Skip to main content

2019 | OriginalPaper | Buchkapitel

Learning Associations Between Clinical Information and Motion-Based Descriptors Using a Large Scale MR-derived Cardiac Motion Atlas

verfasst von : Esther Puyol-Antón, Bram Ruijsink, Hélène Langet, Mathieu De Craene, Paolo Piro, Julia A. Schnabel, Andrew P. King

Erschienen in: Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The availability of large scale databases containing imaging and non-imaging data, such as the UK Biobank, represents an opportunity to improve our understanding of healthy and diseased bodily function. Cardiac motion atlases provide a space of reference in which the motion fields of a cohort of subjects can be directly compared. In this work, a cardiac motion atlas is built from cine MR data from the UK Biobank (\(\approx \) 6000 subjects). Two automated quality control strategies are proposed to reject subjects with insufficient image quality. Based on the atlas, three dimensionality reduction algorithms are evaluated to learn data-driven cardiac motion descriptors, and statistical methods used to study the association between these descriptors and non-imaging data. Results show a positive correlation between the atlas motion descriptors and body fat percentage, basal metabolic rate, hypertension, smoking status and alcohol intake frequency. The proposed method outperforms the ability to identify changes in cardiac function due to these known cardiovascular risk factors compared to ejection fraction, the most commonly used descriptor of cardiac function. In conclusion, this work represents a framework for further investigation of the factors influencing cardiac health.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Bai, W., Shi, W., et al.: A bi-ventricular cardiac atlas built from 1000+ high resolution MR images of healthy subjects and an analysis of shape and motion. Med. Image Anal. 26(1), 133–145 (2015) CrossRef Bai, W., Shi, W., et al.: A bi-ventricular cardiac atlas built from 1000+ high resolution MR images of healthy subjects and an analysis of shape and motion. Med. Image Anal. 26(1), 133–145 (2015) CrossRef
3.
Zurück zum Zitat Hotelling, H.: Analysis of a complex of statistical variables into principal components. J. Educ. Psychol. 24(6), 417 (1933) CrossRef Hotelling, H.: Analysis of a complex of statistical variables into principal components. J. Educ. Psychol. 24(6), 417 (1933) CrossRef
5.
Zurück zum Zitat Jitnarin, N., Kosulwat, V., Rojroongwasinkul, N., et al.: The relationship between smoking, body weight, body mass index, and dietary intake among Thai adults: results of the National Thai Food Consumption Survey. Asia Pac. J. Public Health 26(5), 481–493 (2014) CrossRef Jitnarin, N., Kosulwat, V., Rojroongwasinkul, N., et al.: The relationship between smoking, body weight, body mass index, and dietary intake among Thai adults: results of the National Thai Food Consumption Survey. Asia Pac. J. Public Health 26(5), 481–493 (2014) CrossRef
6.
Zurück zum Zitat Mukamal, K., Chiuve, S., Rimm, E.: Alcohol consumption and risk for coronary heart disease in men with healthy lifestyles. Arch. Intern. Med. 166(19), 2145–2150 (2006) CrossRef Mukamal, K., Chiuve, S., Rimm, E.: Alcohol consumption and risk for coronary heart disease in men with healthy lifestyles. Arch. Intern. Med. 166(19), 2145–2150 (2006) CrossRef
7.
Zurück zum Zitat Nadruz, W., Claggett, B., Gonçalves, A., et al.: Smoking and cardiac structure and function in the elderlyclinical perspective: the ARIC study (atherosclerosis risk in communities). Circ. Cardiovasc. Imaging 9(9), e004950 (2016) Nadruz, W., Claggett, B., Gonçalves, A., et al.: Smoking and cardiac structure and function in the elderlyclinical perspective: the ARIC study (atherosclerosis risk in communities). Circ. Cardiovasc. Imaging 9(9), e004950 (2016)
