Sensitivity of Myocardial Radiomic Features to Imaging Parameters in Cardiac MR Imaging.

BACKGROUND

Cardiac magnetic resonance (MR) images are often collected with different imaging parameters, which may impact the calculated values of myocardial radiomic features.

PURPOSE

To investigate the sensitivity of myocardial radiomic features to changes in imaging parameters in cardiac MR images.

STUDY TYPE

Prospective.

POPULATION

A total of 11 healthy participants/five patients.

FIELD STRENGTH/ SEQUENCE: A 3 T/cine balanced steady-state free-precession, T -weighted spoiled gradient-echo, T -weighted turbo spin-echo, and quantitative T and T mapping. For each sequence, the flip angle, in-plane resolution, slice thickness, and parallel imaging technique were varied to study the sensitivity of radiomic features to alterations in imaging parameters.

ASSESSMENT

Myocardial contours were manually delineated by experienced readers, and a total of 1023 radiomic features were extracted using PyRadiomics with 11 image filters and six feature families.

STATISTICAL TESTS

Sensitivity was defined as the standardized mean difference (D effect size), and the robust features were defined at sensitivity < 0.2. Sensitivity analysis was performed on predefined sets of reproducible features. The analysis was performed using the entire cohort of 16 subejcts.

RESULTS

64% of radiomic features were robust (sensitivity < 0.2) to changes in any imaging parameter. In qualitative sequences, radiomic features were most sensitive to changes in in-plane spatial resolution (spatial resolution: 0.6 vs. flip angle: 0.19, parallel imaging: 0.18, slice thickness: 0.07; P < 0.01 for all); in quantitative sequences, radiomic features were least sensitive to changes in spatial resolution (spatial resolution: 0.07 vs. slice thickness: 0.16, flip angle: 0.24; P < 0.01 for all). In an individual feature level, no singular feature family/image filter was identified as robust (sensitivity < 0.2) across sequences; however, highly sensitive features were predominantly associated with high-frequency wavelet filters across all sequences (32/50 features).

DATA CONCLUSION

In cardiac MR, a considerable number of radiomic features are sensitive to changes in sequence parameters.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 1.