Role of diffusion-weighted magnetic resonance imaging in prostate cancer evaluation

A systematic review and meta-analysis of the diagnostic accuracy of biparametric prostate MRI for prostate cancer in men at risk

INTRODUCTION

Multiparametric magnetic resonance imaging (mpMRI), the use of three multiple imaging sequences, typically T2-weighted, diffusion weighted (DWI) and dynamic contrast enhanced (DCE) images, has a high sensitivity and specificity for detecting significant cancer. Current guidance now recommends its use prior to biopsy. However, the impact of DCE is currently under debate regarding test accuracy. Biparametric MRI (bpMRI), using only T2 and DWI has been proposed as a viable alternative. We conducted a contemporary systematic review and meta-analysis to further examine the diagnostic performance of bpMRI in the diagnosis of any and clinically significant prostate cancer.

METHODS

A systematic review of the literature from 01/01/2017 to 06/07/2019 was performed by two independent reviewers using predefined search criteria. The index test was biparametric MRI and the reference standard whole-mount prostatectomy or prostate biopsy. Quality of included studies was assessed by the QUADAS-2 tool. Statistical analysis included pooled diagnostic performance (sensitivity; specificity; AUC), meta-regression of possible covariates and head-to-head comparisons of bpMRI and mpMRI where both were performed in the same study.

RESULTS

Forty-four articles were included in the analysis. The pooled sensitivity for any cancer detection was 0.84 (95% CI, 0.80-0.88), specificity 0.75 (95% CI, 0.68-0.81) for bpMRI. The summary ROC curve yielded a high AUC value (AUC = 0.86). The pooled sensitivity for clinically significant prostate cancer was 0.87 (95% CI, 0.78-0.93), specificity 0.72 (95% CI, 0.56-0.84) and the AUC value was 0.87. Meta-regression analysis revealed no difference in the pooled diagnostic estimates between bpMRI and mpMRI.

CONCLUSIONS

This meta-analysis on contemporary studies shows that bpMRI offers comparable test accuracies to mpMRI in detecting prostate cancer. These data are broadly supportive of the bpMRI approach but heterogeneity does not allow definitive recommendations to be made. There is a need for prospective multicentre studies of bpMRI in biopsy naïve men.

Prostate cancer GTV delineation with biparametric MRI and 68Ga-PSMA-PET: comparison of expert contours and semi-automated methods

OBJECTIVE

The optimal method for delineation of dominant intraprostatic lesions (DIL) for targeted radiotherapy dose escalation is unclear. This study evaluated interobserver and intermodality variability of delineations on biparametric MRI (bpMRI), consisting of T₂ weighted (T₂W) and diffusion-weighted (DWI) sequences, and ⁶⁸Ga-PSMA-PET/CT; and compared manually delineated GTV contours with semi-automated segmentations based on quantitative thresholding of intraprostatic apparent diffusion coefficient (ADC) and standardised uptake values (SUV).

METHODS

16 patients who had bpMRI and PSMA-PET scanning performed prior to any treatment were eligible for inclusion. Four observers (two radiation oncologists, two radiologists) manually delineated the DIL on: (1) bpMRI (GTV_MRI), (2) PSMA-PET (GTV_PSMA) and (3) co-registered bpMRI/PSMA-PET (GTV_Fused) in separate sittings. Interobserver, intermodality and semi-automated comparisons were evaluated against consensus Simultaneous Truth and Performance Level Estimation (STAPLE) volumes, created from the relevant manual delineations of all observers with equal weighting. Comparisons included the Dice Similarity Coefficient (DSC), mean distance to agreement (MDA) and other metrics.

RESULTS

Interobserver agreement was significantly higher (p < 0.05) for GTV_PSMA (DSC: 0.822, MDA: 1.12 mm) and GTV_Fused (DSC: 0.787, MDA: 1.34 mm) than for GTV_MRI (DSC: 0.705, MDA 2.44 mm). Intermodality agreement between GTV_MRI and GTV_PSMA was low (DSC: 0.440, MDA: 4.64 mm). Agreement between semi-automated volumes and consensus GTV was low for MRI (DSC: 0.370, MDA: 8.16 mm) and significantly higher for PSMA-PET (0.571, MDA: 4.45 mm, p < 0.05).

CONCLUSION

⁶⁸Ga-PSMA-PET appears to improve interobserver consistency of DIL localisation vs bpMRI and may be more viable for simple quantitative delineation approaches; however, more sophisticated approaches to semi-automatic delineation factoring for patient- and disease-related heterogeneity are likely required.

ADVANCES IN KNOWLEDGE

This is the first study to evaluate the interobserver variability of prostate GTV delineations with co-registered bpMRI and ⁶⁸Ga-PSMA-PET.

