PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Coppini G., Favilla R., Moroni D., Pieri G., Schlueter M., Bianchi M., Coceani M., Mazzarisi A., Salvetti O., Marraccini P. Computer technology for the quantification of pericardial fat assessed through cardiac CT. In: ESC Congress 2010 - European Society of Cardiology Congress 2010 (Stockholm, Sweden, 28-08/01-09 2010). Abstract, vol. 31(suppl 1) pp. 436 - 436. (European Heart Journal, vol. 31). Oxford Journals, 2010.
 
 
Abstract
(English)
Purpose: Pericardial fat is associated with the extent of coronary artery disease (CAD) and with cardiovascular mortality. The aim of the study was to develop a computer software for the detection and measurement of pericardial fat in patients with suspected CAD. Methods: A dedicated software was developed to quantify pericardial fat from standard calcium score scans (acquisition triggered at 70% of the R-R interval, image reconstruction with a slice thickness of 2.5 mm without overlap). The procedure is based on the following phases: 1) A trace of the pericardial boundary in two orthogonal long-axis slices of the heart is performed by the operator. 2) An initial and approximate representation of the pericardial surface is generated. 3) The pericardial fat is then segmented by applying a Level Set method; 4) The ventricular region is defined by recognizing the atrioventricular groove and split in two by the interventricular groove. 5) If necessary, further manual editing of the pericardial boundary can be carried out. The method output provides the total volume of pericardial fat, as well as the regional distribution of fat in the right and left ventricles. Results: To test the performance of the software, we used scans from a set of 22 patients (638 years, 64% male, body mass index [BMI] 27.45.2 kg/m2) referred to our Institute for suspected CAD and undergoing cardiac CT. The average time needed to complete the analysis of pericardial fat was less than five minutes. In our patient sample, we observed a total pericardial volume of 95.732.1 mm3, which was divided unevenly between the right (59.428.3 mm3) and left (38.912.6 mm3) ventricles. Conclusions: Pericardial fat volume may be assessed non-invasively through cardiac CT, without leading to increased radiological exposure and post-processing times. The use of a computer software, such as the one tested in the present study, permits a systematic evaluation of epicardial fat that may prove useful for the risk stratification of patients undergoing cardiac CT.
URL: http://eurheartj.oxfordjournals.org/content/31/suppl_1/297.full.pdf
DOI: 10.1093/eurheartj/ehq288
Subject DICOM
Image Segmentation
Computer Tomography
Spherical harmonics representations
J.3 Life and Medical Sciences
I.4.6 Segmentation


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