False positive and false negative diagnoses of prostate cancer at multi-parametric prostate MRI in active surveillance

Prospective comparison of restriction spectrum imaging and non-invasive biomarkers to predict upgrading on active surveillance prostate biopsy

BACKGROUND

Protocol-based active surveillance (AS) biopsies have led to poor compliance. To move to risk-based protocols, more accurate imaging biomarkers are needed to predict upgrading on AS prostate biopsy. We compared restriction spectrum imaging (RSI-MRI) generated signal maps as a biomarker to other available non-invasive biomarkers to predict upgrading or reclassification on an AS biopsy.

METHODS

We prospectively enrolled men on prostate cancer AS undergoing repeat biopsy from January 2016 to June 2019 to obtain an MRI and biomarkers to predict upgrading. Subjects underwent a prostate multiparametric MRI and a short duration, diffusion-weighted enhanced MRI called RSI to generate a restricted signal map along with evaluation of 30 biomarkers (14 clinico-epidemiologic features, 9 molecular biomarkers, and 7 radiologic-associated features). Our primary outcome was upgrading or reclassification on subsequent AS prostate biopsy. Statistical analysis included operating characteristic improvement using AUROC and AUPRC.

RESULTS

The individual biomarker with the highest area under the receiver operator characteristic curve (AUC) was RSI-MRI (AUC = 0.84; 95% CI: 0.71-0.96). The best non-imaging biomarker was prostate volume-corrected Prostate Health Index density (PHI, AUC = 0.68; 95% CI: 0.53-0.82). Non-imaging biomarkers had a negligible effect on predicting upgrading at the next biopsy but did improve predictions of overall time to progression in AS.

CONCLUSIONS

RSI-MRI, PIRADS, and PHI could improve the predictive ability to detect upgrading in AS. The strongest predictor of clinically significant prostate cancer on AS biopsy was RSI-MRI signal output.

Prostate MRI and image quality: The urologist's perspective

The development of different imaging modalities of the prostate has significantly improved tumor detection, patient risk stratification, and quality of care.Among these, multiparametric magnetic resonance imaging (mp-MRI) has emerged as the most sensitive tool.It is useful in the diagnosis, localization, risk stratification, and staging of clinically significant prostate cancer, PCa. As a result, mp-MRI of the prostate is recommended as the initial diagnostic test for men with suspected PCa. A multidisciplinary approach is crucial in the diagnosis and management of prostate cancer and mp-MRI plays a fundamental role in this scenario.While many aspects of image quality certainly fall within the purview of radiology, it is important to recognize that urologists must also be attentive to imaging quality when utilizing mp-MRI to facilitate PCa management. We present our viewpoint as urologists on how image quality impacts the management of men diagnosed with PCa andattempt to identify the factors that impact mp-MRI image quality, consequences of poor image quality, and finally suggestions for improvements.

Pitfalls in Prostate MR Imaging Interpretation

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

Diffusion kurtosis imaging and standard diffusion imaging in the magnetic resonance imaging assessment of prostate cancer

Background and Objective

In recent years, magnetic resonance imaging (MRI) has shown excellent results in the study of the prostate gland. MRI has indeed shown to be advantageous in the prostate cancer (PCa) detection, as in guiding targeting biopsy, improving its diagnostic yield. Although current acquisition protocols provide for multiparametric acquisition, recent evidence has shown that biparametric protocols can be non-inferior in PCa detection. Diffusion-weighted imaging (DWI) sequence, in particular, plays a key role, particularly in the peripheral zone which accounts for the larger part of the prostate. High b-values are generally recommended, although with the possibility of obtaining non-Gaussian diffusion effects, which requires a more sophisticated model for the analysis, namely through the diffusion kurtosis imaging (DKI). Purpose of this narrative review was to analyze the current applications and clinical evidence regarding the use of DKI with a main focus on PCa detection, also in comparison with DWI.

Methods

This narrative review synthesized the findings of literature retrieved from main researches, narrative and systematic reviews, and meta-analyses obtained from PubMed.

Key Content and Findings

DKI analyses the non-Gaussian water diffusivity and describe the effect of signal intensity decay related to high b-value through two main metrics (Dapp and Kapp). Differently from DWI-apparent diffusion coefficient (DWI-ADC) which reflects only water restriction outside of cells, DKI metrics are supposed to represent also the direct interaction of water molecules with cell membranes and intracellular compounds. This review describes current evidence on ADC and DKI metrics in clinical imaging, and finally collect the results derived from the main articles focused on DWI and DKI models in detecting PCa.

Conclusions

DKI advantages, compared to conventional ADC analysis, still remain controversial. Wider application and greater technical knowledge of DKI, however, may help in proving its intrinsic validity in the field of oncology and therefore in the study of clinically significant PCa. Finally, a deep understanding of DKI is important for radiologists to better understand what Kapp and Dapp mean in the context of different cancer and how these metrics may vary specifically in PCa imaging.

Combination of DNA methylation biomarkers with multiparametric magnetic resonance and ultrasound imaging fusion biopsy to detect the local spread of prostate cancer

BACKGROUND

This study aimed to investigate the extent of field cancerization adjacent to index lesions in prostate cancer (PCa) by measuring DNA methylation of selected tumor suppressor genes in the perifocal tissue of PCa not visible on multiparametric magnetic resonanse imaging (mpMRI) for the safe zone of focal therapy identification.

METHODS

A total of 272 patients were enrolled in this study, 44 patients' tissue biosamples were included in the field cancerization research, and 272 urine samples were included in the urine-based test development. Targeted biopsies were performed using the mpMRI/ultrasoundimage fusion system.

RESULTS

Quantitative analysis revealed significantly higher DNA methylation levels of RARB, RASSF1, GSTP1 & APC genes in the index lesion compared with perifocal tissue samples 10 mm away from it (p < 0.0001). Notably, the RARB, GSTP1 & APC and RARB, RASSF1, GSTP1 & APC biomarker combinations exhibited the highest sensitivity and specificity comparing the extent of DNA methylation in index lesions and noncancerous prostate tissues 20 mm away (both area under the curve [AUC] = 0.98; p < 0.0001). The analysis of the potential urinary biomarkers showed that the combination of all four DNA methylation biomarkers with prostate-specific antigen (PSA) or PSA density (PSAD) in the blood significantly improves the detection of clinically significant PCa (csPCa). The combination of the four-biomarker test with PSAD allowed the identification of csPCa with ≥90% sensitivity and specificity.

CONCLUSION

Thus, this study suggests that for focal therapy by region target hemi-ablation, the safe distance from the index lesion is no less than 10 mm. Noninvasive urine DNA methylation tests in combination with PSAD could be used for further follow-up of the patients, but larger prospective studies with external validation are needed.

Dynamic Contrast-Enhanced Study in the mpMRI of the Prostate-Unnecessary or Underutilised? A Narrative Review

The aim of this review is to summarise recent scientific literature regarding the clinical use of DCE-MRI as a component of multiparametric resonance imaging of the prostate. This review presents the principles of DCE-MRI acquisition and analysis, the current role of DCE-MRI in clinical practice with special regard to its role in presently available categorisation systems, and an overview of the advantages and disadvantages of DCE-MRI described in the current literature. DCE-MRI is an important functional sequence that requires intravenous administration of a gadolinium-based contrast agent and gives information regarding the vascularity and capillary permeability of the lesion. Although numerous studies have confirmed that DCE-MRI has great potential in the diagnosis and monitoring of prostate cancer, its role is still inadequate in the PI-RADS categorisation. Moreover, there have been numerous scientific discussions about abandoning the intravenous application of gadolinium-based contrast as a routine part of MRI examination of the prostate. In this review, we summarised the recent literature on the advantages and disadvantages of DCE-MRI, focusing on an overview of currently available data on bpMRI and mpMRI, as well as on studies providing information on the potential better usability of DCE-MRI in improving the sensitivity and specificity of mpMRI examinations of the prostate.

