AI-Powered Preclinical Atherosclerosis Research

The APOE3-Leiden (E3L) and APOE3-Leiden.huCETP (E3L.CETP) mouse models are well-established, translational models for evaluating therapies targeting plasma lipids, lipoprotein metabolism, and atherosclerosis, with proven responsiveness to clinically used lipid-lowering drugs in both preventive and therapeutic study designs. AI-assisted assessment enhances these studies by standardizing lesion quantification, reducing inter- and intra-reader variability, and improving sensitivity to detect treatment effects. TNO Athero AI transforms routine H&E-stained aortic root sections into objective, quantitative datasets that strengthen confidence in your efficacy data.

Score with consistency
Increase scoring confidence by minimizing variability in atherosclerosis trials and research. TNO Athero AI ensures that every lesion is evaluated against the same objective criteria, eliminating the subjective differences that arise between human readers and across different reading sessions.

Segment and classify
TNO Athero AI accurately segments plaques and characterizes their composition, including necrotic core, calcification, fibrous tissue, and smooth muscle content. This detailed compositional analysis reveals treatment effects that conventional area-based measurements would miss entirely.

Efficient workflows
Speed up trials by reducing turnaround times through AI-assisted reading. Automated analysis processes hundreds of whole-slide images in a fraction of the time required for manual pathologist review, enabling faster data delivery without compromising quality or detail.

Precise and standardized plaque readout
TNO Athero AI segmentation enables precise and standardized plaque readout, accurately delineating lesion boundaries across the complete aortic root cross-section. Automated analysis reduces turnaround time and minimizes reader variability, while clear, color-coded outputs make results straightforward to interpret in atherosclerosis research and preclinical efficacy studies. Each plaque component is mapped with pixel-level precision, providing quantitative measurements that go far beyond what manual assessment can achieve. AI segmentation accurately delineates lesion boundaries across the complete aortic root cross-section, mapping each plaque component with pixel-level precision. Small, early-stage lesions are consistently detected.


Consistent detection of early-stage lesions
TNO Athero AI analysis helps ensure that even small, early-stage atherosclerotic lesions are consistently detected and accurately delineated across all study samples. In preventive study designs where lesion burden may be significantly reduced by effective treatment, this sensitivity is critical. The AI model reduces the risk of overlooked features and strengthens the reliability of lesion assessment within and across studies, ensuring that subtle but meaningful treatment effects are captured with statistical confidence.


How HistoSuite Works
By automating the most labor-intensive step in plaque assessment, TNOAthero AI compresses analysis windows from weeks to days ? without sacrificing depth, accuracy, or reproducibility.

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