Is dynamic contrast enhancement still necessary in multiparametric magnetic resonance for diagnosis of prostate cancer: a systematic review and meta-analysis

Background

The purpose of this study is to systematically review the literatures assessing the value of dynamic contrast enhancement (DCE) in the multiparametric magnetic resonance imaging (mpMRI) for the diagnosis of prostate cancer (PCa).

Methods

We searched Embase, PubMed and Web of science until January 2019 to extract articles exploring the possibilities whether the pre-biopsy biparametric magnetic resonance imaging (bpMRI) can replace the position of mpMRI in the diagnosis of PCa. The sensitivity and specificity of bpMRI were all included. The study quality was assessed by QUADAS-2. Bivariate random effects meta-analyses and a hierarchical summary receiver operating characteristic plot were performed for further study through Revman 5 and Stata12.

Results

After searching, we acquired 752 articles among which 45 studies with 5,217 participants were eligible for inclusion. The positive likelihood ratio for the detection of PCa was 2.40 (95% CI: 1.50–3.80) and the negative likelihood ratio was 0.31 (95% CI: 0.18–0.53). The sensitivity and specificity were 0.77 (95% CI: 0.73–0.81) and 0.81 (95% CI: 0.76–0.85) respectively. Based on our result, pooled specificity demonstrated little difference between bpMRI and mpMRI [bpMRI, 0.81 (95% CI, 0.76–0.85); mpMRI, 0.82 (95% CI, 0.72–0.88); P=0.169]. The sensitivity, however, indicated a significant difference between these two groups [bpMRI, 0.77 (95% CI, 0.73–0.81); mpMRI, 0.84 (95% CI, 0.78–0.89); P=0.001].

Conclusions

bpMRI with high b-value is a sensitive tool for diagnosing PCa. Consistent results were found in multiple subgroup analysis.

Role of apparent diffusion coefficient values in prostate diseases characterization on diffusion-weighted magnetic resonance imaging

BACKGROUND

To evaluate if normal and pathological prostate tissue can be distinguished by using apparent diffusion coefficient (ADC) values on magnetic resonance imaging (MRI) and to understand if it is possible to differentiate among pathological prostate tissues using ADC values.

METHODS

Our population consisted in 81 patients (mean age 65.4 years) in which 84 suspicious areas were identified. Regions of interest were placed over suspicious areas, detected on MRI, and over areas with normal appearance, and ADC values were recorded. Statistical differences between ADC values of suspicious and normal areas were evaluated. Histopathological diagnosis, obtained from targeted biopsy using MRI-US fusion biopsies in 39 patients and from prostatectomy in 42 patients, were correlated to ADC values.

RESULTS

Histopathological diagnosis revealed 58 cases of prostate cancer (PCa), 19 patients with indolent PCa (Gleason Score ≤6) and 39 patients with clinically significant PCa (Gleason Score ≥7), 16 of high-grade prostatic intraepithelial neoplasia (HG-PIN) and 10 of atypical small acinar proliferation (ASAP). Significant statistical differences between mean ADC values of normal prostate tissue versus PCa (P<0.00001), HG-PIN (P<0.00001) and ASAP (P<0.00001) were found. Significant differences were observed between mean ADC values of PCa versus HG-PIN (P<0.00001) and ASAP (P<0.00001) with many overlapping values. Differences between mean ADC values of HG-PIN versus ASAP (P=0.015) were not significant. Significant differences of ADC values were also observed between patients with indolent and clinically significant PCa (P<0.00001).

CONCLUSIONS

ADC values allow differentiation between normal and pathological prostate tissue and between indolent and clinically significant PCa but do not allow a definite differentiation between PCa, HG-PIN, and ASAP.

Diagnostic Performance of Biparametric MRI for Detection of Prostate Cancer: A Systematic Review and Meta-Analysis

OBJECTIVE

The purpose of this study was to perform a systematic review and meta-analysis to estimate the diagnostic performance of biparametric MRI (bpMRI) for detection of prostate cancer (PCa).

MATERIALS AND METHODS

Two independent reviewers performed a systematic review of the literature published from January 2000 to July 2017 by using predefined search terms. The standard of pathologic reference was established at prostatectomy or prostate biopsy. The numbers of true- and false-positive and true- and false-negative results were extracted. The Quality Assessment of Diagnostic Accuracy Studies tool was used to assess the quality of the selected studies. Statistical analysis included pooling of diagnostic accuracy, meta-regression, subgroup analysis, head-to-head comparison, and identification of publication bias.

