AUTHOR=Liang Qiang , Li Qiang , Liu Xianwang , Shao Shuqi , Pan Yawen , Wang Hongyu 

TITLE=Noninvasive prediction of Ki-67 expression level in IDH-wildtype glioblastoma using MRI histogram analysis: comparison and combination of MRI morphological features

JOURNAL=Frontiers in Oncology

VOLUME=Volume 15 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2025.1577816

DOI=10.3389/fonc.2025.1577816

ISSN=2234-943X

ABSTRACT=PurposeTo assess and compare the effectiveness of magnetic resonance imaging (MRI) morphological features and MRI histogram analysis in noninvasively predicting Ki-67 expression levels in patients with IDH-wildtype glioblastoma.MethodsForty-six cases of IDH-wildtype glioblastoma with measured Ki-67 expression levels from January 2022 to July 2024 were retrospectively collected. They were divided into Ki-67 low-level expression group (Ki-67<20%, n=20) and Ki-67 high-level expression group (Ki-67≥20%, n=26) according to Ki-67 expression level. MRI morphological features were assessed and recorded. MRI histogram analysis were performed on contrast-enhanced T1-weighted images. Differences between these parameters were compared between the two groups. The diagnostic performance was assessed by the area under the receiver operating characteristic curve (AUC). Spearman correlation was used to evaluate the relationship between histogram parameters and Ki-67 expression level.ResultsHemorrhage was more prone to occur in the Ki-67 high-level expression group (P=0.017). The min, P01, P50, and P75 of IDH-wildtype glioblastoma Ki-67 high-level expression group were higher than those of the Ki-67 low-level expression group (P<0.00357). There was a significant positive correlation between the min (r=0.774), P01 (r=0.729), P50 (r=0.625), P75 (r=0.591), and Ki-67 expression level (P<0.05). The optimal diagnostic performance was obtained by combining MRI morphological features and histogram parameters, with an AUC of 0.867.ConclusionBoth MRI morphological features and histogram parameters could predict the Ki-67 expression level in IDH-wildtype glioblastoma, and the combined model integrating MRI morphological features and histogram parameters can be an excellent imaging biomarker for noninvasively predicting Ki-67 expression levels in patients with IDH-wildtype glioblastoma.