Prostate Multiparametric Magnetic Resonance Imaging Research Articles

Enhancing bone metastasis prediction in prostate cancer using quantitative mpMRI features, ISUP grade and PSA density: a machine learning approach.

Bone metastasis is a critical complication in prostate cancer, significantly impacting patient prognosis and quality of life. This study aims to enhance bone metastasis prediction using machine learning (ML) techniques by integrating dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) perfusion features, International Society of Urological Pathology (ISUP) grade, and prostate-specific antigen (PSA) density. A retrospective analysis was conducted on 122 patients with histopathologically confirmed prostate cancer who underwent multiparametric prostate magnetic resonance imaging (mpMRI). Quantitative mpMRI features, PSA density, and ISUP grades were extracted and normalized. The dataset was balanced using oversampling and divided into training (70%) and test (30%) sets. Various ML models were developed and evaluated using area under the curve (AUC) metrics. Bone metastases were present in 26 patients (21.3%) at diagnosis. IAUGC and MaxSlope showed a statistically significant association with bone metastasis (p = 0.035, p = 0.050 respectively). The optimal PSA density cut-off value of 0.24 yielded a sensitivity of 0.88, specificity of 0.60, and AUC of 0.77. Machine learning models were developed using the dataset created with IAUGC, MaxSlope, ISUP grade, and PSA density values. Among the ML models, XGBoost demonstrated superior performance with validation and test AUCs of 91.5% and 92.6%, respectively, along with high precision (93.3%) and recall (93.1%). Integrating quantitative mpMRI features, ISUP grade, and PSA density through machine learning algorithms, particularly XGBoost, significantly improves the accuracy of bone metastasis prediction in prostate cancer patients. This approach can potentially reduce the need for additional imaging modalities and associated radiation exposure.

Predicting cancer detection rates from multiparametric prostate MRI: Beyond the PI-RADS classification system.

Although the Prostate Imaging-Reporting and Data System (PI RADS) categorization represents the standard method for assessing the risk of prostate cancer using prostate magnetic resonance imaging (MRI), there exists wide variation in cancer detection rates (CDRs) in real-world practice. We therefore evaluated the association of clinical and radiographic features with CDRs and developed a predictive model to improve clinical management. We identified men aged 18-89 years with elevated prostate-specfic antigen (PSA) or on active surveillance for prostate cancer who underwent MRI-ultrasound (US) fusion biopsy or in-bore MRI-targeted biopsy. The associations of features with the per-lesion CDR (Gleason 6- 10) and clinically significant (cs) CDR (Gleason 7-10) were examined using logistic regression, and results were operationalized into a predictive model. Targeted biopsy was performed for 347 lesions in 281 patients. Overall, the CDR was 49.0% and the csCDR was 28.0%. On multivariable analysis, increasing PI-RADS category, no prior prostate biopsies, smaller prostate size, and increasing PSA density were independently associated with higher CDR, while 0-1 prior prostate biopsies, and a solitary PI-RADS 3-5 lesion were associated with higher csCDR. A predictive model provided a greater net benefit than a strategy of performing biopsy in all PI-RADS 3-5 lesions across a wide range of threshold probabilities. Several clinical and radiographic features are independently associated with the risk of prostate cancer in men undergoing MRI-targeted biopsy. A predictive model based on these features can improve clinical decisions regarding biopsy compared to the conventional strategy of performing biopsy for all PI-RADS 3-5 lesions.

Patients' anxieties and fears: a comparison between transrectal prostate biopsy and prostate MRI.

Prostate biopsies are an invasive procedure that can lead to anxieties and fear before the examination. Prostate magnetic resonance imaging (MRI) is seen as a non-invasive test although it is known that "scanxiety" affects many patients. Transrectal ultrasound (TRUS)-guided prostate biopsies and multiparametric prostate MRI (mpMRI) are commonly used methods in patients with suspected prostate cancer (PCa). This study investigates fears and anxieties towards the TRUS and mpMRI. All patients scheduled for mpMRI or TRUS biopsy between January and December 2018 were asked to participate in this single-center study. A total of 196 completed questionnaires were returned and included. On a 5-point Likert scale the fear of the examination was lower for the mpMRI [1.53; 95% confidence interval (CI): 1.38 to 1.69] than for a TRUS biopsy (2.47; 95% CI: 2.21 to 2.71). In detail, patients with a scheduled TRUS biopsy had significantly higher levels for fear of pain [2.49 (95% CI: 2.19 to 2.78) vs. 1.51 (95% CI: 1.35 to 1.67); P<0.001] and fear of complications [2.71 (95% CI: 2.45 to 2.98) vs. 2.11 (95% CI: 1.89 to 2.32); P=0.001]. There was no relevant difference about the fact that patients knew what to expect [3.02 (95% CI: 2.68 to 3.35) vs. 2.99 (95% CI: 2.70 to 3.26); P=0.47] and the expectation that the examination will go over well [3.24 (95% CI: 2.92 to 3.57) vs. 3.27 (95% CI: 3.00 to 3.58); P=0.55]. On average, fear levels were moderate before mpMRI and TRUS biopsy. Patients are more afraid of TRUS biopsy than mpMRI but the differences were low. The biggest fear remains the fear of the result of the examinations independently of the method.