Prostate Cancer: Genetics, Epigenetics and the Need for Immunological Biomarkers

Epidemiological data highlight prostate cancer as a significant global health issue, with high incidence and substantial impact on patients' quality of life. The prevalence of this disease is associated with various factors, including age, heredity, and race. Recent research in prostate cancer genetics has identified several genetic variants that may be associated with an increased risk of developing the disease. However, despite the significance of these findings, genetic markers for prostate cancer are not currently utilized in clinical practice as reliable indicators of the disease. In addition to genetics, epigenetic alterations also play a crucial role in prostate cancer development. Aberrant DNA methylation, changes in chromatin structure, and microRNA (miRNA) expression are major epigenetic events that influence oncogenesis. Existing markers for prostate cancer, such as prostate-specific antigen (PSA), have limitations in terms of sensitivity and specificity. The cost of testing, follow-up procedures, and treatment for false-positive results and overdiagnosis contributes to the overall healthcare expenditure. Improving the effectiveness of prostate cancer diagnosis and prognosis requires either narrowing the risk group by identifying new genetic factors or enhancing the sensitivity and specificity of existing markers. Immunological biomarkers (both circulating and intra-tumoral), including markers of immune response and immune dysfunction, represent a potentially useful area of research for enhancing the diagnosis and prognosis of prostate cancer. Our review emphasizes the need for developing novel immunological biomarkers to improve the diagnosis, prognosis, and management of prostate cancer. We highlight the most recent achievements in the identification of biomarkers provided by circulating monocytes and tumor-associated macrophages (TAMs). We highlight that monocyte-derived and TAM-derived biomarkers can enable to establish the missing links between genetic predisposition, hormonal metabolism and immune responses in prostate cancer.

Differences in the pathogenetic characteristics of prostate cancer in the transitional and peripheral zones and the possible molecular biological mechanisms

Since the theory of modern anatomical partitioning of the prostate was proposed, the differences in the incidence and pathological parameters of prostate cancer between the peripheral zone and transition zone have been gradually revealed. It suggests that there are differences in the pathogenic pathways and molecular biology of prostate cancer between different regions of origin. Over the past decade, advances in sequencing technologies have revealed more about molecules, genomes, and cell types specific to the peripheral and transitional zones. In recent years, the innovation of spatial imaging and multiple-parameter magnetic resonance imaging has provided new technical support for the zonal study of prostate cancer. In this work, we reviewed all the research results and the latest research progress in the study of prostate cancer in the past two decades. We summarized and proposed several vital issues and focused directions for understanding the differences between peripheral and transitional zones in prostate cancer.

Granulomatous prostatitis after bacille Calmette-Guérin instillation resembles prostate carcinoma: A case report and review of the literature

BACKGROUND

Bacille Calmette-Guérin (BCG) instillation is recommended in patients with non-muscle-invasive bladder cancer who have intermediate-risk and high-risk tumors. However, granulomatous prostatitis is a rare complication induced by BCG instillation, which can easily be misdiagnosed as prostate cancer. Here, we report a case of granulomatous prostatitis that resembled prostate cancer.

CASE SUMMARY

A 64-year-old Chinese man with bladder cancer received BCG instillation. Three days later, he stopped BCG instillation and received anti-infective therapy due to the urinary tract infection. Three months after BCG restart, he had rising total prostate-specific antigen (PSA) (9.14 ng/mL) and decreasing free PSA/total PSA (0.09). T2-weighted images of magnetic resonance imaging (MRI) showed a 28 mm × 20 mm diffuse low signal abnormality in the right peripheral zone, which was markedly hyperintense on high b-value diffusion-weighted MRI and hypointense on apparent diffusion coefficient map images. Considering Prostate Imaging Reporting and Data System score of 5 and possibility of prostate cancer, a prostate biopsy was conducted. Histopathology showed typical features of granulomatous prostatitis. The nucleic acid test for tuberculosis was positive. He was finally diagnosed with BCG-induced granulomatous prostatitis. Thereafter, he stopped BCG instillation and received anti-tuberculosis treatment. During 10 mo follow-up, he had no evidence of tumor recurrence or symptoms of tuberculosis.

CONCLUSION

Temporarily elevated PSA and high followed by low signal abnormality on diffusion-weighted MRI are important indicators of BCG-induced granulomatous prostatitis.

Combination of MRI prostate and 18F-DCFPyl PSMA PET/CT detects all clinically significant prostate cancers in treatment-naive patients: An international multicentre retrospective study

INTRODUCTION

Clinical and biochemical assessment and biopsies can miss clinically significant prostate cancers (csPCa) in up to 20% of patients and diagnose clinically insignificant tumours leading to overtreatment. This retrospective study analyses the accuracy of ¹⁸ F-DCFPyL PET/CT in detecting csPCa as a primary diagnostic tool and directly compares it with mpMRI prostate in treatment-naive patients. The two modalities are then correlated to determine whether they are better in combination, than either alone.

METHODS

This is a retrospective dual-institution study of patients who underwent contemporaneous MRI and PSMA-PET between January 2017 and March 2020 with histologic confirmation. The images were re-reviewed and concordance between modalities assessed. Results were compared with histopathology to determine the ability of MRI and PSMA-PET to detect csPCA.

RESULTS

MRI and PSMA-PET detected the same index lesion in 90.8% of cases with a kappa of 0.82. PET detected an additional 6.2% of index lesions which were MRI occult. MRI detected an additional 3.1% which were PET occult. No additional csPCa was identified on pathology which was not seen on imaging. The sensitivity of PSMA-PET in detecting csPCa is 96.7% and that of MRI is 93.4% with no statistically significant difference between the two (P = 0.232). Both modalities detected all four cases of non-csPCa with these being considered false positives.

CONCLUSION

Both mpMRI and 18F-DCFPyL-PSMA-PET/CT have high sensitivity for detecting csPCa with high agreement between modalities. There were no synchronous csPCa lesions detected on pathology that were not detected on imaging too.

Does previous prostate surgery affect multiparametric magnetic resonance imaging accuracy in detecting clinically significant prostate cancer? Results from a single institution series

BACKGROUND

Multiparametric MRI (mpMRI) has demonstrated high diagnostic accuracy for clinically significant PCa (csPCa). However, the accuracy of this test in men that received a previous prostatic surgery is still controversial. We aimed at assessing the effect of previous prostatic surgery on the detection of csPCa in a tertiary referral center.

METHOD

We relied on a cohort of 311 men with a positive mpMRI (prostate imaging - reporting and data system [PI-RADS] ≥ 3) who underwent a targeted (TBx) plus concomitant systematic random biopsy (SBx) at a single tertiary referral center between 2017 and 2020. The study outcome was to compare the detection of csPCa (Gleason score ≥ 3 + 4) between the two groups (no previous prostate surgery [Group 1] vs. previous prostate surgery [Group 2]). Multivariable logistic regression analysis (MVA) was used to assess the relationship between previous prostate surgery and the detection of csPCa at TBx, after taking into account potential clinical confounders.

