In silico Imaging studies provide a viable source of regulatory evidence for evaluating imaging devices, according to an analysis by the U.S. Food and Drug Administration (FDA) published on August 9 in Plos, computational biology.

In connection with medical devices, a in silico “An ISCT clinical trial is a computer-based investigation that evaluates a medical intervention using a cohort of computer-based patient models,” wrote lead author Dr. Pras Pathmanathan, a senior FDA investigator, and colleagues.

Although a in silico Although digital breast tomosynthesis (DBT) is a new method for evaluating medical devices that uses computer-aided modeling and simulation (M&S), little information is available on how to ensure the reliability of these studies, the authors said. They highlighted the ISCT Virtual Imaging Clinical Trial for Regulatory Evaluation (VICTRE) project, which compared digital breast tomosynthesis (DBT) with full-field digital mammography (FFDM) in one of eight ISCT examples presented.

For that The study created a cohort of 3,000 synthetic breast phantoms by sampling a mathematical anatomical model, the researchers noted. Then, FFDM and DBT images were simulated using a physics-based Monte Carlo X-ray transport code. Finally, the detectability of lesions inside the breasts was assessed using mathematical model observers (i.e., a clinician model).

“The results of the ISCT were positive compared to the results of an existing clinical trial used as a reference, suggesting that in silico Imaging studies provide a viable source of regulatory evidence in the evaluation of imaging devices,” wrote Pathmanathan and colleagues.

ISCTs have many potential applications, including expanding or reducing the size of real-world clinical trials and supporting study design through improved inclusion and exclusion criteria, the authors explained. Their paper reveals processes and standard approaches to ensure the credibility of in silico test results and explains what verification, validation and uncertainty quantification mean in this context.

The document complements FDA’s recently published November 2023 guidance on “Evaluating the Credibility of Computational Modeling and Simulation in Medical Device Submissions” and the “Model Credibility Regulatory Science Tool.”

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