Comparing the diagnostic value of 68Ga-prostate-specific membrane antigen PET/CT and multiparametric MRI in pelvic lymph node metastasis of locally advanced prostate cancer.

Background: Multiparametric magnetic resonance imaging (mpMRI) is a commonly used method to diagnose pelvic lymph node metastasis (PLNM) in prostate cancer (PCa) patients, but there are few comparative studies on mpMRI and 68Ga-prostate-specific membrane antigen (PSMA) positron emission tomography (PET)/computed tomography (CT) in locally advanced PCa (LAPC) patients. Therefore, we designed a retrospective study to compare the diagnostic value of 68Ga-PSMA PET/CT and mpMRI for PLNM of LAPC. Methods: A retrospective study was performed on 50 patients with LAPC who underwent radical prostatectomy (RP) in Tongji Hospital from 2021 to 2023. All patients underwent PET/CT and mpMRI examination, and were diagnosed as LAPC before surgery, followed by robot-assisted laparoscopic prostatectomy or laparoscopic RP and extended pelvic lymph node dissection (ePLND). Routine postoperative pathological examination was performed. According to the results, the sensitivity, specificity, positive predictive value, and negative predictive value of 68Ga-PSMA PET/CT and mpMRI for the diagnosis of PLNM of LAPC were compared. Results: Among the 50 patients, the mean age was 65.5±10.3 years, the preoperative total serum prostate-specific antigen (PSA) was 30.7±12.3 ng/mL, and the Gleason score was 7 [7, 8]. The difference in diagnostic efficacy between 68Ga-PSMA PET/CT and mpMRI in the preoperative diagnosis of PLNM of PCa was determined by postoperative pathological results. Based on the number of patients who developed PLNM, the sensitivity, specificity, positive predictive value, and negative predictive value of 68Ga-PSMA PET/CT were as follows: 93.75%, 100.00%, 100.00%, 97.14%, and 68.75%, 97.06%, 91.67%, 86.84% for mpMRI, respectively. Based on the number of pelvic metastatic lymph nodes, the sensitivity, specificity, positive predictive value, and negative predictive value of 68Ga-PSMA PET/CT were 95.24%, 100.00%, 100.00%, 99.48%, and 65.08%, 99.13%, 89.13%, 96.30% for mpMRI, respectively. It turned out that PET/CT was more sensitive than mpMRI in detecting PLNM of PCa, and the difference was statistically significant. Conclusions: 68Ga-PSMA PET/CT is more sensitive than mpMRI in the detection of PLNM in patients with LAPC. It is a promising method in the diagnosis and preoperative assessment of PLNM in LAPC.

Comparison between Three Radiomics Models and Clinical Nomograms for Prediction of Lymph Node Involvement in PCa Patients Combining Clinical and Radiomic Features.

PURPOSE: We aim to compare the performance of three different radiomics models (logistic regression (LR), random forest (RF), and support vector machine (SVM)) and clinical nomograms (Briganti, MSKCC, Yale, and Roach) for predicting lymph node involvement (LNI) in prostate cancer (PCa) patients. MATERIALS AND METHODS: The retrospective study includes 95 patients who underwent mp-MRI and radical prostatectomy for PCa with pelvic lymphadenectomy. Imaging data (intensity in T2, DWI, ADC, and PIRADS), clinical data (age and pre-MRI PSA), histological data (Gleason score, TNM staging, histological type, capsule invasion, seminal vesicle invasion, and neurovascular bundle involvement), and clinical nomograms (Yale, Roach, MSKCC, and Briganti) were collected for each patient. Manual segmentation of the index lesions was performed for each patient using an open-source program (3D SLICER). Radiomic features were extracted for each segmentation using the Pyradiomics library for each sequence (T2, DWI, and ADC). The features were then selected and used to train and test three different radiomics models (LR, RF, and SVM) independently using ChatGPT software (v 4o). The coefficient value of each feature was calculated (significant value for coefficient ≥ ±0.5). The predictive performance of the radiomics models and clinical nomograms was assessed using accuracy and area under the curve (AUC) (significant value for p ≤ 0.05). Thus, the diagnostic accuracy between the radiomics and clinical models were compared. RESULTS: This study identified 343 features per patient (330 radiomics features and 13 clinical features). The most significant features were T2_nodulofirstordervariance and T2_nodulofirstorderkurtosis. The highest predictive performance was achieved by the RF model with DWI (accuracy 86%, AUC 0.89) and ADC (accuracy 89%, AUC 0.67). Clinical nomograms demonstrated satisfactory but lower predictive performance compared to the RF model in the DWI sequences. CONCLUSIONS: Among the prediction models developed using integrated data (radiomics and semantics), RF shows slightly higher diagnostic accuracy in terms of AUC compared to clinical nomograms in PCa lymph node involvement prediction.

Synchronous neuroendocine liver metastases in comparison to primary pancreatic neuroendocrine tumors on MRI and SSR-PET/CT.

