Evidence map›Paper›PMID 39776403›Full record

ArticleInternational urology and nephrology2025

Ultrasound radiomics model based on grayscale transrectal ultrasound-guided biopsy for diagnosing prostate cancer and predicting distant metastasis.

Jie Liu, Zhendong Xiang, Cheng Yi, Tianzi Yang, Dongting Liu

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Article in International urology and nephrology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jie LiuDepartment of Ultrasound, The First College of Clinical Medical Science, China Three Gorges University, Yichang Central People's Hospital, No. 2 Jiefang Road, Xiling District, Yichang, Hubei, China.
Zhendong XiangDepartment of Urology, The First College of Clinical Medical Science, China Three Gorges University, Yichang Central People's Hospital, No. 2 Jiefang Road, Xiling District, Yichang, Hubei, China. 35753701@qq.com.
Cheng YiDepartment of Urology, The First College of Clinical Medical Science, China Three Gorges University, Yichang Central People's Hospital, No. 2 Jiefang Road, Xiling District, Yichang, Hubei, China.
Tianzi YangChina Three Gorges University of Medical Science, Daxue Road, Yichang, Hubei, China.
Dongting LiuDepartment of Ultrasound, The First College of Clinical Medical Science, China Three Gorges University, Yichang Central People's Hospital, No. 2 Jiefang Road, Xiling District, Yichang, Hubei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveA prostate ultrasound (US) imaging omics model was established to assess its effectiveness in diagnosing prostate cancer (PCa), predicting Gleason score (GS), and determining the likelihood of distant metastasis.

methodsUS images of patients with prostate pathology confirmed by biopsy or surgery at our hospital were retrospectively analyzed. Regions of interest (ROI) segmentation, feature extraction, feature screening, and the construction and training of the radiomics model were performed.

resultsArea under the curve (AUC) for the magnetic resonance imaging Prostate Imaging Reporting and Data System (MRI PI-RADS) classification, radiomics alone, and radiomics combined with prostate-specific antigen (PSA) in diagnosing PCa were 70.74%, 71.13%, and 90.47%, respectively. AUCs for the MRI PI-RADS classification, radiomics alone, and radiomics combined with PSA in predicting the GS of PCa were 75.6%, 74.7%, and 88.9%, respectively. Furthermore, AUCs for MRI PI-RADS classification and radiomics alone in predicting distant metastasis of PCa were 66.7% and 90.8%, respectively.

conclusionThe combination of ultrasonic imaging omics and serum PSA significantly improves the efficiency of PCa diagnosis, GS prediction, and distant metastasis prediction. This method is an important tool for PCa screening and follow-up.

Indexed as

Prostatic NeoplasmsUltrasonography, InterventionalAgedHumansImage-Guided BiopsyMagnetic Resonance ImagingMaleMiddle AgedNeoplasm GradingNeoplasm MetastasisPredictive Value of TestsProstate-Specific AntigenRadiomicsRetrospective StudiesUltrasonographyProstate-Specific AntigenDiagnosisPredictProstate cancerUltrasound-guided biopsyUltrasound radiomics

Identifiers

PMID39776403

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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.