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Diffusion Tensor Imaging of Rat Rotator Cuff Muscle with Histopathological Correlation: An Exploratory Study.
Lo, James; Berry, David B; Tang, Qingbo; Cheng, Xin; Toto-Brocchi, Marco; Du, Jiang; Ward, Samuel R; Ma, Yajun; Chang, Eric Y.
Affiliation
  • Lo J; University of California, San Diego.
  • Berry DB; University of California, San Diego.
  • Tang Q; University of California, San Diego.
  • Cheng X; University of California, San Diego.
  • Toto-Brocchi M; University of California, San Diego.
  • Du J; University of California, San Diego.
  • Ward SR; University of California, San Diego.
  • Ma Y; University of California, San Diego.
  • Chang EY; VA San Diego Healthcare System.
Res Sq ; 2024 Sep 03.
Article in En | MEDLINE | ID: mdl-39281861
ABSTRACT
Diffusion tensor imaging (DTI) is a magnetic resonance imaging (MRI) technique that can be used to assess microstructural features of skeletal muscle that are related to tissue function. Although widely used, direct correlations between DTI derived metrics such as fractional anisotropy and spatially matched tissue microstructure assessed with histology have not been performed. This study investigated the relationship between scalar-based DTI measurements and histologically derived muscle microstructural measurements in rat rotator cuff muscles. Despite meticulous co-localization of MRI and histology data, negligible correlations were found between DTI metrics and histological measurements including muscle fiber diameter, cross-sectional area, and surface-to-volume ratio. These findings highlight the challenges in validating DTI with histology due to requirements in anatomical co-localization, necessity of high-quality histology, and consideration of diffusion measurement scales. Our findings underscore the need for further research with optimized imaging parameters to enhance our knowledge regarding the sensitivity of DTI to important features of muscle microstructure.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Res Sq Year: 2024 Document type: Article Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Res Sq Year: 2024 Document type: Article Country of publication: