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

Enhancing the image quality of prostate diffusion-weighted imaging in patients with prostate cancer through model-based deep learning reconstruction

Purpose

To evaluate the utility of model-based deep learning reconstruction in prostate diffusion-weighted imaging (DWI).

Methods

This retrospective study evaluated two prostate diffusion-weighted imaging (DWI) methods: deep learning reconstruction (DL-DWI) and traditional parallel imaging (PI-DWI). We examined 32 patients with radiologically diagnosed and histologically confirmed prostate cancer (PCa) lesions ≥10 mm. Image quality was evaluated both qualitatively (for overall quality, prostate conspicuity, and lesion conspicuity) and quantitatively, using the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) for prostate tissue.

Results

In the qualitative evaluation, DL-DWI scored significantly higher than PI-DWI for all three parameters (p<0.0001). In the quantitative analysis, DL-DWI showed significantly higher SNR and CNR values compared to PI-DWI (p<0.0001). Both the prostate tissue and the lesions exhibited significantly higher ADC values in DL-DWI compared to PI-DWI (p<0.0001, p=0.0014, respectively).

Conclusion

Model-based DL reconstruction enhanced both qualitative and quantitative aspects of image quality in prostate DWI. However, this study did not include comparisons with other DL-based methods, which is a limitation that warrants future research.

Part II: Effect of different evaluation methods to the application of a computer-aided prostate MRI detection/diagnosis (CADe/CADx) device on reader performance

INTRODUCTION

The construction and results of a multiple-reader multiple-case prostate MRI study are described and reported to illustrate recommendations for how to standardize artificial intelligence (AI) prostate studies per the review constituting Part I1.

METHODS

Our previously reported approach was applied to review and report an IRB approved, HIPAA compliant multiple-reader multiple-case clinical study of 150 bi-parametric prostate MRI studies across 9 readers, measuring physician performance both with and without the use of the recently FDA cleared CADe/CADx software ProstatID.

RESULTS

Unassisted reader AUC values ranged from 0.418 - 0.759, with AI assisted AUC values ranging from 0.507 - 0.787. This represented a statistically significant AUC improvement of 0.045 (α = 0.05). A free-response ROC (FROC) analysis similarly demonstrated a statistically significant increase in θ from 0.405 to 0.453 (α = 0.05). The standalone performance of ProstatID performed across all prostate tissues demonstrated an AUC of 0.929, while the standalone lesion level performance of ProstatID at all biopsied locations achieved an AUC of 0.710.

CONCLUSION

This study applies and illustrates suggested reporting and standardization methods for prostate AI studies that will make it easier to understand, evaluate and compare between AI studies. Providing radiologists with the ProstatID CADe/CADx software significantly increased diagnostic performance as assessed by both ROC and free-response ROC metrics. Such algorithms have the potential to improve radiologist performance in the detection and localization of clinically significant prostate cancer.

Part I: prostate cancer detection, artificial intelligence for prostate cancer and how we measure diagnostic performance: a comprehensive review

MRI has firmly established itself as a mainstay for the detection, staging and surveillance of prostate cancer. Despite its success, prostate MRI continues to suffer from poor inter-reader variability and a low positive predictive value. The recent emergence of Artificial Intelligence (AI) to potentially improve diagnostic performance shows great potential. Understanding and interpreting the AI landscape as well as ever-increasing research literature, however, is difficult. This is in part due to widely varying study design and reporting techniques. This paper aims to address this need by first outlining the different types of AI used for the detection and diagnosis of prostate cancer, next deciphering how data collection methods, statistical analysis metrics (such as ROC and FROC analysis) and end points/outcomes (lesion detection vs. case diagnosis) affect the performance and limit the ability to compare between studies. Finally, this work explores the need for appropriately enriched investigational datasets and proper ground truth, and provides guidance on how to best conduct AI prostate MRI studies. Published in parallel, a clinical study applying this suggested study design was applied to review and report a multiple-reader multiple-case clinical study of 150 bi-parametric prostate MRI studies across nine readers, measuring physician performance both with and without the use of a recently FDA cleared Artificial Intelligence software.1.

Recent Developments in Speeding up Prostate MRI

The increasing incidence of prostate cancer cases worldwide has led to a tremendous demand for multiparametric MRI (mpMRI). In order to relieve the pressure on healthcare, reducing mpMRI scan time is necessary. This review focuses on recent techniques proposed for faster mpMRI acquisition, specifically shortening T2W and DWI sequences while adhering to the PI-RADS (Prostate Imaging Reporting and Data System) guidelines. Speeding up techniques in the reviewed studies rely on more efficient sampling of data, ranging from the acquisition of fewer averages or b-values to adjustment of the pulse sequence. Novel acquisition methods based on undersampling techniques are often followed by suitable reconstruction methods typically incorporating synthetic priori information. These reconstruction methods often use artificial intelligence for various tasks such as denoising, artifact correction, improvement of image quality, and in the case of DWI, for the generation of synthetic high b-value images or apparent diffusion coefficient maps. Reduction of mpMRI scan time is possible, but it is crucial to maintain diagnostic quality, confirmed through radiological evaluation, to integrate the proposed methods into the standard mpMRI protocol. Additionally, before clinical integration, prospective studies are recommended to validate undersampling techniques to avoid potentially inaccurate results demonstrated by retrospective analysis. This review provides an overview of recently proposed techniques, discussing their implementation, advantages, disadvantages, and diagnostic performance according to PI-RADS guidelines compared to conventional methods. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 3.

A novel nomogram to predict clinically significant prostate cancer in MR assisted lesion biopsies: Turkish urooncology association nomogram

OBJECTIVE

This study aimed to develop a novel nomogram to predict clinically significant prostate cancer in patients undergoing multi-parametric prostate MRI-assisted lesion biopsies, addressing the challenges in deciding on biopsy for patients with PI-RADS 3 lesions and follow-up strategies for patients with negative PI-RADS 4 or 5 lesions.

MATERIALS AND METHODS

A retrospective case-control study was conducted using the Turkish Urooncology Association Databases (UROCaD). The final dataset included 2428 lesion biopsy data. Univariate analysis, logistic regression, and validation were performed, with 1942 and 486 lesion biopsy data in the training and validation datasets, respectively.

RESULTS

Age, initial total PSA value, PSA density, prostate volume, lesion length, DRE findings, and PI-RADS score were significantly different between benign or non-significant cancer and clinically significant prostate cancer groups. The developed nomogram incorporated PSA density, age, PI-RADS score, lesion length, and DRE findings. The mean area under the curve for the 6-fold cross-validation was 0.836, while the area under the curve values for the training and validation datasets were 0.827 and 0.861, respectively. The nomogram demonstrated a sensitivity of 75.6% and a specificity of 74.8% at a cut-off score of 24.9, with positive and negative predictive values of 42.2% and 92.6%, respectively.

CONCLUSION

The TUA nomogram, based on PSA density, age, PI-RADS score, lesion length, and DRE findings, provides a reliable and accurate prediction tool for detecting clinically significant prostate cancer in patients undergoing multi-parametric prostate MRI-assisted lesion (fusion) biopsies, potentially improving patient management and reducing unnecessary biopsies.

The additional value of 68Ga-PSMA PET/CT SUVmax in predicting ISUP GG ≥ 2 and ISUP GG ≥ 3 prostate cancer in biopsy

BACKGROUND

Prebiopsy magnetic resonance imaging (MRI) increases the detection rate of clinically significant prostate cancer (csPCa). Prostate-specific membrane antigen-positron emission tomography/computed tomography (PSMA PET/CT) maximum standardized uptake value (SUVmax) of the prostate may offer additional value in predicting the likelihood of csPCa in biopsy.

METHODS

A single-center cohort study involving patients with biopsy-proven PCa who underwent both MRI and PSMA PET/CT between 2020 and 2021. Logistic regression models were developed for International Society of Urological Pathology (ISUP) Grade Group (GG) ≥ 2 and GG ≥ 3 using noninvasive prebiopsy parameters: age, (log-)prostate-specific antigen (PSA) density, PI-RADS 5 lesion presence, extraprostatic extension (EPE) on MRI, and SUVmax of the prostate. Models with and without SUVmax were compared using Likelihood ratio tests and area under the curve (AUC). DeLong's test was used to compare the AUCs.

RESULTS

The study included 386 patients, with 262 (68%) having ISUP GG ≥ 2 and 180 (47%) having ISUP GG ≥ 3. Including SUVmax significantly improved both models' goodness of fit (p < 0.001). The GG ≥ 2 model had a higher AUC with SUVmax 89.16% (95% confidence interval [CI]: 86.06%-92.26%) than without 87.34% (95% CI: 83.93%-90.76%) (p = 0.026). Similarly, the GG ≥ 3 model had a higher AUC with SUVmax 82.51% (95% CI: 78.41%-86.6%) than without 79.33% (95% CI: 74.84%-83.83%) (p = 0.003). The SUVmax inclusion improved the GG ≥ 3 model's calibration at higher probabilities.

CONCLUSION

SUVmax of the prostate on PSMA PET/CT potentially improves diagnostic accuracy in predicting the likelihood of csPCa in prostate biopsy.

Targeted microwave ablation for prostate cancer (FOSTINE1b): a prospective 'ablate-and-resect' study

OBJECTIVE

To assess histopathological outcomes, as well as feasibility and safety of targeted microwave ablation (TMA) via the Trinity® system (KOELIS, La Tronche, France).

PATIENTS AND METHODS

Prospective, single-institution, interventional Phase IIa study with an 'ablate-and-resect' design. In all, 11 patients diagnosed with localised prostate cancer (PCa) underwent TMA via the Trinity system under conscious sedation in an outpatient setting using a single transrectal TATO® 18-G antenna with different treatment regimens. Magnetic resonance imaging (MRI) and robot-assisted radical prostatectomy (RARP) were conducted at 7 days and 1 month after TMA, respectively. Nine patients received RARP, and two patients chose to withdraw their consent following TMA. These men chose an active surveillance protocol upon confirmation of a low-risk prostate cancer diagnosis. Functional outcomes and adverse events were evaluated at baseline and follow-up visits using validated questionnaires. Prostate volumetry and confirmation of necrosis were carried out through MRI and whole-mount histopathological examination.

RESULTS

The TMA was successfully executed, and all patients were discharged on the same day. No severe adverse events (Common Terminology Criteria for Adverse Events Grade ≥3) were reported at the 7-day and 1-month follow-up visits. Additionally, no declines were observed in urinary, sexual and ejaculation functional outcomes. T1-weighted MRI revealed clear and well-defined ablation zones. The RARP was executed without difficulty, particularly during the dissection of the posterior plane. As a result, no intraoperative complications were encountered. Histopathological assessment on surgical specimens confirmed the absence of viable cells, indicating complete necrosis of the ablative zone if a power intensity >10 W was used during TMA. Ablation zone volumetry revealed no notable distinctions between the three-dimensional segmentation of the virtual ablation zone at TMA (median volume: 2 mL) and MRI (median volume: 1.923 mL). Conversely, a significant reduction was noted in the surgical specimen (median volume: 0.221 mL).

CONCLUSIONS

Targeted microwave ablation via the Trinity system for localised PCa treatment proves to be a secure and feasible procedure, with complete necrosis evidence within the ablation zone on surgical specimens.

Diffusion weighted MRI and apparent diffusion coefficient as a prognostic biomarker in evaluating chemotherapy-antiangiogenic treated stage IV non-small cell lung cancer: A prospective, single-arm, open-label, clinical trial (BevMar)

PURPOSE

When treating Lung Cancer, it is necessary to identify early treatment failure to enable timely therapeutic adjustments. The Aim of this study was to investigate whether changes in tumor diffusion during treatment with chemotherapy and bevacizumab could serve as a predictor of treatment failure.