The predictive impact of hematological inflammatory markers in detecting prostate cancer in patients with PI-RADS 3 lesions on multiparametric magnetic resonance imaging.

The diagnostic accuracy of suspicious lesions that are classified as PI-RADS 3 in multiparametric prostate magnetic-resonance imaging (mpMRI) is controversial. This study aims to assess the predictive capacity of hematological inflammatory markers such as neutrophil-lymphocyte ratio (NLR), pan-immune-inflammation value (PIV), and systemic immune-response index (SIRI) in detecting prostate cancer in PI-RADS 3 lesions. 276 patients who underwent mpMRI and subsequent prostate biopsy after PI-RADS 3 lesion detection were included in the study. According to the biopsy results, the patients were distributed to two groups as prostate cancer (PCa) and no cancer (non-PCa). Data concerning age, PSA, prostate volume, PSA density, PI-RADS 3 lesion size, prostate biopsy results, monocyte counts (109/L), lymphocyte counts (109/L), platelet counts (109/L), neutrophils count (109/L) were recorded from the complete blood count. From these data; PIV value is obtained by monocyte × neutrophil × platelet/lymphocyte, NLR by neutrophil/lymphocyte, and SIRI by monocyte number × NLR. Significant variations in neutrophil, lymphocyte, and monocyte levels between PCa and non-PCa patient groups were detected (p = 0.009, p = 0.001, p = 0.005 respectively, p < 0.05). NLR, PIV, and SIRI exhibited significant differences, with higher values in PCa patients (p = 0.004, p = 0.001, p < 0.001 respectively, p < 0.05). The area under curve of SIRI was 0.729, with a cut-off value of 1.20 and with a sensitivity 57.70%, and a specificity of 68.70%. SIRI outperformed NLR and PIV in detecting PCa in PI-RADS 3 lesions, showcasing its potential as a valuable biomarker. Implementation of this parameter to possible future nomograms has the potential to individualize and risk-stratify the patients in prostate biopsy decision.

Prevalence and potential predictors of incidental prostate Cancer in patients undergoing surgery for Benign Prostatic obstruction: a retrospective study in the MRI era.

Despite advancements in prostate multiparametric magnetic resonance imaging (mpMRI) and fusion biopsy (FB), the management of incidental prostate cancer (IPCa) after surgery for benign prostatic obstruction (BPO) remains unclear. The aim of this retrospective study is to determine the prevalence of IPCa in our cohort and identify potential predictors for its occurrence. We enrolled patients underwent TURP or simple prostatectomy for BPO at our high-volume center between January 2020-December 2022. Data on age, pre-operative total PSA (tPSA) and PSA density (PSAd) levels, prostate volume, previous MRI, biopsies, specimen weight, rates of positive tissue slices, ISUP score and three-month tPSA were collected. Of 454 patients with negative digital rectal examination who underwent BPO surgery, 74 patients (16.3%) were found to have IPCa. Of these, 33 patients (44.6%) had undergone previous mpMRI. Among the patients who had mpMRI, 23 had negative mpMRI results for suspected prostate cancer, while 10 had positive mpMRI findings (PIRADS ≥ 3) but no evidence of tumor upon FB. KW analysis indicates that PSAd was statistically associated with higher ISUP score, while at univariable regression analysis negative mpMRI (p = 0.03) was the only potential predictor for IPCa. Among the ISUP groups, PSAd showed a correlation with the tumor, while negative mpMRI was protective against clinically significant PCa. In the era of mpMRI and FB, the IPCa rates found at our center is higher than reported in existing literature and if it were confirmed with further studies, maybe there is a need for expansion in urology guidelines.

The value of synthetic magnetic resonance imaging in the diagnosis and assessment of prostate cancer aggressiveness.

