Tag : HEPATOCELLULAR CARCINOMA

CONFERENCE UPDATE

AI-driven multiple instance learning advances precision in HCC histological grading
Multiple instance learning (MIL) applied to whole slide images (WSIs) was shown to improve the accuracy and consistency of hepatocellular carcinoma (HCC) histological differentiation. By capturing spatial and contextual tissue patterns, this artificial intelligence (AI) approach offers a scalable, standardized solution to support pathologists, streamline diagnostic workflows, and potentially improve clinical decision-making in HCC management.
CONFERENCE UPDATE

MASLD drives persistent HCC risk despite HCV cure: Insights from a Japanese multicenter cohort study
MASLD drives persistent HCC risk despite HCV cure: Insights from a Japanese multicenter cohort study
CONFERENCE UPDATE

Multi-target blood test improves early detection of HCC: Evidence from the ALTUS prospective study
The prospective ALTUS study found that a multi-target HCC blood test (mt-HBT) outperformed ultrasound in detecting early- and very early-stage hepatocellular carcinoma (HCC). By providing operator-independent and scalable surveillance, mt-HBT offers a promising alternative to imaging, with the potential to enhance early detection, adherence, and clinical outcomes in at-risk patients.