Spectrum of CT Findings in Thoracic Extranodal Non-Hodgkin Lymphoma
Bibliographic record
Abstract
Non-Hodgkin lymphoma (NHL) frequently manifests in extranodal structures in the chest, often in the form of secondary involvement but occasionally as primary disease. Because staging and treatment are affected by the presence of extranodal disease at imaging, radiologists’ interpretation and management of suspicious findings are critical to patient care. Unfortunately, owing to considerable imaging overlap with other diseases, primary extranodal lymphoma is difficult to diagnose with imaging alone. Radiologists should have a heightened degree of suspicion in patients at risk (including patients with immune compromise, autoimmune diseases, or a history of stem cell or solid organ transplant) or with particular imaging appearances (including the vertebral wraparound sign, nonresolving consolidation, an infiltrative soft-tissue mass, and lesions demonstrating vascular encasement without invasion). For patients with known NHL, positron emission tomography/computed tomography (PET/CT) using fluorine 18 (18F)–labeled fluorodeoxyglucose (FDG) is now preferred for routine staging in most cases. CT remains heavily used, and identification of subtle extranodal involvement with CT can be improved with use of intravenous contrast material and careful review of multiplanar images. Pericardial effusion, pleural soft tissue (even when mild), mass-like consolidation, perilymphatic nodularity, and new lytic bone lesions are particularly suggestive of secondary involvement in a patient with known NHL. Magnetic resonance imaging is a helpful problem-solving tool when equivocal findings would change staging and treatment. This comprehensive review illustrates the spectrum of CT manifestations of extranodal NHL in the chest, including the pleura, lung, airways, heart, pericardium, esophagus, chest wall, and breast. ©RSNA, 2017
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 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".