Limits...
Impact of region-of-interest method on quantitative analysis of DTI data in the optic tracts.

Lilja Y, Gustafsson O, Ljungberg M, Nilsson D, Starck G - BMC Med Imaging (2016)

Bottom Line: ROI selection in small structures is challenging; the final measurement results could be affected due to the significant impact of small geometrical errors.Manual tracing was performed in 1) the b0 image and 2) a T1-weighted image registered to the FA image.Semi-automatic segmentation was performed based on 3) tractography and 4) the FA-skeleton algorithm in the tract-based spatial statistics (TBSS) framework.

View Article: PubMed Central - PubMed

Affiliation: Department of Clinical Neuroscience and Rehabilitation, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. ylva.lilja@neuro.gu.se.

ABSTRACT

Background: To extract DTI parameters from a specific structure, a region of interest (ROI) must be defined. ROI selection in small structures is challenging; the final measurement results could be affected due to the significant impact of small geometrical errors. In this study the optic tracts were analyzed with the aim to assess differences in DTI parameters due to ROI method and to identify the most reliable method.

Methods: Images of 20 healthy subjects were acquired. Fractional anisotropy (FA) was extracted from the optic tracts by four different ROI methods. Manual tracing was performed in 1) the b0 image and 2) a T1-weighted image registered to the FA image. Semi-automatic segmentation was performed based on 3) tractography and 4) the FA-skeleton algorithm in the tract-based spatial statistics (TBSS) framework. Results were analyzed with regard to ROI method as well as to inter-scan, intra-rater and inter-rater reliability.

Results: The resulting FA values divided the ROI methods into two groups that differed significantly: 1) the FA-skeleton and the b0 methods showed higher FA values compared to 2) the tractography and the T1-weighted methods. The intra- and inter-rater variabilities were similar for all methods, except for the tractography method where the inter-rater variability was higher. The FA-skeleton method had a better reproducibility than the other methods.

Conclusion: Choice of ROI method was found to be highly influential on FA values when the optic tracts were analyzed. The FA-skeleton method performed the best, yielding low variability and high repeatability.

No MeSH data available.


Schematic illustration of an ROI (blue squares) of the left optic tract. All ROIs aimed to start at the posterior part of the optic chiasm and to include the central portion of the optic tract. The most anterior 15 mm of all optic tracts could be clearly identified in all subjects, thus the length of an ROI was set to cover a 15 mm anterior-to-posterior distance
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
getmorefigures.php?uid=PMC4940685&req=5

Fig2: Schematic illustration of an ROI (blue squares) of the left optic tract. All ROIs aimed to start at the posterior part of the optic chiasm and to include the central portion of the optic tract. The most anterior 15 mm of all optic tracts could be clearly identified in all subjects, thus the length of an ROI was set to cover a 15 mm anterior-to-posterior distance

Mentions: All four ROI methods were designed to define voxels corresponding to the central portions of the OTs and to avoid inclusion of border zone voxels that could be influenced by partial volume effect. Thus, a maximum of two voxels were selected per coronal slice (i.e., cross section of the OT) for each ROI. The anterior limit of all ROIs was defined as the most posterior part of the optic chiasm, which was identified by visual inspection of coronal slices of color-coded FA maps. Within individual, the same coronal slice was used as the anterior limit for all four ROI methods. For the two manual methods, voxel selection proceeded posteriorly, slice by slice, continuously, until visual inspection no longer could separate the OTs from other structures reliably. Figure 2 illustrates a typical ideal ROI.Fig. 2


Impact of region-of-interest method on quantitative analysis of DTI data in the optic tracts.

Lilja Y, Gustafsson O, Ljungberg M, Nilsson D, Starck G - BMC Med Imaging (2016)

Schematic illustration of an ROI (blue squares) of the left optic tract. All ROIs aimed to start at the posterior part of the optic chiasm and to include the central portion of the optic tract. The most anterior 15 mm of all optic tracts could be clearly identified in all subjects, thus the length of an ROI was set to cover a 15 mm anterior-to-posterior distance
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4940685&req=5

Fig2: Schematic illustration of an ROI (blue squares) of the left optic tract. All ROIs aimed to start at the posterior part of the optic chiasm and to include the central portion of the optic tract. The most anterior 15 mm of all optic tracts could be clearly identified in all subjects, thus the length of an ROI was set to cover a 15 mm anterior-to-posterior distance
Mentions: All four ROI methods were designed to define voxels corresponding to the central portions of the OTs and to avoid inclusion of border zone voxels that could be influenced by partial volume effect. Thus, a maximum of two voxels were selected per coronal slice (i.e., cross section of the OT) for each ROI. The anterior limit of all ROIs was defined as the most posterior part of the optic chiasm, which was identified by visual inspection of coronal slices of color-coded FA maps. Within individual, the same coronal slice was used as the anterior limit for all four ROI methods. For the two manual methods, voxel selection proceeded posteriorly, slice by slice, continuously, until visual inspection no longer could separate the OTs from other structures reliably. Figure 2 illustrates a typical ideal ROI.Fig. 2

Bottom Line: ROI selection in small structures is challenging; the final measurement results could be affected due to the significant impact of small geometrical errors.Manual tracing was performed in 1) the b0 image and 2) a T1-weighted image registered to the FA image.Semi-automatic segmentation was performed based on 3) tractography and 4) the FA-skeleton algorithm in the tract-based spatial statistics (TBSS) framework.

View Article: PubMed Central - PubMed

Affiliation: Department of Clinical Neuroscience and Rehabilitation, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. ylva.lilja@neuro.gu.se.

ABSTRACT

Background: To extract DTI parameters from a specific structure, a region of interest (ROI) must be defined. ROI selection in small structures is challenging; the final measurement results could be affected due to the significant impact of small geometrical errors. In this study the optic tracts were analyzed with the aim to assess differences in DTI parameters due to ROI method and to identify the most reliable method.

Methods: Images of 20 healthy subjects were acquired. Fractional anisotropy (FA) was extracted from the optic tracts by four different ROI methods. Manual tracing was performed in 1) the b0 image and 2) a T1-weighted image registered to the FA image. Semi-automatic segmentation was performed based on 3) tractography and 4) the FA-skeleton algorithm in the tract-based spatial statistics (TBSS) framework. Results were analyzed with regard to ROI method as well as to inter-scan, intra-rater and inter-rater reliability.

Results: The resulting FA values divided the ROI methods into two groups that differed significantly: 1) the FA-skeleton and the b0 methods showed higher FA values compared to 2) the tractography and the T1-weighted methods. The intra- and inter-rater variabilities were similar for all methods, except for the tractography method where the inter-rater variability was higher. The FA-skeleton method had a better reproducibility than the other methods.

Conclusion: Choice of ROI method was found to be highly influential on FA values when the optic tracts were analyzed. The FA-skeleton method performed the best, yielding low variability and high repeatability.

No MeSH data available.