Additional value of combining low-dose computed tomography to V/Q SPECT on a hybrid SPECT-CT camera for pulmonary embolism diagnosis
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: The aim of the study was to assess the potential interest of combining a low-dose computed tomography (ldCT) to ventilation/perfusion (V/Q) single-photon emission computed tomography (SPECT) for the diagnosis of pulmonary embolism (PE). We addressed three main questions: Could ldCT be used in substitution to ventilation SPECT? Could ldCT improve the diagnostic performance of V/Q SPECT? Could ldCT provide alternative diagnoses to PE? METHODS: A total of 393 patients previously analysed in a management outcome study that aimed at assessing the safety of V/Q SPECT for PE diagnosis were assessed. All patients underwent an ldCT under the same SPECT-computed tomography camera, which was not used at the time of initial interpretation. Three retrospective analyses were performed: Q SPECT combined with ldCT, V/Q SPECT combined with ldCT and ldCT only. RESULTS: On the basis of initial V/Q SPECT interpretation, 110 (28%) patients were positive and 283 (72%) were negative for PE.With Q SPECT-ldCT, 139 (35%) patients were positive and 254 (65%) were negative, with 55 (19%) discrepancies when compared with V/Q SPECT. Of the 283 patients with negative V/Q SPECT, 42 were positive with V/Q SPECT-ldCT, and among the 110 patients with positive V/Q SPECT 13 were negative with V/Q SPECT-ldCT. On using V/Q SPECT-ldCT, 97 (25%) patients were positive and 296 (75%) were negative, with 13 (3%) discrepancies when compared with V/Q SPECT (all had had a positive V/Q SPECT but a negative V/Q SPECT-ldCT). Finally, 67 (24%) ldCT scans showed a potential alternative diagnosis to PE. CONCLUSION: For PE diagnosis with lung SPECT, the use of ldCT in substitution to ventilation SPECT is associated with a high risk of overdiagnosis. The diagnostic value of ldCT in addition to V/Q SPECT remains unclear. Further studies are needed to determine its potential role in PE diagnosis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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