Background: The study aimed to compare and correlate morphological and functional parameters in pancreatic neuroendocrine tumors (pNET) and their synchronous liver metastases (NELM), while also assessing prognostic imaging parameters. Methods: Patients with G1/G2 pNET and synchronous NELM underwent pretherapeutic abdominal MRI with DWI and 68Ga-DOTATATE/TOC PET/CT were included. ADC (mean, min), SNR_art and SNT_T2 (SNR on arterial phase and on T2) and SUV (max, mean) for three target NELM and pNET, as well as tumor-free liver and spleen (only in PET/CT) were measured. Morphological parameters including size, location, arterial enhancement, cystic components, T2-hyperintensity, ductal dilatation, pancreatic atrophy, and vessel involvement were noted. Response evaluation used progression-free survival (PFS) with responders (R;PFS>24 months) and non-responders (NR;PFS ≤ 24 months). Results: 33 patients with 33 pNETs and 95 target NELM were included. There were no significant differences in ADC and SUV values between NELM and pNET. 70% of NELM were categorized as hyperenhancing lesions, whereas the pNETs exhibited significantly lower rate (51%) of hyperenhancement (p<0.01) and significant lower SNR_art. NELM were qualitatively and quantitatively (SNR_T2) significantly more hyperintense on T2 compared to pNET (p=0.01 and p<0.001). NELM of R displayed significantly lower ADCmean value in comparison to the ADC mean value of pNET (0.898 versus 1.037x10-3mm²/s,p=0.036). In NR, T2-hyperintensity was notably higher in NELM compared to pNET (p=0.017). The hepatic tumor burden was significantly lower in the R compared to the NR (10% versus 30%). Conclusions: Arterial hyperenhancement and T2-hyperintensity differ between synchronous NELM and pNET. These findings emphasize the importance of a multifaceted approach to imaging and treatment planning in patients with these tumors as well as in predicting treatment responses.

Creating a novel multiparametric magnetic resonance imaging-based biopsy strategy for reducing unnecessary prostate biopsies: a retrospective cohort study.

Background: The overdiagnosis of prostate cancer (PCa) caused by unnecessary prostate biopsy has become a worldwide problem that urgently requires a solution. We aimed to reduce the unnecessary prostate biopsies and increase the detection rate of clinically significant PCa (csPCa) by creating a novel multiparametric magnetic resonance imaging (mpMRI)-based strategy. Methods: A total of 1,194 eligible patients who underwent transperineal prostate biopsies from January 2018 to December 2022 were included in this retrospective study. Of these patients, 1,080 who received prostate biopsies from January 2018 to July 2022 were regarded as cohort 1 for primary analysis, and 114 patients who received prostate biopsies from August 2022 to December 2022 were collected in cohort 2 for validation. All the mpMRI images were quantitatively evaluated by the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v. 2.1). The diagnostic performances were assessed through the receiver operating characteristic (ROC) curve and area under the curve (AUC) and were compared with the DeLong test. Cancer diagnosis-free survival analysis was performed using the Kaplan-Meier method and log-rank test. The primary endpoint of this study was clinically significant PCa with an International Society of Urological Pathology (ISUP) grade ≥2. Results: In cohort 1, the results of ROC curves demonstrated that the PI-RADS score had a higher diagnostic accuracy (AUC =0.898 for any-grade PCa; AUC =0.917 for csPCa) than did the other clinical variables (P<0.001). Under the novel mpMRI-based biopsy strategy, all patients with PI-RADS 1 can safely avoid prostate biopsy. For patients with PI-RADS 2, prostate biopsy should be considered for patients with prostate-specific antigen density (PSAD) ≥0.3 ng/mL2 and prostate volume <65 mL. As for patients with PI-RADS 3, structured surveillance programs can be a viable option if PSAD <0.3 ng/mL2 and prostate volume ≥65 mL. Finally, patients with a PI-RADS score of 4 and 5 should undergo prostate biopsy due to the high probability of clinically significant PCa. In the validation analysis of cohort 2, 48 patients were placed into a biopsy-spared group with no csPCa cases, while 66 patients were placed in a biopsy-needed group, with an csPCa detection rate of 50.0%. Overall, the novel strategy demonstrated a sensitivity, specificity, positive predictive value, and negative predictive value of 98.9%, 57.5%, 50.5%, and 99.2%, respectively, for diagnosing csPCa. Conclusions: An mpMRI-based biopsy strategy can effectively avoid about 40% of prostate biopsies and maintain a high detection rate for clinically significant PCa. It can further provide valuable guidance for patients and physicians in considering the necessity of prostate biopsy.

Clinical significance of prostate cancer identified by transperineal standard template biopsy in men with nonsuspicious multiparametric magnetic resonance imaging.

