A scoping review of computational models on human glucose cerebral metabolism

Understanding cerebral metabolism is an essential undertaking to address brain health and tackle ambiguities in associated neurodegenerative diseases. Despite the abundance of detailed observational findings on specific functionalities of metabolism, there remains a gap in holistic understanding that could provide a suitable predictive framework, and hence be put to clinical use. Computational models can support such wider goals. Accordingly, we performed a scoping review of computational models on human cerebral glucose metabolism on the PubMed database. We selected 15 models on which we conducted a qualitative assessment of Verification based on reproducibility and internal validity; Validation for computational and biological relevance, sensitivity analysis and external validity; and Evaluation, where we inquired whether the model increased domain knowledge, with the capacity to be extended for improved generalizability. We raised critical shortcomings, including overall poor reproducibility, lack of internal and external validity, and certain unclear metabolic assumptions that compromised biological relevance. We proposed that for a computational model to improve its applicability such as predicting metabolic state through the human lifespan, Verification, Validation and Evaluation (VV&E) issues raised should be addressed, which would facilitate the involvement of disciplines beyond mathematics.