Predictive value of ADC histogram analysis in 2 cm peritumoral edema zone for spatial pattern of recurrence in glioblastoma
Clinical Medicine|更新时间:2026-01-09
|
Predictive value of ADC histogram analysis in 2 cm peritumoral edema zone for spatial pattern of recurrence in glioblastoma
Journal of Army Medical UniversityVol. 45, Issue 4, Pages: 318-325(2023)
作者机构:
1.400042 重庆,陆军特色医学中心放射科,重庆市影像医学与核医学临床研究中心
2.400042 重庆,陆军特色医学中心神经外科
作者简介:
基金信息:
the National Natural Science Foundation for Young Scholars of China(81701661);the Clinical Medical Research Talent Project of Army Medical University(2019XLC3049);the Project of Science and Technology Plan of Chongqing Clinical Research Centre of Imaging and Nuclear Medicine(CSTC2015YFPT-gcjsyjzx0175)
Linlan ZENG, Hanwei WANG, Jing TIAN, et al. Predictive value of ADC histogram analysis in 2 cm peritumoral edema zone for spatial pattern of recurrence in glioblastoma[J]. Journal of Army Medical University, 2023, 45(4): 318-325.
DOI:
Linlan ZENG, Hanwei WANG, Jing TIAN, et al. Predictive value of ADC histogram analysis in 2 cm peritumoral edema zone for spatial pattern of recurrence in glioblastoma[J]. Journal of Army Medical University, 2023, 45(4): 318-325. DOI: 10.16016/j.2097-0927.202211009.
Predictive value of ADC histogram analysis in 2 cm peritumoral edema zone for spatial pattern of recurrence in glioblastoma
=22)。选取术前轴位MRI增强图像上肿瘤强化最大层面对应的ADC图像层面,采用Mazda软件沿瘤周水肿2 cm范围边缘勾画提取感兴趣区(region of interest,ROI)进行灰度直方图分析,对提取的特征参数进行统计学分析并应用受试者工作特征曲线计算曲线下面积(area under the curve,AUC),评估其诊断效能。
To evaluate the predictive value of apparent diffusion coefficient (ADC) histogram in preoperative magnetic resonance imaging (MRI) of the 2 cm peritumoral edema zone for spatial pattern of recurrence in IDH wild-type glioblastoma (GB).
Methods
2
A case-control study was performed on 50 patients with IDH wild-type GB treated with standard protocol
diagnosed by pathology as tumor recurrence and accepted regular follow-up MRI in Department of Neurosurgery of Army Medical Center of PLA from January 2012 to December 2021. The postoperative spatial recurrence patterns were divided into the local recurrence group (
n
=28) and the non-local recurrence group (
n
=22) ac
cording to whether the distance between the recurrence foci and the operative cavity was more than 2 cm or not. According to the maximum level of tumor enhancement in axial planes of enhanced MRI
the corresponding level of ADC images were selected. Mazda software was used to outline the region of interest (ROI) along the edge of the 2 cm range of peritumoral edema for histogram analysis. The histogram parameters of the 2 groups with different spatial patterns of recurrence were statistically analyzed
and the area under the curve (AUC) was obtained by receiver operating characteristic curve to evaluate the diagnostic efficacy.
Results
2
Among the 50 patients with recurrent GB
progression-free survival (PFS) and overall survival (OS) in the local recurrence group were longer than those in the non-local recurrence group (median PFS: 6.6
vs
4.6 months; median OS: 15.4
vs
12.4 months)
and the differences were statistically significant(PFS: log-rank
Chi
-square=4.325
P
=0.038; OS: log-rank
Chi
-square=4.022
P
=0.045). Variance
kurtosis and Perc.90% of the 9 features extracted from ADC histogram were statistically significant differences between the 2 groups (
P
<
0.05). Variance had the best diagnostic efficiency (AUC: 0.804
sensitivity: 75.00%
specificity: 81.82%). Among the 4 multivariate logistic regression models constructed based on the variance
kurtosis and Perc.90%
the model constructed by the combination of variance
kurtosis and Perc.90% had the best diagnostic efficiency (AUC: 0.878
sensitivity: 78.57%
specificity: 86.36%).
Conclusion
2
The characteristic parameters of the preoperative ADC histogram in peritumoral edema zone can be used as an imaging marker to predict the different spatial patterns of postoperative recurrence in patients with IDH wild-type GB.
关键词
Keywords
references
MCKINNON C, NANDHABALAN M, MURRAY S A, et al . Glioblastoma: clinical presentation, diagnosis, and management[J ] . Br Med J, 2021, 374: n1560. DOI: 10.1136/bmj.n1560.
QIU J, DENG K X, WANG P, et al . Application of diffusion kurtosis imaging to the study of edema i n solid and peritumoral areas of glioma[J ] . Magn Reson Imaging, 2022, 86: 10-16. DOI: 10.1016/j.mri.2021.11.001.
KHALAFALLAH A M, RAKOVEC M, BETTEGOWDA C, et al . A crowdsourced consensus on supratotal resection versus gross total resection for anatomically distinct primary glioblastoma[J ] . Neurosurgery, 2021, 89(4): 712-719. DOI: 10.1093/neuros/nyab257.
CANTIDIO F S, GIL G O B, QUEIROZ I N, et al . Glioblastoma—treatment and obstacles[J ] . Rep Pract Oncol Radiother, 2022, 27(4): 744-753. DOI: 10.5603/RPOR.a2022.0076.
