Imaging Mechanisms of Disease Progression in Multiple Sclerosis: Beyond Brain Atrophy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Clinicians involved with different aspects of the care of persons with multiple sclerosis (MS) and scientists with expertise on clinical and imaging techniques convened in Dallas, TX, USA on February 27, 2019 at a North American Imaging in Multiple Sclerosis Cooperative workshop meeting. The aim of the workshop was to discuss cardinal pathobiological mechanisms implicated in the progression of MS and novel imaging techniques, beyond brain atrophy, to unravel these pathologies. Indeed, although brain volume assessment demonstrates changes linked to disease progression, identifying the biological mechanisms leading up to that volume loss are key for understanding disease mechanisms. To this end, the workshop focused on the application of advanced magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging techniques to assess and measure disease progression in both the brain and the spinal cord. Clinical translation of quantitative MRI was recognized as of vital importance, although the need to maintain a relatively short acquisition time mandated by most radiology departments remains the major obstacle toward this effort. Regarding PET, the panel agreed upon its utility to identify ongoing pathological processes. However, due to costs, required expertise, and the use of ionizing radiation, PET was not considered to be a viable option for ongoing care of persons with MS. Collaborative efforts fostering robust study designs and imaging technique standardization across scanners and centers are needed to unravel disease mechanisms leading to progression and discovering medications halting neurodegeneration and/or promoting repair.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it