Joon Yul Choi1, Balu Krishnan1, Siyuan Hu2, David Martinez1, Yinging Tang1,3, Xiaofeng Wang4, Ken Sakaie5, Stephen Jones5, Hiroatsu Murakami1, Ingmar Blümcke1,6, Imad Najm1, Dan Ma2, Zhong Irene Wang1. 1. Charles Shor Epilepsy Center, Cleveland Clinic, Neurological Institute, Cleveland, Ohio, USA. 2. Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA. 3. Department of Neurology, West China Hospital of Sichuan University, Chengdu, China. 4. Quantitative Health Science, Cleveland Clinic, Cleveland, Ohio, USA. 5. Imaging Institute, Cleveland Clinic, Cleveland, Ohio, USA. 6. Neuropathology, University of Erlangen, Erlangen, Germany.
Abstract
OBJECTIVE: We aimed to use a novel magnetic resonance fingerprinting (MRF) technique to examine in vivo tissue property characteristics of periventricular nodular heterotopia (PVNH). These characteristics were further correlated with stereotactic-electroencephalographic (SEEG) ictal onset findings. METHODS: We included five patients with PVNH who had SEEG-guided surgery and at least 1 year of seizure freedom or substantial seizure reduction. High-resolution MRF scans were acquired at 3 T, generating three-dimensional quantitative T1 and T2 maps. We assessed the differences between T1 and T2 values from the voxels in the nodules located in the SEEG-defined seizure onset zone (SOZ) and non-SOZ, on -individual and group levels. Receiver operating characteristic analyses were performed to obtain the optimal classification performance. Quantification of SEEG ictal onset signals from the nodules was performed by calculating power spectrum density (PSD). The association between PSD and T1 /T2 values was further assessed at different frequency bands. RESULTS: Individual-level analysis showed T1 was significantly higher in SOZ voxels than non-SOZ voxels (p < .05), with an average 73% classification accuracy. Group-level analysis also showed higher T1 was significantly associated with SOZ voxels (p < .001). At the optimal cutoff (normalized T1 of 1.1), a 76% accuracy for classifying SOZ nodules from non-SOZ nodules was achieved. T1 values were significantly associated with ictal onset PSD at the ultraslow, θ, β, γ, and ripple bands (p < .05). T2 values were significantly associated with PSD only at the ultraslow band (p < .05). SIGNIFICANCE: Quantitative MRF measures, especially T1 , can provide additional noninvasive information to separate nodules in SOZ and non-SOZ. The T1 and T2 tissue property changes carry electrophysiological underpinnings relevant to the epilepsy, as shown by their significant positive associations with power changes during the SEEG seizure onset. The use of MRF as a supplementary noninvasive tool may improve presurgical evaluation for patients with PVNH and pharmacoresistant epilepsy.
OBJECTIVE: We aimed to use a novel magnetic resonance fingerprinting (MRF) technique to examine in vivo tissue property characteristics of periventricular nodular heterotopia (PVNH). These characteristics were further correlated with stereotactic-electroencephalographic (SEEG) ictal onset findings. METHODS: We included five patients with PVNH who had SEEG-guided surgery and at least 1 year of seizure freedom or substantial seizure reduction. High-resolution MRF scans were acquired at 3 T, generating three-dimensional quantitative T1 and T2 maps. We assessed the differences between T1 and T2 values from the voxels in the nodules located in the SEEG-defined seizure onset zone (SOZ) and non-SOZ, on -individual and group levels. Receiver operating characteristic analyses were performed to obtain the optimal classification performance. Quantification of SEEG ictal onset signals from the nodules was performed by calculating power spectrum density (PSD). The association between PSD and T1 /T2 values was further assessed at different frequency bands. RESULTS: Individual-level analysis showed T1 was significantly higher in SOZ voxels than non-SOZ voxels (p < .05), with an average 73% classification accuracy. Group-level analysis also showed higher T1 was significantly associated with SOZ voxels (p < .001). At the optimal cutoff (normalized T1 of 1.1), a 76% accuracy for classifying SOZ nodules from non-SOZ nodules was achieved. T1 values were significantly associated with ictal onset PSD at the ultraslow, θ, β, γ, and ripple bands (p < .05). T2 values were significantly associated with PSD only at the ultraslow band (p < .05). SIGNIFICANCE: Quantitative MRF measures, especially T1 , can provide additional noninvasive information to separate nodules in SOZ and non-SOZ. The T1 and T2 tissue property changes carry electrophysiological underpinnings relevant to the epilepsy, as shown by their significant positive associations with power changes during the SEEG seizure onset. The use of MRF as a supplementary noninvasive tool may improve presurgical evaluation for patients with PVNH and pharmacoresistant epilepsy.
Authors: L Tassi; N Colombo; M Cossu; R Mai; S Francione; G Lo Russo; C Galli; M Bramerio; G Battaglia; R Garbelli; A Meroni; R Spreafico Journal: Brain Date: 2004-12-23 Impact factor: 13.501
Authors: Dan Ma; Stephen E Jones; Anagha Deshmane; Ken Sakaie; Eric Y Pierre; Mykol Larvie; Debra McGivney; Ingmar Blümcke; Balu Krishnan; Mark Lowe; Vikas Gulani; Imad Najm; Mark A Griswold; Z Irene Wang Journal: J Magn Reson Imaging Date: 2018-12-23 Impact factor: 4.813
Authors: L M Li; F Dubeau; F Andermann; D R Fish; C Watson; G D Cascino; S F Berkovic; N Moran; J S Duncan; A Olivier; R Leblanc; W Harkness Journal: Ann Neurol Date: 1997-05 Impact factor: 10.422
Authors: Chaitra Badve; Alice Yu; Matthew Rogers; Dan Ma; Yiying Liu; Mark Schluchter; Jeffrey Sunshine; Mark Griswold; Vikas Gulani Journal: Tomography Date: 2015-12