MATERIAL AND METHODS

A prospective single-arm, open-label, clinical trial was conducted between September 2014 and December 2020, enrolling patients with stage IV non-small cell lung cancer (NSCLC). The patients were treated with chemotherapy-antiangiogenic combination. Diffusion weighted magnetic resonance imaging (DW-MRI) was performed at baseline, two, four, and sixteen weeks after initiating treatment. The differences in apparent diffusion coefficient (ADC) values between pre- and post-treatment MRIs were recorded as Delta values (ΔADC). We assessed whether ΔADC could serve as a prognostic biomarker for overall survival (OS), with a five year follow up.

RESULTS

18 patients were included in the final analysis. Patients with a ΔADC value ≥ -3 demonstrated a significantly longer OS with an HR of 0.12 (95 % CI; 0.03- 0.61; p = 0.003) The median OS in patients with a ΔADC value ≥ -3 was 18 months, (95 % C.I; 7-46) compared to 7 months (95 % C.I; 5-9) in those with a ΔADC value < -3.

CONCLUSION

Our findings suggest that early changes in tumor ADC values, may be indicative of a longer OS. Therefore, DW-MRI could serve as an early biomarker for assessing treatment response in patients receiving chemotherapy combined with antiangiogenic therapy.

Radiomic nomogram based on bi-parametric magnetic resonance imaging to predict the International Society of Urological Pathology grading ≥ 3 prostate cancer: a multicenter study

PURPOSE

To create a reliable radiomic nomogram for the prediction of the International Society of Urological Pathology (ISUP) grading ≥ 3 prostate cancer (PCa) patients.

METHODS

patients with verified PCa were obtained from three different hospitals. The patients were divided into training, internal validation, and two external validation groups. A radiomic signature (rad-score) extracted from T2WI, diffusion-weighted imaging, and apparent diffusion coefficient (ADC) maps were constructed in the training cohort. Eight clinical features were performed to develop a clinical model using univariate and multivariate logistic regression. The combined model incorporated the radiomic signature and clinical model. The model's performance was assessed by the receiver operating characteristic (ROC) curve.

RESULTS

Rad-score, magnetic resonance imaging T-stage, and ADC value were significant predictors of ISUP ≥ 3 PCa. A nomogram of these three factors was shown to have greater diagnostic accuracy than using only the radiomic signature or clinical model alone. The area under the ROC curve was 0.85, 0.88, 0.81, 0.81 for the training, internal, and two external validation cohorts, respectively. In the stratified analysis based on the MR scanner model, the area under the ROC curve of predicting ISUP ≥ 3 PCa for GE, Siemens, and combined groups were 0.84, 0.83, and 0.84, respectively, in the combined training group and an internal validation group.

CONCLUSIONS

The proposed nomogram has the potential to predict the differentiation degree of ISUP PCa patients.

Clinical Validation of Multiparametric Ultrasound for Detecting Clinically Significant Prostate Cancer Using Computer-Aided Diagnosis: A Direct Comparison with the Magnetic Resonance Imaging Pathway

We present the protocol for a study testing the hypothesis that a computer-aided diagnosis (CAD) system for three-dimensional multiparametric ultrasound (3D mpUS) is noninferior to magnetic resonance imaging (MRI) in guiding prostate biopsies for detection of clinically significant prostate cancer (csPCa). The prospective study has a fully paired design for assessment of diagnostic accuracy and is registered on ClinicalTrials.gov as NCT06281769. A total of 438 biopsy-naïve men scheduled for prostate MRI evaluation because of an abnormal digital rectal examination and/or elevated serum prostate-specific antigen will be included. All patients will undergo both MRI (multiparametric or biparametric) and 3D mpUS with CAD (PCaVision). Suspicious lesions will be independently identified using each imaging technique. MRI targeted biopsy (TBx) and/or PCaVision TBx will be performed if suspicious lesions are identified on imaging. When both PCaVision and MRI identify lesions in an individual patient, the TBx order for this patient will be randomized. Three TBx samples per lesion will be taken for a maximum of two lesions per modality. The primary objective is the detection rate for csPCa (International Society of Urological Pathology grade group [GG] ≥2) with the PCaVision versus the MRI TBx pathway. The noninferiority margin for the absolute difference in detection rates is set at a difference of 5%. Secondary outcomes are the proportion of men in whom TBx could have been safely omitted in each pathway. Additional diagnostic accuracy analyses will be performed for different definitions of PCa (GG ≥3; GG ≥2 with cribriform growth and/or intraductal carcinoma; and GG 1). The frequency of insufficient image quality for the two pathways will also be assessed. Lastly, we will determine the diagnostic performance for csPCa detection at various 3D mpUS image quality thresholds for PCaVision.

AI-based automated evaluation of image quality and protocol tailoring in patients undergoing MRI for suspected prostate cancer

PURPOSE

To develop and validate an artificial intelligence (AI) application in a clinical setting to decide whether dynamic contrast-enhanced (DCE) sequences are necessary in multiparametric prostate MRI.

METHODS

This study was approved by the institutional review board and requirement for study-specific informed consent was waived. A mobile app was developed to integrate AI-based image quality analysis into clinical workflow. An expert radiologist provided reference decisions. Diagnostic performance parameters (sensitivity and specificity) were calculated and inter-reader agreement was evaluated.

RESULTS

Fully automated evaluation was possible in 87% of cases, with the application reaching a sensitivity of 80% and a specificity of 100% in selecting patients for multiparametric MRI. In 2% of patients, the application falsely decided on omitting DCE. With a technician reaching a sensitivity of 29% and specificity of 98%, and resident radiologists reaching sensitivity of 29% and specificity of 93%, the use of the application allowed a significant increase in sensitivity.

CONCLUSION

The presented AI application accurately decides on a patient-specific MRI protocol based on image quality analysis, potentially allowing omission of DCE in the diagnostic workup of patients with suspected prostate cancer. This could streamline workflow and optimize time utilization of healthcare professionals.

Comparison of Multiparametric MRI and the Combination of PSMA Plus MRI for the Intraprostatic Diagnosis of Prostate Cancer: A Systematic Review and Meta-Analysis

PURPOSE

The aim of this study was to perform a head-to-head comparison of multiparametric MRI (mpMRI) and the combination of prostate-specific membrane antigen (PSMA) PET plus MRI (PSMA + MRI) for detecting intraprostatic clinically significant prostate cancer (csPCa).

PATIENTS AND METHODS

Relevant databases were searched through November 2023. Only studies directly comparing mpMRI and PSMA + MRI (PET/MRI or PET/CT + mpMRI) were included. A meta-analysis with a random-effects model was used to estimate pooled sensitivity, specificity, and area under the curve for each approach.

RESULTS

A total of 19 studies were included. On a patient-level analysis, PSMA + MRI had higher sensitivity (9 studies) than mpMRI for csPCa detection (96% [95% confidence interval (CI): 92%, 98%] vs 89% [95% CI: 81%, 94%]; P = 0.04). The patient-level specificity (4 studies) of PSMA + MRI was 55% (95% CI: 31%-76%) compared with 50% (95% CI: 44%-57%) of mpMRI ( P = 0.67). Region-level sensitivity (10 studies) was 85% (95% CI: 74%-92%) for PSMA + MRI and 71% (95% CI: 58%-82%) for mpMRI ( P = 0.09), whereas specificity (4 studies) was 87% (95% CI: 76%-94%) and 90% (95% CI: 82%-95%), respectively ( P = 0.59). Lesion-level sensitivity and specificity were similar between modalities with pooled data from less than 4 studies.

CONCLUSIONS

PSMA + MRI had superior pooled sensitivity and similar specificity for the detection of csPCa compared with mpMRI in this meta-analysis of head-to-head studies.

Inter-reader Agreement for Prostate Cancer Detection Using Micro-ultrasound: A Multi-institutional Study

Background and objective

Micro-ultrasound (MUS) uses a high-frequency transducer with superior resolution to conventional ultrasound, which may differentiate prostate cancer from normal tissue and thereby allow targeted biopsy. Preliminary evidence has shown comparable sensitivity to magnetic resonance imaging (MRI), but consistency between users has yet to be described. Our objective was to assess agreement of MUS interpretation across multiple readers.

Methods

After institutional review board approval, we prospectively collected MUS images for 57 patients referred for prostate biopsy after multiparametric MRI from 2022 to 2023. MUS images were interpreted by six urologists at four institutions with varying experience (range 2-6 yr). Readers were blinded to MRI results and clinical data. The primary outcome was reader agreement on the locations of suspicious lesions, measured in terms of Light's κ and positive percent agreement (PPA). Reader sensitivity for identification of grade group (GG) ≥2 prostate cancer was a secondary outcome.

Key findings and limitations

Analysis revealed a κ value of 0.30 (95% confidence interval [CI] 0.21-0.39). PPA was 33% (95% CI 25-42%). The mean patient-level sensitivity for GG ≥2 cancer was 0.66 ± 0.05 overall and 0.87 ± 0.09 when cases with anterior lesions were excluded. Readers were 12 times more likely to detect higher-grade cancers (GG ≥3), with higher levels of agreement for this subgroup (κ 0.41, PPA 45%). Key limitations include the inability to prospectively biopsy reader-delineated targets and the inability of readers to perform live transducer maneuvers.

Conclusions and clinical implications

Inter-reader agreement on the location of suspicious lesions on MUS is lower than rates previously reported for MRI. MUS sensitivity for cancer in the anterior gland is lacking.

Patient summary

The ability to find cancer on imaging scans can vary between doctors. We found that there was frequent disagreement on the location of prostate cancer when doctors were using a new high-resolution scan method called micro-ultrasound. This suggests that the performance of micro-ultrasound is not yet consistent enough to replace MRI (magnetic resonance imaging) for diagnosis of prostate cancer.

Development and validation of a clinical decision support system based on PSA, microRNAs, and MRI for the detection of prostate cancer

OBJECTIVES

The aims of this study are to develop and validate a clinical decision support system based on demographics, prostate-specific antigen (PSA), microRNA (miRNA), and MRI for the detection of prostate cancer (PCa) and clinical significant (cs) PCa, and to assess if this system performs better compared to MRI alone.

METHODS

This retrospective, multicenter, observational study included 222 patients (mean age 66, range 46-75 years) who underwent prostate MRI, miRNA (let-7a-5p and miR-103a-3p) assessment, and biopsy. Monoparametric and multiparametric models including age, PSA, miRNA, and MRI outcome were trained on 65% of the data and then validated on the remaining 35% to predict both PCa (any Gleason grade [GG]) and csPCa (GG ≥ 2 vs GG = 1/negative). Accuracy, sensitivity, specificity, positive and negative predictive value (NPV), and area under the receiver operating characteristic curve were calculated.

RESULTS

MRI outcome was the best predictor in the monoparametric model for both detection of PCa, with sensitivity of 90% (95%CI 73-98%) and NPV of 93% (95%CI 82-98%), and for csPCa identification, with sensitivity of 91% (95%CI 72-99%) and NPV of 95% (95%CI 84-99%). Sensitivity and NPV of PSA + miRNA for the detection of csPCa were not statistically different from the other models including MRI alone.

CONCLUSION

MRI stand-alone yielded the best prediction models for both PCa and csPCa detection in biopsy-naïve patients. The use of miRNAs let-7a-5p and miR-103a-3p did not improve classification performances compared to MRI stand-alone results.

CLINICAL RELEVANCE STATEMENT

The use of miRNA (let-7a-5p and miR-103a-3p), PSA, and MRI in a clinical decision support system (CDSS) does not improve MRI stand-alone performance in the detection of PCa and csPCa.

KEY POINTS

• Clinical decision support systems including MRI improve the detection of both prostate cancer and clinically significant prostate cancer with respect to PSA test and/or microRNA. • The use of miRNAs let-7a-5p and miR-103a-3p did not significantly improve MRI stand-alone performance. • Results of this study were in line with previous works on MRI and microRNA.

