Assessment of Inter-Reader Reliability of Fazekas Scoring on Magnetic Resonance Imaging of the Brain in Adult Patients with Sickle Cell Disease
Bibliographic record
Abstract
Background/Objectives: Cerebral white matter disease is a common finding in patients with sickle cell that has been linked to cognitive impairment. However, there is no standardized approach for quantification of the cerebral disease burden. The Fazekas score is widely used to quantify the burden of white matter disease in chronic small vessel disease. However, its utility in sickle cell disease, specifically the inter-rater variability, has not been established. Methods: A patient cohort was compiled for the purpose of a research ethics board (REB)-approved retrospective study of adult patients with sickle cell disease, each of whom underwent MRI/MRA between the years 2017 and 2019. A total of 90 such patients were captured. All MRI/MRA studies were performed on three Tesla MRIs. Two independent neuroradiologists assessed the axial FLAIR MRI brain sequence (see image 1) for each of the 90 patients, with the sole focus of assigning a Fazekas score (0–3) to each study as a means of quantifying the burden of ischemic white matter lesions. The neuroradiologists were blinded to the scoring assigned by their counterpart and to the clinical information. After the initial assessment was completed, studies with discrepant Fazekas scores were documented and discussed by both readers. A consensus Fazekas score was then assigned to each of these studies. Results: Cohen’s weighted kappa was used as a measure of agreement between readers. The expected agreement was 74.65%, with an observed agreement of 94.44% between readers, with a kappa of 0.7808. Conclusions: We conclude on the basis of our study that there is good inter-reader reliability of Fazekas scoring on axial FLAIR MRI brain sequence in patients with sickle cell disease. The Fazekas is a promising measure that could easily be integrated in systematic evaluation of cerebrovascular lesions of adults with sickle cell disease.
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.
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 | 0.040 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".