Joonho Jung MS, Presenter: Nothing to Disclose

Namkug Kim PhD, Abstract Co-Author: Stockholder, Coreline Soft, Inc

Dong Hyun Yang MD, Abstract Co-Author: Nothing to Disclose

Young-Hak Kim, Abstract Co-Author: Nothing to Disclose

Aortic stenosis is a narrowing of the aortic valve which can cause symptoms and may lead to heart failure. For differentiation between normal control and severe aortic stenosis(AS), we developed cardiac CT quantitative analysis software with patient specific anatomy based

An electrocardiogram-gated cardiac CT images was segmented semi-automatically to make patient specific myocardial 17-segment model (AHA) using seeded region growing method. Two experts manually determined anterior and posterior interventricular groove as a boundary between 1st and 2nd segments and as the other boundary between 3rd and 4th segments respectively to correct the model. Each segment is automatically identified as follows. The outer angle of two boundaries was divided to differentiate 1st, 4th, 5th and 6th segments with basal plane while the inner angle divided 2nd and 3rd segments. Similarly, segments of mid plane are differentiated. The area of the 17 segments was quantitatively assessed on the bull’s eye map using the morphological boundaries. For this procedure, an in-house program was developed on the windows7 x64 environment. CT data (normal control: 35, AS: 144) were evaluated for bull’s eye map analysis. Segment area distributions of AS patients and normal control were significantly different (t-test, all p-values < 0.011) which would be equivalent to maximum thickness of each segment in 3D (t-test, all p-values < 0.02 except 5th segment). In addition, quantitative parameters including mean density, maximum thickness and volume of each segment were structured-reported in this platform.

This patient specific anatomy based 17-segment model could be used for differentiate between AS and normal control. Especially, this model could be equivalent to 3D segment analysis and would be superior to conventional 17-segment model, because it represents patient specific segment anatomy information simultaneously on the bull’s eye map with visualization of morphological boundaries.

We developed the quantitative cardiac analysis platform with 17-segment considering anatomic variation. These quantification parameters could be used for differentiate AS and normal control using cardiac CT scans.

http://abstract.rsna.org/uploads/2014/14016812/14016812_wm7o.jpg

Jung, J, Kim, N, Yang, D, Kim, Y, Development of Patient Specific Anatomy based 17-segment Modeling (AHA) on Bull's Eye Map: Application for differentiation between Normal Control and Severe Aortic Stenosis.  Radiological Society of North America 2014 Scientific Assembly and Annual Meeting, - ,Chicago IL. http://archive.rsna.org/2014/14016812.html