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Article: Acquisition and Analysis of Excised Neocortex from Pediatric Patients with Focal Cortical Dysplasia Using Mesoscale Diffusion MRI.

Fountain, Chandler / Ghuman, Harmanvir / Paldino, Michael / Tamber, Mandeep / Panigrahy, Ashok / Modo, Michel

2023 Volume 13, Issue 9

Abstract: Non-invasive classification of focal cortical dysplasia (FCD) subtypes remains challenging from a radiology perspective. Quantitative imaging biomarkers (QIBs) have the potential to distinguish subtypes that lack pathognomonic features and might help in ... ...

Abstract	Non-invasive classification of focal cortical dysplasia (FCD) subtypes remains challenging from a radiology perspective. Quantitative imaging biomarkers (QIBs) have the potential to distinguish subtypes that lack pathognomonic features and might help in defining the extent of abnormal connectivity associated with each FCD subtype. A key motivation of diagnostic imaging is to improve the localization of a "lesion" that can guide the surgical resection of affected tissue, which is thought to cause seizures. Conversely, surgical resections to eliminate or reduce seizures provided unique opportunities to develop magnetic resonance imaging (MRI)-based QIBs by affording long scan times to evaluate multiple contrast mechanisms at the mesoscale (0.5 mm isotropic voxel dimensions). Using ex vivo hybrid diffusion tensor imaging on a 9.4 T MRI scanner, the grey to white matter ratio of scalar indices was lower in the resected middle temporal gyrus (MTG) of two neuropathologically confirmed cases of FCD compared to non-diseased control postmortem fixed temporal lobes. In contrast, fractional anisotropy was increased within FCD and also adjacent white matter tracts. Connectivity (streamlines/mm
Language	English
Publishing date	2023-04-24
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2662336-5
ISSN	2075-4418
ISSN	2075-4418
DOI	10.3390/diagnostics13091529
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Article ; Online: Sport and exercise in genotype positive (+) phenotype negative (-) individuals: current dilemmas and future perspectives.

Paldino, Alessia / Rossi, Maddalena / Dal Ferro, Matteo / Tavčar, Irena / Behr, Elijah / Sharma, Sanjay / Papadakis, Michael / Sinagra, Gianfranco / Finocchiaro, Gherardo

European journal of preventive cardiology

2023 Volume 30, Issue 9, Page(s) 871–883

Abstract: Genotype positive-phenotype negative (GEN+PHEN-) individuals harbour a pathogenic or likely pathogenic variant without exhibiting a phenotypic manifestation of the disease. In the last few years, the widespread use of genetic testing in probands and ... ...

Abstract	Genotype positive-phenotype negative (GEN+PHEN-) individuals harbour a pathogenic or likely pathogenic variant without exhibiting a phenotypic manifestation of the disease. In the last few years, the widespread use of genetic testing in probands and relatives has increasingly led to the identification of these individuals, with emerging dilemmas regarding their clinical management. A genetic variant may exhibit a variable expressivity even in the same family and spontaneous conversion to overt phenotype is largely unpredictable. Little is known about the possible influence of environmental factors, such intense or moderate exercise with open questions regarding their possible role in promoting or worsening the phenotypic expression. Current guidelines for sports participation in this setting acknowledge the weak burden of evidence and the many uncertainties. The recommendations to engage in intensive exercise and competitive sports are usually contingent on annual clinical surveillance, except for pathogenic variants in specific genes, such as lamin A/C or plakophilin-2. In certain conditions, such as arrhythmogenic cardiomyopathy, guidelines do not differentiate between GEN+PHEN- individuals and patients with overt disease and recommend avoiding participation in high-intensity recreational exercise and competitive sports. It should be emphasized that international guidelines, traditionally restrictive in terms of sports participation and focused on disqualification, embraced recently a more liberal attitude promoting a shared decision-making approach in the absence of clinical markers of increased risk. In this review, we will discuss the current state of knowledge on GEN+PHEN- individuals and the dilemmas surrounding the impact of exercise and prognosis, focusing on cardiomyopathies and channelopathies, which are the predominant causes of sudden cardiac death in the young and in young athletes.
MeSH term(s)	Humans ; Sports ; Exercise ; Cardiomyopathies ; Death, Sudden, Cardiac/etiology ; Death, Sudden, Cardiac/prevention & control ; Phenotype ; Genotype
Language	English
Publishing date	2023-05-05
Publishing country	England
Document type	Review ; Journal Article
ZDB-ID	2626011-6
ISSN	2047-4881 ; 2047-4873
ISSN (online)	2047-4881
ISSN	2047-4873
DOI	10.1093/eurjpc/zwad079
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Article ; Online: Normalization enhances brain network features that predict individual intelligence in children with epilepsy.

