High-Frequency Sonographic Patterns of the Spleen in Children
Bibliographic record
Abstract
PURPOSE: To retrospectively evaluate the normal sonographic appearance of splenic parenchyma in children of various ages with high-frequency transducer sonography. MATERIALS AND METHODS: Research ethics committee board approval was obtained, with waiver of informed consent. We evaluated in vivo sagittal and transverse sonograms of spleens obtained with 13-MHz linear-array transducers in 100 children (age range, 1 day to 17 years) with clinically diagnosed disease that did not affect the lymphoid system. Three radiologists working in consensus defined the grading system for the splenic parenchyma. Thereafter, these same radiologists graded the sonographic reticulonodular pattern independently as granular, mild, or marked. These grades were cross correlated with clinical data by using logistic regression analysis and chi(2) tests. Sonographic measurements of the splenic parenchyma in nine pediatric cadavers separate from the in vivo cohort of the study were compared with those of corresponding histologic slices by means of linear correlation. RESULTS: Both grade 2 and grade 3 patterns occurred more frequently in children older than 1 year but no older than 5 years, whereas grade 1 pattern occurred most frequently in neonates (P < .001). As patients' age (odds ratio, 1.6; P < .001) and splenic dimensions (odds ratio, 3.1; P < .001) increased, the frequency with which the reticulonodular pattern was classified as either grade 2 or grade 3 increased. No association was noted between sonographic patterns and body mass index (P = .85) or sex (P = .07). The parenchymal nodules graded as 2 or 3 on sonograms correlated well with the presence of lymphoid follicles (white pulp) at histologic analysis (r = .71, P = .03). CONCLUSION: High-frequency transducer sonography of the spleen in children can demonstrate normal echo patterns that should not be misinterpreted as indicative of disease.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".