Accurate Segmentation of Tumorous Regions in High-Grade Glioma Employing a Multi-parametric (ADC/PWI/T2-W) Image Fusion Approach
Purpose: Glioblastoma Multiforme (GBM) brain tumor is heterogeneous in nature; so, its quantification depends on how to accurately segment different parts of the tumor, i.e. active tumor, edema and necrosis. This procedure becomes more effective when physiological information like diffusion-weighted...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Tehran University of Medical Sciences
2014-03-01
|
| Series: | Frontiers in Biomedical Technologies |
| Subjects: | |
| Online Access: | https://fbt.tums.ac.ir/index.php/fbt/article/view/16 |
| _version_ | 1818832227547480064 |
|---|---|
| author | Anahita Fathi-Kazerooni Meysam Mohseni Hamidreza Saligheh-Rad |
| author_facet | Anahita Fathi-Kazerooni Meysam Mohseni Hamidreza Saligheh-Rad |
| author_sort | Anahita Fathi-Kazerooni |
| collection | DOAJ |
| description | Purpose: Glioblastoma Multiforme (GBM) brain tumor is heterogeneous in nature; so, its quantification depends on how to accurately segment different parts of the tumor, i.e. active tumor, edema and necrosis. This procedure becomes more effective when physiological information like diffusion-weighted-imaging (DWI) and perfusion-weighted-imaging (PWI) are incorporated with the anatomical MRI. In this preliminary tumor quantification work, the idea is to characterize different regions of the GBM tumors in an MRI-based multi-parametric approach to achieve more accurate characterization of pathological regions, which cannot be obtained by using individual modalities.
Methods: For this purpose, three MR sequences, namely T2-weighted imaging (anatomical MR imaging), PWI and DWI of five GBM patients were acquired. To enhance the delineation of the boundaries of each pathological region (peri-tumoral edema, tumor and necrosis), the spatial fuzzy C-means (FCM) algorithm is combined with the region growing (RG) method.
Results: The results show that exploiting the multi-parametric approach along with the proposed segmentation method can improve characterization of tumor cells, edema and necrosis in comparison to mono-parametric imaging approach.
Conclusion: The proposed MRI-based multi-parametric segmentation approach has the potential to accurately segment tumorous regions, leading to an efficient design of the treatment planning, e.g. in radiotherapy. |
| first_indexed | 2024-12-19T01:59:41Z |
| format | Article |
| id | doaj.art-3ddf80ac44d54a62b60f4eda52f2d226 |
| institution | Directory Open Access Journal |
| issn | 2345-5837 |
| language | English |
| last_indexed | 2024-12-19T01:59:41Z |
| publishDate | 2014-03-01 |
| publisher | Tehran University of Medical Sciences |
| record_format | Article |
| series | Frontiers in Biomedical Technologies |
| spelling | doaj.art-3ddf80ac44d54a62b60f4eda52f2d2262022-12-21T20:41:05ZengTehran University of Medical SciencesFrontiers in Biomedical Technologies2345-58372014-03-0111Accurate Segmentation of Tumorous Regions in High-Grade Glioma Employing a Multi-parametric (ADC/PWI/T2-W) Image Fusion ApproachAnahita Fathi-Kazerooni0Meysam Mohseni1Hamidreza Saligheh-Rad2Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Iran AND Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Institute for Advanced Medical Technologies, Iran.Neurosurgery Ward, Imam Khomeini Hospital, Tehran University of Medical Sciences, Iran.Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Iran AND Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Institute for Advanced Medical Technologies, Iran.Purpose: Glioblastoma Multiforme (GBM) brain tumor is heterogeneous in nature; so, its quantification depends on how to accurately segment different parts of the tumor, i.e. active tumor, edema and necrosis. This procedure becomes more effective when physiological information like diffusion-weighted-imaging (DWI) and perfusion-weighted-imaging (PWI) are incorporated with the anatomical MRI. In this preliminary tumor quantification work, the idea is to characterize different regions of the GBM tumors in an MRI-based multi-parametric approach to achieve more accurate characterization of pathological regions, which cannot be obtained by using individual modalities. Methods: For this purpose, three MR sequences, namely T2-weighted imaging (anatomical MR imaging), PWI and DWI of five GBM patients were acquired. To enhance the delineation of the boundaries of each pathological region (peri-tumoral edema, tumor and necrosis), the spatial fuzzy C-means (FCM) algorithm is combined with the region growing (RG) method. Results: The results show that exploiting the multi-parametric approach along with the proposed segmentation method can improve characterization of tumor cells, edema and necrosis in comparison to mono-parametric imaging approach. Conclusion: The proposed MRI-based multi-parametric segmentation approach has the potential to accurately segment tumorous regions, leading to an efficient design of the treatment planning, e.g. in radiotherapy.https://fbt.tums.ac.ir/index.php/fbt/article/view/16Multi-parametric MRISegmentationGlioblastoma multiforme. |
| spellingShingle | Anahita Fathi-Kazerooni Meysam Mohseni Hamidreza Saligheh-Rad Accurate Segmentation of Tumorous Regions in High-Grade Glioma Employing a Multi-parametric (ADC/PWI/T2-W) Image Fusion Approach Frontiers in Biomedical Technologies Multi-parametric MRI Segmentation Glioblastoma multiforme. |
| title | Accurate Segmentation of Tumorous Regions in High-Grade Glioma Employing a Multi-parametric (ADC/PWI/T2-W) Image Fusion Approach |
| title_full | Accurate Segmentation of Tumorous Regions in High-Grade Glioma Employing a Multi-parametric (ADC/PWI/T2-W) Image Fusion Approach |
| title_fullStr | Accurate Segmentation of Tumorous Regions in High-Grade Glioma Employing a Multi-parametric (ADC/PWI/T2-W) Image Fusion Approach |
| title_full_unstemmed | Accurate Segmentation of Tumorous Regions in High-Grade Glioma Employing a Multi-parametric (ADC/PWI/T2-W) Image Fusion Approach |
| title_short | Accurate Segmentation of Tumorous Regions in High-Grade Glioma Employing a Multi-parametric (ADC/PWI/T2-W) Image Fusion Approach |
| title_sort | accurate segmentation of tumorous regions in high grade glioma employing a multi parametric adc pwi t2 w image fusion approach |
| topic | Multi-parametric MRI Segmentation Glioblastoma multiforme. |
| url | https://fbt.tums.ac.ir/index.php/fbt/article/view/16 |
| work_keys_str_mv | AT anahitafathikazerooni accuratesegmentationoftumorousregionsinhighgradegliomaemployingamultiparametricadcpwit2wimagefusionapproach AT meysammohseni accuratesegmentationoftumorousregionsinhighgradegliomaemployingamultiparametricadcpwit2wimagefusionapproach AT hamidrezasalighehrad accuratesegmentationoftumorousregionsinhighgradegliomaemployingamultiparametricadcpwit2wimagefusionapproach |