AI-Based Quantification of MASH Histology for Drug Development
Quantifying fibrosis, steatosis, ballooning and inflammation with objective, reproducible metrics.
The HistoIndex q-Suite: A Complete Framework for MASH Histology Analysis
HistoIndex’s suite of AI-driven applications for MASH delivers objective, quantitative assessment of the four key histological features of the disease: fibrotic remodeling, hepatic fat accumulation, hepatocellular injury and inflammation.
The suite is anchored by our flagship fibrosis tool, qFibrosis®, and extends to qSteatosis®, qBallooning® & qInflammation®, delivering a comprehensive framework for evaluating disease severity. Together, these applications address the core histological endpoints that regulatory agencies such as the FDA consider when evaluating therapeutic efficacy in MASH clinical trials.
Beyond Conventional Semi-Quantitative Scoring
HistoIndex’s q-Suite translates complex tissue architecture into continuous, reproducible metrics, enabling precise disease characterization and sensitive treatment response evaluation.
By moving beyond conventional semi-quantitative scoring, it reduces subjectivity, improves sensitivity to change, supports robust longitudinal analysis, and strengthens confidence in trial endpoints by distinguishing true biological response from sampling variability.
Objective Metrics
Sensitive Detection
Track Over Time
Reliable Outcomes
q-Suite Imaging Techniques
qFibrosis®, qSteatosis®, and qBallooning® are developed and validated using SHG/TPEF imaging – a non-destructive approach that preserves tissue integrity and enables subsequent hematoxylin and eosin (H&E) staining on the same biopsy section – thereby supporting seamless integration across complementary imaging modalities, including qInflammation®, which is established on digitized H&E images.
Spatially Integrated Tissue Analysis
Notably, all four quantitative q-applications can be co-localized within the same tissue section, allowing analysis of how fibrosis, steatosis, ballooning, and inflammation interact within the liver microenvironment. By capturing these features in context rather than isolation, the q-Suite provides deeper insight into disease progression and reveals how therapeutic interventions modulate these interconnected processes.
