Mr. Soroosh Sanatkhani Profile

Soroosh Sanatkhani

PhD Student at University of Pittsburgh

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Publications (3)

Proceedings Article | 2 March 2018 Paper

Relating regional characteristics of left atrial shape to presence of scar in patients with atrial fibrillation

Soroosh Sanatkhani, Michael Oladosu, Karandeep Chera, Sotirios Nedios, Prahlad Menon

Proceedings Volume 10574, 105742N (2018) https://doi.org/10.1117/12.2293947

KEYWORDS: Atrial fibrillation, Image segmentation, Computed tomography, 3D image processing

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Proceedings Article | 2 March 2018 Paper

Generative statistical modeling of left atrial appendage appearance to substantiate clinical paradigms for stroke risk stratification

Soroosh Sanatkhani, Prahlad Menon

Proceedings Volume 10574, 105742L (2018) https://doi.org/10.1117/12.2291568

KEYWORDS: Atrial fibrillation, Statistical analysis, Computed tomography, Principal component analysis, Volume visualization, Image segmentation, Image filtering, 3D image processing

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Left atrial appendage (LAA) is the source of 91% of the thrombi in patients with atrial arrhythmias (~2.3 million US adults), turning this region into a potential threat for stroke. LAA geometries have been clinically categorized into four appearance groups viz. Cauliflower, Cactus, Chicken-Wing and WindSock, based on visual appearance in 3D volume visualizations of contrast-enhanced computed tomography (CT) imaging, and have further been correlated with stroke risk by considering clinical mortality statistics. However, such classification from visual appearance is limited by human subjectivity and is not sophisticated enough to address all the characteristics of the geometries. Quantification of LAA geometry metrics can reveal a more repeatable and reliable estimate on the characteristics of the LAA which correspond with stasis risk, and in-turn cardioembolic risk. We present an approach to quantify the appearance of the LAA in patients in atrial fibrillation (AF) using a weighted set of baseline eigen-modes of LAA appearance variation, as a means to objectify classification of patient-specific LAAs into the four accepted clinical appearance groups. Clinical images of 16 patients (4 per LAA appearance category) with atrial fibrillation (AF) were identified and visualized as volume images. All the volume images were rigidly reoriented in order to be spatially co-registered, normalized in terms of intensity, resampled and finally reshaped appropriately to carry out principal component analysis (PCA), in order to parametrize the LAA region’s appearance based on principal components (PCs/eigen mode) of greyscale appearance, generating 16 eigen-modes of appearance variation. Our pilot studies show that the most dominant LAA appearance (i.e. reconstructable using the fewest eigen-modes) resembles the Chicken-Wing class, which is known to have the lowest stroke risk per clinical mortality statistics. Our findings indicate the possibility that LAA geometries with high risk of stroke are higher-order statistical variants of underlying lower risk shapes.

Proceedings Article | 24 February 2017 Paper

Personalized design and virtual evaluation of physician-modified stent grafts for juxta-renal abdominal aortic aneurysms

Soroosh Sanatkhani, Sanjeev Shroff, Prahlad Menon

Proceedings Volume 10133, 101332C (2017) https://doi.org/10.1117/12.2254404

KEYWORDS: CFD analysis, 3D modeling, Hemodynamics, 3D image processing, Surgery, Computed tomography, Virtual reality, Fluid dynamics, Arteries, Computational fluid dynamics, Blood circulation, 3D image reconstruction

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