OBJECTIVE: Multiparametric magnetic resonance imaging (mpMRI) of the prostate has excellent sensitivity in detecting clinically significant prostate cancer (csCaP). However, whether a negative mpMRI in patients with a clinical suspicion of CaP can omit a confirmatory biopsy remains less understood and without consensus. Transperineal (TP) standard template biopsy (SBx) provides an effective approach to CaP detection. Our aim is to provide a comprehensive understanding of the CaP characteristics detected through TP SBx that are systematically overlooked by mpMRI. METHODS: We conducted a retrospective analysis of all men who underwent prebiopsy mpMRI and subsequent a 20-core TP SBx at our hospital from September 2019 to February 2021. Patients with suspicious mpMRI received a combined TP SBx and targeted biopsy (TBx) (suspicious group), while those without suspicious (negative) mpMRI and who proceeded to biopsy, received TP SBx only (nonsuspicious group). A negative mpMRI was defined as the absence of suspicious findings and/or the presence of low-risk areas with a PI-RADS score of ≤2. Subsequently, we compared and evaluated the clinical and biopsy characteristics between these 2 groups. RESULTS: We identified 301 men in suspicious group and 215 men in nonsuspicious group. The overall CaP detection rate and csCaP detection rate by TP SBx were 74.1%, 38.9% for suspicious group and 43.3%, 14.9% for nonsuspicious group, respectively. csCaP NPV of mpMRI was 85.1% with a csCaP prevalence 28.9%. The greatest percentage of cancer involvement (GPC) in biopsy core from nonsuspicious group was significantly lower than those of suspicious group (40% vs. 50%, p = 0.005), In multivariate logistic analysis, only PSAD > 0.15 ng/ml/cc was identified as an independent and significant predictor of csCaP in nonsuspicious group. CONCLUSION: Within our cohort, false-negative rates of mpMRI for csCaP are substantial, reaching 15%. Nonsuspicious cases may contain a large volume tumor since the high GPC of SBx. For cases with nonsuspicious imaging and higher PSAD, a confirmatory biopsy may be necessary due to the increased risk of missed csCaP by mpMRI.

Magnetic resonance radiographic features which might lead to misdiagnosis of muscle-invasive bladder cancer based on vesical imaging reporting and data system: the application experience of a single center.

Background: The Vesical Imaging Reporting and Data System (VI-RADS) has been widely used for diagnosing muscle-invasive bladder cancer (MIBC), yet instances of misdiagnosis persist. However, limited research discusses the factors affecting its accuracy. This study aimed to evaluate the diagnostic efficacy of the VI-RADS in our center and to preliminarily identify possible magnetic resonance imaging (MRI) characteristics of misdiagnosis. Methods: From January 2018 to February 2023, a consecutive series of 211 participants pathologically diagnosed with bladder cancer (BC) who underwent an MRI exam were retrospectively enrolled. MRI was interpreted by 2 radiologists with different levels of experience, the diagnostic performance was validated using the receiver operating characteristic (ROC) curve, and VI-RADS ≥4 was considered to indicate MIBC-positive status. The clinical and radiographic characteristics of the true-positive (TP), true-negative (TN), false-positive (FP), and false-negative (FN) groups were analyzed using Kruskal-Wallis test or Fisher exact test. Results: With VI-RADS ≥4 as the cutoff value, the area under the ROC curves (AUCs) were 0.951 (0.912-0.976) and 0.847 (0.791-0.893) for the more-experienced reader and less-experienced reader, respectively, with good interobserver agreement (κ=0.74105). The median tumor size in the TP (more experienced: 57 cases; less experienced: 44 cases) and FP (more experienced: 8 cases; less experienced: 9 cases) groups was larger than that in the TN (more experienced: 141 cases; less experienced: 139 cases) group for the more-experienced reader (TP: 28 mm; FP: 31 mm; TN: 19 mm; P<0.001 and P=0.031, respectively) and the less-experienced reader (TP: 31 mm; FP: 28 mm; TN: 19 mm; P<0.001 and P=0.042, respectively). The tumor base in the TP and FP groups was larger than that in the TN group for the more-experienced reader (TP: 37 mm; FP: 48 mm; TN: 15 mm; both P<0.001) and for the less-experienced reader (FP: 42 mm; FP: 36 mm; TN: 15 mm; P<0.001 and P=0.022, respectively). The median tumor base in the TP group was larger than that in the FN group for the less-experienced reader (TP: 42 mm; FN: 17 mm; P=0.004). Conclusions: We observed good to excellent AUCs with good interobserver agreement among radiologists with different levels of expertise using VI-RADS. Large tumor size and wide tumor base affected the accuracy of VI-RADS in MIBC diagnosis.

Diagnostic performance of multiparametric MRI based Vesical Imaging-Reporting and Data System (VI-RADS) scoring in discriminating between non-muscle invasive and muscle invasive bladder cancer.

