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AI-Driven Tumor Response Evaluation for Solid Tumors

Shanghai Zhongshan Hospital · 2026
ClinicalTrials.gov · Datasets · License: Public Domain · 2026
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artificial-intelligencehepatocellular-carcinomaneoplasms
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.
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