Paldino, Michael J / Golriz, Farahnaz / Zhang, Wei / Chu, Zili D

PloS one

2019 Volume 14, Issue 3, Page(s) e0212901

Abstract: Background and purpose: Architecture of the cerebral network has been shown to associate with IQ in children with epilepsy. However, subject-level prediction on this basis, a crucial step toward harnessing network analyses for the benefit of children ... ...

Abstract	Background and purpose: Architecture of the cerebral network has been shown to associate with IQ in children with epilepsy. However, subject-level prediction on this basis, a crucial step toward harnessing network analyses for the benefit of children with epilepsy, has yet to be achieved. We compared two network normalization strategies in terms of their ability to optimize subject-level inferences on the relationship between brain network architecture and brain function. Materials and methods: Patients with epilepsy and resting state fMRI were retrospectively identified. Brain network nodes were defined by anatomic parcellation, first in patient space (nodes defined for each patient) and again in template space (same nodes for all patients). Whole-brain weighted graphs were constructed according to pair-wise correlation of BOLD-signal time courses between nodes. The following metrics were then calculated: clustering coefficient, transitivity, modularity, path length, and global efficiency. Metrics computed on graphs in patient space were normalized to the same metric computed on a random network of identical size. A machine learning algorithm was used to predict patient IQ given access to only the network metrics. Results: Twenty-seven patients (8-18 years) comprised the final study group. All brain networks demonstrated expected small world properties. Accounting for intrinsic population heterogeneity had a significant effect on prediction accuracy. Specifically, transformation of all patients into a common standard space as well as normalization of metrics to those computed on a random network both substantially outperformed the use of non-normalized metrics. Conclusion: Normalization contributed significantly to accurate subject-level prediction of cognitive function in children with epilepsy. These findings support the potential for quantitative network approaches to contribute clinically meaningful information in children with neurological disorders.
MeSH term(s)	Adolescent ; Brain/diagnostic imaging ; Brain/physiopathology ; Child ; Epilepsy/diagnostic imaging ; Epilepsy/physiopathology ; Female ; Humans ; Image Processing, Computer-Assisted/methods ; Intelligence/physiology ; Machine Learning ; Magnetic Resonance Imaging ; Male ; Nerve Net/diagnostic imaging ; Nerve Net/physiopathology ; Retrospective Studies
Language	English
Publishing date	2019-03-05
Publishing country	United States
Document type	Journal Article
ISSN	1932-6203
ISSN (online)	1932-6203
DOI	10.1371/journal.pone.0212901
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Article: Localization of epileptic seizure focus by computerized analysis of fMRI recordings.

Hekmati, Rasoul / Azencott, Robert / Zhang, Wei / Chu, Zili D / Paldino, Michael J

Brain informatics

2020 Volume 7, Issue 1, Page(s) 13

Abstract: By computerized analysis of cortical activity recorded via fMRI for pediatric epilepsy patients, we implement algorithmic localization of epileptic seizure focus within one of eight cortical lobes. Our innovative machine learning techniques involve ... ...

Abstract	By computerized analysis of cortical activity recorded via fMRI for pediatric epilepsy patients, we implement algorithmic localization of epileptic seizure focus within one of eight cortical lobes. Our innovative machine learning techniques involve intensive analysis of large matrices of mutual information coefficients between pairs of anatomically identified cortical regions. Drastic selection of pairs of regions with biologically significant inter-connectivity provides efficient inputs for our multi-layer perceptron (MLP) classifier. By imposing rigorous parameter parsimony to avoid overfitting, we construct a small-size MLP with very good percentages of successful classification.
Language	English
Publishing date	2020-10-31
Publishing country	Germany
Document type	Journal Article
ISSN	2198-4018
ISSN	2198-4018
DOI	10.1186/s40708-020-00114-0
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Article: Determination of Differences in Seed-Based Resting State Functional Magnetic Resonance Imaging Language Networks in Pediatric Patients with Left- and Right-Lateralized Language: A Pilot Study.

