Diagnostic performance of prospective same-day 18F-FDG PET/MRI and 18F-FDG PET/CT in the staging and response assessment of lymphoma
Bibliographic record
Abstract
BACKGROUND: Accurate staging and response assessment are essential for prognosis and to guide treatment in patients with lymphoma. The aim of this study was to compare the diagnostic performance of FDG PET/MRI versus FDG PET/CT in adult patients with newly diagnosed Hodgkin and Non- Hodgkin lymphoma. METHODS: In this single centre study, 50 patients were prospectively recruited. FDG PET/MRI was performed after staging FDG PET/CT using a single injection of 18F-FDG. Patients were invited to complete same-day FDG PET/MRI with FDG PET/CT at interim and end of treatment response assessments. Performance was assessed using PET/CT as the reference standard for disease site identification, staging, response assessment with Deauville score and concordance in metabolic activity. RESULTS: Staging assessment showed perfect agreement (κ = 1.0, P = 0) between PET/MRI and PET/CT using Ann Arbor staging. There was excellent intermodality correlation with disease site identification at staging (κ = 0.976, P < 0.001) with FDG PET/MRI sensitivity of 96% (95% CI, 94-98%) and specificity of 100% (95% CI, 99-100%). There was good correlation of disease site identification at interim assessment (κ = 0.819, P < 0.001) and excellent correlation at end-of-treatment assessment (κ = 1.0, P < 0.001). Intermodality agreement for Deauville scores was good at interim assessment (κ = 0.808, P < 0.001) and excellent at end-of-treatment assessment (κ = 1.0, P = 0). There was good-excellent concordance in SUV max and mean between modalities across timepoints. Minimum calculated radiation patient effective dose saving was 54% between the two modalities per scan. CONCLUSION: With high concordance in disease site identification, staging and response assessment, PET/MR is a potentially viable alternative to PET/CT in lymphoma that minimises radiation exposure.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".