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Yanmei Tie

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7 papers
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7

YNIMG Journal 2021 Journal Article

Clinical applications of magnetic resonance imaging based functional and structural connectivity

  • Chengyuan Wu
  • Francisca Ferreira
  • Michael Fox
  • Noam Harel
  • Jona Hattangadi-Gluth
  • Andreas Horn
  • Saad Jbabdi
  • Joshua Kahan

Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective.

YNICL Journal 2018 Journal Article

Challenges and techniques for presurgical brain mapping with functional MRI

  • Michael A. Silva
  • Alfred P. See
  • Walid I. Essayed
  • Alexandra J. Golby
  • Yanmei Tie

Functional magnetic resonance imaging (fMRI) is increasingly used for preoperative counseling and planning, and intraoperative guidance for tumor resection in the eloquent cortex. Although there have been improvements in image resolution and artifact correction, there are still limitations of this modality. In this review, we discuss clinical fMRI's applications, limitations and potential solutions. These limitations depend on the following parameters: foundations of fMRI, physiologic effects of the disease, distinctions between clinical and research fMRI, and the design of the fMRI study. We also compare fMRI to other brain mapping modalities which should be considered as alternatives or adjuncts when appropriate, and discuss intraoperative use and validation of fMRI. These concepts direct the clinical application of fMRI in neurosurgical patients.

YNICL Journal 2015 Journal Article

Reconstruction of the arcuate fasciculus for surgical planning in the setting of peritumoral edema using two-tensor unscented Kalman filter tractography

  • Zhenrui Chen
  • Yanmei Tie
  • Olutayo Olubiyi
  • Laura Rigolo
  • Alireza Mehrtash
  • Isaiah Norton
  • Ofer Pasternak
  • Yogesh Rathi

BACKGROUND: Diffusion imaging tractography is increasingly used to trace critical fiber tracts in brain tumor patients to reduce the risk of post-operative neurological deficit. However, the effects of peritumoral edema pose a challenge to conventional tractography using the standard diffusion tensor model. The aim of this study was to present a novel technique using a two-tensor unscented Kalman filter (UKF) algorithm to track the arcuate fasciculus (AF) in brain tumor patients with peritumoral edema. METHODS: Ten right-handed patients with left-sided brain tumors in the vicinity of language-related cortex and evidence of significant peritumoral edema were retrospectively selected for the study. All patients underwent 3-Tesla magnetic resonance imaging (MRI) including a diffusion-weighted dataset with 31 directions. Fiber tractography was performed using both single-tensor streamline and two-tensor UKF tractography. A two-regions-of-interest approach was applied to perform the delineation of the AF. Results from the two different tractography algorithms were compared visually and quantitatively. RESULTS: Using single-tensor streamline tractography, the AF appeared disrupted in four patients and contained few fibers in the remaining six patients. Two-tensor UKF tractography delineated an AF that traversed edematous brain areas in all patients. The volume of the AF was significantly larger on two-tensor UKF than on single-tensor streamline tractography (p < 0.01). CONCLUSIONS: Two-tensor UKF tractography provides the ability to trace a larger volume AF than single-tensor streamline tractography in the setting of peritumoral edema in brain tumor patients.

YNIMG Journal 2014 Journal Article

Decoupling function and anatomy in atlases of functional connectivity patterns: Language mapping in tumor patients

  • Georg Langs
  • Andrew Sweet
  • Danial Lashkari
  • Yanmei Tie
  • Laura Rigolo
  • Alexandra J. Golby
  • Polina Golland

In this paper we construct an atlas that summarizes functional connectivity characteristics of a cognitive process from a population of individuals. The atlas encodes functional connectivity structure in a low-dimensional embedding space that is derived from a diffusion process on a graph that represents correlations of fMRI time courses. The functional atlas is decoupled from the anatomical space, and thus can represent functional networks with variable spatial distribution in a population. In practice the atlas is represented by a common prior distribution for the embedded fMRI signals of all subjects. We derive an algorithm for fitting this generative model to the observed data in a population. Our results in a language fMRI study demonstrate that the method identifies coherent and functionally equivalent regions across subjects. The method also successfully maps functional networks from a healthy population used as a training set to individuals whose language networks are affected by tumors.

