Tailored Intraoperative MRI Strategies in High-Grade Glioma Surgery: A Machine Learning–Based Radiomics Model Highlights Selective Benefits

Author:

Aichholzer Martin1ORCID,Rauch Philip1ORCID,Kastler Lucia1,Pichler Josef2ORCID,Aufschnaiter-Hiessböck Kathrin1,Ruiz-Navarro Francisco1ORCID,Aspalter Stefan1ORCID,Hartl Saskia1,Schimetta Wolfgang3ORCID,Böhm Petra1,Manakov Ilja4ORCID,Thomae Wolfgang1,Gmeiner Matthias1ORCID,Gruber Andreas1ORCID,Stefanits Harald1ORCID

Affiliation:

1. Department of Neurosurgery, Kepler University Hospital, Johannes Kepler University, Linz, Austria;

2. Institute of Neuro-Oncology, Kepler University Hospital, Linz, Austria;

3. Institute of Statistics, Johannes Kepler University, Linz, Austria;

4. ImFusion GmbH, Munich, Germany

Abstract

BACKGROUND AND OBJECTIVES: In high-grade glioma (HGG) surgery, intraoperative MRI (iMRI) has traditionally been the gold standard for maximizing tumor resection and improving patient outcomes. However, recent Level 1 evidence juxtaposes the efficacy of iMRI and 5-aminolevulinic acid (5-ALA), questioning the continued justification of iMRI because of its associated costs and extended surgical duration. Nonetheless, drawing from our clinical observations, we postulated that a subset of intricate HGGs may continue to benefit from the adjunctive application of iMRI. METHODS: In a prospective study of 73 patients with HGG, 5-ALA was the primary technique for tumor delineation, complemented by iMRI to detect residual contrast-enhanced regions. Suboptimal 5-ALA efficacy was defined when (1) iMRI detected contrast-enhanced remnants despite 5-ALA's indication of a gross total resection or (2) surgeons observed residual fluorescence, contrary to iMRI findings. Radiomic features from preoperative MRIs were extracted using a U2-Net deep learning algorithm. Binary logistic regression was then used to predict compromised 5-ALA performance. RESULTS: Resections guided solely by 5-ALA achieved an average removal of 93.14% of contrast-enhancing tumors. This efficacy increased to 97% with iMRI integration, albeit not statistically significant. Notably, for tumors with suboptimal 5-ALA performance, iMRI's inclusion significantly improved resection outcomes (P-value: .00013). The developed deep learning–based model accurately pinpointed these scenarios, and when enriched with radiomic parameters, showcased high predictive accuracy, as indicated by a Nagelkerke R2 of 0.565 and a receiver operating characteristic of 0.901. CONCLUSION: Our machine learning–driven radiomics approach predicts scenarios where 5-ALA alone may be suboptimal in HGG surgery compared with its combined use with iMRI. Although 5-ALA typically yields favorable results, our analyses reveal that HGGs characterized by significant volume, complex morphology, and left-sided location compromise the effectiveness of resections relying exclusively on 5-ALA. For these intricate cases, we advocate for the continued relevance of iMRI.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Neurology (clinical),Surgery

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