RESULTS

Overall, 24 (8%) patients received a previous prostate surgery before undergoing mpMRI. Median prostate-specific antigen density was 0.15 versus 0.08 ng/ml/cc, in Group 1 versus 2, respectively. The most frequent finding at mpMRI was in Group 1 versus 2, PI-RADS 4 (55%) versus PI-RADS 3 and 4 (42% each). The majority of patients were biopsy naïve in both Groups 1 (66%) and 2 (71%). The overall detection of csPCa in Group 1 versus 2 was 83% versus 75%, respectively. Differently, the detection of csPCa at TBx in Groups 1 versus 2 was 76% versus 71%, respectively. At MVA, previous prostate surgery (odds ratio: 0.65; p = 0.02) was significantly associated with lower csPCa detection at TBx, after accounting for potential confounders.

CONCLUSION

The presence of previous prostate surgery significantly decreases the accuracy of mpMRI in detecting csPCa. These results should be taken into account when assessing patients with a history of prostatic surgery and a suspicious lesion at mpMRI, to better select those who might avoid an unnecessary biopsy.

Differentiating False Positive Lesions from Clinically Significant Cancer and Normal Prostate Tissue Using VERDICT MRI and Other Diffusion Models

False positives on multiparametric MRIs (mp-MRIs) result in many unnecessary invasive biopsies in men with clinically insignificant diseases. This study investigated whether quantitative diffusion MRI could differentiate between false positives, true positives and normal tissue non-invasively. Thirty-eight patients underwent mp-MRI and Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumors (VERDICT) MRI, followed by transperineal biopsy. The patients were categorized into two groups following biopsy: (1) significant cancer—true positive, 19 patients; (2) atrophy/inflammation/high-grade prostatic intraepithelial neoplasia (PIN)—false positive, 19 patients. The clinical apparent diffusion coefficient (ADC) values were obtained, and the intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI) and VERDICT models were fitted via deep learning. Significant differences (p < 0.05) between true positive and false positive lesions were found in ADC, IVIM perfusion fraction (f) and diffusivity (D), DKI diffusivity (DK) (p < 0.0001) and kurtosis (K) and VERDICT intracellular volume fraction (fIC), extracellular−extravascular volume fraction (fEES) and diffusivity (dEES) values. Significant differences between false positives and normal tissue were found for the VERDICT fIC (p = 0.004) and IVIM D. These results demonstrate that model-based diffusion MRI could reduce unnecessary biopsies occurring due to false positive prostate lesions and shows promising sensitivity to benign diseases.

Multiple analyses suggests texture features can indicate the presence of tumor in the prostate tissue

Several studies have demonstrated statistical and texture analysis abilities to differentiate cancerous from healthy tissue in magnetic resonance imaging. This study developed a method based on texture analysis and machine learning to differentiate prostate findings. Forty-eight male patients with PI-RADS classification and subsequent radical prostatectomy histopathological analysis were used as gold standard. Experienced radiologists delimited the regions of interest in magnetic resonance images. Six different groups of images were used to perform multiple analyses (seven analyses variations). Those analyses were outlined by specialists in urology as those of most significant importance for the classification. Forty texture features were extracted from each image and processed with Random Forest, Support Vector Machine, K-Nearest Neighbors, and Naive Bayes. Those seven analyses variation results were described in terms of area under the ROC curve (AUC), accuracy, F-score, precision and sensitivity. The highest AUC (93.7%) and accuracy (88.8%) were obtained when differentiating the group with both MRI and histopathology positive findings against the group with both negative MRI and histopathology. When differentiating the group with both MRI and histopathology positive findings versus the peripheral image zone group the AUC value was 86.6%. When differentiating the group with negative MRI/positive histopathology versus the group with both negative MRI and histopathology the AUC value was 80.7%. The evaluation of statistical and texture analysis promoted very suggestive indications for future work in prostate cancer suspicious regions. The method is fast for both region of interest selection and classification with machine learning and the result brings original contributions in the classification of different groups of patients. This tool is low-cost, and can be used to assist diagnostic decisions.

Synthetic correlated diffusion imaging hyperintensity delineates clinically significant prostate cancer

Prostate cancer (PCa) is the second most common cancer in men worldwide and the most frequently diagnosed cancer among men in more developed countries. The prognosis of PCa is excellent if detected at an early stage, making early screening crucial for detection and treatment. In recent years, a new form of diffusion magnetic resonance imaging called correlated diffusion imaging (CDI) was introduced, and preliminary results show promise as a screening tool for PCa. In the largest study of its kind, we investigate the relationship between PCa presence and a new variant of CDI we term synthetic correlated diffusion imaging (CDI\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^s$$\end{document}s), as well as its performance for PCa delineation compared to current standard MRI techniques [T2-weighted (T2w) imaging, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) imaging] across a cohort of 200 patient cases. Statistical analyses reveal that hyperintensity in CDI\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^s$$\end{document}s is a strong indicator of PCa presence and achieves strong delineation of clinically significant cancerous tissue compared to T2w, DWI, and DCE. These results suggest that CDI\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^s$$\end{document}s hyperintensity may be a powerful biomarker for the presence of PCa, and may have a clinical impact as a diagnostic aid for improving PCa screening.

Comparison of Multiparametric Magnetic Resonance Imaging and Gallium-68 Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography for Detecting Carcinoma Prostate in Patients with Serum Prostate-Specific Antigen between 4 and 20 ng/ml

Introduction

We carried out this study to compare the diagnostic accuracy of multiparametric magnetic resonance imaging (mpMRI) and gallium-68 prostate-specific membrane antigen positron emission tomography/computed tomography (Ga-68 PSMA PET/CT) to detect prostatic carcinoma in patients with serum prostate-specific antigen (PSA) between 4 and 20 ng/ml in prebiopsy setting.

Materials and Methods

This prospective study evaluated men with serum PSA values between 4 and 20 ng/ml. All patients underwent mpMRI and Ga-68 PSMA PET/CT, followed by 12-core transrectal ultrasonography (TRUS)-guided biopsy to detect prostatic carcinoma. The diagnostic accuracy of mpMRI and PSMA PET/CT scan was compared with histopathological findings.

Results

There were thirty patients included in the study with a median age of 73 years (age range: 69-79 years). The median total serum PSA was 8.0 ng/ml (5.0-19.9 ng/ml). Of these, 18 had an identifiable lesion on imaging and had histopathological findings suggestive of carcinoma prostate. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of mpMRI were 100%, 92.30%, 94.73%, and 100%, respectively, and that of PSMA PET scan were 94.44%, 100%, 100%, and 92.31%, respectively. The diagnostic accuracy of both was 96.67%.

Conclusion

PSMA PET scan showed higher PPV and specificity while mpMRI showed higher sensitivity and NPV. The accuracy in predicting presence of carcinoma was the same for both. PSMA PET showed higher specificity and PPV and predicted the subsequent need of biopsy. In our study, the NPV of PET, though good, was lower than mpMRI. Prospective trials with larger sample size are needed. In combination, PET/MRI may achieve greater accuracy and may serve as investigation of choice.

