Recent advances in image-guided targeted prostate biopsy

MRI in-bore biopsy following MRI/US fusion-guided biopsy in patients with persistent suspicion of clinically significant prostate cancer

PURPOSE

Patients with suspicion of clinically significant prostate cancer (csPC) on multiparametric prostate MRI (mpMRI) but negative or inconclusive MRI/US fusion-guided biopsy (FB) can be challenging in clinical practice. To assess the utility of MRI in-bore biopsy (IB) in patients with discordant imaging and histopathological findings after FB.

METHODS

Consecutive patients with Prostate Imaging Reporting and Data System (PI-RADS) category 4 or 5 on mpMRI at 3T after FB without histologically confirmed csPC who underwent IB between 01/2014 and 05/2022, were retrospectively included. The primary objective was to assess the detection rate of csPC. Secondary objectives were to analyze clinical parameters, MRI parameters, and lesion localization.

RESULTS

In the final cohort of 51 patients, the IB resulted in an overall detection rate of 71% for PC and 47% for csPC. Furthermore, in 55% of cases with initial low-grade PC, the Gleason score was upgraded after IB. CsPC was often detected apical and/or anterior. The detection rate for PC was 58% in PI-RADS category 4 and 94% in PI-RADS category 5 (csPC 39% and 61%, respectively). Patients with csPC had statistically significant smaller prostate volumes, a higher PI-RADS category, a higher prostate-specific antigen density (PSAD), and were older.

CONCLUSIONS

For a relevant proportion of patients with PI-RADS category 4 or 5 and negative or inconclusive findings on previous FB, but with persistent suspicion of csPC, a subsequent IB verified the presence of csPC. Therefore, IB can be a backup in cases of uncertainty.

Image quality assessment for machine learning tasks using meta-reinforcement learning

In this paper, we consider image quality assessment (IQA) as a measure of how images are amenable with respect to a given downstream task, or task amenability. When the task is performed using machine learning algorithms, such as a neural-network-based task predictor for image classification or segmentation, the performance of the task predictor provides an objective estimate of task amenability. In this work, we use an IQA controller to predict the task amenability which, itself being parameterised by neural networks, can be trained simultaneously with the task predictor. We further develop a meta-reinforcement learning framework to improve the adaptability for both IQA controllers and task predictors, such that they can be fine-tuned efficiently on new datasets or meta-tasks. We demonstrate the efficacy of the proposed task-specific, adaptable IQA approach, using two clinical applications for ultrasound-guided prostate intervention and pneumonia detection on X-ray images.

Deep learning-based artificial intelligence for prostate cancer detection at biparametric MRI

PURPOSE

To present fully automated DL-based prostate cancer detection system for prostate MRI.

METHODS

MRI scans from two institutions, were used for algorithm training, validation, testing. MRI-visible lesions were contoured by an experienced radiologist. All lesions were biopsied using MRI-TRUS-guidance. Lesions masks, histopathological results were used as ground truth labels to train UNet, AH-Net architectures for prostate cancer lesion detection, segmentation. Algorithm was trained to detect any prostate cancer ≥ ISUP1. Detection sensitivity, positive predictive values, mean number of false positive lesions per patient were used as performance metrics.

RESULTS

525 patients were included for training, validation, testing of the algorithm. Dataset was split into training (n = 368, 70%), validation (n = 79, 15%), test (n = 78, 15%) cohorts. Dice coefficients in training, validation sets were 0.403, 0.307, respectively, for AHNet model compared to 0.372, 0.287, respectively, for UNet model. In validation set, detection sensitivity was 70.9%, PPV was 35.5%, mean number of false positive lesions/patient was 1.41 (range 0-6) for UNet model compared to 74.4% detection sensitivity, 47.8% PPV, mean number of false positive lesions/patient was 0.87 (range 0-5) for AHNet model. In test set, detection sensitivity for UNet was 72.8% compared to 63.0% for AHNet, mean number of false positive lesions/patient was 1.90 (range 0-7), 1.40 (range 0-6) in UNet, AHNet models, respectively.

CONCLUSION

We developed a DL-based AI approach which predicts prostate cancer lesions at biparametric MRI with reasonable performance metrics. While false positive lesion calls remain as a challenge of AI-assisted detection algorithms, this system can be utilized as an adjunct tool by radiologists.

