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Purpose: To explore the feasibility of multiparametric MRI-based habitat imaging for distinguishing uterine sarcoma (US) from atypical leiomyoma (ALM)., Methods: This retrospective study included the clinical and preoperative MRI data of 69 patients with US and 225 patients with ALM from three hospitals. At both the individual and cohort levels, the K-means and Gaussian mixture model (GMM) algorithms were utilized to perform habitat imaging on MR images, respectively. Specifically, T2-weighted images (T2WI) and contrast-enhanced T1-weighted images (CE-T1WI) were clustered to generate structural habitats, while apparent diffusion coefficient (ADC) maps and CE-T1WI were clustered to create functional habitats. Parameters of each habitat subregion were extracted to construct distinct habitat models. The integrated models were constructed by combining habitat and clinical independent predictors. Model performance was assessed using the area under the curve (AUC)., Results: Abnormal vaginal bleeding, lactate dehydrogenase (LDH), and white blood cell (WBC) counts can serve as clinical independent predictors of US. The GMM-based functional habitat model at the cohort level had the highest mean AUC (0.766) in both the training and validation cohorts, followed by the GMM-based structural habitat model at the cohort level (AUC = 0.760). Within the integrated models, the K-means functional habitat model based on the cohort level achieved the highest mean AUC (0.905) in both the training and validation cohorts., Conclusion: Habitat imaging based on multiparametric MRI has the potential to distinguish US from ALM. The combination of clinical independent predictors with the habitat models can effectively improve the performance., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Objective: To develop a multiparametric magnetic resonance imaging (mpMRI)-based radiomics nomogram and evaluate its performance in differentiating primary mucinous ovarian cancer (PMOC) from metastatic ovarian cancer (MOC)., Methods: A total of 194 patients with PMOC (n = 72) and MOC (n = 122) confirmed by histology were randomly divided into the primary cohort (n = 137) and validation cohort (n = 57). Radiomics features were extracted from axial fat-saturated T2-weighted imaging (FS-T2WI), diffusion-weighted imaging (DWI), and contrast-enhanced T1-weighted imaging (CE-T1WI) sequences of each lesion. The effective features were selected by minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) regression to develop a radiomics model. Combined with clinical features, multivariate logistic regression analysis was employed to develop a radiomics nomogram. The efficiency of nomogram was evaluated using the receiver operating characteristic (ROC) curve analysis and compared using DeLong test. Finally, the goodness of fit and clinical benefit of nomogram were assessed by calibration curves and decision curve analysis, respectively., Results: The radiomics nomogram, by combining the mpMRI radiomics features with clinical features, yielded area under the curve (AUC) values of 0.931 and 0.934 in the primary and validation cohorts, respectively. The predictive performance of the radiomics nomogram was significantly superior to the radiomics model (0.931 vs. 0.870, P = 0.004; 0.934 vs. 0.844, P = 0.032), the clinical model (0.931 vs. 0.858, P = 0.005; 0.934 vs. 0.847, P = 0.030), and radiologists (all P < 0.05) in the primary and validation cohorts, respectively. The decision curve analysis revealed that the nomogram could provide higher net benefit to patients., Conclusion: The mpMRI-based radiomics nomogram exhibited notable predictive performance in differentiating PMOC from MOC, emerging as a non-invasive preoperative imaging approach., Competing Interests: Declarations. Conflict of interest: The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: Placental site trophoblastic tumor (PSTT) is a rare form of gestational trophoblastic neoplasm with few previous imaging case reports. We report multiparametric MRI findings in four cases of PSTT with special emphasis on the "pseudo-myometrial thinning" underlying the tumor., Methods: We reviewed multiparametric MRI and pathologic findings in four cases of PSTT from four institutions. Signal intensity, enhancement pattern, margins, and location of the tumors were evaluated, and myometrial thickness underlying the tumor and normal myometrial thickness contralateral to the tumor were measured on MRI. The myometrial thickness underlying the tumor was also measured in the resected specimen and compared with the myometrial thickness measured on MRI using the Friedman test., Results: All tumors showed heterogeneous signal intensity on T1-weighted imaging, T2-weighted