Imaging in Cushing's syndrome
Bibliographic record
Abstract
Once the diagnosis of Cushing's syndrome (CS) has been established, the main step is to differentiate between ACTH dependent and independent disease. In adults, 80% of CS is due to ACTH-dependent causes and 20% due to adrenal causes. ACTH-secreting neoplasms cause ACTH-dependent CS. These are usually anterior pituitary microadenomas, which result in the classic Cushing's disease. Non-pituitary ectopic sources of ACTH, such as a small-cell lung carcinoma or carcinoid tumours, are the source of the remainder of ACTH-dependent disease. In the majority of patients presenting with clinical and biochemical evidence of CS, modern non-invasive imaging can accurately and efficiently provide the cause and the nature of the underlying pathology. Imaging is essential for determining the source of ACTH in ectopic ACTH production, locating the pituitary tumours and distinguishing adrenal adenomas, carcinomas and hyperplasias. In our chapter we review the adrenal appearances in ACTH-dependent and ACTH-independent CS. We also include a discussion on the use of MRI and CT for the detection and management of pituitary ACTH secreting adenomas. CT of the chest, abdomen and pelvis with intravenous injection of contrast medium is the most sensitive imaging modality for the identification of the ectopic ACTH source and detecting adrenal pathology. MRI is used for characterising adrenal adenomas, problem solving in difficult cases and for detecting ACTH-secreting pituitary adenomas.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".