Causal AI-based clinical and radiomic analysis for optimizing patient selection in combined immunotherapy and SABR in early-stage NSCLC: a secondary analysis of the phase II I-SABR trial
Combining clinical and radiomic parameters, I-SABR-SELECT uses causal reasoning to individualize treatment selection for patients with early-stage inoperable NSCLC. If validated, it could serve as a foundation for a treatment-focused digital twin by integrating real-time adaptive decision-making. <b>Code:</b> https://github.com/WuLabMDA/ISABR-SELECT.
Authors
- Jia Wu (ORCID: https://orcid.org/0000-0001-8392-8338)
- David A. Jaffray (ORCID: https://orcid.org/0000-0001-7378-7543)
- Joe Y. Chang (ORCID: https://orcid.org/0000-0002-8435-2083)
- Vivek Verma (ORCID: https://orcid.org/0000-0001-8129-4140)
- M. Qayati Mohamed
- Morteza Salehjahromi (ORCID: https://orcid.org/0000-0002-7036-1683)
- Maliazurina B. Saad (ORCID: https://orcid.org/0000-0002-2895-4186)
- John Victor Heymach (ORCID: https://orcid.org/0000-0001-9068-8942)
- Muhammad Aminu (ORCID: https://orcid.org/0000-0002-9903-8812)
- Eman Showkatian (ORCID: https://orcid.org/0000-0002-2059-3769)
- Yuliya Kitsel (ORCID: https://orcid.org/0009-0001-1500-7083)
- Sheeba J. Sujit (ORCID: https://orcid.org/0000-0001-8302-7046)
- Qasem Al-Tashi (ORCID: https://orcid.org/0000-0001-7208-693X)
- Steven Hsesheng Lin (ORCID: https://orcid.org/0000-0003-4411-0634)
- David C. Qian (ORCID: https://orcid.org/0000-0002-8459-009X)
- Caroline Chung (ORCID: https://orcid.org/0000-0002-9662-1519)
- Natalie I. Vokes (ORCID: https://orcid.org/0000-0002-3766-5335)
- Jianjun Zhang (ORCID: https://orcid.org/0000-0001-7872-3477)
- J. Jack Lee (ORCID: https://orcid.org/0000-0001-5469-9214)
- Zhongxing Liao
- Saumil Gandhi (ORCID: https://orcid.org/0000-0002-3349-3521)
- Xinyan Xu
Institutions
- The University of Texas MD Anderson Cancer Center (US)
Publication Details
- Journal
- Journal for ImmunoTherapy of Cancer
- Published
- 2025-10-01
- DOI
- https://doi.org/10.1136/jitc-2025-013074
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36
Funders
- Bristol-Myers Squibb
- National Institutes of Health
- University of Texas MD Anderson Cancer Center
- National Cancer Institute