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Utilizing the TractSeg Tool for Automatic Corticospinal Tract Segmentation in Patients With Brain Pathology.

Yael H Moshe1,2, Dafna Ben Bashat1,3, Zeev Hananis1,4

  • 1Sagol Brain Institute, 26738Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.

Technology in Cancer Research & Treatment
|November 2, 2022
PubMed
Summary

TractSeg enables automatic corticospinal tract segmentation in patients with brain pathology. This method shows superior consistency compared to manual segmentation, benefiting clinical and longitudinal studies.

Keywords:
DTIMRIconsistency measurementscorticospinal tractdeep learningsegmentation

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Area of Science:

  • Neuroimaging
  • Medical Image Analysis
  • Brain Anatomy

Background:

  • White-matter tract segmentation is crucial for surgical planning and tissue integrity assessment in patients with brain pathology.
  • TractSeg, an automated tool, has shown promise for tract segmentation in healthy subjects.

Purpose of the Study:

  • To evaluate TractSeg's efficacy for corticospinal tract (CST) segmentation in a large patient cohort with brain pathology.
  • To assess the consistency of TractSeg in repeated measurements.

Main Methods:

  • Utilized 649 diffusion-tensor-imaging scans from 625 patients and 12 healthy controls (scanned twice).
  • Performed manual CST labeling and compared it with automatic TractSeg segmentation.
  • Evaluated segmentation accuracy using Dice scores and assessed measurement consistency via volume, Fractional Anisotropy (FA), and Mean Diffusivity (MD) correlations.

Main Results:

  • Achieved Dice scores of 0.63 (training) and 0.64 (testing) for automatic CST segmentation.
  • Demonstrated higher measurement consistency for automatic segmentation compared to manual methods (e.g., volume correlation 0.92 vs. 0.65).

Conclusions:

  • TractSeg facilitates automatic CST segmentation in patients with brain pathology.
  • The superior consistency of TractSeg offers advantages for clinical applications and longitudinal studies in neuroimaging.