NeurIPS Conference 2010 Conference Paper

Functional Geometry Alignment and Localization of Brain Areas

  • Georg Langs
  • Yanmei Tie
  • Laura Rigolo
  • Alexandra Golby
  • Polina Golland

Matching functional brain regions across individuals is a challenging task, largely due to the variability in their location and extent. It is particularly difficult, but highly relevant, for patients with pathologies such as brain tumors, which can cause substantial reorganization of functional systems. In such cases spatial registration based on anatomical data is only of limited value if the goal is to establish correspondences of functional areas among different individuals, or to localize potentially displaced active regions. Rather than rely on spatial alignment, we propose to perform registration in an alternative space whose geometry is governed by the functional interaction patterns in the brain. We first embed each brain into a functional map that reflects connectivity patterns during a fMRI experiment. The resulting functional maps are then registered, and the obtained correspondences are propagated back to the two brains. In application to a language fMRI experiment, our preliminary results suggest that the proposed method yields improved functional correspondences across subjects. This advantage is pronounced for subjects with tumors that affect the language areas and thus cause spatial reorganization of the functional regions.

YNIMG Journal 2009 Journal Article

Comparison of blocked and event-related fMRI designs for pre-surgical language mapping

  • Yanmei Tie
  • Ralph O. Suarez
  • Stephen Whalen
  • Alireza Radmanesh
  • Isaiah H. Norton
  • Alexandra J. Golby

Language functional magnetic resonance imaging (fMRI) is a promising non-invasive technique for pre-surgical planning in patients whose lesions are adjacent to or within critical language areas. Most language fMRI studies in patients use blocked experimental design. In this study, we compared a blocked design and a rapid event-related design with a jittered inter-stimulus-interval (ISI) (or stochastic design) for language fMRI in six healthy controls, and eight brain tumor patients, using a vocalized antonym generation task. Comparisons were based on visual inspection of fMRI activation maps and degree of language lateralization, both of which were assessed at a constant statistical threshold for each design. The results indicated a relatively high degree of discordance between the two task designs. In general, the event-related design provided maps with more robust activations in the putative language areas than the blocked design, especially for brain tumor patients. Our results suggest that the rapid event-related design has potential for providing comparable or even higher detection power over the blocked design for localizing language function in brain tumor patients, and therefore may be able to generate more sensitive language maps. More patient studies, and further investigation and optimization of language fMRI paradigms will be needed to determine the utility and validity of this approach for pre-surgical planning.

YNIMG Journal 2008 Journal Article

Group independent component analysis of language fMRI from word generation tasks

  • Yanmei Tie
  • Stephen Whalen
  • Ralph O. Suarez
  • Alexandra J. Golby

Language fMRI has been used to study brain regions involved in language processing and has been applied to pre-surgical language mapping. However, in order to provide clinicians with optimal information, the sensitivity and specificity of language fMRI needs to be improved. Type II error of failing to reach statistical significance when the language activations are genuinely present may be particularly relevant to pre-surgical planning, by falsely indicating low surgical risk in areas where no activations are shown. Furthermore, since the execution of language paradigms involves cognitive processes other than language function per se, the conventional general linear model (GLM) method may identify non-language-specific activations. In this study, we assessed an exploratory approach, independent component analysis (ICA), as a potential complementary method to the inferential GLM method in language mapping applications. We specifically investigated whether this approach might reduce type II error as well as generate more language-specific maps. Fourteen right-handed healthy subjects were studied with fMRI during two word generation tasks. A similarity analysis across tasks was proposed to select components of interest. Union analysis was performed on the language-specific components to increase sensitivity, and conjunction analysis was performed to identify language areas more likely to be essential. Compared with GLM, ICA identified more activated voxels in the putative language areas, and signals from other sources were isolated into different components. Encouraging results from one brain tumor patient are also presented. ICA may be used as a complementary tool to GLM in improving pre-surgical language mapping.

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