The Longitudinal Imaging Tracker (BrICS-LIT): A Cloud Platform for Monitoring Treatment Response in Glioblastoma Patients

被引:9
作者
Ramesh, Karthik [1 ,2 ,3 ]
Gurbani, Saumya S. [1 ,2 ,3 ]
Mellon, Eric A. [4 ]
Huang, Vicki [1 ,2 ,3 ]
Goryawala, Mohammed [5 ]
Barkers, Peter B. [6 ]
Kleinberg, Lawrence [7 ]
Shu, Hui-Kuo G. [1 ]
Shim, Hyunsuk [1 ,2 ,3 ,8 ]
Weinberg, Brent D. [8 ]
机构
[1] Emory Univ, Winship Canc Inst, Dept Radiat Oncol, Atlanta, GA 30322 USA
[2] Georgia Inst Technol, Coulter Dept Biomed Engn, Atlanta, GA 30332 USA
[3] Emory Univ, Sch Med, Atlanta, GA 30322 USA
[4] Univ Miami, Miller Sch Med, Dept Radiat Oncol, Sylvester Comprehens Canc Ctr, Miami, FL 33136 USA
[5] Univ Miami, Miller Sch Med, Dept Radiol, Miami, FL 33136 USA
[6] Johns Hopkins Univ, Dept Radiol & Radiol Sci, Baltimore, MD USA
[7] Johns Hopkins Univ, Dept Radiat Oncol, Baltimore, MD USA
[8] Emory Univ, Sch Med, Dept Radiol & Imaging Sci, Atlanta, GA USA
关键词
Glioblastoma; structured reporting; segmentation; longitudinal tracking; BT-RADS; BI-RADS; CRITERIA; PSEUDOPROGRESSION; TEMOZOLOMIDE; SURVIVAL;
D O I
10.18383/j.tom.2020.00001
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Glioblastoma is a common and aggressive form of brain cancer affecting up to 20,000 new patients in the US annually. Despite rigorous therapies, current median survival is only 15-20 months. Patients who complete initial treatment undergo follow-up imaging at routine intervals to assess for tumor recurrence. Imaging is a central part of brain tumor management, but MRI findings in patients with brain tumor can be challenging to interpret and are further confounded by interpretation variability. Disease-specific structured reporting attempts to reduce variability in imaging results by implementing well-defined imaging criteria and standardized language. The Brain Tumor Reporting and Data System (BT-RADS) is one such framework streamlined for clinical workflows and includes quantitative criteria for more objective evaluation of follow-up imaging. To facilitate accurate and objective monitoring of patients during the follow-up period, we developed a cloud platform, the Brain Imaging Collaborative Suite's Longitudinal Imaging Tracker (BrICS-LIT). BrICS-LIT uses semi-automated tumor segmentation algorithms of both T2-weighted FLAIR and contrast-enhanced T1-weighted MRI to assist clinicians in quantitative assessment of brain tumors. The LIT platform can ultimately guide clinical decision-making for patients with glioblastoma by providing quantitative metrics for BT-RADS scoring. Further, this platform has the potential to increase objectivity when measuring efficacy of novel therapies for patients with brain tumor during their follow-up. Therefore, LIT will be used to track patients in a dose-escalated clinical trial, where spectroscopic MRI has been used to guide radiation therapy (Clinicaltrials.gov NCT03137888), and compare patients to a control group that received standard of care.
引用
收藏
页码:93 / 100
页数:8
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