MR imaging and angiography of primary CNS vasculitis of childhood.
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Primary angiitis of the central nervous system of childhood (cPACNS) is a rare and ill-defined disease. In the absence of a brain biopsy, the diagnosis is based on typical clinical and imaging abnormalities. The aim of this study was to analyze systematically the MR imaging and MR angiographic (MRA) abnormalities in a large cohort of children with cPACNS. METHODS: We analyzed the MR imaging features of a single pediatric center cohort of 45 cPACNS patients. MR imaging studies were performed for all patients, and both MR imaging and MRA were performed for 42 patients, who formed the cohort for review of the presence and correlation of lesions. Proportions were calculated by using the Fisher exact test, and agreement between MR imaging and MRA was calculated by using the McNemar test. The sensitivity of each diagnostic technique was established. RESULTS: The most-common pattern of parenchymal abnormality was multifocal, unilateral involvement, each in 42/45 patients (93%). The lateral lenticulostriate artery terrritory was affected in 56% of cases, with involvement of a supratentorial deep gray matter structure in 91%. No infratentorial lesion occurred in the absence of supratentorial abnormality. MRA was normal in 12/42 patients (28.6%). Among the abnormal studies, stenosis was detected on MRA in 83% and was "benign" in appearance in 73% of patients and "aggressive" in 16.7%. Involvement was proximal in 83% and distal in 27% of patients. Multiple ipsilateral lesions were seen in 63%. MR imaging was abnormal in every patient where MRA was abnormal. With the assumption of MR imaging as the gold standard, the sensitivity of MRA was 72%. The agreement between MR imaging and MRA for abnormality was significant (P = .04). CONCLUSION: We have illustrated the MR imaging and MRA appearances of cPACNS in the largest cohort to date. Both parenchymal and vascular lesions were predominantly proximal, unilateral, and multifocal within the anterior circulation. There was good agreement between MR imaging and MRA for lesion location. MR imaging findings were abnormal in all cases at diagnosis, and this remains the most sensitive technique to the detection of vasculitis.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".