Fully automated detection of prostate transition zone tumors on T2-weighted and apparent diffusion coefficient (ADC) map MR images using U-Net ensemble

PURPOSE

Accurate detection of transition zone (TZ) prostate cancer (PCa) on magnetic resonance imaging (MRI) remains challenging using clinical subjective assessment due to overlap between PCa and benign prostatic hyperplasia (BPH). The objective of this paper is to describe a deep-learning-based framework for fully automated detection of PCa in the TZ using T2-weighted (T2W) and apparent diffusion coefficient (ADC) map MR images.

METHOD

This was a single-center IRB-approved cross-sectional study of men undergoing 3T MRI on two systems. The dataset consisted of 196 patients (103 with and 93 without clinically significant [Grade Group 2 or higher] TZ PCa) to train and test our proposed methodology, with an additional 168 patients with peripheral zone PCa used only for training. We proposed an ensemble of classifiers in which multiple U-Net-based models are designed for prediction of TZ PCa location on ADC map MR images, with initial automated segmentation of the prostate to guide detection. We compared accuracy of ADC alone to T2W and combined ADC+T2W MRI for input images, and investigated improvements using ensembles over their constituent models with different methods of diversity in individual models by hyperparameter configuration, loss function and model architecture.

RESULTS

Our developed algorithm reported sensitivity and precision of 0.829 and 0.617 in 56 test cases containing 31 instances of TZ PCa and in 25 patients without clinically significant TZ tumors. Patient-wise classification accuracy had an area under receiver operator characteristic curve (AUROC) of 0.974. Single U-Net models using ADC alone (sensitivity 0.829, precision 0.534) outperformed assessment using T2W (sensitivity 0.086, precision 0.081) and assessment using combined ADC+T2W (sensitivity 0.687, precision 0.489). While the ensemble of U-Nets with varying hyperparameters demonstrated the highest performance, all ensembles improved PCa detection compared to individual models, with sensitivities and precisions close to the collective best of constituent models.

CONCLUSION

We describe a deep-learning-based method for fully automated TZ PCa detection using ADC map MR images that outperformed assessment by T2W and ADC+T2W.

Detection limits of significant prostate cancer using multiparametric MR and digital rectal examination in men with low serum PSA: Up-date of the Italian Society of Integrated Diagnostic in Urology

Reasons why significant prostate cancer is still missed in early stage were investigated at the 22nd National SIEUN (Italian Society of integrated diagnostic in Urology, Andrology, Nephrology) congress took place from 30th November to 1st December 2020, in virtual modality. Even if multiparametric magnetic resonance (MR) has been introduced in the clinical practice several, limitations are emerging in patient with regular digital rectal examination (DRE) and serum prostate specific antigen (PSA) levels approaching the normal limits. The present paper summarizes highlights observed in those cases where significant prostate cancer may be missed by PSA or imaging and DRE. The issue of multidisciplinary interest had been subdivided and deepened under four main topics: biochemical, clinical, pathological and radiological point of view with a focus on PI-RADS 3 lesions.

Diffusion Is Directional: Innovative Diffusion Tensor Imaging to Improve Prostate Cancer Detection

In the prostate, water diffusion is faster when moving parallel to duct and gland walls than when moving perpendicular to them, but these data are not currently utilized in multiparametric magnetic resonance imaging (mpMRI) for prostate cancer (PCa) detection. Diffusion tensor imaging (DTI) can quantify the directional diffusion of water in tissue and is applied in brain and breast imaging. Our aim was to determine whether DTI may improve PCa detection. We scanned patients undergoing mpMRI for suspected PCa with a DTI sequence. We calculated diffusion metrics from DTI and diffusion weighted imaging (DWI) for suspected lesions and normal-appearing prostate tissue, using specialized software for DTI analysis, and compared predictive values for PCa in targeted biopsies, performed when clinically indicated. DTI scans were performed on 78 patients, 42 underwent biopsy and 16 were diagnosed with PCa. The median age was 62 (IQR 54.4–68.4), and PSA 4.8 (IQR 1.3–10.7) ng/mL. DTI metrics distinguished PCa lesions from normal tissue. The prime diffusion coefficient (λ₁) was lower in both peripheral-zone (p < 0.0001) and central-gland (p < 0.0001) cancers, compared to normal tissue. DTI had higher negative and positive predictive values than mpMRI to predict PCa (positive predictive value (PPV) 77.8% (58.6–97.0%), negative predictive value (NPV) 91.7% (80.6–100%) vs. PPV 46.7% (28.8–64.5%), NPV 83.3% (62.3–100%)). We conclude from this pilot study that DTI combined with T2-weighted imaging may have the potential to improve PCa detection without requiring contrast injection.

Discrepancy between Multiparametric Magnetic Resonance Imaging and 68Ga Prostate-Specific Membrane Antigen Positron Emission Tomography: A Simultaneous Acquired Positron Emission Tomography-Magnetic Resonance Imaging Case

Conventionally, multiparametric magnetic resonance imaging (mpMRI) incorporating T2-weighted, diffusion-weighted, and dynamic contrast-enhanced sequences is considered the standard for detection and staging of clinically important prostate cancer (PCa).[1] The ⁶⁸gallium (⁶⁸Ga)-labeled positron emission tomography (PET) tracer targeting prostate-specific membrane antigen (PSMA), ⁶⁸Ga-PSMA PET, is a promising tool for detection, localization, and staging carcinoma prostate.[2] Here, we present a case of PCa, showing incongruence between ⁶⁸Ga-PSMA PET and the corresponding mpMRI findings. Moreover, the final histopathology revealed a surprise, which exemplifies the complementary nature of combining ⁶⁸Ga-PSMA PET and mpMRI in the diagnosis and staging of carcinoma prostate.

Prostate MRI: practical guidelines for interpreting and reporting according to PI-RADS version 2.1

The increasing precision of multiparametric magnetic resonance imaging of the prostate, together with greater experience and standardization in its interpretation, has given this technique an important role in the management of prostate cancer, the most prevalent non-cutaneous cancer in men. This article reviews the concepts in PI-RADS version 2.1 for estimating the probability and zonal location of significant tumors of the prostate, using a practical approach that includes current considerations about the prerequisites for carrying out the test and recommendations for interpreting the findings. It emphasizes benign findings that can lead to confusion and the criteria for evaluating the probability of local spread, which must be included in the structured report.

Post Prostatectomy Pathologic Findings of Patients With Clinically Significant Prostate Cancer and no Significant PI-RADS Lesions on Preoperative Magnetic Resonance Imaging

OBJECTIVES

We present postprostatectomy pathology results from a series of prostate cancer (Pca) Gleason grade group ≥2 patients who did not have findings suggestive of cancer on preoperative pelvic magnetic resonance imaging (MRI).

METHODS

We performed an institutional retrospective study of prostate magnetic resonance imaging (MRI) examinations done from October 2015 to February 2018. We identified patients who underwent prostatectomy for Pca Gleason ≥3 + 4 diagnosed on prostate biopsy with no associated MRI findings suggestive of malignancy and analyzed their postprostatectomy pathologic findings and MRI imaging results.

RESULTS

At our institution, 850 men with Pca received MRI between 2015 and 2018, and 156/850 patients received robotic-assisted radical prostatectomy. Thirty-three patients (33/156 = 21%) had negative MRI for PIRAD 3 or greater but had a biopsy showing significant Pca. Their mean (range) age was 62.7 (50-86) years. Their median (interquartile range) PSA, and PSA density were, 4.6 (3.7) ng/mL and 0.12 (0.05) ng/mL/cm², respectively; all not significantly different from patients with visible lesions on MRI who underwent surgery. On post prostatectomy pathology, 27/33 (82%) men had Pca Gleason score 7 or greater. The most common pattern was infiltrative growth with cancer glands intermingling between benign glands.

