Multimodality Imaging Characteristics of the Common Renal Cell Carcinoma Subtypes: An Analysis of 544 Pathologically Proven Tumors
Bibliographic record
Abstract
OBJECTIVES: The objective of this study was to define the characteristic imaging appearances of the common renal cell carcinoma (RCC) subtypes. MATERIALS AND METHODS: The Institutional Review Board approval was obtained for this HIPAA-compliant retrospective study, and informed consent was waived. 520 patients (336 men, 184 women; age range, 22-88 years) underwent preoperative cross-sectional imaging of 544 RCCs from 2008 to 2013. The imaging appearances of the RCCs and clinical information were reviewed. Data analysis was performed using parametric and nonparametric statistics, descriptive statistics, and receiver operating characteristic analysis. RESULTS: < 0.001) in several imaging parameters such as tumor margins, tumor consistency, tumor homogeneity, the presence of a central stellate scar, T2 signal intensity, and the degree of tumor enhancement. Low T2 signal intensity on magnetic resonance imaging (MRI) allowed differentiation of papillary RCC from clear cell and chromophobe RCCs with 90.9% sensitivity and 93.1% specificity. A tumor-to-cortex ratio ≥1 on the corticomedullary phase had 98% specificity for clear cell RCC. CONCLUSION: The T2 signal intensity of the tumor on MRI and its degree of enhancement are useful imaging parameters for discriminating between the RCC subtypes while gross morphological findings offer additional value in RCC profiling.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".