Deep learning-based artificial intelligence applications in prostate MRI: brief summary

Prostate cancer (PCa) is the most common cancer type in males in the Western World. MRI has an established role in diagnosis of PCa through guiding biopsies. Due to multistep complex nature of the MRI-guided PCa diagnosis pathway, diagnostic performance has a big variation. Developing artificial intelligence (AI) models using machine learning, particularly deep learning, has an expanding role in radiology. Specifically, for prostate MRI, several AI approaches have been defined in the literature for prostate segmentation, lesion detection and classification with the aim of improving diagnostic performance and interobserver agreement. In this review article, we summarize the use of radiology applications of AI in prostate MRI.

Safety and feasibility of freehand transperineal prostate biopsy under local anesthesia: Our initial experience

INTRODUCTION

With the emergence of multidrug-resistant organisms causing urosepsis after transrectal biopsy of prostate, the need for an alternative approach has increased. We assessed the safety and feasibility of transrectal ultrasound (TRUS) guided free-hand transperineal prostate biopsy under local anesthesia (LA) for suspected prostate cancer.

MATERIALS AND METHODS

This prospective study was conducted from July 2019 to December 2020 in which patients with elevated prostate-specific antigen (PSA) and/or abnormal digital rectal examination underwent magnetic resonance imaging-TRUS cognitive fusion transperineal prostate biopsy (target and systematic) using coaxial needle. Demographic, perioperative, and outcome data of 50 consecutive patients were analyzed.

RESULTS

The mean age of the patients was 69.6 ± 7.61 years, median PSA 13.55 ng/mL (4.17-672) and prostate size 45cc (16-520). Prostate Imaging-Reporting and Data System (PIRADS) 2, 3, 4, and 5 lesions were found in 2, 12, 12, and 24 patients, respectively. Average procedure duration was 20 min (15-40 min) and number of cores ranged from 12 to 38 (median 20). Forty out of fifty (40/50) patients experienced only mild pain with visual analog scale ≤2. Histopathological examination showed adenocarcinoma, benign prostatic hyperplasia, and chronic prostatitis in 41, 5, and 4 patients respectively with 82% cancer detection rate (CDR). Over 95% of cases showed clinically significant cancer (International Society of Urological Pathology class ≥ 2) and 91.7% of patients with PIRADS score 4/5 and 66.7% with PIRADS score 3 had malignancy. Three patients developed complications (two hematuria, one urinary retention), both were managed conservatively and none had urosepsis.

CONCLUSIONS

Free-hand transperineal prostate biopsy by coaxial needle technique under LA is safe and feasible with good tolerability, high CDR, and minimal complications particularly reduced urosepsis.

Recent Advancements in CT and MR Imaging of Prostate Cancer

CT and MRI are both commonly used in prostate cancer (PCa) management, which includes a large spectrum from screening positive pre-diagnosis phase to metastatic disease. CT and MRI have continually evolved to meet the changing demands for PCa management. For CT, novel techniques such as dual energy CT and photon counting CT show promising results for tissue characterization and quantification. For MRI, the detection, staging, and management of prostate cancer has been significantly improved by the development of multiparametric, biparametric, and whole-body MRI techniques. Additionally, research on ultrasmall superparamagnetic particles of iron oxide contrast-enhanced MRI has revealed promising results for nodal staging of PCa. In this manuscript we aim to outline the current status and recent advancements of CT and MRI in PCa imaging.

Comparison of Accuracies between Real-Time Nonrigid and Rigid Registration in the MRI-US Fusion Biopsy of the Prostate

Magnetic resonance imaging (MRI) is increasingly important in the detection and localization of prostate cancer. Regarding suspicious lesions on MRI, a targeted biopsy using MRI fused with ultrasound (US) is widely used. To achieve a successful targeted biopsy, a precise registration between MRI and US is essential. The purpose of our study was to show any decrease in errors using a real-time nonrigid registration technique for prostate biopsy. Nineteen patients with suspected prostate cancer were prospectively enrolled in this study. Registration accuracy was calculated by the measuring distance of corresponding points by rigid and nonrigid registration between MRI and US, and compared for rigid and nonrigid registration methods. Overall cancer detection rates were also evaluated by patient and by core. Prostate volume was measured automatically from MRI and manually from US, and compared to each other. Mean distances between the corresponding points in MRI and US were 5.32 ± 2.61 mm for rigid registration and 2.11 ± 1.37 mm for nonrigid registration (p < 0.05). Cancer was diagnosed in 11 of 19 patients (57.9%), and in 67 of 266 biopsy cores (25.2%). There was no significant difference in prostate-volume measurement between the automatic and manual methods (p = 0.89). In conclusion, nonrigid registration reduces targeting errors.

