Universität zu Köln

Baessler, Bettina ORCID: 0000-0002-3244-3864, Mannil, Manoj, Maintz, David, Alkadhi, Hatem and Manka, Robert (2018). Texture analysis and machine learning of non-contrast T1-weighted MR images in patients with hypertrophic cardiomyopathy-Preliminary results. Eur. J. Radiol., 102. S. 61 - 68. CLARE: ELSEVIER IRELAND LTD. ISSN 1872-7727

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Abstract

Purpose: To test in a first proof-of-concept study whether texture analysis (TA) allows for the detection of myocardial tissue alterations in hypertrophic cardiomyopathy (HCM) on non-contrast T1-weighted cardiac magnetic resonance (CMR) images using machine learning based approaches. Methods: This retrospective, IRB-approved study included 32 patients with known HCM. Thirty patients with normal CMR served as controls. Regions-of-interest for TA encompassing the left ventricle were drawn on short-axis non-contrast T1-weighted images using a freely available software package. Step-wise dimension reduction and texture feature selection was performed for selecting features enabling the detection of myocardial tissue alterations in HCM patients on non-contrast T1-weighted CMR images. Results: Comparing HCM patients and controls, four texture features were identified showing significant differences between groups (Grey-level Non-uniformity [GLevNonU]: 74 +/- 17 vs. 38 +/- 9, p < .001; Energy of wavelet coefficients in low-frequency sub-bands [WavEnLL]: 58 +/- 5 vs. 48 +/- 10, p < .001; Fraction: 0.70 +/- 0.07 vs. 0.78 +/- 0.05, p < .001; Sum Average: 16.6 +/- 0.4 vs. 17.0 +/- 0.5, p = .007). A model containing the single parameter GLevNonU proved to be the best for differentiating between HCM patients and controls with a sensitivity/specificity of 91%/93%. A cut-off of GLevNonU >= 46 allowed for distinguishing HCM patients from controls with a sensitivity/specificity of 94%/90%. Even in patients without late gadolinium enhancement (LGE), the defined cut-off led to a differentiation of LGE-patients from healthy controls with 100% sensitivity and 90% specificity. Conclusions: TA on non-contrast T1-weighted images allows for the detection of myocardial tissue alterations in the setting of HCM with excellent accuracy, delivering potential novel parameters for a non-contrast assessment of myocardial texture alterations.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Baessler, Bettina UNSPECIFIED orcid.org/0000-0002-3244-3864 UNSPECIFIED Mannil, Manoj UNSPECIFIED UNSPECIFIED UNSPECIFIED Maintz, David UNSPECIFIED UNSPECIFIED UNSPECIFIED Alkadhi, Hatem UNSPECIFIED UNSPECIFIED UNSPECIFIED Manka, Robert UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-188043
DOI:	10.1016/j.ejrad.2018.03.013
Journal or Publication Title:	Eur. J. Radiol.
Volume:	102
Page Range:	S. 61 - 68
Date:	2018
Publisher:	ELSEVIER IRELAND LTD
Place of Publication:	CLARE
ISSN:	1872-7727
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language CARDIOVASCULAR MAGNETIC-RESONANCE; LATE GADOLINIUM ENHANCEMENT; MYOCARDIAL-INFARCTION; FEATURE-SELECTION; CLASSIFICATION; FIBROSIS; DIFFERENTIATION; PERFORMANCE; MANAGEMENT; DIAGNOSIS Multiple languages Radiology, Nuclear Medicine & Medical Imaging Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/18804