Peer-Review ReportMagnetic Resonance Imaging Diffusion Tensor Tractography: Evaluation of Anatomic Accuracy of Different Fiber Tracking Software Packages
Introduction
Microsurgical resections of tumors in or near functional areas, including white matter fiber tracts of the brain, represent a great challenge to neurosurgeons. To know what to expect intraoperatively, it is essential for neurosurgeons to have reliable diagnostic imaging available. Visualizing how anatomic structures and functional areas have been displaced by a lesion is essential for planning a surgical approach. A noninvasive imaging technique has been developed in the past 15 years capable of visualizing white matter fiber tracts. This method is diffusion tensor imaging (DTI)–based tractography, which has been used for clinical applications since about 1994 (2) mainly to avoid neurologic deficits by damaging fibers during the surgical approach. Because DTI tractography is the only noninvasive method available to visualize pathways of white matter fiber tracts, an increasing number of centers have implemented this method in routine imaging of tumor patients. A few studies have been published on implementing DTI tractography for preoperative planning and intraoperative localization of major fiber pathways of the brain 17, 18, 19. However, when using DTI tractography, virtual three-dimensional projections of fiber pathways are superimposed on an anatomic image, which in some cases might be misleading. DTI tractography is based on measuring the diffusion of water molecules rather than visualizing the actual anatomic structures of axons. Considering the resolution of diffusion-weighted images, it becomes obvious that this is an attempt to visualize a microscopic entity using a macroscopic resolution. Even though it is generally known that the visualized fiber tracts are based on statistical calculations and probability calculations rather than anatomic facts, the temptation to view DTI tractography images as anatomic facts remains great. Nevertheless, it has been shown that major fiber tracts of the brain can be visualized using DTI tractography 3, 4, 8, 14. Based on this anatomic knowledge, the neurosurgeon has to decide whether or not to rely on the DTI tractography images. Reconstructed fiber tracts can differ depending on the software package, algorithms, and parameter settings being used. Very few data are available on the reliability, reproducibility, and anatomic accuracy of different fiber tracking software packages.
The hypothesis behind this study was that different software packages could potentially show different fibers because various settings are used during data acquisition, and several algorithms are used to perform the fiber tracking. The aim of this study was to compare the results by analyzing the anatomic accuracy of visualized white matter fiber pathways using identical parameter settings in different, readily available DTI tractography software packages.
Section snippets
Test Subjects and Scanning Protocol
Approval from the institutional ethics committee was obtained, and each subject gave his or her written consent agreeing to participate in the study. Magnetic resonance imaging (MRI) scans of the head of 20 healthy volunteers (11 men and 9 women; mean age, 34 years; range, 19–56 years) were acquired using a Siemens Symphony TIM 1.5T scanner (Siemens, Erlangen, Germany) and a 12-channel head array coil. None of the volunteers had a neurologic disease, psychiatric disease, or brain injury in his
Results
The t test showed a homogeneous distribution of all grades (n = 903) given in the two categories by the three examiners. Analyses of the mean grades stratified according to the three examiners showed no statistically significant variation (Table 3).
The mean overall grade for anatomic accuracy was 2.2 (range, 1.1–3.6) with a standard deviation (SD) of 0.9. The mean overall grade for incorrectly displayed fibers was 2.5 (range, 1.6–3.5) with SD of 0.6. The mean grade of the overall program
Discussion
DTI-based tractography has become an integral part of preoperative diagnostic imaging in many neurosurgical centers, and other nonsurgical specialties depend increasingly on DTI tractography as a diagnostic tool. For example, DTI-based tractography has been used in the treatment of epilepsy to differentiate between epileptogenic focal points (6), and some centers use this method as a diagnostic tool in the diagnosis of multiple sclerosis (29) and amyotrophic lateral sclerosis (25).
Since the
Conclusions
The results of this study show that there is a statistically significant difference in the anatomic accuracy of the tested DTI fiber tracking programs. Although incorrectly displayed fibers could lead to wrong conclusions in the neurosciences field, which relies heavily on this noninvasive imaging technique, incorrectly displayed or missing fibers in neurosurgery could lead to surgical decisions potentially harmful for the patient if used without intraoperative brain mapping. DTI fiber tracking
References (31)
- et al.
MR diffusion tensor spectroscopy and imaging
Biophys J
(1994) - et al.
Evaluation of the GTRACT diffusion tensor tractography algorithm: a validation and reliability study
NeuroImage
(2006) - et al.
Fiber tracking from DTI using linear state space models: detectability of the pyramidal tract
NeuroImage
(2002) - et al.
An investigation of functional and anatomical connectivity using magnetic resonance imaging
NeuroImage
(2002) Fiber tracking—a reliable tool for neurosurgery?
World Neurosurg
(2010)- et al.
Minimal gradient encoding for robust estimation of diffusion anisotropy
Magn Reson Imaging
(2000) - et al.
Regularization of diffusion-based direction maps for the tracking of brain white matter fascicles
NeuroImage
(2000) - et al.
Fiber tracking on hardi data using robust ODF fields
ICIP'07
(2007) - et al.
In vivo fiber tractography using DT-MRI data
Magn Reson Med
(2000) - et al.
Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging
Nat Neurosci
(2003)
Brain mapping techniques to maximize resection, safety, and seizure control in children with brain tumors
Neurosurgery
Diffusion tensor tractography detection of functional pathway for the spread of epileptiform activity between temporal lobe and Rolandic region
Childs Nerv Syst
Tracking neuronal fiber pathways in the living human brain
Proc Natl Acad Sci U S A
Visualizing second-order tensor fields with hyper streamlines
IEEE Computer Graphics and Applications
Delayed onset of the supplementary motor area syndrome after surgical resection of the mesial frontal lobe: a time course study using intraoperative mapping in an awake patient
Stereotact Funct Neurosurg
Cited by (86)
Clinical applications of magnetic resonance imaging based functional and structural connectivity
2021, NeuroImageCitation Excerpt :Duffau, 2014, Duffau, 2014) Notably, different software packages with different reconstruction algorithms, each with potential for different parameter selection, directly affect tract estimations. ( Ashmore et al., 2020, Feigl et al., 2014, Pujol et al., 2015) It is therefore particularly concerning that although tractography is frequently used for clinical purposes, many clinicians do not fully understand the methods or parameters used to derive such reconstructions. ( Toescu et al., 2020)
New Navigation Approaches for Endoscopic Lateral Skull Base Surgery
2021, Otolaryngologic Clinics of North AmericaThe Value of White Matter Tractography by Diffusion Tensor Imaging in Altering a Neurosurgeon's Operative Plan
2019, World NeurosurgeryCitation Excerpt :A combination of methods, such as DTI WM tractography and intraoperative subcortical mapping, allows for the accurate identification of eloquent fiber tracts and enhances surgical performance and safety.16 Although DTI WM tractography presents a valuable noninvasive preoperative tool for planning, it requires further validation after important standardization of the acquisition and processing techniques that are available.29 In this article, the small patient population as well as the retrospective design of the study remain limiting factors.
Conflict of interest statement: The authors declare that the article content was composed in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.