Application of data harmonization and tract-based spatial statistics reveals white matter structural abnormalities in pediatric patients with focal cortical dysplasia

Chu, Daniel Y; Adluru, Nagesh; Nair, Veena A.; Adluru, Anusha; Choi, Tae-Jin; Kessler-Jones, Alanna; Dabbs, Kevin; Hou, Jiancheng; Hermann, Bruce P.; Prabhakaran, Vivek; Ahmed, Raheel

doi:10.1016/j.yebeh.2023.109190

Cited by 4 publications

(1 citation statement)

References 49 publications

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“…A major concern when analyzing results from these large consortium datasets is the potential bias introduced by non-biological site-related effects [14]. Previous studies have demonstrated that the site effects, including field strength, manufacture, software upgrade, as well as acquisition protocols, introduced bias and variance in measurements of brain volume [15][16][17], cortical thickness [18][19][20][21][22][23], functional and diffusion MRI [24][25][26][27][28][29][30] in adults, adolescents, children, infants and neonates. Nevertheless, the impact of these site effects on fetal brain MRI remains unknown.…”

Section: Introductionmentioning

confidence: 99%

Site Effects in Multisite Fetal Brain MRI: Morphological Insights into Early Brain Development

Xu,

Sun,

et al. 2023

Preprint

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BackgroundMultisite MRI studies have become prevalent given their advantage in revealing reliable biological or clinical findings. Adult and adolescent multisite studies have demonstrated inevitable site-related non-biological effects that introduce bias. However, the site effect on fetal brain MRI remains unknown.PurposeTo identify crucial acquisition factors affecting fetal brain structural measurements and developmental patterns, while assessing the effectiveness of existing harmonization methods in mitigating site effects.Materials and MethodsBetween May 2017 and March 2022, T2-weighted fast spin-echo sequences in-utero MRI were performed in healthy fetuses from prospectively recruited pregnant volunteers on four different scanners at four sites. A generalized additive model (GAM) was used to quantitatively assess site effects, including field strength (FS), manufacture (M), in-plane resolution (R), and slice thickness (ST), on subcortical volume and cortical morphological measurements, including cortical thickness, curvature, and sulcal depth. Growth models were selected to elucidate developmental trajectories of these morphological measurements. Welch’s test was performed to evaluate the influence of site effects on developmental trajectories. ComBat-GAM harmonization method was applied to mitigate site-related biases.ResultsThe final analytic sample consisted of 340 MRI scans from 218 fetuses (mean gestational age, 30.1 weeks ± 4.4 [range, 21.7–40 weeks]). GAM results showed that low FS and low spatial resolution led to overestimations in selected brain regions of subcortical volumes and cortical morphological measurements, and cortical measurements were more susceptible to site effects than subcortical volumes. Only the peak cortical thickness in developmental trajectories was significantly influenced by the effects of FS and R. Notably, ComBat-GAM harmonization effectively removed site effects while preserving developmental patterns.ConclusionOur findings pinpointed the key acquisition factors in in-utero fetal brain MRI and underscored the necessity of data harmonization when pooling multisite data for fetal brain morphology investigations.

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Section: Introductionmentioning

confidence: 99%

Site Effects in Multisite Fetal Brain MRI: Morphological Insights into Early Brain Development

Xu,

Sun,

et al. 2023

Preprint

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Advances in Neuroimaging and Multiple Post‐Processing Techniques for Epileptogenic Zone Detection of Drug‐Resistant Epilepsy

Yao,

Cheng,

Chen

et al. 2023

Magnetic Resonance Imaging

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Among the approximately 20 million patients with drug‐resistant epilepsy (DRE) worldwide, the vast majority can benefit from surgery to minimize seizure reduction and neurological impairment. Precise preoperative localization of epileptogenic zone (EZ) and complete resection of the lesions can influence the postoperative prognosis. However, precise localization of EZ is difficult, and the structural and functional alterations in the brain caused by DRE vary by etiology. Neuroimaging has emerged as an approach to identify the seizure‐inducing structural and functional changes in the brain, and magnetic resonance imaging (MRI) and positron emission tomography (PET) have become routine noninvasive imaging tools for preoperative evaluation of DRE in many epilepsy treatment centers. Multimodal neuroimaging offers unique advantages in detecting EZ, especially in improving the detection rate of patients with negative MRI or PET findings. This approach can characterize the brain imaging characteristics of patients with DRE caused by different etiologies, serving as a bridge between clinical and pathological findings and providing a basis for individualized clinical treatment plans. In addition to the integration of multimodal imaging modalities and the development of special scanning sequences and image post‐processing techniques for early and precise localization of EZ, the application of deep machine learning for extracting image features and deep learning‐based artificial intelligence have gradually improved diagnostic efficiency and accuracy. These improvements can provide clinical assistance for precisely outlining the scope of EZ and indicating the relationship between EZ and functional brain areas, thereby enabling standardized and precise surgery and ensuring good prognosis. However, most existing studies have limitations imposed by factors such as their small sample sizes or hypothesis‐based study designs. Therefore, we believe that the application of neuroimaging and post‐processing techniques in DRE requires further development and that more efficient and accurate imaging techniques are urgently needed in clinical practice.Level of Evidence5Technical EfficacyStage 2

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White Matter Tractography in Autism Spectrum Disorders Using Diffusion Tensor Imaging

Zaidi,

Acharjya,

Lora

et al. 2024

Lecture Notes in Electrical Engineering

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Application of data harmonization and tract-based spatial statistics reveals white matter structural abnormalities in pediatric patients with focal cortical dysplasia

Cited by 4 publications

References 49 publications

Site Effects in Multisite Fetal Brain MRI: Morphological Insights into Early Brain Development

Site Effects in Multisite Fetal Brain MRI: Morphological Insights into Early Brain Development

Advances in Neuroimaging and Multiple Post‐Processing Techniques for Epileptogenic Zone Detection of Drug‐Resistant Epilepsy

White Matter Tractography in Autism Spectrum Disorders Using Diffusion Tensor Imaging

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