Magnetic Resonance Imaging of the Paranasal Sinuses: Incidental Abnormalities and Their Relationship to Patient Symptoms
Bibliographic record
Abstract
OBJECTIVES: Magnetic resonance imaging (MRI) is able to demonstrate a wide range of abnormalities in the paranasal sinuses, which are often reported as incidental findings on scans performed for indications other than the evaluation of paranasal sinus pathology. However, the clinical significance of these findings remains undefined. We present a prospective study that determines the prevalence of abnormalities in the paranasal sinuses in a population undergoing MRI scans for suspected intracranial disease. These findings are correlated with clinical data pertaining to nasal and sinus symptoms. STUDY DESIGN: Prospective, cross-sectional study. METHODS: Patients undergoing MRI scans for suspected intracranial pathology were asked to complete a questionnaire pertaining to symptoms of nasal/sinus pathology. The T2-weighted scans of 86 patients (mean age = 51 years) were then reviewed for evidence of paranasal sinus pathology using a standardized method for evaluation and reporting of results. These results were then correlated with those obtained from the patient questionnaire. RESULTS: Radiologic abnormalities were found in the paranasal sinuses of 33 (38%) patients. Abnormalities were most commonly seen in the ethmoid sinuses (44.8%) followed by the maxillary (38%), sphenoid (14%), and frontal (3%) sinuses. Analysis of the clinical data revealed no significant relationship between the presence of clinical symptoms of nasal and sinus pathology and abnormalities on MRI scan. CONCLUSION: The assessment of inflammatory sinus pathology remains controversial. Based on the results of this study, incidental abnormalities of the paranasal sinuses detected on MRI scan do not appear to be related to clinical symptoms.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".