scholarly journals The Primacy of High B-Value 3T-DWI Radiomics in the Prediction of Clinically Significant Prostate Cancer

Diagnostics ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 739
Author(s):  
Alessandro Bevilacqua ◽  
Margherita Mottola ◽  
Fabio Ferroni ◽  
Alice Rossi ◽  
Giampaolo Gavelli ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Quantitative Imaging ◽  
B Value ◽  
Support Vector ◽  
Svm Classifier ◽  
Primary Role ◽  
High B Value ◽  
Wilcoxon Rank Sum Test ◽  
Apparent Diffusion ◽  
Clinically Significant

Predicting clinically significant prostate cancer (csPCa) is crucial in PCa management. 3T-magnetic resonance (MR) systems may have a novel role in quantitative imaging and early csPCa prediction, accordingly. In this study, we develop a radiomic model for predicting csPCa based solely on native b2000 diffusion weighted imaging (DWIb2000) and debate the effectiveness of apparent diffusion coefficient (ADC) in the same task. In total, 105 patients were retrospectively enrolled between January–November 2020, with confirmed csPCa or ncsPCa based on biopsy. DWIb2000 and ADC images acquired with a 3T-MRI were analyzed by computing 84 local first-order radiomic features (RFs). Two predictive models were built based on DWIb2000 and ADC, separately. Relevant RFs were selected through LASSO, a support vector machine (SVM) classifier was trained using repeated 3-fold cross validation (CV) and validated on a holdout set. The SVM models rely on a single couple of uncorrelated RFs (ρ < 0.15) selected through Wilcoxon rank-sum test (p ≤ 0.05) with Holm–Bonferroni correction. On the holdout set, while the ADC model yielded AUC = 0.76 (95% CI, 0.63–0.96), the DWIb2000 model reached AUC = 0.84 (95% CI, 0.63–0.90), with specificity = 75%, sensitivity = 90%, and informedness = 0.65. This study establishes the primary role of 3T-DWIb2000 in PCa quantitative analyses, whilst ADC can remain the leading sequence for detection.

scholarly journals Radiomics Driven Diffusion Weighted Imaging Sensing Strategies for Zone-Level Prostate Cancer Sensing

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1539 ◽  
Author(s):  
Chris Dulhanty ◽  
Linda Wang ◽  
Maria Cheng ◽  
Hayden Gunraj ◽  
Farzad Khalvati ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Sensitivity And Specificity ◽  
Diffusion Weighted Imaging ◽  
B Value ◽  
Invasive Approach ◽  
Non Invasive ◽  
High B Value ◽  
Diffusion Weighted ◽  
Apparent Diffusion ◽  
Critical Regions

Prostate cancer is the most commonly diagnosed cancer in North American men; however, prognosis is relatively good given early diagnosis. This motivates the need for fast and reliable prostate cancer sensing. Diffusion weighted imaging (DWI) has gained traction in recent years as a fast non-invasive approach to cancer sensing. The most commonly used DWI sensing modality currently is apparent diffusion coefficient (ADC) imaging, with the recently introduced computed high-b value diffusion weighted imaging (CHB-DWI) showing considerable promise for cancer sensing. In this study, we investigate the efficacy of ADC and CHB-DWI sensing modalities when applied to zone-level prostate cancer sensing by introducing several radiomics driven zone-level prostate cancer sensing strategies geared around hand-engineered radiomic sequences from DWI sensing (which we term as Zone-X sensing strategies). Furthermore, we also propose Zone-DR, a discovery radiomics approach based on zone-level deep radiomic sequencer discovery that discover radiomic sequences directly for radiomics driven sensing. Experimental results using 12,466 pathology-verified zones obtained through the different DWI sensing modalities of 101 patients showed that: (i) the introduced Zone-X and Zone-DR radiomics driven sensing strategies significantly outperformed the traditional clinical heuristics driven strategy in terms of AUC, (ii) the introduced Zone-DR and Zone-SVM strategies achieved the highest sensitivity and specificity, respectively for ADC amongst the tested radiomics driven strategies, (iii) the introduced Zone-DR and Zone-LR strategies achieved the highest sensitivities for CHB-DWI amongst the tested radiomics driven strategies, and (iv) the introduced Zone-DR, Zone-LR, and Zone-SVM strategies achieved the highest specificities for CHB-DWI amongst the tested radiomics driven strategies. Furthermore, the results showed that the trade-off between sensitivity and specificity can be optimized based on the particular clinical scenario we wish to employ radiomic driven DWI prostate cancer sensing strategies for, such as clinical screening versus surgical planning. Finally, we investigate the critical regions within sensing data that led to a given radiomic sequence generated by a Zone-DR sequencer using an explainability method to get a deeper understanding on the biomarkers important for zone-level cancer sensing.

