Evidence map›Paper›PMID 29122287›Full record

ArticleOphthalmology2018

Radiologic and Histopathologic Correlation of Different Growth Patterns of Metastatic Uveal Melanoma to the Liver.

Albert Liao, Pardeep Mittal, David H Lawson, Jenny J Yang, Eszter Szalai, Hans E Grossniklaus

Abstract read
In one paragraph

Article in Ophthalmology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.6field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 17 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Albert LiaoDepartment of Ophthalmology, Emory University School of Medicine, Atlanta, Georgia.
Pardeep MittalDepartment of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia.
David H LawsonDepartment of Hematology and Medical Oncology, Winship Cancer Institute, Emory University School of Medicine, Atlanta, Georgia.
Jenny J YangDepartment of Chemistry, Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, Georgia.
Eszter SzalaiDepartment of Ophthalmology, Emory University School of Medicine, Atlanta, Georgia.
Hans E GrossniklausDepartment of Ophthalmology, Emory University School of Medicine, Atlanta, Georgia; Department of Pathology, Emory University School of Medicine, Atlanta, Georgia. Electronic address: ophtheg@emory.edu.
Emory University · USGeorgia State University · US

Funding

P30-Core Grant for Vision Research Core CP30EY006360 · NEI · EMORY UNIVERSITY · PI BOATRIGHT, JEFFREY H · 1986 to 2025
$15.3M
Noninvasive Contrast Enhanced Early Detection of Melanoma Liver MetastasisR42CA183376 · NCI · INLIGHTA BIOSCIENCES, LLC · PI YANG, JENNY J. · 2017 to 2019
$2.0M
Mechanisms of Action for KCN1 in the Control of Uveal Melanoma MetastasisR01CA176001 · NCI · EMORY UNIVERSITY · PI GROSSNIKLAUS, HANS E., VAN MEIR, ERWIN G. · 2014 to 2018
$1.7M
Discovery of chemical probes for uveal melanomaR01CA180805 · NCI · EMORY UNIVERSITY · PI GROSSNIKLAUS, HANS E., VAN MEIR, ERWIN G. · 2013 to 2015
$1.6M
NCI NIH HHS R01 CA176001NCI NIH HHS R01 CA180805NCI NIH HHS R42 CA183376NEI NIH HHS P30 EY006360
6 · The paper itself

Abstract

purposeThe purpose of this study was to correlate magnetic resonance imaging (MRI) radiographic results with histopathologic growth patterns of metastatic uveal melanoma (UM) to the liver.

designClinicopathologic correlation.

participantsPatients with metastatic UM to the liver.

methodsA retrospective review of MRI images of patients with metastatic UM to the liver at a single institution between 2004 and 2016 was performed. The MRI growth patterns were classified as nodular or diffuse. The histopathologic findings of core liver biopsies of liver metastases identified by needle localization in a subset of these patients were reviewed. The core samples were evaluated by routine light microscopy, including immunohistochemical/immunofluorescent staining for CD31, CD105, and HMB45, and classified as exhibiting an infiltrative or nodular growth pattern.

main outcome measuresMagnetic resonance images and core biopsy findings.

resultsA total of 32 patients were identified with metastatic UM to the liver that was imaged by MRI, and 127 lesions were identified. A total of 46 lesions were classified by MRI as infiltrative and 81 as nodular. There were 9 needle-localized core biopsies that corresponded to MRI of metastatic lesions. Of these 9 lesions, 3 that were classified as infiltrative on MRI exhibited stage I infiltrative histologic growth patterns; of the remaining 6 that were classified as nodular by MRI, 5 histologically demonstrated stage II or stage III infiltrative growth patterns and 1 histologically demonstrated a nodular growth pattern.

conclusionsMagnetic resonance imaging of hepatic infiltrative growth patterns of metastatic UM corresponded to stage I histologic infiltrative growth in the sinusoidal spaces, whereas MRI nodular growth patterns corresponded to stage II/III histologic infiltrative growth that replaced the hepatic lobule or histologic nodular growth in the portal triad that effaced adjacent hepatic parenchyma.

Indexed as

Biomarkers, TumorBiopsyEndoglinFemaleFluorescent Antibody Technique, Indirectgp100 Melanoma AntigenHumansImmunohistochemistryLiver NeoplasmsMagnetic Resonance ImagingMaleMelanomaMelanoma-Specific AntigensMiddle AgedPlatelet Endothelial Cell Adhesion Molecule-1Retrospective StudiesBiomarkers, TumorEndoglinENG protein, humangp100 Melanoma AntigenMelanoma-Specific AntigensPlatelet Endothelial Cell Adhesion Molecule-1PMEL protein, human

Identifiers

PMID29122287
PMCPMC6211288
OpenAlexW2767338021

What Socratic holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.