Transperineal 3-Core Magnetic Resonance Imaging Ultrasound Fusion Targeted Plus Laterally 6-Core Systematic Biopsy in Prostate Cancer Diagnosis

INTRODUCTION

It is important to explore strategies reducing the number of SB cores taken to minimize biopsy-related morbidity and patient's discomfort during biopsy. This study aims to optimize prostate biopsy procedures by reducing the number of systematic biopsy (SB) cores while preserving cancer detection rates in the era of combined biopsy.

PATIENTS AND METHODS

We prospectively recruited patients with ≥1 magnetic resonance imaging (MRI) lesions and they underwent transperineal combined 12-core SB+3-core targeted prostate biopsy (TB, reference standard). New strategy was defined as a laterally 6-core SB+3-core TB. Patients were served as their own control. Detection rates for overall prostate cancer (PCa) and clinically significant PCa (csPCa) were compared among the standard SB, MRI-TB, 6-core SB +3-core TB, and reference standard. Pathology consistency was assessed using the Kappa test.

RESULTS

A total of 204 men were included, of which 111 (54.41%) and 92 (45.10%) harbored overall PCa and csPCa. Referenced combined biopsy detected significantly 6.86% (P = .0005) or 4.90% (P = .0044) more csPCa than performing only SB or 3-core TB, but was comparable to the new biopsy strategy. (45.10% vs. 43.14%, P = .1336) Similar results persisted when limiting patients in biopsy-naïve men or stratified by Prostate Imaging Reporting and Data System scores, PSAD, and index lesion parameters. Additionally, performing 6-core SB+3-core TB demonstrated high consistency with reference standard in grade group distribution (Kappa coefficient: 0.952 for all, 0.961 for biopsy-naïve men) and achieved superior sensitivity of 95.7% (All: 95% CI: 89.2%-99.8%) and 96.9% (Biopsy-naïve: 95% CI: 91.1%-99.7%), respectively.

CONCLUSIONS

The 6-core SB+3-core TB approach maintains expected detection rates while reducing the total core count, offering a promising alternative to the reference standard, which may help to tailor transperineal combined biopsy procedures.

Clinical risk prediction model and external validation of positive surgical margin in laparoscopic radical prostatectomy based on MRI lesion location

OBJECTIVE

To clarify the composition of lesions in different magnetic resonance imaging (MRI) partitions of positive surgical margins (PSM) after laparoscopic radical prostatectomy, explore the influence of lesion location on PSM, and construct a clinical prediction model to predict the risk of PSM.

MATERIALS AND METHODS

This retrospective cohort study included 309 patients who underwent laparoscopic radical prostatectomy from 2018 to 2021 in our center was performed. 129 patients who met the same criteria from January to September 2022 were external validation cohorts.

RESULTS

The incidence of PSM in transition zone (TZ) lesions was higher than that in peripheral zone (PZ) lesions. The incidence of PSM in the middle PZ was lower than that in other regions. Prostate specific antigen (PSA), clinical T-stage, the number of positive cores, international society of urological pathology (ISUP) grade (biopsy), MRI lesion location, extracapsular extension, seminal vesicle invasion (SVI), pseudo-capsule invasion (PCI), long diameter of lesions, lesion volume, lesion volume ratio, PSA density were related to PSM. MRI lesion location and PCI were independent risk factors for PSM. Least absolute shrinkage and selection operator (LASSO) regression was used to construct a clinical prediction model for PSM, including five variables: the number of positive cores, SVI, MRI lesion location, long diameter of lesions, and PSA.

CONCLUSION

The positive rate of surgical margin in middle PZ was significantly lower than that in other regions, and MRI lesion location was an independent risk factor for PSM.

Prospective close monitoring of the effect of vascular-targeted photodynamic therapy and high intensity focused ultrasound of localized prostate cancer by multiparametric magnetic resonance imaging

PURPOSE

The aim of this study is to describe the anatomical and functional changes observed in multiparametric magnetic resonance imaging (mpMRI) during follow-up after focal therapy (FT) for localized prostate cancer (PCa).

MATERIALS AND METHODS

In this prospective study, we analyzed pre- and postoperatively acquired mpMRI of 10 patients after FT (7 days; 3, 6, 9, 12 months). 7/10 (70%) patients underwent vascular-targeted photodynamic therapy (VTP). 3/10 (30%) patients underwent high-intensity focused ultrasound (HIFU). MpMR image analysis was performed using a semi-automatic software for segmentation of the prostate gland (PG) and tumor zones. Signal intensities (SI) of T2-weighted (T2w), T1-weighted (T1w),diffusion-weighted (DWI) and dynamic contrast-enhanced (DCE) images as well as volumes of the prostate gland (PGV) and tumor volumes (TV) were evaluated at each time point.

RESULTS

The results showed a significant increase of PGV 7 days after FT (p = 0.042) and a significant reduction of PGV between 7 days and 6, 9 and 12 months after FT (p < 0.001). The TV increased significantly 7 days after FT (p < 0.001) and decreased significantly between 7 days and 12 months after FT (p < 0.001). There was a significant increase in SI of the ADC in the ablation zone after 6, 9 and 12 months after FT (p < 0.001). 1/9 patients (11%) had recurrent tumor on rebiopsy characterized as a a small focal lesion on mpMRI with strong diffusion restriction (low SI on ADC map and high SI on b-value DWI).

CONCLUSION

MpMRI is able to represent morphologic changes of the ablated zone after FT and might be helpful to detect recurrent tumor.

A comparative study of 18F-PSMA-1007 PET/CT and pelvic MRI in newly diagnosed prostate cancer

PURPOSE

To evaluate the difference in the diagnostic efficacy of 18F-PSMA-1007 PET/CT and pelvic MRI in primary prostate cancer, as well as the correlation between the two methods and histopathological parameters and serum PSA levels.

METHODS

A total of 41 patients with suspected prostate cancer who underwent 18F-PSMA-1007 PET/CT imaging in our department from 2018 to 2023 were retrospectively collected. All patients underwent 18F-PSMA-1007 PET/CT and MRI scans. The sensitivity, PPV and diagnostic accuracy of MRI and 18F-PSMA-1007 PET/CT in the diagnosis of prostate cancer were calculated after comparing the results of MRI and 18F-PSMA-1007 PET/CT with biopsy. The Spearman test was used to calculate the correlation between 18F-PSMA-1007 PET/CT, MRI parameters, histopathological indicators, and serum PSA levels.

RESULTS

Compared with histopathological results, the sensitivity, PPV and diagnostic accuracy of 18F-PSMA-1007 PET/CT in the diagnosis of prostate cancer were 95.1%, 100.0% and 95.1%, respectively. The sensitivity, PPV and diagnostic accuracy of MRI in the diagnosis of prostate cancer were 82.9%, 100.0% and 82.9%, respectively. There was a mild to moderately positive correlation between Gleason (Gs) score, Ki-67 index, serum PSA level and 18F-PSMA-1007 PET/CT parameters (p < 0.05). There was a moderately negative correlation between the expression of AMACR (P504S) and 18F-PSMA-1007 PET/CT parameters (p < 0.05). The serum PSA level and the Gs score were moderately positively correlated with the MRI parameters (p < 0.05). There was no correlation between histopathological parameters and MRI parameters (p > 0.05).

CONCLUSION

Compared with MRI, 18F-PSMA-1007 PET/CT has higher sensitivity and diagnostic accuracy in the detection of malignant prostate tumors. In addition, the Ki-67 index and AMACR (P504S) expression were only correlated with 18F-PSMA-1007 PET/CT parameters. Gs score and serum PSA level were correlated with 18F-PSMA-1007 PET/CT and MRI parameters. 18F-PSMA-1007 PET/CT examination can provide certain reference values for the clinical diagnosis, evaluation, and treatment of malignant prostate tumors.

Clinically significant prostate cancer detection rate in biopsy-naïve patients with mpMRI and microultrasound topographically discordant lesions: A single-center retrospective analysis

INTRODUCTION AND OBJECTIVES

Multiparametric magnetic resonance imaging (mpMRI) has improved the detection of clinically significant prostate cancer (csPCa), and microultrasound (micro-US) shows promise in enhancing detection rates. We compared mpMRI-guided targeted biopsy (MTBx) and micro-US-guided targeted biopsy (micro-US-TBx) in biopsy-naïve patients with discordant lesions at micro-US and mpMRI to detect csPCa (grade group ≥2) and clinically insignificant PCa (ciPCa; grade group 1) and assessed the role of nontargeted systematic biopsy (SBx).

MATERIAL AND METHODS

We analyzed 178 biopsy-naive men with suspected PCa and discordant lesions at mpMRI and micro-US. All patients underwent mpMRI followed by micro-US, the latter being performed immediately before the biopsy. Imaging findings were interpreted blindly, followed by targeted and SBx. Median age was 63 years (IQR, 57-70), median prostate-specific antigen level was 7 ng/mL (IQR, 5-9 ng/mL), and median prostate volume was 49 cm^3 (IQR, 35-64 cm^3). Overall, 86/178 (48%) patients were diagnosed with PCa, 51/178 (29%) with csPCa.

RESULTS

Micro-USTBx detected csPCa in 36/178 men (20%; 95% CI: 26-46), and MTBx detected csPCa in 28/178 men (16%; 95% CI: 36-50), resulting in a -8% difference (95% CI: -10, 4; P = 0.022) and a relative detection rate of 0.043. Micro-USTBx detected ciPCa in 9/178 men (5%; 95% CI: 3, 15), while MTBx detected ciPCa in 12/178 men (7%; 95% CI: 5, 20), resulting in a -3% difference (95% CI: -2 to 4; P = 0.2) and a relative detection rate of 0.1. SBx detected ciPCa in 29 (16%) men. mpMRI plus micro-US detected csPCa in 51/178 men, with no additional cases with the addition of SBx. Similarly, MTBx plus micro-USTBx plus SBx detected ciPCa in 35/178 men (20%; 95% CI: 18, 37) compared to 9 (5%) in the micro-US pathway (P = 0.002) and 14/178 (8%; 95% CI: 6, 26) in the mpMRI plus micro-US pathway (P = 0.004).

CONCLUSIONS

In conclusion, a combined micro-US/mpMRI approach could characterize primary disease in biopsy-naïve patients with discordant lesions, potentially avoiding SBx. Further studies are needed to validate our findings and assess micro-US's role in reducing unnecessary biopsies.

Biparametric MRI of the prostate radiomics model for prediction of pelvic lymph node metastasis in prostate cancers : a two-centre study

OBJECTIVES

Exploring the value of adding correlation analysis (radiomic features (RFs) of pelvic metastatic lymph nodes and primary lesions) to screen RFs of primary lesions in the feature selection process of establishing prediction model.

METHODS

A total of 394 prostate cancer (PCa) patients (263 in the training group, 74 in the internal validation group and 57 in the external validation group) from two tertiary hospitals were included in the study. The cases with pelvic lymph node metastasis (PLNM) positive in the training group were diagnosed by biopsy or MRI with a short-axis diameter ≥ 1.5 cm, PLNM-negative cases in the training group and all cases in validation group were underwent both radical prostatectomy (RP) and extended pelvic lymph node dissection (ePLND). The RFs of PLNM-negative lesion and PLNM-positive tissues including primary lesions and their metastatic lymph nodes (MLNs) in the training group were extracted from T2WI and apparent diffusion coefficient (ADC) map to build the following two models by fivefold cross-validation: the lesion model, established according to the primary lesion RFs selected by t tests and absolute shrinkage and selection operator (LASSO); the lesion-correlation model, established according to the primary lesion RFs selected by Pearson correlation analysis (RFs of primary lesions and their MLNs, correlation coefficient > 0.9), t test and LASSO. Finally, we compared the performance of these two models in predicting PLNM.