Synthetic magnetic resonance imaging (SyMRI) is a fast, standardized, and robust novel quantitative technique that has the potential to circumvent the subjectivity of interpretation in prostate multiparametric magnetic resonance imaging (mpMRI) and the limitations of existing MRI quantification techniques. Our study aimed to evaluate the potential utility of SyMRI in the diagnosis and aggressiveness assessment of prostate cancer (PCA). We retrospectively analyzed 309 patients with suspected PCA who had undergone mpMRI and SyMRI, and pathologic results were obtained by biopsy or PCA radical prostatectomy (RP). Pathological types were classified as PCA, benign prostatic hyperplasia (BPH), or peripheral zone (PZ) inflammation. According to the Gleason Score (GS), PCA was divided into groups of intermediate-to-high risk (GS ≥4+3) and low-risk (GS ≤3+4). Patients with biopsy-confirmed low-risk PCA were further divided into upgraded and nonupgraded groups based on the GS changes of the RP results. The values of the apparent diffusion coefficient (ADC), T1, T2 and proton density (PD) of these lesions were measured on ADC and SyMRI parameter maps by two physicians; these values were compared between PCA and BPH or inflammation, between the intermediate-to-high-risk and low-risk PCA groups, and between the upgraded and nonupgraded PCA groups. The risk factors affecting GS grades were identified via univariate analysis. The effects of confounding factors were excluded through multivariate logistic regression analysis, and independent predictive factors were calculated. Subsequently, the ADC+Sy(T2+PD) combined models for predicting PCA risk grade or GS upgrade were constructed through data processing analysis. The diagnostic performance of each parameter and the ADC+Sy(T2+PD) model was analyzed. The calibration curve was calculated by the bootstrapping internal validation method (200 bootstrap resamples). The T1, T2, and PD values of PCA were significantly lower than those of BPH or inflammation (P≤0.001) in both the PZ or transitional zone. Among the 178 patients with PCA, intermediate-to-high-risk PCA group had significantly higher T1, T2, and PD values but lower ADC values compared with the low-risk group (P<0.05), and the diagnostic efficacy of each single parameter was similar (P>0.05). The ADC+Sy(T2+PD) model showed the best performance, with an area under the curve (AUC) 0.110 [AUC =0.818; 95% confidence interval (CI): 0.754-0.872] higher than that of ADC alone (AUC =0.708; 95% CI: 0.635-0.774) (P=0.003). Among the 68 patients initially classified as PCA in the low-risk group by biopsy, PCA in the postoperative upgraded GS group had significantly higher T1, T2, and PD values but lower ADC values than did those in the nonupgraded group (P<0.01). In addition, the ADC+Sy(T2+PD) model better predicted the upgrade of GS, with a significant increase in AUC of 0.204 (AUC =0.947; 95% CI: 0.864-0.987) compared with ADC alone (AUC =0.743; 95% CI: 0.622-0.841) (P<0.001). Quantitative parameters (T1, T2, and PD) derived from SyMRI can help differentiate PCA from non-PCA. Combining SyMRI parameters with ADC significantly improved the ability to differentiate between intermediate-to-high risk PCA from low-risk PCA and could predict the upgrade of low-risk PCA as confirmed by biopsy.

Does the type of the previous biopsy affect the fusion prostate biopsy results?

BackgroundIt has been more than a decade since fusion prostate biopsy (FPB) has been used in the diagnosis of prostate cancer (PCa). Therefore, patients with a previous history of negative FPB and ongoing suspicion of PCa are beginning to emerge. This study investigated whether the first biopsy type (standard or fusion) should be effective in deciding on a second biopsy. MethodsMale patients aged 40–75, with a serum prostate-specific antigen (PSA) value of less than 10 ng/mL and a negative biopsy history within the last 24 months, who underwent FPB in our clinic due to persistent PSA elevation and/or suspicious multiparametric prostate magnetic resonance imaging (MpMRI) findings were included to the study. Patients were divided into groups according to the type of first biopsy (Group 1; those whose first biopsy was FPB, Group 2; those whose first biopsy was standard prostate biopsy). Some demographic and clinical data of the groups, as well as PCa detection rates, were compared. A p value of less than 0.05 was considered statistically significant. ResultsA total of 275 patients (Group 1: 84, Group 2: 191) were included in this study. The groups were similar in terms of age, PSA values before the first biopsy, PSA values before the second biopsy, family history of PCa, and prostate volume. PCa was detected at a higher rate in Group 2 than Group 1 (23% vs 15.5%, p = 0.044). ConcluisonThe data obtained from this study indicate that the type of initial biopsy should be taken into account when deciding on FPB in secondary patients with a previous negative biopsy history.

A new parameter to increase the predictive value of multiparametric prostate magnetic resonance imaging for clinically significant prostate cancer in targeted biopsies: lesion density

AimTo investigate the predictive value of lesion length in multiparametric prostate magnetic resonance imaging with respect to prostate volume for clinically significant prostate cancer diagnosis in targeted biopsies. Materials and methodsThe data of biopsy-naïve patients in the Turkish Urooncology Association Prostate Cancer Database who underwent targeted prostate biopsies were included in this study. Lesion density is calculated as the ratio of lesion length (mm) in MR to prostate volume (cc). The biopsy results were divided into either clinically significant or insignificant cancer and benign groups. The difference in parameters between groups is evaluated by multivariable analysis to determine independent risk factors for clinically significant prostate cancer diagnosis. ResultsA total of 590 lesion biopsies were included in the study. In univariable analysis, prostate-specific antigen (PSA), PSA density, number of cores taken, lesion length, lesion density, patient age, and digital rectal examination findings were found to be different at a statistically significant level between groups (P values, respectively: 0.001, <0.001, <0.001, <0.001, <0.001, 0.012, 0.001). Subgroup analysis demonstrated that the lesion density was still significantly different between groups for all Prostate Imaging - Reporting and Data System (PI-RADS) 3, 4, and 5 subgroups (P values, respectively: 0.001, <0.001, <0.001). The multivariable analysis demonstrated that lesion density, along with the number of cores taken and the PI-RADS score of the lesion is an independent risk factor for predicting clinically significant prostate cancer, with the highest odds ratio among all parameters (OR: 27.31 [CI: 7.9–94.0]). ConclusionThis study demonstrated that lesion size with respect to prostate volume is an important independent risk factor for the prediction of clinically significant prostate cancer in the lesion-targeted biopsy. Combined with the PI-RADS score and parameters like digital rectal examination (DRE) findings and PSA density may further increase predictive power and help clinicians decide whether to perform a biopsy in low-risk patients or perform a re-biopsy for high-risk patients subsequent to an initial negative biopsy.