Nath, Audrey / Robinson, Meghan / Magnotti, John / Karas, Patrick / Curry, Daniel / Paldino, Michael

Journal of epilepsy research

2019 Volume 9, Issue 2, Page(s) 93–102

Abstract: Background and purpose: The current tools available for localization of expressive language, including functional magnetic resonance imaging (fMRI) and cortical stimulation mapping (CSM), require that the patient remain stationary and follow language ... ...

Abstract	Background and purpose: The current tools available for localization of expressive language, including functional magnetic resonance imaging (fMRI) and cortical stimulation mapping (CSM), require that the patient remain stationary and follow language commands with precise timing. Many pediatric epilepsy patients, however, have intact language skills but are unable to participate in these tasks due to cognitive impairments or young age. In adult subjects, there is evidence that language laterality can be determined by resting state (RS) fMRI activity, however there are few studies on the use of RS to accurately predict language laterality in children. Methods: A retrospective review of pediatric patients at Texas Children's Hospital was performed to identify patients who have undergone epilepsy surgical planning over 3 years with language localization using traditional methods of Wada testing, CSM, or task-based fMRI with calculated laterality index, as well as a 7-minute RS scan available without excessive motion or noise. We found the correlation between each subject's left and right Broca's region activity and each of 68 cortical regions. Results: A group of nine patients with left-lateralized language were found to have greater voxel-wise correlations than a group of six patients with right-lateralized language between a left hemispheric Broca's region seed and the following six cortical regions: left inferior temporal, left lateral orbitofrontal, left pars triangularis, right lateral orbitofrontal, right pars orbitalis and right superior frontal regions. Conclusions: In a cohort of children with epilepsy, we found that patients with left- and right-hemispheric language lateralization have different RS networks.
Language	English
Publishing date	2019-12-31
Publishing country	Korea (South)
Document type	Journal Article
ZDB-ID	2771719-7
ISSN	2233-6257 ; 2233-6249
ISSN (online)	2233-6257
ISSN	2233-6249
DOI	10.14581/jer.19011
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Article ; Online: Normalization enhances brain network features that predict individual intelligence in children with epilepsy.

Michael J Paldino / Farahnaz Golriz / Wei Zhang / Zili D Chu

PLoS ONE, Vol 14, Iss 3, p e

2019 Volume 0212901

Abstract: BACKGROUND AND PURPOSE:Architecture of the cerebral network has been shown to associate with IQ in children with epilepsy. However, subject-level prediction on this basis, a crucial step toward harnessing network analyses for the benefit of children with ...

Abstract	BACKGROUND AND PURPOSE:Architecture of the cerebral network has been shown to associate with IQ in children with epilepsy. However, subject-level prediction on this basis, a crucial step toward harnessing network analyses for the benefit of children with epilepsy, has yet to be achieved. We compared two network normalization strategies in terms of their ability to optimize subject-level inferences on the relationship between brain network architecture and brain function. MATERIALS AND METHODS:Patients with epilepsy and resting state fMRI were retrospectively identified. Brain network nodes were defined by anatomic parcellation, first in patient space (nodes defined for each patient) and again in template space (same nodes for all patients). Whole-brain weighted graphs were constructed according to pair-wise correlation of BOLD-signal time courses between nodes. The following metrics were then calculated: clustering coefficient, transitivity, modularity, path length, and global efficiency. Metrics computed on graphs in patient space were normalized to the same metric computed on a random network of identical size. A machine learning algorithm was used to predict patient IQ given access to only the network metrics. RESULTS:Twenty-seven patients (8-18 years) comprised the final study group. All brain networks demonstrated expected small world properties. Accounting for intrinsic population heterogeneity had a significant effect on prediction accuracy. Specifically, transformation of all patients into a common standard space as well as normalization of metrics to those computed on a random network both substantially outperformed the use of non-normalized metrics. CONCLUSION:Normalization contributed significantly to accurate subject-level prediction of cognitive function in children with epilepsy. These findings support the potential for quantitative network approaches to contribute clinically meaningful information in children with neurological disorders.
Keywords	Medicine ; R ; Science ; Q
Subject code	006
Language	English
Publishing date	2019-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
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Article: Quantitative Sodium (

Bhatia, Aashim / Lee, Vincent Kyu / Qian, Yongxian / Paldino, Michael J / Ceschin, Rafael / Hect, Jasmine / Mountz, James M / Sun, Dandan / Kohanbash, Gary / Pollack, Ian F / Jakacki, Regina I / Boada, Fernando / Panigrahy, Ashok

Diagnostics (Basel, Switzerland)

2022 Volume 12, Issue 5

Abstract: Background: 23Na MRI correlates with tumor proliferation, and studies in pediatric patients are lacking. The purpose of the study: (1) to compare total sodium concentration (TSC) between pediatric glioma and non-neoplastic brain tissue using 23Na MRI; (2) ...