Alterations in protein expression and site-specific N-glycosylation of prostate cancer tissues

Identifying molecular alterations occurring during cancer progression is essential for a deeper understanding of the underlying biological processes. Here we have analyzed cancerous and healthy prostate biopsies using nanoLC-MS(MS) to detect proteins with altered expression and N-glycosylation. We have identified 75 proteins with significantly changing expression during disease progression. The biological processes involved were assigned based on protein-protein interaction networks. These include cellular component organization, metabolic and localization processes. Multiple glycoproteins were identified with aberrant glycosylation in prostate cancer, where differences in glycosite-specific sialylation, fucosylation, and galactosylation were the most substantial. Many of the glycoproteins with altered N-glycosylation were extracellular matrix constituents, and are heavily involved in the establishment of the tumor microenvironment.

Precise Identification of Prostate Cancer from DWI Using Transfer Learning

Background and Objective: The use of computer-aided detection (CAD) systems can help radiologists make objective decisions and reduce the dependence on invasive techniques. In this study, a CAD system that detects and identifies prostate cancer from diffusion-weighted imaging (DWI) is developed. Methods: The proposed system first uses non-negative matrix factorization (NMF) to integrate three different types of features for the accurate segmentation of prostate regions. Then, discriminatory features in the form of apparent diffusion coefficient (ADC) volumes are estimated from the segmented regions. The ADC maps that constitute these volumes are labeled by a radiologist to identify the ADC maps with malignant or benign tumors. Finally, transfer learning is used to fine-tune two different previously-trained convolutional neural network (CNN) models (AlexNet and VGGNet) for detecting and identifying prostate cancer. Results: Multiple experiments were conducted to evaluate the accuracy of different CNN models using DWI datasets acquired at nine distinct b-values that included both high and low b-values. The average accuracy of AlexNet at the nine b-values was 89.2±1.5% with average sensitivity and specificity of 87.5±2.3% and 90.9±1.9%. These results improved with the use of the deeper CNN model (VGGNet). The average accuracy of VGGNet was 91.2±1.3% with sensitivity and specificity of 91.7±1.7% and 90.1±2.8%. Conclusions: The results of the conducted experiments emphasize the feasibility and accuracy of the developed system and the improvement of this accuracy using the deeper CNN.

An external validation of the Candiolo nomogram in a cohort of prostate cancer patients treated by external-beam radiotherapy

Background

the aim of this study is to perform an external validation for the Candiolo nomogram, a predictive algorithm of biochemical and clinical recurrences in prostate cancer patients treated by radical Radiotherapy, published in 2016 on the journal “Radiation Oncology”.

Methods

561 patients, treated by Radiotherapy with curative intent between 2003 and 2012, were classified according to the five risk-classes of the Candiolo nomogram and the three risk-classes of the D’Amico classification for comparison. Patients were treated with a mean prostatic dose of 77.7 Gy and a combined treatment with Androgen-Deprivation-Therapy in 76% of cases. The end-points of the study were biochemical-progression-free-survival (bPFS) and clinical-Progression-Free-Survival (cPFS). With a median follow-up of 50 months, 56 patients (10%) had a biochemical relapse, and 30 patients (5.4%) a clinical progression. The cases were divided according to D’Amico in low-risk 21%, intermediate 40%, high-risk 39%; according to Candiolo very-low-risk 24%, low 37%, intermediate 24%, high 10%, very-high-risk 5%. Statistically, the Kaplan-Meier survival curves were processed and compared using Log-Rank tests and Harrell-C concordance index.

Results

The 5-year bPFS for the Candiolo risk-classes range between 98 and 38%, and the 5-year cPFS between 98 and 50% for very-low and very-high-risk, respectively. The Candiolo nomogram is highly significant for the stratification of both bPFS and cPFS (P < 0.0001), as well as the D’Amico classification (P = 0.004 and P = 0.001, respectively). For the Candiolo nomogram, the C indexes for bPFS and cPFS are 75 and 80%, respectively, while for D’Amico classification they are 64 and 69%, respectively. The Candiolo nomogram can identify a greater number of patients with low and very-low-risk prostate cancer (61% versus 21% according to D’Amico) and it better picks out patients with high and very-high-risk of recurrence, equal to only 15% of the total cases but subject to 48% (27/56) of biochemical relapses and 63% (19/30) of clinical progressions.

Conclusions

the external validation of the Candiolo nomogram was overall successful with C indexes approximately 10% higher than the D’Amico control classification for bPFS and cPFS. Therefore, its clinical use is justified in prostate cancer patients before radical Radiotherapy.

Trial registration Retrospectively registered.

