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Record W2272378317 · doi:10.2214/ajr.15.14932

Comparison of Contrast-Enhanced Multiphase Renal Protocol CT Versus MRI for Diagnosis of Papillary Renal Cell Carcinoma

2016· article· en· W2272378317 on OpenAlexaff
Marc Dilauro, Matthew Quon, Matthew D. F. McInnes, Maryam Vakili, Andrew D. Chung, Trevor A. Flood, Nicola Schieda

Bibliographic record

VenueAmerican Journal of Roentgenology · 2016
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsUniversity of OttawaOttawa Hospital
Fundersnot available
KeywordsMedicinePapillary renal cell carcinomasRenal cell carcinomaContrast (vision)RadiologyIntravenous contrastProtocol (science)Nuclear medicineComputed tomographyInternal medicinePathology

Abstract

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OBJECTIVE: The objective of this study was to compare contrast-enhanced (CE) CT with MRI for the diagnosis of papillary renal cell carcinoma (pRCC). MATERIALS AND METHODS: Between 2006 and 2013, a total of 27 pRCCs were assessed using CECT or CE-MRI. A blinded radiologist placed ROIs that measured attenuation on unenhanced CT; corticomedullary and nephrographic phase CECT images, with an attenuation difference of 20 HU or more denoting enhancing lesions, 10-19 HU indicating indeterminate findings, and less than 10 HU denoting nonenhancing lesions. MRI enhancement ratios were calculated as follows: (signal intensity on gadolinium-enhanced image minus signal intensity) / (signal intensity on unenhanced image × 100) for phase 1 (acquired at 30 s), phase 2 (acquired at 70 s), and phase 3 (acquired at 180 s), where a difference of 15% or more denoted enhancement. Two additional blinded radiologists qualitatively assessed tumor margin, homogeneity, and calcification with the use of CT, and they also assessed enhancement with the use of subtraction MRI. A fourth radiologist established consensus. Twenty consecutive hemorrhagic/proteinaceous cysts served as a control group. Statistical analyses were performed using a chi-square test and multivariate regression. RESULTS: There was no statistically significant difference in patient age (p = 0.22), patient sex (p = 0.36), or tumor size (p = 0.29), when pRCCs were compared with hemorrhagic/proteinaceous cysts. On unenhanced CT, attenuation of pRCCs (mean ± SD, 35.7 ± 12.9 HU; range, 19-66 HU) was similar to that of hemorrhagic/proteinaceous cysts (mean, 38.9 ± 16.9; range, 8-71 HU) (p = 0.48). A total of 51.9% of pRCCs (14/27) had either absent or indeterminate enhancement on corticomedullary phase CECT images (mean attenuation difference, 23.2 ± 20.3 HU; range, 6-105 HU), and 14.8% of pRCCs (4/27) had indeterminate enhancement on nephrographic phase CECT images (mean attenuation difference, 36.4 ± 24.9; range, 10-128 HU). No pRCC was nonenhancing on nephrographic phase CECT. Qualitatively, pRCCs were more heterogeneous (80% vs 45%; p = 0.02; κ = 0.24), irregular (50% vs 5%; p < 0.001; κ = 0.21), and calcified (25% vs 0%; p = 0.004; κ = 0.67), with overlap existing between hemorrhagic/proteinaceous cysts. On CE-MRI, all pRCCs were quantitatively enhanced by phase 2 (95.4 ± 83.1; percentage change in signal intensity ratio, 16-450%) and qualitatively enhanced after consensus review. No hemorrhagic/proteinaceous cyst enhanced on MRI when quantitative or subjective analysis was performed. CONCLUSION: A small number of pRCCs have indeterminate enhancement when renal protocol CT is used. Heterogeneity, irregular margins, and calcification are suggestive diagnostic features; however, quantitative and qualitative CE-MRI can accurately differentiate hemorrhagic/proteinaceous cysts from pRCC.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.045
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.034
GPT teacher head0.339
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations62
Published2016
Admission routes1
Has abstractyes

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