Impact of region-of-interest method on quantitative analysis of DTI data in the optic tracts. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Lilja, Ylva; Gustafsson, Oscar; Ljungberg, Maria; Nilsson, Daniel; Starck, Göran
• Is Part Of: BMC medical imaging. Volume 16:Issue 1(2016)
• Page Start: 1
• Page End: 10
• Publication Date: 2016-12
• Subjects: Diagnostic imaging -- Periodicals; 616.075405
• DOI: 10.1186/s12880-016-0145-9
• Languages: English
• ISSNs: 1471-2342

Abstract

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.