Investigation of hippocampal substructures in focal temporal lobe epilepsy with and without hippocampal sclerosis at 7T

Santyr, Brendan; Goubran, Maged; Lau, Jonathan C.; Kwan, Benjamin Y. M.; Salehi, Fateme; Lee, Donald H.; Mirsattari, Seyed M.; Burneo, Jorge G.; Steven, David; Parrent, Andrew G.; Ribaupierre, Sandrine de; Hammond, Robert; Peters, Terry M.; Khan, Ali R.

doi:10.1002/jmri.25447

Cited by 44 publications

(47 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Previous work has shown that volume loss in selective hippocampal subfields is correlated to epilepsy. [39][40][41] It has been shown that different parts of the hippocampus show different levels of resistance to disruption in perfusion, with the CA1 region known to be particularly sensitive, whereas CA2 and CA3 are thought to be particularly resistant. 42 Thus, it may be possible that this change in VD is also associated with particular hippocampal subfields.…”

Section: Additional Limitations and Future Directionsmentioning

confidence: 99%

Seven‐tesla susceptibility‐weighted analysis of hippocampal venous structures: Application to magnetic‐resonance–normal focal epilepsy

et al. 2020

View full text Add to dashboard Cite

Objective Vascular structures may play a significant role in epileptic pathology. Although previous attempts to characterize vasculature relative to epileptogenic zones and hippocampal sclerosis have been inconsistent, an in vivo method of analysis would assist in resolving these inconsistencies and facilitate a comparison against healthy controls in a human model. Magnetic resonance imaging is a noninvasive technique that provides excellent soft tissue contrast, and the relatively recent development of susceptibility‐weighted imaging has dramatically improved the visibility of small veins. Methods We built and tested a Hessian‐based segmentation technique, which takes advantage of the increased signal and contrast available at 7 T to detect venous structures in vivo. We investigate the ability of this technique to quantify vessels in the brain and apply it to an asymmetry analysis of vessel density in the hippocampus in patients with mesial temporal lobe epilepsy (MTLE) and neocortical epilepsy. Results Vessel density was highly symmetric in the hippocampus in controls (mean asymmetry = 0.080 ± 0.076, median = 0.05027), whereas average vessel density asymmetry was greater in neocortical (mean asymmetry = 0.23 ± 0.17, median = 0.14) and MTLE (mean asymmetry = 0.37 ± 0.46, median = 0.26) patients, with the decrease in vessel density ipsilateral to the suspected seizure onset zone. Post hoc testing with one‐way analysis of variance and Tukey post hoc test indicated significant differences in the group means (P < .02) between MTLE and the control group only. Significance Asymmetry in vessel density in the hippocampus is visible in patients with MTLE, even when qualitative and quantitative measures of hippocampal asymmetry show little volumetric difference between epilepsy patients and healthy controls.

show abstract

Section: Additional Limitations and Future Directionsmentioning

confidence: 99%

Seven‐tesla susceptibility‐weighted analysis of hippocampal venous structures: Application to magnetic‐resonance–normal focal epilepsy

et al. 2020

View full text Add to dashboard Cite

show abstract

“…The hippocampus is implicated in many neurological diseases including Alzheimer's disease (AD), epilepsy, and schizophrenia, among others (Barnes et al, 2009;Bernasconi, Natsume, & Bernasconi, 2005;Goubran et al, 2016;Santyr et al, 2017;Steen, Mull, McClure, Hamer, & Lieberman, 2006). Hippocampal volumetry has been found to be a critical biomarker of aging and dementia (Courchesne et al, 2000;Jack Jr et al, 1998).…”

mentioning

confidence: 99%

Hippocampal segmentation for brains with extensive atrophy using three‐dimensional convolutional neural networks

