ArticleQuantitative imaging in medicine and surgery2023
A scoring diagnostic system based on biparametric ultrasound features for prostate cancer risk assessment.
Article in Quantitative imaging in medicine and surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- An innovative approach for predicting prostate cancer Gleason grading: machine learning-based fusion of multimodal ultrasound, clinical and laboratory indicators.European journal of medical research · 2025Article
- Radiogenomic analysis of ultrasound phenotypic features coupled to proteomes predicts metastatic risk in primary prostate cancer.BMC cancer · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.