<sup>68</sup>Ga PET/CT Ventilation–Perfusion Imaging for Pulmonary Embolism: A Pilot Study with Comparison to Conventional Scintigraphy
Bibliographic record
Abstract
UNLABELLED: Ventilation-perfusion (V/Q) scintigraphy is established for regional assessment of lung function in a variety of diseases, including pulmonary embolism (PE). PET/CT may further improve the accuracy and utility of V/Q imaging because of its superior technical characteristics. This pilot study assessed the feasibility of performing V/Q PET/CT and compared diagnostic utility with conventional V/Q imaging in patients with clinical suspicion of PE. METHODS: Ten patients undergoing conventional V/Q imaging were prospectively recruited. PET/CT V/Q imaging was performed after inhalation of (68)Ga-carbon nanoparticles ("Galligas") and administration of (68)Ga-macroaggregated albumin. Blinded to the results of the other study, SPECT/CT (n = 9) or SPECT (n = 1) images and PET/CT images were graded by a predefined scoring system for scan quality. The number of matched or unmatched defects and diagnosis were also measured and compared with a final diagnosis. RESULTS: PET image quality was equivalent or superior to SPECT in all patients, with more homogeneous radiotracer distribution for both ventilation and perfusion studies (P < 0.01). Based on conventional V/Q imaging, the diagnosis was acute PE in 2 patients and no PE in 7 patients, and the imaging results were nondiagnostic in 1 patient. The PET/CT diagnosis was concordant in 8 patients, and these studies demonstrated a similar number and distribution of matched and unmatched defects. In 1 discordant case, a patient with a SPECT/CT study that was nondiagnostic because of severe airway disease showed no PE on PET/CT. In another, the diagnosis of PE established on SPECT/CT was not reported on PET/CT 2 d later, possibly because of interval clot lysis or migration. CONCLUSION: This intraindividual comparative study demonstrated that V/Q PET/CT with (68)Ga-labeled radiotracers can be performed in clinical practice. Compared with conventional V/Q imaging, advantages include higher-resolution, fully tomographic images with potentially better regional quantitation of lung function. The short half-life of (68)Ga also enables more flexible acquisition protocols with the option of performing ventilation studies selectively on patients with abnormal perfusion. On the basis of our results, further studies are indicated to assess whether V/Q PET/CT can improve diagnostic algorithms for patients with suspected PE.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".