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Record W2913143244 · doi:10.1002/jmri.26542

Renal and adrenal masses containing fat at MRI: Proposed nomenclature by the society of abdominal radiology disease‐focused panel on renal cell carcinoma

2019· article· en· W2913143244 on OpenAlexaff
Nicola Schieda, Matthew S. Davenport, Iván Pedrosa, Atul B. Shinagare, Hersh Chandarana, Nicole E. Curci, Ankur M. Doshi, Gary M. Israel, Erick M. Remer, Jane Wang, Stuart G. Silverman

Bibliographic record

VenueJournal of Magnetic Resonance Imaging · 2019
Typearticle
Languageen
FieldMedicine
TopicMRI in cancer diagnosis
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersNational Cancer Institute
KeywordsMedicineLipomaArtifact (error)VoxelRenal cell carcinomaIntensity (physics)Magnetic resonance imagingPathologyRadiologyInternal medicineBiologyNeurosciencePhysics

Abstract

fetched live from OpenAlex

This article proposes a consensus nomenclature for fat‐containing renal and adrenal masses at MRI to reduce variability, improve understanding, and enhance communication when describing imaging findings. The MRI appearance of "macroscopic fat" occurs due to a sufficient number of aggregated adipocytes and results in one or more of: 1) intratumoral signal intensity (SI) loss using fat‐suppression techniques, or 2) chemical shift artifact of the second kind causing linear or curvilinear India‐ink (etching) artifact within or at the periphery of a mass at macroscopic fat–water interfaces. "Macroscopic fat" is most commonly observed in adrenal myelolipoma and renal angiomyolipoma (AML) and only rarely encountered in other adrenal cortical tumors and renal cell carcinomas (RCC). Nonlinear noncurvilinear signal intensity loss on opposed‐phase (OP) compared with in‐phase (IP) chemical shift MRI (CSI) may be referred to as "microscopic fat" and is due to: a) an insufficient amount of adipocytes, or b) the presence of fat within tumor cells. Determining whether the signal intensity loss observed on CSI is due to insufficient adipocytes or fat within tumor cells cannot be accomplished using CSI alone; however, it can be inferred when other imaging features strongly suggest a particular diagnosis. Fat‐poor AML are homogeneously hypointense on T 2 ‐weighted (T 2 W) imaging and avidly enhancing; signal intensity loss at OP CSI is uncommon, but when present is usually focal and is caused by an insufficient number of adipocytes within adjacent voxels. Conversely, clear‐cell RCC are heterogeneously hyperintense on T 2 W imaging and avidly enhancing, with the signal intensity loss observed on OP CSI being typically diffuse and due to fat within tumor cells. Adrenal adenomas, adrenal cortical carcinoma, and adrenal metastases from fat‐containing primary malignancies also show signal intensity loss on OP CSI due to fat within tumor cells and not from intratumoral adipocytes. Level of Evidence : 5 Technical Efficacy Stage : 3 J. Magn. Reson. Imaging 2019;49:917–926.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.093
Threshold uncertainty score0.790

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.240
Teacher spread0.228 · 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 teacher head, 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".

Quick stats

Citations48
Published2019
Admission routes1
Has abstractyes

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