imaging (T2WI), and diffusion-weighted imaging. Three of the four tumors had a hypervascular area on dynamic contrast-enhanced (DCE) MRI. A hypointense rim on T2WI and DCE-MRI was seen in all tumors. All tumors protruded into the uterine cavity to varying degrees and extended into the myometrium close to the serosa. The myometrial thickness underlying the tumor measured on MRI (median thickness, 1.2 mm) was significantly thinner than that measured on pathology (median thickness, 9.5 mm) and normal myometrial thickness contralateral to the tumor on MRI (median thickness, 10.3 mm) (P = 0.02), and there was no significant difference between the latter two., Conclusions: The thickness of the myometrium underlying the tumor on MRI was approximately one tenth of the thickness on pathology. Thus, the tumors appeared to have almost transmural invasion even when pathologically located within the superficial myometrium. This "pseudo-thinning" of the underlying myometrium and the hypointense rim on MRI could be caused by focal compression of the myometrium by the tumor, possibly due to the fragility of the myometrium at the placental site., Competing Interests: Declarations. Ethical approval: This study was conducted in accordance with the principles of the Declaration of Helsinki. This study was approved by the Research Ethics Committee of Osaka University (approval number: 23216). Informed consent: Written informed consent for participation was waived owing to the retrospective nature of the study, and patient records were anonymously analyzed. Competing interests: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: To investigate the effectiveness of multiparametric MRI examination in determining tumor response after neoadjuvant chemoradiotherapy (CRT) in locally advanced rectal tumors., Methods: 46 patients with locally advanced rectal adenocarcinoma were included and were divided into two groups as complete responders and nonresponders based on Mandard score. On MRI, relative T2w signal intensity and ADC values obtained before and after treatment and tumour volumes in dynamic contrast enhanced images (DCI) were used to determine complete response to treatment., Results: There were no significant differences between mean ADC values obtained by single slice ADC and three circular ROI methods. There were significant differences between two groups in terms of Post-CRT ADC value, ΔADC and %ΔADC obtained by whole tumour volume ADC method (p < 0.05). There were significant differences between Pre-CRT and Post-CRT volume values. ΔV DCI and %ΔV DCI, ΔV ADC and T2w volume values were significantly lower in complete responders (p < 0.05). In multivariate analysis, sensitivity and specificity were calculated as 88.9% and 91.9% (AUC = 0.943) when Post-CRT mean ADC value and Post-CRT DCI volume values were used together, and sensitivity and specificity were calculated as 88.9% and 94.6% (AUC = 0.949) when ΔADC and Post-CRT DCI volume values were used together., Conclusion: Whole tumour volume mean ADC value is the most useful method to determine treatment response. Post-CRT DCI volume measurement stands out as the most useful method in assessing complete response alone. The highest diagnostic values are achieved when the post-CRT DCI volume is combined with the ADC change value of the whole tumor volume., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: To non-invasively quantify pancreatic fibrosis and grade severity of chronic pancreatitis (CP) on dual-energy CT (DECT) and multiparametric MRI (mpMRI)., Methods: We included 72 patients (mean age:30years; 59 men) with suspected or confirmed CP from December 2019 to December 2021 graded as equivocal(n = 20), mild(n = 18), and moderate-marked(n = 34) using composite imaging and endoscopic ultrasound criteria. Study patients underwent multiphasic DECT and mpMRI of the abdomen. Normalized iodine concentration(NIC) and fat fraction(FF) on 6-minute delayed DECT, and T1 relaxation time(T1Rt), extracellular volume fraction(ECVf), intravoxel incoherent motion-based perfusion fraction(PF), and magnetization transfer ratio(MTR) on mpMRI of pancreas were compared. 