European Radiology: Eliminating Bias: FFRCT in Diabetic Patients

At this stage , cardiovascular disease remains the leading cause of death and disability in people with diabetes (DM) .

At this stage , cardiovascular disease remains the leading cause of death and disability in people with diabetes (DM) .

In recent years, techniques based on coronary CT angiography (CCTA) images and applying principles of computational fluid dynamics or machine learning (ML) algorithms to calculate coronary flow and pressure over the entire length of the coronary vessel are promising non-invasive imaging tools .

Recently, a study published in the journal European Radiology evaluated the difference between the diagnostic accuracy of FFR _CT CT in patients with DM and those without DM using invasive FFR as a reference standard, and also explored the difference between CCTA and coronary artery calcium score.

This study retrospectively analyzed 484 patients with suspected or known coronary artery disease from 11 Chinese medical centers

The sensitivity, specificity, accuracy, and AUC of FFR _CT CT were 0.

Representative cases of the DM group and the non-DM group .

Representative cases of the DM group and the non-DM group .

In conclusion, the diagnostic accuracy of FFR _CT CT was not affected by DM, coronary stenosis, and calcification

Original source :

Yi Xue , Min Wen Zheng , Yang Hou , et al .

Yi Xue Min Wen Zheng Yang Hou , et al Influence of diabetes mellitus on the diagnostic performance of machine learning-based coronary CT angiography-derived fractional flow reserve: a multicenter study 10.
1007/s00330-021-08468-7 10.
1007/s00330-021- 08468-7

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