Work

Portable Perfusion Phantom Offers Quantitative Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Accurate Prostate Cancer Grade Stratification: A Pilot Study

Year: 2020

Type: article

Abstract: Rationale and Objectives The study goal was to test whether the improved accuracy in quantitative dynamic contrast-enhanced magnetic resonance imaging measurement using a point-of-care portable perfusion phantom (P4) leads to better stratification of prostate cancer grade. Materials and Methods A prospective clinical study was conducted recruiting 44 patients scheduled for multi-parameter MRI prostate exams. All participants were imaged with the P4 placed under their pelvic regions. Tissue sampling was carried out for 25 patients at 22 ± 18 (mean ± SD) days after multi-parameter MRI. On histologic examination, a total of 31 lesions were confirmed as prostate cancer. Tumors were classified into low grade (n = 14), intermediate grade (n = 10), and high grade (n = 7). Tumor perfusion was assessed by volume transfer constant, K trans , before and after P4-based error correction, and the K trans of low, intermediate and high-grade tumors were statistically compared. Results After P4-based error correction, the K trans of low, intermediate, and high-grade tumors were 0.109 ± 0.026 min −1 (95% CI: 0.0094 to 0.124 min −1 ), 0.163 ± 0.049 min −1 (95% CI: 0.129 to 0.198 min −1 ) and 0.356 ± 0.156 min −1 (95% CI: 0.215 to 0.495 min −1 ), respectively, with statistically significant difference among the groups (low vs intermediate: p = 0.002; intermediate vs high: p = 0.002; low vs high: p < 0.001). The sensitivity and specificity of K trans value, 0.14 min −1 , to detect the clinically significant prostate cancer were 88% and 93%, respectively, after P4 based error correction, but those before error correction were 88% and 86%, respectively. Conclusion The P4 allows to reduce errors in quantitative dynamic contrast-enhanced magnetic resonance imaging measurement, enhancing accuracy in stratification of prostate cancer grade.

Source: Academic Radiology

DOI: 10.1016/j.acra.2020.02.027

Authors: Harrison Kim, John V. Thomas, Jeffrey W. Nix, Jennifer B. Gordetsky, Yufeng Li, Soroush Rais-Bahrami

Institutions: University of Alabama at Birmingham, UAB Medicine, O'Neal Comprehensive Cancer Center

Language: English

Topic: MRI in cancer diagnosis

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $2,750