20 renal donors(for DECT) and 20 patients with renal mass(for mpMRI) served as controls., Results: NIC of pancreas in controls and progressive grades of CP were 0.24 ± 0.05, 0.80 ± 0.18, 1.06 ± 0.23, 1.40 ± 0.36, FF were 9.28 ± 5.89, 14.19 ± 5.29, 17.31 ± 5.99, 29.32 ± 12.22, T1Rt were 590.11 ± 61.13, 801.93 ± 211.01, 1006.79 ± 352.18, 1388.01 ± 312.23ms, ECVf were 0.07 ± 0.03, 0.30 ± 0.12, 0.41 ± 0.12, 0.53 ± 0.13, PF were 0.38 ± 0.04, 0.28 ± 0.07, 0.25 ± 0.09, 0.21 ± 0.05 and MTR were 0.12 ± 0.03, 0.15 ± 0.06, 0.21 ± 0.07, 0.26 ± 0.06, respectively. There were significant differences for all quantitative parameters between controls and mild CP; for NIC, PF, and ECVf between controls and progressive CP grades (p < 0.05). Area under curve for NIC, FF, T1Rt, ECVf, PF, and MTR in differentiating controls and mild CP were 1.00, 0.86, 0.95, 1.00, 0.90 and 0.84 respectively and for NIC, FF, ECVf and PF in differentiating controls and equivocal CP were 1.00, 0.76, 0.95 and 0.92 respectively., Conclusion: DECT and mpMRI were useful in quantifying pancreatic fibrosis and grading the severity of CP. NIC was the most accurate marker., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Prostate Imaging Reporting and Data System (PI-RADS) was designed to standardize the interpretation of multiparametric magnetic resonance imaging (MRI) of the prostate, aiding in assessing the probability of clinically significant prostate cancer. By providing a structured scoring system, it enables better risk stratification, guiding decisions regarding the need for biopsy and subsequent treatment options. In this article, we explore both the strengths and weaknesses of PI-RADS, offering insights into its updated diagnostic performance and clinical applications, while also addressing potential pitfalls using diverse, representative MRI cases., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: To explore the value of deep learning-based multi-parametric magnetic resonance imaging (mp-MRI) nomogram in predicting the Ki-67 expression in rectal cancer., Methods: The data of 491 patients with rectal cancer from two centers were retrospectively analyzed and divided into training, internal validation, and external validation sets. They were categorized into high- and low-expression group based on postoperative pathological Ki-67 expression. Each patient's mp-MRI data were analyzed to extract and select the most relevant features of deep learning, and a deep learning model was constructed. Independent predictive risk factors were identified and incorporated into a clinical model, and the clinical and deep learning models were combined to obtain a nomogram for the prediction of Ki-67 expression. The performance characteristics of the DL-model, clinical model, and nomogram were assessed using ROCs, calibration curve, decision curve, and clinical impact curve analysis., Results: The strongest deep learning features were extracted and screened from mp-MRI data. Two independent predictive factors, namely Magnetic Resonance Imaging T (mrT) staging and differentiation degree, were identified through clinical feature selection. Three models were constructed: a deep learning (DL)-model, a clinical model, and a nomogram. The AUCs of clinical model in the training, internal validation, and external validation set were 0.69, 0.78, and 0.67, respectively. The AUCs of the deep model and nomogram ranged from 0.88 to 0.98. The prediction performance of the deep learning model and nomogram was significantly better than the clinical model (P < 0.001)., Conclusion: The nomogram based on deep learning can help clinicians accurately and conveniently predict the expression status of Ki-67 in rectal cancer., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The adoption of multiparametric MRI (mpMRI) and the Prostate Imaging Reporting and Data System has significantly changed prostate cancer diagnosis and management. These advancements, alongside novel biomarkers and updated International Society of Uropathology grade groups, have improved cancer detection and prognostication. Despite this progress, varying levels of expertise in mpMRI among radiologists have resulted in inconsistent assessments, potentially leading to unnecessary procedures and diminished confidence in the modality. This review assesses the educational landscape for prostate MRI, highlighting available resources for radiologists at all professional stages. It emphasizes the need for targeted educational strategies to bridge knowledge gaps and improve patient care outcomes in prostate cancer management., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: To assess liver and spleen characteristics of a population with Gaucher disease (GD) using multiparametric MRI and MR elastography (MRE) for evaluation of diffuse liver and spleen disease, which includes liver fat fraction, liver and spleen volume and iron deposition, and liver and spleen stiffness correlated with DS3 Severity Scoring System for Gaucher disease (GD-DS3)., Methods: We prospectively evaluated 41 patients with type 1 Gaucher disease using a 3.0 T MRI and MRE between January 2019 and February 2020. Clinical, laboratory, and imaging data was collected. Mann-Whitney, Kruskal-Wallis, and Spearman's correlation were applied to evaluate liver and spleen MRI and MRE, clinical and laboratory variables, and GD-DS3. ERT and SRT treatment groups