Preliminary Evaluation of Longitudinal Brain MRI Volumetric Quantification in Persons with Cognitive Decline and Confirmed Amyloid Burden Undergoing Multi‐Modal Interventions at an Outpatient Memory Clinic
Bibliographic record
Abstract
Abstract Background Personalized multi‐modal interventions for Alzheimer dementia hold promise to slow progression of symptoms yet related quantitative neuroimaging biomarkers have not been investigated[1,2]. Method We selected 16 participants (mean age 68.6±5.9 [range 57‐77] years, 50% female) from the Pacific Brain Health Center at Providence St. John’s Health Center, with biomarker evidence of Alzheimer dementia amyloidosis. All participants received data‐supported clinical recommendations (DSCR), [3–7] which included a modified SHIELD program[8] recommending a low carbohydrate diet. DSCRs were personalized based on clinical evaluations and laboratory values and closely overseen by a dementia specialist (DM, CW). T1‐weighted MR images were acquired at baseline and with a 1‐year average follow up. Total gray and white matter, hippocampal, lateral ventricle, temporal, parietal, occipital and frontal lobe volumes were quantified using Neuroreader[9]. Global cognition was tested using the Montreal Cognitive Assessment (MoCA). Paired t‐tests were done for these metrics. Result Changes in hippocampal volumes (t=+1.6, p=0.11), temporal (t=+0.03, p=0.97) and frontal lobes (t=‐0.63, p=0.53) were not significant. There was a marginally significant decline in the parietal lobes (t=+2.1, p=.048) and statistically significant increased lateral ventricles (t=‐4.9, p<0.01). White matter volume declined significantly (t=‐2.8, p=0.01) while gray matter did not change significantly (t=+1.2, p=0.21). Table 1 shows annualized percent changes for these regions. These changes were attenuated compared to literature values for the following regions: gray matter at ‐2%/year [10], hippocampus at ‐3.5%/year [11], temporal lobes at ‐3.23%/year, parietal lobes at ‐3.62%/year and frontal lobes at ‐2.88%/year [12]. Total gray matter and frontal lobe volumes showed increased average annualized changes at +1.97%/year and +0.87%/year respectively. Over the same time period as the brain‐volume trajectory measurements, there was an average decline in MoCA (‐1.5 from 22.06±4.1 to 20.56±6.1, p=0.06) that trended towards but was not statistically significant. Conclusion Regional volume loss, while present, was moderated compared to literature derived rates. Increased ventricular volumes appear driven by white matter volume loss. These preliminary data suggest that efforts to track and report on clinical outcomes in settings providing close medical management and multimodal lifestyle recommendations may be a worthwhile step towards validating research findings.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".