Prostate Imaging Reporting and Data System Version 2.1: 2019 Update of Prostate Imaging Reporting and Data System Version 2

Evaluation of Extra-Prostatic Extension on Deep Learning-Reconstructed High-Resolution Thin-Slice T2-Weighted Images in Patients with Prostate Cancer

The aim of this study was to compare diagnostic performance for extra-prostatic extension (EPE) and image quality among three image datasets: conventional T2-weighted images (T2WIconv, slice thickness, 3 mm) and high-resolution thin-slice T2WI (T2WIHR, 2 mm), with and without deep learning reconstruction (DLR) in patients with prostatic cancer (PCa). A total of 88 consecutive patients (28 EPE-positive and 60 negative) diagnosed with PCa via radical prostatectomy who had undergone 3T-MRI were included. Two independent reviewers performed a crossover review in three sessions, in which each reviewer recorded five-point confidence scores for the presence of EPE and image quality using a five-point Likert scale. Pathologic topographic maps served as the reference standard. For both reviewers, T2WIconv showed better diagnostic performance than T2WIHR with and without DLR (AUCs, in order, for reviewer 1, 0.883, 0.806, and 0.772, p = 0.0006; for reviewer 2, 0.803, 0.762, and 0.745, p = 0.022). The image quality was also the best in T2WIconv, followed by T2WIHR with DLR and T2WIHR without DLR for both reviewers (median, in order, 3, 4, and 5, p < 0.0001). In conclusion, T2WIconv was optimal in regard to image quality and diagnostic performance for the evaluation of EPE in patients with PCa.

Defining the role of multiparametric MRI in predicting prostate cancer extracapsular extension

OBJECTIVES

To identify the predictive factors of prostate cancer extracapsular extension (ECE) in an institutional cohort of patients who underwent multiparametric MRI of the prostate prior to radical prostatectomy (RP).

PATIENTS AND METHODS

Overall, 126 patients met the selection criteria, and their medical records were retrospectively collected and analysed; 2 experienced radiologists reviewed the imaging studies. Logistic regression analysis was conducted to identify the variables associated to ECE at whole-mount histology of RP specimens; according to the statistically significant variables associated, a predictive model was developed and calibrated with the Hosmer-Lomeshow test.

RESULTS

The predictive ability to detect ECE with the generated model was 81.4% by including the length of capsular involvement (LCI) and intraprostatic perineural invasion (IPNI). The predictive accuracy of the model at the ROC curve analysis showed an area under the curve (AUC) of 0.83 [95% CI (0.76-0.90)], p < 0.001. Concordance between radiologists was substantial in all parameters examined (p < 0.001). Limitations include the retrospective design, limited number of cases, and MRI images reassessment according to PI-RADS v2.0.

CONCLUSION

The LCI is the most robust MRI factor associated to ECE; in our series, we found a strong predictive accuracy when combined in a model with the IPNI presence. This outcome may prompt a change in the definition of PI-RADS score 5.

Is multiparametric MRI always needed in biopsy-naïve patients with abnormal digital rectal examination? A single-institutional experience combining clinical and micro-ultrasonography-based factors to optimize prostate cancer detection

PURPOSE

To assess the diagnostic performance of microultrasound-targeted biopsy (microUSTBx) and systematic biopsy (SBx) in detecting clinically significant prostate cancer (csPCa) among men with abnormal digital rectal examination (DRE) and suspicious lesions at multiparametric magnetic resonance imaging (mpMRI), and to compare the diagnostic performance of this approach with a mpMRI-guided targeted biopsy (MTBx) plus SBx-based strategy.

METHODS

Biopsy-naïve men with suspicious lesions at mpMRI and abnormal DRE were prospectively evaluated between October 2017 and January 2023. csPCa detection rate by microUSTBx plus SBx and MTBx plus SBx was assessed and then compared by McNemar's test. The added value of prostate-specific antigen density (PSAd) was also evaluated.

RESULTS

Overall, 182 biopsy naïve men were included. MicroUSTBx plus SBx achieved comparable detection rate to MTBx plus SBx in diagnosis of ciPCa and csPCa (ciPCa: 9.3% [17/182] vs 10% [19/182]; csPCa: 63% [114/182] vs 62% [113/182]). MicroUSTBx outperformed MTBx (ciPCa: 5.5% [10/182] vs 6.0% [11/182]; csPCa: 57% [103/182] vs 54% [99/182]). Using microUSTBx plus SBx would have avoided 68/182 (37%) unnecessary mpMRI, while missing only 2/116 (1.7%) csPCa. The decision curve analysis of suspicious microUS plus PSAd ≥ 0.15 ng/ml showed higher net benefit in the ability to identify true positives and reduce the number of unnecessary prostate biopsy in this subcategory of patients.

CONCLUSIONS

The combination of microUSTBx and SBx showed equal diagnostic performance to an mpMRI-based approach in biopsy-naïve patients with an abnormal DRE. The combination of this approach with PSAd maximize the diagnostic accuracy while lowering the need for unnecessary biopsies.

Abbreviated MRI Protocols in the Abdomen and Pelvis

Abbreviated MRI (AMRI) protocols rely on the acquisition of a limited number of sequences tailored to a specific question. The main objective of AMRI protocols is to reduce exam duration and costs, while maintaining an acceptable diagnostic performance. AMRI is of increasing interest in the radiology community; however, challenges limiting clinical adoption remain. In this review, we will address main abdominal and pelvic applications of AMRI in the liver, pancreas, kidney, and prostate, including diagnostic performance, pitfalls, limitations, and cost effectiveness will also be discussed. Level of Evidence: 3 Technical Efficacy Stage: 3.

Quantitative MRI in the Local Staging of Prostate Cancer: A Systematic Review and Meta-Analysis

BACKGROUND

Local staging of prostate cancer (PCa) is important for treatment planning. Radiologist interpretation using qualitative criteria is variable with high specificity but low sensitivity. Quantitative methods may be useful in the diagnosis of extracapsular extension (ECE).

PURPOSE

To assess the performance of quantitative MRI markers for detecting ECE.

STUDY TYPE

Systematic review and meta-analysis.

SUBJECTS

4800 patients from 28 studies with histopathologically confirmed PCa on radical prostatectomy were pooled for meta-analysis. Patients from 46 studies were included for systematic review.

FIELD STRENGTH/SEQUENCE

Diffusion-weighted, T2-weighted, and dynamic contrast-enhanced MRI at 1.5 T or 3 T.

ASSESSMENT

PubMed, Embase, Web of Science, Scopus, and Cochrane databases were searched to identify studies on diagnostic test accuracy or association of any quantitative MRI markers with ECE. Results extracted by two independent reviewers for tumor contact length (TCL) and mean apparent diffusion coefficient (ADC-mean) were pooled for meta-analysis, but not for other quantitative markers including radiomics due to low number of studies available.

STATISTICAL TESTS

Hierarchical summary receiver operating characteristic (HSROC) curves were computed for both TCL and ADC-mean, but summary operating points were computed for TCL only. Heterogeneity was investigated by meta-regression. Results were significant if P ≤ 0.05.

RESULTS

At the 10 mm threshold for TCL, summary sensitivity and specificity were 0.76 [95% confidence interval (CI) 0.71-0.81] and 0.68 [95% CI 0.63-0.73], respectively. At the 15 mm threshold, summary sensitivity and specificity were 0.70 [95% CI 0.53-0.83] and 0.74 [95% CI 0.60-0.84] respectively. The area under the HSROC curves for TCL and ADC-mean were 0.79 and 0.78, respectively. Significant sources of heterogeneity for TCL included timing of MRI relative to biopsy.

DATA CONCLUSION

Both 10 mm and 15 mm thresholds for TCL may be reasonable for clinical use. From comparison of the HSROC curves, ADC-mean may be superior to TCL at higher sensitivities.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2.

A pilot study of an organised population-based testing programme for prostate cancer

OBJECTIVE

To determine the feasibility of a digitally automated population-based programme for organised prostate cancer testing (OPT) in Southern Sweden.

PATIENTS AND METHODS

A pilot project for a regional OPT was conducted between September 2020 and February 2021, inviting 999 randomly selected men aged 50, 56, or 62 years. Risk stratification was based on prostate-specific antigen (PSA) level, PSA density (PSAD), and bi-parametric prostate magnetic resonance imaging (MRI). Men with a PSA level of 3-99 ng/mL had an MRI, and men with elevated PSA level (≥3 ng/mL) had a urological check-up, including a digital rectal examination and transrectal ultrasonography (TRUS). Indications for targeted and/or systematic transrectal prostate biopsies were suspicious lesions on MRI (Prostate Imaging-Reporting and Data System [PI-RADS] 4-5) and/or PSAD > 0.15 ng/mL/mL. Additional indications for prostate biopsies were palpable tumours, PSA ratio < 0.1, or cancer suspicion on TRUS. Patient selection, mail correspondence, data collection, and algorithm processing were performed by an automated digital management system. Feasibility is reported descriptively.

RESULTS

A total of 418 men had a PSA test (42%), with increasing participation rates by age (50 years, 38%; 56 years, 44%; and 62 years, 45%). Among these, 35 men (8%) had elevated PSA levels (≥3 ng/mL: one of 139, aged 50 years; 10/143, aged 56 years; and 24/146, aged 62 years). On MRI, 16 men (48%) had a negative scan (PI-RADS < 3), seven men (21%) had PI-RADS 3, nine men (27%) had PI-RADS 4, and one man (3%) had PI-RADS 5. All men with PI-RADS 4 or 5 underwent prostate biopsies, as well as two men with PI-RADS 3 due to PSAD > 0.15 ng/mL/mL or a suspicious finding on TRUS. Prostate cancer was diagnosed in 10 men. Six men underwent active treatment, whereas four men were assigned to active surveillance.

