Reduced blood flow velocity in lenticulostriate arteries of patients with CADASIL assessed by PC-MRA at 7T
Bibliographic record
Abstract
Previous studies reported cerebral hypoperfusion ocurred in patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL).1 2 As a cerebral small vessels disease, the reduction of blood flow velocity in cerebral small arteries may precede cerebral hypoperfusion and lesions formation. Due to the limitations of spatial resolution, conventional methods failed to detect the velocity of cerebral small vessels. Ultrahigh field MRI provided us a non-invasive way to investigate the velocity in lenticulostriate arteries (LSAs) of patients with CADASIL.3–5 Assessing blood flow velocity of small arteries can monitor the progress of the disease in long-term follow-up of patients. We enrolled 32 patients with CADASIL and 34 healthy controls from September 2019 to September 2020 at Peking University First Hospital. Details of subject selection, clinical assessment, MRI acquisition and analysis were described in online supplemental methods, online supplemental figure 1, online supplemental tables 1 and 2. The phase contrast magnetic resonance angiography (PC-MRA) was acquired at a 7 T MR scanner with high resolution (0.35×0.35×0.40 mm3) and low velocity-encoding (VENC) value (15.00 cm/s) was acquired to measure blood flow velocities of LSAs. The analysis pipeline of LSA velocities includes: (1) intensity bias corrections; (2) LSA region extraction on maximum intensity projection images; (3) threshold-based noise masking; (4) velocity components reconstruction from phase-difference data; (5) extracting dominant branches of the LSAs and calculating mean velocity. Test–retest experiments and Bland-Altman analysis were performed to validate the precision of the measurement method (online supplemental figure 2).5 ### Supplementary data [jnnp-2021-326258supp001.pdf] ### Demographic and clinical features One patient and three healthy controls were excluded for excessive head motion causing large artefacts and poor image quality. Ultimately, we included 31 patients from 24 pedigrees and 31 healthy controls in this study. The heterozygous mutations affecting the patients with CADASIL were listed in online supplemental table 3 …
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 | 0.003 |
| 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".