Task-based fMRI

Abstract

This chapter gives an overview of the various analysis steps that are required after a functional magnetic resonance imaging (fMRI) experiment has been designed and carried out. The resulting data must be passed through various analysis steps before the experimenter can get answers to questions about experimentally related activations at the individual or multi-subject level. The aim of fMRI analysis is to identify in which voxels’ time-series the signal of interest is significantly greater than the noise level. The chapter also provides a brief overview of different approaches to obtaining activation maps, followed by a detailed introduction to analysis via the general linear model – currently the most popular statistical approach – and also various methods of thresholding the resulting statistics maps. It describes briefly the practical and numerical details involved in the analysis of a particular fMRI experiment.

https://academic.oup.com/book/10207/chapter-abstract/157892261

Abstract

Background and purpose:Language task-based functional MRI (fMRI) is increasingly used for presurgical planning in patients with brain lesions. Different paradigms elicit activations of different components of the language network. The aim of this study is to optimize fMRI clinical usage by comparing the effectiveness of three language tasks for language lateralization and localization in a large group of patients with brain lesions.

Methods:We analyzed fMRI data from a sequential retrospective cohort of 51 patients with brain lesions who underwent presurgical fMRI language mapping. We compared the effectiveness of three language tasks (Antonym Generation, Sentence Completion (SC), and Auditory Naming) for lateralizing language function and for activating cortex within patient-specific regions-of-interest representing eloquent language areas, and assessed the degree of spatial overlap of the areas of activation elicited by each task.

Results:The tasks were similarly effective for lateralizing language within the anterior language areas. The SC task produced higher laterality indices within the posterior language areas and had a significantly higher agreement with the clinical report. Dice coefficients between the task pairs were in the range of .351-.458, confirming substantial variation in the components of the language network activated by each task.

Conclusions:SC task consistently produced large activations within the dominant hemisphere and was more effective for lateralizing language within the posterior language areas. The low degree of spatial overlap among the tasks strongly supports the practice of using a battery of tasks to help the surgeon to avoid eloquent language areas.

https://pubmed.ncbi.nlm.nih.gov/30648771/

Abstract

Little is known about how language functional MRI (fMRI) is executed in clinical practice in spite of its widespread use. Here we comprehensively documented its execution in surgical planning in epilepsy. A questionnaire focusing on cognitive design, image acquisition, analysis and interpretation, and practical considerations was developed. Individuals responsible for collecting, analyzing, and interpreting clinical language fMRI data at 63 epilepsy surgical programs responded. The central finding was of marked heterogeneity in all aspects of fMRI. Most programs use multiple tasks, with a fifth routinely using 2, 3, 4, or 5 tasks with a modal run duration of 5 min. Variants of over 15 protocols are in routine use with forms of noun-verb generation, verbal fluency, and semantic decision-making used most often. Nearly all aspects of data acquisition and analysis vary markedly. Neither of the two best-validated protocols was used by more than 10% of respondents. Preprocessing steps are broadly consistent across sites, language-related blood flow is most often identified using general linear modeling (76% of respondents), and statistical thresholding typically varies by patient (79%). The software SPM is most often used. fMRI programs inconsistently include input from experts with all required skills (imaging, cognitive assessment, MR physics, statistical analysis, and brain-behavior relationships). These data highlight marked gaps between the evidence supporting fMRI and its clinical application. Teams performing language fMRI may benefit from evaluating practice with reference to the best-validated protocols to date and ensuring individuals trained in all aspects of fMRI are involved to optimize patient care.

https://pubmed.ncbi.nlm.nih.gov/29962111/

Abstract

Blood-oxygenation-level-dependent functional magnetic resonance imaging (BOLD fMRI) and diffusion tensor imaging (DTI) are specialized MRI-techniques used to map eloquent cortices and neural tracts in gray and white matter of the brain, respectively. By having the patient performing given tasks while inside the MRI-scanner (e.g. finger tapping), it is possible to map the cortical areas active during task performance (e.g. primary motor cortex) and visualize them as color maps overlain anatomical MRI-images. The most commonly areas mapped before neurosurgery in patients with brain lesions are primary motor and language areas. By acquiring DTI-images and further process them using a technique called tractography, it is possible to map important neural tracts and visualize them as fiber bundles (e.g. the corticospinal tract). The results from these examinations may be helpful during planning and resection of brain lesions, by providing information on functional eloquent cortices and important white matter tracts in close proximity to the lesion, as the goal of surgery is to maximize resection without inflicting neurological damage. This functional information may also be incorporated into neuronavigation systems and utilized during surgery, thus named functional neuronavigation. The following chapter will give an introduction to the basis of BOLD fMRI and DTI, as well as their methodological considerations and how to perform these investigations in practice, followed by how they have been utilized for preoperative mapping and functional neuronavigation so far. Finally, some suggestions to future directions are given.

https://link.springer.com/chapter/10.1007/978-94-007-1706-0_23

Abstract

This profile provides guidance for using functional magnetic resonance imaging (fMRI) to map the central brain components of the motor system for use in planning and guiding brain surgery or radiation treatment. The current focus is on using fMRI as a location biomarker for the center-of-mass of brain areas supporting hand movement that may be at risk of damage from invasive treatments. Accordingly, the goal of this QIBA Profile is to help the user to achieve a useful and specified level of performance of the biomarker.

This QIBA Profile (Mapping of Brain Motor Regions using Blood Oxygenation Level Dependent (BOLD) functional MRI as a Pretreatment Assessment Tool) has been developed to provide a systematic approach for optimizing Blood Oxygen Level Dependent (BOLD) fMRI brain mapping for treatment planning prior to surgery or invasive treatment intervention. It places requirements on Acquisition Devices, Technologists, Radiologist, Post-Processing Software and Image Analysis Tools involved in Subject Handling, Image Data Acquisition, Image Data Processing, Image QA and Image Analysis. Note users who plan to bill for imaging services using this profile should also consult the current procedural terminology (CPT) codes which may have additional requirements. Please refer to the ASFNR website for further information (https://www.asfnr.org/cpt-codes/).

https://qibawiki.rsna.org/images/b/b8/QIBA_fMRI_Profile_1_PC-rev1.pdf