MRI For Detection Of Prostate Cancer Research Articles

AI-ADC: Channel and Spatial Attention-Based Contrastive Learning to Generate ADC Maps from T2W MRI for Prostate Cancer Detection.

Apparent Diffusion Coefficient (ADC) maps in prostate MRI can reveal tumor characteristics, but their accuracy can be compromised by artifacts related with patient motion or rectal gas associated distortions. To address these challenges, we propose a novel approach that utilizes a Generative Adversarial Network to synthesize ADC maps from T2-weighted magnetic resonance images (T2W MRI). By leveraging contrastive learning, our model accurately maps axial T2W MRI to ADC maps within the cropped region of the prostate organ boundary, capturing subtle variations and intricate structural details by learning similar and dissimilar pairs from two imaging modalities. We trained our model on a comprehensive dataset of unpaired T2-weighted images and ADC maps from 506 patients. In evaluating our model, named AI-ADC, we compared it against three state-of-the-art methods: CycleGAN, CUT, and StyTr2. Our model demonstrated a higher mean Structural Similarity Index (SSIM) of 0.863 on a test dataset of 3240 2D MRI slices from 195 patients, compared to values of 0.855, 0.797, and 0.824 for CycleGAN, CUT, and StyTr2, respectively. Similarly, our model achieved a significantly lower Fréchet Inception Distance (FID) value of 31.992, compared to values of 43.458, 179.983, and 58.784 for the other three models, indicating its superior performance in generating ADC maps. Furthermore, we evaluated our model on 147 patients from the publicly available ProstateX dataset, where it demonstrated a higher SSIM of 0.647 and a lower FID of 113.876 compared to the other three models. These results highlight the efficacy of our proposed model in generating ADC maps from T2W MRI, showcasing its potential for enhancing clinical diagnostics and radiological workflows.

Value of T2 Mapping MRI for Prostate Cancer Detection and Classification

ROI Measurements of benign tissue in the peripheral zone (PZ; purple ROI) and transition zone (TZ; orange ROI), and PCA (red ROI). Quantitative T2 map (A), T2 TSE (B), and calculatedadc map of RS-DWI (C). On Radical prostatectomy (RPE), an ISUP grade 5 PCA was confirmed. by Maximilian Klingebiel et al. (413–422)

52 - Value of urinary biomarker-based risk score and multiparametric MRI for prostate cancer detection in biopsy-naive patients: A randomized clinical trial.

52 - Value of urinary biomarker-based risk score and multiparametric MRI for prostate cancer detection in biopsy-naive patients: A randomized clinical trial.

Multiparametric MRI for Prostate Cancer Detection: New Insights into the Combined Use of a Radiomic Approach with Advanced Acquisition Protocol.

Prostate cancer (PCa) is a disease affecting an increasing number of men worldwide. Several efforts have been made to identify imaging biomarkers to non-invasively detect and characterize PCa, with substantial improvements thanks to multiparametric Magnetic Resonance Imaging (mpMRI). In recent years, diffusion kurtosis imaging (DKI) was proposed to be directly related to tissue physiological and pathological characteristic, while the radiomic approach was proven to be a key method to study cancer imaging phenotypes. Our aim was to compare a standard radiomic model for PCa detection, built using T2-weighted (T2W) and Apparent Diffusion Coefficient (ADC), with an advanced one, including DKI and quantitative Dynamic Contrast Enhanced (DCE), while also evaluating differences in prediction performance when using 2D or 3D lesion segmentation. The obtained results in terms of diagnostic accuracy were high for all of the performed comparisons, reaching values up to 0.99 for the area under a receiver operating characteristic curve (AUC), and 0.98 for both sensitivity and specificity. In comparison, the radiomic model based on standard features led to prediction performances higher than those of the advanced model, while greater accuracy was achieved by the model extracted from 3D segmentation. These results provide new insights into active topics of discussion, such as choosing the most convenient acquisition protocol and the most appropriate postprocessing pipeline to accurately detect and characterize PCa.