CONCLUSION

Our OPT model is feasible from an operational point of view, but due to the limited scale of this study no conclusions can be made regarding the efficacy of the diagnostic model or outcome.

Prostagram magnetic resonance imaging in a screening population: Prostate Imaging-Reporting and Data System or Likert?

OBJECTIVE

To compare biopsy recommendation rates and accuracy of the Prostate Imaging-Reporting and Data System, version 2 (PI-RADSv2) with the Likert scale for detection of clinically significant and insignificant prostate cancer in men screened within the Imperial Prostate 1 Prostate Cancer Screening Trial Using Imaging (IP1-PROSTAGRAM).

PATIENTS AND METHODS

Men aged 50-69 years were screened with Prostagram MRI. Scans were prospectively reported using both PI-RADSv2 (excluding dynamic contrast-enhanced sequence score) and 5-point Likert scores by expert uro-radiologists. Systematic and targeted transperineal biopsy was recommended if the scan was scored ≥ 3, based on either reporting system. The proportion of patients recommended for biopsy and detection rates for Grade Groups (GGs) 1 and ≥ 2 were compared. Receiver operating characteristic (ROC) analysis was performed to compare performance.

RESULTS

A total of 406 men underwent Prostagram MRI. The median (interquartile range) age and prostate-specific antigen level were 57 (53-61) years and 0.91 (0.56-1.74) ng/mL, respectively. At MRI score ≥ 3, more patients were recommended for biopsy based on Likert criteria (94/406; 23%, 95% confidence interval [CI] 19.2%-27.6%) compared to PI-RADSv2 (72/406; 18%, 95% CI 14.2%-21.9%; P = 0.03). For MRI scores ≥ 4, PI-RADSv2 and Likert scales led to 43/406 (11%, 95% CI 7.9%-14.1%) and 35/406 (9%, 95% CI 6.2%-11.9%) men recommended for biopsy (P = 0.40). For GG ≥ 2 detection, PIRADSv2 and Likert detected 22% (95% CI 11.4%-30.8%, 14/72) and 16% (95% CI 9.5%-25.3%, 15/94), respectively (P = 0.56). For GG1 cancers detection these were 11% (95% CI 4.3%-19.6%, seven of 72) vs 11% (95% CI 4.7%-17.8%, nine of 94; P = 1.00). The accuracy of PI-RADSv2 and Likert scale was similar (area under the ROC curve 0.64 vs 0.65, P = 0.95).

CONCLUSIONS

In reporting non-contrast-enhanced Prostagram MRI in a screening population, the PI-RADSv2 and Likert scoring systems were equally accurate; however, Likert scale use led to more men undergoing biopsy without a subsequent increase in significant cancer detection rates. To improve reporting of Prostagram MRI, either the PI-RADSv2 or a modified Likert scale or a standalone scoring system should be developed.

PI-RADS Version 2.0 Versus Version 2.1: Comparison of Prostate Cancer Gleason Grade Upgrade and Downgrade Rates From MRI-Targeted Biopsy to Radical Prostatectomy

BACKGROUND. Precise risk stratification through MRI/ultrasound (US) fusion-guided targeted biopsy (TBx) can guide optimal prostate cancer (PCa) management. OBJECTIVE. The purpose of this study was to compare PI-RADS version 2.0 (v2.0) and PI-RADS version 2.1 (v2.1) in terms of the rates of International Society of Urological Pathology (ISUP) grade group (GG) upgrade and downgrade from TBx to radical prostatectomy (RP). METHODS. This study entailed a retrospective post hoc analysis of patients who underwent 3-T prostate MRI at a single institution from May 2015 to March 2023 as part of three prospective clinical trials. Trial participants who underwent MRI followed by MRI/US fusion-guided TBx and RP within a 1-year interval were identified. A single genitourinary radiologist performed clinical interpretations of the MRI examinations using PI-RADS v2.0 from May 2015 to March 2019 and PI-RADS v2.1 from April 2019 to March 2023. Upgrade and downgrade rates from TBx to RP were compared using chi-square tests. Clinically significant cancer was defined as ISUP GG2 or greater. RESULTS. The final analysis included 308 patients (median age, 65 years; median PSA density, 0.16 ng/mL2). The v2.0 group (n = 177) and v2.1 group (n = 131) showed no significant difference in terms of upgrade rate (29% vs 22%, respectively; p = .15), downgrade rate (19% vs 21%, p = .76), clinically significant upgrade rate (14% vs 10%, p = .27), or clinically significant downgrade rate (1% vs 1%, p > .99). The upgrade rate and downgrade rate were also not significantly different between the v2.0 and v2.1 groups when stratifying by index lesion PI-RADS category or index lesion zone, as well as when assessed only in patients without a prior PCa diagnosis (all p > .01). Among patients with GG2 or GG3 at RP (n = 121 for v2.0; n = 103 for v2.1), the concordance rate between TBx and RP was not significantly different between the v2.0 and v2.1 groups (53% vs 57%, p = .51). CONCLUSION. Upgrade and downgrade rates from TBx to RP were not significantly different between patients whose MRI examinations were clinically interpreted using v2.0 or v2.1. CLINICAL IMPACT. Implementation of the most recent PI-RADS update did not improve the incongruence in PCa grade assessment between TBx and surgery.

Computer-aided detection of prostate cancer in early stages using multi-parameter MRI: A promising approach for early diagnosis

BACKGROUND

Transrectal ultrasound-guided prostate biopsy is the gold standard diagnostic test for prostate cancer, but it is an invasive examination of non-targeted puncture and has a high false-negative rate.

OBJECTIVE

In this study, we aimed to develop a computer-assisted prostate cancer diagnosis method based on multiparametric MRI (mpMRI) images.

METHODS

We retrospectively collected 106 patients who underwent radical prostatectomy after diagnosis with prostate biopsy. mpMRI images, including T2 weighted imaging (T2WI), diffusion weighted imaging (DWI), and dynamic-contrast enhanced (DCE), and were accordingly analyzed. We extracted the region of interest (ROI) about the tumor and benign area on the three sequential MRI axial images at the same level. The ROI data of 433 mpMRI images were obtained, of which 202 were benign and 231 were malignant. Of those, 50 benign and 50 malignant images were used for training, and the 333 images were used for verification. Five main feature groups, including histogram, GLCM, GLGCM, wavelet-based multi-fractional Brownian motion features and Minkowski function features, were extracted from the mpMRI images. The selected characteristic parameters were analyzed by MATLAB software, and three analysis methods with higher accuracy were selected.

RESULTS

Through prostate cancer identification based on mpMRI images, we found that the system uses 58 texture features and 3 classification algorithms, including Support Vector Machine (SVM), K-nearest Neighbor (KNN), and Ensemble Learning (EL), performed well. In the T2WI-based classification results, the SVM achieved the optimal accuracy and AUC values of 64.3% and 0.67. In the DCE-based classification results, the SVM achieved the optimal accuracy and AUC values of 72.2% and 0.77. In the DWI-based classification results, the ensemble learning achieved optimal accuracy as well as AUC values of 75.1% and 0.82. In the classification results based on all data combinations, the SVM achieved the optimal accuracy and AUC values of 66.4% and 0.73.

CONCLUSION

The proposed computer-aided diagnosis system provides a good assessment of the diagnosis of the prostate cancer, which may reduce the burden of radiologists and improve the early diagnosis of prostate cancer.

Magnetic Resonance Imaging-guided Active Surveillance Without Annual Rebiopsy in Patients with Grade Group 1 or 2 Prostate Cancer: The Prospective PROMM-AS Study

Background

Multiparametric magnetic resonance imaging (mpMRI) may allow patients with prostate cancer (PC) on active surveillance (AS) to avoid repeat prostate biopsies during monitoring.

Objective

To assess the ability of mpMRI to reduce guideline-mandated biopsy and to predict grade group upgrading in patients with International Society of Urological Pathology grade group (GG) 1 or GG 2 PC using Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) scores. The hypothesis was that the AS disqualification rate (ASDQ) rate could be reduced to 15%.

Design setting and participants

PROMM-AS was a prospective study assessing 2-yr outcomes for an mpMRI-guided AS protocol. A 12 mo after AS inclusion on the basis of MRI/transrectal ultrasound fusion-guided biopsy (FBx), all patients underwent mpMRI. For patients with stable mpMRI (PRECISE 1-3), repeat biopsy was deferred and follow-up mpMRI was scheduled for 12 mo later. Patients with mpMRI progression (PRECISE 4-5) underwent FBx. At the end of the study, follow-up FBx was indicated for all patients.

Outcome measurements and statistical analysis

We calculated the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for upgrading to GG 2 in the GG 1 group, and to GG 3 in the GG 2 group on MRI. We performed regression analyses that included clinical variables.

Results and limitations

The study included 101 patients with PC (60 GG 1 and 41 GG 2). Histopathological progression occurred in 31 patients, 18 in the GG 1 group and 13 in the GG 2 group. Thus, the aim of reducing the ASDQ rate to 15% was not achieved. The sensitivity, specificity, PPV, and NPV for PRECISE scoring of MRI were 94%, 64%, 81%, and 88% in the GG 1 group, and 92%, 50%, 92%, and 50%, respectively, in the GG 2 group. On regression analysis, initial prostate-specific antigen (p < 0.001) and higher PRECISE score (4-5; p = 0.005) were significant predictors of histological progression of GG 1 PC. Higher PRECISE score (p = 0.009), initial Prostate Imaging-Reporting and Data System score (p = 0.009), previous negative biopsy (p = 0.02), and percentage Gleason pattern 4 (p = 0.04) were significant predictors of histological progression of GG 2 PC. Limitations include extensive MRI reading experience, the small sample size, and limited follow-up.

