Metabolic Abnormalities in the Hippocampus of Patients with Schizophrenia: A 3D Multivoxel MR Spectroscopic Imaging Study at 3T
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Schizophrenia is well-known to be associated with hippocampal structural abnormalities. We used 1H-MR spectroscopy to test the hypothesis that these abnormalities are accompanied by NAA deficits, reflecting neuronal dysfunction, in patients compared with healthy controls. MATERIALS AND METHODS: Nineteen patients with schizophrenia (11 men; mean age, 40.6 ± 10.1 years; mean disease duration, 19.5 ± 10.5 years) and 11 matched healthy controls (5 men; mean age, 33.7 ± 10.1 years) underwent MR imaging and multivoxel point-resolved spectroscopy (TE/TR, 35/1400 ms) 1H-MRS at 3T to obtain their hippocampal GM absolute NAA, Cr, Cho, and mIns concentrations. Unequal variance t tests and ANCOVA were used to compare patients with controls. Bilateral volumes from manually outlined hippocampal masks were compared by using unequal variance t tests. RESULTS: Patients9 average hippocampal GM Cr concentrations were 19% higher than that of controls, 8.7 ± 2.2 versus 7.4 ± 1.2 mmol/L (P < .05); showing no differences, concentrations in NAA were 8.8 ± 1.6 versus 8.7 ± 1.2 mmol/L; in Cho, 2.3 ± 0.7 versus 2.1 ± 0.3 mmol/L; and in mIns, 6.1 ± 1.5 versus 5.2 ± 0.9 (all P > .1). There was a positive correlation between mIns and Cr in patients (r = 0.57, P = .05) but not in controls. The mean bilateral hippocampal volume was ∼10% lower in patients: 7.5 ± 0.9 versus 8.4 ± 0.7 cm3 (P < .05). CONCLUSIONS: These findings suggest that the hippocampal volume deficit in schizophrenia is not due to net loss of neurons, in agreement with histopathology studies but not with prior 1H-MR spectroscopy reports. Elevated Cr is consistent with hippocampal hypermetabolism, and its correlation with mIns may also suggest an inflammatory process affecting some cases; these findings may suggest treatment targets and markers to monitor them.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".