Centrally Infiltrating Renal Masses on CT: Differentiating Intrarenal Transitional Cell Carcinoma From Centrally Located Renal Cell Carcinoma
Bibliographic record
Abstract
OBJECTIVE: The objective of our study was to retrospectively determine the accuracy of CT for differentiating intrarenal transitional cell carcinoma (TCC) from centrally located renal cell carcinoma (RCC) and to define the most discriminating diagnostic CT features. MATERIALS AND METHODS: CT studies of 98 pathologically proven central renal tumors (64 centrally located RCCs and 34 intrarenal TCCs) seen over 5 years at three university hospitals were reviewed by five specialty-trained radiologists who were blinded to the final diagnosis. Multiple CT features and global impression were graded on a 4-point score. The sensitivity and specificity of each feature and of global assessment were calculated and compared using receiver operating characteristic (ROC) analysis. Interobserver agreement (kappa values) was also calculated for each parameter. RESULTS: All five readers recognized intrarenal TCCs with a high diagnostic accuracy (sensitivity, 90%; specificity, 90%; area under ROC curve [AUC], 0.80-0.95 for global assessment) with moderate-to-excellent interobserver agreement (κ = 0.72-1). Six CT features were most diagnostically specific for identifying intrarenal TCCs: tumor centered within the collecting system; focal filling defect in the pelvicalyceal system; preserved renal shape; absence of cystic or necrotic change; homogeneous tumor enhancement; and tumor extension toward the ureteropelvic junction (sensitivity, 68-82%; specificity, 79-89%; AUC, 0.75-0.84). There was moderate-to-good agreement among the readers over all these features (κ = 0.44-0.69). CONCLUSION: Intrarenal TCC can be recognized with a high accuracy on CT; global impression showed the best diagnostic performance. A solid, homogeneously enhancing mass that is centered on the collecting system and extends toward the ureteropelvic junction combined with a focal pelvicalyceal filling defect and preserved renal outline is more likely to be an intrarenal TCC than a centrally located RCC.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".