Functionalized Anatomical Models for Computational Life Sciences.

Area of Science:

• Computational Life Sciences (CLS)
• Computational Anatomy
• Biomedical Simulation

Background:

• Static anatomical models are insufficient for applications requiring consideration of dynamic physiological changes.
• Examples include thermal risk assessment in MRI and cancer treatment planning, where breathing and thermoregulation affect outcomes.
• Existing models lack the ability to separate anatomical variability from physics and physiology.

Purpose of the Study:

• To introduce advanced functionalized anatomical models to overcome limitations of static models in CLS.
• To broaden the applicability of CLS in basic research, device/therapy development, and safety/efficacy assessment.
• To present the o2S2PARC platform for integrating heterogeneous computational models.

Main Methods:

• Functionalization of anatomical models through shape parametrization, physical property distributions, physiological dynamics, and integration of simulation/measurement data.
• Development of the o2S2PARC platform as an integration and sharing service for heterogeneous computational models.
• Integration of models from the NIH SPARC initiative within a unified computational environment.

Main Results:

• Functionalized models enhance realism by ensuring consistency between anatomy and functionalization layers.
• Validated functionalization layers can be used as standalone simulation tools, facilitating integration into larger models.
• The o2S2PARC platform enables the study of the peripheral nervous system's role in organ physiology.

Conclusions:

• Functionalized anatomical models represent a significant advancement in CLS, enabling higher levels of simulation realism.
• The functionalization concept provides a foundation for diverse CLS applications and integration with initiatives like the Physiome Project.
• The o2S2PARC platform facilitates the integration and sharing of computational models for comprehensive physiological studies.