Baseline ¹8F-FDG PET/CT radiomics predict early progression and survival in small cell lung cancer

Baseline thoracic PET/CT radiomics, particularly logTLG, independently predict survival in SCLC. MTV and LDH identify early progression, while age, stage, and SUV entropy predict short-term mortality, supporting integrated imaging-clinical risk stratification.

Authors

Institutions

Publication Details

Journal
BMC Cancer
Published
2026-01-13
DOI
https://doi.org/10.1186/s12885-025-15523-9
Citations
1
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
31.92
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Baseline ¹8F-FDG PET/CT radiomics predict early progression and survival in small cell lung cancer

Chia-Hsin Liu, Chen-Liang Tsai, Yucheng Wu, Cheng-Yin Liu et al.
1 citations
BMC Cancer
Radiomics and Machine Learning in Medical Imaging
31.92
article

Baseline ¹8F-FDG PET/CT radiomics predict early progression and survival in small cell lung cancer

Chia-Hsin Liu, Chen-Liang Tsai, Yucheng Wu, Cheng-Yin Liu, Tsai-Wang Huang, Li-Fan Lin
article en
1 citations

Abstract

Baseline thoracic PET/CT radiomics, particularly logTLG, independently predict survival in SCLC. MTV and LDH identify early progression, while age, stage, and SUV entropy predict short-term mortality, supporting integrated imaging-clinical risk stratification.

BMC CancerVol. 26(1)
Hualien Armed Forces General Hospital (TW), National Defense Medical Center (TW)
Good health and well-being
Openalex Percentile: Top 2%
Radiomics and Machine Learning in Medical Imaging
31.92
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.