RESULTS

The AUC and the DeLong test of AUC in the lesion model and lesion-correlation model were as follows: training groups (0.8053, 0.8466, p = 0.0002), internal validation group (0.7321, 0.8268, p = 0.0429), and external validation group (0.6445, 0.7874, p = 0.0431), respectively.

CONCLUSION

The lesion-correlation model established by features of primary tumors correlated with MLNs has more advantages than the lesion model in predicting PLNM.

Refining clinically relevant cut-offs of prostate specific antigen density for risk stratification in patients with PI-RADS 3 lesions

BACKGROUND

Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions, identified through multiparametric magnetic resonance imaging (mpMRI), present a clinical challenge due to their equivocal nature in predicting clinically significant prostate cancer (csPCa). Aim of the study is to improve risk stratification of patients with PI-RADS 3 lesions and candidates for prostate biopsy.

METHODS

A cohort of 4841 consecutive patients who underwent MRI and subsequent MRI-targeted and systematic biopsies between January 2016 and April 2023 were retrospectively identified from independent prospectively maintained database. Only patients who have PI-RADS 3 lesions were included in the final analysis. A multivariable logistic regression analysis was performed to identify covariables associated with csPCa defined as International Society of Urological Pathology (ISUP) grade group ≥2. Performance of the model was evaluated using the area under the receiver operating characteristic curve (AUC), calibration, and net benefit. Significant predictors were then selected for further exploration using a Chi-squared Automatic Interaction Detection (CHAID) analysis.

RESULTS

Overall, 790 patients had PI-RADS 3 lesions and 151 (19%) had csPCa. Significant associations were observed for age (OR: 1.1 [1.0-1.1]; p = 0.01) and PSA density (OR: 1643 [2717-41,997]; p < 0.01). The CHAID analysis identified PSAd as the sole significant factor influencing the decision tree. Cut-offs for PSAd were 0.13 ng/ml/cc (csPCa detection rate of 1% vs. 18%) for the two-nodes model and 0.09 ng/ml/cc and 0.16 ng/ml/cc for the three-nodes model (csPCa detection rate of 0.5% vs. 2% vs. 17%).

CONCLUSIONS

For individuals with PI-RADS 3 lesions on prostate mpMRI and a PSAd below 0.13, especially below 0.09, prostate biopsy can be omitted, in order to avoid unnecessary biopsy and overdiagnosis of non-csPCa.

Association between mpMRI detected tumor apparent diffusion coefficient and 5-year biochemical recurrence risk after radical prostatectomy

PURPOSE

To assess the ability of tumor apparent diffusion coefficient (ADC) values obtained from multiparametric magnetic resonance imaging (mpMRI) to predict the risk of 5-year biochemical recurrence (BCR) after radical prostatectomy (RP).

MATERIALS AND METHODS

This retrospective analysis included 1207 peripheral and 232 non-peripheral zone prostate cancer (PCa) patients who underwent mpMRI before RP (2012-2015), with the outcome of interest being 5-year BCR. ADC was evaluated as a continuous variable and as categories: low (< 850 µm2/s), intermediate (850-1100 µm2/s), and high (> 1100 µm2/s). Kaplan-Meier curves with log-rank testing of BCR-free survival, multivariable Cox proportional hazard regression models were formed to estimate the risk of BCR.

RESULTS

Among the 1439 males with median age 63 (± 7) years, the median follow-up was 59 months, and 306 (25%) patients experienced BCR. Peripheral zone PCa patients with BCR had lower tumor ADC values than those without BCR (874 versus 1025 µm2/s, p < 0.001). Five-year BCR-free survival rates were 52.3%, 74.4%, and 87% for patients in the low, intermediate, and high ADC value categories, respectively (p < 0.0001). Lower ADC was associated with BCR, both as continuously coded variable (HR: 5.35; p < 0.001) and as ADC categories (intermediate versus high ADC-HR: 1.56, p = 0.017; low vs. high ADC-HR; 2.36, p < 0.001). In the non-peripheral zone PCa patients, no association between ADC and BCR was observed.

CONCLUSION

Tumor ADC values and categories were found to be predictive of the 5-year BCR risk after RP in patients with peripheral zone PCa and may serve as a prognostic biomarker.

Target Volume Optimization for Localized Prostate Cancer

PURPOSE

To provide a comprehensive review of the means by which to optimize target volume definition for the purposes of treatment planning for patients with intact prostate cancer with a specific emphasis on focal boost volume definition.

METHODS

Here we conduct a narrative review of the available literature summarizing the current state of knowledge on optimizing target volume definition for the treatment of localized prostate cancer.

RESULTS

Historically, the treatment of prostate cancer included a uniform prescription dose administered to the entire prostate with or without coverage of all or part of the seminal vesicles. The development of prostate magnetic resonance imaging (MRI) and positron emission tomography (PET) using prostate-specific radiotracers has ushered in an era in which radiation oncologists are able to localize and focally dose-escalate high-risk volumes in the prostate gland. Recent phase 3 data has demonstrated that incorporating focal dose escalation to high-risk subvolumes of the prostate improves biochemical control without significantly increasing toxicity. Still, several fundamental questions remain regarding the optimal target volume definition and prescription strategy to implement this technique. Given the remaining uncertainty, a knowledge of the pathological correlates of radiographic findings and the anatomic patterns of tumor spread may help inform clinical judgement for the definition of clinical target volumes.

CONCLUSION

Advanced imaging has the ability to improve outcomes for patients with prostate cancer in multiple ways, including by enabling focal dose escalation to high-risk subvolumes. However, many questions remain regarding the optimal target volume definition and prescription strategy to implement this practice, and key knowledge gaps remain. A detailed understanding of the pathological correlates of radiographic findings and the patterns of local tumor spread may help inform clinical judgement for target volume definition given the current state of uncertainty.

Comparison of synthesized and acquired high b-value diffusion-weighted MRI for detection of prostate cancer

BACKGROUND

High b-value diffusion-weighted images (DWI) are used for detection of clinically significant prostate cancer (csPCa). This study qualitatively and quantitatively compares synthesized DWI (sDWI) to acquired (aDWI) for detection of csPCa.

METHODS

One hundred fifty-one consecutive patients who underwent prostate MRI and biopsy were included in the study. Axial DWI with b = 0, 500, 1000, and 2000 s/mm2 using a 3T clinical scanner using a 32-channel phased-array body coil were acquired. We retrospectively synthesized DWI for b = 2000 s/mm2 via extrapolation based on mono-exponential decay, using b = 0 and b = 500 s/mm2 (sDWI500) and b = 0, b = 500 s/mm2, and b = 1000 s/mm2 (sDWI1000). Differences in signal intensity between sDWI and aDWI were evaluated within different regions of interest (prostate alone, prostate plus 5 mm, 30 mm and 70 mm margin and full field of view). The maximum DWI value within each ROI was evaluated for prediction of csPCa. Classification accuracy was compared to Restriction Spectrum Imaging restriction score (RSIrs), a previously validated biomarker based on multi-exponential DWI. Discrimination of csPCa was evaluated via area under the receiver operating characteristic curve (AUC).

RESULTS

Within the prostate, mean ± standard deviation of percent mean differences between sDWI and aDWI signal were -46 ± 35% for sDWI1000 and -67 ± 24% for sDWI500. AUC for aDWI, sDWI500, sDWI1000, and RSIrs within the prostate 0.62[95% confidence interval: 0.53, 0.71], 0.63[0.54, 0.72], 0.65[0.56, 0.73] and 0.78[0.71, 0.86], respectively.

CONCLUSION

sDWI is qualitatively comparable to aDWI within the prostate. However, hyperintense artifacts are introduced with sDWI in the surrounding pelvic tissue that interfere with quantitative cancer detection and might mask metastases. In the prostate, RSIrs yields superior quantitative csPCa detection than sDWI or aDWI.

Non-invasively identifying candidates of active surveillance for prostate cancer using magnetic resonance imaging radiomics

Active surveillance (AS) is the primary strategy for managing patients with low or favorable-intermediate risk prostate cancer (PCa). Identifying patients who may benefit from AS relies on unpleasant prostate biopsies, which entail the risk of bleeding and infection. In the current study, we aimed to develop a radiomics model based on prostate magnetic resonance images to identify AS candidates non-invasively. A total of 956 PCa patients with complete biopsy reports from six hospitals were included in the current multicenter retrospective study. The National Comprehensive Cancer Network (NCCN) guidelines were used as reference standards to determine the AS candidacy. To discriminate between AS and non-AS candidates, five radiomics models (i.e., eXtreme Gradient Boosting (XGBoost) AS classifier (XGB-AS), logistic regression (LR) AS classifier, random forest (RF) AS classifier, adaptive boosting (AdaBoost) AS classifier, and decision tree (DT) AS classifier) were developed and externally validated using a three-fold cross-center validation based on five classifiers: XGBoost, LR, RF, AdaBoost, and DT. Area under the receiver operating characteristic curve (AUC), accuracy (ACC), sensitivity (SEN), and specificity (SPE) were calculated to evaluate the performance of these models. XGB-AS exhibited an average of AUC of 0.803, ACC of 0.693, SEN of 0.668, and SPE of 0.841, showing a better comprehensive performance than those of the other included radiomic models. Additionally, the XGB-AS model also presented a promising performance for identifying AS candidates from the intermediate-risk cases and the ambiguous cases with diagnostic discordance between the NCCN guidelines and the Prostate Imaging-Reporting and Data System assessment. These results suggest that the XGB-AS model has the potential to help identify patients who are suitable for AS and allow non-invasive monitoring of patients on AS, thereby reducing the number of annual biopsies and the associated risks of bleeding and infection.

Integration of PSAd and multiparametric MRI to forecast biopsy outcomes in biopsy-naïve patients with PSA 4~20 ng/ml

Introduction

This study aims to investigate whether the transrectal ultrasound-guided combined biopsy (CB) improves the detection rates of prostate cancer (PCa) and clinically significant PCa (csPCa) in biopsy-naïve patients. We also aimed to compare the Prostate Imaging Reporting and Data System (PI-RADS v2.1) score, ADC values, and PSA density (PSAd) in predicting csPCa by the combined prostate biopsy.

Methods

This retrospective and single-center study included 389 biopsy-naïve patients with PSA level 4~20 ng/ml, of whom 197 underwent prebiopsy mpMRI of the prostate. The mpMRI-based scores (PI-RADS v2.1 scores and ADC values) and clinical parameters were collected and evaluated by logistic regression analyses. Multivariable models based on the mpMRI-based scores and clinical parameters were developed by the logistic regression analyses to forecast biopsy outcomes of CB in biopsy-naïve patients. The ROC curves measured by the AUC values, calibration plots, and DCA were performed to assess multivariable models.

Results

The CB can detect more csPCa compared with TRUSB (32.0% vs. 53%). The Spearman correlation revealed that Gleason scores of the prostate biopsy significantly correlated with PI-RADS scores and ADC values. The multivariate logistic regression confirmed that PI-RADS scores 4, 5, and prostate volume were important predictors of csPCa. The PI-RADS+ADC+PSAd (PAP) model had the highest AUCs of 0.913 for predicting csPCa in biopsy-naïve patients with PSA level 4~20 ng/ml. When the biopsy risk threshold of the PAP model was greater than or equal to 0.10, 51% of patients could avoid an unnecessary biopsy, and only 5% of patients with csPCa were missed.

Conclusion

The prebiopsy mpMRI and the combined prostate biopsy have a high CDR of csPCa in biopsy-naïve patients. A multivariable model based on the mpMRI-based scores and PSAd could provide a reference for clinicians in forecasting biopsy outcomes in biopsy-naïve patients with PSA 4~20 ng/ml and make a more comprehensive assessment during the decision-making of the prostate biopsy.