CONCLUSION

We describe the pathologic and imaging findings in an extensive series of men with clinically significant Pca with no significant lesions on preoperative MRI. Our results support the importance of patient counseling on the risk of missing significant Pca on MRI in isolation from other clinical variables.

MRI-targeted prostate biopsy: key considerations for pathologists

We discuss the role of the pathologist for MRI-targeted prostate biopsy with a focus on specimen processing, reporting of pathological findings and quality assurance in establishing a successful MRI-targeted biopsy programme. The authors discuss the current issues relevant to pathologists regarding MRI-targeted prostate biopsy. In addition, a brief review of the recently published literature was performed using an English literature search on PubMed with a focus on original investigations related to MRI-targeted prostate biopsy. Our search terms included the following: 'prostate cancer', 'pathology', 'histology', 'reporting', 'cores', 'imaging', 'MRI' and 'mpMRI'. Prostate multiparametric magnetic resonance imaging (mp-MRI) and MRI-targeted biopsy has been shown to improve the diagnosis of clinically significant prostatic adenocarcinoma and can affect the management of patients with prostate cancer. The current active surveillance guidelines were based on data from TRUS biopsies and not MRI-targeted biopsies. MRI-targeted biopsy acquires multiple cores of tissue from one or more suspicious lesions found on mp-MRI. The way in which multiple targeted core biopsies obtained from a single image-directed region of interest are analysed and reported can potentially alter the Gleason score and tumour burden as reported on biopsy, which could undoubtedly alter patient management. Pathologists play an important role in the reporting of MRI-targeted prostate biopsies. How we report prostate cancer grade and extent on these biopsies can influence patient management. In addition, the pathologist should be involved in the quality assurance for patients undergoing MRI-targeted prostate biopsy.

Quantitative Prostate MRI

Prostate MRI is reported in clinical practice using the Prostate Imaging and Data Reporting System (PI-RADS). PI-RADS aims to standardize, as much as possible, the acquisition, interpretation, reporting, and ultimately the performance of prostate MRI. PI-RADS relies upon mainly subjective analysis of MR imaging findings, with very few incorporated quantitative features. The shortcomings of PI-RADS are mainly: low-to-moderate interobserver agreement and modest accuracy for detection of clinically significant tumors in the transition zone. The use of a more quantitative analysis of prostate MR imaging findings is therefore of interest. Quantitative MR imaging features including: tumor size and volume, tumor length of capsular contact, tumor apparent diffusion coefficient (ADC) metrics, tumor T₁ and T₂ relaxation times, tumor shape, and texture analyses have all shown value for improving characterization of observations detected on prostate MRI and for differentiating between tumors by their pathological grade and stage. Quantitative analysis may therefore improve diagnostic accuracy for detection of cancer and could be a noninvasive means to predict patient prognosis and guide management. Since quantitative analysis of prostate MRI is less dependent on an individual users' assessment, it could also improve interobserver agreement. Semi- and fully automated analysis of quantitative (radiomic) MRI features using artificial neural networks represent the next step in quantitative prostate MRI and are now being actively studied. Validation, through high-quality multicenter studies assessing diagnostic accuracy for clinically significant prostate cancer detection, in the domain of quantitative prostate MRI is needed. This article reviews advances in quantitative prostate MRI, highlighting the strengths and limitations of existing and emerging techniques, as well as discussing opportunities and challenges for evaluation of prostate MRI in clinical practice when using quantitative assessment. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.

Histomorphological analysis of false positive PI-RADS 4 and 5 lesions

INTRODUCTION

Multiparametric magnetic resonance imaging (mpMRI)/ultrasound fusion-guided biopsy, in short "targeted biopsy (TB)", is becoming more attractive as it improves the detection of clinically significant prostate cancer (CaP). The accuracy of fusion-guided biopsies is limited due to false positive radiological findings as well as to histological evidence for cancer in radiologically inconspicuous regions of the prostate. We aimed to analyze histomorphological findings on mpMRI lesions highly suspicious for CaP classified as PI-RADS 4 or PI-RADS 5 (Prostate Imaging - Recording and Data System) but cancer-negative in the biopsy of this region of interest (ROI), and to compare them with findings in radiologically inconspicuous regions.

MATERIALS AND METHODS

We re-evaluated prostate biopsies from 57 patients who underwent TB in combination with systematic standard biopsy (SB) from June 2017 to July 2018 at the University Hospital Schleswig Holstein Campus Luebeck. Out of 143 ROIs, 34 PI-RADS 4/5 cancer-negative lesions were identified and subjected to comprehensive histomorphological reevaluation. Contralateral cancer-negative SBs were used as control. Chi-square test was used for statistical analysis.

RESULTS

The frequency of histomorphological alterations including stromal, glandular, vascular, and inflammatory alterations were 97% and 79.2% in prostatic tissues from cancer-negative TBs and SBs, respectively. Stromal, glandular, and inflammatory alterations were present in the majority of biopsies from both TBs and SBs. Statistical analysis revealed no significant difference between TBs and SBs with regard to stromal, glandular, and inflammatory alterations. However, vascular abnormalities were exclusively detected in TBs (18.2%).

CONCLUSION

The frequency of histomorphological alterations is slightly higher in prostate tissues from TBs compared to SB. Only vascular alterations seem to be distinct for TBs. However, it has to be assumed that additional factors influence the false-negative rate of mpMRI/ultrasound fusion-guided TB.

Role of MRI in Staging of Penile Cancer

Penile cancer is one of the male-specific cancers. Accurate pretreatment staging is crucial due to a plethora of treatment options currently available. The 8^th edition American Joint Committee on Cancer-Tumor Node and Metastasis (AJCC-TNM) revised the staging for penile cancers, with invasion of corpora cavernosa upstaged from T2 to T3 and invasion of urethra downstaged from T3 to being not separately relevant. With this revision, MRI is more relevant in local staging because MRI is accurate in identifying invasion of corpora cavernosa, while the accuracy is lower for detection of urethral involvement. The recent European Urology Association (EAU) guidelines recommend MRI to exclude invasion of the corpora cavernosa, especially if penis preservation is planned. Identification of satellite lesions and measurement of residual-penile-length help in surgical planning. When nonsurgical treatment modalities of the primary tumor are being considered, accurate local staging helps in decision-making regarding upfront inguinal lymph node dissection as against surveillance. MRI helps in detection and extent of inguinal and pelvic lymphadenopathy and is superior to clinical palpation, which continues to be the current approach recommended by National Comprehensive Cancer Network (NCCN) treatment guidelines. MRI helps the detection of "bulky" lymph nodes that warrant neoadjuvant chemotherapy and potentially identify extranodal extension. However, tumor involvement in small lymph nodes and differentiation of reactive vs. malignant lymphadenopathy in large lymph nodes continue to be challenging and the utilization of alternative contrast agents (superparamagnetic iron oxide), positron emission tomography (PET)-MRI along with texture analysis is promising. In locally recurrent tumors, MRI is invaluable in identification of deep invasion, which forms the basis of treatment. Multiparametric MRI, especially diffusion-weighted-imaging, may allow for quantitative noninvasive assessment of tumor grade and histologic subtyping to avoid biopsy undersampling. Further research is required for incorporation of MRI with deep learning and artificial intelligence algorithms for effective staging in penile cancer. Level of Evidence: 5 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2020;51:1612-1629.

