acePeritumoral ultrasound-driven multimodal AI model for predicting lymphovascular space invasion and prognosis in cervical cancer
Purpose Accurate preoperative assessment of lymphovascular space invasion (LVSI) in cervical cancer (CC) remains challenging despite its importance for treatment planning and risk stratification. This study aimed to develop and evaluate a hybrid model integrating peritumoral ultrasound radiomics features, deep learning features, and clinical data for preoperative prediction of LVSI in CC. Additionally, we assessed the model's prognostic value for disease-free survival (DFS) and explored LVSI-associated molecular…
A hybrid model combining peritumoral ultrasound radiomics, deep learning scores and clinical data predicted lymphovascular space invasion in a prospective cohort better than single-modality models.
The authors state that further validation in larger independent multicenter cohorts is needed before clinical application, and the prospective test set was small with a wide confidence interval.
Evidence
- Peer-reviewedAbdominal Radiology2026-10-08
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Truvace Impact Record TRV-2026-1721, v1: “Peritumoral ultrasound-driven multimodal AI model for predicting lymphovascular space invasion and prognosis in cervical cancer.” Truvace, 2026-10-17. /record/TRV-2026-1721 (accessed at citation time). sha256 b367ca28aa8a4179…
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