Value of reduced field-of-view diffusion-weighted MRI for prostate cancer detection in the TRUS-guided transperineal prostate biopsy

Objective To observe the value of reduced field-of-view diffusion-weighted MRI (rFOV DWI) for prostate cancer (PCa) detection in the TRUS-guided transperineal prostate biopsy. Methods A total of 54 patients with suspected PCa underwent rFOV DWI before TRUS-guided prostate biopsy were prospectively enrolled in this study. All rFOV DWI data were carried out by two independent radiologists using prostate imaging-reporting and data system (PI-RADS) assessment category, and systemic 10-core biopsy (SB) combined with rFOV DWI targeted biopsy (rFOV DWI-TB) were taken. According to histopathology results, the performance of rFOV DWI was analysed. Additionally, the detection rate of PCa and the positive rate of punctures of SB, rFOV DWI-TB and SB combined with rFOV DWI-TB were compared. Results Overall, 26 of the 54 patients (48.15%) had histologically confirmed PCa. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for detecting PCa with rFOV DWI was 80.77%, 89.29%, 87.5% and 83.33%, respectively. The ROC curve analysis revealed the AUC was 0.916. Additionally, the sensitivity for detecting clinically significant PCa with rFOV DWI was 95%. The PCa detection rate of SB, rFOV DWI-TB, and combination of SB and rFOV DWI-TB was 37.04%, 42.59% and 48.15%, respectively. The detection rate for combination of SB and rFOV DWI-TB was significantly higher than that of SB only (P=0.031). Additionally, the detection rate for rFOV DWI-TB cores (78.33%) was significantly better than for SB cores (15.5%)(χ2=124.377, P=0.000). Conclusions rFOV DWI may be useful for providing more information of PCa lesions in targeted prostate biopsy, and has potential value in clinically significant PCa detecting. Key words: Prostatic Neoplasms; Magnetic Resonance Imaging; Biopsy, Needle; Ultrasonography

EP187 - Initial Results Comparing Micro-Ultrasound with MRI for Prostate Cancer Detection

EP187 - Initial Results Comparing Micro-Ultrasound with MRI for Prostate Cancer Detection

A urinary biomarker‐based risk score correlates with multiparametric MRI for prostate cancer detection

Prostate cancer (PCa) diagnostics would greatly benefit from more accurate, non-invasive techniques for the detection of clinically significant disease, leading to a reduction of over-diagnosis and over-treatment. The aim of this study was to determine the association between a novel urinary biomarker-based risk score (SelectMDx), multiparametric MRI (mpMRI) outcomes, and biopsy results for PCa detection. This retrospective observational study used data from the validation study of the SelectMDx score, in which urine was collected after digital rectal examination from men undergoing prostate biopsies. A subset of these patients also underwent a mpMRI scan of the prostate. The indications for performing mpMRI were based on persistent clinical suspicion of PCa or local staging after PCa was found upon biopsy. All mpMRI images were centrally reviewed in 2016 by an experienced radiologist blinded for the urine test results and biopsy outcome. The PI-RADS version 2 was used. In total, 172 patients were included for analysis. Hundred (58%) patients had PCa detected upon prostate biopsy, of which 52 (52%) had high-grade disease correlated with a significantly higher SelectMDx score (P < 0.01). The median SelectMDx score was significantly higher in patients with a suspicious significant lesion on mpMRI compared to no suspicion of significant PCa (P < 0.01). For the prediction of mpMRI outcome, the area-under-the-curve of SelectMDx was 0.83 compared to 0.66 for PSA and 0.65 for PCA3. There was a positive association between SelectMDx score and the final PI-RADS grade. There was a statistically significant difference in SelectMDx score between PI-RADS 3 and 4 (P < 0.01) and between PI-RADS 4 and 5 (P < 0.01). The novel urinary biomarker-based SelectMDx score is a promising tool in PCa detection. This study showed promising results regarding the correlation between the SelectMDx score and mpMRI outcomes, outperforming PCA3. Our results suggest that this risk score could guide clinicians in identifying patients at risk for significant PCa and selecting patients for further radiological diagnostics to reduce unnecessary procedures.