Conclusions

MRI-guided monitoring of patients on AS using PRECISE scores avoided unnecessary follow-up biopsies in 88% of patients with GG 1 PC and predicted upgrading during 2-yr follow-up in both GG 1 and GG 2 PC.

Patient summary

We investigated whether MRI (magnetic resonance imaging) scores can be used to guide whether patients with lower-risk prostate cancer who are on active surveillance (AS) need to undergo repeat biopsies. Follow-up biopsy was deferred for 1 year for patients with a stable score and performed for patients whose score progressed. After 24 months on AS, all men underwent MRI and biopsy. Among patients with grade group 1 cancer and a stable MRI score, 88% avoided biopsy. For patients with MRI score progression, AS termination was correctly recommended in 81% of grade group 1 and 92% of grade group 2 cases.

Microultrasound in the detection of the index lesion in prostate cancer

INTRODUCTION AND OBJECTIVE

The natural progression of prostate cancer is primarily driven by an index lesion (IL). Studies have shown that different metastases within the same patient arise from a single precursor cell. Therefore, our aim is to assess the effectiveness of transrectal microultrasound (MUS) in comparison to multiparametric magnetic resonance imaging (mpMRI) for detecting the IL in prostate cancer. We used quarter-mount pathological results as the reference standard for this evaluation.

MATERIALS AND METHODS

Three hundred and sixty-three patients who underwent Robot-Assisted Radical Prostatectomy (RARP) from June 2021 to August 2022 were included. All received mpMRI and MUS before RARP. MUS was performed by experienced operators blinded to mpMRI and biopsy results. The IL in the radical prostatectomy specimen was defined as the lesion with extraprostatic extension, the highest Grade Group (GG), or the largest tumor volume if the GG was the same. The correlation between imaging and final pathology findings was performed. A descriptive statistical analysis is presented.

RESULTS

The patients' prostates were analyzed in 12 regions (anterior/posterior, right/left, apex/mid/base). A total of 4308 regions were identified. Of these, 935 were involved by the ILs. Compared with final pathology, MUS demonstrated a sensitivity, specificity, PPV, and NPV of 68.7%, 96.3%, 80.8%, and 93.1%, respectively, while mpMRI showed a sensitivity, specificity, PPV, and NPV of 68.6%, 97.2%, 86.1%, and 92.5%, respectively, for the detection of the IL. Most of the lesions missed by MUS were located in the anterior zone (62%).

CONCLUSION

MUS exhibits a diagnostic performance similar to mpMRI when it comes to detecting the IL in prostate cancer. MUS is a cost-effective option, offers real-time evaluation, and has no delay in the acquisition process.

The PRIMARY Score: Diagnostic Performance and Added Value Compared With MRI in Detecting Clinically Significant Prostate Cancer

PURPOSE

Multiparametric MRI is the current standard for detecting clinically significant prostate cancer (csPCa). However, men with negative or equivocal MRI often undergo unnecessary biopsies due to concerns about false-negative results. The recently proposed 68 Ga-PSMA PET/CT-based PRIMARY score exhibited good diagnostic performance for csPCa. This study aimed to externally validate the performance of the PRIMARY score and evaluate its added diagnostic value to MRI triage in detecting csPCa.

PATIENTS AND METHODS

This retrospective cohort study included 431 men who underwent both 68 Ga-PSMA PET/CT and MRI before biopsy. Performance was assessed using the area under the receiver operating characteristic curve and the decision curve analysis. The PRIMARY score + MRI was considered positive for either PRIMARY score 3-5 or Prostate Imaging Reporting and Data System (PI-RADS) 4/5.

RESULTS

The prevalence of csPCa was 51.7% (223/431). The area under the receiver operating characteristic curve of the 5-level PRIMARY score for csPCa was significantly higher than that of MRI (0.873 vs 0.786, P < 0.001). For the entire group, sensitivity, specificity, positive predictive value, and negative predictive value of the PRIMARY score were 90.6%, 61.1%, 71.4%, and 85.8%, respectively, which outperformed 87.9%, 49.0%, 64.9%, and 79.1% of PI-RADS on MRI. The PRIAMRY score + MRI improved sensitivity (96.0% vs 87.9%, P < 0.001) and negative predictive value (91.5% vs 79.1%, P < 0.001) without compromising specificity and positive predictive value compared with MRI alone. This combined approach avoided 24.6% (106/431) of unnecessary biopsies, while missing 4.0% (9/223) of csPCa cases. The addition of the PRIMARY score in men with PI-RADS 1-3 showed a net benefit, but not in men with PI-RADS 4/5.

CONCLUSIONS

The PRIMARY score was superior to MRI in detecting csPCa, and its added diagnostic value was in men with negative or equivocal MRI results. The PRIMARY score + MRI improved negative predictive value and sensitivity for csPCa compared with MRI alone. Further prospective trials will validate whether men with clinical suspicion of csPCa but negative PRIMARY score + MRI can safely avoid unnecessary biopsies.

Risk factors for prostate cancer in men with false-negative mpMRI: A retrospective single center cohort study of image quality scores and clinical parameters

PURPOSE

To identify predictors of prostate cancer (PCa) and clinically significant prostate cancer (csPCa) in men with prior false-negative multiparametric MRI (mpMRI), focusing on image quality scoring systems and clinical parameters.

METHODS

In this IRB-approved retrospective single-center study, patients with a negative mpMRI (PI-RADS score ≤2) and subsequent prostate biopsies were included. Histopathological results served as reference standard. Welch's t-Test was conducted to identify significant differences in image quality scores (PI-QUAL and PSHS) between patients with and without PCa/csPCA. In addition, clinical parameters (age, BMI, PSA density) and image quality scores (PI-QUAL and PSHS) were examined as potential predictors of PCa/csPCa detection after a false-negative mpMRI in uni- and multivariate analyses.

RESULTS

Among 96 patients with negative mpMRI results, 44.8 % had PCa and 16.7 % had csPCa upon biopsy with histopathological confirmation. PI-QUAL scores were significantly lower in patients with PCa (p = 0.03) and csPCa (p = 0.005). PSHS scores were lower in patients with csPCa, but the difference was not statistically significant (p = 0.1). Higher age (p = 0.035) and a lower PI-QUAL score (p < 0.004) were predictors of subsequent csPCa detection upon biopsy, however, a lower PI-QUAL score was the only independent predictor of missed csPCa in false-negative mpMRIs.

CONCLUSIONS

Lower image quality scores were associated with missed PCa/csPCa in patients with false-negative mpMRIs, with PI-QUAL being an independent predictor of failed csPCa detection. This highlights the importance of image quality for prostate MRI and advocats the inclusion of its measurement into the standardized report.

Office-based Magnetic Resonance Imaging-guided Transperineal Prostate Biopsy Without Antibiotic Prophylaxis: A Real-world Clinical Utility Study

Background and objective

Advances in for magnetic resonance imaging (MRI)-guided transperineal biopsy (TPBx) techniques have facilitated outpatient prostate biopsies under local anaesthesia to lower postbiopsy infection rates. However, there is debate regarding antibiotic prophylaxis because of concerns regarding antibiotic resistance and interactions. Our objective was to assess the transition from office-based transrectal biopsy to TPBx performed under local anaesthesia without antibiotic prophylaxis despite potential risk factors for infectious complications.

Methods

We conducted a prospective assessment of 665 men undergoing office-based MRI-guided TPBx. The primary outcome was the rate of urosepsis or febrile urinary tract infections requiring hospitalisation and/or antibiotics within 2 wk after biopsy. Secondary outcomes included patient-reported procedure tolerability and the prostate cancer detection rate.

Key findings and limitations

TPBx using a median of nine cores per patient (range 4-15) detected prostate cancer in 534/665 men (80%). Only four men (0.6%) were hospitalised for suspected postbiopsy infection; no patient experienced urosepsis. The TPBx procedure was well tolerated, with low pain scores (median Visual Analogue Scale score of 2, interquartile range [IQR] 1-3) and positive patient ratings (median rating 1 [no problem], IQR 1-2). Limitations include the single-centre analysis and lack of randomisation for antibiotic prophylaxis.

Conclusions and clinical implications

An office-based TPBx strategy under local anaesthesia without antibiotic prophylaxis is well tolerated and has a very low risk of side effects. This approach should be considered as the standard of care. Further studies may determine if a subgroup of predisposed men could benefit from antibiotic prophylaxis.

Patient summary

For prostate biopsy the sampling needle can be inserted through the rectum or through the perineum, which is the skin between the rectum and the scrotum. Our study confirms that in everyday clinical practice, prostate biopsy via the perineum can be carried out under local anaesthetic and without routine use of antibiotics because of its lower risk of infection. Patients reported low pain scores and positive ratings for the overall experience.

The Probability of Metastases Within Different Prostate-specific Antigen Ranges Using Prostate-specific Membrane Antigen Positron Emission Tomography in Patients with Newly Diagnosed Prostate Cancer

Background and objectives

The association between prostate-specific antigen (PSA) level and probability of metastatic disease on prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) has not yet been established in patients with newly diagnosed prostate cancer (PCa). Our objective was to assess the probability of metastatic disease within different PSA ranges using PSMA PET/CT for initial staging of PCa, and to identify both the anatomical distribution and the predictors of metastases on PSMA PET/CT.

Methods

In total, 2193 patients with newly diagnosed PCa were retrospectively studied. PSMA PET/CT was performed for staging purposes between January 2017 and May 2022. The proportion of patients with PSMA-avid metastases, stratified by PSA level, was studied. A vast majority of patients in whom at least one high-risk prognostic factor was present underwent PSMA PET/CT. A multivariable logistic regression analysis was performed to identify the predictors of metastases on PSMA PET/CT using clinical, biochemical, radiological, and pathological variables.

