IMG-56. Primary tumor type influences anatomical destination in large metastases to the brain and shows a preference for the posterior fossa
Bibliographic record
Abstract
Abstract The “seed and soil” hypothesis has driven considerable interest in understanding the unique influences of the primary tumor microenvironment on ultimate destination. Given their known predilection for CNS metastasis, a significant amount of work has focused on breast and lung cancers–with less attention to other primary types. Moreover, the influence of tumor volume on anatomical distributions within the brain is also unknown. As such, data regarding the characteristics of large metastatic lesions (>2cm) is scarce. We sought to map the anatomic distribution of metastases to the brain for multiple primary sites of origin for large metastatic lesions (>2cm) treated with stereotactic radiosurgery. 1218 lesions from 619 patients were obtained from a large retrospectively collected database for individuals undergoing treatment with stereotactic radiosurgery (SRS). Lesion centroids were calculated from T1 weighted post-contrast imaging and their precise locations on a template brain obtained and displayed (Montreal Neurological Institute Atlas (MNI305)). Expected metastatic rates were calculated based on relative region volume as a percentage of total brain volume. Metastatic lesions measuring at least 2 cm in one or more dimensions were included. Six different primary tumor types were highlighted: gastrointestinal (esophageal, colorectal, gastric, etc; 64 lesions), lung (non-small cell; 319 lesions), lung (small cell; 79 lesions), melanoma (281 lesions), breast (276 lesions), and renal (107 lesions). Breast, GI, and lung (small cell and non-small cell) cancers were identified at a greater-than-expected proportion in the posterior fossa (based on relative volume). Melanoma lesions appeared underrepresented in the posterior fossa. Metastases from renal cancer appeared overrepresented in the temporal lobe. Large metastases have an overall predilection for the posterior fossa. An infratentorial preference may suggest unique characteristics of the posterior fossa including arterial supply, venous drainage, or the unique cytoarchitecture of the cerebellum and brain stem. Metastatic melanoma appeared less likely to be in the posterior fossa. Metastatic renal lesions showed a preference for the temporal lobe.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.005 | 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".