The Significance of Streamlined Postprocessing Approaches for Clinical fMRI

Pillai, Jay J.

doi:10.3174/ajnr.a3446

Cited by 5 publications

(1 citation statement)

References 9 publications

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“…Both these techniques require additional scan time and processing time, and, for this reason, they are not routinely applied in presurgical clinical functional imaging examinations. 29 For this reason, a manual coregistration approach has been suggested by Nennig and colleagues 30 in their proposed pipeline for standardized clinical fMRI data processing. This approach has been shown to provide reliable results but is still operator dependent and requires dedicated personnel.…”

Section: Geometric Distortionsmentioning

confidence: 99%

Special Considerations/Technical Limitations of Blood-Oxygen-Level-Dependent Functional Magnetic Resonance Imaging

Zacà

Agarwal

Gujar

et al. 2014

Neuroimaging Clinics of North America

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Section: Geometric Distortionsmentioning

confidence: 99%

Special Considerations/Technical Limitations of Blood-Oxygen-Level-Dependent Functional Magnetic Resonance Imaging

Zacà

Agarwal

Gujar

et al. 2014

Neuroimaging Clinics of North America

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fMRI and DTI: Review of Complementary Techniques

Agarwal

Khalifah

Zacà

et al. 2023

Functional Neuroradiology

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PreSurgMapp: a MATLAB Toolbox for Presurgical Mapping of Eloquent Functional Areas Based on Task-Related and Resting-State Functional MRI

et al. 2016

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The main goal of brain tumor surgery is to maximize tumor resection while minimizing the risk of irreversible postoperative functional sequelae. Eloquent functional areas should be delineated preoperatively, particularly for patients with tumors near eloquent areas. Functional magnetic resonance imaging (fMRI) is a noninvasive technique that demonstrates great promise for presurgical planning. However, specialized data processing toolkits for presurgical planning remain lacking. Based on several functions in open-source software such as Statistical Parametric Mapping (SPM), Resting-State fMRI Data Analysis Toolkit (REST), Data Processing Assistant for Resting-State fMRI (DPARSF) and Multiple Independent Component Analysis (MICA), here, we introduce an open-source MATLAB toolbox named PreSurgMapp. This toolbox can reveal eloquent areas using comprehensive methods and various complementary fMRI modalities. For example, PreSurgMapp supports both model-based (general linear model, GLM, and seed correlation) and data-driven (independent component analysis, ICA) methods and processes both task-based and resting-state fMRI data. PreSurgMapp is designed for highly automatic and individualized functional mapping with a user-friendly graphical user interface (GUI) for time-saving pipeline processing. For example, sensorimotor and language-related components can be automatically identified without human input interference using an effective, accurate component identification algorithm using discriminability index. All the results generated can be further evaluated and compared by neuro-radiologists or neurosurgeons. This software has substantial value for clinical neuro-radiology and neuro-oncology, including application to patients with low- and high-grade brain tumors and those with epilepsy foci in the dominant language hemisphere who are planning to undergo a temporal lobectomy.

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The Significance of Streamlined Postprocessing Approaches for Clinical fMRI

Cited by 5 publications

References 9 publications

Special Considerations/Technical Limitations of Blood-Oxygen-Level-Dependent Functional Magnetic Resonance Imaging

Special Considerations/Technical Limitations of Blood-Oxygen-Level-Dependent Functional Magnetic Resonance Imaging

fMRI and DTI: Review of Complementary Techniques

PreSurgMapp: a MATLAB Toolbox for Presurgical Mapping of Eloquent Functional Areas Based on Task-Related and Resting-State Functional MRI

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