LIU M M, HE Y X. Research progress of magnetic resonance imaging in predicting postoperative recurrence patterns of high-grade gliomas[J]. Chin J Magn Reson Imaging, 2021, 12(12): 99-101. DOI: 10.12015/issn.1674-8034.2021.12.023.
PIPER R J, SENTHIL K K, YAN J L, et al . Neuroimaging classification of progression patterns in glioblastoma: a system- atic review[J ] . J Neurooncol, 2018, 139(1): 77-88. DOI: 10.1007/s11060-018-2843-3.
JIANG H H, YU K F, LI M X, et al . Classification of progression patterns in glioblastoma: analysis of predictive factors and clinical implications[J ] . Front Oncol, 2020, 10: 590648. DOI: 10.3389/fonc.2020.590648.
TOH C H, LIAU C T, WEI K C, et al . Baseline multicentric tumors, distant recurrences and leptomeningeal dissemination predict poor survival in patients with recurrent glioblastomas receiving bevacizumab[J ] . J Neurooncol, 2019, 142(1): 149-159. DOI: 10.1007/s11060-018-03075-x.
ZHOU B, TONG H P, CHEN X, et al . Value of multimodal MRI in evaluation of tissue factor expression in glioblastoma[J ] . J Third Mil Med Univ, 2020, 42(3): 307-313. DOI: 10.16016/j.1000-5404.201909037.
LEWIS M A, GANESHAN B, BARNES A, et al . Filtration-histogram based magnetic resonance texture analysis (MRTA) for glioma IDH and 1p19q genotyping[J ] . Eur J Radiol, 2019, 113: 116-123. DOI: 10.1016/j.ejrad.2019.02.014.
GAO A K, ZHANG H T, YAN X, et al . Whole-tumor histo- gram analysis of multiple diffusion metrics for glioma ge notyping[J ] . Radiology, 2022, 302(3): 652-661. DOI: 10.1148/radiol.210820.
ZHANG H W, LYU G W, HE W J, et al . Differential diagnosis of central lymphoma and high-grade glioma: dynamic contrast-enhanced histogram[J ] . Acta Radiol, 2020, 61(9): 1221-1227. DOI: 10.1177/0284185119896519.
HU Y, CHEN Y, WANG J, et al . Non-invasive estimation of glioma IDH 1 mutation and VEGF expression by histogram analysis of dynamic contrast-enhanced MRI[J ] . Front Oncol, 2020, 10: 593102. DOI: 10.3389/fonc.2020.593102..
LOUIS D N, PERRY A, WESSELING P, et al . The 2021 WHO classification of tumors of the central nervous system: a summary[J ] . Neuro Oncol, 2021, 23(8): 1231-1251. DOI: 10.1093/Neuonc/noab106.
ELLINGSON B M, WEN P Y, CLOUGHESY T F. Modified criteria for radiographic response assessment in glioblastoma clinical trials[J]. Neurotherapeutics, 2017, 14(2): 307-320. DOI: 10.1007/s13311-016-0507-6.
BLYSTAD I, WARNTJES J B M, SMEDBY Ö, et al . Quantitative MRI for analysis of peritumoral edema in malignant gliomas[J ] . PLoS One, 2017, 12 (5): e0177135. DOI: 10.1371/journal.pone.0177135.
VELÁSQUEZ C, MANSOURI S, MORA C, et al . Mole cular and clinical insights into the invasive capacity of glioblastoma cells[J ] . J Oncol, 2019, 2019: 1740763. DOI: 10.1155/2019/1740763.
TU Z W, XIONG H F, QIU Y, et al . Limited recurrence distance of glioblastoma under modern radiotherapy era[J ] . BMC Cancer, 2021, 21(1): 720. DOI: 10.1186/s12885-021-08467-3.
AUER T A, KERN M, FEHRENBACH U, et al . T2 mapping of the peritumoral infiltration zone of glioblastoma and anaplastic astrocytoma[J ] . Neuroradiol J, 2021, 34(5): 392-400. DOI: 10.1177/1971400921989325.
WANG J, HU C H, WANG X M. ADC-based gray histogram analysis for differentiating between solitary fibrous tumor/hemangiopericytoma and hemangioma meningioma[J]. Radiol Pract, 2020, 35(2): 154-158. DOI: 10.13609/j.cnki.1000-0313.2020.02.006.
STADLBAUER A, KINFE T M, EYVPOGLU I, et al . Tissue hypoxia and alterations in microvascular architecture predict glioblastoma recurrence in humans[J ] . Clin Cancer Res, 2021, 27(6): 1641-1649. DOI: 10.1158/1078-0432.CCR-20-3580.
FERRACCI F X, MICHAUD K, DUFFAU H. The landscape of postsurgical recurrence patterns in diffuse low-grade gliomas[J]. Crit Rev Oncol, 2019, 138: 148-155. DOI: 10.1016/j.critrevonc.2019.04.009.
LIU S Y, LIU S Z, LIN Z X, et al . Influence of features of peritumoral brain edema in MRI of brain glioma on recurrence sites and morphology after total resection[J ] . Int Med Health Guid News, 2017, 23(19): 2967-2969, 2974. DOI: 10.3760/cma.j.issn.1007-1245.2017.19.002.