Whole-Body Diffusion-Weighted MRI Compared to <sup>18 F</sup> FDG PET/CT in Initial Staging and Therapy Response Assessment of Hodgkin Lymphoma in Pediatric Patients
Bibliographic record
Abstract
Purpose: The aim of our study was to compare whole-body diffusion-weighted MRI (WB-DWI-MRI) to fluoro-2-deoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) in the assessment of initial staging and treatment response in pediatric patients with Hodgkin lymphoma. Materials and Methods: This prospective study comprised 11 children with Hodgkin lymphoma. Whole-body DWI-MRI and FDG-PET/CT were obtained at baseline and after 2 cycles of chemotherapy. Two radiologists measured the apparent diffusion coefficient (ADC) values of the sites of involvement agreed upon in consensus and 1 nuclear medicine physician assessed the PET/CT. Reliability of radiologists’ ratings was assessed by intraclass correlation coefficients (ICC 2,1 ). The sensitivity and positive predictive value (PPV) of DW-MRI relative to PET/CT were calculated for nodal and extranodal sites. The patients were staged according to both modalities. Association of treatment responses was assessed through the Pearson correlation between the ADC ratios and the change standardized uptake value (SUV) between baseline and follow-up. Results: There was good agreement between the raters for nodal and extranodal ADC measurements. The sensitivity and PPV of DW-MRI relative to PET/CT of nodal disease was 0.651 and 1.0, respectively, at baseline, and 0.697 and 0.885 at follow-up. The sensitivity and PPV of extranodal disease were 0.545 and 0.6 at baseline, and 0.167 and 0.333 at follow-up. Diffusion-weighted MRI determined correct tumor stage in 8 of 11 examinations. There was poor correlation between the ADC ratios and the absolute change in SUV between baseline and follow-up (0.348). Conclusion: Our experience showed that WB-DWI-MRI is inferior to PET/CT for initial staging and assessment of treatment response of Hodgkin lymphoma in pediatric patients.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".