Texture analysis of nonenhanced cine MR images accurately diagnosed large and small subacute and chronic myocardial infarction, with an area under the curve of 0.93 and 0.92, respectively.
Case-Control (n=180)
Blinded readers
Does texture analysis on nonenhanced cine MR images accurately diagnose subacute and chronic myocardial infarction compared to LGE imaging in patients undergoing cardiac MRI?
Texture analysis of nonenhanced cine MR images can accurately diagnose subacute and chronic myocardial infarction, potentially offering a diagnostic alternative that avoids gadolinium contrast.
Effect estimate: AUC 0.93 for large MI, 0.92 for small MI
p-value: p=<.001
Purpose To test whether texture analysis (TA) allows for the diagnosis of subacute and chronic myocardial infarction (MI) on noncontrast material–enhanced cine cardiac magnetic resonance (MR) images. Materials and Methods In this retrospective, institutional review board–approved study, 120 patients who underwent cardiac MR imaging and showed large transmural (volume of enhancement on late gadolinium enhancement LGE images >20%, n = 72) or small (enhanced volume ≤20%, n = 48) subacute or chronic ischemic scars were included. Sixty patients with normal cardiac MR imaging findings served as control subjects. Regions of interest for TA encompassing the left ventricle were drawn by two blinded, independent readers on cine images in end systole by using a freely available software package. Stepwise dimension reduction and texture feature selection based on reproducibility, machine learning, and correlation analyses were performed for selecting features, enabling the diagnosis of MI on nonenhanced cine MR images by using LGE imaging as the standard of reference. Results Five independent texture features allowed for differentiation between ischemic scar and normal myocardium on cine MR images in both subgroups: Teta1, Perc.01, Variance, WavEnHH.s-3, and S(5,5)SumEntrp (in patients with large MI: all P values < .001; in patients with small MI: Teta1 and Perc.01, P < .001; Variance, P = .026; WavEnHH.s-3, P = .007; S5,5SumEntrp, P = .045). Multiple logistic regression models revealed that combining the features Teta1 and Perc.01 resulted in the highest accuracy for diagnosing large and small MI on cine MR images, with an area under the curve of 0.93 and 0.92, respectively. Conclusion This proof-of-concept study indicates that TA of nonenhanced cine MR images allows for the diagnosis of subacute and chronic MI with high accuracy. © RSNA, 2017 Online supplemental material is available for this article.
Baeßler et al. (Thu,) conducted a case-control in Subacute and chronic myocardial infarction (n=180). Texture analysis on nonenhanced cine MR images vs. Late gadolinium enhancement (LGE) imaging was evaluated on Diagnosis of large and small MI on cine MR images (AUC 0.93 for large MI, 0.92 for small MI, p=<.001). Texture analysis of nonenhanced cine MR images accurately diagnosed large and small subacute and chronic myocardial infarction, with an area under the curve of 0.93 and 0.92, respectively.