were compared., Results: Hepatomegaly was seen in 15% and splenomegaly in 42% of the population. Moderate and strong and correlations were found between liver and spleen iron overload (rho = 0.537; p = 0.002); between liver and spleen volume (rho = 0.692, p < 0.001) and between liver and spleen stiffness (rho = 0.453, p = 0.006). Moderate correlations were found between liver stiffness and GD-DS3 (rho = 0.559; p < 0.001) and between splenic volume and GD-DS3 (rho = 0.524; p = 0.001)., Conclusion: The prevalence of hepatosplenomegaly, liver fibrosis, and liver iron overload in treated patients with GD is low, which may be related to the beneficial effect of treatment. Liver MRE and splenic volume correlate with severity score and may be biomarkers of disease severity., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Bladder cancer (BC), predominantly comprising urothelial carcinomas (UCs), ranks as the tenth most common cancer worldwide. UCs with variant histology (variant UC), including squamous differentiation, glandular differentiation, plasmacytoid variant, micropapillary variant, sarcomatoid variant, and nested variant, accounting for 5-10% of cases, exhibit more aggressive and advanced tumor characteristics compared to pure UC. The Vesical Imaging-Reporting and Data System (VI-RADS), established in 2018, provides guidelines for the preoperative evaluation of muscle-invasive bladder cancer (MIBC) using multiparametric magnetic resonance imaging (mpMRI). This technique integrates T2-weighted imaging (T2WI), dynamic contrast-enhanced (DCE)-MRI, and diffusion-weighted imaging (DWI) to distinguish MIBC from non-muscle-invasive bladder cancer (NMIBC). VI-RADS has demonstrated high diagnostic performance in differentiating these two categories for pure UC. However, its accuracy in detecting muscle invasion in variant UCs is currently under investigation. These variant UCs are associated with a higher likelihood of disease recurrence and require precise preoperative assessment and immediate surgical intervention. This review highlights the potential value of mpMRI for different variant UCs and explores the clinical implications and prospects of VI-RADS in managing these patients, emphasizing the need for careful interpretation of mpMRI examinations including DCE-MRI, particularly given the heterogeneity and aggressive nature of variant UCs. Additionally, the review addresses the fundamental MRI reading procedures, discusses potential causes of diagnostic errors, and considers future directions in the use of artificial intelligence and radiomics to further optimize the bladder MRI protocol., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: To investigate the application value of multiparametric MRI in evaluating the expression status of human epithelial growth factor receptor 2 (HER2) in bladder cancer (BCa)., Methods: From April 2021 to July 2023, preoperative imaging manifestations of 90 patients with pathologically confirmed BCa were retrospectively collected and analyzed. All patients underwent multiparametric MRI including synthetic MRI, DWI, from which the T1, T2, proton density (PD) and apparent diffusion coefficient (ADC) values were obtained. The clinical and imaging characteristics as well as quantitative parameters (T1, T2, PD and ADC values) between HER2-positive and -negative BCa were compared using student t test and chi-square test. The diagnostic efficacy of parameters in predicting HER2 expression status was evaluated by calculating the area under ROC curve (AUC)., Results: In total, 76 patients (mean age, 63.59 years ± 12.84 [SD]; 55 men) were included: 51 with HER2-negative and 25 with HER2-positive BCa. HER2-positive group demonstrated significantly higher ADC, T1, and T2 values than HER2-negative group (all P < 0.05). The combination of ADC values and tumor grade yielded the best diagnostic performance in evaluating HER2 expression level with an AUC of 0.864., Conclusion: The multiparametric MR characterization can accurately evaluate the HER2 expression status in BCa, which may further guide the determination of individualized anti-HER2 targeted therapy strategies., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: Aimed to investigate the role of multiparametric magnetic resonance imaging (mp-MRI) in the diagnosis of granulomatous prostatitis caused by intravesical Bacillus Calmette-Guérin (BCG)., Methods: In this prospective, single-center study, 10 male patients who were given intravesical BCG due to intermediate- and high-risk bladder cancer were included. Before transurethral resection of bladder tumors (TURB), all patients were evaluated by mp-MRI, serum prostate-specific antigen (PSA), and digital rectal examination (DRE). Serum PSA levels and DRE findings were evaluated