Purpose: The purpose of the present study was to assess the diagnostic accuracy of the Vesical Imaging-Reporting and Data System (VI-RADS) scoring system in predicting muscle infiltration of bladder cancer (BC) on a pre-operative multiparametric magnetic resonance imaging (mpMRI). Methods: The prospective study enrolled patients with bladder lesions detected on a preliminary ultrasonography or cystoscopy. The patients underwent mpMRI on a 3T MRI scanner followed by surgery within 2 weeks. The tumours were assigned a VI-RADS score by 2 experienced abdominal radiologists. The VI-RADS score was compared with postoperative histopathological findings to confirm detrusor muscle infiltration. The diagnostic performance of VI-RADS for predicting muscle invasion was assessed by calculating sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy. Results: A total of 60 patients were included in the study with a male: female ratio of 4.4 : 1. Transurethral resection of bladder tumour (TURBT) was performed in 47 (78.4%) and radical cystectomy in 13 (21.6%) patients. 19 (31.7%) had non-muscle invasive invasive BC (NMIBCa) and 41 (68.3%) had muscle invasive BC (MIBCa) on histopathology. There was a significant association between VI-RADS score and its components with muscle invasion (p < 0.05). A VI-RADS score of ≥ 3 had a sensitivity of 97.56% (95% CI: 0.87-0.99%), specificity of 73.68% (95% CI: 0.49-0.91), positive predictive value of 88.9% (95% CI: 0.79-0.94), negative predictive value of 93.33% (95% CI: 0.66-0.99), and diagnostic accuracy of 90% (95% CI: 0.80-0.96) for prediction of muscle invasion. Conclusion: VI-RADS scoring system pre-operatively predicts the likelihood of muscle invasion in BC with a satisfactory diagnostic performance, and it should be incorporated in the diagnostic work-up of BC patients.

A multi-institutional study of 1,111 men with 4K score, multiparametric magnetic resonance imaging, and prostate biopsy.

OBJECTIVE: Prostate magnetic resonance imaging (MRI) and biomarkers are often used in conjunction to enhance the selection process for prostate biopsy. However, the optimal sequence of ordering these tests has not been established. A comprehensive evaluation was conducted on a large multi-institutional cohort of patients who underwent MRI, 4K score, and biopsy of the prostate to examine the impact of utilizing both tests vs. either test alone and to determine if the order in which these tests are administered affects the ability to detect clinically significant prostate cancer (csCaP). METHODS AND MATERIALS: We evaluated men from 8 different institutions who were referred for prostate cancer evaluation and underwent MRI, 4K score test, and prostate biopsy. The primary outcome was the presence of csCaP, defined as grade group 2 or higher cancer on a biopsy of the prostate. We used logistic regression, calibration plots, and decision curve analysis to evaluate using a 4K score or MRI alone vs. both tests together for detecting csCaP. In addition, we evaluated several strategies using one or both tests for selecting men for biopsy and compared them based on the proportion of biopsies avoided and the csCaP's missed. RESULTS: Among the 1,111 men who formed the final cohort, 553 (49.8%) had prostate cancer, and 353 (31.8%) had csCaP. We found that using MRI and 4K score together had better discrimination, calibration, and a higher clinical utility on decision curve analysis compared to using either test individually. Using both tests together resulted in fewer biopsies avoided and missed cancers compared to using either test alone. Strategies that sequence MRI and 4K score tests resulted in the largest biopsy reduction, with no appreciable difference between starting with an MRI vs. a biomarker. CONCLUSIONS: We found that using both an MRI and 4K score together was superior to using either test alone but found no appreciable difference between starting with an MRI vs. starting with a 4K score. Prospective studies are needed to identify the best strategy to sequence MRI and biomarkers in the evaluation of csCaP.

A scoring diagnostic system based on biparametric ultrasound features for prostate cancer risk assessment.

Background: Ultrasound has advantages in prostate cancer (PCa) detection and biopsy guidance but lacks a comprehensive quantitative evaluation model with multiparametric features. We aimed to construct a biparametric ultrasound (BU) scoring system for PCa risk assessment and to provide an option for clinically significant prostate cancer (csPCa) detection. Methods: From January 2015 to December 2020, 392 consecutive patients at Chongqing University Cancer Hospital who underwent BU (grayscale, Doppler flow imaging, and contrast-enhanced ultrasound) and multiparametric magnetic resonance imaging (mpMRI) before biopsy were retrospectively enrolled in the training set to construct the scoring system. From January 2021 to May 2022, 166 consecutive patients at Chongqing University Cancer Hospital were retrospectively enrolled in the validation set. The ultrasound system was compared with mpMRI, and the gold standard was a biopsy. The primary outcome was the detection of csPCa in any area with a Gleason score (GS) ≥3+4, and the secondary outcome was defined as a GS ≥4+3 and/or maximum cancer core length (MCCL) ≥6 mm. Results: Malignant association features in the nonenhanced biparametric ultrasound (NEBU) scoring system included echogenicity, capsule, and gland asymmetrical vascularity. In the biparametric ultrasound scoring system (BUS), the feature of contrast agent arrival time was added. In the training set, the area under the curves (AUCs) of the NEBU scoring system, BUS, and mpMRI were 0.86 [95% confidence interval (CI): 0.82-0.90], 0.86 (95% CI: 0.82-0.90), and 0.86 (95% CI: 0.83-0.90), respectively (P>0.05). Similar results were also observed in the validation set, in which the areas under the curves were 0.89 (95% CI: 0.84-0.94), 0.90 (95% CI: 0.85-0.95), and 0.88 (95% CI: 0.82-0.94), respectively (P>0.05). Conclusions: We constructed a BUS that showed efficacy and value for csPCa diagnosis as compared with mpMRI. However, in limited circumstances, the NEBU scoring system may also be an option.

