Streamlining the Imaging of Clinically Suspected Pheochromocytoma: Using Urine Metanephrines to Decrease Imaging Costs
Bibliographic record
Abstract
PURPOSE: To improve the cost efficiency of the imaging evaluation of clinically suspected pheochromocytoma by using 24-hour fractionated urine metanephrine (FUM) results. METHODS: A retrospective review of I-123 meta-iodo-benzyl-guanidine single photon emission tomography (SPECT) computed tomography (CT) studies performed at our institution between January 2007 and February 2011 for clinically suspected pheochromocytoma was performed. SPECT-CT results from 70 patients were compared with results from 24-hour FUM analysis (within 2 months of SPECT-CT) and with relevant CT or magnetic resonance imaging studies (within 6 months of SPECT-CT). An imaging algorithm was developed to maximize cost efficiency without altering the final imaging interpretation. Actual imaging costs for the studied cohort were compared with the expected costs if this algorithm had been applied. RESULTS: If the 24-hour FUMs were normal, then all the SPECT-CT studies were negative (16/70). Eighty-seven percent of patients with abnormal total metanephrine had a positive SPECT-CT. If the total metanephrine was normal but 1 or more of the metanephrine fractions were abnormal, then 39%-58% of the SPECT-CT studies were positive. Within this subgroup, none had a positive SPECT-CT if a CT or magnetic resonance image was negative or benign. The actual imaging costs averaged CAD$2833.19 per patient for this cohort. Applying a streamlined imaging algorithm guided by 24-hour FUM analysis would result in an average imaging cost of CAD$1225.97 per patient without an expected change in the final imaging impression. CONCLUSION: By using 24-hour FUM results to streamline imaging, considerable cost savings per patient (56.7%) can be attained without a change in the final overall imaging interpretation.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".