Distinguishing glioblastoma progression from treatment-related changes using DTI directionality growth analysis

Author:

van den Elshout R.ORCID,Ariëns B.,Esmaeili M.,Akkurt B.,Mannil M.,Meijer F. J. A.,van der Kolk A. G.,Scheenen T. W. J.,Henssen D.

Abstract

Abstract Background It is difficult to distinguish between tumor progression (TP) and treatment-related abnormalities (TRA) in treated glioblastoma patients via conventional MRI, but this distinction is crucial for treatment decision making. Glioblastoma is known to exhibit an invasive growth pattern along white matter architecture and vasculature. This study quantified lesion development patterns in treated glioblastoma lesions and their relation to white matter microstructure to distinguish TP from TRA. Materials and methods Glioblastoma patients with confirmed TP or TRA with T1-weighted contrast-enhanced and DTI MR scans from two posttreatment follow-up timepoints were reviewed. The contrast-enhancing regions were segmented, and the regions were coregistered to the DTI data. Lesion increase vectors were categorized into two groups: parallel (0–20 degrees) and perpendicular (70–90 degrees) to white matter. FA-values were also extracted. To test for a statistically significant difference between the TP and TRA groups, a Mann‒Whitney U test was performed. Results Of 73 glioblastoma patients, fifteen were diagnosed with TRA, whereas 58 patients suffered TP. TP had a 25.8% (95% CI 24.1%-27.6%) increase in parallel lesions, and TRA had a 25.4% (95% CI 20.9%-29.9%) increase in parallel lesions. The perpendicular increase was 14.7% for TP (95% CI 13.0%-16.4%) and 18.0% (95% CI 13.5%-22.5%) for TRA. These results were not significantly different (p = 0.978). FA value for TP showed to be 0.248 (SD = 0.054) and for TRA it was 0.231 (SD = 0.075), showing no statistically significant difference (p = 0.121). Conclusions Based on our results, quantifying posttreatment contrast-enhancing lesion development directionality with DTI in glioblastoma patients does not appear to effectively distinguish between TP and TRA.

Funder

ZonMw

Helse Sør-Øst RHF

Publisher

Springer Science and Business Media LLC

Reference39 articles.

1. Civita P, Valerio O, Naccarato AG, Gumbleton M, Pilkington GJ (2020) Satellitosis, a crosstalk between neurons, vascular structures and neoplastic cells in Brain tumours; early Manifestation of Invasive Behaviour. Cancers 12(12). https://doi.org/10.3390/cancers12123720

2. Kawauchi D, Ohno M, Honda-Kitahara M, Miyakita Y, Takahashi M, Yanagisawa S, Tamura Y, Kikuchi M, Ichimura K, Narita Y (2023) Clinical characteristics and prognosis of Glioblastoma patients with infratentorial recurrence. BMC Neurol 23(1):9. https://doi.org/10.1186/s12883-022-03047-9

3. Li Y, Ma Y, Wu Z, Xie R, Zeng F, Cai H, Lui S, Song B, Chen L, Wu M (2021) Advanced Imaging techniques for differentiating pseudoprogression and Tumor Recurrence after Immunotherapy for Glioblastoma. Front Immunol 12:790674. https://doi.org/10.3389/fimmu.2021.790674

4. Brandes AA, Franceschi E, Tosoni A, Blatt V, Pession A, Tallini G, Bertorelle R, Bartolini S, Calbucci F, Andreoli A, Frezza G, Leonardi M, Spagnolli F, Ermani M (2008) MGMT promoter methylation status can predict the incidence and outcome of pseudoprogression after concomitant radiochemotherapy in newly diagnosed glioblastoma patients. J Clin Oncol 26(13):2192–2197. https://doi.org/10.1200/jco.2007.14.8163

5. Rowe LS, Butman JA, Mackey M, Shih JH, Cooley-Zgela T, Ning H, Gilbert MR, Smart DK, Camphausen K, Krauze AV (2018) Differentiating pseudoprogression from true progression: analysis of radiographic, biologic, and clinical clues in GBM. J Neurooncol 139(1):145–152. https://doi.org/10.1007/s11060-018-2855-z

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3