Abstract	Background: 23Na MRI correlates with tumor proliferation, and studies in pediatric patients are lacking. The purpose of the study: (1) to compare total sodium concentration (TSC) between pediatric glioma and non-neoplastic brain tissue using 23Na MRI; (2) compare tissue conspicuity of bound sodium concentration (BSC) using 23Na MRI dual echo relative to TSC imaging. Methods: TSC was measured in: (1) non-neoplastic brain tissues and (2) three types of manually segmented gliomas (diffuse intrinsic brainstem glioma (DIPG), recurrent supratentorial low-grade glioma (LGG), and high-grade glioma (HGG)). In a subset of patients, serial changes in both TSC and BSC (dual echo 23Na MRI) were assessed. Results: Twenty-six pediatric patients with gliomas (median age of 12.0 years, range 4.9−23.3 years) were scanned with 23Na MRI. DIPG treated with RT demonstrated higher TSC values than the uninvolved infratentorial tissues (p < 0.001). Recurrent supratentorial LGG and HGG exhibited higher TSC values than the uninvolved white matter (WM) and gray matter (GM) (p < 0.002 for LGG, and p < 0.02 for HGG). The dual echo 23Na MRI suppressed the sodium signal within both CSF and necrotic foci. Conclusion: Quantitative 23Na MRI of pediatric gliomas demonstrates a range of values that are higher than non-neoplastic tissues. Dual echo 23Na MRI of BCS improves tissue conspicuity relative to TSC imaging.
Language	English
Publishing date	2022-05-13
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2662336-5
ISSN	2075-4418
ISSN	2075-4418
DOI	10.3390/diagnostics12051223
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Article ; Online: Metrics of brain network architecture capture the impact of disease in children with epilepsy.

Paldino, Michael J / Zhang, Wei / Chu, Zili D / Golriz, Farahnaz

NeuroImage. Clinical

2017 Volume 13, Page(s) 201–208

Abstract: Background and objective: Epilepsy is associated with alterations in the structural framework of the cerebral network. The aim of this study was to measure the potential of global metrics of network architecture derived from resting state functional MRI ...

Abstract	Background and objective: Epilepsy is associated with alterations in the structural framework of the cerebral network. The aim of this study was to measure the potential of global metrics of network architecture derived from resting state functional MRI to capture the impact of epilepsy on the developing brain. Methods: Pediatric patients were retrospectively identified with: 1. Focal epilepsy; 2. Brain MRI at 3 Tesla, including resting state functional MRI; 3. Full scale IQ measured by a pediatric neuropsychologist. The cerebral cortex was parcellated into approximately 700 gray matter network nodes. The strength of a connection between two nodes was defined as the correlation between their resting BOLD signal time series. The following global network metrics were then calculated: clustering coefficient, transitivity, modularity, path length, and global efficiency. Epilepsy duration was used as an index for the cumulative impact of epilepsy on the brain. Results: 45 patients met criteria (age: 4-19 years). After accounting for age of epilepsy onset, epilepsy duration was inversely related to IQ ( Conclusions: We observed that a machine learning algorithm accurately predicted epilepsy duration based on global metrics of network architecture derived from resting state fMRI. These findings suggest that network metrics have the potential to form the basis for statistical models that translate quantitative imaging data into patient-level markers of cognitive deterioration.
Language	English
Publishing date	2017
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2701571-3
ISSN	2213-1582 ; 2213-1582
ISSN (online)	2213-1582
ISSN	2213-1582
DOI	10.1016/j.nicl.2016.12.005
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Article ; Online: Localization of epileptic seizure focus by computerized analysis of fMRI recordings

Rasoul Hekmati / Robert Azencott / Wei Zhang / Zili D. Chu / Michael J. Paldino

Brain Informatics, Vol 7, Iss 1, Pp 1-

2020 Volume 13

Abstract: Abstract By computerized analysis of cortical activity recorded via fMRI for pediatric epilepsy patients, we implement algorithmic localization of epileptic seizure focus within one of eight cortical lobes. Our innovative machine learning techniques ... ...

