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SU-F-R-32: Evaluation of MRI Acquisition Parameter Variations On Texture Feature Extraction Using ACR Phantom.

Publication ,  Journal Article
Xie, Y; Wang, J; Wang, C; Chang, Z
Published in: Med Phys
June 2016

PURPOSE: To investigate the sensitivity of classic texture features to variations of MRI acquisition parameters. METHODS: This study was performed on American College of Radiology (ACR) MRI Accreditation Program Phantom. MR imaging was acquired on a GE 750 3T scanner with XRM explain gradient, employing a T1-weighted images (TR/TE=500/20ms) with the following parameters as the reference standard: number of signal average (NEX) = 1, matrix size = 256×256, flip angle = 90°, slice thickness = 5mm. The effect of the acquisition parameters on texture features with and without non-uniformity correction were investigated respectively, while all the other parameters were kept as reference standard. Protocol parameters were set as follows: (a). NEX = 0.5, 2 and 4; (b).Phase encoding steps = 128, 160 and 192; (c). Matrix size = 128×128, 192×192 and 512×512. 32 classic texture features were generated using the classic gray level run length matrix (GLRLM) and gray level co-occurrence matrix (GLCOM) from each image data set. Normalized range ((maximum-minimum)/mean) was calculated to determine variation among the scans with different protocol parameters. RESULTS: For different NEX, 31 out of 32 texture features' range are within 10%. For different phase encoding steps, 31 out of 32 texture features' range are within 10%. For different acquisition matrix size without non-uniformity correction, 14 out of 32 texture features' range are within 10%; for different acquisition matrix size with non-uniformity correction, 16 out of 32 texture features' range are within 10%. CONCLUSION: Initial results indicated that those texture features that range within 10% are less sensitive to variations in T1-weighted MRI acquisition parameters. This might suggest that certain texture features might be more reliable to be used as potential biomarkers in MR quantitative image analysis.

Duke Scholars

Published In

Med Phys

DOI

EISSN

2473-4209

Publication Date

June 2016

Volume

43

Issue

6

Start / End Page

3380

Location

United States

Related Subject Headings

  • Nuclear Medicine & Medical Imaging
  • 1112 Oncology and Carcinogenesis
  • 0903 Biomedical Engineering
  • 0299 Other Physical Sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Xie, Y., Wang, J., Wang, C., & Chang, Z. (2016). SU-F-R-32: Evaluation of MRI Acquisition Parameter Variations On Texture Feature Extraction Using ACR Phantom. Med Phys, 43(6), 3380. https://doi.org/10.1118/1.4955804
Xie, Y., J. Wang, C. Wang, and Z. Chang. “SU-F-R-32: Evaluation of MRI Acquisition Parameter Variations On Texture Feature Extraction Using ACR Phantom.Med Phys 43, no. 6 (June 2016): 3380. https://doi.org/10.1118/1.4955804.
Xie, Y., et al. “SU-F-R-32: Evaluation of MRI Acquisition Parameter Variations On Texture Feature Extraction Using ACR Phantom.Med Phys, vol. 43, no. 6, June 2016, p. 3380. Pubmed, doi:10.1118/1.4955804.

Published In

Med Phys

DOI

EISSN

2473-4209

Publication Date

June 2016

Volume

43

Issue

6

Start / End Page

3380

Location

United States

Related Subject Headings

  • Nuclear Medicine & Medical Imaging
  • 1112 Oncology and Carcinogenesis
  • 0903 Biomedical Engineering
  • 0299 Other Physical Sciences