Clinical-imaging metrics for the diagnosis of prostate cancer in PI-RADS 3 lesions

OBJECTIVE

To explore the feasibility and efficacy of clinical-imaging metrics in the diagnosis of prostate cancer (PCa) and clinically significant prostate cancer (csPCa) in prostate imaging-reporting and data system (PI-RADS) category 3 lesions.

METHODS

A retrospective analysis was conducted on lesions diagnosed as PI-RADS 3. They were categorized into benign, non-csPCa and csPCa groups. Apparent diffusion coefficient (ADC), T2-weighted imaging signal intensity (T2WISI), coefficient of variation of ADC and T2WISI, prostate-specific antigen density (PSAD), ADC density (ADCD), prostate-specific antigen lesion volume density (PSAVD) and ADC lesion volume density (ADCVD) were measured and calculated. Univariate and multivariate analyses were used to identify risk factors associated with PCa and csPCa. Receiver operating characteristic curve (ROC) and decision curves were utilized to assess the efficacy and net benefit of independent risk factors.

RESULTS

Among 202 patients, 133 had benign prostate disease, 25 non-csPCa and 44 csPCa. Age, PSA and lesion location showed no significant differences (P > 0.05) among the groups. T2WISI and coefficient of variation of ADC (ADCcv) were independent risk factors for PCa in PI-RADS 3 lesions, yielding an area under the curve (AUC) of 0.68. ADC was an independent risk factor for csPCa in PI-RADS 3 lesions, yielding an AUC of 0.65. Decision curve analysis showed net benefit for patients at certain probability thresholds.

CONCLUSIONS

T2WISI and ADCcv, along with ADC, respectively showed considerable promise in enhancing the diagnosis of PCa and csPCa in PI-RADS 3 lesions.

Deep learning-based image quality assessment: impact on detection accuracy of prostate cancer extraprostatic extension on MRI

OBJECTIVE

To assess impact of image quality on prostate cancer extraprostatic extension (EPE) detection on MRI using a deep learning-based AI algorithm.

MATERIALS AND METHODS

This retrospective, single institution study included patients who were imaged with mpMRI and subsequently underwent radical prostatectomy from June 2007 to August 2022. One genitourinary radiologist prospectively evaluated each patient using the NCI EPE grading system. Each T2WI was classified as low- or high-quality by a previously developed AI algorithm. Fisher's exact tests were performed to compare EPE detection metrics between low- and high-quality images. Univariable and multivariable analyses were conducted to assess the predictive value of image quality for pathological EPE.

RESULTS

A total of 773 consecutive patients (median age 61 [IQR 56-67] years) were evaluated. At radical prostatectomy, 23% (180/773) of patients had EPE at pathology, and 41% (131/318) of positive EPE calls on mpMRI were confirmed to have EPE. The AI algorithm classified 36% (280/773) of T2WIs as low-quality and 64% (493/773) as high-quality. For EPE grade ≥ 1, high-quality T2WI significantly improved specificity for EPE detection (72% [95% CI 67-76%] vs. 63% [95% CI 56-69%], P = 0.03), but did not significantly affect sensitivity (72% [95% CI 62-80%] vs. 75% [95% CI 63-85%]), positive predictive value (44% [95% CI 39-49%] vs. 38% [95% CI 32-43%]), or negative predictive value (89% [95% CI 86-92%] vs. 89% [95% CI 85-93%]). Sensitivity, specificity, PPV, and NPV for EPE grades ≥ 2 and ≥ 3 did not show significant differences attributable to imaging quality. For NCI EPE grade 1, high-quality images (OR 3.05, 95% CI 1.54-5.86; P < 0.001) demonstrated a stronger association with pathologic EPE than low-quality images (OR 1.76, 95% CI 0.63-4.24; P = 0.24).

CONCLUSION

Our study successfully employed a deep learning-based AI algorithm to classify image quality of prostate MRI and demonstrated that better quality T2WI was associated with more accurate prediction of EPE at final pathology.

Prostate cancer risk assessment and avoidance of prostate biopsies using fully automatic deep learning in prostate MRI: comparison to PI-RADS and integration with clinical data in nomograms

OBJECTIVES

Risk calculators (RCs) improve patient selection for prostate biopsy with clinical/demographic information, recently with prostate MRI using the prostate imaging reporting and data system (PI-RADS). Fully-automated deep learning (DL) analyzes MRI data independently, and has been shown to be on par with clinical radiologists, but has yet to be incorporated into RCs. The goal of this study is to re-assess the diagnostic quality of RCs, the impact of replacing PI-RADS with DL predictions, and potential performance gains by adding DL besides PI-RADS.

MATERIAL AND METHODS

One thousand six hundred twenty-seven consecutive examinations from 2014 to 2021 were included in this retrospective single-center study, including 517 exams withheld for RC testing. Board-certified radiologists assessed PI-RADS during clinical routine, then systematic and MRI/Ultrasound-fusion biopsies provided histopathological ground truth for significant prostate cancer (sPC). nnUNet-based DL ensembles were trained on biparametric MRI predicting the presence of sPC lesions (UNet-probability) and a PI-RADS-analogous five-point scale (UNet-Likert). Previously published RCs were validated as is; with PI-RADS substituted by UNet-Likert (UNet-Likert-substituted RC); and with both UNet-probability and PI-RADS (UNet-probability-extended RC). Together with a newly fitted RC using clinical data, PI-RADS and UNet-probability, existing RCs were compared by receiver-operating characteristics, calibration, and decision-curve analysis.

RESULTS

Diagnostic performance remained stable for UNet-Likert-substituted RCs. DL contained complementary diagnostic information to PI-RADS. The newly-fitted RC spared 49% [252/517] of biopsies while maintaining the negative predictive value (94%), compared to PI-RADS ≥ 4 cut-off which spared 37% [190/517] (p < 0.001).

CONCLUSIONS

Incorporating DL as an independent diagnostic marker for RCs can improve patient stratification before biopsy, as there is complementary information in DL features and clinical PI-RADS assessment.

CLINICAL RELEVANCE STATEMENT

For patients with positive prostate screening results, a comprehensive diagnostic workup, including prostate MRI, DL analysis, and individual classification using nomograms can identify patients with minimal prostate cancer risk, as they benefit less from the more invasive biopsy procedure.

KEY POINTS

The current MRI-based nomograms result in many negative prostate biopsies. The addition of DL to nomograms with clinical data and PI-RADS improves patient stratification before biopsy. Fully automatic DL can be substituted for PI-RADS without sacrificing the quality of nomogram predictions. Prostate nomograms show cancer detection ability comparable to previous validation studies while being suitable for the addition of DL analysis.

Diagnostic Performance of [18F]AlF-Thretide PET/CT in Patients with Newly Diagnosed Prostate Cancer Using Histopathology as Reference Standard

This study aimed to assess the diagnostic value of [18F]AlF-thretide PET/CT in patients with newly diagnosed prostate cancer (PCa). Methods: In total, 49 patients with biopsy-proven PCa were enrolled in this prospective study. All patients underwent [18F]AlF-thretide PET/CT, and the scoring system of the PRIMARY trial was used for PET image analysis. The dosimetry evaluation of [18F]AlF-thretide was performed on 3 patients. Pathologic examination was used as the reference standard to evaluate the location, number, size, and Gleason score of tumors, for comparison with the [18F]AlF-thretide PET/CT results. PSMA expression was evaluated by immunohistochemical staining. Results: All patients tolerated the [18F]AlF-thretide PET/CT well. The total effective dose of [18F]AlF-thretide was 1.16E-02 mSv/MBq. For patient-based analysis of intraprostatic tumors, 46 of 49 (93.9%) patients showed pathologic uptake on [18F]AlF-thretide PET/CT. For lesion-based analysis of intraprostatic tumors, the sensitivity and positive predictive value for [18F]AlF-thretide PET/CT were 58.2% and 90.5%, respectively. Delayed images can detect more lesions than standard images (n = 57 vs. 49, P = 0.005), and the SUVmax and tumor-to-background ratio of the former were higher than those of the latter (SUVmax: 14.5 ± 16.7 vs. 11.4 ± 13.6, P < 0.001; tumor-to-background ratio: 37.1 ± 42.3 vs. 23.1 ± 27.4, P < 0.001). The receiver-operating-characteristic curve analysis showed that the areas under the curve for PRIMARY score-predicted true-positive and false-positive lesions were significantly higher than those for the SUVmax of standard images (P = 0.015) and seemed higher than those for the SUVmax of delayed images (P = 0.257). [18F]AlF-thretide PET/CT showed a higher detection rate than multiparametric MRI for all intraprostatic foci (53.5% vs. 40.8%, P = 0.012) and clinically significant PCa (75.0% vs. 61.4%, P = 0.031). Conclusion: [18F]AlF-thretide PET/CT showed high diagnostic value for patients with primary PCa and can be used as an excellent imaging modality for preoperative evaluation of PCa patients.

Transperineal Versus Transrectal Magnetic Resonance Imaging-targeted and Systematic Prostate Biopsy to Prevent Infectious Complications: The PREVENT Randomized Trial

BACKGROUND AND OBJECTIVE

The transrectal biopsy approach is traditionally used to detect prostate cancer. An alternative transperineal approach is historically performed under general anesthesia, but recent advances enable transperineal biopsy to be performed under local anesthesia. We sought to compare infectious complications of transperineal biopsy without antibiotic prophylaxis versus transrectal biopsy with targeted prophylaxis.

METHODS

We assigned biopsy-naïve participants to undergo transperineal biopsy without antibiotic prophylaxis versus transrectal biopsy with targeted prophylaxis (rectal culture screening for fluoroquinolone-resistant bacteria and antibiotic targeting to culture and sensitivity results) through a multicenter, randomized trial. The primary outcome was post-biopsy infection captured by a prospective medical review and patient report on a 7-d survey. The secondary outcomes included cancer detection, noninfectious complications, and a numerical rating scale (0-10) for biopsy-related pain and discomfort during and 7-d after biopsy.

KEY FINDINGS AND LIMITATIONS

A total of 658 participants were randomized, with zero transperineal versus four (1.4%) transrectal biopsy infections (difference -1.4%; 95% confidence interval [CI] -3.2%, 0.3%; p = 0.059). The rates of other complications were very low and similar. Importantly, detection of clinically significant cancer was similar (53% transperineal vs 50% transrectal, adjusted difference 2.0%; 95% CI -6.0, 10). Participants in the transperineal arm experienced worse periprocedural pain (0.6 adjusted difference [0-10 scale], 95% CI 0.2, 0.9), but the effect was small and resolved by 7-d.

CONCLUSIONS AND CLINICAL IMPLICATIONS

Office-based transperineal biopsy is tolerable, does not compromise cancer detection, and did not result in infectious complications. Transrectal biopsy with targeted prophylaxis achieved similar infection rates, but requires rectal cultures and careful attention to antibiotic selection and administration. Consideration of these factors and antibiotic stewardship should guide clinical decision-making.

PATIENT SUMMARY

In this multicenter randomized trial, we compare prostate biopsy infectious complications for the transperineal versus transrectal approach. The absence of infectious complications with transperineal biopsy without the use of preventative antibiotics is noteworthy, but not significantly different from transrectal biopsy with targeted antibiotic prophylaxis.

Artificial intelligence and radiologists in prostate cancer detection on MRI (PI-CAI): an international, paired, non-inferiority, confirmatory study

BACKGROUND

Artificial intelligence (AI) systems can potentially aid the diagnostic pathway of prostate cancer by alleviating the increasing workload, preventing overdiagnosis, and reducing the dependence on experienced radiologists. We aimed to investigate the performance of AI systems at detecting clinically significant prostate cancer on MRI in comparison with radiologists using the Prostate Imaging-Reporting and Data System version 2.1 (PI-RADS 2.1) and the standard of care in multidisciplinary routine practice at scale.

