Fiber Tractography Lab

The goal of the Fiber Tractography Lab is to solve the structure-function puzzles of the brain and to improve clinical diagnosis and evaluation of brain disorders using novel brain imaging techniques.

We leverage three principle approaches to achieve this goal:

Construct analytical tools for mapping and analyzing brain connections
Collect and curate high-resolution brain atlas resources that reveal brain connections.
Apply novel analytical tools for clinical studies to improve diagnostic and prognostic evaluation.

The following is a list of ongoing projects

DSI Studio—An Integrative Platform for Tractography

DSI Studio

DSI Studio is the major contribution of the PI in his academic career. Since its introduction, DSI Studio has been used and cited in more than 3000 publications.

DSI Studio is an open-source diffusion MRI analysis tool that maps brain connections, characterizes their biophysical metrics, and correlates the metrics with neuropsychological variables. It is a collective implementation of diffusion MRI methods and has established its unique scientific impact.

At UPMC, DSI Studio has been used to assist clinical research, such as brain tumor pre-surgical planning and tractography visualization with sEEG electrodes.

Reference:

Yeh, Fang-Cheng. "DSI Studio: an integrated tractography platform and fiber data hub for accelerating brain research." Nature Methods (2025): 1-3.

Website:

http://dsi-studio.labsolver.org

Source Code:

https://github.com/frankyeh/DSI-Studio

Diffusion MRI has arisen as the only non-invasive way to map white matter bundles and assess their structural integrity in the human brain. With fast imaging sequences, diffusion MRI, in particular its high angular resolution variants, can be acquired on standard clinical scanners. This advancement has gained considerable interest because of its roles in mapping human connectome and potential for accessing neuropsychological disorders. There is a growing interest in large-scale analysis of diffusion MRI to explore its promising applications in biomedical research as an imaging biomarker of neuropathology.

We developed a high-accuracy fiber tracking method powered by generalized q-sampling imaging (Yeh et al., 2010) and its derived tracking method (Yeh et al., 2013). The method was released as an open-source tool to the public known as “DSI Studio” (http://dsi-studio.labsolver.org). This fiber tracking method is a long-term collaborative effort between diffusion MRI radiologists, psychologists, and neurosurgeons (Fernandez-Miranda et al., 2012; Yeh et al., 2013b; Yeh et al., 2010). The approach was previously optimized using capillary phantoms and validated by experienced neurosurgeons (Yeh et al., 2013b), leading to its outperformance over other competing algorithms.

Right: DSI Studio tractography on the cover of “Nature Reviews Neurology” for the whole year of 2017. About the cover. Brains and beauty — the 2017 cover. Nat Rev Neurol 13, 1 (2017)

Tractography for Brain Tumor Surgical Planning

Removing a brain tumor is a difficult task for neurosurgeons without the appropriate tools. Brain tumor surgery involves a decision process during presurgical planning that may compromise the safety of patients due to the increased risk of developing permanent disabilities. This risk will always be present, as long as neurosurgeons perform approaches without visualizing the position of critical brain structures or knowing their relationship with the tumor.

Visualization of white matter pathways can be achieved by the use of tractography, a technology that involves the combination of acquisition of brain images through diffusion MRI, which are later reconstructed using generalized q-sampling imaging to obtain voxel-sized information such as quantitative anisotropy that allows to map white matter pathways in the brain. The mapping of brain connections involved in critical functions (e.g. vision, language) from one region to another may be used by neurosurgeons to preserve these pathways and safely remove the tumor without producing unnecessary damage and preventing patients from developing permanent disabilities.

Under the research projects, our research tool has helped more than 200 brain tumor patients at the University of Pittsburgh Medical Center:

Patient’s story: 1, 2, 3

Fiber tracking in DSI Studio provides a superior presurgical evaluation of the fiber tracts for patients with complex brain lesions, including low-grade and high-grade gliomas. Presurgical studies are built upon precise and accurate neuroanatomical knowledge, which allows doctors to reconstruct perilesional or intralesional fiber tracts, design the less invasive trajectory into the target lesion and apply more effectively intraoperative electrical mapping techniques for maximal and safe tumor resection in eloquent cortical and subcortical regions.

Our clinical experience applying DSI Studio fiber tracking has been reported in Neurosurgery, Journal of Neurosurgery, and Neuro-oncology among others. We are actively investigating its potential for not only presurgical planning and intraoperative navigation but also for neurostructural damage assessment, estimation of postsurgical neural pathways damage and recovery, and tracking of postsurgical changes and responses to rehabilitation therapy. The latest innovation is the reconstruction of cranial nerves for presurgical evaluation in skull base surgery, with very promising results. The ultimate goal is to facilitate brain function preservation and recovery in patients undergoing complex brain surgery.

