Quantification of intratumoral heterogeneity using habitat-based MRI radiomics for predicting high-Gleason scores and castration-resistant PCa: retrospective study

Our study developed ITH signatures that quantified ITH using habitat-based MRI radiomics, which demonstrated outstanding performance in predicting both high GS and CRPC.

Authors

Institutions

Publication Details

Journal
BMC Cancer
Published
2025-11-21
DOI
https://doi.org/10.1186/s12885-025-15300-8
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantification of intratumoral heterogeneity using habitat-based MRI radiomics for predicting high-Gleason scores and castration-resistant PCa: retrospective study

Xin Yang, Yongsheng He, Xuan Qi, Chang Zhai et al.
BMC Cancer
Radiomics and Machine Learning in Medical Imaging
article

Quantification of intratumoral heterogeneity using habitat-based MRI radiomics for predicting high-Gleason scores and castration-resistant PCa: retrospective study

Xin Yang, Yongsheng He, Xuan Qi, Chang Zhai, Hongkai Yang
article en

Abstract

Our study developed ITH signatures that quantified ITH using habitat-based MRI radiomics, which demonstrated outstanding performance in predicting both high GS and CRPC.

BMC CancerVol. 25(1)
Anshan Hospital (CN)
Openalex Percentile: Top 50%
Radiomics and Machine Learning in Medical Imaging
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.