Comparison of quantitative parameters and radiomic features as inputs into machine learning models to predict the Gleason score of prostate cancer lesions.

INTRODUCTION: The classification of prostate cancer (PCa) lesions using Prostate Imaging Reporting and Data System (PI-RADS) suffers from poor inter-reader agreement. This study compared quantitative parameters or radiomic features from multiparametric magnetic resonance imaging (mpMRI) or positron emission tomography (PET), as inputs into machine learning (ML) to predict the Gleason scores (GS) of detected lesions for improved PCa lesion classification. METHODS: 20 biopsy-confirmed PCa subjects underwent imaging before radical prostatectomy. A pathologist assigned GS from tumour tissue. Two radiologists and one nuclear medicine physician delineated the lesions on the mpMR and PET images, yielding 45 lesion inputs. Seven quantitative parameters were extracted from the lesions, namely T2-weighted (T2w) image intensity, apparent diffusion coefficient (ADC), transfer constant (KTRANS), efflux rate constant (Kep), and extracellular volume ratio (Ve) from mpMR images, and SUVmean and SUVmax from PET images. Eight radiomic features were selected out of 109 radiomic features from T2w, ADC and PET images. Quantitative parameters or radiomic features, with risk factors of age, prostate-specific antigen (PSA), PSA density and volume, of 45 different lesion inputs were input in different combinations into four ML models - Decision Tree (DT), Support Vector Machine (SVM), k-Nearest-Neighbour (kNN), Ensembles model (EM). RESULTS: SUVmax yielded the highest accuracy in discriminating detected lesions. Among the 4 ML models, kNN yielded the highest accuracies of 0.929 using either quantitative parameters or radiomic features with risk factors as input. CONCLUSIONS: ML models' performance is dependent on the input combinations and risk factors further improve ML classification accuracy.

Development of a novel nomogram for predicting clinically significant prostate cancer with the prostate health index and multiparametric MRI.

Introduction: On prostate biopsy, multiparametric magnetic resonance imaging (mpMRI) and the Prostate Health Index (PHI) have allowed prediction of clinically significant prostate cancer (csPCa). Methods: To predict the likelihood of csPCa, we created a nomogram based on a multivariate model that included PHI and mpMRI. We assessed 315 males who were scheduled for prostate biopsies. Results: We used the Prostate Imaging Reporting and Data System version 2 (PI-RADS V2) to assess mpMRI and optimize PHI testing prior to biopsy. Univariate analysis showed that csPCa may be identified by PHI with a cut-off value of 77.77, PHID with 2.36, and PI-RADS with 3 as the best threshold. Multivariable logistic models for predicting csPCa were developed using PI-RADS, free PSA (fPSA), PHI, and prostate volume. A multivariate model that included PI-RADS, fPSA, PHI, and prostate volume had the best accuracy (AUC: 0.882). Decision curve analysis (DCA), which was carried out to verify the nomogram's clinical applicability, showed an ideal advantage (13.35% higher than the model that include PI-RADS only). Discussion: In conclusion, the nomogram based on PHI and mpMRI is a valuable tool for predicting csPCa while avoiding unnecessary biopsy as much as possible.

Quantib Prostate Compared to an Expert Radiologist for the Diagnosis of Prostate Cancer on mpMRI: A Single-Center Preliminary Study.

Background: To evaluate the clinical utility of an Artificial Intelligence (AI) radiology solution, Quantib Prostate, for prostate cancer (PCa) lesions detection on multiparametric Magnetic Resonance Images (mpMRI). Methods: Prostate mpMRI exams of 108 patients were retrospectively studied. The diagnostic performance of an expert radiologist (>8 years of experience) and of an inexperienced radiologist aided by Quantib software were compared. Three groups of patients were assessed: patients with positive mpMRI, positive target biopsy, and/or at least one positive random biopsy (group A, 73 patients); patients with positive mpMRI and a negative biopsy (group B, 14 patients), and patients with negative mpMRI who did not undergo biopsy (group-C, 21 patients). Results: In group A, the AI-assisted radiologist found new lesions with positive biopsy correlation, increasing the diagnostic PCa performance when compared with the expert radiologist, reaching an SE of 92.3% and a PPV of 90.1% (vs. 71.7% and 84.4%). In group A, the expert radiologist found 96 lesions on 73 mpMRI exams (17.7% PIRADS3, 56.3% PIRADS4, and 26% PIRADS5). The AI-assisted radiologist found 121 lesions (0.8% PIRADS3, 53.7% PIRADS4, and 45.5% PIRADS5). At biopsy, 33.9% of the lesions were ISUP1, 31.4% were ISUP2, 22% were ISUP3, 10.2% were ISUP4, and 2.5% were ISUP5. In group B, where biopsies were negative, the AI-assisted radiologist excluded three lesions but confirmed all the others. In group-C, the AI-assisted radiologist found 37 new lesions, most of them PIRADS 3, with 32.4% localized in the peripherical zone and 67.6% in the transition zone. Conclusions: Quantib software is a very sensitive tool to use specifically in high-risk patients (high PIRADS and high Gleason score).