Reasons for missing clinically significant prostate cancer by targeted magnetic resonance imaging/ultrasound fusion-guided biopsy

OBJECTIVES

This study evaluates cases with clinically significant prostate cancer (csPCa) missed by targeted biopsy (TB) and analyzes the diagnostic impact of an additional systematic biopsy (SB) in a large patient collective.

METHODS

Consecutive patients with a 3 T multiparametric prostate MRI (mpMRI) and a subsequent MRI/US fusion-guided TB plus 12-core US-guided SB from 01/2014 to 04/2019 were included in this study. Primary study endpoint was the analysis of cases with a csPCa missed by TB and detected by SB. Secondary study objectives were the PCa detection and the correlation with clinical and MRI parameters.

RESULTS

In total 785 patients met the inclusion criteria. 342 patients had a csPCa (median PSAD 0.29 ng/mL/cm³). In 42 patients (13 %), a csPCa was detected only by SB. In 36 of these cases, the localization of the positive SB cores matched with the cancer suspicious region described on mpMRI (mCSR). Cases with a csPCA missed by TB showed either an insufficient MRI segmentation (prostate boundary correlation) (31 %) and/or insufficient lesion registration (lesion transfer, tracking, and/or matching) (48 %), a missed small lesion (14 %), or a failed center of a large lesion (10 %). Median PSAD of patients with non-significant PCa detected by SB was 0.15 ng/mL/cm³.

CONCLUSIONS

Main reasons for missing a csPCa by TB were insufficient prostate segmentation or imprecise lesion registration within MRI/US fusion-guided biopsy. Consequently, verification of MRI quality, exact mCSR assessment, and advanced biopsy experience may improve accuracy. Altogether, an additional SB adds limited clinical benefit in men with PSAD ≤ 0.15 ng/mL/cm³.

Transperineal prostate biopsy: a review of technique

As the second most diagnosed cancer worldwide, prostate cancer is confirmed via tissue biopsy. Given the large number of prostate biopsies performed each year, the technique should be as accurate and safe as possible for the patient’s well-being. Transrectal ultrasound guided prostate biopsy (TRUS-biopsy) is most offered worldwide. Transperineal biopsy (TPP-biopsy), on the other hand, has been gaining popularity due to its superior sensitivity and lower rate of sepsis. This article offers a review of the brachytherapy grid technique used to perform a TPP-biopsy, as well as a discussion of possible variations in the procedure. TPP-biopsy is typically performed under general anaesthesia with patient in lithotomy. Through the perineum, cores of tissue are taken systematically, with or without targeting, under US guidance. Different fusion techniques (cognition, MRI-US fusion software, MRI in-bore) can be used to target pre-identified lesions on MRI. The sampling can be done either by free hand or using a brachytherapy grid. Robotic assisted prostate biopsy is also available on the market as an alternative. In recent years, there has been accumulating evidence showing that it is safe and feasible to perform TPPB under local anaesthesia. This may improve the uptake of TPPB as the preferred biopsy technique for prostate cancer.

Development of a Device-to-Image Registration Free Needle Guide for Magnetic Resonance Imaging-Guided Targeted Prostate Biopsy

Significant research has been done in the past decade for the development of magnetic resonance imaging (MRI) guided needle guide (NG) systems for prostate intervention. Most of these systems have been restricted to application in the lab environment with lack of progress toward clinical application. Bulky and complex designs can be attributed to this practice. These systems also demand complex technical setup and usage procedures, which require extra technical personnel during the intervention in addition to specialized training for physicians. Moreover, “device-to-image” registration, essential for accurate and precise targeting, further complicates the overall process while increasing total time for intervention. In order to address these limitations, a simplified, MRI-guided, transperineal prostate biopsy NG system was designed and developed for rapid adoption into the clinical environment. The system consists of a NG device and a software toolkit. It does not require any special intraprocedural technical expertise or dedicated training. Also, to simplify and shorten total procedure time, the device uses the unique concept of “fixed coordinate device” eliminating the need for any device-to-image registration making it clinically friendly. To verify the NG design along with the registration free feature, image quality tests and agar phantom-based targeting experiments were performed under the guidance of 3T MRI scanner. The imaging tests resulted in a distortion of less than 1% in presence of the device and an average change of 1.3% in signal-to-noise ratio. For targeting experiments, maximum in-plane error distance of 3.8 mm with a mean of 2.2 mm and standard deviation of 0.8 mm was observed. The results show that an MRI-compatible simplified intervention device without the need of device-to-image registration is technically feasible.

