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Orthogonal Shape Modes Describing Clinical Indices of Remodeling

  • Xingyu Zhang
  • Bharath Ambale-Venkatesh
  • David A. Bluemke
  • Brett R. Cowan
  • J. Paul Finn
  • William G. Hundley
  • Alan H. Kadish
  • Daniel C. Lee
  • Joao A.C. Lima
  • Avan Suinesiaputra
  • Alistair A. Young
  • Pau Medrano-Gracia
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9126)

Abstract

Quantification of the left ventricle (LV) shape changes (remodeling) is of great importance for therapeutic management of myocardial infarction. Orthogonal shape modes derived from principal component analysis (PCA) often do not describe clinical remodeling indices. We developed a method for deriving orthogonal shape modes directly from any set of clinical indices. Cardiac magnetic resonance images of 1,991 asymptomatic volunteers from the MESA study (age 44−84, mean age 62, 52 % women) and 300 patients with myocardial infarction from the DETERMINE study (age 31−86, mean age 63, 20 % women) were obtained from the Cardiac Atlas Project. Clinical indices of LV size, sphericity, wall thickness and apical conicity were calculated. For each index, cases outside two standard deviations of the mean, but within one standard deviation for all other indices, were chosen as a representative subgroup. Orthogonal modes were defined sequentially, using the first principal component of each subgroup. At each step, the contribution of the previous mode was removed mathematically from the shape description, similar to Gram–Schmidt orthogonalization. Correlation analysis and logistic regression were performed to show the effectiveness of these features to characterize remodeling due to myocardial infarction.

Keywords

Cardiac remodeling Magnetic resonance imaging Principal component analysis 

Notes

Acknowledgements

This project was supported by award numbers R01HL087773 and R01HL121754 from the National Heart, Lung, and Blood Institute. MESA was supported by contracts N01-HC-95159 through N01-HC-95169 from the NHLBI and by grants UL1-RR-024156 and UL1-RR-025005 from NCRR. DETERMINE was supported by St. Jude Medical, Inc; and the National Heart, Lung and Blood Institute (R01HL91069). A list of participating DETERMINE investigators can be found at http://www.clinicaltrials.gov. David A. Bluemke is supported by the NIH intramural research program. Xingyu Zhang would like to gratefully acknowledge financial support from the China Scholarship Council.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Xingyu Zhang
    • 1
  • Bharath Ambale-Venkatesh
    • 2
  • David A. Bluemke
    • 3
  • Brett R. Cowan
    • 1
  • J. Paul Finn
    • 4
  • William G. Hundley
    • 6
  • Alan H. Kadish
    • 5
  • Daniel C. Lee
    • 5
  • Joao A.C. Lima
    • 2
  • Avan Suinesiaputra
    • 1
  • Alistair A. Young
    • 1
  • Pau Medrano-Gracia
    • 1
  1. 1.Department of Anatomy with RadiologyUniversity of AucklandAucklandNew Zealand
  2. 2.The Donald W. Reynolds Cardiovascular Clinical Research CenterThe Johns Hopkins UniversityBaltimoreUSA
  3. 3.National Institute of Biomedical Imaging and BioengineeringBethesdaUSA
  4. 4.Department of RadiologyUCLALos AngelesUSA
  5. 5.Feinberg Cardiovascular Research InstituteNorthwestern University Feinberg School of MedicineChicagoUSA
  6. 6.Section of Cardiology Medical Center BlvdWinston SalemUSA

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