Computed Tomography–detected Noncalcified Pulmonary Nodules: A Review of Evidence for Significance and Management
Bibliographic record
Abstract
Our purpose was to review the reported behavior and malignant risk of small noncalcified pulmonary nodules detected by computed tomography (CT). A review of published clinical guidelines and studies using CT scan for lung cancer screening was performed. Small pulmonary nodules are found in 5 to 60% of patients in published CT screening studies. The detection rate is influenced by the CT scan technique used, definition of a significant nodule, and the population of subjects screened. There is limited published systematic longitudinal observation of all nodules of any size. The malignancy rate of small nodules detected in smokers is likely less than 1 to 2%, and predictors of malignancy include semisolid appearance, diameter greater than or equal to 10 mm or persistent growth on greater than or equal to two CT scans. There is a wide variation in the performance of positron emission tomography (PET) scan in screening detected lung cancers. In summary, multidetector row CT detects greater than or equal to 1 nodule in most high-risk patients. The risk of malignancy for a single nodule appears to be low, but is increased by serial growth, diameter greater than or equal to 10 mm, and semisolid appearance. The role of PET in evaluating these nodules needs further exploration. Serial follow-up for 24 months in a high-risk cohort appears reasonable based on present data, but further longitudinal information is required.
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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) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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".