METHODS

In this international, paired, non-inferiority, confirmatory study, we trained and externally validated an AI system (developed within an international consortium) for detecting Gleason grade group 2 or greater cancers using a retrospective cohort of 10 207 MRI examinations from 9129 patients. Of these examinations, 9207 cases from three centres (11 sites) based in the Netherlands were used for training and tuning, and 1000 cases from four centres (12 sites) based in the Netherlands and Norway were used for testing. In parallel, we facilitated a multireader, multicase observer study with 62 radiologists (45 centres in 20 countries; median 7 [IQR 5-10] years of experience in reading prostate MRI) using PI-RADS (2.1) on 400 paired MRI examinations from the testing cohort. Primary endpoints were the sensitivity, specificity, and the area under the receiver operating characteristic curve (AUROC) of the AI system in comparison with that of all readers using PI-RADS (2.1) and in comparison with that of the historical radiology readings made during multidisciplinary routine practice (ie, the standard of care with the aid of patient history and peer consultation). Histopathology and at least 3 years (median 5 [IQR 4-6] years) of follow-up were used to establish the reference standard. The statistical analysis plan was prespecified with a primary hypothesis of non-inferiority (considering a margin of 0·05) and a secondary hypothesis of superiority towards the AI system, if non-inferiority was confirmed. This study was registered at ClinicalTrials.gov, NCT05489341.

FINDINGS

Of the 10 207 examinations included from Jan 1, 2012, through Dec 31, 2021, 2440 cases had histologically confirmed Gleason grade group 2 or greater prostate cancer. In the subset of 400 testing cases in which the AI system was compared with the radiologists participating in the reader study, the AI system showed a statistically superior and non-inferior AUROC of 0·91 (95% CI 0·87-0·94; p<0·0001), in comparison to the pool of 62 radiologists with an AUROC of 0·86 (0·83-0·89), with a lower boundary of the two-sided 95% Wald CI for the difference in AUROC of 0·02. At the mean PI-RADS 3 or greater operating point of all readers, the AI system detected 6·8% more cases with Gleason grade group 2 or greater cancers at the same specificity (57·7%, 95% CI 51·6-63·3), or 50·4% fewer false-positive results and 20·0% fewer cases with Gleason grade group 1 cancers at the same sensitivity (89·4%, 95% CI 85·3-92·9). In all 1000 testing cases where the AI system was compared with the radiology readings made during multidisciplinary practice, non-inferiority was not confirmed, as the AI system showed lower specificity (68·9% [95% CI 65·3-72·4] vs 69·0% [65·5-72·5]) at the same sensitivity (96·1%, 94·0-98·2) as the PI-RADS 3 or greater operating point. The lower boundary of the two-sided 95% Wald CI for the difference in specificity (-0·04) was greater than the non-inferiority margin (-0·05) and a p value below the significance threshold was reached (p<0·001).

INTERPRETATION

An AI system was superior to radiologists using PI-RADS (2.1), on average, at detecting clinically significant prostate cancer and comparable to the standard of care. Such a system shows the potential to be a supportive tool within a primary diagnostic setting, with several associated benefits for patients and radiologists. Prospective validation is needed to test clinical applicability of this system.

FUNDING

Health~Holland and EU Horizon 2020.

Biparametric versus multiparametric MRI for the detection of clinically significant prostate cancer in a diverse, multiethnic population

PURPOSE

There is not yet satisfactory performance data comparing multiparametric MRI (mpMRI) versus biparametric MRI (bpMRI) for detecting prostate cancer (PCa), particularly in high-risk populations. We compared both protocols for detecting overall PCa and clinically significant PCa (CS-PCa; defined as Grade Group ≥ 2) in a multiethnic urban population.

METHODS

We retrospectively reviewed electronic medical record data from men who underwent image-guided fusion prostate biopsy (FB) between 2016 and 2021 at our institution. Patient characteristics, Prostate Imaging Reporting and Data System (PI-RADS) scores, and FB outcomes were analyzed based on MRI protocol. Multivariate mixed-effects logistic regression models were used to examine associations of bpMRI versus mpMRI for detecting overall PCa and CS-PCa in targeted lesions, among all patients and stratified by race/ethnicity.

RESULTS

Overall, 566 men (44.0% Non-Hispanic Black [NHB]; 27.0% Hispanic) with 975 PI-RADS 3-5 lesions on MRI underwent FB. Of these, 312 (55%) men with 497 lesions underwent mpMRI and 254 (45%) men with 478 lesions underwent bpMRI. On multivariate analyses among all men, the odds of detecting overall PCa (OR = 1.18, 95% CI: 1.05-3.11, p = 0.031) and CS-PCa (OR = 2.15, 95% CI: 1.16-4.00, p = 0.014) on FB were higher for lesions identified on bpMRI than mpMRI. When stratified by race/ethnicity, the odds of detecting overall PCa (OR = 1.86; p = 0.15) and CS-PCa (OR = 2.20; p = 0.06) were not statistically different between lesions detected on bpMRI or mpMRI.

CONCLUSION

BpMRI has similar diagnostic performance to mpMRI in detecting overall and CS-PCa within a racially/ethnically diverse population. BpMRI can be utilized for evaluating suspected CS-PCa among NHB and Hispanic men.

MRI-guided in-bore biopsy of the prostate - defining the optimal number of cores needed

BACKGROUND

Numerous studies have shown that magnetic resonance imaging (MRI)-targeted biopsy approaches are superior to traditional systematic transrectal ultrasound guided biopsy (TRUS-Bx). The optimal number of biopsy cores to be obtained per lesion identified on multiparametric MRI (mpMRI) images, however, remains a matter of debate. The aim of this study was to evaluate the incremental value of additional biopsy cores in an MRI-targeted "in-bore"-biopsy (MRI-Bx) setting.

PATIENTS AND METHODS

Two hundred and forty-five patients, who underwent MRI-Bx between June 2014 and September 2021, were included in this retrospective single-center analysis. All lesions were biopsied with at least five biopsy cores and cumulative detection rates for any cancer (PCa) as well as detection rates of clinically significant cancers (csPCa) were calculated for each sequentially labeled biopsy core. The cumulative per-core detection rates are presented as whole numbers and as proportion of the maximum detection rate reached, when all biopsy cores were considered. CsPCa was defined as Gleason Score (GS) ≥ 7 (3 + 4).

RESULTS

One hundred and thirty-two of 245 Patients (53.9%) were diagnosed with prostate cancer and csPCa was found in 64 (26.1%) patients. The first biopsy core revealed csPCa/ PCa in 76.6% (49/64)/ 81.8% (108/132) of cases. The second, third and fourth core found csPCa/ PCa not detected by previous cores in 10.9% (7/64)/ 8.3% (11/132), 7.8% (5/64)/ 5.3% (7/132) and 3.1% (2/64)/ 3% (4/132) of cases, respectively. Obtaining one or more cores beyond the fourth biopsy core resulted in an increase in detection rate of 1.6% (1/64)/ 1.5% (2/132).

CONCLUSION

We found that obtaining five cores per lesion maximized detection rates. If, however, future research should establish a clear link between the incidence of serious complications and the number of biopsy cores obtained, a three-core biopsy might suffice as our results suggest that about 95% of all csPCa are detected by the first three cores.

Manual prostate MRI segmentation by readers with different experience: a study of the learning progress

OBJECTIVE

To evaluate the learning progress of less experienced readers in prostate MRI segmentation.

MATERIALS AND METHODS

One hundred bi-parametric prostate MRI scans were retrospectively selected from the Göteborg Prostate Cancer Screening 2 Trial (single center). Nine readers with varying degrees of segmentation experience were involved: one expert radiologist, two experienced radiology residents, two inexperienced radiology residents, and four novices. The task was to segment the whole prostate gland. The expert's segmentations were used as reference. For all other readers except three novices, the 100 MRI scans were divided into five rounds (cases 1-10, 11-25, 26-50, 51-76, 76-100). Three novices segmented only 50 cases (three rounds). After each round, a one-on-one feedback session between the expert and the reader was held, with feedback on systematic errors and potential improvements for the next round. Dice similarity coefficient (DSC) > 0.8 was considered accurate.

RESULTS

Using DSC > 0.8 as the threshold, the novices had a total of 194 accurate segmentations out of 250 (77.6%). The residents had a total of 397/400 (99.2%) accurate segmentations. In round 1, the novices had 19/40 (47.5%) accurate segmentations, in round 2 41/60 (68.3%), and in round 3 84/100 (84.0%) indicating learning progress.

CONCLUSIONS

Radiology residents, regardless of prior experience, showed high segmentation accuracy. Novices showed larger interindividual variation and lower segmentation accuracy than radiology residents. To prepare datasets for artificial intelligence (AI) development, employing radiology residents seems safe and provides a good balance between cost-effectiveness and segmentation accuracy. Employing novices should only be considered on an individual basis.

CLINICAL RELEVANCE STATEMENT

Employing radiology residents for prostate MRI segmentation seems safe and can potentially reduce the workload of expert radiologists. Employing novices should only be considered on an individual basis.

KEY POINTS

• Using less experienced readers for prostate MRI segmentation is cost-effective but may reduce quality. • Radiology residents provided high accuracy segmentations while novices showed large inter-reader variability. • To prepare datasets for AI development, employing radiology residents seems safe and might provide a good balance between cost-effectiveness and segmentation accuracy while novices should only be employed on an individual basis.

Martin B, Jacobsen NE, Evans H, Gao Y, Hung R, Abele J, Dromparis P, Lima JF, Bismar T, Michelakis E, Sutendra G, Wuest F, Tu W, Adam BA, Fung C, Tamm A, Kinnaird A. Fluorine-18 Prostate-Specific Membrane Antigen-1007 PET/CT vs Multiparametric MRI for Locoregional Staging of Prostate Cancer

Importance

Prostate-specific membrane antigen (PSMA) demonstrates overexpression in prostate cancer and correlates with tumor aggressiveness. PSMA positron emission tomography (PET) is superior to conventional imaging for the metastatic staging of prostate cancer per current research but studies of second-generation PSMA PET radioligands for locoregional staging are limited.

Objective

To determine the accuracy of fluorine-18 PSMA-1007 PET/computed tomography (18F-PSMA-1007 PET/CT) compared to multiparametric magnetic resonance imaging (MRI) in the primary locoregional staging of intermediate-risk and high-risk prostate cancers.

Design, Setting, and Participants

The Next Generation Trial was a phase 2 prospective validating paired cohort study assessing the accuracy of 18F-PSMA-1007 PET/CT and MRI for locoregional staging of prostate cancer, with results of histopathologic examination as the reference standard comparator. Radiologists, nuclear medicine physicians, and pathologists were blinded to preoperative clinical, pathology, and imaging data. Patients underwent all imaging studies and radical prostatectomies at 2 tertiary care hospitals in Alberta, Canada. Eligible participants included men with intermediate-risk or high-risk prostate cancer who consented to radical prostatectomy. Participants who underwent radical prostatectomy were included in the final analysis. Patients were recruited between March 2022 and June 2023, and data analysis occurred between July 2023 and December 2023.

Exposures

All participants underwent both 18F-PSMA-1007 PET/CT and MRI within 2 weeks of one another and before radical prostatectomy.

Main Outcomes and Measures

The primary outcome was the correct identification of the prostate cancer tumor stage by each imaging test. The secondary outcomes were correct identification of the dominant nodule, laterality, extracapsular extension, and seminal vesical invasion.

Results

Of 150 eligible men with prostate cancer, 134 patients ultimately underwent radical prostatectomy (mean [SD] age at prostatectomy, 62.0 [5.7] years). PSMA PET was superior to MRI for the accurate identification of the final pathological tumor stage (61 [45%] vs 38 [28%]; P = .003). PSMA PET was also superior to MRI for the correct identification of the dominant nodule (126 [94%] vs 112 [83%]; P = .01), laterality (86 [64%] vs 60 [44%]; P = .001), and extracapsular extension (100 [75%] vs 84 [63%]; P = .01), but not for seminal vesicle invasion (122 [91%] vs 115 [85%]; P = .07).