Editorial Comment

Multiple studies have demonstrated that multiparametric magnetic resonance imaging (mpMRI) can significantly improve the detection of prostate cancers belonging to Grade Groups ≥2 when compared with systematic transrectal ultrasound-guided biopsies. 1 de Rooij M. Hamoen E.H. Fütterer J.J. Barentsz J.O. Rovers M.M. Accuracy of multiparametric MRI for prostate cancer detection: a meta-analysis. AJR Am J Roentgenol. 2014; 202: 343-351 Crossref PubMed Scopus (346) Google Scholar The ability of mpMRI to predict a negative systematic biopsy result has also been demonstrated, although to a lesser extent; this is considered one of the main potential benefits of mpMRI, as it could help reduce the number of unnecessary biopsies, cases of overtreatment, and any associated side effects. 2 Wysock J.S. Mendhiratta N. Zattoni F. et al. Predictive value of negative 3T multiparametric magnetic resonance imaging of the prostate on 12-core biopsy results. BJU Int. 2016; 118: 515-520 Crossref PubMed Scopus (98) Google Scholar , 3 Wang R.S. Kim E.H. Vetter J.M. et al. Determination of the role of negative magnetic resonance imaging of the prostate in clinical practice: is biopsy still necessary?. Urology. 2016; (S0090-4295(16)30815-9[pii]; Epub ahead of print)https://doi.org/10.1016/j.urology.2016.10.040 Abstract Full Text Full Text PDF Scopus (30) Google Scholar

Accuracy of high b-value diffusion-weighted MRI for prostate cancer detection: a meta-analysis.

Background The diagnostic accuracy of diffusion-weighted imaging (DWI) to detect prostate cancer is well-established. DWI provides visual as well as quantitative means of detecting tumor, the apparent diffusion coefficient (ADC). Recently higher b-values have been used to improve DWI's diagnostic performance. Purpose To determine the diagnostic performance of high b-value DWI at detecting prostate cancer and whether quantifying ADC improves accuracy. Material and Methods A comprehensive literature search of published and unpublished databases was performed. Eligible studies had histopathologically proven prostate cancer, DWI sequences using b-values ≥ 1000 s/mm2, less than ten patients, and data for creating a 2 × 2 table. Study quality was assessed with QUADAS-2 (Quality Assessment of diagnostic Accuracy Studies). Sensitivity and specificity were calculated and tests for statistical heterogeneity and threshold effect performed. Results were plotted on a summary receiver operating characteristic curve (sROC) and the area under the curve (AUC) determined the diagnostic performance of high b-value DWI. Results Ten studies met eligibility criteria with 13 subsets of data available for analysis, including 522 patients. Pooled sensitivity and specificity were 0.59 (95% confidence interval [CI], 0.57-0.61) and 0.92 (95% CI, 0.91-0.92), respectively, and the sROC AUC was 0.92. Subgroup analysis showed a statistically significant ( P = 0.03) improvement in accuracy when using tumor visual assessment rather than ADC. Conclusion High b-value DWI gives good diagnostic performance for prostate cancer detection and visual assessment of tumor diffusion is significantly more accurate than ROI measurements of ADC.

MP33-17 POTENTIAL ROLE OF A NOVEL URINARY BIOMARKER-BASED RISK SCORE TO SELECT PATIENTS FOR MULTIPARAMETRIC MRI FOR PROSTATE CANCER DETECTION.

