BACKGROUND: Abdominal aortic calcification (AAC) is a marker of atherosclerosis and a predictor of subsequent vascular disease. To date, there has been little research into the automatic detection and quantification of AAC. METHODS: In this study, lateral dual energy X-ray absorptiometry (DXA) scans are used to detect AAC; this is possible because of the anatomical position of the abdominal aorta anterior to the lumbar spine. The deformable shape modelling techniques active shape (ASM) and active appearance (AAM) models are used to model the calcified aorta and four vertebrae of the lumbar spine L1-L4. RESULTS: ASM and AAM were trained and tested on 14 DXA images. The shape of both calcified aorta and four lumbar vertebrae were extracted automatically from the DXA scans using combined shape and appearance models. CONCLUSION: ASM and AAM were implemented successfully. The calcified aorta obtained from the DXA scans was segmented using this modelling technique. The next step is to develop a new automated method to quantify the calcification within the aorta. arabic 13 English 89
Karima Elmasri(6-2015)

Cardiovascular disease (CVD) is a major cause of mortality and the main cause of morbidity worldwide. CVD may lead to heart attacks and strokes and most of these are caused by atherosclerosis; this is a medical condition in which the arteries become narrowed and hardened due to an excessive build-up of plaque on the inner artery wall. Arterial calcification and, in particular, abdominal aortic calcification (AAC) is a manifestation of atherosclerosis and a prognostic indicator of CVD. In this paper, a two-stage automatic method to detect and quantify the severity of AAC is described; it is based on the analysis of lateral vertebral fracture assessment (VFA) images. These images were obtained on a dual energy x-ray absorptiometry (DXA) scanner used in single energy mode. First, an active appearance model was used to segment the lumbar vertebrae L1-L4 and the aorta on VFA images; the segmentation of the aorta was based on its position with respect to the vertebrae. In the second stage, feature vectors representing calcified regions in the aorta were extracted to quantify the severity of AAC. The presence and severity of AAC was also determined using an established visual scoring system (AC24). The abdominal aorta was divided into four parts immediately anterior to each vertebra, and the severity of calcification in the anterior and posterior walls was graded separately for each part on a 0-3 scale. The results were summed to give a composite severity score ranging from 0 to 24. This severity score was classified as follows: mild AAC (score 0-4), moderate AAC (score 5-12) and severe AAC (score 12-24). Two classification algorithms (k-nearest neighbour and support vector machine) were trained and tested to assign the automatically extracted feature vectors into the three classes. There was good agreement between the automatic and visual AC24 methods and the accuracy of the automated technique relative to visual classification indicated that it is capable of identifying and quantifying AAC over a range of severity. arabic 30 English 163
Karima Mohamed Ali Elmasri, William Evans, Yulia Hicks(1-2016)

The 6MV photon beam production by the Elekta Line accelerateur of Tripoli of medical center (TMC) was modeled using Beamnrc and Dosexyzne Monte Carlo codes. The Beamnrc code was used to model the accelerator head and generate phase files. The phase space files were then used as input to the Dosexyzne code to simulate octogenarian deth dose and beam profiles. simulation were first stared using nominal provided by the vendor, a field size of 10x10cm2 and Source to surface distance (SSD) of 100 cm. simulation were compared with experimental data and energy tuning procedures were applied to validate the model. Energy tuning procedures indicated that the nominal energy of 6 MV and a FWHM of the Gaussian distribution of the source of 0.35 cm were the optimal energy and FWHM for the model. The depth of maximum dose at 6 MV was found to be 1.5 cm. The percentage relative differences between calculated and experimental Pdd(s) ranged from 0.5% to 3% for field size of 10cm2 and reached a value of 8% at depths greater than 20cm, The model was later used to calculate PDD(s) and beam profile and output factors for different field size ranging from 3x3cm2 to 25x25cm2. Calculated output factors were in good agreement with experimental values (the percentage relative differences ranged from 1% to 4%). (Author) arabic 42 English 152
Karima Elmasri, Tawfik Giaddui(12-2012)