Key findings and limitations

The median PSA level at PSMA PET/CT was 14.1 ng/ml. Any metastatic disease (miN1-M1a-c) was observed in 34.7% (763/2193) of all patients and distant metastases (miM1a-c) in 25.4% (557/2193) of patients. The presence of any metastatic disease increased with PSA levels, being 15.4% in men with PSA levels <10 ng/ml and 87.5% in men with PSA levels >100 ng/ml. The multivariable logistic regression analysis found significant associations between the presence of any metastatic disease and PSA subgroups, clinical tumor stage ≥T2, grade group >3, and radiological tumor stage ≥T3b.

Conclusions and clinical implications

This is the first large epidemiological study in patients with PCa demonstrating the association between PSA subgroups and metastatic disease on modern imaging PSMA PET/CT. Data from this study can be used to counsel patients on the probability of metastatic disease at the time of PSA screening and to provide guidance on existing guidelines.

Patient summary

The prostate-specific antigen level could be used to assess the risk of metastases on prostate-specific membrane antigen positron (PSMA) emission tomography/computed tomography (PET/CT). This knowledge is valuable for selecting patients who will benefit most from metastatic screening with PSMA PET/CT.

Active Surveillance for Prostate Cancer: Expanding the Role of MR Imaging and the Use of PRECISE Criteria

Multiparametric magnetic resonance (MR) imaging has had an expanding role in active surveillance (AS) for prostate cancer. It can improve the accuracy of prostate biopsies, assist in patient selection, and help monitor cancer progression. The PRECISE recommendations standardize reporting of serial MR imaging scans during AS. We summarize the evidence on MR imaging-led AS and provide a clinical primer to help report using the PRECISE criteria. Some limitations to both serial imaging and the PRECISE recommendations must be considered as we move toward a more individualized risk-stratified approach to AS.

Potential Clinical Applications of Dedicated Prostate Positron Emission Tomography

The diagnosis of prostate cancer (PCa) is usually based on transrectal or transperineal biopsies (from 12 to 24 samples) in most cases after the performance of a dedicated MRI and/or transrectal ultrasound. A small-dedicated PET scanner could improve spatial resolution and increase sensitivity, allowing a precise detection and location of the PCa foci, thus allowing an image-guided biopsy. In this short review, we will focus our attention on the potential application of a dedicated prostate PET scanner and on the prototype that has been already assembled for this purpose.

Multiregion sampling of de novo metastatic prostate cancer reveals complex polyclonality and augments clinical genotyping

De novo metastatic prostate cancer is highly aggressive, but the paucity of routinely collected tissue has hindered genomic stratification and precision oncology. Here, we leveraged a rare study of surgical intervention in 43 de novo metastatic prostate cancers to assess somatic genotypes across 607 synchronous primary and metastatic tissue regions plus circulating tumor DNA. Intra-prostate heterogeneity was pervasive and impacted clinically relevant genes, resulting in discordant genotypes between select primary restricted regions and synchronous metastases. Additional complexity was driven by polyclonal metastatic seeding from phylogenetically related primary populations. When simulating clinical practice relying on a single tissue region, genomic heterogeneity plus variable tumor fraction across samples caused inaccurate genotyping of dominant disease; however, pooling extracted DNA from multiple biopsy cores before sequencing can rescue misassigned somatic genotypes. Our results define the relationship between synchronous treatment-sensitive primary and metastatic lesions in men with de novo metastatic prostate cancer and provide a framework for implementing genomics-guided patient management.

Robustness of magnetic resonance imaging and positron emission tomography radiomic features in prostate cancer: Impact on recurrence prediction after radiation therapy

Background and purpose

Radiomic features from MRI and PET are an emerging tool with potential to improve prostate cancer outcomes. However, feature robustness due to image segmentation variations is currently unknown. Therefore, this study aimed to evaluate the robustness of radiomic features with segmentation variations and their impact on predicting biochemical recurrence (BCR).

Materials and methods

Multi-scanner, pre-radiation therapy imaging from 142 patients with localised prostate cancer was used. Imaging included T2-weighted (T2), apparent diffusion coefficient (ADC) MRI, and prostate-specific membrane antigen (PSMA)-PET. The prostate gland and intraprostatic tumours were manually and automatically segmented, and differences were quantified using Dice Coefficient (DC). Radiomic features including shape, first-order, and texture features were extracted for each segmentation from original and filtered images. Intraclass Correlation Coefficient (ICC) and Mean Absolute Percentage Difference (MAPD) were used to assess feature robustness. Random forest (RF) models were developed for each segmentation using robust features to predict BCR.

Results

Prostate gland segmentations were more consistent (mean DC = 0.78) than tumour segmentations (mean DC = 0.46). 112 (3.6 %) radiomic features demonstrated 'excellent' robustness (ICC > 0.9 and MAPD < 1 %), and 480 features (15.4 %) demonstrated 'good' robustness (ICC > 0.75 and MAPD < 5 %). PET imaging provided more features with excellent robustness than T2 and ADC. RF models showed strong predictive power for BCR with a mean area under the receiver-operator-characteristics curve (AUC) of 0.89 (range 0.85-0.93).

Conclusion

When using radiomic features for predictive modelling, segmentation variability should be considered. To develop BCR predictive models, radiomic features from the entire prostate gland are preferable over tumour segmentation-based features.

Multiparametric Approach to Breast Cancer With Emphasis on Magnetic Resonance Imaging in the Era of Personalized Breast Cancer Treatment

ABSTRACT

A multiparametric approach to breast cancer imaging offers the advantage of integrating the diverse contributions of various parameters. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is the most important MRI sequence for breast imaging. The vascularity and permeability of lesions can be estimated through the use of semiquantitative and quantitative parameters. The increased use of ultrafast DCE-MRI has facilitated the introduction of novel kinetic parameters. In addition to DCE-MRI, diffusion-weighted imaging provides information associated with tumor cell density, with advanced diffusion-weighted imaging techniques such as intravoxel incoherent motion, diffusion kurtosis imaging, and time-dependent diffusion MRI opening up new horizons in microscale tissue evaluation. Furthermore, T2-weighted imaging plays a key role in measuring the degree of tumor aggressiveness, which may be related to the tumor microenvironment. Magnetic resonance imaging is, however, not the only imaging modality providing semiquantitative and quantitative parameters from breast tumors. Breast positron emission tomography demonstrates superior spatial resolution to whole-body positron emission tomography and allows comparable delineation of breast cancer to MRI, as well as providing metabolic information, which often precedes vascular and morphological changes occurring in response to treatment. The integration of these imaging-derived factors is accomplished through multiparametric imaging. In this article, we explore the relationship among the key imaging parameters, breast cancer diagnosis, and histological characteristics, providing a technical and theoretical background for these parameters. Furthermore, we review the recent studies on the application of multiparametric imaging to breast cancer and the significance of the key imaging parameters.

Quality of T2-weighted MRI re-acquisition versus deep learning GAN image reconstruction: A multi-reader study

PURPOSE

To evaluate CycleGAN's ability to enhance T2-weighted image (T2WI) quality.

METHOD

A CycleGAN algorithm was used to enhance T2WI quality. 96 patients (192 scans) were identified from patients who underwent multiple axial T2WI due to poor quality on the first attempt (RAD1) and improved quality on re-acquisition (RAD2). CycleGAN algorithm gave DL classifier scores (0-1) for quality quantification and produced enhanced versions of QI1 and QI2 from RAD1 and RAD2, respectively. A subset (n = 20 patients) was selected for a blinded, multi-reader study, where four radiologists rated T2WI on a scale of 1-4 for quality. The multi-reader study presented readers with 60 image pairs (RAD1 vs RAD2, RAD1 vs QI1, and RAD2 vs QI2), allowing for selecting sequence preferences and quantifying the quality changes.

RESULTS

The DL classifier correctly discerned 71.9 % of quality classes, with 90.6 % (96/106) as poor quality and 48.8 % (42/86) as diagnostic in original sequences (RAD1, RAD2). CycleGAN images (QI1, QI2) demonstrated quantitative improvements, with consistently higher DL classifier scores than original scans (p < 0.001). In the multi-reader analysis, CycleGAN demonstrated no qualitative improvements, with diminished overall quality and motion in QI2 in most patients compared to RAD2, with noise levels remaining similar (8/20). No readers preferred QI2 to RAD2 for diagnosis.

CONCLUSION

Despite quantitative enhancements with CycleGAN, there was no qualitative boost in T2WI diagnostic quality, noise, or motion. Expert radiologists didn't favor CycleGAN images over standard scans, highlighting the divide between quantitative and qualitative metrics.

Interpretation of Prostate Magnetic Resonance Imaging Using Prostate Imaging and Data Reporting System Version 2.1: A Primer

Prostate magnetic resonance imaging (MRI) is increasingly being used to diagnose and stage prostate cancer. The Prostate Imaging and Data Reporting System (PI-RADS) version 2.1 is a consensus-based reporting system that provides a standardized and reproducible method for interpreting prostate MRI. This primer provides an overview of the PI-RADS system, focusing on its current role in clinical interpretation. It discusses the appropriate use of PI-RADS and how it should be applied by radiologists in clinical practice to assign and report PI-RADS assessments. We also discuss the changes from prior versions and published validation studies on PI-RADS accuracy and reproducibility.

Contemporary Approach to Prostate Imaging and Data Reporting System Score 3 Lesions

The aim of this article is to review the technical and clinical considerations encountered with PI-RADS 3 lesions, which are equivocal for clinically significant Prostate Cancer (csPCa) with detection rates ranging between 10% and 35%. The number of PI-RADS 3 lesions reported vary according to several factors including MRI quality and radiologist training/expertise among the most influential. PI-RADS v.2.1 updated definitions for scores 2 and 3 in the PZ and scores 1 and 2 in the TZ is reviewed. The role of DWI role is highlighted in the assessment of the TZ with the possibility of upgrading score 2 lesions to score 3 based on DWI score. Given the increased utilization for prostate MRI, biparametric MRI can be considered as an alternative for low-risk patients where there is a need to rule out csPCa acknowledging this technique may increase the number of indeterminate cases going for biopsies. Management of patients with equivocal lesions at mpMRI and factors influencing biopsy decision process remain as an unmet need and additional studies using molecular/imaging markers as well as artificial intelligence tools are needed to further address their role in proper patient selection for biopsy.