Conclusions and Relevance

In this phase 2 prospective validating paired cohort study, 18F-PSMA-1007 PET/CT was superior to MRI for the locoregional staging of prostate cancer. These findings support PSMA PET in the preoperative workflow of intermediate-risk and high-risk tumors.

Is There an Added Value of Quantitative DCE-MRI by Magnetic Resonance Dispersion Imaging for Prostate Cancer Diagnosis?

In this multicenter, retrospective study, we evaluated the added value of magnetic resonance dispersion imaging (MRDI) to standard multiparametric MRI (mpMRI) for PCa detection. The study included 76 patients, including 51 with clinically significant prostate cancer (csPCa), who underwent radical prostatectomy and had an mpMRI including dynamic contrast-enhanced MRI. Two radiologists performed three separate randomized scorings based on mpMRI, MRDI and mpMRI+MRDI. Radical prostatectomy histopathology was used as the reference standard. Imaging and histopathology were both scored according to the Prostate Imaging-Reporting and Data System V2.0 sector map. Sensitivity and specificity for PCa detection were evaluated for mpMRI, MRDI and mpMRI+MRDI. Inter- and intra-observer variability for both radiologists was evaluated using Cohen's Kappa. On a per-patient level, sensitivity for csPCa for radiologist 1 (R1) for mpMRI, MRDI and mpMRI+MRDI was 0.94, 0.82 and 0.94, respectively. For the second radiologist (R2), these were 0.78, 0.94 and 0.96. R1 detected 4% additional csPCa cases using MRDI compared to mpMRI, and R2 detected 20% extra csPCa cases using MRDI. Inter-observer agreement was significant only for MRDI (Cohen's Kappa = 0.4250, p = 0.004). The results of this study show the potential of MRDI to improve inter-observer variability and the detection of csPCa.

What the urologist needs to know before radical prostatectomy: MRI effective support to pre-surgery planning

BACKGROUND

Radical prostatectomy (RP) is recommended in case of localized or locally advanced prostate cancer (PCa), but it can lead to side effects, including urinary incontinence (UI) and erectile dysfunction (ED). Magnetic resonance imaging (MRI) is recommended for PCa diagnosis and staging, but it can also improve preoperative risk-stratification.

PURPOSE

This nonsystematic review aims to provide an overview on factors involved in RP side effects, highlighting anatomical and pathological aspects that could be included in a structured report.

EVIDENCE SYNTHESIS

Considering UI evaluation, MR can investigate membranous urethra length (MUL), prostate volume, the urethral sphincter complex, and the presence of prostate median lobe. Longer MUL measurement based on MRI is linked to a higher likelihood of achieving continence restoration. For ED assessment, MRI and diffusion tensor imaging identify the neurovascular bundle and they can aid in surgery planning. Finally, MRI can precisely describe extra-prostatic extension, prostate apex characteristics and lymph-node involvement, providing valuable preoperative information for PCa treatment.

CONCLUSIONS

Anatomical principals structures involved in RP side effects can be assessed with MR. A standardized MR report detailing these structures could assist urologists in planning optimal and tailored surgical techniques, reducing complications, and improving patients' care.

Repeat Prostate-specific Antigen Testing Improves Risk-based Selection of Men for Prostate Biopsy After Magnetic Resonance Imaging

Background and objective

The aim of our study was to investigate whether repeat prostate-specific antigen (PSA) testing as currently recommended improves risk stratification for men undergoing magnetic resonance imaging (MRI) and targeted biopsy for suspected prostate cancer (PCa).

Methods

Consecutive men undergoing MRI and prostate biopsy who had at least two PSA tests before prostate biopsy were retrospectively registered and assigned to a development cohort (n = 427) or a validation (n = 174) cohort. Change in PSA level was assessed as a predictor of clinically significant PCa (csPCa; Gleason score ≥3 + 4, grade group ≥2) by multivariable logistic regression analysis. We developed a multivariable prediction model (MRI-RC) and a dichotomous biopsy decision strategy incorporating the PSA change. The performance of the MRI-RC model and dichotomous decision strategy was assessed in the validation cohort and compared to prediction models and decision strategies not including PSA change in terms of discriminative ability and decision curve analysis.

Results

Men who had a decrease on repeat PSA testing had significantly lower risk of csPCa than men without a decrease (odds ratio [OR] 0.3, 95% confidence interval [CI] 0.16-0.54; p < 0.001). Men with an increased repeat PSA had a significantly higher risk of csPCa than men without an increase (OR 2.97, 95% CI 1.62-5.45; p < 0.001). Risk stratification using both the MRI-RC model and the dichotomous decision strategy was improved by incorporating change in PSA as a parameter.

Conclusions and clinical implications

Repeat PSA testing gives predictive information regarding men undergoing MRI and targeted prostate biopsy. Inclusion of PSA change as a parameter in an MRI-RC model and a dichotomous biopsy decision strategy improves their predictive performance and clinical utility without requiring additional investigations.

Patient summary

For men with a suspicion of prostate cancer, repeat PSA (prostate-specific antigen) testing after an MRI (magnetic resonance imaging) scan can help in identifying patients who can safely avoid prostate biopsy.

Predictors of Gleason Grading Group Upgrading in Low-Risk Prostate Cancer Patients From Transperineal Biopsy After Radical Prostatectomy

RATIONALE AND OBJECTIVES

To investigate the predictors of Gleason Grading Group (GGG) upgrading in low-risk prostate cancer (Gleason score=3 + 3) from transperineal biopsy after radical prostatectomy (RP).

MATERIALS AND METHODS

The clinical data of 160 patients who underwent transperineal biopsy and RP from January 2017 to December 2022 were retrospectively analyzed. First, univariate and multivariate logistic regression analysis were used to obtain independent predictors of postoperative GGG upgrading. Then receiver operating characteristic curve was used to evaluate the diagnostic efficacy of predictors. Finally, Linear-by-Linear Association test was used to analyze the risk trends of patients in different predictor groups in the postoperative GGG.

RESULTS

In this study, there were 81 cases (50.6%) in the GGG concordance group and 79 cases (49.4%) in the GGG upgrading group. Univariate analysis showed age, free/total prostate-specific antigen (f/tPSA), proportion of positive biopsies, positive target of magnetic-resonance imaging (MRI) and positive target of contrast-enhanced ultrasound had significant effects on GGG upgrading (all P < .05). In multivariate logistic regression analysis, age (odds ratio [OR]=1.066, 95%CI=1.007-1.127, P = .027), f/tPSA (OR=0.001, 95%CI=0-0.146, P = .001) and positive target of MRI (OR=3.005, 95%CI=1.353-76.674, P = .007) were independent predictors. The prediction model (area under curve=0.751 P < .001) had higher predictive efficacy than all independent predictors. The proportion of patients in exposed group of different GGG increased with the level of GGG, but decreased in nonexposed group, and the linear trend was significantly different (all P < .001).

CONCLUSION

Age, f/tPSA, and positive target of MRI were independent predictors of postoperative GGG upgrading. The predictive model constructed had the best diagnostic efficacy.

Strategies for improving image quality in prostate MRI

Prostate magnetic resonance imaging (MRI) stands as the cornerstone in diagnosing prostate cancer (PCa), offering superior detection capabilities while minimizing unnecessary biopsies. Despite its critical role, global disparities in MRI diagnostic performance persist, stemming from variations in image quality and radiologist expertise. This manuscript reviews the challenges and strategies for enhancing image quality in prostate MRI, spanning patient preparation, MRI unit optimization, and radiology team engagement. Quality assurance (QA) and quality control (QC) processes are pivotal, emphasizing standardized protocols, meticulous patient evaluation, MRI unit workflow, and radiology team performance. Additionally, artificial intelligence (AI) advancements offer promising avenues for improving image quality and reducing acquisition times. The Prostate-Imaging Quality (PI-QUAL) scoring system emerges as a valuable tool for assessing MRI image quality. A comprehensive approach addressing technical, procedural, and interpretative aspects is essential to ensure consistent and reliable prostate MRI outcomes.

Impact of prostate MRI image quality on diagnostic performance for clinically significant prostate cancer (csPCa)

OBJECTIVES

With the widespread clinical application of prostate magnetic resonance imaging (MRI), there has been an increasing demand for lesion detection and accurate diagnosis in prostate MR, which relies heavily on satisfactory image quality. Focusing on the primary sequences involved in Prostate Imaging Reporting and Data System (PI-RADS), this study have evaluated common quality issues in clinical practice (such as signal-to-noise ratio (SNR), artifacts, boundaries, and enhancement). The aim of the study was to determine the impact of image quality on clinically significant prostate cancer (csPCa) detection, positive predictive value (PPV) and radiologist's diagnosis in different sequences and prostate zones.

METHODS

This retrospective study included 306 patients who underwent prostate MRI with definitive pathological reports from February 2021 to December 2022. All histopathological specimens were evaluated according to the recommendations of the International Society of Urological Pathology (ISUP). An ISUP Grade Group ≥ 2 was considered as csPCa. Three radiologists from different centers respectively performed a binary classification assessment of image quality in the following ten aspects: (1) T2WI in the axial plane: SNR, prostate boundary conditions, the presence of artifacts; (2) T2WI in the sagittal or coronal plane: prostate boundary conditions; (3) DWI: SNR, delineation between the peripheral and transition zone, the presence of artifacts, the matching of DWI and T2WI images; (4) DCE: the evaluation of obturator artery enhancement, the evaluation of dynamic contrast enhancement. Fleiss' Kappa was used to determine the inter-reader agreement. Wilson's 95% confidence interval (95% CI) was used to calculate PPV. Chi-square test was used to calculate statistical significance. A p-value < 0.05 was considered statistically significant.

RESULTS

High-quality images had a higher csPCa detection rate (56.5% to 64.3%) in axial T2WI, DWI, and DCE, with significant statistical differences in SNR in axial T2WI (p 0.002), the presence of artifacts in axial T2WI (p 0.044), the presence of artifacts in DWI (p < 0.001), and the matching of DWI and T2WI images (p < 0.001). High-quality images had a higher PPV (72.5% to 78.8%) and showed significant statistical significance in axial T2WI, DWI, and DCE. Additionally, we found that PI-RADS 3 (24.0% to 52.9%) contained more low-quality images compared to PI-RADS 4-5 (20.6% to 39.3%), with significant statistical differences in the prostate boundary conditions in axial T2WI (p 0.048) and the presence of artifacts in DWI (p 0.001). Regarding the relationship between csPCa detection and image quality in different prostate zones, this study found that significant statistical differences were only observed between high- (63.5% to 75.7%) and low-quality (30.0% to 50.0%) images in the peripheral zone (PZ).

CONCLUSION

Prostate MRI quality may have an impact on the diagnostic performance. The poorer image quality is associated with lower csPCa detection rates and PPV, which can lead to an increase in radiologist's ambiguous diagnosis (PI-RADS 3), especially for the lesions located at PZ.