before and after intravesical BCG treatment. Prostate mp-MRI was performed for patients with elevated levels of serum PSA and/or with abnormal DRE findings. Then, MRI fusion + systematic prostate biopsy was performed. Demographic data of the patients before and after intravesical BCG were compared., Results: The average age of the patients was 66.9 years (55-87 years). While PSA was 1.7 ng/ml before intravesical BCG treatment, it was 4.3 ng/ml after intravesical BCG treatment (p = 0.005). PSA density (PSAD) was 0.04 and 0.10 before and after the treatment, respectively (p = 0.012). DRE findings of all patients were normal before the treatment. However, abnormal findings were detected in 80% of them after the treatment (p = 0.008). PI-RADS ≥ 3 lesions were found to be significantly higher in all patients after intravesical BCG (p = 0.004)., Conclusion: Granulomatous prostatitis is a rare complication of intravesical BCG. High PSA, abnormal DRE, and PI-RADS ≥ 3 lesions detected after intravesical BCG should suggest granulomatous prostatitis and unnecessary biopsies may be avoided., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: To investigate the MRI manifestations of the spontaneous intratumoral coagulative necrosis (iCN) in patients with hepatocellular carcinoma (HCC) and its value in predicting the postoperative early recurrence (≤ 2 years)., Methods: Patients with HCC who underwent preoperative multiparametric MRI between January 2015 and February 2019 were enrolled in this retrospective study. The MRI manifestations of iCNs on TIWI, T2WI, and ADC were recorded. The sensitivity and specificity of MRI for the detection of iCNs were also evaluated. A multivariable Cox proportional hazards model and the Kaplan-Meier method were used to verify the value of histologically-confirmed and MRI-identified iCNs, respectively, in predicting early recurrence., Results: A total of 163 patients (median age, 56 years; interquartile range, 49-64 years; 139 men) with HCCs were evaluated, of whom 27(16.6%) had histologically-confirmed iCNs. MRI identified 92.6% (25 of 27; 95% confidence interval [CI] 74.2%, 98.7%) of iCNs (sensitivity), with a specificity of 79.4% (78 of 136; 95% CI 71.4%, 85.7%), based on non-enhancement on post-contrast MRI. And the MRI-identified iCNs were characterized by a similar appearance to surrounding tumour tissue shown on pre-contrast MRI but not enhanced on post-contrast MRI. The multivariable Cox proportional hazards model revealed that only the presence of histologically-confirmed iCN was independently associated with early HCC recurrence (hazard ratio = 2.73; 95% CI 1.20, 6.21; P = 0.017). The Kaplan-Meier curve showed that the presence of MRI-identified iCN was also associated with early recurrence (P < 0.001)., Conclusion: Multiparametric MRI identified iCNs with high sensitivity and modest specificity. The presence of iCNs is associated with early HCC recurrence., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: There is not yet satisfactory performance data comparing multiparametric MRI (mpMRI) versus biparametric MRI (bpMRI) for detecting prostate cancer (PCa), particularly in high-risk populations. We compared both protocols for detecting overall PCa and clinically significant PCa (CS-PCa; defined as Grade Group ≥ 2) in a multiethnic urban population., Methods: We retrospectively reviewed electronic medical record data from men who underwent image-guided fusion prostate biopsy (FB) between 2016 and 2021 at our institution. Patient characteristics, Prostate Imaging Reporting and Data System (PI-RADS) scores, and FB outcomes were analyzed based on MRI protocol. Multivariate mixed-effects logistic regression models were used to examine associations of bpMRI versus mpMRI for detecting overall PCa and CS-PCa in targeted lesions, among all patients and stratified by race/ethnicity., Results: Overall, 566 men (44.0% Non-Hispanic Black [NHB]; 27.0% Hispanic) with 975 PI-RADS 3-5 lesions on MRI underwent FB. Of these, 312 (55%) men with 497 lesions underwent mpMRI and 254 (45%) men with 478 lesions underwent bpMRI. On multivariate analyses among all men, the odds of detecting overall PCa (OR = 1.18, 95% CI: 1.05-3.11, p = 0.031) and CS-PCa (OR = 2.15, 95% CI: 1.16-4.00, p = 0.014) on FB were higher for lesions identified on bpMRI than mpMRI. When stratified by race/ethnicity, the odds of detecting overall PCa (OR = 1.86; p = 0.15) and CS-PCa (OR = 2.20; p = 0.06) were not statistically different between lesions detected on bpMRI or mpMRI., Conclusion: BpMRI has similar diagnostic performance to mpMRI in detecting overall and CS-PCa within a racially/ethnically diverse population. BpMRI can be utilized for evaluating suspected CS-PCa among NHB and Hispanic men., (© 2024. The Author(s).)