Real-Time MRI-Guided Prostate Interventions.

Prostate cancer (PCa) is the second most common cause of cancer death in males. Targeting MRI-visible lesions has led to an overall increase in the detection of clinically significant PCa compared to the prior practice of random ultrasound-guided biopsy of the prostate. Additionally, advances in MRI-guided minimally invasive focal treatments are providing new options for patients with PCa. This review summarizes the currently utilized real-time MRI-guided interventions for PCa diagnosis and treatment.

Multiparametric Magnetic Resonance Imaging in the Diagnosis of Clinically Significant Prostate Cancer: an Updated Systematic Review.

There has been growing utilisation of multiparametric magnetic resonance imaging (MPMRI) as a non-invasive tool to diagnose and localise clinically significant prostate cancer (CSPCa). This updated systematic review examines the use of MPMRI in patients with an elevated risk of CSPCa who have had a prior negative transrectal ultrasound systematic biopsy (TRUS-SB) and who were biopsy naïve. MEDLINE, EMBASE and the Cochrane Database of Systematic Reviews were searched for existing systematic reviews published up to September 2020. The literature search of the electronic databases combined disease-specific terms (prostate cancer, prostate carcinoma, etc.) and treatment-specific terms (magnetic resonance, etc.). Studies were included if they were randomised controlled trials (RCTs) comparing MPMRI to template transperineal mapping biopsy (TPMB) or to TRUS-SB. Thirty-six RCTs were eligible. For biopsy-naïve men, accuracy of diagnosis of CSPCa showed sensitivities from 87 to 96% and specificities ranging from 29 to 45%. Meta-analyses for CSPCa showed increased detection favouring MPMRI-targeted biopsy over TRUS-SB by 3% (95% confidence interval 0-7%, P = 0.03) and decreased detection of clinically insignificant prostate cancer (CISPCa) favouring MPMRI by 8% (95% confidence interval -11 to 5%, P < 0.00001). Accuracy of MPMRI for men with prior negative biopsy showed sensitivities of 78-100% and specificities of 30-100%. Meta-analyses comparing MPMRI to TRUS-SB showed increased detection of 5% (95% confidence interval 3-7%, P < 0.0001) with a reduction of CISPCa detection of 7% (95% confidence interval 4-9%, P < 0.00001). The growing acceptance of MPMRI utilisation internationally and the recent publication of several RCTs regarding MPMRI in reducing CISPCa detection rates, particularly in biopsy-naïve men, without loss of sensitivity for CSPCa necessitates the synthesis of updated evidence examining MPMRI in the diagnosis of CSPCa.

Development and validation of a nomogram based on multiparametric magnetic resonance imaging and elastography-derived data for the stratification of patients with prostate cancer.

BACKGROUND: This study sought to develop and validate a nomogram combining the elastographic Q-analysis score (EQS), the Prostate Imaging Reporting and Data System (PI-RADS) score, and clinical parameters for the stratification of patients with prostate cancer (PCa). METHODS: A retrospective study was conducted of 375 patients with 375 lesions who underwent volume-navigation transrectal ultrasound (TRUS) and multiparametric magnetic resonance imaging (MP-MRI)-fusion targeted biopsies between April 2017 and January 2020. Based on a multivariate logistic regression model, a nomogram was created to assess any PCa and high-risk PCa [Gleason score (GS) ≥4+3] using data from patients diagnosed between April 2017 and June 2019 (n=271), and was validated in patients diagnosed after July 2019 (n=104). The nomogram's performance was evaluated based on its discrimination, calibration, and clinical usefulness. RESULTS: The areas under the curve (AUCs) of the nomogram for predicting any PCa and high-risk PCa were 0.949 [95% confidence interval (CI), 0.921 to 0.978] and 0.936 (95% CI, 0.906 to 0.965), respectively, in the training cohort, and 0.946 (95% CI, 0.894 to 0.997) and 0.971 (95% CI, 0.9331 to 1), respectively, in the validation cohort. The nomogram was well calibrated, and no significant difference was found between the predicted and observed probabilities. A decision curve analysis (DCA) for the nomogram with and without the EQS showed that the threshold probability of for any PCa was <67%. CONCLUSIONS: The nomogram that combined elastography-derived and MP-MRI data was more clinically useful than the model based on PI-RADS and clinical parameters alone. Our nomogram could aid urologists to make decisions and avoid unnecessary biopsies.