Update on Optimization of Prostate MR Imaging Technique and Image Quality

Prostate MR imaging quality has improved dramatically over recent times, driven by advances in hardware, software, and improved functional imaging techniques. MRI now plays a key role in prostate cancer diagnostic work-up, but outcomes of the MRI-directed pathway are heavily dependent on image quality and optimization. MR sequences can be affected by patient-related degradations relating to motion and susceptibility artifacts which may enable only partial mitigation. In this Review, we explore issues relating to prostate MRI acquisition and interpretation, mitigation strategies at a patient and scanner level, PI-QUAL reporting, and future directions in image quality, including artificial intelligence solutions.

Developing a diagnostic model for predicting prostate cancer: a retrospective study based on Chinese multicenter clinical data

The overdiagnosis of prostate cancer (PCa) caused by nonspecific elevation serum prostate-specific antigen (PSA) and the overtreatment of indolent PCa have become a global problem that needs to be solved urgently. We aimed to construct a prediction model and provide a risk stratification system to reduce unnecessary biopsies. In this retrospective study, clinical data of 1807 patients from three Chinese hospitals were used. The final model was built using stepwise logistic regression analysis. The apparent performance of the model was assessed by receiver operating characteristic curves, calibration plots, and decision curve analysis. Finally, a risk stratification system of clinically significant prostate cancer (csPCa) was created, and diagnosis-free survival analyses were performed. Following multivariable screening and evaluation of the diagnostic performances, a final diagnostic model comprised of the PSA density and Prostate Imaging-Reporting and Data System (PI-RADS) score was established. Model validation in the development cohort and two external cohorts showed excellent discrimination and calibration. Finally, we created a risk stratification system using risk thresholds of 0.05 and 0.60 as the cut-off values. The follow-up results indicated that the diagnosis-free survival rate for csPCa at 12 months and 24 months postoperatively was 99.7% and 99.4%, respectively, for patients with a risk threshold below 0.05 after the initial negative prostate biopsy, which was significantly better than patients with higher risk. Our diagnostic model and risk stratification system can achieve a personalized risk calculation of csPCa. It provides a standardized tool for Chinese patients and physicians when considering the necessity of prostate biopsy.

Prostate Cancer Local Staging with Magnetic Resonance Imaging

Accurate determination of the local stage of prostate cancer is crucial for treatment planning and prognosis. The primary objective of local staging is to distinguish between organ-confined and locally advanced disease, with the latter carrying a worse clinical prognosis. The presence of locally advanced disease features of prostate cancer, such as extra-prostatic extension, seminal vesicle invasion, and positive surgical margin, can impact the choice of treatment. Over the past decade, multiparametric MRI (mpMRI) has become the preferred imaging modality for the local staging of prostate cancer and has been shown to provide accurate information on the location and extent of disease. It has demonstrated superior performance compared to staging based on traditional clinical nomograms. Despite being a relatively new technique, mpMRI has garnered considerable attention and ongoing investigations. Therefore, in this review, we will discuss the current use of mpMRI on prostate cancer local staging.

Pitfalls in Prostate MR Imaging Interpretation

Multiparametric MR imaging of the prostate is an essential diagnostic study in the evaluation of prostate cancer. Several entities including normal anatomic structures, benign lesions, and posttreatment changes can mimic prostate cancer. An in depth understanding of the pitfalls is important for accurate interpretation of prostate MR imaging.

Evaluation of Prostate Cancer Recurrence with MR Imaging and Prostate Imaging for Recurrence Reporting Scoring System

Detection of prostate cancer recurrence after whole-gland treatment with curative intent is critical to identify patients who may benefit from local salvage therapy. Among the different imaging modalities used in clinical practice, MR imaging is the most accurate in identifying local prostate cancer recurrence; indeed, it is an excellent technique for local recurrence detection superior to PET/CT, even at low PSA, but provides no information about extra-pelvic lymph nodes or bone metastasis. In 2021, a group of experts developed the Prostate Imaging for local Recurrence Reporting scoring system to standardize acquisition, interpretation, and reporting of prostate cancer recurrence.

Prostate health index can stratify patients with Prostate Imaging Reporting and Data System score 3 lesions on magnetic resonance imaging to reduce prostate biopsies

We aim to evaluate prostate health index as an additional risk-stratification tool in patients with Prostate Imaging Reporting and Data System score 3 lesions on multiparametric magnetic resonance imaging. Men with biochemical or clinical suspicion of having prostate cancer who underwent multiparametric magnetic resonance imaging in two tertiary centers (Queen Mary Hospital and Princess Margaret Hospital, Hong Kong, China) between January 2017 and June 2022 were included. Ultrasound-magnetic resonance imaging fusion biopsies were performed after prostate health index testing. Those who only had Prostate Imaging Reporting and Data System score 3 lesions were further stratified into four prostate health index risk groups and the cancer detection rates were analyzed. Out of the 747 patients, 47.3% had Prostate Imaging Reporting and Data System score 3 lesions only. The detection rate of clinically significant prostate cancer in this group was 15.0%. The cancer detection rates of clinically significant prostate cancer had statistically significant differences 5.3% in prostate health index <25.0, 7.4% in prostate health index 25.0-34.9, 17.9% in prostate health index 35.0-54.9, and 52.6% in prostate health index ≥55.0 (P < 0.01). Among the patients, 26.9% could have avoided a biopsy with a prostate health index <25.0, at the expense of a 5.3% risk of missing clinically significant prostate cancer. Prostate health index could be used as an additional risk stratification tool for patients with Prostate Imaging Reporting and Data System score 3 lesions. Biopsies could be avoided in patients with low prostate health index, with a small risk of missing clinically significant prostate cancer.

Future Imaging of Prostate Cancer: Do We Need More Than PSMA PET/CT?

In the setting of prostate cancer (PCa), many different imaging modalities are available to correctly assess staging, restaging, treatment response and radio-ligand therapy recruitment. The introduction of fluoride or gallium-labelled prostate specific membrane antigen (PSMA) made a revolution in PCa management, also due to its possible theragnostic use. Nowadays PSMA-PET/CT is a fundamental tool for staging and restaging PCa. This review discusses the latest findings in PSMA imaging in PCa patients and the impact of PSMA imaging on the patients' management in primary staging, biochemical recurrence and in advanced prostate cancer, always keeping in mind the important theragnostic role of PSMA. This review tries also to assess the current role of other radiopharmaceuticals as Choline, FACBC or other radiotracers like gastrin-releasing peptide receptor targeting tracers and FAPI in different PCa settings.

mpMRI-targeted biopsy of the prostate in men ≥ 75 years. 7-year report from a high-volume referral center

OBJECTIVE

Multiparametric magnetic resonance imaging (mpMRI) -Ultrasound- fusion guided biopsy of the prostate (FBx) is the new gold standard for the detection of prostate cancer. Hallmark studies showing superior detection rates of FBx over randomized biopsies routinely excluded patients≥75 years and information on outcome of FBx on this patient cohort is sparse. As a large referral center, we have performed FBx on a substantial number of patients this age. By evaluating outcome of FBx of patients over the age of 75 years we wanted to close the gap of knowledge on this patient cohort.

MATERIALS AND METHODS

Between 2015 -2022, 1577 patients underwent FBx at our department and were considered for analysis. Clinical and histopathological parameters were recorded. Clinical data comprised age at FBx, serum level of Prostate-specific antigen (PSA), prostate volume, PSA-density, history of previous biopsies of the prostate, result of the digital rectal examination (DRE) and assessment of the indexlesion of mpMRI according to the Prostate Imaging and Reporting Data System (PI-RADS). Univariate analysis and multivariable logistic regression was used to identify age barrier of 75 years as a potential risk factor of detection of clinically significant prostate cancer by FBx.

RESULTS

379/1577 patients (24%) were≥75 years and 1198/1577 (76%) patients were < 75 years, respectively. Preoperative PSA was significantly higher in patients≥75 years compared to patients < 75 years (9.54 vs. 7.8, p < 0.001). Patients≥75 years presented significantly more often with mpMRI target lesions classified as PI-RADS 5 compared to patients < 75 years (45% vs. 29%, p < 0.001). Detection rate of clinically significant prostate cancer was significantly higher in patients≥75 years compared to patients < 75 years (63% vs. 43%, p < 0.001). Aggressive prostate cancer grade ISUP 5 was significantly more often detected in patients≥75 years compared to patients < 75 years (13% vs. 8%, p = 0.03). On multivariable logistic regression model adjusted for PSA and PI-RADS score, age barrier of 75 years was identified as a significant risk factor for the detection of clinically significant prostate cancer by FBx (OR: 1.77, 95% CI: 1.36 -2.31, p < 0.001).

CONCLUSION

After evaluation of a large patient cohort, we show that age≥75 years represents a significant risk factor for the detection of clinically significant prostate cancer. Further studies on mid- and long term outcome are necessary to draw conclusions for clinical decision making in this patient cohort.

