Abstract
The purpose of this study was to evaluate an improved and reliable visualization method for pediatric spinal cord MR images in healthy subjects and patients with spinal cord injury (SCI). A total of 15 pediatric volunteers (10 healthy subjects and 5 subjects with cervical SCI) with a mean age of 11.41 years (range 8–16 years) were recruited and scanned using a 3.0T Siemens Verio MR scanner. T2-weighted axial images were acquired covering entire cervical spinal cord level C1 to C7. These gray-scale images were then converted to color images by using five different techniques including hue-saturation-value (HSV), rainbow, red-green-blue (RGB), and two enhanced RGB techniques using automated contrast stretching and intensity inhomogeneity correction. Performance of these techniques was scored visually by two neuroradiologists within three selected cervical spinal cord intervertebral disk levels (C2-C3, C4-C5, and C6-C7) and quantified using signal to noise ratio (SNR) and contrast to noise ratio (CNR). Qualitative and quantitative evaluation of the color images shows consistent improvement across all the healthy and SCI subjects over conventional gray-scale T2-weighted gradient echo (GRE) images. Inter-observer reliability test showed moderate to strong intra-class correlation (ICC) coefficients in the proposed techniques (ICC > 0.73). The results suggest that the color images could be used for quantification and enhanced visualization of the spinal cord structures in addition to the conventional gray-scale images. This would immensely help towards improved delineation of the gray/white and CSF structures and further aid towards accurate manual or automatic drawings of region of interests (ROIs).
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This work was supported by National Institute of Neurological Disorders of the National Institutes of Health under award number R01NS079635.
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Alizadeh, M., Shah, P., Conklin, C.J. et al. Application of Color Transformation Techniques in Pediatric Spinal Cord MR Images: Typically Developing and Spinal Cord Injury Population. J Digit Imaging 31, 543–552 (2018). https://doi.org/10.1007/s10278-017-0048-5
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DOI: https://doi.org/10.1007/s10278-017-0048-5