White Matter Tract Density Index Prediction Model of Overall Survival in Glioblastoma

Author:

Salvalaggio Alessandro12,Pini Lorenzo12,Gaiola Matteo1,Velco Aron1,Sansone Giulio1,Anglani Mariagiulia3,Fekonja Lucius45,Chioffi Franco6,Picht Thomas45,Thiebaut de Schotten Michel78,Zagonel Vittorina9,Lombardi Giuseppe9,D’Avella Domenico10,Corbetta Maurizio1211

Affiliation:

1. Clinica Neurologica, Department of Neuroscience, University of Padova, Padova, Italy

2. Padova Neuroscience Center, University of Padova, Padova, Italy

3. Neuroradiology Unit, University Hospital of Padova, Padova, Italy

4. Department of Neurosurgery, Charité Universitätsmedizin Berlin, Berlin, Germany

5. Cluster of Excellence “Matters of Activity. Image Space Material,” Humboldt University, Berlin, Germany

6. Division of Neurosurgery, Azienda Ospedaliera Università di Padova, Padova, Italy

7. Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France

8. Groupe d’Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France

9. Department of Oncology, Oncology 1, Veneto Institute of Oncology IOV-IRCCS, Padova, Italy

10. Academic Neurosurgery, Department of Neurosciences, University of Padova, Padova, Italy

11. Venetian Institute of Molecular Medicine, Fondazione Biomedica, Padova, Italy

Abstract

ImportanceThe prognosis of overall survival (OS) in patients with glioblastoma (GBM) may depend on the underlying structural connectivity of the brain.ObjectiveTo examine the association between white matter tracts affected by GBM and patients’ OS by means of a new tract density index (TDI).Design, Setting, and ParticipantsThis prognostic study in patients with a histopathologic diagnosis of GBM examined a discovery cohort of 112 patients who underwent surgery between February 1, 2015, and November 30, 2020 (follow-up to May 31, 2023), in Italy and 70 patients in a replicative cohort (n = 70) who underwent surgery between September 1, 2012, and November 30, 2015 (follow-up to May 31, 2023), in Germany. Statistical analyses were performed from June 1, 2021, to May 31, 2023. Thirteen and 12 patients were excluded from the discovery and the replicative sets, respectively, because of magnetic resonance imaging artifacts.ExposureThe density of white matter tracts encompassing GBM.Main Outcomes and MeasuresCorrelation, linear regression, Cox proportional hazards regression, Kaplan-Meier, and prediction analysis were used to assess the association between the TDI and OS. Results were compared with common prognostic factors of GBM, including age, performance status, O6-methylguanine-DNA methyltransferase methylation, and extent of surgery.ResultsIn the discovery cohort (n = 99; mean [SD] age, 62.2 [11.5] years; 29 female [29.3%]; 70 male [70.7%]), the TDI was significantly correlated with OS (r = −0.34; P < .001). This association was more stable compared with other prognostic factors. The TDI showed a significant regression pattern (Cox: hazard ratio, 0.28 [95% CI, 0.02-0.55; P = .04]; linear: t = −2.366; P = .02). and a significant Kaplan-Meier stratification of patients as having lower or higher OS based on the TDI (log-rank test = 4.52; P = .03). Results were confirmed in the replicative cohort (n = 58; mean [SD] age, 58.5 [11.1] years, 14 female [24.1%]; 44 male [75.9%]). High (24-month cutoff) and low (18-month cutoff) OS was predicted based on the TDI computed in the discovery cohort (accuracy = 87%).Conclusions and RelevanceIn this study, GBMs encompassing regions with low white matter tract density were associated with longer OS. These findings indicate that the TDI is a reliable presurgical outcome predictor that may be considered in clinical trials and clinical practice. These findings support a framework in which the outcome of GBM depends on the patient’s brain organization.

Publisher

American Medical Association (AMA)

Subject

Neurology (clinical)

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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