ORIGINAL RESEARCH article
Front. Oncol.
Sec. Neuro-Oncology and Neurosurgical Oncology
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1577816
Noninvasive prediction of Ki-67 expression level in IDH-wildtype glioblastoma using MRI histogram analysis: comparison and combination of MRI morphological features
Provisionally accepted
- Department of Neurosurgery, Lanzhou University Second Hospital, Lanzhou, China
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Purpose: To 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.Methods: Forty-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. Results: Haemorrhage 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. Conclusion: Both 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.
Keywords: brain tumor, Glioblastoma, Magnetic Resonance Imaging, Histogram analysis, Ki-67
Received: 16 Feb 2025; Accepted: 23 Apr 2025.
Copyright: © 2025 Liang, Li, Liu, Shao, Pan and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Yawen Pan, Department of Neurosurgery, Lanzhou University Second Hospital, Lanzhou, China
Hongyu Wang, Department of Neurosurgery, Lanzhou University Second Hospital, Lanzhou, China
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