Objective: To developed a magnetic resonance imaging (MRI) radiomics nomogram to identify adenocarcinoma at the cervix-corpus junction originating from the endometrium or cervix in order to better guide clinical treatment., Methods: Between February 2011 and September 2021, the clinicopathological data and MRI in 143 patients with histopathologically confirmed cervical adenocarcinoma (CAC, n = 86) and endometrioid adenocarcinoma (EAC, n = 57) were retrospectively analyzed at the cervix-corpus junction. Radiomics features were extracted from fat-suppressed T2-weighted imaging (FS-T2WI), diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) maps, and delayed phase contrast-enhanced T1-weighted imaging (CE-T1WI) sequences. A radiomics nomogram was developed integrating radscore with independent clinical risk factors. The area under the curve (AUC) was used to evaluate the diagnostic efficacy of the radscore, nomogram and two different experienced radiologists in differentiating CAC from EAC at the cervix-corpus junction, and Delong test was applied to compare the differences of their diagnostic performance., Results: In the training cohort, the AUC was 0.93 for radscore; 0.97 for radiomics nomograms; 0.85 and 0.86 for radiologists 1 and 2, respectively. Delong test showed that the differential efficacy of nomogram was significant better than those of radiologists in the training cohort (both P < 0.05)., Conclusions: The nomogram based on radscore and clinical risk factors could better differentiate CAC from EAC at the cervix-corpus junction than radiologists, and preoperatively and non-invasively identify the origin of adenocarcinoma at the cervix-corpus junction, which facilitates clinicians to make individualized treatment decision., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: To investigate the correlation between quantitative MR parameters and prognostic factors in prostate cancer (PCa)., Method: A total of 186 patients with pathologically confirmed PCa who underwent preoperative multiparametric MRI (mpMRI), including synthetic MRI (SyMRI), were enrolled from two medical centers. The histogram metrics of SyMRI [T1, T2, proton density (PD)] and apparent diffusion coefficient (ADC) values were extracted. The Mann‒Whitney U test or Student's t test was employed to determine the association between these histogram features and the prognostically relevant factors. Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the differentiation performance. Spearman's rank correlation coefficients were calculated to determine the correlations between histogram parameters and the International Society of Urological Pathology (ISUP) grade group as well as pathological T stage., Results: Significant correlations were found between the histogram parameters and the ISUP grade as well as pathological T stage of PCa. Among these histogram parameters, ADC&#95;minimum had the strongest correlation with the ISUP grade (r = - 0.481, p < 0.001), and ADC&#95;Median showed the strongest association with pathological T stage (r = - 0.285, p = 0.008). The ADC&#95;10th percentile exhibited the highest performance in identifying clinically significant prostate cancer (csPCa) (AUC 0.833; 95% CI 0.771-0.883). When discriminating between the status of different prognostically relevant factors, a significant difference was observed between extraprostatic extension-positive and -negative cancers with regard to histogram parameters of the ADC map (10th percentile, 90th percentile, mean, median, minimum) and T1 map (minimum) (p = 0.002-0.032). Moreover, histogram parameters of the ADC map (90th percentile, maximum, mean, median), T2 map (10th percentile, median), and PD map (10th percentile, median) were significantly lower in PCa with perineural invasion (p = 0.009-0.049). The T2 values were significantly lower in patients with seminal vesicle invasion (minimum, p = 0.036) and positive surgical margin (10th percentile, 90th percentile, mean, median, and minimum, p = 0.015-0.025)., Conclusion: Quantitative histogram parameters derived from synthetic MRI and ADC maps may have great potential for predicting the prognostic features of PCa., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: To determine whether multiparametric magnetic resonance imaging (MRI) radiomics-based machine learning methods can improve preoperative local staging in patients with endometrial cancer (EC)., Methods: Data of patients with histologically confirmed EC who underwent preoperative MRI were retrospectively analyzed and divided into a training or test