Mohammad-Reza Nazem-Zadeh1, Kost V Elisevich2, Jason M Schwalb3, Hassan Bagher-Ebadian4, Fariborz Mahmoudi5, Hamid Soltanian-Zadeh6. 1. Department of Research Administration, Henry Ford Health System, Detroit, MI 48202, USA; Department of Radiology, Henry Ford Health System, Detroit, MI, 48202, USA. Electronic address: mohamadn@rad.hfh.edu. 2. Department of Clinical Neurosciences, Spectrum Health Medical Group, Grand Rapids, MI 49503, USA. Electronic address: kost.elisevich@spectrumhealth.org. 3. Department of Neurosurgery, Henry Ford Health System, Detroit, MI 48202, USA. Electronic address: jschwal1@hfhs.org. 4. Department of Radiology, Henry Ford Health System, Detroit, MI, 48202, USA; Department of Neurology, Henry Ford Health System, Detroit, MI 48202, USA. Electronic address: hbagher1@hfhs.org. 5. Department of Research Administration, Henry Ford Health System, Detroit, MI 48202, USA; Department of Radiology, Henry Ford Health System, Detroit, MI, 48202, USA; Computer and IT engineering Faculty, Islamic Azad University, Qazvin Branch, Iran. Electronic address: fariborzm@rad.hfh.edu. 6. Department of Research Administration, Henry Ford Health System, Detroit, MI 48202, USA; Department of Radiology, Henry Ford Health System, Detroit, MI, 48202, USA; Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer, University of Tehran, Tehran, Iran. Electronic address: hamids@rad.hfh.edu.
Abstract
PURPOSE: Multiple modalities are used in determining laterality in mesial temporal lobe epilepsy (mTLE). It is unclear how much different imaging modalities should be weighted in decision-making. The purpose of this study is to develop response-driven multimodal multinomial models for lateralization of epileptogenicity in mTLE patients based upon imaging features in order to maximize the accuracy of noninvasive studies. METHODS AND MATERIALS: The volumes, means and standard deviations of FLAIR intensity and means of normalized ictal-interictal SPECT intensity of the left and right hippocampi were extracted from preoperative images of a retrospective cohort of 45 mTLE patients with Engel class I surgical outcomes, as well as images of a cohort of 20 control, nonepileptic subjects. Using multinomial logistic function regression, the parameters of various univariate and multivariate models were estimated. Based on the Bayesian model averaging (BMA) theorem, response models were developed as compositions of independent univariate models. RESULTS: A BMA model composed of posterior probabilities of univariate response models of hippocampal volumes, means and standard deviations of FLAIR intensity, and means of SPECT intensity with the estimated weighting coefficients of 0.28, 0.32, 0.09, and 0.31, respectively, as well as a multivariate response model incorporating all mentioned attributes, demonstrated complete reliability by achieving a probability of detection of one with no false alarms to establish proper laterality in all mTLE patients. CONCLUSION: The proposed multinomial multivariate response-driven model provides a reliable lateralization of mesial temporal epileptogenicity including those patients who require phase II assessment.
PURPOSE: Multiple modalities are used in determining laterality in mesial temporal lobe epilepsy (mTLE). It is unclear how much different imaging modalities should be weighted in decision-making. The purpose of this study is to develop response-driven multimodal multinomial models for lateralization of epileptogenicity in mTLE patients based upon imaging features in order to maximize the accuracy of noninvasive studies. METHODS AND MATERIALS: The volumes, means and standard deviations of FLAIR intensity and means of normalized ictal-interictal SPECT intensity of the left and right hippocampi were extracted from preoperative images of a retrospective cohort of 45 mTLE patients with Engel class I surgical outcomes, as well as images of a cohort of 20 control, nonepileptic subjects. Using multinomial logistic function regression, the parameters of various univariate and multivariate models were estimated. Based on the Bayesian model averaging (BMA) theorem, response models were developed as compositions of independent univariate models. RESULTS: A BMA model composed of posterior probabilities of univariate response models of hippocampal volumes, means and standard deviations of FLAIR intensity, and means of SPECT intensity with the estimated weighting coefficients of 0.28, 0.32, 0.09, and 0.31, respectively, as well as a multivariate response model incorporating all mentioned attributes, demonstrated complete reliability by achieving a probability of detection of one with no false alarms to establish proper laterality in all mTLE patients. CONCLUSION: The proposed multinomial multivariate response-driven model provides a reliable lateralization of mesial temporal epileptogenicity including those patients who require phase II assessment.
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