Validation of a novel method for localization of parathyroid adenomas using SPECT/CT
Bibliographic record
Abstract
BACKGROUND: Accurate localization of parathyroid adenomas is of critical importance in surgical planning for minimally invasive parathyroidectomy. SPECT/CT is considered the investigation of choice but has limitations regarding localization of superior versus inferior adenomas. We proposed a novel method for localization using SPECT/CT by determining the anterior-posterior relationship of the adenoma to a horizontal line in the coronal plane through the tracheoesophageal groove. Our objective was to determine the accuracy, validity, and inter-rater reliability of this method. METHOD: This was a retrospective review of patients who underwent parathyroidectomy for a single adenoma between 2010-2017. SPECT/CT images were reviewed by two staff Otolaryngologists, a Radiologist, an Otolaryngology fellow and Otolaryngology resident. Results were compared using intra-operative report as the gold standard. Overall accuracy in determining superior/inferior and right/left adenomas was calculated, as well as Cohen's Kappa to determine agreement with operative report and inter-rater reliability. The performance was compared to that of the original radiology report. RESULTS: One hundred thirty patients met criteria and were included. Our method correctly identified the location of the adenoma in terms of both side and superior/inferior position in 80.4% [76 - 84%] of patients, which considerably outperformed the original radiology report at 48.5% [4-78%] accuracy. The agreement level between our method and operative report was high (Kappa=0.717 [0.691-0.743]), as was the inter-rater reliability (Kappa=0.706 [0.674-0.738]). CONCLUSION: We report a novel method for localization of parathyroid adenomas using SPECT/CT which outperforms standard radiology reporting. This tool can be used by surgeons and radiologists to better inform and plan for minimally invasive parathyroidectomy.
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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 | 0.016 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".