Predictive intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) parameters in the staging of fibrosis in hepatitis B patients

IVIM-DWI, particularly the <i>D</i>, <i>D*</i>, and ADC parameters, is an adjunctive non-invasive alternative to biopsy in the staging of HBV-related liver fibrosis, especially for the prediction of advanced fibrosis.

Authors

Institutions

Publication Details

Journal
Polish Journal of Radiology
Published
2025-02-07
DOI
https://doi.org/10.5114/pjr/199686
Citations
1
Primary Topic
MRI in cancer diagnosis
Type
article
Field-Weighted Citation Impact
1.36
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predictive intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) parameters in the staging of fibrosis in hepatitis B patients

Fatma Kulalı, İlkay Tosun, Sevde Nur Emir, Yaşar Bükte
1 citations
Polish Journal of Radiology
MRI in cancer diagnosis
1.36
article

Predictive intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) parameters in the staging of fibrosis in hepatitis B patients

Fatma Kulalı, İlkay Tosun, Sevde Nur Emir, Yaşar Bükte
article en
1 citations

Abstract

IVIM-DWI, particularly the <i>D</i>, <i>D*</i>, and ADC parameters, is an adjunctive non-invasive alternative to biopsy in the staging of HBV-related liver fibrosis, especially for the prediction of advanced fibrosis.

Polish Journal of RadiologyVol. 90
Ümraniye Eğitim ve Araştırma Hastanesi (TR), Sağlık Bilimleri Üniversitesi (TR)
Good health and well-being
Openalex Percentile: Top 23%
MRI in cancer diagnosis
1.36
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.