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Habitat-aware radiomics and adaptive 2.5D deep learning predict treatment response and long-term survival in ESCC patients undergoing neoadjuvant chemoimmunotherapy

Crossref DOI link: https://doi.org/10.1007/s00259-025-07522-6

Published Online: 2025-09-17

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Gao, Xing

Yang, Liping

She, Tianyu

Wang, Fei

Ding, Hongchao

Lu, Yanhong

Xu, Yuchao

Wang, Yuan

Li, Ping

Duan, Xiaoyi

Leng, Xiaoping
Funding

Funding for this research was provided by:

Natural Science Foundation of China (U22A20346)

Longjiang science and Technology Talent Wild ChunYan Support Project (CYCX24003)
License Information

Text and Data Mining valid from 2025-09-17

Version of Record valid from 2025-09-17
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Article History

Received: 4 June 2025

Accepted: 6 August 2025

First Online: 17 September 2025

Declarations

:

: The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the Institutional Review Board and Ethical Committee of the First Affiliated Hospital of Xi’an Jiaotong University and the Second Affiliated Hospital of Harbin Medical University. Individual consent for this retrospective analysis was waived.

: Not applicable.

: Informed consent was waived for this retrospective study.

: The authors declare that they have no competing interests.

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