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Proceedings Paper

Relating regional characteristics of left atrial shape to presence of scar in patients with atrial fibrillation
Author(s): Soroosh Sanatkhani; Michael Oladosu; Karandeep Chera; Sotirios Nedios; Prahlad G. Menon
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Paper Abstract

Pulmonary vein isolation (PVI) is an established procedure for atrial fibrillation (AF) patients. Pre-procedural screening is necessary prior to PVI in order to reduce the likelihood of AF recurrence and improve overall success rate of the procedure. However, current reliable methods to determine AF triggers are invasive. In this paper, we present an approach to relate the regional characteristics of left atrial (LA) shape to existence of low-voltage areas (LVA) which indicate the presence of scar in invasive exams. A cohort of 29 AF patient-specific clinical images were each segmented into 3D surface bodies representing the LA. Iterative closest point based similarity transformation was used to find the best fit sphere to each patient-specific LA and the mean deviation of LA wall to this sphere of best fit was determined using a signed point-to-surface regional distance metric. Regional departure from the best-fit sphere was reduced into a metric of global LA sphericity. Next, the LA was divided into six regions to perform an analysis of regional sphericity. Regional sphericity analysis revealed that sphericity of the inferior-posterior LA region was found to be related to several clinical variables, including a direct correlation with body mass index (BMI) and an inverse correlation with left ventricular ejection fraction (EF), which presents a diseased heart that has been asymmetrically inflated. Our observations therefore demonstrate promise in being leveraged as a non-invasive patient selection tool to increase the success rate of PVI procedures.

Paper Details

Date Published: 2 March 2018
PDF: 7 pages
Proc. SPIE 10574, Medical Imaging 2018: Image Processing, 105742N (2 March 2018); doi: 10.1117/12.2293947
Show Author Affiliations
Soroosh Sanatkhani, Univ. of Pittsburgh (United States)
Michael Oladosu, Duquesne Univ. (United States)
Karandeep Chera, Duquesne Univ. (United States)
Sotirios Nedios, Massachusetts General Hospital, Harvard Medical School (United States)
Prahlad G. Menon, Univ. of Pittsburgh (United States)
Duquesne Univ. (United States)


Published in SPIE Proceedings Vol. 10574:
Medical Imaging 2018: Image Processing
Elsa D. Angelini; Bennett A. Landman, Editor(s)

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