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Article

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

by
Karthik Ramesh
1,2,
Saumya S. Gurbani
1,2,
Eric A. Mellon
3,
Vicki Huang
1,2,
Mohammed Goryawala
4,
Peter B. Barker
5,
Lawrence Kleinberg
6,
Hui-Kuo G. Shu
1,
Hyunsuk Shim
1,2,7,* and
Brent D. Weinberg
7,*
1
Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, GA, USA
2
Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University School of Medicine, Atlanta, GA, USA
3
Departments of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miami, FL, USA
4
Departments of Radiology, University of Miami Miller School of Medicine, Miami, FL, USA
5
Departments of Radiology and Radiological Science, The Johns Hopkins University, Baltimore, MD, USA
6
Departments of Radiation Oncology, The Johns Hopkins University, Baltimore, MD, USA
7
Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA 30322, USA
*
Authors to whom correspondence should be addressed.
Tomography 2020, 6(2), 93-100; https://doi.org/10.18383/j.tom.2020.00001
Submission received: 11 March 2020 / Revised: 8 April 2020 / Accepted: 5 May 2020 / Published: 1 June 2020

Abstract

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 semiautomated 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.
Keywords: glioblastoma; structured reporting; segmentation; longitudinal tracking; BT-RADS glioblastoma; structured reporting; segmentation; longitudinal tracking; BT-RADS

Share and Cite

MDPI and ACS Style

Ramesh, K.; Gurbani, S.S.; Mellon, E.A.; Huang, V.; Goryawala, M.; Barker, P.B.; Kleinberg, L.; Shu, H.-K.G.; Shim, H.; Weinberg, B.D. The Longitudinal Imaging Tracker (BrICS-LIT):A Cloud Platform for Monitoring Treatment Response in Glioblastoma Patients. Tomography 2020, 6, 93-100. https://doi.org/10.18383/j.tom.2020.00001

AMA Style

Ramesh K, Gurbani SS, Mellon EA, Huang V, Goryawala M, Barker PB, Kleinberg L, Shu H-KG, Shim H, Weinberg BD. The Longitudinal Imaging Tracker (BrICS-LIT):A Cloud Platform for Monitoring Treatment Response in Glioblastoma Patients. Tomography. 2020; 6(2):93-100. https://doi.org/10.18383/j.tom.2020.00001

Chicago/Turabian Style

Ramesh, Karthik, Saumya S. Gurbani, Eric A. Mellon, Vicki Huang, Mohammed Goryawala, Peter B. Barker, Lawrence Kleinberg, Hui-Kuo G. Shu, Hyunsuk Shim, and Brent D. Weinberg. 2020. "The Longitudinal Imaging Tracker (BrICS-LIT):A Cloud Platform for Monitoring Treatment Response in Glioblastoma Patients" Tomography 6, no. 2: 93-100. https://doi.org/10.18383/j.tom.2020.00001

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