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04.05.2018 | Cardiac

LGE-CMR-derived texture features reflect poor prognosis in hypertrophic cardiomyopathy patients with systolic dysfunction: preliminary results

verfasst von: Sainan Cheng, Mengjie Fang, Chen Cui, Xiuyu Chen, Gang Yin, Sanjay K. Prasad, Di Dong, Jie Tian, Shihua Zhao

Erschienen in: European Radiology | Ausgabe 11/2018

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Abstract

Objectives

To evaluate the prognostic value of texture features based on late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) images in hypertrophic cardiomyopathy (HCM) patients with systolic dysfunction.

Methods

67 HCM patients with systolic dysfunction (41 male and 26 female, mean age ± standard deviation, 46.20 years ± 13.38) were enrolled. All patients underwent 1.5 T CMR cine and LGE imaging. Texture features were extracted from LGE images. Cox proportional hazard analysis and Kaplan-Meier analysis were used to determine the association of texture features and traditional parameters with event free survival.

Results

Family history (hazard ratio [HR]=2.558, 95 % confidence interval [CI]=1.060–6.180), NYHA III-IV (HR=5.627, CI=1.652–19.173), left ventricular ejection fraction (HR=0.945, CI=0.902–0.991), left ventricular end-diastolic volume index (HR=1.006, CI=1.000–1.012), LGE extent (HR=1.911, CI=1.348–2.709) and three texture parameters [X0_H_skewness (HR=0.783, CI=0.691–0.889), X0_GLCM_cluster_tendency (HR=0.735, CI=0.616–0.877) and X0_GLRLM_energy (HR=1.344, CI=1.173–1.540)] were significantly associated with event free survival in univariate analysis (p<0.05). The HR of LGE extent (HR=1.548 [CI=1.046–2.293], 1.650 [CI=1.122–2.428] and 1.586 [CI=1.044–2.409] per 10 % increase, p<0.05) remained significant when adjusted by one of the three texture features.

Conclusion

Increased LGE heterogeneity (higher X0_GLRLM_energy, lower X0_H_skewness and lower X0_GLCM_cluster_tendency) was associated with adverse events in HCM patients with systolic dysfunction.

Key Points

• Textural analysis from CMR can be applied in HCM.

• Texture features derived from LGE images can capture fibrosis heterogeneity.

• CMR texture analysis provides prognostic information in HCM patients.

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Semsarian C, Ingles J, Maron MS, Maron BJ (2015) New perspectives on the prevalence of hypertrophic cardiomyopathy. J Am Coll Cardiol 65:1249–1254CrossRef

Maron BJ, Ommen SR, Semsarian C, Spirito P, Olivotto I, Maron MS (2014) Hypertrophic cardiomyopathy: present and future, with translation into contemporary cardiovascular medicine. J Am Coll Cardiol 64:83–99CrossRef

American College of Cardiology Foundation Task Force on Expert Consensus Documents, Hundley WG, Bluemke DA et al (2010) ACCF/ACR/AHA/NASCI/SCMR 2010 expert consensus document on cardiovascular magnetic resonance: a report of the American College of Cardiology Foundation Task Force on Expert Consensus Documents. J Am Coll Cardiol 55:2614–2662

Choudhury L, Mahrholdt H, Wagner A et al (2002) Myocardial scarring in asymptomatic or mildly symptomatic patients with hypertrophic cardiomyopathy. J Am Coll Cardiol 40:2156–2164CrossRef

O'Hanlon R, Grasso A, Roughton M et al (2010) Prognostic significance of myocardial fibrosis in hypertrophic cardiomyopathy. J Am Coll Cardiol 56:867–874CrossRef

Rubinshtein R, Glockner JF, Ommen SR et al (2010) Characteristics and clinical significance of late gadolinium enhancement by contrast-enhanced magnetic resonance imaging in patients with hypertrophic cardiomyopathy. Circ Heart Fail 3:51–58

Green JJ, Berger JS, Kramer CM, Salerno M (2012) Prognostic value of late gadolinium enhancement in clinical outcomes for hypertrophic cardiomyopathy. JACC Cardiovasc Imaging 5:370–377CrossRef

Chan RH, Maron BJ, Olivotto I et al (2014) Prognostic value of quantitative contrast-enhanced cardiovascular magnetic resonance for the evaluation of sudden death risk in patients with hypertrophic cardiomyopathy. Circulation 130:484–495

Kim JH, Ko ES, Lim Y et al (2017) Breast Cancer Heterogeneity: MR Imaging Texture Analysis and Survival Outcomes. Radiology 282:665–675CrossRef

10.

Pickles MD, Lowry M, Gibbs P (2016) Pretreatment Prognostic Value of Dynamic Contrast-Enhanced Magnetic Resonance Imaging Vascular, Texture, Shape, and Size Parameters Compared With Traditional Survival Indicators Obtained From Locally Advanced Breast Cancer Patients. Invest Radiol 51:177–185CrossRef

11.

Kickingereder P, Burth S, Wick A et al (2016) Radiomic Profiling of Glioblastoma: Identifying an Imaging Predictor of Patient Survival with Improved Performance over Established Clinical and Radiologic Risk Models. Radiology 280:880–889CrossRef

12.

Yoon SH, Park CM, Park SJ, Yoon JH, Hahn S, Goo JM (2016) Tumor Heterogeneity in Lung Cancer: Assessment with Dynamic Contrast-enhanced MR Imaging. Radiology 280(3):940–948CrossRef

13.

