Computed Tomography-Based Radiomics Features Characterize Low and High-Risk Lung Cancer Among People Living With HIV: An Early Report
Clinical Practice Points Distinct radiomic features distinguish between highand low-risk lung cancer patients. Distinct radiomic features distinguish between among people living with HIV and patients without HIV. These results support the contention that the biology of lung tumors among people living with HIV versus their counterparts without HIV. Radiomics features could stratify patients to prevent overtreatment in low-risk patients and guide more aggressive treatment in high-risk patients.
Authors
- Oya Altinok (ORCID: https://orcid.org/0000-0002-8713-0697)
- Anna E. Coghill (ORCID: https://orcid.org/0000-0001-7142-7499)
- Ranjita Poudel (ORCID: https://orcid.org/0000-0003-4343-1153)
- Jessica Y. Islam (ORCID: https://orcid.org/0000-0002-3690-3848)
- Christine Vinci (ORCID: https://orcid.org/0000-0001-8883-0989)
- Vani N. Simmons (ORCID: https://orcid.org/0000-0002-4381-5336)
- Kristina Bowles (ORCID: https://orcid.org/0000-0002-1091-0978)
- Matthew B. Schabath (ORCID: https://orcid.org/0000-0003-3241-3216)
Institutions
- Moffitt Cancer Center (US)
Publication Details
- Journal
- Clinical Lung Cancer
- Published
- 2025-12-25
- DOI
- https://doi.org/10.1016/j.cllc.2025.12.008
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Moffitt Cancer Center
- National Cancer Institute