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
相关论文
共 35 条
[1]   Tumour progression or pseudoprogression? A review of post-treatment radiological appearances of glioblastoma [J].
Abdulla, S. ;
Saada, J. ;
Johnson, G. ;
Jefferies, S. ;
Ajithkumar, T. .
CLINICAL RADIOLOGY, 2015, 70 (11) :1299-1312
[2]   Implementation of a Novel Surveillance Template for Head and Neck Cancer: Neck Imaging Reporting and Data System (NI-RADS) [J].
Aiken, Ashley H. ;
Farley, April ;
Baugnon, Kristen L. ;
Corey, Amanda ;
El-Deiry, Mark ;
Duszak, Richard ;
Beitler, Jonathan ;
Hudgins, Patricia A. .
JOURNAL OF THE AMERICAN COLLEGE OF RADIOLOGY, 2016, 13 (06) :743-746
[3]  
Annangi P, 2011, MED IMAGING 2011 ULT
[4]  
Bauer S, 2012, SKULL STRIPPING FILT
[5]  
Cramer JA, 2014, APPL RADIOL, V43, P18
[6]   BI-RADS decoded: Detailed guidance on potentially confusing issues [J].
D'Orsi, Carl J. ;
Newell, Mary S. .
RADIOLOGIC CLINICS OF NORTH AMERICA, 2007, 45 (05) :751-+
[7]  
Dempsey MF, 2005, AM J NEURORADIOL, V26, P770
[8]   Consensus recommendations for a standardized Brain Tumor Imaging Protocol in clinical trials [J].
Ellingson, Benjamin M. ;
Bendszus, Martin ;
Boxerman, Jerrold ;
Barboriak, Daniel ;
Erickson, Bradley J. ;
Smits, Marion ;
Nelson, Sarah J. ;
Gerstner, Elizabeth ;
Alexander, Brian ;
Goldmacher, Gregory ;
Wick, Wolfgang ;
Vogelbaum, Michael ;
Weller, Michael ;
Galanis, Evanthia ;
Kalpathy-Cramer, Jayashree ;
Shankar, Lalitha ;
Jacobs, Paula ;
Pope, Whitney B. ;
Yang, Dewen ;
Chung, Caroline ;
Knopp, Michael V. ;
Cha, Soonme ;
van den Bent, Martin J. ;
Chang, Susan ;
Al Yung, W. K. ;
Cloughesy, Timothy F. ;
Wen, Patrick Y. ;
Gilbert, Mark R. .
NEURO-ONCOLOGY, 2015, 17 (09) :1188-1198
[9]   Structured Reporting in Radiology [J].
Ganeshan, Dhakshinamoorthy ;
Phuong-Anh Thi Duong ;
Probyn, Linda ;
Lenchik, Leon ;
McArthur, Tatum A. ;
Retrouvey, Michele ;
Ghobadi, Emily H. ;
Desouches, Stephane L. ;
Pastel, David ;
Francis, Isaac R. .
ACADEMIC RADIOLOGY, 2018, 25 (01) :66-73
[10]   Institutional Implementation of a Structured Reporting System: Our Experience with the Brain Tumor Reporting and Data System [J].
Gore, Ashwani ;
Hoch, Michael J. ;
Shu, Hui-Kuo G. ;
Olson, Jeffrey J. ;
Voloschin, Alfredo D. ;
Weinberg, Brent D. .
ACADEMIC RADIOLOGY, 2019, 26 (07) :974-980