Childhood Cancer Data Initiative Annual Symposium (Abstract Registration): Submission #37
Submission information
Submission Number: 37
Submission ID: 148228
Submission UUID: c739aad9-221a-44f5-ac78-1240feef0292
Submission URI: /nci/ccdisymposium/abstract
Created: Wed, 08/06/2025 - 12:34
Completed: Wed, 08/06/2025 - 12:53
Changed: Wed, 08/06/2025 - 12:53
Remote IP address: 10.208.24.36
Submitted by: Anonymous
Language: English
Is draft: No
Abstract Submission for Poster Presentation
Developing predictive and translational magnetic resonance imaging biomarkers of neuroinflammation, cognitive impairment, and survival outcomes for radiotherapy-induced brain injury
Introduction: Radiotherapy-induced brain injury (RIBI) affects up to 90% of brain tumor survivors treated with radiotherapy. Thus, there is a great need for imaging strategies capable of detecting RIBI early on, for its effective management.
Objective: Here, we used multi-parametric magnetic resonance imaging (MRI) to identify translational and predictive biomarkers of RIBI in a preclinical mouse model.
Method: Mice were stereotactically irradiated with an X-ray beam at a dose of 80 Gy (1.7Gy/min), and longitudinally monitored using MRI, behavioral tests of learning and memory, positron emission tomography (PET), histology, and immunohistochemistry. The irradiated mice were studied in comparison to non-irradiated control mice.
Results: Contrast-enhanced T1-weighted MRI was best suited to detect the onset of injury, by detecting changes in the blood-brain barrier (BBB) permeability. Maximum BBB permeability was detected at one-month post-irradiation. This coincided with the detection of maximum neuroinflammation, using IBA1 and CD68 immunohistochemistry and 11C-CPPC and 11C-DPA PET radiotracers of neuroinflammation. This simultaneous maximum BBB permeability and neuroinflammation detection also coincided with the onset of transient cognitive impairment, detected using the fear-conditioning behavioral test of learning and memory. T2-weighted MRI was best suited to detect intermediate injury, while T2*-weighted MRI was best suited to detect late injury. This MRI biomarker of late injury preceded significant weight loss, severe cognitive impairment, and decreased survival outcomes in the irradiated mice compared to the non-irradiated mice.
Conclusion: We identified three translational and predictive MRI biomarkers of RIBI that could enable the better management of RIBI in brain tumor survivors.
Objective: Here, we used multi-parametric magnetic resonance imaging (MRI) to identify translational and predictive biomarkers of RIBI in a preclinical mouse model.
Method: Mice were stereotactically irradiated with an X-ray beam at a dose of 80 Gy (1.7Gy/min), and longitudinally monitored using MRI, behavioral tests of learning and memory, positron emission tomography (PET), histology, and immunohistochemistry. The irradiated mice were studied in comparison to non-irradiated control mice.
Results: Contrast-enhanced T1-weighted MRI was best suited to detect the onset of injury, by detecting changes in the blood-brain barrier (BBB) permeability. Maximum BBB permeability was detected at one-month post-irradiation. This coincided with the detection of maximum neuroinflammation, using IBA1 and CD68 immunohistochemistry and 11C-CPPC and 11C-DPA PET radiotracers of neuroinflammation. This simultaneous maximum BBB permeability and neuroinflammation detection also coincided with the onset of transient cognitive impairment, detected using the fear-conditioning behavioral test of learning and memory. T2-weighted MRI was best suited to detect intermediate injury, while T2*-weighted MRI was best suited to detect late injury. This MRI biomarker of late injury preceded significant weight loss, severe cognitive impairment, and decreased survival outcomes in the irradiated mice compared to the non-irradiated mice.
Conclusion: We identified three translational and predictive MRI biomarkers of RIBI that could enable the better management of RIBI in brain tumor survivors.
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Johns Hopkins University School of Medicine