Germline DNA Damage Response Gene Mutations in Localized Prostate Cancer

Background and Objectives: Germline DNA damage response (DDR) gene mutations correlate with increased prostate cancer (PCa) risk and a more aggressive form of the disease. DDR mutation testing is recommended for metastatic PCa cases, while eligible information about the mutations' burden in the early-stage localized PCa is still limited. This study is aimed at the prospective detection of DDR pathway mutations in cases with localized PCa and correlation with clinical, histopathological, and radiological data. A comparison to the previously assessed cohort of the advanced PCa was performed. Materials and Methods: Germline DDR gene mutations were assessed prospectively in DNA samples from 139 patients, using a five-gene panel (BRCA1, BRCA2, ATM, CHEK2, and NBN) targeted next-generation sequencing. Results: This study revealed an almost three-fold higher risk of localized PCa among mutation carriers as compared to non-carriers (OR 2.84 and 95% CI: 0.75-20.23, p = 0.16). The prevalence of germline DDR gene mutations in PCa cases was 16.8% (18/107) and they were detected only in cases with PI-RADS 4/5 lesions. BRCA1/BRCA2/ATM mutation carriers were 2.6 times more likely to have a higher (>1) cISUP grade group compared to those with a CHEK2 mutation (p = 0.27). However, the number of cISUP > 1-grade patients with a CHEK2 mutation was significantly higher in advanced PCa than in localized PCa: 66.67% vs. 23.08% (p = 0.047). Conclusions: The results of our study suggest the potential of genetic screening for selected DDR gene mutations for early identification of cases at risk of aggressive PCa.

Use of PIRADS 2.1 to predict capsular invasion in patients with radiologic T3a prostate cancer

Objective

Using multi-parametric magnetic resonance imaging (mpMRI) to identify patients with clinical T3a (cT3a) who were overestimated on mpMRI with final pathological T2 (pT2). To suggest that the neurovascular bundle (NVB) can be preserved by evaluating the characteristics of patients according to their pathological grade among cT3a prostate cancer (PCa) patients using mpMRI.

Materials and methods

Patients who underwent robot-assisted laparoscopic radical prostatectomy (RALP) were retrospectively analyzed and those patients with clinical T3aN0M0 were enrolled. These enrolled patients were divided into a localized cancer group with pT2 PCa and a locally advanced group with pT3a or higher. Factors affecting the diagnosis of localized PCa after RALP in patients with cT3a PCa were evaluated.

Results

Among the preoperative parameters of patients with cT3a PCa, the prostate specific antigen density (PSAD) (OR: 3.76, 95% CI: 1.85-7.64, p<0.001), international society of urological pathology (ISUP) grade (p<0.05), and index lesion size (OR: 1.44, 95% CI: 1.85-7.64, p<0.001) were significantly associated with pathological locally advanced PCa. Optimal cut-off values for prediction of pT3a or higher were 0.36 ng/mL2 for PSAD (sensitivity: 55.7%, specificity: 70.8%), 1.77 cm for index lesion size (sensitivity: 54.3%, specificity: 66.0%), and 2.5 for ISUP grading (sensitivity: 67.6%, specificity: 53.2%). For prediction of pT3a or higher among patients with cT3a PCa, a nomogram was developed using ISUP grade, index lesion size, and PSAD on prostate biopsy (area under the curve: 0.71, 95% CI: 0.670-0.754, p<0.001). PSAD less than 0.36 index lesion size less than 1.77 cm, and biopsy ISUP grade 1-2 are highly likely to indicate that there is no actual extracapsular extension in cT3a PCa patients.

Conclusions

PSAD, ISUP, and index lesion size showed significant associations with the classification of pathologic localized and locally advanced PCa in patients with cT3a PCa. A nomogram including these features can predict the diagnosis of locally advanced PCa in patients with cT3a PCa.

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

INTRODUCTION AND OBJECTIVES

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Which protocol for prostate biopsies in patients with a positive MRI? Interest of systematic biopsies by sectors

BACKGROUND

Current prostate biopsy (PBx) protocol for prostate cancer (PCa) diagnosis is to perform systematic biopsies (SBx) combined with targeted biopsies (TBx) in case of positive MRI (i.e. PI-RADS ≥ 3). To assess the utility of performing SBx in combination with TBx, we determined the added value of SBx brought to the diagnosis of PCa according to their sextant location and MRI target characteristics.

METHODS

In our local prospectively collected database, we conducted a single-center retrospective study including all patients with a suspicion of PCa, who underwent transrectal ultrasound-guided (TRUS) prostate biopsies (PBx) with a prior MRI and a single lesion classified as PI-RADS ≥ 3. We have characterized the SBx according to their location on MRI: same sextant (S-SBx), adjacent sextant (A-SBx), ipsilateral side (I-SBx) and contralateral side (C-SBx). The added value of SBx and TBx was defined as any upgrading to significant PCa (csPCa) (ISUP ≥2).

RESULTS

371 patients were included in the study. The added value of SBx was 10% overall. Regarding the lesion location and the SBx sextant, the added value of SBx was: 5.1% for S-SBx, 5.4% for A-SBx, 4.9% for I-SBx and 1.9% for C-SBx. The overall added value of SBx was 6.8% for PI-RADS 3 lesions, 14% for PI-RADS 4 lesions and 6.7% for PI-RADS 5 lesions (p = 0.063). The added value of SBx for contralateral side was 1.9% (2/103), 3.1% (5/163) and 0% (0/105) for PI-RADS 3, PI-RADS 4 and PI-RADS 5 lesions, respectively (p = 0,4). The added value of SBx was lower when the number of TBx was higher (OR 0.57; CI 95% 0.37-0.85; p = 0.007).

CONCLUSIONS

Our results suggest that the utility of performing SBx in the contralateral lobe toward the MRI lesion was very low, supporting that they might be avoided.

Quantification and significance of extraprostatic findings on prostate MRI: a retrospective analysis and three-tier classification

OBJECTIVES

To quantify extraprostatic findings (EPFs) on prostate MRI, estimate the proportion of reported and unreported EPFs, assess their clinical importance, and propose standardized reporting of EPFs.

MATERIALS AND METHODS

Prostate 3-T MRI studies, reports, and clinical data from 623 patients (age 67.9 ± 8.2 years) were retrospectively analyzed and re-evaluated for the presence of EPFs and their clinical significance: E1-no finding or findings that have no clinical significance; E2-potentially significant findings; and E3-significant findings.

RESULTS

Secondary reading identified 1236 EPFs in 593 patients (1.98 ± 1.13 EPFs per patient, no EPFs in 30 patients), from which 468 (37.8%) were mentioned in the original report. The most common findings included diverticulosis (44% of patients), hydrocele (34%), inguinal fat hernia (16%), and bladder wall trabecular hypertrophy (15%). There were 80 (6.5%) E2 EPFs and 30 (2.4%) E3 EPFs. From E3 EPFs, 10 (33%) were not originally reported. A workup was suggested in 35 (52%) of the 67 originally reported E2 and E3 findings with follow-up and performed in 20 (30%). Fourteen (21%) EPFs in 11 patients influenced their management. Four experienced radiologists originally reported 1.8 to 2.5 findings per patient (p < 0.0001).

CONCLUSIONS

EPFs on prostate MRI are frequent, but only 2.4% are clinically significant (E3), and 33% of these are not reported. Only 30% of E2 and E3 findings are further explored, and 21% influence patient management. We suggest that an "E" category should be attached to the PI-RADS system to identify the presence of EPFs that require further workup.

CRITICAL RELEVANCE STATEMENT

Extraprostatic findings on prostate MRI are frequent, but only 2.4% are clinically significant (E3), and 33% of these are not reported. We advocate standardized reporting of extraprostatic findings indicating their clinical significance.

KEY POINTS

• Extraprostatic findings on prostate MRI are frequent with an average of two findings per patient. • 2.4% of extraprostatic findings are significant, and 33% of these are not reported. • There is a significant variability among experienced radiologists in reporting extraprostatic findings.

A radiomics based method for prediction of prostate cancer Gleason score using enlarged region of interest

BACKGROUND

Prostate cancer (PCa) is one of the most common cancers in men worldwide, and its timely diagnosis and treatment are becoming increasingly important. MRI is in increasing use to diagnose cancer and to distinguish between non-clinically significant and clinically significant PCa, leading to more precise diagnosis and treatment. The purpose of this study is to present a radiomics-based method for determining the Gleason score (GS) for PCa using tumour heterogeneity on multiparametric MRI (mp-MRI).

METHODS

Twenty-six patients with biopsy-proven PCa were included in this study. The quantitative T2 values, apparent diffusion coefficient (ADC) and signal enhancement rates (α) were calculated using multi-echo T2 images, diffusion-weighted imaging (DWI) and dynamic contrast-enhanced MRI (DCE-MRI), for the annotated region of interests (ROI). After texture feature analysis, ROI range expansion and feature filtering was performed. Then obtained data were put into support vector machine (SVM), K-Nearest Neighbor (KNN) and other classifiers for binary classification.

RESULTS

The highest classification accuracy was 73.96% for distinguishing between clinically significant (Gleason 3 + 4 and above) and non-significant cancers (Gleason 3 + 3) and 83.72% for distinguishing between Gleason 3 + 4 from Gleason 4 + 3 and above, which was achieved using initial ROIs drawn by the radiologists. The accuracy improved when using expanded ROIs to 80.67% using SVM and 88.42% using Bayesian classification for distinguishing between clinically significant and non-significant cancers and Gleason 3 + 4 from Gleason 4 + 3 and above, respectively.

CONCLUSIONS

Our results indicate the research significance and value of this study for determining the GS for prostate cancer using the expansion of the ROI region.

Deep-learning prostate cancer detection and segmentation on biparametric versus multiparametric magnetic resonance imaging: Added value of dynamic contrast-enhanced imaging

OBJECTIVES

To develop diagnostic algorithms of multisequence prostate magnetic resonance imaging for cancer detection and segmentation using deep learning and explore values of dynamic contrast-enhanced imaging in multiparametric imaging, compared with biparametric imaging.