Effect of Bacillus Calmette–Guerin Exposure on Prostate Cancer Detection Using Magnetic Resonance Imaging: A Cohort Study

BackgroundGranulomatous prostatitis is a medical condition that may mimic prostate cancer. PurposeGranulomatous prostatitis resulting from BCG-exposure can confound the diagnosis of prostate cancer based on prostate imaging and data system (PI-RADS) classification observed on multiparametric prostate magnetic resonance imaging (mpMRI). Study type, Population, Assessment and Statistical TestsA cohort study was conducted, enrolling consecutive males at risk for prostate cancer who underwent an mpMRI-targeted prostate biopsy between February 2016 and August 2023. The focus of the study was on prior BCG-exposure as adjuvant treatment for non–muscle-invasive urothelial carcinoma within the 3 years prior the magnetic resonance imaging (MRI). Exclusion criteria were a prior androgen deprivation therapy, prostate surgery or radiation, and BCG-exposure occurring more than 3 years and less than 3 months before the MRI. Chi-square, logistic-regression, statistical association, and homogeneity tests were used. ResultsTotal 712 patients, 899 biopsied lesions (218 PI-RADS 3, 521 PI-RADS 4 and 160 PI-RADS 5) and 20 patients with 30 lesions within the BCG-exposed cohort. Chi-square and logistic-regression tests showed an association between PI-RADS with malignancy and significant tumor (ST), considering PI-RADS3 as the reference (OR: 4.9 [95% CI, 3.4-7.1] for PI-RADS4 and OR: 21.7 [95% CI, 12.4-37.8] for PI-RADS5 for malignancy, and OR: 5.3 [95% CI, 3.2-8.7] for PI-RADS4 and OR: 16.5 [95% CI, 9.4-28.9] for PI-RADS5 regarding ST). A statistically significant negative association was demonstrated between malignancy and ST with respect to BCG-exposure (OR: 0.15 [95% CI, 0.06-0.39] and OR: 0.39 [95% CI, 0.15-1.0], respectively). Statistically significant risk-difference for malignancy in patients nonexposed to BCG regarding those exposed was 45% (61.6% vs. 16.7%) for PI-RADS4, and 68.5% (90.7% vs. 22.2%) and 42.7% (64.9% vs. 22.2%) concerning malignancy and ST for PI-RADS5, respectively. Data ConclusionsGranulomatous prostate reaction caused by BCG-exposure acts as confounding factor for prostate MRI interpretation. The risk of malignancy and significant tumor on targeted biopsy to PI-RADS 3, 4 and 5 is notably lower in exposed patients.

Long-term follow-up results of multiparametric prostate MRI and the prognostic value of PI-RADS: a single-center retrospective cohort study

We aim to examine the long-term outcomes of patients who underwent multiparametric prostate magnetic resonance imaging (mp-MRI) for suspected prostate cancer (PCa), specifically based on their initial Prostate Imaging Reporting and Data System (PI-RADS) categories and various clinical factors. Our secondary aim is to evaluate the prognostic value of the PI-RADS through the National Comprehensive Cancer Network (NCCN) risk group distribution. This research was conducted as a single-center retrospective cohort study in a tertiary care hospital. A total of 1,359 cases having at least one histopathological examination after the initial mp-MRI and/or adequate clinical/radiological follow-up data were included in the clinically significant PCa (cs-PCa) diagnosis-free survival analysis. Initial mp-MRI dates were accepted as the start of follow-up for the time-to-event analysis. The event was defined as cs-PCa diagnosis (International Society of Urological Pathology ≥2). Patients who were not diagnosed with cs-PCa during follow-up were censored according to predefined literature-based criteria at the end of the maximum follow-up duration with no reasonable suspicion of PCa and no biopsy indication. The impact of various factors on survival was assessed using a log-rank test and multivariable Cox regression. Subsequently, 394 cases diagnosed with PCa during follow-up were evaluated, based on initial PI-RADS categories and NCCN risk groups. Three main risk factors for cs-PCa diagnosis during follow-up were an initial PI-RADS 5 category, initial PI-RADS 4 category, and high MRI-defined PSA density (mPSAD), with average hazard ratios of 29.52, 14.46, and 3.12, respectively. The PI-RADS 3 category, advanced age group, and biopsy-naïve status were identified as additional risk factors (hazard ratios: 2.03, 1.54-1.98, and 1.79, respectively). In the PI-RADS 1-2 cohort, 1, 3, and 5-year cs-PCa diagnosis-free survival rates were 99.1%, 96.5%, and 93.8%, respectively. For the PI-RADS 3 cohort, 1, 3, and 5-year cs-PCa diagnosis-free survival rates were 94.9%, 90.9%, and 89.1%, respectively. For the PI-RADS 4 cohort, 1, 3, and 5-year cs-PCa diagnosis-free survival rates were 56.6%, 55.1%, and 55.1%, respectively. These rates were found to all be 24.2% in the PI-RADS 5 cohort. Considering the 394 cases diagnosed with PCa during follow-up, PI-RADS ≥4 cases were more likely to harbor unfavorable PCa compared to PI-RADS ≤3 cases (P < 0.001). In the PI-RADS 3 subgroup analysis, a low mPSAD (<0.15 ng/mL2) was found to be a protective prognostic factor against unfavorable PCa (P = 0.005). The PI-RADS category has a significant impact on patient management and provides important diagnostic and prognostic information. Higher initial PI-RADS categories are associated with decreased follow-up losses, a shorter time to PCa diagnosis, increased biopsy rates, a higher likelihood of developing cs-PCa during follow-up, and a worse PCa prognosis. Combining mPSAD with PI-RADS categories could enhance diagnostic stratification in the identification of cs-PCa.

