2021
DOI: 10.1002/jmri.27581
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Sensitivity of Myocardial Radiomic Features to Imaging Parameters in Cardiac MR Imaging

Abstract: 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, T1‐weighted spoiled gradient‐echo, T2‐weighted turbo… Show more

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Cited by 16 publications
(9 citation statements)
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References 28 publications
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“…Across all analyses, first order and gray level co-occurrence matrix were the most frequently identified reproducible radiomic feature classes. Another CMR imaging study by Jang et al 57 has evaluated, in a group of healthy participants and in a heterogeneous group of patients, the sensitivity of radiomic features estimate to changes in acquisition sequence parameters including flip angle, in-plane spatial resolution, slice thickness, and parallel imaging technique. As a whole, they have found that approximately 60% of the 4007 considered radiomic features were robust to changes in any acquisition parameters (i.e., standardized Cohen’s mean difference < 0.2), with qualitative acquisition sequences (i.e., cine balanced steady-state free-precession, T1-weighted spoiled gradient-echo, T2-weighted turbo spin-echo) and quantitative T1/T2 mapping most sensitive to changes in in-plane spatial resolution and flip angle, respectively.…”
Section: Introductionmentioning
confidence: 99%
“…Across all analyses, first order and gray level co-occurrence matrix were the most frequently identified reproducible radiomic feature classes. Another CMR imaging study by Jang et al 57 has evaluated, in a group of healthy participants and in a heterogeneous group of patients, the sensitivity of radiomic features estimate to changes in acquisition sequence parameters including flip angle, in-plane spatial resolution, slice thickness, and parallel imaging technique. As a whole, they have found that approximately 60% of the 4007 considered radiomic features were robust to changes in any acquisition parameters (i.e., standardized Cohen’s mean difference < 0.2), with qualitative acquisition sequences (i.e., cine balanced steady-state free-precession, T1-weighted spoiled gradient-echo, T2-weighted turbo spin-echo) and quantitative T1/T2 mapping most sensitive to changes in in-plane spatial resolution and flip angle, respectively.…”
Section: Introductionmentioning
confidence: 99%
“…We observed that only a few radiomic features were common among different cross-validations in the Radiomics model (Additional file 2 : Table S2) or the DL-Radiomics model (Additional file 2 : Table S3). Despite differences in important radiomics features between different cross-validation splits, the performance was consistent across the different cross-validation splits, which is expected given the high correlation among the radiomic features [ 37 , 38 ]. We also observed similar differences between the selected important radiomic features between the DL-Radiomics and Radiomics models.…”
Section: Discussionmentioning
confidence: 85%
“…103,104 Despite the promises of radiomic imaging as a novel approach to extract imaging markers with diagnostic and prognostic value beyond standard cardiac MR parameters, there are challenges in the standardization of feature extraction, selection, and model development. Additionally, reproducibility and sensitivity in radiomics remain major research topics, with recent data showing moderate reproducibility, 105,106 sensitivity to imaging sequence parameters, 107 and sensitivity to image acquisition timing in the cardiac cycle. 108 The clinical utility and robustness of radiomic imaging markers should be further investigated using rigorous multicenter and multivendor studies.…”
Section: Radiomics Analysismentioning
confidence: 99%