Elsevier

World Neurosurgery

Volume 81, Issue 1, January 2014, Pages 144-150
World Neurosurgery

Peer-Review Report
Magnetic Resonance Imaging Diffusion Tensor Tractography: Evaluation of Anatomic Accuracy of Different Fiber Tracking Software Packages

https://doi.org/10.1016/j.wneu.2013.01.004Get rights and content

Background

Diffusion tensor imaging (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. The aim of this study was to analyze the anatomic accuracy of visualized white matter fiber pathways using different, readily available DTI tractography software programs.

Methods

Magnetic resonance imaging scans of the head of 20 healthy volunteers were acquired using a Siemens Symphony TIM 1.5T scanner and a 12-channel head array coil. The standard settings of the scans in this study were 12 diffusion directions and 5-mm slices. The fornices were chosen as an anatomic structure for the comparative fiber tracking. Identical data sets were loaded into nine different fiber tracking packages that used different algorithms. The nine software packages and algorithms used were NeuroQLab (modified tensor deflection [TEND] algorithm), Sörensen DTI task card (modified streamline tracking technique algorithm), Siemens DTI module (modified fourth-order Runge-Kutta algorithm), six different software packages from Trackvis (interpolated streamline algorithm, modified FACT algorithm, second-order Runge-Kutta algorithm, Q-ball [FACT algorithm], tensorline algorithm, Q-ball [second-order Runge-Kutta algorithm]), DTI Query (modified streamline tracking technique algorithm), Medinria (modified TEND algorithm), Brainvoyager (modified TEND algorithm), DTI Studio modified FACT algorithm, and the BrainLab DTI module based on the modified Runge-Kutta algorithm. Three examiners (a neuroradiologist, a magnetic resonance imaging physicist, and a neurosurgeon) served as examiners. They were double-blinded with respect to the test subject and the fiber tracking software used in the presented images. Each examiner evaluated 301 images. The examiners were instructed to evaluate screenshots from the different programs based on two main criteria: (i) anatomic accuracy of the course of the displayed fibers and (ii) number of fibers displayed outside the anatomic boundaries.

Results

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 a SD of 0.6. The mean grade of the overall program ranking was 2.3 with a SD of 0.6. The overall mean grade of the program ranked number one (NeuroQLab) was 1.7 (range, 1.5–2.8). The mean overall grade of the program ranked last (BrainLab iPlan Cranial 2.6 DTI Module) was 3.3 (range, 1.7–4). The difference between the mean grades of these two programs was statistically highly significant (P < 0.0001). There was no statistically significant difference between the programs ranked 1–3: NeuroQLab, Sörensen DTI Task Card, and Siemens DTI module.

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 fibers in neurosurgery could lead to surgical decisions potentially harmful for the patient if used without intraoperative cortical stimulation. DTI fiber tracking presents a valuable noninvasive preoperative imaging tool, which requires further validation after important standardization of the acquisition and processing techniques currently available.

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

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    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.

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