Characteristic CT Findings After Percutaneous Cryoablation Treatment of Malignant Lung Nodules
Bibliographic record
Abstract
Assess computed tomography (CT) imaging characteristics after percutaneous cryotherapy for lung cancer.A retrospective IRB-approved analysis of 40 patients who underwent nonsurgical treatment for primary stage 1 lung cancer performed from January 2007 to March 2011 was included in this study. All procedures were performed using general anesthesia and CT guidance. Follow-up imaging with CT of the chest was obtained at 1 month, 3 months, 6 months, and 12 months postprocedure to evaluate the ablated lung nodule. Nodule surface area, density (in Hounsfield units), and presence or absence of cavitations were recorded. In addition, the degree of nodule enhancement was also recorded. Patients who were unable to obtain the aforementioned follow-up were excluded from the study.Thirty-six patients underwent percutaneous cryoablation with men to women ratio of 75% with mean age for men 74.6 and mean age for women 74.3 years of age. The average nodule surface area preablation and postcryoablation at 1-, 3-, 6-, and 12-month follow-ups were 2.99, 7.86, 3.89, 3.18 and 3.07[REPLACEMENT CHARACTER]cm, respectively. The average precontrast nodule density before cryoablation was 8.9 and average precontrast nodule density postprocedure at 1, 3, 6, and 12 months follow-ups were 8.5, -5.9, -9.4, and -3.8 HU, respectively. There is increased attenuation of lung nodules over time with an average postcontrast enhancement of 11.4, 18.5, 16.1, and 25.7 HU at the aforementioned time intervals. Cavitations occurred in the cryoablation zone in 53% (19/36) of patients. 80.6% (29/36) of the cavitations in the cryoablation zone resolved within 12 months. Four patients (11%) had recurrence of tumor at the site of cryoablation and none of the patients had satellite or distant metastasis.Our study shows that patients who underwent cryotherapy for lung nodules treatment had characteristic changes on follow-up CT including. The surface area of the nodule increases at the 1-month follow-up with subsequent gradual decrease in the surface area. Decreased nodule density (Hounsfield units) at each interval follow-up is associated with complete ablation of the lung cancer whereas increasing nodule density was suggestive of recurrence. Cavity formation within the region of the ablated nodule, most of which typically resolved within the first 3 to 6 months. Nodule enhancement is difficult to assess because of the limited data sets that are available.
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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) | 0.001 | 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".