Why the study?
Does a two-step precision risk prediction technology using MRI/PET fusion and a supervised classifier improve prediction of sudden cardiac death in patients with cardiac sarcoidosis?
Population
45 patients with cardiac sarcoidosis
Comparison
Personalized MRI and PET fusion mechanistic modeling with a supervised classifier vs clinical metrics
Design
Retrospective study
Authors
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May support SCD risk stratification in cardiac sarcoidosis; leaves open prospective validation before clinical use.
Does a two-step precision risk prediction technology using MRI/PET fusion and a supervised classifier improve prediction of sudden cardiac death in patients with cardiac sarcoidosis?
A novel personalized MRI and PET fusion mechanistic model combined with a supervised classifier showed promising performance (AUC 0.754) for predicting sudden cardiac death risk in cardiac sarcoidosis, outperforming standard clinical metrics.
Shade et al. (2021) studied this question.
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