Chemical Shift MR Imaging of Hyperattenuating (>10 HU) Adrenal Masses: Does It Still Have a Role?
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Bibliographic record
Abstract
PURPOSE: To evaluate chemical shift magnetic resonance (MR) imaging for the characterization of hyperattenuating adrenal masses. MATERIALS AND METHODS: Adrenal MR images obtained from January 1998 to February 2003 were reviewed. Patients were excluded if they did not undergo unenhanced computed tomography or did not have an adrenal mass with attenuation higher than 10 HU, adequate follow-up, or pathologic diagnosis for use as a reference standard. A diagnosis of adenoma required at least 24 weeks of stability on images. Thirty-eight masses in 36 patients were identified (27 adenomas, nine metastases, one adrenocortical oncocytoma, and one pheochromocytoma). Signal intensity (SI) decrease between in-phase and opposed-phase MR images was measured for the entire mass and normalized to the renal parenchymal SI. In 21 of 36 (58%) patients, dual-echo single-breath-hold MR imaging was used to eliminate misregistration. RESULTS: The attenuation of 61% (23 of 38) of all masses and 70% (19 of 27) of adenomas was 10-30 HU. With a threshold of 20% SI decrease, the sensitivity of chemical shift MR imaging for hyperattenuating adenoma was 67% (18 of 27 masses). When considering masses with attenuation of 10-30 HU, the sensitivity for adenoma was 89% (17 of 19 masses) and remained reasonable at 75% (six of eight masses) for adenomas with attenuation of 20-30 HU. Only one adenoma with attenuation higher than 30 HU had SI decrease of more than 20%. Specificity for diagnosis of adenoma was 100% (11 of 11). CONCLUSION: In certain circumstances, chemical shift MR imaging is a reasonable second imaging test for further characterization of a hyperattenuating adrenal mass.
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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 | 0.000 |
| 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 it