Motion Analysis and Assessment of Cardiac Function for Cardiac Images

The study develops software for motion analysis and assessment of cardiac function for cardiac images. Cardiac catheterization ventriculography of several randomly selected patients were taken from our hospital's PACS system. The investigators remove the patient information on the images, and use the image for motion analysis and assessment.

Study Overview

• Status: Completed
• Conditions: Heart; Functional Disturbance

Detailed Description

The study develops software for motion analysis and assessment of cardiac function for cardiac images. Twenty patients who have both cardiac catheterization ventriculography and cardiac echo studies will be randomly selected. Cardiac catheterization ventriculography of the selected patients were taken from our hospital's PACS system. The investigators remove the patient information on the images, and use the image for motion analysis and assessment. The results will be compared and correlated with their cardiac echo, which could validate the clinical usefulness of the software.

• Study Type: Observational
• Enrollment (Actual): 20

Contacts and Locations

Study Locations

• Taiwan
  • New Taipei, Taiwan, 22060
    • Far Eastern Memorial Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Probability Sample

Study Population

randomly selected patients

Description

Inclusion Criteria:

• patients who already have cardiac catheterization ventriculography and cardiac echo studies.

Exclusion Criteria:

• patients who do not have either cardiac catheterization ventriculography or cardiac echo studies.

Study Plan

How is the study designed?

Design Details

• Observational Models: Case-Only
• Time Perspectives: Retrospective

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort
normal heart function
abnormal heart function

Collaborators and Investigators

• Sponsor: Far Eastern Memorial Hospital
• Investigators: Principal Investigator: Yu-Chien Shiau, PhD, Far Eastern Memorial Hospital

Publications and helpful links

General Publications

• Bravo A, Medina R. An unsupervised clustering framework for automatic segmentation of left ventricle cavity in human heart angiograms. Comput Med Imaging Graph. 2008 Jul;32(5):396-408. doi: 10.1016/j.compmedimag.2008.03.003.
• White RD, Setser RM. Integrated approach to evaluating coronary artery disease and ischemic heart disease. Am J Cardiol. 2002 Nov 21;90(10C):49L-55L. doi: 10.1016/s0002-9149(02)02964-8.
• Oost E, Koning G, Sonka M, Oemrawsingh PV, Reiber JH, Lelieveldt BP. Automated contour detection in X-ray left ventricular angiograms using multiview active appearance models and dynamic programming. IEEE Trans Med Imaging. 2006 Sep;25(9):1158-71. doi: 10.1109/tmi.2006.877094.
• Suzuki K, Horiba I, Sugie N, Nanki M. Extraction of left ventricular contours from left ventriculograms by means of a neural edge detector. IEEE Trans Med Imaging. 2004 Mar;23(3):330-9. doi: 10.1109/TMI.2004.824238.

Study record dates

Study Major Dates

• Study Start: August 1, 2011
• Primary Completion (Actual): April 1, 2012
• Study Completion (Actual): April 1, 2012

Study Registration Dates

• First Submitted: June 22, 2012
• First Submitted That Met QC Criteria: June 25, 2012
• First Posted (Estimate): June 26, 2012

Study Record Updates

• Last Update Posted (Estimate): June 26, 2012
• Last Update Submitted That Met QC Criteria: June 25, 2012
• Last Verified: June 1, 2012

More Information

Terms related to this study

• Keywords: Heart Wall Motion Function
• Other Study ID Numbers: FEMH-IRB-100070-E