the Duke University Health System from January 2, 2015, to January 29, 2021, were analyzed. Exclusion criteria were applied, for a total of 5343 male patients and 6264 prostate mpMRI reports. These reports were then analyzed by our RegEx algorithm to be categorized as PI-RADS 1 through PI-RADS 5, Recurrent Disease, or "No Information Available." A stratified, random sample of 502 mpMRI reports was reviewed by a blinded clinical team to assess performance of the RegEx algorithm. RESULTS: Compared to manual review, the RegEx algorithm achieved overall accuracy of 92.6%, average precision of 88.8%, average recall of 85.6%, and F1 score of 0.871. The clinical team also reviewed 344 cases that were classified as "No Information Available," and found that in 150 instances, no numerical PI-RADS score for any lesion was included in the impression section of the mpMRI report. CONCLUSION: Rule-based processing is an accurate method for the large-scale, automated extraction of PI-RADS scores from the text of radiology reports. These natural language processing approaches can be used for future initiatives in quality improvement in prostate mpMRI reporting with PI-RADS.

Quantitative multiparametric MRI as a promising tool for the assessment of early response to neoadjuvant chemotherapy in bladder cancer.

PURPOSE: Magnetic resonance imaging (MRI) has been applied to predict the neoadjuvant chemotherapy (NAC) response of bladder cancer at an early stage, but the performance remains poor. A tool for the selection of patients with muscle-invasive bladder cancer (MIBC) with high probability of benefitting from NAC is not yet available. We designed a prospective study to assess a quantitative MRI for predicting the early response of MIBC to NAC. METHODS: All individuals underwent a time-course MRI at pre-NAC, 24 h after initial cisplatin medication (24 h-NAC) and post-NAC.Chemosensitivity was evaluated according to pathological response.The transfer constant (Ktrans), plasma volume (Vp), extravascular extracellular space (Ve), and apparent diffusion coefficient (ADC) were quantitated based on dynamic contrast-enhanced and diffusion-weighted imaging.Quantitative RECIST criteria were constructed by modelling pre-NAC and 24 h-NAC MRI measures, and then compared with conventional RECIST by using pre- and post-NAC MRI measures. RESULTS: In this pilot study, a total of 24 patients were enrolled into the study. Eight patients were pathologically confirmed to be NAC-responders. After a thorough evaluation of these parameters, different parameters showed good discrimination at different point in time. ROC curves showed quantitative MRI can predict the response to NAC, especially ADC_M (AUC = 0.859, P = 0.005) and ADC index (AUC = 0.844, P = 0.007) at pre-NAC timing and ADC_M (AUC = 0.816, P = 0.013) at 24 h-NAC timing. Then, a qRECIST model was established for predicting NAC sensitivity, with AUC of 0.91, TP rate of 0.8, and accuracy of 0.75. CONCLUSION: The diagnostic performance of mpMRI parameters for NAC response is excellent. The qRECIST derived between pre- and 24 h NAC MRI could predict the early response of MIBC to NAC and help for candidate selection.

Noninvasive assessment of breast cancer molecular subtypes on multiparametric MRI using convolutional neural network with transfer learning.

BACKGROUND: To evaluate the performances of multiparametric MRI-based convolutional neural networks (CNNs) for the preoperative assessment of breast cancer molecular subtypes. METHODS: A total of 136 patients with 136 pathologically confirmed invasive breast cancers were randomly divided into training, validation, and testing sets in this retrospective study. The CNN models were established based on contrast-enhanced T1 -weighted imaging (T1 C), Apparent diffusion coefficient (ADC), and T2 -weighted imaging (T2 W) using the training and validation sets. The performances of CNN models were evaluated on the testing set. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy were calculated to assess the performance. RESULTS: For the separation of each subtype from other subtypes on the testing set, the T1 C-based models yielded AUCs from 0.762 to 0.920; the ADC-based models yielded AUCs from 0.686 to 0.851; and the T2 W-based models achieved AUCs from 0.639 to 0.697. CONCLUSION: T1 C-based models performed better than ADC-based models and T2 W-based models in assessing the breast cancer molecular subtypes. The discriminating performances of our CNN models for triple negative and human epidermal growth factor receptor 2-enriched subtypes were better than that of luminal A and luminal B subtypes.

Prospective assessment of VI-RADS score in multiparametric MRI in bladder cancer: accuracy and the factors affecting the results.

