AI-Driven Tumor Response Evaluation for Solid Tumors

Purpose: This study is developing and validating an artificial intelligence (AI)-driven system to evaluate tumor response using changes in total tumor volume. The goal is to determine whether this AI-based approach can better predict patient survival compared with the current standard method (RECIST), which relies on linear measurements of a few selected tumors. Participants: The study includes both retrospective and prospective cohorts. The retrospective cohort includes approximately 6,000 patients with solid tumors who received non-surgical treatment between 2015 and 2025. The prospective cohort will enroll approximately 120 patients starting in mid-2026. Study details include: Study Duration: Approximately 3 years Participation Duration: Up to 6 months for prospective participants; retrospective participants contribute existing medical records only Visit Frequency: For prospective participants, follow-up visits occur every 3 months (up to 6 months) aligned with routine clinical care Intervention: None. This is an observational study using routine clinical imaging (CT/MRI) and medical records Primary endpoints: Overall survival (OS) and progression-free survival (PFS). The study will also evaluate the feasibility and impact of AI-assisted tumor response reporting on clinical workflow and patient understanding. Participants in the prospective cohort will receive either a standard RECIST report or an AI-assisted dynamic tumor response report. This comparison is for research purposes only and does not alter standard medical care.

Sex

All

Minimum age

18 Years

Inclusion Criteria:

1. Age ≥ 18 years, any sex.
2. Radiologically or pathologically confirmed diagnosis of solid tumor.
3. Received non-surgical treatment with a clearly defined treatment start date.
4. Availability of baseline and at least one follow-up imaging study (CT/MRI) of sufficient quality for AI-based segmentation and volumetric analysis.
5. Availability of key clinical data and follow-up outcome information.
6. For retrospective cohort: prior signed informed consent for biobank donation, agreeing to donate samples and data for medical research.
7. For prospective cohort: planned to receive or currently receiving non-surgical treatment, and able to provide written informed consent.

Exclusion Criteria:

1. Imaging data incomplete or of insufficient quality for accurate segmentation or volumetric calculation.
2. Key clinical information or follow-up outcome data missing.
3. Treatment start or baseline time point cannot be clearly determined.
4. Concurrent other malignancy that cannot be distinguished from the primary study tumor.
5. Severe underlying diseases (e.g., cardiac, pulmonary, renal insufficiency) that may significantly affect survival outcome assessment.
6. Cognitive impairment or other conditions that prevent cooperation with study procedures.
7. For prospective cohort: expected inability to complete follow-up.
8. Other conditions judged by the investigator as unsuitable for study inclusion. -