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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.


Correction for position by redefining the first position in each ROI as the most anterior coronal slice included in both ROIs. Inter-rater (blue) and intra-rater variability (red) for all methods and position. The repeatability coefficient (intra-rater) was expressed as an interval with the same midpoint as the corresponding limit of agreement (inter-rater) for easier comparisons
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Fig6: Correction for position by redefining the first position in each ROI as the most anterior coronal slice included in both ROIs. Inter-rater (blue) and intra-rater variability (red) for all methods and position. The repeatability coefficient (intra-rater) was expressed as an interval with the same midpoint as the corresponding limit of agreement (inter-rater) for easier comparisons

Mentions: Almost all the variability between measurements within and between raters was explained by different starting points, which can be seen in Fig. 6, where varying starting point was corrected for. This effect was especially pronounced for the manual b0 and the FA-skeleton methods. For the manual T1W method, varying start points explained less of the variability. For the tractography method the repeatability coefficient was reduced to almost zero when a start point correction was applied, whereas the limits of agreement (inter-rater variability) remained almost unchanged.Fig. 6


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)

Correction for position by redefining the first position in each ROI as the most anterior coronal slice included in both ROIs. Inter-rater (blue) and intra-rater variability (red) for all methods and position. The repeatability coefficient (intra-rater) was expressed as an interval with the same midpoint as the corresponding limit of agreement (inter-rater) for easier comparisons
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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

Fig6: Correction for position by redefining the first position in each ROI as the most anterior coronal slice included in both ROIs. Inter-rater (blue) and intra-rater variability (red) for all methods and position. The repeatability coefficient (intra-rater) was expressed as an interval with the same midpoint as the corresponding limit of agreement (inter-rater) for easier comparisons
Mentions: Almost all the variability between measurements within and between raters was explained by different starting points, which can be seen in Fig. 6, where varying starting point was corrected for. This effect was especially pronounced for the manual b0 and the FA-skeleton methods. For the manual T1W method, varying start points explained less of the variability. For the tractography method the repeatability coefficient was reduced to almost zero when a start point correction was applied, whereas the limits of agreement (inter-rater variability) remained almost unchanged.Fig. 6

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.