3T multiparametric MRI’s accuracy in detecting prostate cancer using Prostate Imaging Reporting and Data System (PIRADS) version 2.1 with prostate biopsy as a reference

BackgroundMultiparametric magnetic resonance imaging (MRI) is valuable in detecting prostate cancer due to its high sensitivity to malignant lesions. It is commonly utilized to improve the identification of clinically significant cancers within the prostate. This study aimed to correlate the findings from 3T multiparametric MRI of the prostate using the updated Prostate Imaging Reporting and Data System version 2.1 (PIRADSv2.1) from 2019 with reference to prostate biopsy results. Additionally, PIRADSv2.1 was used to calculate the sensitivity, specificity, positive predictive value, and negative predictive value of the 3T multiparametric MRI of the prostate.Methods and materialsA retrospective study was conducted at a tertiary center, wherein we identified patients who underwent a prostate biopsy between June 2019 and June 2021 and had a corresponding MRI of the prostate performed at the same institution, evaluated with PIRADSv2.1 criteria.ResultsA total of 50 patients were eligible for final analysis. The prevalence of prostate cancer was 69% (95% confidence interval (CI) 54–81%). Receiver operating characteristic (ROC) curves were generated for 3T multiparametric MRI of the prostate using PIRADSv2.1 to diagnose prostate cancer; the area under the ROC curve was 0.81 (95% CI 0.68–0.95, p < 0.001). The sensitivity, specificity, positive predictive value, and negative predictive value of the 3T multiparametric prostate MRI using PIRADSv2.1 were 74.0%, 87.0%, 92.9%, and 59.1%, respectively.ConclusionsPIRADSv2.1 exhibited good overall performance in the diagnosis of prostate cancer.

Pearls and Pitfalls in Applying PI-RADS 2.1

AbstractThe use of Prostate Imaging Reporting and Data System (PI-RADS) with multiparametric magnetic resonance imaging (MRI) has significantly improved the detection of clinically significant prostate cancer (csPCa), but there are certain challenges that the reader may face. This review provides an overview of the pitfalls associated with the PI-RADS system for multiparametric prostate MRI (mpMRI), with suggestions/pearls to help overcome these pitfalls.PI-RADS assessment is hindered by several causes of false positives (FPs) and false negatives (FNs). In addition, there is wide variability in the positive predictive value (PPV) of the PI-RADS system across different centers, highlighting the need for improvement. While the negative predictive value (NPV) for csPCa is generally high, variations exist.This review discusses the pitfalls contributing to FNs, including MRI artifacts, such as susceptibility and motion artifacts. Techniques to optimize image acquisition, such as switching the phase encoding direction and reducing bowel peristalsis, are suggested to mitigate these artifacts. Improper b-value selection for diffusion-weighted imaging (DWI) is another pitfall, emphasizing the importance of using high b-values (≥1,400 s/mm2) to optimize neoplasm detection. Similarly, optimizing window settings to visualize csPCa, correctly positioning the endorectal coil, awareness of rare variants like mucinous adenocarcinoma and cribriform adenocarcinoma, and distinguishing central zone tumors from normal central zone are discussed.This article highlights the common pitfalls causing FPs, such as benign pathologies like prostatitis, granulomatous prostatitis, prostatic abscess, stromal BPH nodules, extruded BPH nodules, and prostatic calcifications. It also discusses the pitfalls related to normal anatomical structures, including the central zone, anterior fibromuscular stroma, thickened surgical capsule, neurovascular bundle, and periprostatic venous plexus. Techniques for carefully evaluating these entities' morphology and distribution of signal abnormalities are described to avoid overdiagnosing these as PCa. The article also addresses the pitfalls related to postintervention changes, including postbiopsy hemorrhage and artifacts caused by the UroLift procedure, while providing recommendations for managing these challenges.Finally, the pitfalls that may be encountered during staging, including evaluation for extraprostatic extension, and pelvic nodal and osseous metastases, are highlighted.

