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Hyperpolarized 13C metabolic imaging detects long-lasting metabolic alterations following mild repetitive traumatic brain injury.
Chaumeil, Myriam; Guglielmetti, Caroline; Qiao, Kai; Tiret, Brice; Ozen, Mustafa; Krukowski, Karen; Nolan, Amber; Paladini, Maria Serena; Lopez, Carlos; Rosi, Susanna.
Afiliação
  • Chaumeil M; University of California, San Francisco.
  • Guglielmetti C; University of California, San Francisco.
  • Qiao K; University of California, San Francisco.
  • Tiret B; University of California, San Francisco.
  • Ozen M; Bay Area Institute of Science, Altos Labs.
  • Krukowski K; Bay Area Institute of Science, Altos Labs.
  • Nolan A; University of Washington.
  • Paladini MS; Bay Area Institute of Science, Altos Labs.
  • Lopez C; Bay Area Institute of Science, Altos Labs.
  • Rosi S; Bay Area Institute of Science, Altos Labs.
Res Sq ; 2023 Aug 14.
Article em En | MEDLINE | ID: mdl-37645937
ABSTRACT
Career athletes, active military, and head trauma victims are at increased risk for mild repetitive traumatic brain injury (rTBI), a condition that contributes to the development of epilepsy and neurodegenerative diseases. Standard clinical imaging fails to identify rTBI-induced lesions, and novel non-invasive methods are needed. Here, we evaluated if hyperpolarized 13C magnetic resonance spectroscopic imaging (HP 13C MRSI) could detect long-lasting changes in brain metabolism 3.5 months post-injury in a rTBI mouse model. Our results show that this metabolic imaging approach can detect changes in cortical metabolism at that timepoint, whereas multimodal MR imaging did not detect any structural or contrast alterations. Using Machine Learning, we further show that HP 13C MRSI parameters can help classify rTBI vs. Sham and predict long-term rTBI-induced behavioral outcomes. Altogether, our study demonstrates the potential of metabolic imaging to improve detection, classification and outcome prediction of previously undetected rTBI.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Res Sq Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Res Sq Ano de publicação: 2023 Tipo de documento: Article