A Low-Cost Highly Configurable Phantom for Simulation of Imaging-Guided Endocavitary Procedures

We developed a method to create customizable phantoms suitable for endocavitary imaging and interventional research, based on the fabrication of an acrylic phantom mold, and development of a phantom matrix composed of gelatin, agar, graphite particles, and propanol. Our phantom was mechanically stable, easily fabricated, and highly adjustable, and its ultrasound (US) and magnetic resonance imaging (MRI) scans showed the qualification for the procedure guidance compared with the human prostate image using the same US system. To test the feasibility of the phantom for the research, the seeds placement guided by MRI/US fusion was performed, and the overall test error (distance from the seed center to the virtual lesion center in olives) was 2.59 ± 0.59 mm. We have created a simple, low-cost, configurable, gelatin-based phantom and tested its feasibility for simulating endorectal interventional US procedures. The design of the phantom mold and matrix is likely to be useful to the broader medical training community, and the preliminary data from the experiment of MRI/US-guided seeds placement showed its potential to test the clinical hypothesis in US research.

Prostate cancer detection from multi-institution multiparametric MRIs using deep convolutional neural networks

Multiparametric magnetic resonance imaging (mpMRI) of the prostate aids in early diagnosis of prostate cancer, but is difficult to interpret and subject to interreader variability. Our objective is to generate probability maps, overlaid on original mpMRI images to help radiologists identify where a cancer is suspected as a computer-aided diagnostic (CAD). We optimized the holistically nested edge detection (HED) deep convolutional neural network. Our dataset contains T2, apparent diffusion coefficient, and high b -value images from 186 patients across six institutions worldwide: 92 with an endorectal coil (ERC) and 94 without. Ground-truth was based on tumor segmentations manually drawn by expert radiologists based on histologic evidence of cancer. The training set consisted of 120 patients and the validation set and test set included 19 and 47, respectively. Slice-level probability maps are evaluated at the lesion level of analysis. The best model: HED using 5 × 5 convolutional kernels, batch normalization, and optimized using Adam. This CAD performed significantly better ( p < 0.001 ) in the peripheral zone ( AUC = 0.94 ± 0.01 ) than the transition zone. It outperforms a previous CAD from our group in a head-to-head comparison on the same ERC-only test cases ( AUC = 0.97 ± 0.01 ; p < 0.001 ). Our CAD establishes a state-of-the-art performance for predicting prostate cancer lesions on mpMRIs.

Computer-aided diagnosis prior to conventional interpretation of prostate mpMRI: an international multi-reader study

OBJECTIVES

To evaluate if computer-aided diagnosis (CAD) prior to prostate multi-parametric MRI (mpMRI) can improve sensitivity and agreement between radiologists.

METHODS

Nine radiologists (three each high, intermediate, low experience) from eight institutions participated. A total of 163 patients with 3-T mpMRI from 4/2012 to 6/2015 were included: 110 cancer patients with prostatectomy after mpMRI, 53 patients with no lesions on mpMRI and negative TRUS-guided biopsy. Readers were blinded to all outcomes and detected lesions per PI-RADSv2 on mpMRI. After 5 weeks, readers re-evaluated patients using CAD to detect lesions. Prostatectomy specimens registered to MRI were ground truth with index lesions defined on pathology. Sensitivity, specificity and agreement were calculated per patient, lesion level and zone-peripheral (PZ) and transition (TZ).

RESULTS

Index lesion sensitivity was 78.2% for mpMRI alone and 86.3% for CAD-assisted mpMRI (p = 0.013). Sensitivity was comparable for TZ lesions (78.7% vs 78.1%; p = 0.929); CAD improved PZ lesion sensitivity (84% vs 94%; p = 0.003). Improved sensitivity came from lesions scored PI-RADS < 3 as index lesion sensitivity was comparable at PI-RADS ≥ 3 (77.6% vs 78.1%; p = 0.859). Per patient specificity was 57.1% for CAD and 70.4% for mpMRI (p = 0.003). CAD improved agreement between all readers (56.9% vs 71.8%; p < 0.001).

CONCLUSIONS

CAD-assisted mpMRI improved sensitivity and agreement, but decreased specificity, between radiologists of varying experience.

KEY POINTS

• Computer-aided diagnosis (CAD) assists clinicians in detecting prostate cancer on MRI. • CAD assistance improves agreement between radiologists in detecting prostate cancer lesions. • However, this CAD system induces more false positives, particularly for less-experienced clinicians and in the transition zone. • CAD assists radiologists in detecting cancer missed on MRI, suggesting a path for improved diagnostic confidence.

