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Evaluation of nonrigid registration around the hippocampus for the construction of statistical maps in a multicenter dataset of epilepsy laser ablation patients
Author(s): Srijata Chakravorti; Walter J. Jermakowicz; Chengyuan Wu; Rui Li; Raul Wirz-Gonzalez; Benoit M. Dawant; Pierre-François D'Haese
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Paper Abstract

Laser interstitial thermal therapy (LITT) is a novel minimally-invasive neurosurgical ablative tool that is par ticularly well-suited for treating patients suffering from drug-resistant mesial temporal lobe epilepsy (mTLE). Although morbidity to patients is lower with LITT compared to the open surgical gold standard, seizure freedom rates appear inferior, likely a result of our lack of knowledge of which mesial temporal subregions are most critical for treating seizures. The wealth of post-LITT imaging and outcomes data provides a means for elucidating these critical zones, but such analyses are hindered by variations in patient anatomy and the distribution of these novel data among multiple academic institutions, each employing different imaging and surgical protocols. Adequate population analyses of LITT outcomes require normalization of imaging and clinical data to a common reference atlas. This paper discusses a method to nonrigidly register preoperative images to an atlas and quantitatively evaluate its performance in our region of interest, the hippocampus. Knowledge of this registration error would allow us to both select an appropriate registration method and define our level of confidence in the correspondence of the postoperative images to the atlas. Once the registration process is validated, we aim to create a statistical map from all the normalized LITT ablation images to analyze and identify factors that correlate with good outcomes.

Paper Details

Date Published: 8 March 2019
PDF: 7 pages
Proc. SPIE 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 109511J (8 March 2019); doi: 10.1117/12.2512587
Show Author Affiliations
Srijata Chakravorti, Vanderbilt Univ. (United States)
Walter J. Jermakowicz, Univ. of Miami Miller School of Medicine (United States)
Chengyuan Wu, Thomas Jefferson Univ. (United States)
Rui Li, Vanderbilt Univ. (United States)
Raul Wirz-Gonzalez, Vanderbilt Univ. (United States)
Benoit M. Dawant, Vanderbilt Univ. (United States)
Pierre-François D'Haese, Vanderbilt Univ. (United States)

Published in SPIE Proceedings Vol. 10951:
Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)

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