Imaging in Primary Central Nervous System Lymphoma
Bibliographic record
Abstract
Primary central nervous system (CNS) lymphoma (PCNSL) accounts for approximately 3% of all primary CNS tumors. Congenital or acquired immunodeficiency is the only established risk factor for PCNSL. Rates decreased slightly in the mid-1990s, concordantly with the decreasing rates of AIDS. However, the incidence has been increasing in the elderly immunocompetent population, and this trend seems to be independent of improvements in diagnostic techniques, and of overall trends in the incidence of brain tumors and systemic lymphomas. This study presents our experience with the imaging features of PCNSL. Computed tomography (CT) and magnetic resonance imaging (MRI) findings were reviewed in a series of 38 cases of pathologically proven PCNSL. The incidence rate of PCNSL was higher in men than in women (58% versus 42%). Mean age at presentation was 63 years; 120 lesions were demonstrated in the 38 patients, with a 53% frequency of tumor multiplicity. Both CT and MR mainly showed solitary or multiple well-defined round or oval-shaped mass lesions, typically hyperdense on unenhanced CT scans, iso to hypointense on T2 MR weighted images. These lesions also showed an increased signal intensity on diffusion-weighted images. Virtually all lesions enhanced after intravenous administration of contrastmedium. On (1)H-magnetic resonance spectroscopy ((1)H-MRS) most lesions presented increased Cho/Cr, Cho/NAA and lactate/Cr ratios when compared to normal gray matter. No changes in the imaging presentation have occurred over the past two decades, apart from lesions now being smaller at diagnosis. Our imaging findings are in agreement with the existing literature data and with the reported increasing trend of multifocal tumors. Our epidemiologic results add value to the existing evidence of increasing incidence rates among the immunocompetent elderly population.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".