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EUS-Anchored Multimodal Evaluation of Pancreatic Cystic Lesions: Toward a Conceptual Diagnostic Framework

Year: 2026
Type: article
Abstract: Pancreatic cystic lesions (PCLs) represent a growing clinical challenge due to their diverse biological behaviors and the substantial overlap in imaging features between benign, premalignant, and malignant entities. Traditional diagnostic approaches relying on cross-sectional imaging or isolated morphologic criteria frequently fail to achieve adequate risk discrimination. Advances in endoscopic ultrasound (EUS) now permit detailed morphologic assessment complemented by cyst-fluid biochemical markers, proteomic signatures, and comprehensive genomic profiling using next-generation sequencing. Parallel progress in artificial intelligence (AI) further strengthens diagnostic precision by integrating EUS features with multimodal biomarker data to reduce subjectivity and support individualized clinical decision-making. This review introduces an EUS-based multimodal diagnostic framework of PCLs that integrates morphological evaluation, cyst-fluid biochemical testing, molecular profiling, and AI-assisted analysis. By synthesizing current evidence, we outline how the integrative approach enhances diagnostic accuracy, biological interpretability, and individualized risk stratification for PCLs.
Language: English
Subfield: Oncology
Field: Medicine
Open Access status: gold
Estimated APC paid: $3,137
OpenAlex ID: W7161626401
FWCI:
Cites: 78
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