Neuroscience

Hyperpolarized ¹³C metabolic imaging detects long-lasting metabolic alterations following mild repetitive traumatic brain injury

Caroline Guglielmetti
Kai Qiao
Brice Tiret
Mustafa Ozen
Karen Krukowski
Amber Nolan
Maria Serena Paladini
Carlos F Lopez
Myriam M Chaumeil author has email address
Susanna Rosi author has email address

Department of Physical Therapy and Rehabilitation Science, University of California, San Francisco, San Francisco, United States
Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, United States
Bay Area Institute of Science, Altos Labs, Redwood City, United States
Brain and Spinal Injury Center, University of California, San Francisco, San Francisco, United States
Knoebel Institute for Healthy Aging, University of Denver, Denver, United States
Department of Laboratory Medicine and Pathology, University of Washington, Seattle, United States
Weill institute for Neuroscience, University of California, San Francisco, San Francisco, United States
Department of Neurological Surgery, University of California, San Francisco, San Francisco, United States

https://doi.org/10.7554/eLife.106736.1

Open access
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Figures and data

Study outline.
Experimental timeline of the study. Two-month old male mice received a rTBI using the CHIMERA device or underwent a Sham procedure (no impact). Risk-taking behavior was evaluated at 3 months post-injury using the Elevated Plus Maze. MR imaging was performed 3.5 months after Sham or rTBI, and included HP ¹³C MRSI, T₂-weighted MRI, T₁ mapping MRI, and SWI MRI. Tissue was collected 4 months after Sham or rTBI procedures to evaluate PDH and LDH activities, and expression of MCT1 and MCT4. ML analyses methods were used to identify the best classifiers between rTBI and Sham, and the best predictors of the risk-taking behavior and HP ¹³C Lac/Pyr in the cortex.

HP ¹³C spectra following co-injection of HP [1-¹³C]pyruvate and [¹³C]urea.
Representative T₂-weighted MR image overlaid with the grid used for HP ¹³C MRSI acquisitions. Representative ¹³C spectra showing HP [1-¹³C]pyruvate, HP [¹³C]urea and HP [1-¹³C]lactate in the (a) cortex (red voxel) and (b) subcortex (red voxel) for a Sham and a rTBI mouse.

HP ¹³C MRSI detects long-lasting metabolic alterations following rTBI.
Quantitative analyses of (a) HP [1-¹³C]lactate levels, (b) HP [1-¹³C]pyruvate levels, (c) HP ¹³C Lac/Pyr, and (d) HP [¹³C]urea for the cortex (highlighted red voxels), revealed lower HP [1-¹³C]lactate levels (p = 0.0073), higher HP [1-¹³C]pyruvate levels (p = 0.0073), and lower HP ¹³C Lac/Pyr (p = 0.0071) in rTBI compared to Sham mice. In contrast, quantitative analyses of (e) HP [1-¹³C]lactate levels, (f) HP [1-¹³C]pyruvate levels, (g) HP ¹³C Lac/Pyr, and (h) HP [¹³C]urea for the subcortex (highlighted red voxels), did not detect differences between rTBI and Sham mice. (i) Representative HP ¹³C heatmaps for a Sham and a rTBI mouse, highlighting lower HP [1-¹³C]lactate, higher HP [1-¹³C]pyruvate and lower HP ¹³C Lac/Pyr in cortical areas in rTBI mice. N= 9 rTBI and 10 Sham mice. Unpaired t-test **p ≤ 0.01);data are expressed as means ± SD.

Multimodal MRI does not detect long-lasting effect of injury in rTBI.
(a) Representative T₂-weighted MRI data and corresponding manual brain masking. (b) Quantitative analyses of T₂-weighted signal intensity revealed no significant differences for brain subregions between Sham and rTBI. (c) Representative T₁ map and corresponding manual brain masking. (d) Quantitative analyses of T₁ maps revealed no significant differences for brain subregions between Sham and rTBI. (e) Representative SWI data and corresponding manual brain masking. (f) Quantitative analyses of SWI intensity revealed no significant differences for brain subregions between Sham and rTBI. Brain masking color code: yellow: cortex, green: light blue: prefrontal cortex; hippocampus; dark blue: thalamus. N= 10 rTBI and 10 Sham mice. Unpaired t-test; data are expressed as means ± SD.

PDH and LDH enzyme activity.

MCT1 and MCT4 protein expression.

List of variables used for ML analyses.

List of variables used for ML analyses.

ML analyses identify best rTBI and Sham classifiers and best predictors of changes in risk-taking behavior and HP ¹³C Lac/Pyr Ctx.
(a) Top two triplets that can classify rTBI (red) and Sham (black) mice. Here, circles represent the mice for which all three variables are measured whereas triangles represent mice for which at least one of the three variables were missing and predicted by ML algorithms (see Methods). (b-c) Prediction performance of the best predictors of risk-taking behavior (b, bottom panel), and HP ¹³C Lac/Pyr Ctx (c, bottom panel) compared to the prediction performance of the case in which all variables are used (b-c top panel). N= 10 rTBI and 10 Sham mice.

Brain region volumes.
Quantitative analyses of brain volumes calculated from T₂-weighted MRI indicated no significant differences for the cortex, hippocampus, prefrontal cortex, thalamus, whole brain and ventricles areas between Sham (filled circles) and rTBI (red open circles). N= 10 rTBI and 10 Sham mice. Unpaired t-tests; data are expressed as means ± SD.

Other three best classifying triplets of rTBI and Sham mice.
Circles represent the mice for which all three variables are measured whereas triangles represent mice for which at least one of the three variables were missing and predicted by ML algorithms (see Methods). N= 10 rTBI and 10 Sham mice.

The ML pipeline.
(1) The original data was scaled due to their numerical uneven scales for fair treatment within ML algorithms. (2) The scaled data was split into training and testing data separately for rTBI and Sham mice. (3) Random Forrest Regressor was trained using the training datasets and (4) missing variable measurements were predicted by the learned regressor using the testing data. (5) Lastly, ML classification and feature extraction algorithms were used to classify and rank the variables based on their contribution to the classification of the two groups. Each step is explained in details in the Methods section.

Example of original versus scaled data distributions.
(a) Original measurements for Var 4. (b) Scaled measurements for Var 4. N= 10 rTBI and 10 Sham mice.

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