Evidence map›Paper›PMID 42587539›Full record

ReviewDiagnostics (Basel, Switzerland)2026

Tumor or Inflammation? How Multi-Modality Image Fusion and Shear Wave Elastography Can Help Solve the Diagnostic Dilemma.

Efstathios T Detorakis, George Bontzos, Eleni E Drakonaki

Abstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Efstathios T DetorakisDepartment of Ophthalmology, University Hospital of Heraklion, 715 00 Crete, Greece.
George BontzosDepartment of Ophthalmology, University Hospital of Heraklion, 715 00 Crete, Greece.
Eleni E DrakonakiDepartment of Anatomy, University Hospital of Heraklion, 715 00 Crete, Greece.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Differentiating intraocular tumors from inflammatory conditions remains a major diagnostic challenge in ophthalmology, particularly in masquerade syndromes where clinical and imaging features overlap. Despite advances in ocular imaging, no single modality provides sufficient diagnostic specificity. This narrative review synthesizes current evidence on optical imaging modalities, ultrasonography, and elastography, focusing on their complementary roles in intraocular disease characterization, with emphasis on shear wave elastography (SWE) within a multimodal framework. Conventional imaging provides partial insights: OCT and ultrasonography define structural features, while angiographic techniques assess vascular behavior. Elastography adds a biomechanical dimension by enabling in vivo assessment of tissue stiffness. Malignant lesions typically exhibit increased stiffness and heterogeneity, whereas inflammatory processes show more variable profiles, yet overlap exists. Integrating structural, vascular, and biomechanical data improves pattern recognition and diagnostic confidence. A tri-axis fusion model and a practical diagnostic workflow are proposed to support clinical decision-making. Multi-modality image fusion represents a shift toward hybrid multi-dimensional tissue characterization in ophthalmology. The addition of elastography may assist in the differential diagnosis process between intraocular tumors and inflammatory conditions. Further standardization, validation, and integration with artificial intelligence are required for routine clinical implementation.

Indexed as

differential diagnosisintraocular lesionsmasquerade syndromes

Identifiers

PMID42587539
PMCPMC13464794

What OpenQuestion holds

Textmetadata
Read underepoch 390

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 OpenQuestion graph.