Selection of Patients for Lung Volume Reduction LVRS Using a Power Law Analysis of the Computed Tomographic Scan
Bibliographic record
Abstract
Selection of Patients for Lung Volume Reduction LVRS Using a Power Law Analysis of the Computed Tomographic Scan Thorax. 2003;58:510–514. Coxson HO, Whittall KP, Nakano Y, Rogers RM, Sciurba FC, Keenan RJ, Hogg JC. University of British Columbia, McDonald Research Laboratories, St. Paul's Hospital, Department of Radiology, Vancouver General Hospital, Vancouver, BC, Canada; and Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, and Division of Thoracic Surgery, Department of Surgery, University of Pittsburgh Medical Center and School of Medicine, Pittsburgh, PA. Comments: This study was planned to test the hypothesis that patients respond better to lung volume reduction LVRS (LVRS) if their emphysema is confluent and predominantly located in the upper lobes. A density mask analysis was used to identify voxels inflated beyond 10.2 mL gas/g tissue (−910 HU) on preoperative and postoperative computed tomography scans from patients who underwent LVRS. These hyperinflated regions were considered to represent emphysematous lesions. A power law analysis was used to determine the relationship between the number (K) and size (A) of the emphysematous lesions in the whole lung and 2 anatomic regions using the power law equation Y = KA−D. The analysis was performed on 21 subjects who underwent bilateral LVRS using either video-assisted thoracoscopy (n = 17) or median sternotomy (n = 4). The analysis showed a positive correlation between the change in the power law exponent (D) and the change in exercise (Watts) after LVRS (r = 0.47, P = 0.03). There was also a negative correlation between the power law exponent D in the upper region of the lung preoperatively and the change in exercise after LVRS (r = −0.60, P < 0.05). The authors conclude that patients with large upper lobe lesions respond better to LVRS than patients with small uniformly distributed disease, and that power law analysis of lung computed tomography scans provides a quantitative method for determining the extent and location of emphysema within the lungs of patients with chronic obstructive pulmonary disease. This study informs us that quantitative analyses of computed tomography scans show a better correlation with pulmonary pathology and provide direct evidence that LVRS reduces both the volume of large emphysematous lesions (>5 mm diameter) and total lung volume. The recent studies from NETT have shown that an upper peripheral distribution of emphysema is predictive of improvement in cardiopulmonary exercise after LVRS. The power law analysis of the computed tomography scan, as described by Coxson and colleagues, seems capable of providing objective assessment of the extent and location of emphysema within the lungs of patients undergoing LVRS. Several studies have shown that subjects with a heterogeneous pattern of emphysema on computed tomography scanning respond better to LVRS than those with a homogeneous distribution. The radiologic technique described by Coxson and associates could help better identify patients with heterogeneous pattern of emphysema.
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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 | 0.001 |
| 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) | 0.000 | 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".