Comparison of diagnostic performance and inter-reader agreement between PI-RADS v2.1 and PI-RADS v2: systematic review and meta-analysis

2021 ◽  
pp. 20210509
Author(s):  
Chau Hung Lee ◽  
Balamurugan Vellayappan ◽  
Cher Heng Tan
Keyword(s):  
Prostate Cancer ◽  
Systematic Review ◽  
Predictive Value ◽  
Diagnostic Performance ◽  
Meta Analysis ◽  
B Value ◽  
High B Value ◽  
Lower Specificity ◽  
Clinically Significant ◽  
Sensitivity Specificity

Objectives: To perform a systematic review and meta-analysis comparing diagnostic performance and inter reader agreement between PI-RADS v. 2.1 and PI-RADS v. 2 in the detection of clinically significant prostate cancer (csPCa). Methods: A systematic review was performed, searching the major biomedical databases (Medline, Embase, Scopus), using the keywords “PIRADS 2.1” or “PI RADS 2.1” or “PI-RADS 2.1”. Studies reporting on head-to-head diagnostic comparison between PI-RADS v. 2.1 and v. 2 were included. Pooled sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were compared between PI-RADS v. 2.1 and v. 2. Summary receiver operator characteristic graphs were plotted. Analysis was performed for whole gland, and pre-planned subgroup analysis was performed by tumour location (whole gland vs transition zone (TZ)), high b-value DWI (b-value ≥1400 s/mm2), and reader experience (<5 years vs ≥5 years with prostate MRI interpretation). Inter-reader agreement and pooled rates of csPCa for PI-RADS 1–3 lesions were compared between PI-RADS v. 2.1 and v. 2. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool v. 2 (QUADAS-2). Results: Eight studies (1836 patients, 1921 lesions) were included. Pooled specificity for PI-RADS v. 2.1 was significantly lower than PI-RADS v. 2 for whole gland (0.62 vs 0.66, p = 0.02). Pooled sensitivities, PPVs and NPVs were not significantly different (p = 0.17, 0.31, 0.41). Pooled specificity for PI-RADS v. 2.1 was significantly lower than PI-RADS v. 2 for TZ only (0.67 vs 0.72, p = 0.01). Pooled sensitivities, PPVs and NPVs were not significantly different (p = 0.06, 0.36, 0.17). Amongst studies utilising diffusion-weighted imaging with highest b-value of ≥1400 s/mm2, pooled sensitivities, specificities, PPVs and NPVs were not significantly different (p = 0.52, 0.4, 0.5, 0.47). There were no significant differences in pooled sensitivities, specificities, PPVs and NPVs between PI-RADS v. 2.1 and PI-RADS v. 2 for less-experienced readers (p = 0.65, 0.37, 0.65, 0.81) and for more experienced readers (p = 0.57, 0.90, 0.91, 0.65). For PI-RADS v. 2.1 alone, there were no significant differences in pooled sensitivity, specificity, PPV and NPV between less and more experienced readers (p = 0.38, 0.70, 1, 0.48). Inter-reader agreement was moderate to substantial for both PI-RADS v. 2.1 and v. 2. There were no significant differences between pooled csPCa rates between PI-RADS v. 2.1 and v. 2 for PI-RADS 1–2 lesions (6.6% vs  7.3%, p = 0.53), or PI-RADS 3 lesions (24.1% vs  26.8%, p = 0.28). Conclusions: Diagnostic performance and inter-reader agreement for PI-RADS v. 2.1 is comparable to PI-RADS v. 2, however the significantly lower specificity of PI-RADS v. 2.1 may result in increased number of unnecessary biopsies. Advances in knowledge: 1. Compared to PI-RADS v. 2, PI-RADS v. 2.1 has a non-significantly higher sensitivity but a significantly lower specificity for detection of clinically significant prostate cancer. 2. PI-RADS v. 2.1 could potentially result in considerable increase in number of negative targeted biopsy rates for PI-RADS 3 lesions, which could have been potentially avoided.

scholarly journals Patient-level detection of grade group ≥2 prostate cancer using quantitative diffusion MRI

2021 ◽  
Author(s):  
Allison Y Zhong ◽  
Leonardino A Digma ◽  
Troy Hussain ◽  
Christine H Feng ◽  
Christopher C Conlin ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Characteristic Curve ◽  
Grade Group ◽  
Bootstrap Confidence Intervals ◽  
Patient Level ◽  
Apparent Diffusion ◽  
Spectrum Imaging ◽  
Group 2 ◽  
Clinically Significant ◽  
Group 1