Early change in apparent diffusion coefficient as a predictor of response to neoadjuvant androgen deprivation and external beam radiation therapy for intermediate- to high-risk prostate cancer

To determine the role of serial apparent diffusion coefficient (ADC) as a biomarker for response to neoadjuvant androgen deprivation therapy (nADT) followed by external beam radiation therapy (EBRT) in intermediate- to high-risk prostate cancer (PCa) patients. This Health Insurance Portability and Accountability Act (HIPAA)-compliant, institutional review board (IRB)-approved prospective study included 12 patients with intermediate- to high-risk PCa patients prior to nADT and EBRT, who underwent serial serum prostate-specific antigen (PSA) and multiparametric prostate magnetic resonance imaging (mpMRI) at baseline (BL), 8-weeks after nADT initiation (time point [TP]1), 6-weeks into EBRT delivery (TP2), and 6-months after nADT initiation (TP3). Tumour volume (tVOL) and tumour and normal tissue ADC (tADC and nlADC) were determined at all TPs. tADC and nlADC dynamics were correlated with post-treatment PSA using Pearson's correlation coefficient. Paired t-tests compared pre/post-treatment ADC. There was a sequential decrease in PSA at all TPs, reaching their lowest values at TP3 post-treatment completion. Mean tADC increased significantly from baseline to TP1 (917.8±107.7×10-6 versus 1033.8±139.3×10-6 mm2/s; p<0.01), with no subsequent change at TP2 or TP3. Both percentage and absolute change in tADC from BL to TP1 correlated with post-treatment PSA (r=-0.666, r=-0.674; p=0.02). Post-treatment PSA in good responders (<0.1 ng/ml) versus poor responders (≥ 0.1 ng/ml) was associated with a greater increase in tADC from BL to TP1 (169.2±122.4×10-6 versus 22.9±75.5×10-6 mm2/s, p=0.03). This pilot study demonstrates the potential for early ADC metrics as a biomarker of response to nADT and EBRT in intermediate to high-risk PCA.

Utilization trend of prebiopsy multiparametric magnetic resonance imaging and its impact on prostate cancer detection: Real-world insights from a high-volume center in southwest China.

Data on the utilization and effects of prebiopsy prostate multiparametric magnetic resonance imaging (mpMRI) to support its routine use in real-world setting are still scarce. To evaluate the change of clinical practice of prebiopsy mpMRI over time, and assess its diagnostic accuracy. We retrospectively analyzed data from 6168 patients who underwent primary prostate biopsy (PBx) between January 2011 and December 2021 and had prostate-specific antigen (PSA) values ranging from 3 to 100 ng/mL. Prebiopsy MRI at the time of PBx. We performed general linear regression and to elucidate trends in the annual use of prebiopsy mpMRI and conducted multivariable logistic regression to evaluate the potential benefits of incorporating prebiopsy mpMRI for prostate cancer (PCa) detection. The utilization of prebiopsy mpMRI significantly increased from 9.2% in 2011 to 75.0% in 2021 (p < 0.001). In addition, prebiopsy mpMRI significantly reduced negative PBx by 8.6% while improving the detection of clinically significant PCa (csPCa) by 7.0%. Regression analysis showed that the utilization of prebiopsy mpMRI was significantly associated with a 48% (95% confidence interval [CI]: 1.19-1.84) and 36% (95% CI: 1.12-1.66) increased PCa detection rate in the PSA 3-10 ng/mL and 10-20 ng/mL groups, respectively; and a 34% increased csPCa detection rate in the PSA 10-20 ng/mL group (95% CI: 1.09-1.64). The retrospective design and the single center cohort constituted the limitations of this study. Our study demonstrated a notable rise in the utilization of prebiopsy mpMRI in the past decade. The adoption of this imaging technique was significantly associated with an increased probability of detecting prostate cancer. From 2011 to 2021, we demonstrated a steady increase in the utilization of prebiopsy mpMRI among biopsy-naïve men. We also confirmed the positive impact of prebiopsy mpMRI utilization on the detection of prostate cancer.

The importance of periprostatic fat tissue thickness measured by preoperative multiparametric magnetic resonance imaging in upstage prediction after robot-assisted radical prostatectomy.

We analyzed the surgical results of patients who were treated and followed up for prostate cancer in our clinic to predict the relationship between periprostatic adipose tissue and patients with and without pathologically upstaged disease. The study included patients who had undergone robot-assisted radical prostatectomy and preoperative multiparametric prostate magnetic resonance imaging between 18 February 2019 and 1 April 2022. The patients were divided into two groups, and the surgical and transrectal ultrasound-guided biopsy pathology results were compared according to tumor grade and distribution in 124 patients who met the selection criteria. We analyzed the relationships between upgrading/upstaging and periprostatic adipose tissue thickness (PPATT) and subcutaneous adipose tissue thickness (SATT) as measured in magnetic resonance imaging. The median PPATT was 4.03 mm, whereas the median SATT was 36.4 mm. Upgrading was detected in 45 patients (36.3%), and upstaging was detected in 42 patients (33.9%). A receiver operating characteristic regression analysis revealed that a PPATT >3 mm was a predictive factor for upstaging after radical prostatectomy (area under curve=0.623, 95% confidence interval [CI] 0.519-0.727, p=0.025). Multivariate logistic regression analyses revealed that prostate specific antigen density ≥0.15 ng/mL/cm3 (odds ratio [OR] 5.054, 95% CI 2.008-12.724, p=0.001), International Society of Urological Pathology grade ≥4 (OR 9.369, 95% CI 2.109-21.626, p=0.003) and higher PPATT (OR 1.358, 95% CI 1.081-1.707, p=0.009) were independent risk factors for upstaging after radical prostatectomy. We believe that the PPATT may be a predictive indicator for upstaging after robot-assisted laparoscopic radical prostatectomy.

Using an artificial intelligence model to detect and localize visible clinically significant prostate cancer in prostate magnetic resonance imaging: a multicenter external validation study.