All over the map: An interobserver agreement study of tumor location based on the PI-RADSv2 sector map

BACKGROUND

Prostate imaging reporting and data system version 2 (PI-RADSv2) recommends a sector map for reporting findings of prostate cancer mulitparametric MRI (mpMRI). Anecdotally, radiologists may demonstrate inconsistent reproducibility with this map.

PURPOSE

To evaluate interobserver agreement in defining prostate tumor location on mpMRI using the PI-RADSv2 sector map.

STUDY TYPE

Retrospective.

POPULATION

Thirty consecutive patients who underwent mpMRI between October, 2013 and March, 2015 and who subsequently underwent prostatectomy with whole-mount processing.

FIELD STRENGTH

3T mpMRI with T2 W, diffusion-weighted imaging (DWI) (apparent diffusion coefficient [ADC] and b-2000), dynamic contrast-enhanced (DCE).

ASSESSMENT

Six radiologists (two high, two intermediate, and two low experience) from six institutions participated. Readers were blinded to lesion location and detected up to four lesions as per PI-RADSv2 guidelines. Readers marked the long-axis of lesions, saved screen-shots of each lesion, and then marked the lesion location on the PI-RADSv2 sector map. Whole-mount prostatectomy specimens registered to the MRI served as ground truth. Index lesions were defined as the highest grade lesion or largest lesion if grades were equivalent.

STATISTICAL TEST

Agreement was calculated for the exact, overlap, and proportion of agreement.

RESULTS

Readers detected an average of 1.9 lesions per patient (range 1.6-2.3). 96.3% (335/348) of all lesions for all readers were scored PI-RADS ≥3. Readers defined a median of 2 (range 1-18) sectors per lesion. Agreement for detecting index lesions by screen shots was 83.7% (76.1%-89.9%) vs. 71.0% (63.1-78.3%) overlap agreement on the PI-RADS sector map (P < 0.001). Exact agreement for defining sectors of detected index lesions was only 21.2% (95% confidence interval [CI]: 14.4-27.7%) and rose to 49.0% (42.4-55.3%) when overlap was considered. Agreement on defining the same level of disease (ie, apex, mid, base) was 61.4% (95% CI 50.2-71.8%).

DATA CONCLUSION

Readers are highly likely to detect the same index lesion on mpMRI, but exhibit poor reproducibility when attempting to define tumor location on the PI-RADSv2 sector map. The poor agreement of the PI-RADSv2 sector map raises concerns its utility in clinical practice.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2018;48:482-490.

Cognitive-Targeted versus Magnetic Resonance Imaging-Guided Prostate Biopsy in Prostate Cancer Detection

Introduction

Purpose of this study is to evaluate the detection rates of prostate cancer (PCa) for cognitive-targeted biopsy (CTB) in comparison with magnetic resonance imaging (MRI)-guided biopsy (MRGB) related to prostate imaging reporting and data system (PI-RADS) score, lesion location and lesion volume. Furthermore, the addition of systematic transrectal ultrasound-guided biopsy (TRUS-GB) to CTB is evaluated.

Materials and Methods

We included all patients with cancer-suspicious lesions on 3-Tesla multiparametric MRI who underwent either CTB and additional TRUS-GB or only MRGB (in-bore) in Haga Teaching Hospital between January 2013 and January 2015.

Results

In total 219 patients were included: 64 CTB + TRUS-GB and 155 MRGB. In 32 (50%) men with CTB was positive for PCa. PI-RADS 3-, 4- and 5-lesions were in 17, 69 and 95% positive, respectively. In 100 men (65%) with MRGB was positive for PCa. Detection rates for PI-RADS 3-, 4- and 5-lesions were 10, 77 and 89%, respectively. CTB missed 4 (11%) low-grade tumors detected by TRUS-GB. In lesions between 0-1.5 ml PCa were significantly more often detected with MRGB than with CTB (69 vs. 39%).

Conclusion

CTB has a high detection rate of PCa in men with cancer-suspicious lesions on MRI. Correction for lesion volume shows that in lesions < 1.5 ml MRGB is more accurate than CTB. The addition of TRUS-GB to CTB can safely be avoided without missing any high grade PCa.

Future Perspectives and Challenges of Prostate MR Imaging

MR imaging is an important part of prostate cancer diagnosis. Variations in quality and skill in general practice mean results are not as impressive as they were in academic centers. This observation provides an impetus to improve the method. Improved quality assurance will likely result in better outcomes. Improved characterization of clinically significant prostate cancer may assist in making MR imaging more useful. Improved methods of registering MR imaging with transrectal ultrasound imaging and robotic arms controlling the biopsy can reduce the impact of inexperienced operators and make the entire system of MR imaging-guided biopsies more robust.