Combining clinical and MRI data to manage PI-RADS 3 lesions and reduce excessive biopsy.

BACKGROUND: Prostate Imaging Reporting and Data System version 2 (PI-RADS V2) 3 category lesions are of intermediate status with an equivocal risk of presenting clinically significant prostate cancer (csPCa). How to avoid excessive biopsies while improving the csPCa detection rate in these lesions has always been a clinical problem that needed to be solved. The purpose of this study is to explore the csPCa diagnostic value of clinical and magnetic resonance imaging (MRI) data for peripheral and transitional zone (PZ and TZ, respectively) PI-RADS 3 lesions to aid in clinical decision-making and reduce excessive biopsies. METHODS: From March 2016 to October 2018, a total of 629 men who underwent a prostate MRI and subsequently biopsy were enrolled. Two radiologists (with 3 and 7 years of experience, respectively) independently reviewed and scored all images using the PI-RADS V2 scoring criteria. Clinical and MRI data of men with PI-RADS 3 index lesions were collected by another radiologist. Univariate and multivariate analyses were performed to identify the risk factors of csPCa. RESULTS: In a subset of 121 men with 121 PI-RADS 3 index lesions, 25.6% of the lesions (31/121) were PCa (Gleason score ≥6), and 11.6% (14/121) were csPCa (Gleason score ≥7). Further, 44.6% of lesions (54/121) were located in the PZ and 55.4% (67/121) in the TZ. For PZ lesions, 18.5% of the lesions (10/54) were csPCa. Prostate-specific antigen density (PSAD) (P=0.024) and age (P=0.026) were independent risk factors for csPCa in the multivariate logistic analysis. The combination of PSAD and age yielded an area under the curve (AUC) value of 0.816 for predicting csPCa. If biopsy had been restricted to patients with a PSAD ≥0.15 ng/mL2 or an age >68 years, 24.1% (13/54) of patients would have avoided biopsy but only 1 (10%) csPCa would have been missed, with a sensitivity of 80.0% and negative predictive value (NPV) of 92.3%. For TZ lesions, only 6.0% of the lesions (4/67) were csPCa. The PSA and PSAD values in the PI-RADS 3 TZ lesions were higher in the csPCa group (45.07 and 0.47 ng/mL2, respectively) than in the non-csPCa group (10.03 and 0.17 ng/mL2, respectively). CONCLUSIONS: CsPCa was detected at a relatively high rate in PI-RADS 3 PZ lesions. Combining PSAD and age could help to reduce excessive biopsies of such lesions. CsPCa is unlikely to be detected in PI-RADS 3 TZ lesions; thus, active surveillance may be an optimal choice for these lesions, especially among patients without high-risk factors.

Evaluation of Vesical Imaging-Reporting and Data System (VI-RADS) scoring system in predicting muscle invasion of bladder cancer.

BACKGROUND: To investigate the accuracy of using the Vesical Imaging-Reporting and Data System (VI-RADS) scoring system in prediction preoperative muscle invasion of bladder cancer. METHODS: The study retrospectively reviewed consecutive patients with bladder cancer who received multiparametric magnetic resonance imaging (MRI) between January 2017 and June 2019. Clinical and pathological parameters were collected. Bladder tumors were re-evaluated with 5-point VI-RADS scoring system by two experienced radiologists independently. The VI-RADS score was compared with postoperative pathology for each tumor for determining muscle invasion. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each VI-RADS cutoff. RESULTS: A total of 126 patients were included in analysis, with 82 patients received transurethral resection of bladder tumor (TURBt) while 44 underwent radical cystectomy. Fifty patients were muscle-invasive bladder cancer and 76 were non-muscle invasive tumor confirmed pathologically. VI-RADS score was only predictive factor to muscle invasion in multivariate analysis. Setting VI-RADS score greater than or equal to 4 reached the best sensitivity and specificity of 94.00% and 92.11%, with PPV and NPV value of 88.68% and 95.89%. CONCLUSIONS: VI-RADS score system is a promising and effective modality in determining detrusor muscle invasion of bladder cancer preoperatively.

Systematic sampling during MRI-US fusion prostate biopsy can overcome errors of targeting-prospective single center experience after 300 cases in first biopsy setting.