You have accessJournal of UrologyProstate Cancer: Detection & Screening III1 Apr 2017MP33-17 POTENTIAL ROLE OF A NOVEL URINARY BIOMARKER-BASED RISK SCORE TO SELECT PATIENTS FOR MULTIPARAMETRIC MRI FOR PROSTATE CANCER DETECTION. Rianne J Hendriks, Leander Van Neste, Mulders Marloes, Jack A Schalken, and Inge M Van Oort Rianne J HendriksRianne J Hendriks More articles by this author , Leander Van NesteLeander Van Neste More articles by this author , Mulders MarloesMulders Marloes More articles by this author , Jack A SchalkenJack A Schalken More articles by this author , and Inge M Van OortInge M Van Oort More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2017.02.1013AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Prostate cancer (PCa) diagnostics would greatly benefit from more accurate, non-invasive techniques for the detection of clinically significant disease, leading to a reduction of over-diagnosis and over-treatment. Multiparametric MRI (mpMRI) is being used increasingly and has proven to be a valuable addition to the PCa diagnostic pathway. A novel biomarker-based risk score (SelectMDx) assessing urinary HOXC6 and DLX1 mRNA expression levels combined with traditional clinical risk factors, was recently developed to predict high-grade PCa (Gleason score >/=7) upon prostate biopsy and to reduce the number of unnecessary biopsies. The aim of this study was to investigate the correlation between the risk score and mpMRI outcomes. METHODS The patients in this retrospective observational cohort were previously included in the validation study of the SelectMDx risk score, in which urine was collected after digital rectal examination (DRE) from men undergoing prostate biopsies based on an elevated serum PSA level (>/=3.0 ng/ml) and/or suspicious DRE. A subset of patients underwent an mpMRI after prostate biopsies were performed (n=174). The indications for performing MRI were based on persistent clinical suspicion of PCa after negative prostate biopsies or staging after PCa was found upon biopsy. RESULTS 102 of 174 patients (59%) had PCa detected upon prostate biopsy, of which 54 (53%) had high-grade disease and a significantly higher SelectMDx risk score (p<0.001). The median SelectMDx risk score was also significantly higher in patients who had a suspicious lesion on MRI (p<0.001). For 81 mpMRI's the PIRADS classification was reported and there was a positive correlation observed between the risk score and the PIRADS classification (Figure 1). A Kruskal-Wallis test indicated a statistically significant difference in SelectMDx risk scores between the different PIRADS groups (p<0.001). CONCLUSIONS The novel urinary biomarker-based risk score is a promising tool in PCa detection. This study showed promising results regarding the correlation between the SelectMDx risk score with MRI outcomes. This risk score could potentially guide clinicians in selecting patients at risk for significant PCa for mpMRI. © 2017FiguresReferencesRelatedDetails Volume 197Issue 4SApril 2017Page: e424 Advertisement Copyright & Permissions© 2017MetricsAuthor Information Rianne J Hendriks More articles by this author Leander Van Neste More articles by this author Mulders Marloes More articles by this author Jack A Schalken More articles by this author Inge M Van Oort More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

Accuracy of high b-value diffusion-weighted MRI for prostate cancer detection: a meta-analysis

Accuracy of high b-value diffusion-weighted MRI for prostate cancer detection: a meta-analysis

Multiparametric MRI for prostate cancer detection: Preliminary results on quantitative analysis of dynamic contrast enhanced imaging, diffusion-weighted imaging and spectroscopy imaging

IntroductionEarly promising data suggest that combined use of both morphological and functional MRI (multi-parametric MR, mpMRI) including MRSI, DWI and DCE may be of additional value for prostate cancer localization and its local staging. The objective of this paper is to evaluate the diagnostic performance of mpMRI in the detection of prostate cancer. MethodsThirty-one consecutive male patients were screened to be enrolled in a single center prospective observational study. All eligible patients underwent multi-parametric MRI and TRUS (Trans Rectal Ultra Sound) guided prostate biopsies. A register, approved by the Institutional Ethics Committee, included patients enrolled in this study. All patients who decided to undergo the MRI examination signed an explicit informed consensus. MRI data were aligned on a common spatial grid and several functional parameters (perfusion, diffusion and metabolic parameters) were computed. Statistical analysis was conducted in order to compare mpMRI with biopsy-based analysis. ResultsStatistically significant differences between median values in high Gleason score (≥5) and low Gleason score (<5) to Wilcox on rank sum test were obtained for MRSI parameters and for plasma fraction (Tofts model) of DCE-MRI. The area under curve obtained with ROC analysis showed that the best-performing single-parameter was vp (plasma fraction of Tofts model), while the best parameters combination to discriminate the area with high Gleason score were (Cho+Cr)/Cit and Cho+Cr. Linear Discrimination Analysis showed that the best results were obtained considering the linear combination of all MRSI parameters and the linear combination of all features (perfusion, diffusion and metabolic parameters). ConclusionsIn conclusion, our findings showed that by combining morphological MRI, DWI, DCE-MRI and MRSI, an increase in sensitivity and specificity correlated to biopsy Gleason grade could be obtained. Furthermore, morphological and functional MRI could have a diagnostic role in patients with prostate cancer, identifying those patients who will have a negative work-up and those patients at high risk for a high Gleason score cancer of the prostate.