An increasing number of patients with suspected clinically significant prostate cancer (csPCa) are undergoing prostate multiparametric magnetic resonance imaging (mpMRI). The role of artificial intelligence (AI) algorithms in interpreting prostate mpMRI needs to be tested with multicenter external data. This study aimed to investigate the diagnostic efficacy of an AI model in detecting and localizing visible csPCa on mpMRI a multicenter external data set. The data of 2,105 patients suspected of having prostate cancer from four hospitals were retrospectively collected to develop an AI model to detect and localize suspicious csPCa. The lesions were annotated based on pathology records by two radiologists. Diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) values were used as the input for the three-dimensional U-Net framework. Subsequently, the model was validated using an external data set comprising the data of 557 patients from three hospitals. Sensitivity, specificity, and accuracy were employed to evaluate the diagnostic efficacy of the model. At the lesion level, the model had a sensitivity of 0.654. At the overall sextant level, the model had a sensitivity, specificity, and accuracy of 0.846, 0.884, and 0.874, respectively. At the patient level, the model had a sensitivity, specificity, and accuracy of 0.943, 0.776, and 0.849, respectively. The AI-predicted accuracy for the csPCa patients (231/245, 0.943) was significantly higher than that for the non-csPCa patients (242/312, 0.776) (P<0.001). The lesion number and tumor volume were greater in the correctly diagnosed patients than the incorrectly diagnosed patients (both P<0.001). Among the positive patients, those with lower average ADC values had a higher rate of correct diagnosis than those with higher average ADC values (P=0.01). The AI model exhibited acceptable accuracy in detecting and localizing visible csPCa at the patient and sextant levels. However, further improvements need to be made to enhance the sensitivity of the model at the lesion level.

Targeted augmented reality-guided transperineal prostate biopsies study: initial experience.

Transperineal biopsy of magnetic resonance imaging (MRI)-detected prostate lesions is now the established technique used in prostate cancer (CaP) diagnostics. Virtual Surgery Intelligence (VSI) Holomedicine by Apoqlar (Hamburg, Germany) is a mixed reality (MR)/augmented reality (AR) software platform that runs on the HoloLens II system (Microsoft, Redford, USA). Multiparametric prostate MRI images were converted into 3D holograms and added into a MR space, enabling visualization of a 3D hologram and image-assisted prostate biopsy. The Targeted Augmented Reality-GuidEd Transperineal (TARGET) study investigated the feasibility of performing AR-guided prostate biopsies in a MR framework, using the VSI platform in patients with MRI-detected prostate lesions. Ten patients with a clinical suspicion of CaP on MRI (Prostate Imaging-Reporting and Data System, PI-RADS 4/5) were uploaded to the VSI HoloLens system. Two MR/AR-guided prostate biopsies were then acquired using the PrecisionPoint Freehand transperineal biopsy system. Cognitive fusion biopsies were performed as standard of care following the MR/AR-guided prostate biopsies. All 10 patients successfully underwent MR/AR-guided prostate biopsy after 3D MR images were overlaid on the patient's body. Prostatic tissue was obtained in all MR/AR-guided specimens. Seven patients (70%) had matching histology in both the standard and MR/AR-guided biopsies. The remaining three had ISUP (International Society of Urological Pathology) Grade 2 CaP. There were no immediate complications. We believe this is a world first. The initial feasibility data from the TARGET study demonstrated that an MR/AR-guided prostate biopsy utilizing the VSI Holomedicine system is a viable option in CaP diagnostics. The next stage in development is to combine AR images with real-time needle insertion and to provide further data to formally appraise the sensitivity and specificity of the technique.

Predictors of prostate cancer detection in MRI PI-RADS 3 lesions - Reality of a tertiary center.