A Hybrid End-to-End Approach Integrating Conditional Random Fields into CNNs for Prostate Cancer Detection on MRI

Prostate Cancer (PCa) is the most common oncological disease in Western men. Even though a growing effort has been carried out by the scientific community in recent years, accurate and reliable automated PCa detection methods on multiparametric Magnetic Resonance Imaging (mpMRI) are still a compelling issue. In this work, a Deep Neural Network architecture is developed for the task of classifying clinically significant PCa on non-contrast-enhanced MR images. In particular, we propose the use of Conditional Random Fields as a Recurrent Neural Network (CRF-RNN) to enhance the classification performance of XmasNet, a Convolutional Neural Network (CNN) architecture specifically tailored to the PROSTATEx17 Challenge. The devised approach builds a hybrid end-to-end trainable network, CRF-XmasNet, composed of an initial CNN component performing feature extraction and a CRF-based probabilistic graphical model component for structured prediction, without the need for two separate training procedures. Experimental results show the suitability of this method in terms of classification accuracy and training time, even though the high-variability of the observed results must be reduced before transferring the resulting architecture to a clinical environment. Interestingly, the use of CRFs as a separate postprocessing method achieves significantly lower performance with respect to the proposed hybrid end-to-end approach. The proposed hybrid end-to-end CRF-RNN approach yields excellent peak performance for all the CNN architectures taken into account, but it shows a high-variability, thus requiring future investigation on the integration of CRFs into a CNN.

PEG-coated and Gd-loaded fluorescent silica nanoparticles for targeted prostate cancer magnetic resonance imaging and fluorescence imaging

Background: Multimodal imaging probes have become a powerful tool for improving detection sensitivity and accuracy, which are important in disease diagnosis and treatment.

Methods: In this study, novel bifunctional magnetic resonance imaging (MRI)/fluorescence probes were prepared by loading gadodiamide into fluorescent silica nanoparticles (NPs) (Gd@Cy5.5@SiO₂-PEG-Ab NPs) for targeting of prostate cancer (PCa). The physicochemical characteristics, biosafety and PCa cell targeting ability of the Gd@Cy5.5@SiO₂-PEG-Ab NPs were studied in vitro and in vivo.

Results: The Gd@Cy5.5@SiO₂-PEG-Ab NPs had a spherical morphology with a relatively uniform size distribution and demonstrated high efficiency for Gd loading. In vitro and in vivo cell-targeting experiments demonstrated a high potential for the synthesized NPs to target prostate-specific membrane antigen (PSMA) receptor-positive PCa cells, enabling MRI and fluorescence imaging. In vitro cytotoxicity assays and in vivo hematological and pathological assays showed that the prepared NPs exhibited good biological safety.

Conclusion: Our study demonstrates that the synthesized Gd@Cy5.5@SiO₂-PEG-Ab NPs have great potential as MRI/fluorescence contrast agents for specific identification of PSMA receptor-positive PCa cells.

Effects of the addition of quantitative apparent diffusion coefficient data on the diagnostic performance of the PI-RADS v2 scoring system to detect clinically significant prostate cancer

PURPOSE

To evaluate the impact of the addition of quantitative apparent diffusion coefficient (ADC) data into the diagnostic performance of the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) scoring system to predict clinically significant prostate cancer (CSPCa).

METHODS

We retrospectively included 91 consecutive patients who underwent prostate multiparametric magnetic resonance imaging (mp-MRI) and histopathological evaluation. Mp-MRI images were reported by the PI-RADSv2 scoring system and patients were divided into groups considering the likelihood of CSPCa. ADC value and ratio were obtained. Findings were correlated with histopathological data.

RESULTS

CSPCa was found in 41.8% of cases (n = 38). PI-RADSv2 score 3-5 yielded a sensitivity of 97.4% (95% confidence intervals 86.5-99.5), a specificity of 50.9% (37.9-63.9), and AUC of 0.74 (0.67-0.81) to predict CSPCa. ADC value < 750 µm²/s and an ADC ratio < 0.62 were the most accurate thresholds for differentiation of CSPCa, with AUC of 0.81 and 0.76, respectively. Combined PI-RADSv2 score 3-5 and ADC value < 750 µm²/s yielded a specificity of 84.9 (72.9-92.2), sensitivity of 70.3 (54.2-82.5), and AUC of 0.77 (0.68-0.86). Combined PI-RADSv2 score 3-5 and ADC ratio < 0.62 yielded a specificity of 86.5 (74.7-93.3), sensitivity of was 64.9 (48.8-78.2), and AUC of 0.75 (0.66-0.84).

CONCLUSION

Quantitative ADC data might not be beneficial to be used routinely in mp-MR imaging as criteria to detect clinically significant lesions due to the reduced sensitivity. Instead, when prostate lesions present a PI-RADSv2 score ≥ 3, additional quantitative ADC criteria can be helpful to increase the PI-RADS score specificity.

Update on Gadolinium-Based Contrast Agent-Enhanced Imaging in the Genitourinary System

OBJECTIVE. The purpose of this article is to review gadolinium-based contrast agent (GBCA)-enhanced MRI applications in the genitourinary system. CONCLUSION. Nephrogenic systemic fibrosis is rare or nonexistent with standard dosing of group II GBCAs. Gadolinium retention, cost, and examination times are emerging considerations affecting GBCA use. GBCA is unnecessary to diagnose adrenal adenomas, simple cysts, and some Bosniak category II cysts; however, it is required to determine solid or septal renal mass enhancement. Biparametric prostate MRI requires high-quality and reproducible DWI; therefore, dynamic contrast-enhanced MRI remains valuable in selected prostate MRI examinations.

Automated segmentation of prostate zonal anatomy on T2-weighted (T2W) and apparent diffusion coefficient (ADC) map MR images using U-Nets

PURPOSE

Accurate regional segmentation of the prostate boundaries on magnetic resonance (MR) images is a fundamental requirement before automated prostate cancer diagnosis can be achieved. In this paper, we describe a novel methodology to segment prostate whole gland (WG), central gland (CG), and peripheral zone (PZ), where PZ + CG = WG, from T2W and apparent diffusion coefficient (ADC) map prostate MR images.

METHODS

We designed two similar models each made up of two U-Nets to delineate the WG, CG, and PZ from T2W and ADC map MR images, separately. The U-Net, which is a modified version of a fully convolutional neural network, includes contracting and expanding paths with convolutional, pooling, and upsampling layers. Pooling and upsampling layers help to capture and localize image features with a high spatial consistency. We used a dataset consisting of 225 patients (combining 153 and 72 patients with and without clinically significant prostate cancer) imaged with multiparametric MRI at 3 Tesla.

RESULTS AND CONCLUSION

Our proposed model for prostate zonal segmentation from T2W was trained and tested using 1154 and 1587 slices of 100 and 125 patients, respectively. Median of Dice similarity coefficient (DSC) on test dataset for prostate WG, CG, and PZ were 95.33 ± 7.77%, 93.75 ± 8.91%, and 86.78 ± 3.72%, respectively. Designed model for regional prostate delineation from ADC map images was trained and validated using 812 and 917 slices from 100 and 125 patients. This model yielded a median DSC of 92.09 ± 8.89%, 89.89 ± 10.69%, and 86.1 ± 9.56% for prostate WG, CG, and PZ on test samples, respectively. Further investigation indicated that the proposed algorithm reported high DSC for prostate WG segmentation from both T2W and ADC map MR images irrespective of WG size. In addition, segmentation accuracy in terms of DSC does not significantly vary among patients with or without significant tumors.