From a clinical perspective, our tracking method provides accurate structural connectivity studies in patients with intracerebral lesions (Abhinav et al., 2014b; Fernandez-Miranda et al., 2012; Yeh et al., 2013a) with other numerous applications in neurological and psychiatric disorders (see more than 200 journal publications in the last three years using DSI Studio, allowing for qualitative and quantitative white matter damage assessment, aiding in understanding lesion patterns of white matter structural injury, and facilitating innovative neurological and psychiatric applications. We conducted several studies to show that our tracking approach correlates well with histology (Gangolli et al., 2017; Modo et al., 2016) and cadaver microdissection in mapping several fiber pathways (Fernandez-Miranda et al., 2012; Fernandez-Miranda et al., 2014; Meola et al., 2016a; Meola et al., 2015; Meola et al., 2016b; Wang et al., 2016; Wang et al., 2013; Yoshino et al., 2016) and is a major improvement over DTI tractography (Abhinav et al., 2014a; Abhinav et al., 2014c; Abhinav et al., 2014d; Yeh et al., 2013b).

Tractography Atlases for Human and Animal Brains

Population averaged tractography atlas created using Human Connectome Project Data

We collaborate with Duke CIVM to build expert-vetted, tractography atlases of the brain connections using ultra-high-resolution diffusion MRI data.

This was achieved by tractography to generate trajectories of representative white matter fascicles. The trajectories were clustered and labeled by a team of experienced neuroanatomists.

This atlas of the structural connectome represents normative neuroanatomical organization of human brain white matter, complementary to traditional histologically-derived and voxel-based white matter atlases, allowing for better modeling and simulation of brain connectivity for future connectomic studies as well as clinical and educational applications.

Download:

http://brain.labsolver.org

Reference:

Yeh FC, Panesar S, Fernandes D, Meola A, Yoshino M, Fernandez-Miranda JC, Vettel JM, Verstynen T. Population-averaged atlas of the macroscale human structural connectome and its network topology. NeuroImage. 2018 Sep 1;178:57-68.

Decode Structure-Function Relations using Correlational Tractography

Correlational Tractography

Correlational tractography is a novel tractography modality invented in our lab. It is designed to explore a group of subjects and understand the correlation of brain connections with a study variable.

The technique adopts a “tracking-the-correlation” paradigm to map fiber pathways correlated with a study variable. The statistical significance of the findings can be further tested by connectometry, which leverages multiple regression, partial correlation, or non-parametric correlation to derive correlational tractography and study the circuit mechanism.

Correlational tractography has been used by ~200 publications to understand the structure-function relation in both healthy subjects and patients.

Shape Analysis of White Matter Pathways

Tool and documentation:

http://dsi-studio.labsolver.org/doc/gui_cx.html

Reference:

Yeh FC, Badre D, Verstynen T. Connectometry: a statistical approach harnessing the analytical potential of the local connectome. NeuroImage. 2016 Jan 15;125:162-71.
Hula WD, Panesar S, Gravier ML, Yeh FC, Dresang HC, Dickey MW, Fernandez-Miranda JC. Structural white matter connectometry of word production in aphasia: an observational study. Brain. 2020 Aug 1;143(8):2532-44.

Correlational tractography showing pathways positively (red) and negatively (light yellow) correlated with semantic processing in patients with aphasic stroke. (Hula et al. Brain 143.8 (2020): 2532-2544.)

Dignosis of Brain Disorders using Differential Tractography

(a) Conventional tractography map existence of all fiber pathways, whereas (b) differential tractography uses longitudinal scans to map pathways with neuronal change for disease diagnosis or monitoring.http://dsi-studio.labsolver.org/Manual/differential-tractographyReference:

Differential Tractography

Differential tractography is another novel tractography modality invented in our lab. It aims to explore individual brain connections to find neuronal change that leads to better clinical diagnosis or prognosis evaluation.

Differential tractography uses a “tracking-the-differences” paradigm to track pathways with neuronal change in a patient. It can be applied to either longitudinal studies or cross-sectional studies. The approach boosts the sensitivity and specificity of the imaging findings through the fiber tracking algorithms.

We are currently applying the techiqnue to ALS patients, with an aim to achieve accurate early diagnosis.

Tool and documentation:

http://dsi-studio.labsolver.org/doc/gui_t3_dt.html

Reference:

Yeh FC, Badre D, Verstynen T. Connectometry: a statistical approach harnessing the analytical potential of the local connectome. NeuroImage. 2016 Jan 15;125:162-71.2019 Nov 15;202:116131.

Fang-Cheng (Frank) Yeh

frank.yeh@pitt.edu

Department of Neurological Surgery

UPMC Presbyterian, Suite B-400

200 Lothrop Street

Pittsburgh, PA 15213

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