Accuracy of Dual Phase Single-Photon Emission Computed Tomography/Computed Tomography in Primary Hyperparathyroidism: Correlation with Serum Parathyroid Hormone Levels
Bibliographic record
Abstract
PURPOSE: The objectives of this study were: 1) to determine the accuracy of dual-phase (99m)Tc -methoxyisobutylisonitrile (MIBI) with single-photon emission computed tomography/computed tomography (SPECT/CT) for the preoperative localization of parathyroid adenomas in the setting of primary hyperparathyroidism; 2) to determine the accuracy of localization for ectopic glands; and 3) to assess the relationship between accuracy and serum parathyroid hormone (PTH) levels. METHODS: Eighty-eight patients who underwent (99m)Tc-MIBI SPECT/CT imaging for primary hyperparathyroidism at our institution over a 27-month period were retrospectively assessed. The preoperative SPECT/CT results were compared to intraoperative findings (within 1 year of imaging). The relationship between serum PTH level (within 3 months) and SPECT/CT accuracy was then evaluated. RESULTS: Accuracy indices for the retrothyroid subgroup were sensitivity 86.7%, specificity 96.4%, positive predictive value 98.1%, negative predictive value 77.1%, and accuracy 89.8%. Accuracy indices for ectopic parathyroid adenomas were sensitivity 81.5%, specificity 100%, positive predictive value 100%, negative predictive value 92.4%, and accuracy 94.3%. For the overall group, SPECT/CT demonstrated a sensitivity of 85.1% and a PPV of 98.7%. SPECT/CT correctly identified the abnormal parathyroid gland in 60% of patients with a normal serum PTH (<6.9 pmol/L), 73% between 6.9-9.9 pmol/L, 86% between 10.0-14.9 pmol/L, 100% between 15.0-19.9 pmol/L, 88% between 20.0-24.5 pmol/L, and 100% of patients with a PTH greater than 25.0 pmol/L. CONCLUSIONS: Dual-phase (99m)Tc- MIBI with SPECT/CT is an accurate and reliable means to correctly localize both retrothyroid and ectopic parathyroid adenomas for the purpose of surgical planning. The accuracy of SPECT/CT increases with increasing serum PTH levels.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".