SIGNIFICANCE

We describe a method for automated prostate zonal segmentation using T2W and ADC map MR images independent of prostate size and the presence or absence of tumor. Our results are important in terms of clinical perspective as fully automated methods for ADC map images, which are considered as one of the most important sequences for prostate cancer detection in the PZ and CG, have not been reported previously.

Characteristics of missed prostate cancer lesions on 3T multiparametric-MRI in 518 patients: based on PI-RADSv2 and using whole-mount histopathology reference

PURPOSE

To determine the characteristics of missed prostate cancer (PCa) lesions on 3T multiparametric-MRI (mpMRI) based on PI-RADSv2 with whole-mount histopathology (WMHP) correlation.

MATERIALS AND METHODS

This IRB-approved, HIPAA-compliant study, included 614 consecutive men with 3T mpMRI prior to prostatectomy at a single tertiary center between 12/2009 and 4/2017. Clinical, mpMRI, and pathologic features were obtained. PI-RADSv2-based MRI detected lesions were matched with previously finalized WMHP by a genitourinary (GU) radiologist and a GU pathologist. Patients with no mpMRI detected PCa lesion, but with at least one lesion ≥ 1 cm on WMHP, were reviewed retrospectively and assigned a PI-RADSv2 score. Tumor characteristics were compared between missed and detected lesions.

RESULT

The final cohort included 518 patients with 1085 WMHP lesions. 51.9% (563/1085) of lesions were missed on 3T mpMRI. 71.4% (402/563), 21.7% (122/563), 4.4% (25/563), and 2.5% (14/563) of the missed lesions were Gleason scores (GS) 3 + 3, 3 + 4, 4 + 3, and 8 - 10, respectively. Missed PCa lesions had significantly lower proportion of GS ≥ 7 (p < 0.001) and smaller size for overall (p < 0.001) and index subcohorts (p < 0.001), as compared to detected lesions. 34.5% (194) of overall and 71.2% (79) index missed lesions were larger than 1 cm. In 13.7% (71/518) of patients without MR detected PCa, 149 lesions were detected on WMHP, with 70 (47%) lesions ≥ 1 cm. In retrospective review of these lesions, 42.9% (30), 18.6% (13), 21.5% (15), 10% (7), and 7% (5) were PI-RADSv2 1, 2, 3, 4, and 5, respectively.

CONCLUSION

3T mpMRI has an excellent per patients diagnostic performance for PCa and majority of missed lesions are clinically nonsignificant.

Comparison of percentage free PSA, MRI and GaPSMA PET scan for diagnosing cancer prostate in men with PSA between 4 and 20 ng/ml

Introduction:

We compared the diagnostic accuracy of percentage free prostate-specific antigen (PSA), multiparametric magnetic resonance imaging (mpMRI), and gallium-68 prostate-specific membrane antigen positron emission tomography (Ga-PSMA PET) to detect cancer prostate in men with PSA between 4 and 20 ng/ml in prebiopsy settings.

Materials and Methods:

This prospective study evaluated men with PSA values between 4 and 20 ng/ml, and all patients underwent percentage free PSA estimation, mpMRI, and Ga-PSMA PET scan, followed by cognitive fusion/registration biopsy along with systematic 12-core biopsy to detect cancer prostate. The diagnostic accuracy of percentage free PSA, mpMRI, and Ga-PSMA PET scan was compared with results of cognitive fusion/registration biopsy.

Results:

A total of 15 patients were included, of which 11 had an identifiable lesion on imaging and 9 had malignancy on the final histopathology report. The sensitivity, specificity, positive predictive value, negative predictive value (NPV), and diagnostic accuracy of mpMRI were 62.5%, 71.4%, 71.4%, 62.5%, and 66.6%, respectively, and that of Ga-PSMA PET scan were 88.8%, 66.6%, 80%, 80%, and 80%, respectively. The sensitivity of detection of clinically significant cancers for Ga-PSMA was higher (100%) compared to MRI (33.3%). However, Ga-PSMA also detected a greater number of insignificant lesions as compared to MRI.

Conclusion:

Ga-PSMA PET scan has high NPV and accuracy in predicting presence of cancer and can also be used to direct specific biopsy cores during systematic biopsy.

Detection rate of clinically significant prostate cancer in magnetic resonance imaging and ultrasonography-fusion transperineal targeted biopsy for lesions with a prostate imaging reporting and data system version 2 score of 3-5

Objectives

To evaluate the detection rates of clinically significant prostate cancer classified according to the prostate imaging reporting and data system scoring system using magnetic resonance imaging/ultrasound rigid fusion targeted biopsy.

Methods

A total of 339 patients underwent transperineal magnetic resonance imaging/ultrasound rigid fusion targeted biopsy in our institution between January 2015 and July 2017. Patients with prostate imaging reporting and data system category 1 or 2 and those with a pre‐biopsy prostate‐specific antigen value of >30 ng/mL were excluded from this study. Finally, 310 patients were recruited.

Results

The detection rates of clinically significant prostate cancer with prostate imaging reporting and data system category 3, 4, and 5 were 1.0% (1/98), 35.1% (47/134) and 73.1% (57/78), respectively. The factors affecting the detection of clinically significant prostate cancer with prostate imaging reporting and data system categories 4 and 5 were: (i) prostate imaging reporting and data system category 5; (ii) prostate volume <40 cc; (iii) no previous biopsy; (iv) lesion located in the peripheral zone; and (v) prostate‐specific antigen density >0.35 ng/mL/mL.

Conclusions

The detection rate of clinically significant prostate cancer on magnetic resonance imaging/ultrasound rigid fusion targeted biopsy is very low in patients with prostate imaging reporting and data system category 3; therefore, patients with this classification should not undergo targeted biopsy. Prostate‐specific antigen density, prostate volume, locations of suspected cancer and history of biopsy should be considered to predict the detection rate of clinically significant prostate cancer with prostate imaging reporting and data system categories 4 and 5.

MRI in active surveillance: a critical review

INTRODUCTION

Recent technological advancements and the introduction of modern anatomical and functional sequences have led to a growing role for multiparametric magnetic resonance imaging (mpMRI) in the detection, risk assessment and monitoring of early prostate cancer. This includes men who have been diagnosed with lower-risk prostate cancer and are looking at the option of active surveillance (AS). The purpose of this paper is to review the recent evidence supporting the use of mpMRI at different time points in AS, as well as to discuss some of its potential pitfalls.

METHODS

A combination of electronic and manual searching methods were used to identify recent, important papers investigating the role of mpMRI in AS.

RESULTS

The high negative predictive value of mpMRI can be exploited for the selection of AS candidates. In addition, mpMRI can be efficiently used to detect higher risk disease in patients already on surveillance.

CONCLUSION

Although there is an ongoing debate regarding the precise nature of its optimal implementation, mpMRI is a promising risk stratification tool and should be considered for men on AS.

