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Segmentation of corpus callosum using diffusion tensor imaging: validation in patients with glioblastoma.

Nazem-Zadeh MR, Saksena S, Babajani-Fermi A, Jiang Q, Soltanian-Zadeh H, Rosenblum M, Mikkelsen T, Jain R - BMC Med Imaging (2012)

Bottom Line: In this algorithm, diffusion pattern of corpus callosum was used as prior information.Dice coefficients, estimated to compare automatic and manual segmentation results for Witelson subdivisions, ranged from 94% to 98% for control subjects and from 81% to 95% for tumor patients, illustrating closeness of automatic and manual segmentations.Studying the effect of corpus callosum rotation by different Euler angles showed that although segmentation results were more sensitive to azimuth and elevation than skew, rotations caused by brain tumors do not have major effects on the segmentation results.

View Article: PubMed Central - HTML - PubMed

Affiliation: Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, University of Tehran, Tehran 14399, Iran.

ABSTRACT

Background: This paper presents a three-dimensional (3D) method for segmenting corpus callosum in normal subjects and brain cancer patients with glioblastoma.

Methods: Nineteen patients with histologically confirmed treatment naïve glioblastoma and eleven normal control subjects underwent DTI on a 3T scanner. Based on the information inherent in diffusion tensors, a similarity measure was proposed and used in the proposed algorithm. In this algorithm, diffusion pattern of corpus callosum was used as prior information. Subsequently, corpus callosum was automatically divided into Witelson subdivisions. We simulated the potential rotation of corpus callosum under tumor pressure and studied the reproducibility of the proposed segmentation method in such cases.

Results: Dice coefficients, estimated to compare automatic and manual segmentation results for Witelson subdivisions, ranged from 94% to 98% for control subjects and from 81% to 95% for tumor patients, illustrating closeness of automatic and manual segmentations. Studying the effect of corpus callosum rotation by different Euler angles showed that although segmentation results were more sensitive to azimuth and elevation than skew, rotations caused by brain tumors do not have major effects on the segmentation results.

Conclusions: The proposed method and similarity measure segment corpus callosum by propagating a hyper-surface inside the structure (resulting in high sensitivity), without penetrating into neighboring fiber bundles (resulting in high specificity).

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Related in: MedlinePlus

Segmented corpus callosum by the proposed method for 11 control subjects. The colors show the Witelson subdivisions results for the corpus callosum. Rostrum: blue, Genu: green, Rostral Body: cyan, Anterior Mid-body: red, Posterior Mid-body: turquoise, Isthmus: yellow, Splenium: gray.
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Figure 5: Segmented corpus callosum by the proposed method for 11 control subjects. The colors show the Witelson subdivisions results for the corpus callosum. Rostrum: blue, Genu: green, Rostral Body: cyan, Anterior Mid-body: red, Posterior Mid-body: turquoise, Isthmus: yellow, Splenium: gray.

Mentions: Performance of the proposed method can be ascertained by visualizing the segmentation results (Figures 5, 6, 7). Figure 5 shows the segmentation results of the proposed method for 11 control subjects. Figure 6 shows the results for 12 Group 1 patients where the glioblastoma tumor does not infiltrate corpus callosum. These 12 patients were selected based on the severity of the effect of tumor on the rotation of corpus callosum. Note that although these cases include major geometric deviations from the normal state, the proposed method has successfully segmented corpus callosum and its subdivisions. Figure 7 shows the segmentation results for 7 Group 2 patients where the glioblastoma tumor has infiltrated corpus callosum. This figure illustrates that the proposed method has successfully segmented corpus callosum and its subdivisions in these extreme cases. Note that in all cases, the segmented corpus callosum does not penetrate into the adjacent fiber bundles such as cingulum, tapetum, minor and major forceps, superior longitudinal fasciculus, or tracts of corona radiata.


Segmentation of corpus callosum using diffusion tensor imaging: validation in patients with glioblastoma.

Nazem-Zadeh MR, Saksena S, Babajani-Fermi A, Jiang Q, Soltanian-Zadeh H, Rosenblum M, Mikkelsen T, Jain R - BMC Med Imaging (2012)

Segmented corpus callosum by the proposed method for 11 control subjects. The colors show the Witelson subdivisions results for the corpus callosum. Rostrum: blue, Genu: green, Rostral Body: cyan, Anterior Mid-body: red, Posterior Mid-body: turquoise, Isthmus: yellow, Splenium: gray.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3368740&req=5

Figure 5: Segmented corpus callosum by the proposed method for 11 control subjects. The colors show the Witelson subdivisions results for the corpus callosum. Rostrum: blue, Genu: green, Rostral Body: cyan, Anterior Mid-body: red, Posterior Mid-body: turquoise, Isthmus: yellow, Splenium: gray.
Mentions: Performance of the proposed method can be ascertained by visualizing the segmentation results (Figures 5, 6, 7). Figure 5 shows the segmentation results of the proposed method for 11 control subjects. Figure 6 shows the results for 12 Group 1 patients where the glioblastoma tumor does not infiltrate corpus callosum. These 12 patients were selected based on the severity of the effect of tumor on the rotation of corpus callosum. Note that although these cases include major geometric deviations from the normal state, the proposed method has successfully segmented corpus callosum and its subdivisions. Figure 7 shows the segmentation results for 7 Group 2 patients where the glioblastoma tumor has infiltrated corpus callosum. This figure illustrates that the proposed method has successfully segmented corpus callosum and its subdivisions in these extreme cases. Note that in all cases, the segmented corpus callosum does not penetrate into the adjacent fiber bundles such as cingulum, tapetum, minor and major forceps, superior longitudinal fasciculus, or tracts of corona radiata.

Bottom Line: In this algorithm, diffusion pattern of corpus callosum was used as prior information.Dice coefficients, estimated to compare automatic and manual segmentation results for Witelson subdivisions, ranged from 94% to 98% for control subjects and from 81% to 95% for tumor patients, illustrating closeness of automatic and manual segmentations.Studying the effect of corpus callosum rotation by different Euler angles showed that although segmentation results were more sensitive to azimuth and elevation than skew, rotations caused by brain tumors do not have major effects on the segmentation results.

View Article: PubMed Central - HTML - PubMed

Affiliation: Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, University of Tehran, Tehran 14399, Iran.

ABSTRACT

Background: This paper presents a three-dimensional (3D) method for segmenting corpus callosum in normal subjects and brain cancer patients with glioblastoma.

Methods: Nineteen patients with histologically confirmed treatment naïve glioblastoma and eleven normal control subjects underwent DTI on a 3T scanner. Based on the information inherent in diffusion tensors, a similarity measure was proposed and used in the proposed algorithm. In this algorithm, diffusion pattern of corpus callosum was used as prior information. Subsequently, corpus callosum was automatically divided into Witelson subdivisions. We simulated the potential rotation of corpus callosum under tumor pressure and studied the reproducibility of the proposed segmentation method in such cases.

Results: Dice coefficients, estimated to compare automatic and manual segmentation results for Witelson subdivisions, ranged from 94% to 98% for control subjects and from 81% to 95% for tumor patients, illustrating closeness of automatic and manual segmentations. Studying the effect of corpus callosum rotation by different Euler angles showed that although segmentation results were more sensitive to azimuth and elevation than skew, rotations caused by brain tumors do not have major effects on the segmentation results.

Conclusions: The proposed method and similarity measure segment corpus callosum by propagating a hyper-surface inside the structure (resulting in high sensitivity), without penetrating into neighboring fiber bundles (resulting in high specificity).

Show MeSH
Related in: MedlinePlus