Accuracy of Multiparametric MRI for Prostate Cancer Detection: A Meta-Analysis

The purpose of this diagnostic meta-analysis was to determine the diagnostic accuracy of multiparametric MRI for prostate cancer detection using anatomic T2-weighted imaging combined with two functional techniques: diffusion-weighted imaging (DWI) and dynamic contrast-enhanced MRI (DCE-MRI). We searched electronic databases, including MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials (CENTRAL) up to February 3, 2012. We included diagnostic accuracy studies using a combination of T2-weighted imaging, DWI, and DCE-MRI to detect prostate cancer with histopathologic data from prostatectomy or biopsy as the reference standard. The methodologic quality was assessed with version 2 of the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool by two independent reviewers. Sensitivity and specificity of all studies were calculated from 2 × 2 tables, and the results were plotted in a hierarchic summary receiver operating characteristic plot. Seven studies that met the inclusion criteria (526 patients) could be analyzed. The pooled data showed a specificity of 0.88 (95% CI, 0.82-0.92) and sensitivity of 0.74 (95% CI, 0.66-0.81) for prostate cancer detection, with negative predictive values (NPVs) ranging from 0.65 to 0.94. Subgroup analyses showed no significant difference between the subgroups. The high specificity with variable but high NPVs and sensitivities implies a potential role for multiparametric MRI in detecting prostate cancer.

Multiparametric MRI for prostate cancer detection: performance in patients with prostate-specific antigen values between 2.5 and 10 ng/mL.

To assess the diagnostic performance of multiparametric MRI (mpMRI), in the detection of prostate cancer, including morphologic sequences (mMRI), diffusion-weighted imaging (DWI), and MR spectroscopy (MRS). Combined morphological and functional MRI scoring systems was used for urological–radiological work-up of patients with a prostate-specific antigen (PSA) value ≤ 10 ng/mL. The study included 136 of 200 consecutive patients with PSA values between 2.5 and 4 ng/mL and an abnormal digital rectal examination (DRE), or patients with PSA values between 4 and 10 ng/mL, independently from DRE. Each patient provided informed consent to undergo at serum free/total PSA ratio (f/t PSA) assay, mMRI, MRS, DWI, and transrectal ultrasonography (TRUS) biopsy. The MRI datasets were scored singularly; then mMRI and DWI, mMRI and MRS data were combined in a coupled score, and finally mMRI, DWI, and MRS data were combined in a single score (cMRI score). Scores were correlated to negative biopsies and significant/insignificant Gleason score biopsies. Receiver-operator-characteristic curve and McNemar tests were performed. Cancer was diagnosed in 18% of patients. The cMRI score showed: (i) the highest sensitivity (0.84) and negative predictive value (0.93); (ii) a significant correlation with Gleason score; and (iii) a statistically different median value between significant and insignificant Gleason score. The cMRI score could identify patients with a PSA≤10 ng/mL who will have a negative work-up, for its high negative predictive value, and patients at high risk for significant prostate cancer because of its correlation with the Gleason score

Scoring systems used for the interpretation and reporting of multiparametric MRI for prostate cancer detection, localization, and characterization: could standardization lead to improved utilization of imaging within the diagnostic pathway?

