Graph-cuts based reconstructing patient specific right ventricle: First human study

• Published in: 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Vol. 2014; pp. 6770 - 6773
• Main Authors: Zhong, Liang, Wan, Min, Su, Yi, Teo, Soo Kng, Lim, Chi Wan, Zhao, Xiaodan, Zhang, Jun-Mei, Su, Bo Yang, Tan, Ju Le, Tan, Ru San
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 01.01.2014
• Subjects: Adolescent; Adult; Aged; Algorithms; Arteries; Biomedical imaging; Female; Heart; Heart Defects, Congenital - diagnosis; Heart Defects, Congenital - physiopathology; Heart Ventricles - pathology; Humans; Image Interpretation, Computer-Assisted; Image reconstruction; Imaging, Three-Dimensional; Magnetic Resonance Imaging; Male; Middle Aged; Shape; Smoothing methods; Software; Surface reconstruction; Ventricular Function, Right; Young Adult
• ISSN: 1094-687X; 1557-170X
• DOI: 10.1109/EMBC.2014.6945182

Right ventricular (RV) function is increasingly recognized to play an important role in the clinical status and long-term outcome in patients with congenital heart disease as well as ischemic cardiomyopathy with left ventricular dysfunction. However, quantification of RV characteristics and function are still challenging due to its complex morphology and its thin wall with coarse trabeculations. To assess RV functions quantitatively, establishing the patient-specific model from medical images is a prerequisite task. This study aims to develop a novel method for RV model reconstruction. Magnetic resonance images were acquired and preprocessed. Contours of right ventricle, right atrium and pulmonary artery were manually delineated at all slices and all time frames. The contour coordinates as well as the medical image specifications such as image pixel resolution and slick thickness were exported. The contours were transformed to the correct positions. Reorientation and matching were executed in between neighboring contours; extrapolation and interpolation were conducted upon all contours. After preprocessing, the more dense point set was reconstructed through a variational tool. A Delaunay-based tetrahedral mesh was generated on the region of interest. The weighted minimal surface model was used to describe RV surface. The graphcuts technique, i.e., max-flow/min-cut algorithm, was applied to minimize the energy defined by the model. The reconstructed surface was extracted from the mesh according to the mincut. Smoothing and remeshing were performed. The CPU time to reconstruct the model for one frame was approximately 2 minutes. In 10 consecutive subjects referred for cardiac MRI (80% female), right ventricular volumes were measured using our method against the commercial available CMRtools package. The results demonstrated that there was a significant correlation in end-diastolic and end-systolic volumes between our method and commercial software (r= 0.89 for end-diastolic volume and r=0.79 for end-systolic volume, both P<;0.0001). The time to obtain right ventricular volumes was shorter using our method than commercial one. In conclusion, a new method for right ventricle reconstruction has been developed. We envisage that this automatic modeling tool could be used by radiographer and cardiologists to assess the RV function in diverse heart diseases.