BACKGROUND: Multiparametric magnetic resonance imaging (mpMRI) and targeted biopsy have become an integral part of the diagnosis of prostate cancer (PCa), as recommended by the European Association of Urology Guidelines. The aim of the current study was to evaluate the performance of MRI and MRI-transrectal ultrasound (TRUS) fusion prostate biopsy as first biopsy setting in a tertiary center. METHODS: A cohort of 300 patients was included in the current analysis. All patients presented with clinical or biochemical suspicion of PCa and harbored at least one suspect lesion on mpMRI. MRI-TRUS fusion prostate biopsy, followed by 12 core systematic prostate biopsy were performed by the same operator using a rigid registration system. RESULTS: The mean age of the patients was 64 years (IQR: 58-68.5 years) and the mean PSA was 6.35 ng/mL (IQR: 4.84-9.46 ng/mL). Overall cancer and csPCa diagnosis rates were 47% and 40.66%. Overall PCa/csPCa detection rates were 20.4%/11.1%, 52%/45% and 68.5%/66.7% for PI-RADS lesions 3, 4 and 5 (P<0.001/P<0.0001). Larger lesion diameter and lesion volume were associated with PCa diagnosis (P=0.006 and P=0.001, respectively). MRI-TRUS fusion biopsy missed PCa diagnosis in 37 cases (of whom 48.6% ISUP 1) in comparison with 9 patients missed by systematic biopsy (of whom 11.1% ISUP 1). In terms of csPCa, systematic biopsy missed 77.7% of the tumors located in the anterior and transitional areas. The rate of csPCa was highest when targeted biopsy was associated with systematic biopsy: 86.52% vs. 68.79% for targeted biopsy vs. 80.14% for systematic biopsy, P=0.0004. In 60.6% of cases, systematic biopsy was positive for PCa at the same site as the targeted lesion. Of these patients, eight harbored csPCa and were diagnosed exclusively on systematic biopsy. CONCLUSIONS: MRI-TRUS fusion prostate biopsy improves the diagnosis of csPCa. The main advantage of an MRI-guided approach is the diagnosis of anterior and transitional area tumors. The best results in terms of csPCa diagnosis are obtained by the combination of MRI-TRUS fusion with systematic biopsy. The systematic biopsy performed during MRI-targeted biopsy could have an important role in overcoming errors of MRI-TRUS fusion systems.

Magnetic resonance imaging (MRI)-based radiomics for prostate cancer radiotherapy.

In radiotherapy (RT) of prostate cancer, dose escalation has been shown to reduce biochemical failure. Dose escalation only to determinate prostate tumor habitats has the potential to improve tumor control with less toxicity than when the entire prostate is dose escalated. Other issues in the treatment of the RT patient include the choice of the RT technique (hypo- or standard fractionation) and the use and length of concurrent/adjuvant androgen deprivation therapy (ADT). Up to 50% of high-risk men demonstrate biochemical failure suggesting that additional strategies for defining and treating patients based on improved risk stratification are required. The use of multiparametric MRI (mpMRI) is rapidly gaining momentum in the management of prostate cancer because of its improved diagnostic potential and its ability to combine functional and anatomical information. Currently, the Prostate Imaging, Reporting and Diagnosis System (PIRADS) is the standard of care for region of interest (ROI) identification and risk classification. However, PIRADS was not designed for 3D tumor volume delineation; there is a large degree of subjectivity and PIRADS does not accurately and reproducibly elucidate inter- and intra-lesional spatial heterogeneity. "Radiomics", as it refers to the extraction and analysis of large number of advanced quantitative radiological features from medical images using high throughput methods, is perfectly suited as an engine to effectively sift through the multiple series of prostate mpMRI sequences and quantify regions of interest. The radiomic efforts can be summarized in two main areas: (I) detection/segmentation of the suspicious lesion; and (II) assessment of the aggressiveness of prostate cancer. As related to RT, the goal of the latter is in particular to identify patients at high risk for metastatic disease; and the aim of the former is to identify and segment cancerous lesions and thus provide targets for radiation boost. The article is structured as follows: first, we describe the radiomic approach; and second, we discuss the radiomic pipeline as tailored for RT of prostate cancer. In this process we summarize the current efforts and progress in integrating mpMRI radiomics into the radiotherapeutic management of prostate cancer with emphasis placed on its role in treatment target definition, treatment plan strategizing, and prognostic assessment. The described concepts, methods and tools are not currently applicable to the radiation oncology practice outside of the research setting. More data are required in the form of clinical trials to assess the robustness of radiomics-based predictive models, and to maximize the efficacy of these models.

"Super-active surveillance": MRI ultrasound fusion biopsy and ablation for less invasive management of prostate cancer.

Multiparametric magnetic resonance imaging (mpMRI) of the prostate has allowed clinicians to better visualize and target suspicious lesions during biopsy. Targeted prostate biopsies give a more accurate representation of the true cancer volume and stage so that appropriate treatment or active surveillance can be selected. Advances in technology have led to the development of MRI and ultrasound fusion platforms used for targeted biopsies, monitoring cancer progression, and more recently for the application of focal therapy. Lesions visualized on mpMRI can be targeted for ablation with a variety of energy sources employed under both local and general anesthesia. Focal ablation may offer an alternative option for treating prostate cancer as compared to the well-established interventions of whole-gland radiation or prostatectomy. Focal ablation may also be an option for patients on active surveillance who wish to be even more "active" in their surveillance. In this review, we describe the advancements and development of fusion biopsies, the rationale behind focal therapy, and introduce focal ablative techniques for indolent prostate cancers ("super-active surveillance"), including cryoablation and focal laser ablation (FLA) and the subsequent MRI/biopsy surveillance.