Ng F, Ganeshan B, Kozarski R, Yoon JH, Hahn S, Goo JM (2013) Assessment of primary colorectal cancer heterogeneity by using whole-tumor texture analysis: contrast-enhanced CT texture as a biomarker of 5-year survival. Radiology 266:177–184CrossRef

14.

Gillies RJ, Kinahan PE, Hricak H (2015) Radiomics: images are more than pictures, they are data. Radiology 278:563–577CrossRef

15.

Authors/Task Force members, Elliott PM, Anastasakis A et al (2014) 2014 ESC Guidelines on diagnosis and management of hypertrophic cardiomyopathy: the Task Force for the Diagnosis and Management of Hypertrophic Cardiomyopathy of the European Society of Cardiology (ESC). Eur Heart J 35:2733–2779

16.

Goto D, Kinugawa S, Hamaguchi S et al (2013) Clinical characteristics and outcomes of dilated phase of hypertrophic cardiomyopathy: report from the registry data in Japan. J Cardiol 61:65–70CrossRef

17.

Lang RM, Badano LP, Mor-Avi V et al (2015) Recommendations for cardiac chamber quantification by echocardiography in adults: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. Eur Heart J Cardiovasc Imaging 16:233–270CrossRef

18.

Schulz-Menger J, Bluemke DA, Bremerich J et al (2013) Standardized image interpretation and post processing in cardiovascular magnetic resonance: Society for Cardiovascular Magnetic Resonance (SCMR) board of trustees task force on standardized post processing. J Cardiovasc Magn Reson 15(1):35CrossRef

19.

Moravsky G, Ofek E, Rakowski H et al (2013) Myocardial fibrosis in hypertrophic cardiomyopathy: accurate reflection of histopathological findings by CMR. JACC Cardiovasc Imaging 6:587–596PubMed

20.

Maron M, Appelbaum E, Harrigan C et al (2008) Clinical profile and significance of delayed enhancement in hypertrophic cardiomyopathy. Circ Heart Fail 1:184–191CrossRef

21.

Elliott PM, Poloniecki J, Dickie S et al (2000) Sudden death in hypertrophic cardiomyopathy: identification of high risk patients. J Am Coll Cardiol 36:2212–2218CrossRef

22.

Hicks KA, Tcheng JE, Bozkurt B et al (2015) 2014 ACC/AHA Key Data Elements and Definitions for Cardiovascular Endpoint Events in Clinical Trials: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Data Standards (Writing Committee to Develop Cardiovascular Endpoints Data Standards). J Am Coll Cardiol 66:403–469

23.

Ismail TF, Jabbour A, Gulati A et al (2014) Role of late gadolinium enhancement cardiovascular magnetic resonance in the risk stratification of hypertrophic cardiomyopathy. Heart 100:1851–1858CrossRef

24.

Giganti F, Antunes S, Salerno A et al (2017) Gastric cancer: texture analysis from multidetector computed tomography as a potential preoperative prognostic biomarker. Eur Radiol 27:1831–1839CrossRef

25.

Thévenin FS, Drapé JL, Biau D et al (2010) Assessment of vascular invasion by bone and soft tissue tumours of the limbs: usefulness of MDCT angiography. Eur Radiol 20:1524–1531CrossRef

26.

Ng F, Ganeshan B, Kozarski R, Miles KA, Goh V (2013) Assessment of primary colorectal cancer heterogeneity by using whole-tumor texture analysis: contrast-enhanced CT texture as a biomarker of 5-year survival. Radiology 266:177–184CrossRef

27.

Machii M, Satoh H, Shiraki K et al (2014) Distribution of late gadolinium enhancement in end-stage hypertrophic cardiomyopathy and dilated cardiomyopathy: differential diagnosis and prediction of cardiac outcome. Magn Reson Imaging 32:118–124CrossRef

28.

29.

Maron BJ, Maron MS (2016) LGE Means Better Selection of HCM Patients for Primary Prevention Implantable Defibrillators. JACC Cardiovasc Imaging 9:1403–1406CrossRef

30.

Galati G, Leone O, Pasquale F et al (2016) Histologic and histometric characterization of myocardial fibrosis in end-stage hypertrophic cardiomyopathy: a clinical-pathological study of 30 explanted hearts. Circ Heart Fail 9:e003090

31.

Wu KC (2017) Sudden Cardiac Death Substrate Imaged by Magnetic Resonance Imaging: From Investigational Tool to Clinical Applications. Circ Cardiovasc Imaging 10(7):e005461CrossRef

32.

Harris KM, Spirito P, Maron MS et al (2006) Prevalence, clinical profile, and significance of left ventricular remodeling in the end-stage phase of hypertrophic cardiomyopathy. Circulation 114:216–225CrossRef

Titel: LGE-CMR-derived texture features reflect poor prognosis in hypertrophic cardiomyopathy patients with systolic dysfunction: preliminary results
verfasst von: Sainan Cheng
Mengjie Fang
Chen Cui
Xiuyu Chen
Gang Yin
Sanjay K. Prasad
Di Dong
Jie Tian
Shihua Zhao
Publikationsdatum: 04.05.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: European Radiology / Ausgabe 11/2018
Print ISSN: 0938-7994
Elektronische ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-018-5391-5

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LGE-CMR-derived texture features reflect poor prognosis in hypertrophic cardiomyopathy patients with systolic dysfunction: preliminary results