Multiparametric Prostate MRI Accuracy of Prostate Imaging Reporting and Data System (v2.1) Scores 4 and 5: The Influence of Image Quality According to the Prostate Imaging Quality Score

Purpose: The accuracy of multiparametric magnetic resonance imaging (mpMRI) heavily relies on image quality, as evidenced by the evolution of the prostate imaging quality (PI-QUAL) scoring system for the evaluation of clinically significant prostate cancer (csPC). This study aims to evaluate the impact of PI-QUAL scores in detecting csPC within PI-RADS 4 and 5 lesions. Methods: We retrospectively selected from our database all mpMRI performed from January 2019 to March 2022. Inclusion criteria were as follows: (1) mpMRI acquired in our institution according to the technical requirements from the PI-RADS (v2.1) guidelines; (2) single lesion scored as PI-RADS (v2.1) 4 or 5; (3) MRI-TBx performed in our institution; (4) complete histology report; and (5) complete clinical record. Results: A total of 257 male patients, mean age 70.42 ± 7.6 years, with a single PI-RADS 4 or 5 lesion undergoing MRI-targeted biopsy, were retrospectively studied. Of these, 61.5% were PI-RADS 4, and 38.5% were PI-RADS 5, with 84% confirming neoplastic cells. In high-quality image lesions (PI-QUAL ≥ 4), all PI-RADS 5 lesions were accurately identified as positive at the final histological examination (100% of CDR). For PI-RADS 4 lesions, 37 (23%) were negative, resulting in a cancer detection rate of 77% (95% CI: 67.51-84.83). Conclusions: The accuracy of mpMRI, independently of the PI-RADS score, progressively decreased according to the decreasing PI-QUAL score. These findings emphasize the crucial role of the PI-QUAL scoring system in evaluating PI-RADS 4 and 5 lesions, influencing mpMRI accuracy.

Image-guided multiparametric magnetic resonance imaging-transrectal ultrasound fusion biopsy augmented with a sextant versus an extended template random biopsy: Comparison of cancer detection rates, complication and functional outcomes

PURPOSE

To compare the efficacy of a novel fusion template "reduced six-core systemic template and multiparametric magnetic resonance imaging/transrectal ultrasound (mpMRI/TRUS) fusion targeted biopsy" (TBx+6c), with mpMRI/TRUS fusion-targeted biopsy and 12-core systematic biopsy template (TBx+12c) in the diagnosis of prostate cancer (PCa).

MATERIALS AND METHODS

This is an institutional review board approved single-center observational study involving adult men undergoing fusion-targeted biopsies for the diagnosis of PCa. Patients were sorted into cohorts of TBx+6c or TBx+12c based on the systematic biopsy template used. The study's main objective was to determine the cancer detection rate (CDR) for overall PCa and clinically significant PCa (csPCa) and the secondary objectives were to compare complication rates and functional outcome differences between the cohort.

RESULTS

A total of 204 patients met study's inclusion criteria. TBx+6c group had 120 patients, while TBx+12c cohort had 84 patients. The groups had similar baseline characteristics and overall CDR in the TBx+6c cohort was 71.7% versus 79.8%, compared to the TBx+12c (p = 0.18) whereas, the csPCa detection rate in the TBx+6c group was 50.8% versus 54.8% in the TBx+12c group (p = 0.5). TBx+6c cohort had lower overall complication rate of 3% versus 13%, (p = 0.01) and ≥ grade 2 complication rates (1 (1%) vs. 3(4%), p = 0.03) compared to the TBx+12c cohort. There were no differences in IIEF-5 (p = 0.5) or IPSS (p = 0.1) scores at baseline and 2-weeks and 6-weeks post-biopsy.

CONCLUSION

TBx+6c cohort, when compared to the TBx+12c cohort, demonstrated comparable diagnostic performance along with similar functional outcomes and lower complication rates. These results suggest the importance of further exploring the clinical implications of adopting a TBx+6c schema for PCa diagnosis in comparison to the widely used TBx+12c schema through a multicenter randomized controlled trial.

Value of MRI - T2 Mapping to Differentiate Clinically Significant Prostate Cancer

Standardized reporting of multiparametric prostate MRI (mpMRI) is widespread and follows international standards (Pi-RADS). However, quantitative measurements from mpMRI are not widely comparable. Although T2 mapping sequences can provide repeatable quantitative image measurements and extract reliable imaging biomarkers from mpMRI, they are often time-consuming. We therefore investigated the value of quantitative measurements on a highly accelerated T2 mapping sequence, in order to establish a threshold to differentiate benign from malignant lesions. For this purpose, we evaluated a novel, highly accelerated T2 mapping research sequence that enables high-resolution image acquisition with short acquisition times in everyday clinical practice. In this retrospective single-center study, we included 54 patients with clinically indicated MRI of the prostate and biopsy-confirmed carcinoma (n = 37) or exclusion of carcinoma (n = 17). All patients had received a standard of care biopsy of the prostate, results of which were used to confirm or exclude presence of malignant lesions. We used the linear mixed-effects model-fit by REML to determine the difference between mean values of cancerous tissue and healthy tissue. We found good differentiation between malignant lesions and normal appearing tissue in the peripheral zone based on the mean T2 value. Specifically, the mean T2 value for tissue without malignant lesions was (151.7 ms [95% CI: 146.9-156.5 ms] compared to 80.9 ms for malignant lesions [95% CI: 67.9-79.1 ms]; p < 0.001). Based on this assessment, a limit of 109.2 ms is suggested. Aditionally, a significant correlation was observed between T2 values of the peripheral zone and PI-RADS scores (p = 0.0194). However, no correlation was found between the Gleason Score and the T2 relaxation time. Using REML, we found a difference of -82.7 ms in mean values between cancerous tissue and healthy tissue. We established a cut-off-value of 109.2 ms to accurately differentiate between malignant and non-malignant prostate regions. The addition of T2 mapping sequences to routine imaging could benefit automated lesion detection and facilitate contrast-free multiparametric MRI of the prostate.

Perspectives on technology: Prostate Imaging-Reporting and Data System (PI-RADS) interobserver variability

OBJECTIVES

To explore the topic of Prostate Imaging-Reporting and Data System (PI-RADS) interobserver variability, including a discussion of major sources, mitigation approaches, and future directions.

METHODS

A narrative review of PI-RADS interobserver variability.

RESULTS

PI-RADS was developed in 2012 to set technical standards for prostate magnetic resonance imaging (MRI), reduce interobserver variability at interpretation, and improve diagnostic accuracy in the MRI-directed diagnostic pathway for detection of clinically significant prostate cancer. While PI-RADS has been validated in selected research cohorts with prostate cancer imaging experts, subsequent prospective studies in routine clinical practice demonstrate wide variability in diagnostic performance. Radiologist and biopsy operator experience are the most important contributing drivers of high-quality care among multiple interrelated factors including variability in MRI hardware and technique, image quality, and population and patient-specific factors such as prostate cancer disease prevalence. Iterative improvements in PI-RADS have helped flatten the curve for novice readers and reduce variability. Innovations in image quality reporting, administrative and organisational workflows, and artificial intelligence hold promise in improving variability even further.

CONCLUSION

Continued research into PI-RADS is needed to facilitate benchmark creation, reader certification, and independent accreditation, which are systems-level interventions needed to uphold and maintain high-quality prostate MRI across entire populations.

Comparing Two Targeted Biopsy Schemes for Detecting Clinically Significant Prostate Cancer in Magnetic Resonance Index Lesions: Two- to Four-Core versus Saturated Transperineal Targeted Biopsy

Since the optimal scheme for targeted biopsies of magnetic resonance imaging (MRI) suspicious lesions remains unclear, we compare the efficacy of two schemes for these index lesions. A prospective trial was conducted in 1161 men with Prostate Imaging Reporting and Data System v 2.1 3-5 undergoing targeted and 12-core systematic biopsy in four centers between 2021 and 2023. Two- to four-core MRI-transrectal ultrasound fusion-targeted biopsies via the transperineal route were conducted in 900 men in three centers, while a mapping per 0.5 mm core method (saturated scheme) was employed in 261 men biopsied in another center. A propensity-matched 261 paired cases were selected for avoiding confounders other than the targeted biopsy scheme. CsPCa (grade group ≥ 2) was identified in 125 index lesions (41.1%) when the two- to four-core scheme was employed, while in 187 (71.9%) when the saturated biopsy (p < 0.001) was used. Insignificant PCa (iPCa) was detected in 18 and 11.1%, respectively (p = 0.019). Rates of csPCa and iPCa remained similar in systematic biopsies. CsPCa detected only in systematic biopsies were 5 and 1.5%, respectively (p = 0.035) in each group. The saturated scheme for targeted biopsies detected more csPCa and less iPCa than did the two- to four-core scheme in the index lesions. The rate of csPCa detected only in the systematic biopsies decreased when the saturated scheme was employed.

The importance and future of prostate MRI report templates: improving oncological care

The radiologist's report is crucial for guiding care post-imaging, with ongoing advancements in report construction. Recent studies across various modalities and organ systems demonstrate enhanced clarity and communication through structured reports. This article will explain the benefits of disease-state specific reporting templates using prostate MRI as the model system. We identify key reporting components for prostate cancer detection and staging as well as imaging in active surveillance and following therapy. We discuss relevant reporting systems including PI-QUAL, PI-RADS, PRECISE, PI-RR and PI-FAB systems. Additionally, we examine optimal reporting structure including disruptive technologies such as graphical reporting and using artificial intelligence to improve report clarity and applicability.

Phantoms for Quantitative Body MRI: a review and discussion of the phantom value

In this paper, we review the value of phantoms for body MRI in the context of their uses for quantitative MRI methods research, clinical trials, and clinical imaging. Certain uses of phantoms are common throughout the body MRI community, including measuring bias, assessing reproducibility, and training. In addition to these uses, phantoms in body MRI methods research are used for novel methods development and the design of motion compensation and mitigation techniques. For clinical trials, phantoms are an essential part of quality management strategies, facilitating the conduct of ethically sound, reliable, and regulatorily compliant clinical research of both novel MRI methods and therapeutic agents. In the clinic, phantoms are used for development of protocols, mitigation of cost, quality control, and radiotherapy. We briefly review phantoms developed for quantitative body MRI, and finally, we review open questions regarding the most effective use of a phantom for body MRI.

Clinical characteristics and pathological features of undetectable clinically significant prostate cancer on multiparametric magnetic resonance imaging: A single-center and retrospective study

Objectives

The objectives of this study were to clarify the pathological features of clinically significant prostate cancer (csPC) that is undetectable on multiparametric magnetic resonance imaging (mpMRI).

Material and Methods

This single-center and retrospective study enrolled 33 men with prostate cancer (PC), encompassing 109 PC lesions, who underwent mpMRI before radical prostatectomy. Two radiologists independently assessed the mpMR images of all lesions and compared them with the pathological findings of PC. All PC lesions were marked on resected specimens using prostate imaging reporting and data system version 2.1 and classified into magnetic resonance imaging (MRI)-detectable and MRI-undetectable PC lesions. Each lesion was classified into csPC and clinically insignificant PC. Pathological characteristics were compared between MRI-detectable and MRI-undetectable csPC. Statistical analysis was performed to identify factors associated with MRI detectability. A logistic regression model was used to determine the factors associated with MRI-detectable and MRI-undetectable csPC.

Results

Among 109 PC lesions, MRI-detectable and MRI-undetectable PCs accounted for 31% (34/109) and 69% (75/109) of lesions, respectively. All MRI-detectable PCs were csPC. MRI-undetectable PCs included 30 cases of csPC (40%). The detectability of csPC on mpMRI was 53% (34/64). The MRI-undetectable csPC group had a shorter major diameter (10.6 ± 6.6 mm vs. 19.0 ± 6.9 mm, P < 0.001), shorter minor diameter (5.7 ± 2.9 mm vs. 10.7 ± 3.4 mm, P < 0.001), and lower percentage of lesions with Gleason pattern 5 (17% vs. 71%, P < 0.001). Shorter minor diameter (odds ratio [OR], 2.62; P = 0.04) and lower percentage of Gleason pattern 5 (OR, 24; P = 0.01) were independent predictors of MRI-undetectable csPC.

Conclusion

The pathological features of MRI-undetectable csPC included shorter minor diameter and lower percentage of Gleason pattern 5. csPC with shorter minor diameter may not be detected on mpMRI. Some MRI-undetectable csPC lesions exhibited sufficient size and Gleason pattern 5, emphasizing the need for further understanding of pathological factors contributing to MRI detectability.