Personalized optimization of systematic prostate biopsy core number based on mpMRI radiomics features: a large-sample retrospective analysis

The optimization PCS model described in this study could therefore effectively reduce the number of systematic biopsy cores obtained from patients with high PCS, especially for biopsy cores far away from suspicious lesions. This method can enhance patient experience without reducing tumor detection rate.

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Publication Details

Journal
BMC Cancer
Published
2025-01-22
DOI
https://doi.org/10.1186/s12885-024-13391-3
Citations
1
Primary Topic
Prostate Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
1.52

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article

Personalized optimization of systematic prostate biopsy core number based on mpMRI radiomics features: a large-sample retrospective analysis

Shaoqin Jiang, Ciquan Liu, Yue Xu, Ruiling Dou et al.
1 citations
BMC Cancer
Prostate Cancer Diagnosis and Treatment
1.52
article

Personalized optimization of systematic prostate biopsy core number based on mpMRI radiomics features: a large-sample retrospective analysis

Shaoqin Jiang, Ciquan Liu, Yue Xu, Ruiling Dou, Zhenlin Chen, Zequn Lin, Yewen Lin, Zhihao Li, Shaoshan Lin, Zijie Zheng, Mengqiang Li
article en
1 citations

Abstract

The optimization PCS model described in this study could therefore effectively reduce the number of systematic biopsy cores obtained from patients with high PCS, especially for biopsy cores far away from suspicious lesions. This method can enhance patient experience without reducing tumor detection rate.

BMC CancerVol. 25(1)
Fujian Medical University (CN), Union Hospital (CN)
Natural Science Foundation of Fujian Province, Changhai Hospital of Shanghai, Fujian Medical University, Fujian Provincial Health Technology Project
Gender equality
Openalex Percentile: Top 23%
Prostate Cancer Diagnosis and Treatment
1.52
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Personalized optimization of systematic prostate biopsy core number based on mpMRI radiomics features: a large-sample retrospective analysis — Shaoqin Jiang, Ciquan Liu, et al. · BMC Cancer (2025) | TGRS Research Map | TGRS