Purpose: Multiparametric MRI (mpMRI) improves detection of clinically significant prostate cancer (csPCa), but the qualitative PI-RADS system and quantitative apparent diffusion coefficient (ADC) yield inconsistent results. An advanced Restrictrion Spectrum Imaging (RSI) model may yield a better quantitative marker for csPCa, the RSI restriction score (RSIrs). We evaluated RSIrs for patient-level detection of csPCa. Materials and Methods: Retrospective analysis of men who underwent mpMRI with RSI and prostate biopsy for suspected prostate cancer from 2017-2019. Maximum RSIrs within the prostate was assessed by area under the receiver operating characteristic curve (AUC) for discriminating csPCa (grade group ≥2) from benign or grade group 1 biopsies. Performance of RSIrs was compared to minimum ADC and PI-RADS v2-2.1via bootstrap confidence intervals and bootstrap difference (two-tailed α=0.05). We also tested whether the combination of PI-RADS and RSIrs (PI-RADS+RSIrs) was superior to PI-RADS, alone. Results: 151 patients met criteria for inclusion. AUC values for ADC, RSIrs, and PI-RADS were 0.50 [95% confidence interval: 0.41, 0.60], 0.76 [0.68, 0.84], and 0.78 [0.71, 0.85], respectively. RSIrs (p=0.0002) and PI-RADS (p<0.0001) were superior to ADC for patient-level detection of csPCa. The performance of RSIrs was comparable to that of PI-RADS (p=0.6). AUC for PI-RADS+RSIrs was 0.84 [0.77, 0.90], superior to PI-RADS or RSIrs, alone (p=0.008, p=0.009). Conclusions: RSIrs was superior to conventional ADC and comparable to (routine, clinical) PI-RADS for patient-level detection of csPCa. The combination of PI-RADS and RSIrs was superior to either alone. RSIrs is a promising quantitative marker worthy of prospective study in the setting of csPCa detection.

Clinical impact of ultra-high b-value (3000 s/mm2) diffusion-weighted magnetic resonance imaging in prostate cancer at 3T: comparison with b-value of 2000 s/mm2

2021 ◽  
pp. 20210465
Author(s):  
Tsutomu Tamada ◽  
Ayumu Kido ◽  
Yu Ueda ◽  
Mitsuru Takeuchi ◽  
Takeshi Fukunaga ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Diagnostic Performance ◽  
Signal To Noise Ratio ◽  
B Value ◽  
Single Shot ◽  
Signal To Noise ◽  
High B Value ◽  
Diffusion Weighted ◽  
Significant Difference ◽  
Noise Ratio

Objective: High b-value diffusion-weighted imaging (hDWI) with a b-value of 2000 s/mm2 provides insufficient image contrast between benign and malignant tissues and an overlap of apparent diffusion coefficient (ADC) between Gleason grades (GG) in prostate cancer (PC). We compared image quality, PC detectability, and discrimination ability for PC aggressiveness between ultra-high b-value DWI (uhDWI) of 3000 s/mm2 and hDWI. Methods: The subjects were 49 patients with PC who underwent 3T multiparametric MRI. Single-shot echo-planar DWI was acquired with b-values of 0, 2000, and 3000 s/mm2. Anatomical distortion of prostate (AD), signal intensity of benign prostate (PSI), and lesion conspicuity score (LCS) were assessed using a 4-point scale; and signal-to-noise ratio, contrast-to-noise ratio, and mean ADC (×10–3 mm2/s) of lesion (lADC) and surrounding benign region (bADC) were measured. Results: PSI was significantly lower in uhDWI than in hDWI (p < 0.001). AD, LCS, signal-to-noise ratio, and contrast-to-noise ratio were comparable between uhDWI and hDWI (all p > 0.05). In contrast, lADC was significantly lower than bADC in both uhDWI and hDWI (both p < 0.001). In comparison of lADC between tumors of ≤GG2 and those of ≥GG3, both uhDWI and hDWI showed significant difference (p = 0.007 and p = 0.021, respectively). AUC for separating tumors of ≤GG2 from those of ≥GG3 was 0.731 in hDWI and 0.699 in uhDWI (p = 0.161). Conclusion: uhDWI suppressed background signal better than hDWI, but did not contribute to increased diagnostic performance in PC. Advances in knowledge: Compared with hDWI, uhDWI could not contribute to increased diagnostic performance in PC.

Image quality and diagnostic accuracy of complex-averaged high b value images in diffusion-weighted MRI of prostate cancer

2019 ◽  
Vol 44 (6) ◽  
pp. 2244-2253 ◽  
Author(s):  
Hamed Kordbacheh ◽  
Ravi Teja Seethamraju ◽  
Elisabeth Weiland ◽  
Berthold Kiefer ◽  
Marcel Dominik Nickel ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Image Quality ◽  
Diagnostic Accuracy ◽  
B Value ◽  
Diffusion Weighted Mri ◽  
High B Value ◽  
Diffusion Weighted

scholarly journals The diagnostic accuracy of high b-value diffusion- and T2-weighted imaging for the detection of prostate cancer: a meta-analysis

2017 ◽  
Vol 43 (7) ◽  
pp. 1787-1797 ◽  
Author(s):  
Tom J. Syer ◽  
Keith C. Godley ◽  
Donnie Cameron ◽  
Paul N. Malcolm
Keyword(s):  
Prostate Cancer ◽  
Diagnostic Accuracy ◽  
Meta Analysis ◽  
B Value ◽  
High B Value
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