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Dynamic contrast-enhanced MRI of pulmonary nodule at 3T

$160,328R21FY2007CANIH

Brigham And Women'S Hospital, Boston MA

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Abstract

[unreadable] DESCRIPTION (provided by applicant): Lung cancer is the most common cause of cancer and cancer death throughout the world, with 169,400 new cases of cancer and 154,900 cancer deaths for 2002 in the United States alone. Lung cancer is the leading cause of cancer death in both males and females, 31% and 25% respectively. With advances in multi- detector row computed tomography (CT), the number of small lung nodules detected has increased. The introduction of lung cancer screening has likewise accelerated the detection of small lung nodules. Despite advances in assessment of solitary pulmonary nodules using hemodynamic information from CT and biochemical characteristics from PET (positron emission tomography), a substantial portion of solitary pulmonary nodules remain indeterminate for specific diagnosis. MR perfusion of solitary pulmonary nodules using 3T MR with high spatial and temporal resolution can potentially provide a second-stage method for characterizing lung nodules with minimal associated risks which may help to avoid unnecessary intervention for benign lung nodules and associated mortality/morbidity. The purpose of this proposal is to develop such a test using 3T MR perfusion method with parametric analysis as a second-stage characterization tool of solitary pulmonary nodules. The long term aim is to determine the perfusion characteristics of solitary pulmonary nodules which predict the outcome - and response to therapy - of lung tumors. Specific Aim 1: To develop a method for MR perfusion study of solitary pulmonary nodules. In adapting the existing MR perfusion method for evaluation of solitary pulmonary nodule, a method for correcting respiratory motion must be developed; and, parametric analysis of acquired MR data must be optimized. Specific Aim 2: To determine the diagnostic accuracy of this method in well-characterized pulmonary nodules by pathology. We will correlate the perfusion parameters derived from MR imaging data with pathology to provide preliminary estimates of the sensitivity, specificity, accuracy, and positive and negative predictive values of the MR-derived perfusion parameters. [unreadable] [unreadable] [unreadable]

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