Multiparametric magnetic resonance imaging (mpMRI) is increasingly being used earlier in the prostate cancer diagnostic pathway in order to detect and localize disease. Its results can be used to help decide on the indication, type, and localization of a prostate biopsy for cancer diagnosis. In addition, mpMRI has the potential to contribute information on the characterization, or aggressiveness, of detected cancers including tumor progression over time. There is considerable variation in the way results of different MRI sequences are reported. We conducted a review of scoring systems that have been used in the detection and characterization of prostate cancer. This revealed that existing scoring and reporting systems differ in purpose, scale, and range. We evaluate these differences in this review. This first step in collating all methods of scoring and reporting mpMRI will ultimately lead to consensus approaches to develop a standardized reporting scheme that can be widely adopted and validated to ensure comparability of research outputs and optimal clinical practice.

Detectability of low and intermediate or high risk prostate cancer with combined T2-weighted and diffusion-weighted MRI

To evaluate the incremental value of diffusion-weighted imaging (DWI) in combination with T2-weighted imaging to detect low (Gleason score, ≤ 6) and intermediate or high risk (Gleason score, ≥ 7) prostate cancer. Fifty-one patients who underwent MRI before prostatectomy were evaluated. Two readers independently scored the probability of tumour in eight regions of prostate on T2-weighted images (T2WI) and T2WI combined with apparent diffusion coefficient (ADC) maps. Data were divided into two groups--low risk and intermediate or high risk prostate cancer--and correlated with histopathological results. Diagnostic performance parameters, areas under the receiver-operating characteristic curve (AUCs) and interreader agreement were calculated. For both readers, AUCs of combined T2WI and ADC maps were greater than those of T2WI in intermediate or high risk (reader 1, 0.887 vs. 0.859; reader 2, 0.732 vs 0.662, P < 0.05) prostate cancers, but not in low risk (reader 1, 0.719 vs 0.725; reader 2, 0.685 vs. 0.680, P > 0.05) prostate cancers. Weighted κ value of combined T2WI and ADC maps was 0.689. The addition of DWI to T2-weighted imaging improves the accuracy of detecting intermediate or high risk prostate cancers, but not for low risk prostate cancer detection. • Gleason scores influence diagnostic performance of MRI for prostate cancer detection. • Addition of DWI does not improve low risk prostate cancer detection. • Combined T2WI and DWI may help select intermediate or high risk patients.

The value of diffusion-weighted MRI for prostate cancer detection and localization

The aim of this study was to evaluate the role of prebiopsy T2-weighted imaging (T2WI), quantitative diffusion-weighted imaging (DWI), and the combination of these magnetic resonance (MR) techniques (T2WI+DWI) in the detection and localization of peripheral zone prostate cancer. T2WI and DWI (b value = 800 s/mm2) with an endorectal coil at 1.5 T were performed prospectively in 43 consecutive male patients with suspicion of prostate cancer before a systematic 12-core prostate biopsy. The peripheral zone of the prostate was evaluated after dividing it into sextants (n = 258). Minimum apparent diffusion coefficient (ADC) values of each sextant in the peripheral zone were measured. Two core biopsies were obtained from each sextant under transrectal ultrasound guidance. The mean minimum ADC values of the malignant sextants were significantly lower than that of noncancerous tissue, with a significant negative correlation between the ADC value and the Gleason score. The sensitivity, specificity, and area under the receiver operating characteristic curve for the detection and localization of prostate cancer within the peripheral zone were 71%, 77%, and 0.741 for T2WI alone; 84%, 82%, and 0.830 for quantitative DWI alone; and 81%, 92%, and 0.863 for T2WI+DWI, respectively. The use of quantitative DWI, alone or combined with T2WI, improved diagnostic performance in prostate cancer detection and localization compared with T2WI alone (P = 0.020 and P = 0.001, respectively). Prebiopsy DWI is valuable in detecting, localizing, and grading prostate cancer within the peripheral zone, and the lowest ADC values can indicate the regions to be biopsied.