The Current State of MR Imaging-targeted Biopsy Techniques for Detection of Prostate Cancer

Systematic transrectal ultrasonography (US)-guided biopsy is the standard approach for histopathologic diagnosis of prostate cancer. However, this technique has multiple limitations because of its inability to accurately visualize and target prostate lesions. Multiparametric magnetic resonance (MR) imaging of the prostate is more reliably able to localize significant prostate cancer. Targeted prostate biopsy by using MR imaging may thus help to reduce false-negative results and improve risk assessment. Several commercial devices are now available for targeted prostate biopsy, including in-gantry MR imaging-targeted biopsy and real-time transrectal US-MR imaging fusion biopsy systems. This article reviews the current status of MR imaging-targeted biopsy platforms, including technical considerations, as well as advantages and challenges of each technique. ^© RSNA, 2017.

Computer-aided diagnosis of prostate cancer with MRI

Multi-parametric magnetic resonance imaging (mp-MRI) has an increasingly important role in the diagnosis of prostate cancer. Due to the large amount of data and variations in mp-MRI, tumor detection can be affected by multiple factors, such as the observer's clinical experience, image quality, and appearance of the lesions. In order to improve the quantitative assessment of the disease and reduce the reporting time, various computer-aided diagnosis (CAD) systems have been designed to help radiologists identify lesions. This manuscript presents an overview of the literature regarding prostate CAD using mp-MRI, while focusing on the studies of the most recent five years. Current prostate CAD technologies and their utilization are discussed in this review.

PRECISION MANAGEMENT OF LOCALIZED PROSTATE CANCER

INTRODUCTION

The vast majority of men who are diagnosed with prostate cancer die of other causes, highlighting the importance of determining which patient has a risk of death from prostate cancer. Precision management of prostate cancer patients includes distinguishing which men have potentially lethal disease and employing strategies for determining which treatment modality appropriately balances the desire to achieve a durable response while preventing unnecessary overtreatment.

AREAS COVERED

In this review, we highlight precision approaches to risk assessment and a context for the precision-guided application of definitive therapy. We focus on three dilemmas relevant to the diagnosis of localized prostate cancer: screening, the decision to treat, and postoperative management.

EXPERT COMMENTARY

In the last five years, numerous precision tools have emerged with potential benefit to the patient. However, to achieve optimal outcome, the decision to employ one or more of these tests must be considered in the context of prevailing conventional factors. Moreover, performance and interpretation of a molecular or imaging precision test remains practitioner-dependent. The next five years will witness increased marriage of molecular and imaging biomarkers for improved multi-modal diagnosis and discrimination of disease that is aggressive versus truly indolent.

Computer-aided Detection of Prostate Cancer with MRI: Technology and Applications

One in six men will develop prostate cancer in his lifetime. Early detection and accurate diagnosis of the disease can improve cancer survival and reduce treatment costs. Recently, imaging of prostate cancer has greatly advanced since the introduction of multiparametric magnetic resonance imaging (mp-MRI). Mp-MRI consists of T2-weighted sequences combined with functional sequences including dynamic contrast-enhanced MRI, diffusion-weighted MRI, and magnetic resonance spectroscopy imaging. Because of the big data and variations in imaging sequences, detection can be affected by multiple factors such as observer variability and visibility and complexity of the lesions. To improve quantitative assessment of the disease, various computer-aided detection systems have been designed to help radiologists in their clinical practice. This review paper presents an overview of literatures on computer-aided detection of prostate cancer with mp-MRI, which include the technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application.

Multiparametric prostate magnetic resonance imaging in the evaluation of prostate cancer

Imaging has traditionally played a minor role in the diagnosis and staging of prostate cancer. However, recent controversies generated by the use of prostate-specific antigen (PSA) screening followed by random biopsy have encouraged the development of new imaging methods for prostate cancer. Multiparametric magnetic resonance imaging (mpMRI) has emerged as the imaging method best able to detect clinically significant prostate cancers and to guide biopsies. Here, the authors explain what mpMRI is and how it is used clinically, especially with regard to high-risk populations, and we discuss the impact of mpMRI on treatment decisions for men with prostate cancer. CA Cancer J Clin 2016;66:326-336. © 2015 American Cancer Society.

Evaluating the Role of mpMRI in Prostate Cancer Assessment

Prostate cancer is the most common malignancy among American men. The role of multi-parametric MRI has recently gained more importance in detection of prostate cancer, its targeted biopsy, and focal therapy guidance. In this review, uses of multi-parametric MRI in prostate cancer assessment and treatment are discussed.