METHODS

We collected 3227 multiparametric imaging sets from 332 patients, including 218 cancer patients (291 biopsy-proven foci) and 114 noncancer patients. Diagnostic algorithms of T2-weighted, T2-weighted plus dynamic contrast-enhanced, biparametric, and multiparametric imaging were built using 2578 sets, and their performance for clinically significant cancer was evaluated using 649 sets.

RESULTS

Biparametric and multiparametric imaging had following region-based performance: sensitivity of 71.9% and 74.8% (p = 0.394) and positive predictive value of 61.3% and 74.8% (p = 0.013), respectively. In side-specific analyses of cancer images, the specificity was 72.6% and 89.5% (p < 0.001) and the negative predictive value was 78.9% and 83.5% (p = 0.364), respectively. False-negative cancer on multiparametric imaging was smaller (p = 0.002) and more dominant with grade group ≤2 (p = 0.028) than true positive foci. In the peripheral zone, false-positive regions on biparametric imaging turned out to be true negative on multiparametric imaging more frequently compared with the transition zone (78.3% vs. 47.2%, p = 0.018). In contrast, T2-weighted plus dynamic contrast-enhanced imaging had lower specificity than T2-weighted imaging (41.1% vs. 51.6%, p = 0.042).

CONCLUSIONS

When using deep learning, multiparametric imaging provides superior performance to biparametric imaging in the specificity and positive predictive value, especially in the peripheral zone. Dynamic contrast-enhanced imaging helps reduce overdiagnosis in multiparametric imaging.

Value of the newly developed pelvic dimension index/prostate volume ratio in predicting positive surgical margin in prostate cancer

PURPOSE

To evaluate the diagnostic performance of pelvimetric measurements, in particular the pelvic dimension index (PDI)/prostate volume (PV) ratio (PDI/PV), in predicting positive surgical margin (PSM) in prostate cancer (PC).

MATERIALS AND METHODS

127 patients who had pre-operative pelvic imaging were included in this study. Demographic and clinical data were recorded. Apical depth (AD), interspinous distance (ISD), intertuberous distance (ITD), bony femoral width (BFW), soft-tissue width (SW), symphysis angle (SA), anteroposterior diameter of the pelvic inlet (API), anteroposterior diameter of the pelvic mid-plane (APM), anteroposterior diameter of the pelvic outlet (APO), pelvic depth (PD), bony width index (BWI), soft tissue width index (SWI), pelvic cavity index (PCI), PDI and PV were measured on MRI or CT. Using PDI and PV, we developed a new parameter of "PDI to PV ratio" (PDI/PV). Logistic regression analysis was used to determine the predictive potential of variables in detection of PSM.

RESULTS

The AD, PV, SA and total prostate specific antigen (PSA) were significantly higher in PSM( +), while PDI, BWI, SWI, API, PDI/PV and PD were significantly lower in PSM( +) (p < 0.05). In multivariate analysis, PDI/PV ratio and clinical stage were all significant predictor of PSM, where PDI/PV ratio was the strongest predictor, followed by clinical stage.

CONCLUSION

Pelvimetric measurements indicating deep location of the prostatic apex rather than pelvic width are more effective in predicting PSM. Prediction of PSM with pelvimetric measurements, in particular PDI/PV ratio, may be helpful for surgical planning in preoperative period.

Artificial intelligence as diagnostic aiding tool in cases of Prostate Imaging Reporting and Data System category 3: the results of retrospective multi-center cohort study

PURPOSE

To study the effect of artificial intelligence (AI) on the diagnostic performance of radiologists in interpreting prostate mpMRI images of the PI-RADS 3 category.

METHODS

In this multicenter study, 16 radiologists were invited to interpret prostate mpMRI cases with and without AI. The study included a total of 87 cases initially diagnosed as PI-RADS 3 by radiologists without AI, with 28 cases being clinically significant cancers (csPCa) and 59 cases being non-csPCa. The study compared the diagnostic efficacy between readings without and with AI, the reading time, and confidence levels.

RESULTS

AI changed the diagnosis in 65 out of 87 cases. Among the 59 non-csPCa cases, 41 were correctly downgraded to PI-RADS 1-2, and 9 were incorrectly upgraded to PI-RADS 4-5. For the 28 csPCa cases, 20 were correctly upgraded to PI-RADS 4-5, and 5 were incorrectly downgraded to PI-RADS 1-2. Radiologists assisted by AI achieved higher diagnostic specificity and accuracy than those without AI [0.695 vs 0.000 and 0.736 vs 0.322, both P < 0.001]. Sensitivity with AI was not significantly different from that without AI [0.821 vs 1.000, P = 1.000]. AI reduced reading time significantly compared to without AI (mean: 351 seconds, P < 0.001). The diagnostic confidence score with AI was significantly higher than that without AI (Cohen Kappa: -0.016).

CONCLUSION

With the help of AI, there was an improvement in the diagnostic accuracy of PI-RADS category 3 cases by radiologists. There is also an increase in diagnostic efficiency and diagnostic confidence.

Impact of operator expertise on transperineal free-hand mpMRI-fusion-targeted biopsies under local anaesthesia for prostate cancer diagnosis: a multicenter prospective learning curve

PURPOSE

Transperineal mpMRI-targeted fusion prostate biopsies (TPFBx) are recommended for prostate cancer diagnosis, but little is known about their learning curve (LC), especially when performed under local anaesthesia (LA). We investigated how operators' and institutions' experience might affect biopsy results.

METHODS

Baseline, procedure and pathology data of consecutive TPFBx under LA were prospectively collected at two academic Institutions, from Sep 2016 to May 2019. Main inclusion criterion was a positive MRI. Endpoints were biopsy duration, clinically significant prostate cancer detection rate on targeted cores (csCDR-T), complications, pain and urinary function. Data were analysed per-centre and per-operator (with ≥ 50 procedures), comparing groups of consecutive patient, and subsequently through regression and CUSUM analyses. Learning curves were plotted using an adjusted lowess smoothing function.

RESULTS

We included 1014 patients, with 27.3% csCDR-T and a median duration was 15 min (IQR 12-18). A LC for biopsy duration was detected, with the steeper phase ending after around 50 procedures, in most operators. No reproducible evidence in favour of an impact of experience on csPCa detection was found at operator's level, whilst a possible gentle LC of limited clinical relevance emerged at Institutional level; complications, pain and IPSS variations were not related to operator experience.

CONCLUSION

The implementation of TPFBx under LA was feasible, safe and efficient since early phases with a relatively short learning curve for procedure time.

Current magnetic resonance imaging-based diagnostic strategies for prostate cancer

Recent developments in multiparametric MRI and MRI-targeted biopsy have made it possible to detect clinically significant cancers more accurately and efficiently than ever before. Furthermore, software that enables easy MRI/US image fusion has been developed and is already available on the market, and this has provided a tailwind for the spread of MRI-based prostate cancer diagnostic strategies. Such precise diagnosis of prostate cancer localization is essential for highly accurate focal therapy. In addition, a recent large-scale study applying MRI to community screening for prostate cancer has reported its usefulness. By contrast, concerns about overdiagnosis and overtreatment, the existence of inter-reader variability in MRI diagnosis, and issues with current MRI-targeted biopsy have emerged. In this article, we review the development of multiparametric MRI and MRI-targeted biopsy to date and the current issues and discuss future directions.

Patient-related characteristics predict prostate cancers in men with PI-RADS 4-5 to further optimize the diagnostic performance of MRI

PURPOSE

To develop a prediction model based on patient-related characteristics for detecting prostate cancer (PCa) in patients with Prostate Imaging Reporting and Data System (PI-RADS) 4-5 in multiparametric magnetic resonance imaging (mp-MRI), aiming to optimize pre-biopsy risk stratification in MRI.

MATERIALS AND METHODS

The patient-related characteristics including the lesion location, age, prostate-specific antigen (PSA), free prostate-specific antigen (fPSA), fPSA/PSA, prostate-specific antigen density (PSAD) and body mass index (BMI) were collected for patients who underwent mp-MRI and prostate biopsy between February 2014 and October 2022. Univariate and multivariate logistic regression analyses were conducted to select independent predictors of PCa and further create a prediction model. The diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUC). Moreover, sensitivity, specificity, positive-predictive value (PPV) and negative-predictive value (NPV) were also calculated.

RESULTS

A total of 833 patients were included in this study. In the subgroup PI-RADS 4, the independent characteristics of lesion location, age, fPSA/PSA and PSAD were selected to create the prediction model with an AUC of 0.748 (95% CI 0.694-0.803), sensitivity of 61.88%, specificity of 85.32%, PPV of 92.52%, and NPV of 43.26%. Besides, the prediction model in PI-RADS 5 was created using PSA and PSAD with an AUC of 0.893 (95% CI 0.844-0.941), sensitivity of 81.40%, specificity of 84.85%, PPV of 98.37% and NPV of 28.87%.

CONCLUSION

The patient-related clinical characteristics were significant predictors of PCa and the prediction model based on selected characteristics could achieve a medium risk prediction of PCa in PI-RADS 4-5.

Parameterized Gompertz-Guided Morphological AutoEncoder for Predicting Pulmonary Nodule Growth

The growth rate of pulmonary nodules is a critical clue to the cancerous diagnosis. It is essential to monitor their dynamic progressions during pulmonary nodule management. To facilitate the prosperity of research on nodule growth prediction, we organized and published a temporal dataset called NLSTt with consecutive computed tomography (CT) scans. Based on the self-built dataset, we develop a visual learner to predict the growth for the following CT scan qualitatively and further propose a model to predict the growth rate of pulmonary nodules quantitatively, so that better diagnosis can be achieved with the help of our predicted results. To this end, in this work, we propose a parameterized Gempertz-guided morphological autoencoder (GM-AE) to generate any future-time-span high-quality visual appearances of pulmonary nodules from the baseline CT scan. Specifically, we parameterize a popular mathematical model for tumor growth kinetics, Gompertz, to predict future masses and volumes of pulmonary nodules. Then, we exploit the expected growth rate on the mass and volume to guide decoders generating future shape and texture of pulmonary nodules. We introduce two branches in an autoencoder to encourage shape-aware and textural-aware representation learning and integrate the generated shape into the textural-aware branch to simulate the future morphology of pulmonary nodules. We conduct extensive experiments on the self-built NLSTt dataset to demonstrate the superiority of our GM-AE to its competitive counterparts. Experiment results also reveal the learnable Gompertz function enjoys promising descriptive power in accounting for inter-subject variability of the growth rate for pulmonary nodules. Besides, we evaluate our GM-AE model on an in-house dataset to validate its generalizability and practicality. We make its code publicly available along with the published NLSTt dataset.

