Impact of [18F]FDG PET/CT in the Assessment of Immunotherapy-Induced Arterial Wall Inflammation in Melanoma Patients Receiving Immune Checkpoint Inhibitors
Bibliographic record
Abstract
We aimed to investigate the role of [18F]FDG positron emission tomography/computed tomography (PET/CT) in the early detection of arterial wall inflammation (AWI) in melanoma patients receiving immune checkpoint inhibitors (ICIs). Our retrospective study enrolled 95 melanoma patients who had received ICIs. Inclusion criteria were ICI therapy for at least six months and at least three [18F]FDG PET/CTs, including one pretreatment session plus two scans three and six months after treatment initiation. AWI was assessed using quantitative and qualitative methods in the subclavian artery, thoracic aorta, and abdominal aorta. We found three patients with AWI visual suspicion in the baseline scan, which increased to five in the second and twelve in the third session. Most of these patients’ treatments were terminated due to either immune-related adverse events (irAEs) or disease progression. In the overall population, the ratio of arterial-wall maximum standardized uptake value (SUVmax)/liver-SUVmax was significantly higher three months after treatment than the pretreatment scan in the thoracic aorta (0.83 ± 0.12 vs. 0.79 ± 0.10; p-value = 0.01) and subclavian artery (0.67 ± 0.13 vs. 0.63 ± 0.12; p-value = 0.01), and it remained steady in the six-month follow-up. None of our patients were diagnosed with definite clinical vasculitis on the dermatology follow-up reports. To conclude, our study showed [18F]FDG PET/CT’s potential to visualise immunotherapy-induced subclinical inflammation in large vessels. This may lead to more accurate prediction of irAEs and better patient management.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".