A Case of In-Bore Transperineal MRI-Guided Prostate Biopsy of a Patient with Ileal Pouch-Anal Anastomosis

Ulcerative colitis (UC) is an inflammatory disease that specifically affects the colon. Ulcerative colitis is primarily treated medically and refractory disease is treated with proctocolectomy and ileal pouch-anal anastomosis (IPAA). Gastroenterologists advise against digital rectal exams, pelvic radiation therapy, and transrectal ultrasound (TRUS) biopsies of the prostates of ileal pouch-anal anastomosis patients. Any form of pouch manipulation can lead to severe bleeding, inflammation, and pain. Urologists are therefore faced with the challenge of doing a prostate biopsy without a transrectal ultrasound. We report the rare case of a patient with an ileal pouch-anal anastomosis who underwent in-bore transperineal MRI-guided biopsy of the prostate.

The economic effect of using magnetic resonance imaging and magnetic resonance ultrasound fusion biopsy for prostate cancer diagnosis

Prostate magnetic resonance imaging (MRI) is a maturing imaging modality that has been used to improve detection and staging of prostate cancer. The goal of this review is to evaluate the economic effect of the use of MRI and MRI fusion in the diagnosis of prostate cancer. A literature review was used to identify articles regarding efficacy and cost of MRI and MRI-guided biopsies. There are currently a limited number of studies evaluating cost of incorporating MRI into clinical practice. These studies are primarily models projecting cost estimates based on meta-analyses of the literature. There is considerable variance in the effectiveness of MRI-guided biopsies, both cognitive and fusion, based on user experience, type of MRI (3T vs. 1.5T), use of endorectal coil and type of scoring system for abnormalities such that there is still potential for improvement in accuracy. There is also variability in assumed costs of incorporating MRI into clinical practice. The addition of MRI to the diagnostic algorithm for prostate cancer has caused a shift in how we understand the disease and in what tumors are found on initial and repeat biopsies. Further risk stratification may allow more men to pursue noncurative therapy, which in and of itself is cost-effective in properly selected men. As prostate cancer care comes under increasing scrutiny on a national level, there is pressure on providers to be more accurate in their diagnoses. This in turn can lead to additional testing including Multiparametric MRI, which adds upfront cost. Whether the additional cost of prostate MRI is warranted in detection of prostate cancer is an area of intense research.

Partial Gland Ablation for Prostate Cancer: Report of a Food and Drug Administration, American Urological Association, and Society of Urologic Oncology Public Workshop

OBJECTIVE

To summarize the discussion that took place at a public workshop, co-sponsored by the U.S. Food and Drug Administration, the American Urological Association, and Society of Urologic Oncology reviewing the current state of the art for partial gland ablation (PGA) for the management of patients with prostate cancer. The purpose of this workshop was to discuss potential indications, current available evidence, and designs for future trials to provide the evidence needed by patients and providers to decide how and when to use PGA.

METHODS

A workshop evaluating PGA for prostate cancer was held in New Orleans, Louisiana, in May 2015. Invited experts representing all stakeholders and attendees discussed the regulatory development of medical products, technology available, potential indications, and designs of trials to evaluate this modality of therapy.

RESULTS

The panel presented the current information on the technologies available to perform PGA, the potential indications, and results of prior consensus conferences. Use of magnetic resonance imaging for patient selection, guide therapy, and follow-up was discussed. Designs of trials to assess PGA outcomes were discussed.

CONCLUSION

The general consensus was that currently available technologies are capable of selective ablation with reasonable accuracy, but that criteria for patient selection remain debatable, and long-term cancer control remains to be established in properly designed and well-performed prospective clinical trials. Concerns include the potential for excessive, unnecessary use in patients with low-risk cancer and, conversely, that current diagnostic techniques may underestimate the extent and aggressiveness of some cancers, leading to inadequate treatment.

Molecular Profiles of Prostate Cancer: To Treat or Not to Treat

A major dilemma in the selection of treatment for men with prostate cancer is the difficulty in accurately characterizing the risk posed by the cancer. This uncertainty has led physicians to recommend aggressive therapy for most men diagnosed with prostate cancer and has led to concerns about the benefits of screening and the adverse consequences of excessive treatment. Genomic analyses of prostate cancer reveal distinct patterns of alterations in the genomic landscape of the disease that show promise for improved prediction of prognosis and better medical decision making. Several molecular profiles are now commercially available and are being used to inform medical decisions. This article describes the clinical tests available for distinguishing aggressive from nonaggressive prostate cancer, reviews the new genomic tests, and discusses their advantages and limitations and the evidence for their utility in various clinical settings.