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Record W2474628354 · doi:10.1055/s-0042-106652

Hepatic Epiteloid Hemangioendothelioma, a Diagnosis to keep in mind when finding Incidentalomas

2016· article· en· W2474628354 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUltrasound International Open · 2016
Typearticle
Languageen
FieldMedicine
TopicVascular Tumors and Angiosarcomas
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHemangioendotheliomaLiver transplantationVEGF receptorsHepatic tumorPathologyTransplantationInternal medicine

Abstract

fetched live from OpenAlex

Introduction Hepatic Epitheloid Hemangioendothelioma (HEH) is considered a rare tumor with vascular origins that has an overexpression of vascular endothelial growth factor (VEGF) and its receptors VEGFR (Weiss SW, Enzinger FM. Cancer 1982 Sept; 50(5): 970–981). Until now, there has been no standardized treatment for this pathology, the only suitable treatment being surgery, including liver resection, liver transplantation, or considering recent studies, transcatheter arterial chemoembolization (Mehrabi A et al. Cancer 2006 Nov; 107: 2108-2121; Cardinal J et al. Arch Surg. 2009; 144: 1035–1039). The evolution of a HEH is unpredictable. Sometimes the tumor has a quiet and stable course but it can also evolve aggressively and become metastatic (Sangro B et al. Rare Tumors 2012 Apr; 4(2): e34). The diagnosis of HEH is established first through imaging methods; it is shown as an hypoechoic tumor on ultrasonography (Lyburn ID et al. American Journal of Roentgenology 2003; 180: 1359-1364), with low density on CT, and on MRI usually exhibits low signal intensity on T1 weighted images and high signal intensity on T2 weighted images (Salech F et al. Ann Hepatol. 2011; 99–102, Ros LH et al. Canadian Association of Radiologists Journal. 1999; 387–389; Kehagias DT et al. Hepato-Gastroenterology. 2000; 1711–1713). The imaging findings of HEH have some typical features but have a size-dependent pattern with contrast enhancement, on both CT and MRI images (Lisha Z, et al. BMC Gastroenterol. 2015; DOI: doi: 10.1186/s12876-015-0299-x). HEH exhibits great heterogeneity regarding the imaging findings (Lyburn ID et al. American Journal of Roentgenology. 2003 May; vol.180: 1359–1364). Studies show that it can appear as a single or multiple avascular masses with calcification, and can involve the entire liver (den Bakker MA et al. Pathol Res Pract 1998; 194; Issue 3: 194–198; EH, Rha SE, Lee YJ et al. Abdom Imaging. 2015 Mar; 40(3): 500–509). Some imaging suggestions have been proposed in order to improve diagnostic accuracy, such as the retraction sign (capsule retraction of the liver, near the lesion) (Miller WJ et al. American Journal of Roentgenology. 1992; 159: 53–57). Another is the halo sign, which is related to the i.v administration of contrast medium (a hyperintense layer between the hypointense center and periphery) ( Linand J, Ji Y. Hepatobiliary and Pancreatic Diseases International. 2010; 154–8), even though HEH is often misdiagnosed as being a metastatic tumor. In this report we shall present a case of a young woman diagnosed with multiple liver tumors that proved to be HEH. We shall likewise discuss related imaging aspects.

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.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.026
GPT teacher head0.316
Teacher spread0.290 · 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