set. Radiomic features extracted from multiparametric MR images were used to train and test the prediction of deep myometrial invasion (DMI) and cervical stromal invasion (CSI). Two radiologists assessed the presence of DMI and CSI on conventional MR images. A combined model incorporating a radiomic signature and conventional MR images was constructed and presented as a nomogram. Performance of the predictive models was assessed using the area under curve (AUC) in the receiver operating curve analysis and pairwise comparison using DeLong's test with Bonferroni correction., Results: This study included 198 women (training set = 138, test set = 60). Conventional MRI achieved AUCs of 0.837 and 0.799 for detecting DMI and 0.825 and 0.858 for detecting CSI in the training and test sets, respectively. The nomogram achieved AUCs of 0.928 and 0.869 for detecting DMI and 0.913 and 0.937 for detecting CSI in the training and test sets, respectively. The ability of the nomogram to detect DMI and CSI in the two sets was superior to that of conventional MRI (adjusted p < 0.05), except for the ability to detect CSI in the test set (adjusted p > 0.05)., Conclusion: A nomogram incorporating radiomics signature into conventional MRI improved the efficacy of preoperative local staging of EC., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: To study the detection of clinically significant prostate cancer (PCa) by readers with different experience, comparing performance with biparametric magnetic resonance imaging (bmMRI) and with the reference multiparametric (mpMRI)., Methods: Retrospective analysis of 68 patients with mpMRI of the prostate at 1.5 Tesla using a 32 phased-array coil. Forty-five patients (cases) underwent radical prostatectomy, whereas 23 (controls) had a negative prostate biopsy and ≥ 2.5 years of negative follow-up. Six observers (two with 1000 cases interpreted, two with 300, two with 100) performed the analysis first with bpMRI including diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) maps and T2-weighted (T2W) imaging in three planes and, after 1 month, with mpMRI, adding dynamic contrast enhancement (DCE). The performance was quantified by sensitivity (SNS), specificity (SPC) and area under the curve (AUC) of the ROC (Receiver Operating Characteristics) procedure., Results: Concordance within observers of equivalent experience was good (weighted Cohen's k ≈ 0.7). The two expert readers performed as well in bpMRI as in mpMRI (SNS = 0.91-0.96, AUC = 0.86-0.93; p ≥ 0.10); readers with 300 cases performed well in mpMRI, but significantly worse in bpMR: SNS = 0.58 versus 0.91 (p < 0.0001) and AUC = 0.73 versus 0.86 (p = 0.01); the limited experience of readers with 100 cases showed in mpMRI (SNS = 0.71; AUC = 0.77) and even more in bpMRI (SNS = 0.50; AUC = 0.68)., Conclusion: The study revealed the impact of the readers' experience when using bpMRI. The bpMRI without contrast media was a valid alternative for expert readers, whereas less experienced ones needed DCE to significantly boost SNS and AUC. Results indicate 700-800 cases as threshold for reliable interpretation with bpMRI.

Purpose: To assess the diagnostic accuracy of PI-RADS v2 categories ≥ 3 to detect clinically significant prostate cancer (csPCa) against histopathology of Transperineal Mapping Biopsy (TPMB)., Materials and Methods: IRB-approved retrospective cohort study included 47 men who had 3.0 T multi-parametric MRI (mpMRI) and TPMB of prostate. Two radiologists independently evaluated T2, DWI, ADC map, and DCE images using PI-RADS v2 categories. A third radiologist served as tie-breaker. PI-RADS v2 score (PS) ≥ 3 lesions were correlated with 3D model of TPMB (3DTPMB) results based on prostate sectors. Two groups of csPCa status were separately analyzed for accuracy measures at lesion and person levels: Group 1 with GS (Gleason Score) ≥ 7 and group 2 with tumor volume ≥ 0.5 cc. Inter-rater reliability for PS and MR lexicon was calculated., Results: Forty-seven patients with 3DTPMB had at least one lesion with PS ≥ 3 on mpMRI. PS of 5 had high PPV and high specificity of 100% at the lesion and person levels. Sensitivity of a PS ≥ 3 was 68.27% for group 1 and was 48.39% for group 2. Specificity was 93.56% for group 1 and was 95.53% for group 2. At the person level, sensitivity of PS ≥ 3 was 81.25% for group 1 and was 82.35% for group 2. Specificity was 32.26% for group 1 and was 53.85% for group 2., Conclusion: PI-RADS v2 category of 5 had high PPV and specificity; however, combined PS ≥ 3 had mixed performance in detection of csPCa.

