Volumetric brain analysis in neurosurgery: Part 3. Volumetric CT analysis as a predictor of seizure outcome following temporal lobectomy

Background X-ray Computed Tomography (CT) imaging of the brain is commonly used in diagnostic settings. Although CT scans are primarily used in clinical practice, they are increasingly used in research. A fundamental processing step in brain imaging research is brain extraction – the process of separating the brain tissue from all other tissues. Methods for brain extraction have either been 1) validated but not fully automated, or 2) fully automated and informally proposed, but never formally validated. Aim To systematically analyze and validate the performance of FSL's brain extraction tool (BET) on head CT images of patients with intracranial hemorrhage. This was done by comparing the manual gold standard with the results of several versions of automatic brain extraction and by estimating the reliability of automated segmentation of longitudinal scans. The effects of the choice of BET parameters and data smoothing is studied and reported. Methods All images were thresholded using a 0 – 100 Hounsfield units (HU) range. In one variant of the pipeline, data were smoothed using a 3-dimensional Gaussian kernel (σ = 1mm3) and re-thresholded to 0 – 100 HU; in the other, data were not smoothed. BET was applied using 1 of 3 fractional intensity (FI) thresholds: 0.01, 0.1, or 0.35 and any holes in the brain mask were filled. For validation against a manual segmentation, 36 images from patients with intracranial hemorrhage were selected from 19 different centers from the MISTIE (Minimally Invasive Surgery plus recombinant-tissue plasminogen activator for Intracerebral Evacuation) stroke trial. Intracranial masks of the brain were manually created by one expert CT reader. The resulting brain tissue masks were quantitatively compared to the manual segmentations using sensitivity, specificity, accuracy, and the Dice Similarity Index (DSI). Brain extraction performance across smoothing and FI thresholds was compared using the Wilcoxon signed-rank test. The intracranial volume (ICV) of each scan was estimated by multiplying the number of voxels in the brain mask by the dimensions of each voxel for that scan. From this, we calculated the ICV ratio comparing manual and automated segmentation: 1ICVautomatedICVmanual. To estimate the performance in a large number of scans, brain masks were generated from the 6 BET pipelines for 1095 longitudinal scans from 129 patients. Failure rates were estimated from visual inspection. ICV of each scan was estimated and and an intraclass correlation (ICC) was estimated using a one-way ANOVA. Results Smoothing images improves brain extraction results using BET for all measures except specificity (all p < 0.01, uncorrected), irrespective of the FI threshold. Using an FI of 0.01 or 0.1 performed better than 0.35. Thus, all reported results refer only to smoothed data using an FI of 0.01 or 0.1. Using an FI of 0.01 had a higher median sensitivity (0.9901) than an FI of 0.1 (0.9884, median difference: 0.0014, p < 0.001), accuracy (0.9971 vs. 0.9971; median difference: 0.0001, p < 0.001), and...

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“…This method was also performed on a set of brains with disease [10, 11]. This method is not fully automated, however.…”

Section: Introductionmentioning

confidence: 99%

Validated automatic brain extraction of head CT images

et al. 2015

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“…Many different applications based on volume, area and shape measurements have been used on anatomical brain structures to measure changes caused by neurovascular diseases [11,12,17]. Recently, statistical shape analysis has become more important in the medical and biological sciences [7].…”

Section: Introductionmentioning

confidence: 99%

Statistical shape analysis of temporal lobe in mesial temporal sclerosis patients

et al. 2015

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“…The publications were mainly longitudinal studies, case-series, case-control studies and one randomized controlled study. They include nine publications from six African countries [33][34][35][36][37][38][39][40][41][42]; 52 publications from 12 Latin American and the Caribbean countries ; 85 publications from 13 Asian countries [83, and three publications from two Eastern European countries [178][179][180]. The bulk of the published literatures are from India, China, and Brazil.…”

Section: Resultsmentioning

confidence: 99%

“…Information on whether they had sufficient qualified personnel or adequate training was mainly not mentioned or difficult to extract. Some papers reported on collaborative work between HIC and LMIC in Uganda [36][37][38], Tunisia [41], Thailand, India and Argentina [83,105], Pakistan [168], and Iran [171]. The collaborative epilepsy surgery program between North America and the CURE Children's Hospital of Uganda (CCHU) assessed the feasibility of an epilepsy surgery program in a resource-poor setting using just videoelectroencephalography (EEG) and computed tomography (CT) volumetric analysis [38].…”

Section: Resultsmentioning

confidence: 99%

“…Some of the established centers had adequate infrastructure, manpower and training, but this is not universal. The Ugandan experience shows that the lack of sophisticated modern equipment should not be a limitation to surgery [36,38]. Their model utilized technology and expertise that was reasonably available and could function sustainably in resource-poor setting.…”

Section: Discussionmentioning

confidence: 99%

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Epilepsy surgery in low- and middle-income countries: A scoping review

Watila

Xiao

Keezer

et al. 2019

Epilepsy & Behavior

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Background: Epilepsy surgery is an important treatment option for people with drug resistant epilepsy. Although surgical procedures are under-utilized worldwide, it is far worse in Low-and Middle-Income Countries (LMIC) and it is less clear to what extent people with drug resistant epilepsy receive such treatment at all. Here we review the existing evidence for the availability and outcome of epilepsy surgery in LMIC, and discuss some challenges and priority. Methods: We used the six stage methodological framework developed by Arskey and O'Malley as a guide. We searched PubMed, Embase, Global Health Archives, Index Medicus for South East Asia Region (IMSEAR), Index Medicus for Eastern Mediterranean Region (IMEMR), Latin American & Caribbean Health Sciences Literature (LILACS), African Journal Online (AJOL), and African Index Medicus (AIM) to identify the relevant literature. Results: We retrieved 148 articles on epilepsy surgery from 31 countries representing 22% of the 143 LMIC. Epilepsy surgery appears established in some of these centers in Asia and Latin America, while some are in their embryonic stage reporting procedures in a small cohort performed mostly by motivated neurosurgeons. The commonest surgical procedure reported was temporal lobectomies. The post-operative seizure-free rates and quality of life are comparable to those in the high-income countries (HIC). Some models have shown that epilepsy surgery can be performed within a resourcelimited setting through collaboration with international partners and through the use of information and communication technology. The cost of surgery is a fraction of what is available in HIC. Conclusion: This review has demonstrated the availability of epilepsy surgery in few LMIC. The information available is inadequate to make any reasonable conclusion of its existence as routine practice. Collaborations with international partners can provide an opportunity to bring high-quality academic training and technological transfer directly to surgeons working in these regions and should be encouraged.

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Volumetric brain analysis in neurosurgery: Part 3. Volumetric CT analysis as a predictor of seizure outcome following temporal lobectomy

Cited by 11 publications

References 38 publications

Validated automatic brain extraction of head CT images

Validated automatic brain extraction of head CT images

Statistical shape analysis of temporal lobe in mesial temporal sclerosis patients

Epilepsy surgery in low- and middle-income countries: A scoping review

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