Quantitative Flow Measurements in the Internal Jugular Veins of Multiple Sclerosis Patients Using Magnetic Resonance Imaging
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
PURPOSE: To study the blood flow through the internal jugular veins (IJVs) of the MS population. MATERIALS AND METHODS: Two hundred MS patients and 14 normal volunteers were evaluated with magnetic resonance imaging (MRI) at 3T. Contrast-enhanced time-resolved 3D MR angiography and 2D time-of-flight imaging were performed to assess abnormalities in the extracranial vascular anatomy. Based on this assessment, the MS population was divided into subgroups of non-stenotic (NST), cervical 1 stenotic only (C1ST) and cervical 6 stenotic (C6ST) subjects. In this study, 2D phase contrast MR imaging was used to quantify blood flow through major veins and arteries in the neck and flow differences among the groups were analyzed. RESULTS: Of the 200 MS patients, 87 (43.5%) belonged to the NST group, 50 (25%) belonged to the C1ST group and 63 (31.5%) belonged to the C6ST group. The total IJV flow normalized to the total arterial flow of the NST group was 75.12 ± 12.22 %. This was significantly higher than that of the C1ST group, 63.93 ± 16.08 % (p < 0.0001), which in turn was significantly higher than that of the C6ST group, 52.13 ± 20.71 % (p = 0.001). Seventy-nine percent of the stenotic groups had a normalized subdominant IJV flow of less than 20%, a combined IJV flow of less than 5o% and/or a sub-dominant IJV flow vs. dominant IJV flow ratio of less than 1/3. Only 2% of the NST group had a combined IJV flow of less than 50%, compared to 35% of the stenotic groups. CONCLUSION: Blood flow through the IJVs was reduced in the MS population with stenoses compared to those without.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.039 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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