The Prostate Imaging Reporting and Data System (PI-RADS) score reports the likelihood of a clinically significant prostate cancer (CsPCa) based on various multiparametric prostate magnetic resonance imaging (mpMRI) characteristics. The PI-RADS category 3 is an intermediate status, with an equivocal risk of malignancy. The PSA density (PSAD) has been proposed as a tool to facilitate biopsy decisions on PI-RADS category 3 lesions. The objective of this study is to determine the frequency of CsPCa, assess the diagnostic value of targeted biopsy and identify clinical predictors to improve the CsPCa detection rate in PI-RADS category 3 lesions. Between 1st January 2017 and 31st December 2022, a total of 1661 men underwent a prostate biopsy at our institution. Clinical and mpMRI data of men with PI-RADS 3 lesions was reviewed. The study population was divided into two groups: target group, including those submitted to systematic plus targeted biopsy versus non-target group when only systematic or saturation biopsy were performed. Patients with PI-RADS 3 lesions were divided into three categories based on pathological biopsy results: benign, clinically insignificant disease (score Gleason = 6 or International Society of Urologic Pathologic (ISUP) 1) and clinically significant cancer (score Gleason ≥ 7 (3+4) or ISUP ≥ 2) according to target and non-target group. Univariate and multivariate analyses were performed to identify clinical predictors to improve the CsPCa detection rate in PI-RADS category 3 lesions. A total of 130 men with PIRADS 3 index lesions were identified. Pathologic results were benign in 77 lesions (59.2%), 19 (14.6%) were clinically insignificant (Gleason score 6) and 34 (26.2%) were clinically significant (Gleason score 7 or higher). Eighty-seven of the patients were included in the target group (66.9%) and 43 in the non-target group (33.1%). The CsPCa detection was higher in the non-target group (32.6%, n = 14 vs 23.0%, n = 20 respectively). When systematic and target biopsies were jointly performed, if the results of systematic biopsies are not considered and only the results of target biopsies are taken into account, a CsPCa diagnosis would be missed on 9 patients. The differences of insignificant cancer and CsPCa rates among the target or non-target group were not statistically significant (p = 0.50 and p = 0.24, respectively). on multivariate analysis, the abnormal DRE and lesions localized in Peripheral zone (PZ) were significantly associated with a presence of CsPCa in PI-RADS 3 lesions (oR = 3.61, 95% CI [1.22,10.72], p = 0.02 and oR = 3.31, 95% CI [1.35, 8.11], p = 0.01, respectively). A higher median PSAD significantly predisposed for CsPCa on univariate analyses (p = 0.05), however, was not significant in the multivariate analysis (p = 0.76). In our population, using 0.10 ng/ml/ml as a cut-off to perform biopsy, 41 patients would have avoided biopsy (31.5%), but 5 cases of CsPCa would not have been detected (3.4%). We could not identify any statistical significance between other clinical and imagiological variables and CsPCa detection. PI-RADS 3 lesions were associated with a low likelihood of CsPCa detection. A systematic biopsy associated or not with target biopsy is essential in PI-RADS 3 lesions, and targeted biopsy did not demonstrate to be superior in the detection of CsPCa. The presence of abnormal DRE and lesions localized in PZ potentially predict the presence of CsPCa in biopsied PI-RADS 3 lesions.

The effect of the combination of prostate-specific antigen derivatives with multiparametric prostate magnetic resonance imaging scores on the negative predictive value of it in grey zone patients

ObjectiveTo calculate the negative predictive value (NPV) of negative multiparametric prostate magnetic resonance imaging (mpMRI), accepted as no lesions on images, when combined with prostate-specific antigen density (PSAD) and free/total prostate-specific antigen ratio (f/t PSA) in grey zone patients. Methods191 patients with PSA levels between 4−10 mg/mL and negative mpMRI were analyzed. The NPV of negative mpMRI was calculated according to a PSAD level of <0.15 ng/mL/mL, f/t PSA ratio of >0.15, and a combination of both. Patients were divided into three risk groups according to these two parameters, which were PSAD 0.01−0.07 ng/mL/mL and f/t PSA ratio ≥25 in a low-risk group, PSAD 0.08−0.15 ng/mL/mL, and f/t PSA ratio 0.15−0.24 in an intermediate-risk group and high-risk group, in which PSAD > 0.15 ng/mL/mL and f/t PSA ratio <15. ResultsNPV of negative mpMRI was 92.6% for clinically significant prostate carcinoma (CSPCa). It increased to 97.5% in a low-risk group and decreased to 33.3% for CSPCa in a high-risk group. NPV of negative mpMRI results were so close when combined with PSAD < 0.15 ng/mL/mL and f/t PSA > 15. Conclusionf/t PSA ratio might also be used to increase the NPV of mpMRI, like PSAD. We advise not to avoid prostate biopsy when PSAD is >0.15 ng/mL/mL and the f/t PSA ratio is <0.15. However, we need randomized controlled studies with more patients to confirm our study.

The Role of Multiparametric MRI in the Local Staging of Prostate Cancer.

Prostate cancer ranks as the second most frequently diagnosed cancer globally among men and stands as the fifth leading cause of cancer-related death in males. Hence, an early and precise diagnosis and staging are critical. Traditional staging is based on clinical nomograms but presents a lower performance than prostate multiparametric magnetic resonance imaging (mpMRI). Since tumor staging serves as the basis for risk stratification, prognosis, and treatment decision-making, the primary objective of mpMRI is to distinguish between organ-confined and locally advanced diseases. Therefore, this imaging modality has emerged as the optimal selection for the local staging of prostate cancer, offering incremental value in evaluating pelvic nodal disease and bone involvement, and supplying supplementary insights regarding the precise location and disease extension. As per the Prostate Imaging Reporting & Data System v2.1 guideline, a comprehensive and accurate mpMRI requires several key sequences, which include T1-weighted imaging (T1WI) and T2-weighted imaging (T2WI) for morphological assessment, with T2WI serving as the cornerstone for local staging. Additionally, diffusion-weighted imaging (DWI) and dynamic sequences acquired with intravenous administration of paramagnetic contrast medium (DCE) are crucial components. It is worth noting that while MRI exhibits high specificity, its sensitivity in diagnosing extracapsular extension, seminal vesicle invasion, and lymph node metastases is limited. Moreover, mpMRI has its own constraints and is not as effective in detecting distant metastases or evaluating lymph nodes, for which extended pelvic lymph node dissection remains the gold standard. This review aims to highlight the significance of mpMRI in prostate cancer staging and provide a practical approach to assessing extracapsular extension, seminal vesicle invasions, and the involvement of adjacent organs and lymph nodes.