Ultrasound Fusion Imaging In Oncohepatology.

The article presents a review of the literature concerning the assessment of the possibilities of ultrasound hybrid imaging methods in oncohepathology. Fusion imaging includes the combined use of computed tomography (CT) or magnetic resonance imaging (MRI) with greyscale ultrasound and contrast-enhanced ultrasound (CEUS). The main areas of application of ultrasound fusion imaging, such as differential diagnosis of liver lesions, navigation for biopsy and for thermal ablation. Fusion imaging in oncohepatology increases the sensitivity of the detection of liver lesions, assesses its structure and predicts the response of treatment

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Publication Details

Journal
Journal of oncology diagnostic radiology and radiotherapy
Published
2025-06-29
DOI
https://doi.org/10.37174/2587-7593-2025-8-2-96-102
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
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article

Ultrasound Fusion Imaging In Oncohepatology.

E. A. Zubareva, Т. Yu. Danzanova, S. N. Berdnikov, П. И. Лепэдату et al.
Journal of oncology diagnostic radiology and radiotherapy
Radiomics and Machine Learning in Medical Imaging
article

Ultrasound Fusion Imaging In Oncohepatology.

E. A. Zubareva, Т. Yu. Danzanova, S. N. Berdnikov, П. И. Лепэдату, G. Т. Sinyukova, Е. В. Ковалева
article en

Abstract

The article presents a review of the literature concerning the assessment of the possibilities of ultrasound hybrid imaging methods in oncohepathology. Fusion imaging includes the combined use of computed tomography (CT) or magnetic resonance imaging (MRI) with greyscale ultrasound and contrast-enhanced ultrasound (CEUS). The main areas of application of ultrasound fusion imaging, such as differential diagnosis of liver lesions, navigation for biopsy and for thermal ablation. Fusion imaging in oncohepatology increases the sensitivity of the detection of liver lesions, assesses its structure and predicts the response of treatment

Journal of oncology diagnostic radiology and radiotherapyVol. 8(2)
Pirogov Russian National Research Medical University (RU)
Openalex Percentile: Top 77%
Radiomics and Machine Learning in Medical Imaging
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