The goal of this project is to develop functional magnetic resonance imaging (fMRI) tools to assist the diagnosis and treatment of human patients with a brain tumor or other operable pathology. The specific focus of this proposal is to produce a practical, clinic-ready suite of MR imaging methods, analyses and display tools to solve the number one impediment to routine use of fMRI for guiding brain surgery and radiation treatment: risk of brain damage due to the treatment itself. Currently, the primary clinical use of fMRI is to identify healthy brain tissue that might be damaged by surgery or radiation treatment and thereby cause an unintended neurological deficit such as partial blindness or paralysis. Neurosurgeons who use fMRI for this purpose have reported that it allows them to be more aggressive in removing the tumor because they don't have to guess where the healthy brain tissue is located. However, the success of using fMRI for this purpose depends on its ability to reliably distinguish between healthy brain tissue and diseased tissue that can be removed without causing a deficit. Herein, lies a critical problem. fMRI signals are not generated by the brain cells themselves but, rather, by localized changes in blood flow and oxygenation that are triggered when the brain cells become active as the patient performs a sensory, motor or cognitive task. The cascade of cellular events that link changes in brain cell activity to changes in blood flow is complex and can be disrupted by a brain tumor or other disease process. Disrupting this cascade causes neurovascular uncoupling (NVU) and results in a localized loss of the fMRI signal even though nearby brain cells are still functional. If NVU is not detected, healthy brain tissue can be mistaken for diseased tissue and inadvertently resected or irradiated. This can result in treatment-induced deficits such as partial loss of vision or limb movement. Fortunately, there are two promising methods that can be used to detect NVU but they have not been fully tested with patients nor have they been developed into tools that are ready for routine clinical use and distribution to the health care community. Consequently, the specific goal of this project is to address this need through a collaborative effort between imaging scientists and physicians at the Medical College of Wisconsin, Johns Hopkins University and Prism Clinical Imaging, Inc. This Phase 1 STTR project will address the feasibility of combining the two most promising methods, testing the combined method with a small number of patients, and developing prototype software for acquisition, analysis and visualization of NVU-related data. Successful completion of this project will lead to a subsequent Phase 2 project that will focus on testing a larger range of patients and pathologies and creating a commercial product ready for release to hospitals and clinics. It is anticipated that the proposed technology will have a significant impact on the use of fMRI for guiding brain surgery and on the acceptance of fMRI as standard of care for this purpose.
The goal of this project is to develop functional magnetic resonance imaging (fMRI) tools to assist the diagnosis and treatment of human patients with a brain tumor or other operable pathology. The specific focus of this proposal is to produce a practical, clinic-ready suite of MR imaging methods, analyses and display tools to solve the number one impediment to routine use of fMRI for guiding brain surgery and radiation treatment: risk of brain damage due to the treatment itself. Currently, the primary clinical use of fMRI is to identify healthy brain tissue that might be damaged by surgery or radiation treatment and thereby cause an unintended neurological deficit such as partial blindness or paralysis. Neurosurgeons who use fMRI for this purpose have reported that it allows them to be more aggressive in removing the tumor because they don't have to guess where the healthy brain tissue is located. However, the success of using fMRI for this purpose depends on its ability to reliably distinguish between healthy brain tissue and diseased tissue that can be removed without causing a deficit. Herein, lies a critical problem. fMRI signals are not generated by the brain cells themselves but, rather, by localized changes in blood flow and oxygenation that are triggered when the brain cells become active as the patient performs a sensory, motor or cognitive task. The cascade of cellular events that link changes in brain cell activity to changes in blood flow is complex and can be disrupted by a brain tumor or other disease process. Disrupting this cascade causes 'neurovascular uncoupling' (NVU) and results in a localized loss of the fMRI signal even though nearby brain cells are still functional. If NVU is not detected, healthy brain tissue can be mistaken for diseased tissue and inadvertently resected or irradiated. This can result in treatment-induced deficits such as partial loss of vision or limb movement. Fortunately, there are two promising methods that can be used to detect NVU but they have not been fully tested with patients nor have they been developed into tools that are ready for routine clinical use and distribution to the health care community. Consequently, the specific goal of this project is to address this need through a collaborative effort between imaging scientists and physicians at the Medical College of Wisconsin, Johns Hopkins University and Prism Clinical Imaging, Inc. This Phase 1 STTR project will address the feasibility of combining the two most promising methods, testing the combined method with a small number of patients, and developing prototype software for acquisition, analysis and visualization of NVU-related data. Successful completion of this project will lead to a subsequent Phase 2 project that will focus on testing a larger range of patients and pathologies and creating a commercial product ready for release to hospitals and clinics. It is anticipated that the proposed technology will have a significant impact on the use of fMRI for guiding brain surgery and on the acceptance of fMRI as 'standard of care' for this purpose.
