Increasing the rate of datasets amenable to CTFFR and quantitative plaque analysis: Value of software for reducing stair-step artifacts demonstrated in photon-counting detector CT

Purpose

To determine the value of an algorithm for reducing stair-step artifacts for advanced coronary analyses in sequential mode coronary CT angiography (CCTA).

Methods

Forty patients undergoing sequential mode photon-counting detector CCTA with at least one stair-step artifact were included. Twenty patients (14 males; mean age 57±17years) with 45 segments showing stair-step artifacts and without atherosclerosis were included for CT_FFR analysis. Twenty patients (20 males; mean age 74±13years) with 22 segments showing stair-step artifacts crossing an atherosclerotic plaque were included for quantitative plaque analysis. Artifacts were graded, and CT_FFR and quantitative coronary plaque analyses were performed in standard reconstructions and in those reconstructed with a software (entitled ZeeFree) for artifact reduction.

Results

Stair-step artifacts were significantly reduced in ZeeFree compared to standard reconstructions (p<0.05). In standard reconstructions, CT_FFR was not feasible in 3/45 (7 %) segments but was feasible in all ZeeFree reconstructions. In 9/45 (20 %) segments without atherosclerosis, the ZeeFree algorithm led to a change of CT_FFR values from pathologic in standard to physiologic values in ZeeFree reconstructions. In one segment (1/22, 5 %), quantitative plaque analysis was not feasible in standard but only in ZeeFree reconstruction. The mean overall plaque volume (111±60 mm³), the calcific (77±47 mm³), fibrotic (31±28 mm³), and lipidic (4±3 mm³) plaque components were higher in standard than in ZeeFree reconstructions (overall 75±50 mm³, p<0.001; calcific 51±42 mm³, p<0.001; fibrotic 22±19 mm³, p<0.05; lipidic 3±3 mm³, p=0.055).

Conclusion

Despite the lack of reference standard modalities for CT_FFR and coronary plaque analysis, initial evidence indicates that an algorithm for reducing stair-step artifacts in sequential mode CCTA increases the rate and quality of datasets amenable to advanced coronary artery analysis, hereby potentially improving patient management.