Journal
QUANTITATIVE IMAGING IN MEDICINE AND SURGERY
Volume -, Issue -, Pages -Publisher
AME PUBLISHING COMPANY
DOI: 10.21037/qims-22-1354
Keywords
-
Ask authors/readers for more resources
This study aimed to construct a biparametric ultrasound (BU) scoring system for the risk assessment of prostate cancer (PCa) and to provide an option for the detection of clinically significant PCa. The results showed that the BU scoring system had similar efficacy and value compared to multiparametric magnetic resonance imaging (mpMRI) in clinical practice.
Background: Ultrasound has advantages in prostate cancer (PCa) detection and biopsy guidance but lacks a comprehensive quantitative evaluation model with multiparametric features. We aimed to construct a biparametric ultrasound (BU) scoring system for PCa risk assessment and to provide an option for clinically significant prostate cancer (csPCa) detection. Methods: From January 2015 to December 2020, 392 consecutive patients at Chongqing University Cancer Hospital who underwent BU (grayscale, Doppler flow imaging, and contrast-enhanced ultrasound) and multiparametric magnetic resonance imaging (mpMRI) before biopsy were retrospectively enrolled in the training set to construct the scoring system. From January 2021 to May 2022, 166 consecutive patients at Chongqing University Cancer Hospital were retrospectively enrolled in the validation set. The ultrasound system was compared with mpMRI, and the gold standard was a biopsy. The primary outcome was the detection of csPCa in any area with a Gleason score (GS) >_3+4, and the secondary outcome was defined as a GS >_4+3 and/or maximum cancer core length (MCCL) >_6 mm. Results: Malignant association features in the nonenhanced biparametric ultrasound (NEBU) scoring system included echogenicity, capsule, and gland asymmetrical vascularity. In the biparametric ultrasound scoring system (BUS), the feature of contrast agent arrival time was added. In the training set, the area under the curves (AUCs) of the NEBU scoring system, BUS, and mpMRI were 0.86 [95% confidence interval (CI): 0.82-0.90], 0.86 (95% CI: 0.82-0.90), and 0.86 (95% CI: 0.83-0.90), respectively (P>0.05). Similar results were also observed in the validation set, in which the areas under the curves were 0.89 (95% CI: 0.84-0.94), 0.90 (95% CI: 0.85-0.95), and 0.88 (95% CI: 0.82-0.94), respectively (P>0.05). Conclusions: We constructed a BUS that showed efficacy and value for csPCa diagnosis as compared with mpMRI. However, in limited circumstances, the NEBU scoring system may also be an option.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available