Goubran

Ntiri

Akhavein

et al. 2019

Human Brain Mapping

Self Cite

View full text Add to dashboard Cite

Hippocampal volumetry is a critical biomarker of aging and dementia, and it is widely used as a predictor of cognitive performance; however, automated hippocampal segmentation methods are limited because the algorithms are (a) not publicly available, (b) subject to error with significant brain atrophy, cerebrovascular disease and lesions, and/or (c) computationally expensive or require parameter tuning. In this study, we trained a 3D convolutional neural network using 259 bilateral manually delineated segmentations collected from three studies, acquired at multiple sites on different scanners with variable protocols. Our training dataset consisted of elderly cases difficult to segment due to extensive atrophy, vascular disease, and lesions. Our algorithm, (HippMapp3r), was validated against four other publicly available state-of-the-art techniques (HippoDeep, FreeSurfer, SBHV, volBrain, and FIRST). HippMapp3r outperformed the other techniques on all three metrics, generating an average Dice of 0.89 and a correlation coefficient of 0.95. It was two orders of magnitude faster than some of the tested techniques. Further validation was performed on 200 subjects from two other disease populations (frontotemporal dementia and vascular cognitive impairment), highlighting our method's low outlier rate. We finally tested the methods on real and simulated "clinical adversarial" cases to study their robustness to corrupt, low-quality scans. The pipeline and models are available at: https://hippmapp3r.readthedocs.ioto facilitate the study of the hippocampus in large multisite studies.

show abstract

“…The key advantage of PMC in this setting is that we can achieve high SNR using averaging of scans with clinically tractable scan durations without the need for image registration, which can be difficult for slabs with limited coverage and can introduce blurring. Our rater analysis demonstrates that PMC with this system provides significantly improved overall image quality (ie, reduced motion artifact) and allows for better visualization of clinically important structures: the gray–white junction (focal cortical dysplasias), the deep gray nuclei (movement disorders), and the hippocampus (neurodegenerative diseases, epilepsy, and mild traumatic brain injury). The effect of motion correction is seen in healthy, compliant subjects with minimal motion, but a larger improvement is seen in the context of larger magnitude motion.…”

Section: Discussionmentioning

confidence: 94%

A within‐coil optical prospective motion‐correction system for brain imaging at 7T

DiGiacomo

Maclaren

Aksoy

et al. 2020

Magnetic Resonance in Med

View full text Add to dashboard Cite

Purpose: Motion artifact limits the clinical translation of high-field MR. We present an optical prospective motion correction system for 7 Tesla MRI using a custombuilt, within-coil camera to track an optical marker mounted on a subject. Methods: The camera was constructed to fit between the transmit-receive coils with direct line of sight to a forehead-mounted marker, improving upon prior mouthpiece work at 7 Tesla MRI. We validated the system by acquiring a 3D-IR-FSPGR on a phantom with deliberate motion applied. The same 3D-IR-FSPGR and a 2D gradient echo were then acquired on 7 volunteers, with/without deliberate motion and with/ without motion correction. Three neuroradiologists blindly assessed image quality.In 1 subject, an ultrahigh-resolution 2D gradient echo with 4 averages was acquired with motion correction. Four single-average acquisitions were then acquired serially, with the subject allowed to move between acquisitions. A fifth single-average 2D gradient echo was acquired following subject removal and reentry. Results: In both the phantom and human subjects, deliberate and involuntary motion were well corrected. Despite marked levels of motion, high-quality images were produced without spurious artifacts. The quantitative ratings confirmed significant improvements in image quality in the absence and presence of deliberate motion across both acquisitions (P < .001). The system enabled ultrahigh-resolution visualization of the hippocampus during a long scan and robust alignment of serially acquired scans with interspersed movement. Conclusion: We demonstrate the use of a within-coil camera to perform optical prospective motion correction and ultrahigh-resolution imaging at 7 Tesla MRI. The 1662 | DIGIACOMO et Al.

show abstract

Investigation of hippocampal substructures in focal temporal lobe epilepsy with and without hippocampal sclerosis at 7T

Cited by 44 publications

References 32 publications

Seven‐tesla susceptibility‐weighted analysis of hippocampal venous structures: Application to magnetic‐resonance–normal focal epilepsy

Seven‐tesla susceptibility‐weighted analysis of hippocampal venous structures: Application to magnetic‐resonance–normal focal epilepsy

Hippocampal segmentation for brains with extensive atrophy using three‐dimensional convolutional neural networks

A within‐coil optical prospective motion‐correction system for brain imaging at 7T

Contact Info

Product

Resources

About