Abstract	Abstract By computerized analysis of cortical activity recorded via fMRI for pediatric epilepsy patients, we implement algorithmic localization of epileptic seizure focus within one of eight cortical lobes. Our innovative machine learning techniques involve intensive analysis of large matrices of mutual information coefficients between pairs of anatomically identified cortical regions. Drastic selection of pairs of regions with biologically significant inter-connectivity provides efficient inputs for our multi-layer perceptron (MLP) classifier. By imposing rigorous parameter parsimony to avoid overfitting, we construct a small-size MLP with very good percentages of successful classification.
Keywords	Time series ; Deep learning ; Mutual information ; fMRI ; Epilepsy ; Seizure focus ; Computer applications to medicine. Medical informatics ; R858-859.7 ; Computer software ; QA76.75-76.765
Language	English
Publishing date	2020-10-01T00:00:00Z
Publisher	SpringerOpen
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Indirect revascularization with the dural inversion technique for pediatric moyamoya disease: 20-year experience.

Gadgil, Nisha / Lam, Sandi / Pyarali, Monika / Paldino, Michael / Pan, I-Wen / Dauser, Robert C

Journal of neurosurgery. Pediatrics

2018 Volume 22, Issue 5, Page(s) 541–549

Abstract: OBJECTIVENumerous surgical procedures facilitate revascularization of the ischemic brain in patients with moyamoya disease. Dural inversion is a technique in which flaps of dura mater centered around the middle meningeal artery are inverted, encouraging ... ...

Abstract	OBJECTIVENumerous surgical procedures facilitate revascularization of the ischemic brain in patients with moyamoya disease. Dural inversion is a technique in which flaps of dura mater centered around the middle meningeal artery are inverted, encouraging the formation of a rich collateral blood supply. This procedure has been used in combination with encephaloduroarteriosynangiosis for more than 20 years at the authors' institution for the treatment of pediatric moyamoya disease. The objective of this study was to describe the clinical and radiographic outcomes for a cohort of consecutive pediatric moyamoya patients undergoing dural inversion.METHODSClinical and radiographic data on patients who had undergone dural inversion in the period from 1997 to 2016 were reviewed. Univariate and multivariate logistic regression and Kaplan-Meier analyses were performed to assess the risk of postoperative stroke, functional outcome, and the angiographic degree of revascularization.RESULTSDural inversion was performed on 169 hemispheres in 102 patients. Median follow-up was 4.3 years. Six patients (3.6% of hemispheres) suffered postoperative ischemic or hemorrhagic stroke. Overall mortality was 1.0%. Good postoperative neurological status (modified Rankin Scale [mRS] score ≤ 2) was observed in 90 patients (88%); preoperative and postoperative mRS scores showed significant improvement (p < 0.001). Eighty-six percent of hemispheres had Matsushima grade A or B revascularization. Younger age was associated with postoperative stroke and poor functional outcome. Patients with secondary moyamoya syndrome had a significantly worse radiographic outcome. The cumulative 5-year Kaplan-Meier risk for stroke was 6.4%.CONCLUSIONSDural inversion is a useful technique of cerebral revascularization in pediatric moyamoya disease. A 20-year experience demonstrates the safety and efficacy of this technique with a relatively low rate of postoperative stroke, good functional outcomes, and favorable angiographic results.
MeSH term(s)	Adolescent ; Brain/diagnostic imaging ; Brain/surgery ; Cerebral Angiography ; Cerebral Revascularization/methods ; Child ; Child, Preschool ; Dura Mater/surgery ; Female ; Humans ; Infant ; Magnetic Resonance Angiography ; Magnetic Resonance Imaging ; Male ; Moyamoya Disease/diagnostic imaging ; Moyamoya Disease/surgery ; Retrospective Studies ; Treatment Outcome ; Young Adult
Language	English
Publishing date	2018-08-06
Publishing country	United States
Document type	Journal Article
ZDB-ID	2403985-8
ISSN	1933-0715 ; 1933-0707
ISSN (online)	1933-0715
ISSN	1933-0707
DOI	10.3171/2018.5.PEDS18163
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