RESULTS

Thirty-three studies were used for general data pooling. The overall sensitivity was 0.81 (95% CI, 0.76-0.85), and overall specificity was 0.77 (95% CI, 0.69-0.84). As for clinically relevant PCa, bpMRI maintained high diagnostic value (AUC, 0.85; 95% CI, 0.82-0.88). There was no evidence of publication bias (p = 0.67). From head-to-head comparison for detection of PCa, multiparametric MRI (mpMRI) had significantly higher pooled sensitivity (0.85; 95% CI, 0.78-0.93) than did bpMRI (0.80; 95% CI, 0.71-0.90) (p = 0.01). However, the pooled specificity values were not significantly different (mpMRI, 0.77 [95% CI, 0.58-0.95]; bpMRI, 0.80 [95% CI, 0.64-0.96]; p = 0.82).

CONCLUSION

The results of this meta-analysis suggest that bpMRI has high diagnostic accuracy in the detection of PCa and maintains a high detection rate for clinically relevant PCa. However, owing to high heterogeneity among the included studies, caution is needed in applying the results of the meta-analysis.

The value of diffusion-weighted imaging in the detection of prostate cancer: a meta-analysis

Objectives

To evaluate the diagnostic performance of diffusion-weighted imaging (DWI) as a single non-invasive method in detecting prostate cancer (PCa) and to deduce its clinical utility.

Methods

A systematic literature search was performed to identify relevant original studies. Quality of included studies was assessed by QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies). Data were extracted to calculate sensitivity and specificity as well as running the test of heterogeneity and threshold effect. The summary receiver operating characteristic (SROC) curve was drawn and area under SROC curve (AUC) served as a determination of the diagnostic performance of DWI for the detection of PCa.

Results

A total of 21 studies were included, with 27 subsets of data available for analysis. The pooled sensitivity and specificity with corresponding 95 % confidence interval (CI) were 0.62 (95 % CI 0.61–0.64) and 0.90 (95 % CI 0.89–0.90), respectively. Pooled positive likelihood ratio and negative likelihood ratio were 5.83 (95 % CI 4.61–7.37) and 0.30 (95 % CI 0.23–0.39), respectively. The AUC was 0.8991. Significant heterogeneity was observed. There was no notable publication bias.

Conclusions

DWI is an informative MRI modality in detecting PCa and shows moderately high diagnostic accuracy. General clinical application was limited because of the absence of standardized DW-MRI techniques.

Key points

• DWI provides incremental information for the detection and evaluation of PCa

• DWI has moderately high diagnostic accuracy in detecting PCa

• Patient condition, imaging protocols and study design positively influence diagnostic performance

• General clinical application requires optimization of image acquisition and interpretation

Evaluation of the normal-to-diseased apparent diffusion coefficient ratio as an indicator of prostate cancer aggressiveness

Background

We tested the feasibility of a simple method for assessment of prostate cancer (PCa) aggressiveness using diffusion-weighted magnetic resonance imaging (MRI) to calculate apparent diffusion coefficient (ADC) ratios between prostate cancer and healthy prostatic tissue.

Methods

The requirement for institutional review board approval was waived. A set of 20 standardized core transperineal saturation biopsy specimens served as the reference standard for placement of regions of interest on ADC maps in tumorous and normal prostatic tissue of 22 men with PCa (median Gleason score: 7; range, 6–9). A total of 128 positive sectors were included for evaluation. Two diagnostic ratios were computed between tumor ADCs and normal sector ADCs: the ADC peripheral ratio (the ratio between tumor ADC and normal peripheral zone tissue, ADC-PR), and the ADC central ratio (the ratio between tumor ADC and normal central zone tissue, ADC-CR). The performance of the two ratios in detecting high-risk tumor foci (Gleason 8 and 9) was assessed using the area under the receiver operating characteristic curve (AUC).

Results

Both ADC ratios presented significantly lower values in high-risk tumors (0.48 ± 0.13 for ADC-CR and 0.40 ± 0.09 for ADC-PR) compared with low-risk tumors (0.66 ± 0.17 for ADC-CR and 0.54 ± 0.09 for ADC-PR) (p < 0.001) and had better diagnostic performance (ADC-CR AUC = 0.77, sensitivity = 82.2%, specificity = 66.7% and ADC-PR AUC = 0.90, sensitivity = 93.7%, specificity = 80%) than stand-alone tumor ADCs (AUC of 0.75, sensitivity = 72.7%, specificity = 70.6%) for identifying high-risk lesions.

Conclusions

The ADC ratio as an intrapatient-normalized diagnostic tool may be better in detecting high-grade lesions compared with analysis based on tumor ADCs alone, and may reduce the rate of biopsies.

Functional and molecular imaging: applications for diagnosis and staging of localised prostate cancer

Prostate cancer is currently the most common solid organ cancer type among men in the Western world. Currently, all decision-making algorithms and nomograms rely on demographics, clinicopathological data and symptoms. Such an approach can easily miss significant cancers while detecting many insignificant cancers. In this review, novel functional and molecular imaging techniques used in the diagnosis and staging of localised prostate cancer and their effect on treatment decisions are discussed.