Dataset Information

Predicting Prostate Biopsy Outcomes: A Preliminary Investigation on Screening with Ultrahigh B-Value Diffusion-Weighted Imaging as an Innovative Diagnostic Biomarker.

ABSTRACT:

Background

Routine screening of prostate specific antigen (PSA) is no longer recommended because of a high rate of over-diagnosis of prostate cancer (PCa).

Objective

To evaluate the efficacy of diffusion-weighted magnetic resonance imaging (DW-MRI) for PCa detection, and to explore the clinical utility of ultrahigh b-value DW-MRI in predicting prostate biopsy outcomes.

Methodology

73 male patients were selected for the study. They underwent 3T MRI using T2WI conventional DW-MRI with b-value 1000 s/mm2, and ultrahigh b-value DW-MRI with b-values of 2000 s/mm2 and 3000 s/mm2. Two radiologists evaluated individual prostate gland images on a 5-point rating scale using PI-RADS, for the purpose of region-specific comparisons among modalities. Sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV) and likelihood ratios (LR) were investigated for each MRI modality. The area under the receiver operating characteristic (ROC) curve (AUC) was also calculated.

Results

Results showed the improved diagnostic value of ultrahigh b-value DWI-MRI for detection of PCa when compared to other b values and conventional MRI protocols. Sensitivity values for 3000 s/mm2 in both peripheral zone (PZ) and transition zone (TZ) were significantly higher than those observed with conventional DW-MRI-Specificity values for 3000 s/mm2 in the TZ were significantly higher than other b-value images, whereas specificity values using 3000 s/mm2 in the PZ were not significantly higher than 2000 s/mm2 images. PPV and NPV between 3000 s/mm2 and the other three modalities were significantly higher for both PZ and TZ images. The PLRs and NLRs of b-value 3000 s/mm2 DW-MRI in the PZ and TZ were also recorded. ROC analysis showed greater AUCs for the b value 3000 s/mm2 DWI than for the other three modalities.

Conclusions

DW-MRI with a b-value of 3000 s/mm2 was found to be the most accurate and reliable MRI modality for PCa tumor detection and localization, particularly for TZ lesion discrimination. It may be stated that the b-value of 3000 s/mm2 is a novel, improved diagnostic biomarker with greater predictive accuracy for PCa prior to biopsy.

SUBMITTER: Zhang K

PROVIDER: S-EPMC4786278 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Predicting Prostate Biopsy Outcomes: A Preliminary Investigation on Screening with Ultrahigh B-Value Diffusion-Weighted Imaging as an Innovative Diagnostic Biomarker.

Zhang Kun K Shen Yanguang Y Zhang Xu X Ma Lu L Wang Haiyi H An Ningyu N Guo Aitao A Ye Huiyi H

PloS one 20160310 3

<h4>Background</h4>Routine screening of prostate specific antigen (PSA) is no longer recommended because of a high rate of over-diagnosis of prostate cancer (PCa).<h4>Objective</h4>To evaluate the efficacy of diffusion-weighted magnetic resonance imaging (DW-MRI) for PCa detection, and to explore the clinical utility of ultrahigh b-value DW-MRI in predicting prostate biopsy outcomes.<h4>Methodology</h4>73 male patients were selected for the study. They underwent 3T MRI using T2WI conventional DW ...[more]