Prostate Imaging after Focal Ablation (PI-FAB): A Proposal for a Scoring System for Multiparametric MRI of the Prostate After Focal Therapy

At present there is no standardised system for scoring the appearance of the prostate on multiparametric magnetic resonance imaging (MRI) after focal ablation for localised prostate cancer. We propose a novel scoring system, the Prostate Imaging after Focal Ablation (PI-FAB) score, to fill this gap. PI-FAB involves a 3-point scale for rating MRI sequences in sequential order: (1) dynamic contrast-enhanced sequences; (2) diffusion-weighted imaging, split into assessment of the high-b-value sequence first and then the apparent diffusion coefficient map; and (3) T2-weighted imaging. It is essential that the pretreatment scan is also available to help with this assessment. We designed PI-FAB using our experience of reading postablation scans over the past 15 years and include details for four representative patients initially treated with high-intensity focus ultrasound at our institution to demonstrate the scoring system. We propose PI-FAB as a standardised method for evaluating prostate MRI scans after treatment with focal ablation. The next step is to evaluate its performance across multiple experienced readers of MRI after focal therapy in a clinical data set. PATIENT SUMMARY: We propose a scoring system called PI-FAB for assessing the appearance of magnetic resonance imaging scans of the prostate after focal treatment for localised prostate cancer. This will help clinicians in deciding on further follow-up.

Head-to-Head Comparison of 18F-PSMA-1007 Positron Emission Tomography/Computed Tomography and Multiparametric Magnetic Resonance Imaging with Whole-mount Histopathology as Reference in Localisation and Staging of Primary Prostate Cancer

BACKGROUND

Accurate local staging is critical for treatment planning and prognosis in prostate cancer (PCa). Although multiparametric magnetic resonance imaging (mpMRI) has high specificity for detection of extraprostatic extension (EPE) and seminal vesicle invasion (SVI), its sensitivity remains limited. 18F-PSMA-1007 positron emission tomography/computed tomography (PET/CT) may be more accurate in determining T stage.

OBJECTIVE

To assess the diagnostic performance of 18F-PSMA-1007 PET/CT in comparison to mpMRI for intraprostatic tumour localisation and detection of EPE and SVI in men with primary PCa undergoing robot-assisted radical prostatectomy (RARP).

DESIGN, SETTING, AND PARTICIPANTS

Between February 2019 and October 2020, 105 treatment-naïve patients with biopsy-proven intermediate- or high-risk PCa undergoing mpMRI and 18F-PSMA-1007 PET/CT before RARP were prospectively enrolled.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The diagnostic accuracy of 18F-PSMA-1007 PET/CT and mpMRI for intraprostatic tumour localisation and detection of EPE and SVI was assessed via histopathological examination of whole-mount RP specimens. The sensitivity, specificity, negative predictive value, positive predictive value, and accuracy were calculated. The McNemar test was used to compare outcomes between imaging modalities.

RESULTS AND LIMITATIONS

In 80 RP specimens, 129 PCa lesions were found, of which 96 were clinically significant PCa (csPCa). Per-lesion sensitivity for localisation of overall PCa was 85% (95% confidence interval [CI] 77-90%) with PSMA PET/CT and 62% (95% CI 53-70%) with mpMRI (p < 0.001). Per-lesion sensitivity for csPCa was 95% (95% CI 88-98%) with PSMA PET/CT and 73% (95% CI 63-81%) with mpMRI (p < 0.001). The diagnostic accuracy of PSMA PET/CT and mpMRI for detection of EPE per lesion did not significantly differ (sensitivity 45%, 95% CI 31-60% vs 55%, 95% CI 40-69%; p = 0.3; specificity 85%, 95% CI 75-92% vs 90%, 95% CI 81-86%; p = 0.5). The sensitivity and specificity of PSMA PET/CT and mpMRI for detection of SVI did not significantly differ (sensitivity 47%, 95% CI 21-73% vs 33%, 95% CI 12-62; p = 0.6; specificity 94%, 95% CI 88-98% vs 96%, 95% CI 90-99%; p = 0.8).

CONCLUSIONS

18F-PSMA-1007 is a promising imaging modality for localising intraprostatic csPCa but did not show additional value in assessing EPE and SVI in comparison to mpMRI.

PATIENT SUMMARY

A new imaging technique called PET/CT (positron emission tomography/computed tomography) with the radioactive tracer 18F-PSMA-1007 shows promise in identifying the location of clinically significant prostate cancer. However, it does not seem to be of additional value over magnetic resonance imaging (MRI) for determining the local tumour stage.

Is prostatic adenocarcinoma with cribriform architecture more difficult to detect on prostate MRI?

BACKGROUND

Cribriform (CBFM) pattern on prostate biopsy has been implicated as a predictor for high-risk features, potentially leading to adverse outcomes after definitive treatment. This study aims to investigate whether the CBFM pattern containing prostate cancers (PCa) were associated with false negative magnetic resonance imaging (MRI) and determine the association between MRI and histopathological disease burden.

METHODS

Patients who underwent multiparametric magnetic resonance imaging (mpMRI), combined 12-core transrectal ultrasound (TRUS) guided systematic (SB) and MRI/US fusion-guided biopsy were retrospectively queried for the presence of CBFM pattern at biopsy. Biopsy cores and lesions were categorized as follows: C0 = benign, C1 = PCa with no CBFM pattern, C2 = PCa with CBFM pattern. Correlation between cancer core length (CCL) and measured MRI lesion dimension were assessed using a modified Pearson correlation test for clustered data. Differences between the biopsy core groups were assessed with the Wilcoxon-signed rank test with clustering.

RESULTS

Between 2015 and 2022, a total of 131 consecutive patients with CBFM pattern on prostate biopsy and pre-biopsy mpMRI were included. Clinical feature analysis included 1572 systematic biopsy cores (1149 C0, 272 C1, 151 C2) and 736 MRI-targeted biopsy cores (253 C0, 272 C1, 211 C2). Of the 131 patients with confirmed CBFM pathology, targeted biopsy (TBx) alone identified CBFM in 76.3% (100/131) of patients and detected PCa in 97.7% (128/131) patients. SBx biopsy alone detected CBFM in 61.1% (80/131) of patients and PCa in 90.8% (119/131) patients. TBx and SBx had equivalent detection in patients with smaller prostates (p = 0.045). For both PCa lesion groups there was a positive and significant correlation between maximum MRI lesion dimension and CCL (C1 lesions: p < 0.01, C2 lesions: p < 0.001). There was a significant difference in CCL between C1 and C2 lesions for T2 scores of 3 and 5 (p ≤ 0.01, p ≤ 0.01, respectively) and PI-RADS 5 lesions (p ≤ 0.01), with C2 lesions having larger CCL, despite no significant difference in MRI lesion dimension.

CONCLUSIONS

The extent of disease for CBFM-containing tumors is difficult to capture on mpMRI. When comparing MRI lesions of similar dimensions and PIRADS scores, CBFM-containing tumors appear to have larger cancer yield on biopsy. Proper staging and planning of therapeutic interventions is reliant on accurate mpMRI estimation. Special considerations should be taken for patients with CBFM pattern on prostate biopsy.

A radiomics approach based on MR imaging for classification of deficiency and excess syndrome of traditional Chinese medicine in prostate cancer

Objective

To explore the potential imaging biomarkers for predicting Traditional Chinese medicine (TCM) deficiency and excess syndrome in prostate cancer (PCa) patients by radiomics approach based on MR imaging.

Methods

A total of 121 PCa patients from 2 centers were divided into 1 training cohort with 84 PCa patients and 1 validation cohort with 37 PCa patients. The PCa patients were divided into deficiency and excess syndrome group according to TCM syndrome differentiation. Radiomic features were extracted from T2-weighted imaging (T2WI), diffusion-weighted imaging and apparent diffusion coefficient images originated from diffusion-weighted imaging. A radiomic signature was constructed after reduction of dimension in training group by the minimum redundancy maximum relevance and the least absolute shrinkage and selection operator. The performance of the model was evaluated by receiver operating characteristic (ROC) curve and calibration curve.

Results

The radiomic scores of PCa with TCM excess syndrome group were statistically higher than those of PCa with TCM deficiency syndrome group among T2WI, diffusion-weighted imaging and apparent diffusion coefficient imaging models. The area under ROC curves for T2WI, diffusion-weighted imaging and apparent diffusion coefficient imaging models were 0.824, 0.824, 0.847 in the training cohort and 0.759, 0.750, 0.809 in the validation cohort, respectively. The apparent diffusion coefficient imaging model had the best discrimination in separating patients with TCM excess syndrome and deficiency syndrome, and its accuracy was 0.788, 0.778 in the training and validation cohort, respectively. The calibration curve demonstrated that there was a high consistency between the prediction of radiomic scores and the actual classification of TCM's deficiency and excess syndrome in PCa.

Conclusion

The radiomic signature based on MR imaging can be performed as a non-invasive, potential approach to discriminate TCM deficiency syndrome from excess syndrome in PCa, in which apparent diffusion coefficient imaging model has the best diagnostic efficiency.