Available online 4 January 2013
Publication year: 2013
Source:World Neurosurgery
Objective DTI based tractography has become an integral part of pre-operative diagnostic imaging in many neurosurgical centers and also other non surgical specialties depend increasingly on DTI tractography as a diagnostic tool. It was the aim of this study to analyze the anatomical accuracy of visualized white matter fiber pathways using different, readily available DTI tractography software programs. Methods MRI scans of the head of twenty healthy volunteers were acquired using a Siemens Symphony TIM, 1.5 T scanner and a 12 channel head array coil. 12 diffusion directions and 5mm slices were selected for the standard settings of the scans in this study. The fornices were chosen as an anatomical structure for the comparative fiber tracking. Identical data sets were loaded into nine different fiber tracking packages which used different algorithms. The nine software packages and algorithms used were: NeuroQLab (modified TEND algorithm), Sörensen DTI task card (modified STT algorithm), Siemens DTI module (modified 4th order Runge-Kutta algorithm), six different software packages from Trackvis (interpolated streamline algorithm, interpolated streamline algorithm, 2nd order Runge Kutta algorithm, Q-ball -> FACT algorithm, tensorline algorithm, Q-ball -> 2nd order Runge Kutta algorithm), DTI Query (modified STT 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 MRI 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. A total of 301 images were evaluated from each examiner. They were instructed to evaluate screenshots from the different programs based on 2 main criteria: 1. anatomical accuracy of the course of the displayed fibers and 2. the number of fibers displayed outside the anatomical boundaries. Results The mean overall grade for anatomical 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. Conclusion The results of this study show that there is a statistically significant difference in the anatomical accuracy of the tested DTI fiber tracking programs. While incorrectly displayed fibers could lead to wrong conclusions in the field of neurosciences which relies heavily on this non invasive imaging technique, in neurosurgery incorrectly displayed fibers could lead to surgical decisions potentially harmful for the patient if used without intra-operative cortical stimulation. DTI fiber tracking presents a valuable non-invasive preoperative imaging tool which requires further validation after important standardization of the acquisition and processing techniques currently available.
Publication year: 2013
Source:World Neurosurgery
Objective DTI based tractography has become an integral part of pre-operative diagnostic imaging in many neurosurgical centers and also other non surgical specialties depend increasingly on DTI tractography as a diagnostic tool. It was the aim of this study to analyze the anatomical accuracy of visualized white matter fiber pathways using different, readily available DTI tractography software programs. Methods MRI scans of the head of twenty healthy volunteers were acquired using a Siemens Symphony TIM, 1.5 T scanner and a 12 channel head array coil. 12 diffusion directions and 5mm slices were selected for the standard settings of the scans in this study. The fornices were chosen as an anatomical structure for the comparative fiber tracking. Identical data sets were loaded into nine different fiber tracking packages which used different algorithms. The nine software packages and algorithms used were: NeuroQLab (modified TEND algorithm), Sörensen DTI task card (modified STT algorithm), Siemens DTI module (modified 4th order Runge-Kutta algorithm), six different software packages from Trackvis (interpolated streamline algorithm, interpolated streamline algorithm, 2nd order Runge Kutta algorithm, Q-ball -> FACT algorithm, tensorline algorithm, Q-ball -> 2nd order Runge Kutta algorithm), DTI Query (modified STT 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 MRI 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. A total of 301 images were evaluated from each examiner. They were instructed to evaluate screenshots from the different programs based on 2 main criteria: 1. anatomical accuracy of the course of the displayed fibers and 2. the number of fibers displayed outside the anatomical boundaries. Results The mean overall grade for anatomical 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. Conclusion The results of this study show that there is a statistically significant difference in the anatomical accuracy of the tested DTI fiber tracking programs. While incorrectly displayed fibers could lead to wrong conclusions in the field of neurosciences which relies heavily on this non invasive imaging technique, in neurosurgery incorrectly displayed fibers could lead to surgical decisions potentially harmful for the patient if used without intra-operative cortical stimulation. DTI fiber tracking presents a valuable non-invasive preoperative imaging tool which requires further validation after important standardization of the acquisition and processing techniques currently available.
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