9.
Zurück zum Zitat Oksuz, I., Ruijsink, B., Puyol-Antón, E., et al.: Automatic left ventricular outflow tract classification for accurate cardiac MR planning, pp. 462–465 (2018) Oksuz, I., Ruijsink, B., Puyol-Antón, E., et al.: Automatic left ventricular outflow tract classification for accurate cardiac MR planning, pp. 462–465 (2018)
10.
Zurück zum Zitat Peressutti, D., Sinclair, M., et al.: A framework for combining a motion atlas with non-motion information to learn clinically useful biomarkers: application to cardiac resynchronisation therapy response prediction. Med. Image Anal. 35, 669–684 (2017) CrossRef Peressutti, D., Sinclair, M., et al.: A framework for combining a motion atlas with non-motion information to learn clinically useful biomarkers: application to cardiac resynchronisation therapy response prediction. Med. Image Anal. 35, 669–684 (2017) CrossRef
11.
Zurück zum Zitat Petersen, S., Matthews, P., Francis, J., et al.: UK biobank’s cardiovascular magnetic resonance protocol. J. Cardiovasc. Magn. Reson. 18(1), 8 (2016) CrossRef Petersen, S., Matthews, P., Francis, J., et al.: UK biobank’s cardiovascular magnetic resonance protocol. J. Cardiovasc. Magn. Reson. 18(1), 8 (2016) CrossRef
12.
Zurück zum Zitat Roweis, S., Saul, L.: Nonlinear dimensionality reduction by locally linear embedding. Science 290(5500), 2323–2326 (2000) CrossRef Roweis, S., Saul, L.: Nonlinear dimensionality reduction by locally linear embedding. Science 290(5500), 2323–2326 (2000) CrossRef
13.
Zurück zum Zitat Rueckert, D., Sonoda, L., et al.: Nonrigid registration using free-form deformations: application to breast MR images. IEEE Trans. Med. Imag. 18(8), 712–721 (1999) CrossRef Rueckert, D., Sonoda, L., et al.: Nonrigid registration using free-form deformations: application to breast MR images. IEEE Trans. Med. Imag. 18(8), 712–721 (1999) CrossRef
14.
Zurück zum Zitat Sinclair, M., Bai, W., Puyol-Antón, E., Oktay, O., Rueckert, D., King, A.P.: Fully automated segmentation-based respiratory motion correction of multiplanar cardiac magnetic resonance images for large-scale datasets. In: Descoteaux, M., Maier-Hein, L., Franz, A., Jannin, P., Collins, D.L., Duchesne, S. (eds.) MICCAI 2017. LNCS, vol. 10434, pp. 332–340. Springer, Cham (2017). https://​doi.​org/​10.​1007/​978-3-319-66185-8_​38 CrossRef Sinclair, M., Bai, W., Puyol-Antón, E., Oktay, O., Rueckert, D., King, A.P.: Fully automated segmentation-based respiratory motion correction of multiplanar cardiac magnetic resonance images for large-scale datasets. In: Descoteaux, M., Maier-Hein, L., Franz, A., Jannin, P., Collins, D.L., Duchesne, S. (eds.) MICCAI 2017. LNCS, vol. 10434, pp. 332–340. Springer, Cham (2017). https://​doi.​org/​10.​1007/​978-3-319-66185-8_​38 CrossRef
15.
Zurück zum Zitat Vincent, P., Larochelle, H., Lajoie, I., Bengio, Y., Manzagol, P.A.: Stacked denoising autoencoders: learning useful representations in a deep network with a local denoising criterion. J. Mach. Learn. Res. 11, 3371–3408 (2010) MathSciNetMATH Vincent, P., Larochelle, H., Lajoie, I., Bengio, Y., Manzagol, P.A.: Stacked denoising autoencoders: learning useful representations in a deep network with a local denoising criterion. J. Mach. Learn. Res. 11, 3371–3408 (2010) MathSciNetMATH
Metadaten
Titel
Learning Associations Between Clinical Information and Motion-Based Descriptors Using a Large Scale MR-derived Cardiac Motion Atlas
verfasst von
Esther Puyol-Antón
Bram Ruijsink
Hélène Langet
Mathieu De Craene
Paolo Piro
Julia A. Schnabel
Andrew P. King
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-030-12029-0_11