Schofield, R;
Ganeshan, B;
Fontana, M;
Nasis, A;
Castelletti, S;
Rosmini, S;
Treibel, TA;
... Moon, JC; + view all
(2019)
Texture Analysis of Cardiovascular Magnetic Resonance Cine Images differentiates etiologies of left ventricular hypertrophy.
Clinical Radiology
, 74
(2)
pp. 140-149.
10.1016/j.crad.2018.09.016.
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Ganeshan_Texture Analysis of Cardiovascular Magnetic Resonance Cine Images differentiates etiologies of left ventricular hypertrophy_AAM.pdf - Accepted Version Download (1MB) | Preview |
Abstract
BACKGROUND: Textural analysis (TA) shows promise as radiological biomarker. The use of native TA in the field of cardiology is unproven. We hypothesized that Cardiovascular Magnetic Resonance pre-contrast bSSFP cine images could be analysed using TA software; TA features would differentiate different aetiologies of disease causing increased myocardial wall thickness (left ventricular hypertrophy {LVH}) and indicate the severity of myocardial tissue abnormality. METHOD: A mid short axis pre-contrast cine frame of 216 cases (50 hypertrophic cardiomyopathy (predominantly LVOTO sub type) (HCM), 52 cardiac amyloid (predominantly AL sub-type) (CA), 68 aortic stenosis (AS), 15 hypertensive with LVH (HTN+LVH) and 31 healthy volunteers (HV)) underwent CMRTA using TexRAD (TexRAD Ltd, Cambridge, UK). Among HV, 16/ 31 were scanned twice to form a test-retest reproducibility cohort. CMRTA comprised a filtration-histogram technique to extract and quantify features using 6 parameters. RESULTS: Test-retest analysis in HV showed a medium filter (3mm) was the most reproducible (intra-class correlation of 0.9 for kurtosis and skewness and 0.8 for mean and SD). Disease cohorts were statistically different (p<0.001) to health for all parameters. Pair wise comparisons of CMRTA parameters showed kurtosis and skewness consistently significant in ranking degree of difference from HV (greatest to least); CA, HCM, LVH+HTN, AS (p<0.001). Similarly mean, SD, entropy and mean positive pixel (MPP) were consistent in ranking degree of difference from HV; HCM, CA, AS and HTN+LVH. CONCLUSION: Radiomic features of bSSFP CMR data sets, derived using TA, show promise in discriminating between aetiologies of LVH.
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