PURPOSE We aimed to investigate the accuracy of Vesical Imaging - Reporting and Data System (VI-RADS) in the detection of muscle-invasive bladder cancer (MIBC) and to determine which factors affect the results of this scoring system. METHODS A prospective data analysis of 80 patients who were detected to have bladder tumor was performed between March 2019 and October 2020. VI-RADS scoring was used to determine the probability of muscle invasion. The scores were compared with pathological results to evaluate the accuracy of the VI-RADS scoring system. Interobserver agreement was assessed by VI-RADS scoring of 20 randomly chosen patients by a different experienced radiologist. RESULTS Using the VI-RADS scoring system, the sensitivity, specificity, positive predictive value, and negative predictive value of multiparametric magnetic resonance imaging (mpMRI) were 87.5%, 87.5%, 63.6%, and 96.6%, respectively. The interobserver agreement expressed as the interclass correlation coefficient (ICC) was 0.72 (95% CI: 0.44-0.84, P < .001). In addition, the flat appearance of the tumor was an important factor affecting the accuracy of the VI-RADS score (odds ratio: 5.3 [95% CI: 1.1-27.0] and relative risk: 1.87 [95% CI: 1.24-2.82]). CONCLUSION The mpMRI, used in conjunction with VI-RADS, has proven to be an effective imaging method for detecting muscle invasion in cases of bladder cancer. VI-RADS scoring system can distinguish whether there is a muscle-invasive and non-muscle invasive bladder cancer with acceptable accuracy. In addition, the flat appearance of the tumor is an important entity that can affect the accuracy of the VI-RADS scoring system.

Precision-guidance vs Systematic Sampling: Optimizing Biopsy Assessment of Secondary Prostate Cancer Suspicious Multiparametric Magnetic Resonance Imaging Lesions.

PURPOSE: We assessed the diagnostic yield of consecutive transperineal targeted biopsy of multiparametric magnetic resonance imaging index lesion and secondary lesion and additive systematic biopsy in patients who received combined targeted biopsy+systematic biopsy of prostate. MATERIALS AND METHODS: Of 1,467 patients with targeted biopsy+systematic biopsy, analyses were restricted to 571 patients with index lesion+secondary lesion, Prostate Imaging-Reporting and Data System score ≥3. Index lesion was defined as having the greatest Prostate Imaging-Reporting and Data System score and/or lesion volume as opposed to secondary lesion. We retrospectively compared clinically significant prostate cancer rates (ie, Gleason Grade Group ≥2) between index lesion+secondary lesion and index lesion+secondary lesion+systematic biopsy. Subgroup analyses in men with ipsilateral index lesion+secondary lesion focused on contralateral systematic biopsy. Multivariable logistic regression analyses to predict any clinically significant prostate cancer included age, previous biopsies, prostate specific antigen density, respective index lesion/secondary lesion volumes, side relation, Prostate Imaging-Reporting and Data System strata, and number of targeted biopsy and systematic biopsy cores. RESULTS: Clinically significant prostate cancer rates for index lesion+secondary lesion vs index lesion+secondary lesion+systematic biopsy were 38% vs 42% (P = .2) at expense of significantly higher median number of biopsy cores (9 vs 25, P < .001). In the subgroup with ipsilateral index lesion+secondary lesion (n = 236), contralateral systematic biopsy detected clinically significant prostate cancer in 17%. In the narrower subgroup with ipsilateral index lesion+secondary lesion (n = 131) without any clinically significant prostate cancer, contralateral systematic biopsy detected clinically significant prostate cancer in 3.8%. Multivariable logistic regression analyses confirmed contralateral systematic biopsy as independent predictor, but performed similarly without systematic biopsy information (area under the curve 87.1% vs 86.6%). CONCLUSIONS: Targeted biopsy of secondary lesion should be included in targeted biopsy protocols due to added diagnostic information. However, for targeted biopsy of index lesion+secondary lesion additional systematic biopsy is of limited informative value in terms of overall clinically significant prostate cancer detection. However, when index lesion+secondary lesion are ipsilateral, contralateral systematic biopsy should be recommended for purpose of prostate lobe information. Our results indicate great potential to reduce systematic biopsy cores and associated potential morbidity, and warrant prospective evaluation.

Cost-effectiveness analysis of short biparametric magnetic resonance imaging protocol in men at risk of prostate cancer.

OBJECTIVES: To compare the cost-effectiveness of a short biparametric MRI (BP-MRI) with that of contrast-enhanced multiparametric MRI (MP-MRI) for the detection of prostate cancer in men with elevated prostatespecific antigen (PSA) levels. MATERIALS AND METHODS: We compared two diagnostic procedures for detection of prostate cancer (Pca), BP-MRI and MP-MRI, in terms of quality-adjusted life years (QALY), incremental costeffectiveness ratio (ICER) and net monetary benefit (NMB) for a hypothetical cohort of 10,000 patients. We compared two scenarios in which different protocols would be used for the early diagnosis of prostate cancer in relation to PSA values. Scenario 1. BP-MRI/MP-MRI yearly if > 3.0 ng/ml, every 2 years otherwise; Scenario 2. BP-MRI/MP-MRI yearly with age-dependent threshold 3.5 ng/ml (50-59 years), 4.5 ng/ml (60-69 years), 6.5 ng/ml (70-79 years). RESULTS: BP-MRI was more effective than the comparator in terms of cost (160.10 € vs 249.99€) QALYs (a mean of 9.12 vs 8.46), ICER (a mean of 232.45) and NMB (a mean of 273.439 vs 251.863). BP-MRI was dominant, being more effective and less expensive, with a lower social cost. Scenario 2 was more cost-effective compared to scenario 1. CONCLUSIONS: Our results confirmed the hypothesis that a short bi-parametric MRI protocol represents a cost-efficient procedure, optimizing resources in a policy perspective.