Evidence map›Paper›PMID 36943581›Full record

ArticleMagma (New York, N.Y.)2023

Histopathological graded liver lesions: what role does the IVIM analysis method have?

Mona Bagheri, Farzaneh Ghorbani, Hossein Akbari-Lalimi, Hadi Akbari-Zadeh, Mohsen Asadinezhad, Afshin Shafaghi, Alireza Montazerabadi

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Article in Magma (New York, N.Y.), 2023. 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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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.

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5 · Who and what money

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7 authors.

Mona BagheriDepartment of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Farzaneh GhorbaniDepartment of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Hossein Akbari-LalimiDepartment of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Hadi Akbari-ZadehDepartment of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Mohsen AsadinezhadDepartment of Radiology Technology, School of Paramedical Sciences, Mashhad University of Medical Sciences, Mashhad, Iran.
Afshin ShafaghiCaspian Digestive Disease Research Center, Guilan University of Medical Sciences, Rasht, Iran.
Alireza MontazerabadiDepartment of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran. alireza.montazerabadi@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study aims to investigate three different image processing methods on quantitative parameters of IVIM sequence, as well as apparent diffusion coefficients and simple perfusion fractions, for benign and malignant liver tumors. MATERIALS AND

methodsIVIM images with 8 b-values (0-1000 s/mm

resultsOur results indicate that the image processing method can change statistical comparisons between different groups for each parameter. The D value is the only quantity in this technique that does not depend on the fitting process and can be used as an indicator of comparison between studies (P < 0.05). The most effective method to distinguish liver lesions is the extrapolated f method (first method). This method created a significant difference (P < 0.05) between the perfusion parameters between benign and malignant lesions.

conclusionUsing extrapolated f is the most effective method of distinguishing liver lesions using IVIM parameters. The comparison between groups does not depend on the fitting method only for parameter D.

Indexed as

Brain NeoplasmsLiver NeoplasmsAbdomenDiffusion Magnetic Resonance ImagingHumansImage Processing, Computer-AssistedMotionBenignDiffusionFitting methodIVIMLiverMalignantPerfusion

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