Evidence map›Paper›PMID 41801380›Full record

ArticleAbdominal radiology (New York)2026

"Liver stiffness variations after locoregional treatment do not predict outcomes in liver cancer: limitations of elastography as a prognostic tool".

Serena Pisoni, Daniel Pérez Enguix, Adrián Picado Bermúdez, José J Martínez-Rodrigo, Luis Martí-Bonmatí

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Article in Abdominal radiology (New York), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Serena PisoniBiomedical Imaging Research Group, Instituto de Investigación Sanitaria La Fe, Valencia, Spain. serena_pisoni@iislafe.es.
Daniel Pérez EnguixDepartment of Radiology, Clinical Area of Medical Imaging, Hospital Universitari i Politècnic La Fe, Valencia, Spain.
Adrián Picado BermúdezDepartment of Radiology, Clinical Area of Medical Imaging, Hospital Universitari i Politècnic La Fe, Valencia, Spain.
José J Martínez-RodrigoDepartment of Radiology, Clinical Area of Medical Imaging, Hospital Universitari i Politècnic La Fe, Valencia, Spain.
Luis Martí-BonmatíBiomedical Imaging Research Group, Instituto de Investigación Sanitaria La Fe, Valencia, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis prospective study evaluates the exploratory value of tumor and liver stiffness, measured pre-operatively by 2D shear wave elastography (2D-SWE), in patients with liver cancer undergoing locoregional therapies, including ablation, transarterial chemoembolization (TACE), and transarterial radioembolization (TARE). The aim is to assess whether stiffness changes occur after treatment and to explore their possible association with clinical outcomes.

methods100 patients with liver cancer eligible for locoregional treatment were enrolled. Tumoral tissue, peritumoral area, and proximal liver tissue stiffness were evaluated by 2D-SWE before treatment and one month afterward. Clinical and radiological data were collected, including tumor response up to 6 months. The final series consisted of 76 patients due to exclusion based on technical limitations in elastography acquisition, inability to undergo treatment, or loss to follow-up. Correlations between stiffness, pathological characteristics, and clinical outcomes were statistically assessed. Subgroup analyses were performed by treatment type but given the sample size, these results should be interpreted with caution and as exploratory.

resultsBaseline tumor stiffness showed no correlation tumor type (p = 0.48) or lesion size (p = 0.35). Tumor stiffness increased after ablation (p = 0.02) and TACE (p = 0.04) but remained stable following TARE (p = 0.69). No significant changes were detected in peritumoral or liver stiffness after treatment. Despite these findings, no significant correlation was found between baseline tumor stiffness (p = 0.72), peritumoral stiffness (p = 0.61), liver stiffness (p = 0.29) and short-term clinical outcomes.

conclusions2D-SWE showed measurable changes in tumor stiffness after locoregional treatments, suggesting a potential role in monitoring tissue alterations. However, no evidence was found to support its ability to predict treatment response or clinical outcomes. These findings should be interpreted as preliminary, and further validation in larger and homogeneous cohorts is needed.

Indexed as

Carcinoma, HepatocellularElasticity Imaging TechniquesLiver NeoplasmsAgedAged, 80 and overChemoembolization, TherapeuticFemaleHumansLiverMaleMiddle AgedPredictive Value of TestsPrognosisProspective StudiesRadioembolization, TherapeuticTreatment OutcomeElastographyHepatocellular carcinomaInterventional oncologyLiver stiffnessLocoregional therapies

Identifiers

PMID41801380

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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.