PMID: 26963936

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Project description:BACKGROUND:The change in apparent diffusion coefficient (ADC) measured from diffusion-weighted imaging (DWI) has been shown to be predictive of pathologic complete response (pCR) for patients with locally invasive breast cancer undergoing neoadjuvant chemotherapy. PURPOSE:To investigate the additive value of tumor ADC in a multicenter clinical trial setting. STUDY TYPE:Retrospective analysis of multicenter prospective data. POPULATION:In all, 415 patients who enrolled in the I-SPY 2 TRIAL from 2010 to 2014 were included. FIELD STRENGTH/SEQUENCE:1.5T or 3T MRI system using a fat-suppressed single-shot echo planar imaging sequence with b-values of 0 and 800 s/mm2 for DWI, followed by a T1-weighted sequence for dynamic contrast-enhanced MRI (DCE-MRI) performed at pre-NAC (T0), after 3 weeks of NAC (T1), mid-NAC (T2), and post-NAC (T3). ASSESSMENT:Functional tumor volume and tumor ADC were measured at each MRI exam; pCR measured at surgery was assessed as the binary outcome. Breast cancer subtype was defined by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status. STATISTICAL TESTS:A logistic regression model was used to evaluate associations between MRI predictors with pCR. The cross-validated area under the curve (AUC) was calculated to assess the predictive performance of the model with and without ADC. RESULTS:In all, 354 patients (128 HR+/HER2-, 60 HR+/HER2+, 34 HR-/HER2+, 132 HR-/HER2-) were included in the analysis. In the full cohort, adding ADC predictors increased the AUC from 0.76 to 0.78 at mid-NAC and from 0.76 to 0.81 at post-NAC. In HR/HER2 subtypes, the AUC increased from 0.52 to 0.65 at pre-NAC for HR+/HER2-, from 0.67 to 0.73 at mid-NAC and from 0.72 to 0.76 at post-NAC for HR+/HER2+, from 0.71 to 0.81 at post-NAC for triple negatives. DATA CONCLUSION:The addition of ADC to standard functional tumor volume MRI showed improvement in the prediction of treatment response in HR+ and triple-negative breast cancer. LEVEL OF EVIDENCE:2 Technical Efficacy Stage: 4 J. Magn. Reson. Imaging 2019;50:1742-1753.

Project description:PurposeTo investigate radiomics based on DWI (diffusion-weighted imaging) for predicting 1-year ischemic stroke recurrence.MethodsA total of 1,580 ischemic stroke patients were enrolled in this retrospective study conducted from January 2018 to April 2021. Demographic and clinical characteristics were compared between recurrence and non-recurrence groups. On DWI, lesions were segmented using a 2D U-Net automatic segmentation network. Further, radiomics feature extraction was done using the segmented mask matrix on DWI and the corresponding ADC map. Additionally, radiomics features were extracted. The study participants were divided into a training cohort (n = 157, 57 recurrence patients, and 100 non-recurrence patients) and a test cohort (n = 846, 28 recurrence patients, 818 non-recurrence patients). A sparse representation feature selection model was performed to select features. Further classification was accomplished using a recurrent neural network (RNN). The area under the receiver operating characteristic curve values was obtained for model performance.ResultsA total of 1,003 ischemic stroke patients (682 men and 321 women; mean age: 65.90 ± 12.44 years) were included in the final analysis. About 85 patients (8.5%) recurred in 1 year, and patients in the recurrence group were older than the non-recurrence group (P = 0.003). The stroke subtype was significantly different between recurrence and non-recurrence groups, and cardioembolic stroke (11.3%) and large artery atherosclerosis patients (10.3%) showed a higher recurrence percentage (P = 0.005). Secondary prevention after discharge (statins, antiplatelets, and anticoagulants) was found significantly different between the two groups (P = 0.004). The area under the curve (AUC) of clinical-based model and radiomics-based model were 0.675 (95% CI: 0.643-0.707) and 0.779 (95% CI: 0.750-0.807), respectively. With an AUC of 0.847 (95% CI: 0.821-0.870), the model that combined clinical and radiomic characteristics performed better.ConclusionDWI-based radiomics could help to predict 1-year ischemic stroke recurrence.

Dataset Information

Predicting Prostate Biopsy Outcomes: A Preliminary Investigation on Screening with Ultrahigh B-Value Diffusion-Weighted Imaging as an Innovative Diagnostic Biomarker.

Background

Objective

Methodology

Results

Conclusions

Publications

Predicting Prostate Biopsy Outcomes: A Preliminary Investigation on Screening with Ultrahigh B-Value Diffusion-Weighted Imaging as an Innovative Diagnostic Biomarker.

Similar Datasets

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