Abstract
To characterize gliomas from dynamic susceptibility contrast (DSC)-based cerebral blood volume (CBV) maps, a CBV value from a normal-appearing region of interest is typically identified manually and used to normalize the CBV maps. This method is user-dependent and time-consuming. We propose an alternative approach based on automatic identification of normal-appearing first-pass curves from brain tissue. Our results in 101 patients suggest similar or better diagnostic accuracy values than the manual approach.
Publication types
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Research Support, Non-U.S. Gov't
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Validation Study
MeSH terms
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Adolescent
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Adult
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Aged
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Blood Volume Determination / standards
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Brain Mapping / methods
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Brain Mapping / standards*
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Brain Neoplasms / blood supply*
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Brain Neoplasms / mortality
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Brain Neoplasms / pathology
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Calibration
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Cerebral Angiography / methods
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Cerebral Angiography / standards*
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Cerebrovascular Circulation*
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Child
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Female
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Glioma / blood supply*
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Glioma / mortality
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Glioma / pathology
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Humans
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Kaplan-Meier Estimate
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Magnetic Resonance Angiography / methods
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Magnetic Resonance Angiography / standards*
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Male
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Middle Aged
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Proportional Hazards Models
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Reference Standards
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Risk Factors
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Young Adult