Quantitative evaluation of the relative apparent diffusion coefficient values on multiparametric magnetic resonance imaging to predict higher Gleason score prostate cancer

INTRODUCTION

Apparent diffusion coefficient (ADC) values on multiparametric magnetic resonance imaging (mpMRI) have been reported to correlate with high-Gleason score (GS) prostate cancer. However, the relative ADC values between tumor lesions and normal tissue have been suggested as more suitable than the absolute ADC values for evaluation of diffusion abnormalities, because absolute ADC values are susceptible to differences in scanners or scanner settings. The present study evaluated the usefulness of the relative assessment of ADC values between tumor lesions and normal tissue on preoperative mpMRI for the prediction of high-risk prostate cancer on radical prostatectomy specimens.

MATERIALS AND METHODS

A retrospective analysis of 48 men who underwent radical prostatectomy between January 2013 and December 2014 was conducted. MpMRI was performed with a 3.0-T scanner using b-values of 0 and 1500 s/mm². ADC values of the tumor (ADC_TUMOR) and normal prostate and the relative ADC tumor/normal ratio (ADC_TNR) were evaluated by two radiologists.

RESULTS

The inter-rater reliability between two radiologists for ADC_TUMOR measurement was high, with Pearson's r = 0.982. There was no difference in ADC_TUMOR between GS ≤7 and GS ≥8. In contrast, ADC_TNR was significantly lower in GS ≥8 than in GS ≤7. ROC curves of ADC_TNR to predict higher GS (≥8) showed better classification performance (AUC = 0.8243, p = .0012 by radiologist A and AUC = 0.7961, p = .0031 by radiologist B) than of ADC_TUMOR.

CONCLUSIONS

The relative assessment of ADC values between tumor lesions and normal tissue could improve the detection rate of high-risk prostate cancers.

Multiparametric magnetic resonance imaging - Transrectal ultrasound-guided cognitive fusion biopsy of the prostate: Clinically significant cancer detection rates stratified by the Prostate Imaging and Data Reporting System version 2 assessment category

INTRODUCTION

We aimed to report the clinically significant prostate cancer (PCa) detection rate in men undergoing magnetic resonance imaging-transrectal ultrasound (MRI-TRUS)-cognitive fusion (CF) targeted biopsies stratified by the Prostate Imaging and Data Reporting System (PI-RADS) version 2 (v2) scores.

METHODS

With a quality assurance waiver from the IRB, we identified a cohort of men who underwent MRI-TRUS-CF and synchronous template biopsy from 2015-2017. MRI (PI-RADS v2 score, lesion size, lesion location [peripheral or transition zone (PZ/TZ)]), and CF-TRUS biopsy (operator experience, TRUS visibility, and number of biopsies) features were extracted. The primary outcome was diagnosis of clinically significant (Gleason score ≥3+4=7 or International Society of Urological Pathology (ISUP) grade group ≥2) PCa.

RESULTS

During the study period, 131 men (with 142 PIRADS v2 score ≥3 lesions) met inclusion criteria; 98 men had previously negative template biopsy and 33 were on active surveillance for previously detected low-grade PCa. In total, 41.9% (55/131) men had clinically significant PCa - 17.6% (23/131) detected on targeted biopsy only, 8.4% (11/131) on template biopsy only, and 16.0% (21/131) on both targeted and template biopsy. Clinically significant PCa detection stratified by PI-RADS v2 scores were: 11.1% (3/27) for score 3 (indeterminate), 42.9% (24/56) for score 4 (significant cancer likely), and 35.6% (21/59) for score 5 (significant cancer very likely). Clinically significant PCa detection rates in targeted biopsies were better among PZ (41.8% [33/79]) compared to TZ (23.8% [15/63]) lesions (p=0.025) in TRUS visible lesions (p=0.033) and in the most experienced radiologists (p=0.05), with no difference by lesion size or number of additional core biopsies performed (all p>0.05).

CONCLUSIONS

Cognitive fusion MRI-TRUS-guided targeted biopsy yielded substantially lower rates of clinically significant cancer in PI-RADS v2 score 4 and 5 lesions when compared to published results using in-bore MR-guided or automated MRI-TRUS fusion guidance systems. Cancer detection was worst for TZ lesions.

Follow-up of negative MRI-targeted prostate biopsies: when are we missing cancer?

INTRODUCTION

Multiparametric magnetic resonance imaging (mpMRI) has improved clinicians' ability to detect clinically significant prostate cancer (csPCa). Combining or fusing these images with the real-time imaging of transrectal ultrasound (TRUS) allows urologists to better sample lesions with a targeted biopsy (Tbx) leading to the detection of greater rates of csPCa and decreased rates of low-risk PCa. In this review, we evaluate the technical aspects of the mpMRI-guided Tbx procedure to identify possible sources of error and provide clinical context to a negative Tbx.

METHODS

A literature search was conducted of possible reasons for false-negative TBx. This includes discussion on false-positive mpMRI findings, termed "PCa mimics," that may incorrectly suggest high likelihood of csPCa as well as errors during Tbx resulting in inexact image fusion or biopsy needle placement.

RESULTS

Despite the strong negative predictive value associated with Tbx, concerns of missed disease often remain, especially with MR-visible lesions. This raises questions about what to do next after a negative Tbx result. Potential sources of error can arise from each step in the targeted biopsy process ranging from "PCa mimics" or technical errors during mpMRI acquisition to failure to properly register MRI and TRUS images on a fusion biopsy platform to technical or anatomic limits on needle placement accuracy.

CONCLUSIONS

A better understanding of these potential pitfalls in the mpMRI-guided Tbx procedure will aid interpretation of a negative Tbx, identify areas for improving technical proficiency, and improve both physician understanding of negative Tbx and patient-management options.

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.

[Value of PI-RADS v2 scores combined with prostate specific antigen in diagnosis of peripheral zone prostate cancer: a logistic regression analysis]

OBJECTIVE

To assess the value of Prostate Imaging and Reporting and Data System: Version 2 (PI-RADS v2) combined with prostate specific antigen (PSA) in the diagnosis of peripheral zone (PZ) prostate cancer (PCa).

METHODS

The preoperative magnetic resonance imaging and PSA data were ananlyzed for 69 patients with pathologically confirmed PCa and 109 non-PCa patients. PI-RADS v2 scores (1-5) was used to evaluate the risk of PZ PCa. The total PSA (tPSA) level, free to total PSA ratio (f/t PSA), PSA density (PSAD), PZ-PSAD and PI-RADS v2 scores were compared between the PCa and non-PCa patients. Logistic regression models were established with parameters that differed significantly the two groups. The receiver opearting characteristics (ROC) curve was constructed based on the P values derived from the logical regression models and PI-RADS scores to assess the diagnostic efficiency.

RESULTS

PI-RADS v2 score, tPSA, f/t PSA, PSAD and PZ-PSAD differed significantly between the two groups (P<0.01). Four predictive multivariate models were established: Logit P=-6.825+1.024PI-RADS v2+ 0.223tPSA (A), Logit P=-4.354+1.586PI-RADS v2-12.7841f/tPSA (B), Logit P=-8.993+1.630PI-RADS v2+17.091PSAD (C), and Logit P=-9.434+1.596PI-RADS v2+10.494PZ-PSAD (D), whose area under the ROC curves was 0.908, 0.891, 0.944, and 0.961, respectively, all significantly greater than that of PI-RADS v2 score (P<0.05).

CONCLUSION

Compared with PI-RADS v2 score alone, the combination of PI-RADS v2 score and PSA in the logistic regression model can improve the diagnostic efficiency of PZ PCa and offers better confidence in the decision of biopsy in suspected cases.