Multimodal MRI staging for tracking progression and clinical-imaging correlation in sporadic Creutzfeldt-Jakob disease
Bibliographic record
Abstract
Diffusion imaging is very useful for the diagnosis of sporadic Creutzfeldt-Jakob disease, but it has limitations in tracking disease progression as mean diffusivity changes non-linearly across the disease course. We previously showed that mean diffusivity changes across the disease course follow a quasi J-shaped curve, characterized by decreased values in earlier phases and increasing values later in the disease course. Understanding how MRI metrics change over-time, as well as their correlations with clinical deficits are crucial steps in developing radiological biomarkers for trials. Specifically, as mean diffusivity does not change linearly and atrophy mainly occurs in later stages, neither alone is likely to be a sufficient biomarker throughout the disease course. We therefore developed a model combining mean diffusivity and Volume loss (MRI Disease-Staging) to take into account mean diffusivity's non-linearity. We then assessed the associations between clinical outcomes and mean diffusivity alone, Volume alone and finally MRI Disease-Staging. In 37 sporadic Creutzfeldt-Jakob disease subjects and 30 age- and sex-matched healthy controls, high angular resolution diffusion and high-resolution T1 imaging was performed cross-sectionally to compute z-scores for mean diffusivity (MD) and Volume. Average MD and Volume were extracted from 41 GM volume of interest (VOI) per hemisphere, within the images registered to the Montreal Neurological Institute (MNI) space. Each subject's volume of interest was classified as either "involved" or "not involved" using a statistical threshold of ± 2 standard deviation (SD) for mean diffusivity changes and/or -2 SD for Volume. Volumes of interest were MRI Disease-Staged as: 0 = no abnormalities; 1 = decreased mean diffusivity only; 2 = decreased mean diffusivity and Volume; 3 = normal ("pseudo-normalized") mean diffusivity, reduced Volume; 4 = increased mean diffusivity, reduced Volume. We correlated Volume, MD and MRI Disease-Staging with several clinical outcomes (scales, score and symptoms) using 4 major regions of interest (Total, Cortical, Subcortical and Cerebellar gray matter) or smaller regions pre-specified based on known neuroanatomical correlates. Volume and MD z-scores correlated inversely with each other in all four major ROIs (cortical, subcortical, cerebellar and total) highlighting that ROIs with lower Volumes had higher MD and vice-versa. Regarding correlations with symptoms and scores, higher MD correlated with worse Mini-Mental State Examination and Barthel scores in cortical and cerebellar gray matter, but subjects with cortical sensory deficits showed lower MD in the primary sensory cortex. Volume loss correlated with lower Mini-Mental State Examination, Barthel scores and pyramidal signs. Interestingly, for both Volume and MD, changes within the cerebellar ROI showed strong correlations with both MMSE and Barthel. Supporting using a combination of MD and Volume to track sCJD progression, MRI Disease-Staging showed correlations with more clinical outcomes than Volume or MD alone, specifically with Mini-Mental State Examination, Barthel score, pyramidal signs, higher cortical sensory deficits, as well as executive and visual-spatial deficits. Additionally, when subjects in the cohort were subdivided into tertiles based on their Barthel scores and their percentile of disease duration/course ("Time-Ratio"), subjects in the lowest (most impaired) Barthel tertile showed a much greater proportion of more advanced MRI Disease-Stages than the those in the highest tertile. Similarly, subjects in the last Time-Ratio tertile (last tertile of disease) showed a much greater proportion of more advanced MRI Disease-Stages than the earliest tertile. Therefore, in later disease stages, as measured by time or Barthel, there is overall more Volume loss and increasing MD. A combined multiparametric quantitative MRI Disease-Staging is a useful tool to track sporadic Creutzfeldt-Jakob- disease progression radiologically.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".