Purpose: The aim of this study was to compare the complication rates between transrectal ultrasound (TRUS) systematic prostate biopsy and multiparametric magnetic resonance imaging (MRI)-TRUS fusion prostate biopsy techniques., Materials and Methods: This is a single-center retrospective study, institutional review board approved. Systematic TRUS and MRI-TRUS fusion prostate biopsy complication rates were compared in 967 men. A total of 319 patients were received systematic TRUS prostate biopsy and 648 patients underwent systematic TRUS + MRI-TRUS fusion prostate biopsy. Complications were divided into immediate (those that occurred during the hospital observation period) and late (those that occurred within 5 days after biopsy)., Results: Seventeen complications were observed in patients who received either a systematic prostate biopsy or MRI-TRUS fusion prostate biopsy. Severe complications were not observed in both groups. Among patients who underwent systematic prostate biopsy, 6 (1.9%) cases of complications were observed and between those who received MRI-TRUS fusion prostate biopsy 11 (1.7%) cases of complications after the procedure (p = 0.873) were observed, with no statistical difference between groups. Also, no statistical differences between early and late complication groups (p > 0.999) were observed., Conclusions: The complication rates were low in both groups, with no critical clinical outcomes and no significant difference of complication rates between systematic TRUS prostate biopsy and MRI-TRUS fusion prostate biopsy techniques.

Objective: To correlate the findings on 3T multiparametric prostate MRI using PIRADS version 2 with prostate biopsy results as the standard of reference., Materials and Methods: 134 consecutive treatment naive patients (mean age 64 years, range 41-82 years) underwent MRI-directed prostate biopsy. MRI-TRUS fusion biopsy was used for 77 (77/134 = 57.5%) patients, cognitive fusion for 51 (51/134 = 38.0%) patients, and 6 patients (6/134 = 4.5%) without a target nodule had systematic biopsy only. Out of the 1676 biopsy sites, 237 (237/1676 = 14.1%) were positive on MRI for a PIRADS 3, 4, or 5 nodule. Fifty-eight (58/134, 43.3%) patients had clinically significant prostate cancer (csPCa). The findings on MRI using PIRADS version 2 were correlated with the biopsy results., Results: The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of PIRADS ≥ 3 for csPCa were 89%, 76.5%, 89.7%, 31.7%, and 98.4%, respectively. The detection rates of csPCa for PIRADS 3, 4, and 5 nodules were 6.1% (4/66), 33.3% (42/126), and 64.4% (29/45), respectively. MRI did not identify a nodule in 23/1676 (1.4%) biopsy sites that contained csPCa. The MRI reader, biopsy operator, method of fusion biopsy, and zonal location of prostate nodule did not significantly affect the odds of having a biopsy result positive for csPCa., Conclusion: PIRADS ≥ 3 had high specificity and high negative predictive value for csPCa using biopsy results as the standard of reference. The presence of csPCa from a biopsy site was highly unlikely in the absence of a corresponding PIRADS ≥ 3 nodule.

Purpose: To compare the predictive roles of qualitative (PI-RADSv2) and quantitative assessment (ADC metrics), in differentiating Gleason pattern (GP) 3 + 4 from the more aggressive GP 4 + 3 prostate cancer (PCa) using radical prostatectomy (RP) specimen as the reference standard., Methods: We retrospectively identified treatment-naïve peripheral (PZ) and transitional zone (TZ) Gleason Score 7 PCa patients who underwent multiparametric 3T prostate MRI (DWI with b value of 0,1400 and where unavailable, 0,500) and subsequent RP from 2011 to 2015. For each lesion identified on MRI, a PI-RADSv2 score was assigned by a radiologist blinded to pathology data. A PI-RADSv2 score ≤ 3 was defined as "low risk," a PI-RADSv2 score ≥ 4 as "high risk" for clinically significant PCa. Mean tumor ADC (ADC T ), ADC of adjacent normal tissue (ADC N ), and ADC ratio (ADC T /ADC N ) were calculated. Stepwise regression analysis using tumor location, ADC T and ADC ratio , b value, low vs. high PI-RADSv2 score was performed to differentiate GP 3 + 4 from 4 + 3., Results: 119 out of 645 cases initially identified met eligibility requirements. 76 lesions were GP 3 + 4, 43 were 4 + 3. ADC ratio was significantly different between the two GP groups (p = 0.001). PI-RADSv2 score ("low" vs. "high") was not significantly different between the two GP groups (p = 0.17). Regression analysis selected ADC T (p = 0.03) and ADC ratio (p = 0.0007) as best predictors to differentiate GP 4 + 3 from 3 + 4. Estimated sensitivity, specificity, and accuracy of the predictive model in differentiating GP 4 + 3 from 3 + 4 were 37, 82, and 66%, respectively., Conclusions: ADC metrics could differentiate GP 3 + 4 from 4 + 3 PCa with high specificity and moderate accuracy while PI-RADSv2, did not differentiate between these patterns.