There is an enormous economic and social burden of lung disease that demands improved tools to diagnose, stage, and follow treatment response. To assess heterogeneous and localized pulmonary diseases, cross- sectional imaging is often performed, most commonly with computed tomography (CT) or radioactive tracers (SPECT/PET). While these techniques provide structural and functional information, respectively, they deliver considerable radiation dose which limits use in radiosensitive and pediatric populations. This proposal aims to shift the current clinical practice paradigms for pulmonary imaging by making magnetic resonance imaging (MRI) a valuable modality for lung imaging. MRI delivers no ionizing radiation and can thus be used for longitudinal follow-up or screening in radio-sensitive populations. Furthermore, MRI provides multi- parametric contrast based on microstructure, ventilation, perfusion, cellular metabolism, and inflammation that can improve the assessment of lung diseases. Unfortunately, the radiation-free and multi-parametric benefits of MRI are not currently clinically available for lung imaging due to low signal in the lung and sensitivity to motion with current imaging methods. Recent developments by our group and others have demonstrated that the MRI acquisition paradigm can be modified to enable dramatic improvements in the visualization of the lung that rival CT in ventilated and cooperative subjects with the added benefit of providing improved soft tissue contrast. However, patients often suffer from poor lung function and/or have difficulty with compliance, which leads to complex, irregular breathing and bulk motion that cannot be handled by current MRI techniques. We propose a next generation of pulmonary MRI techniques that are designed to address and overcome the limitations of motion and low lung signal while also incorporating multiple MR soft tissue contrast mechanisms. These address all aspects of MRI scanning including patient preparation and experience, the MRI acquisition, and the reconstruction of images from the data. Specifically, we develop an audiovisual biofeedback system to improve the patient experience while also reducing the likelihood for complex motion, develop multi-contrast MRI sampling strategies which maximize embedded motion information, and create a reconstruction architecture which leverages the MRI data directly to estimate and correct for motion even in the case of complex motion. These methods would be beneficial for characterizing numerous diseases of the lung, both in pediatric and adult populations, including pulmonary nodules, pulmonary embolism, interstitial fibrosis, cystic fibrosis, COPD, asthma, and pulmonary infection. They will have the most significant impact in pediatrics, where there is an urgent need to limit ionizing radiation exposure. Anticipating applications to this population, we have included a broad evaluation in pediatric subjects and a specific pediatric imaging evaluation of pulmonary nodules from other primary malignancies. These nodule evaluations are most common use of pediatric chest CT at our institutions, and thus represent a substantial opportunity for dose reduction.
There is an enormous economic and social burden of lung disease that demands improved tools such as non- invasive imaging to diagnose, stage, and follow treatment response. The most commonly used lung imaging techniques are computed tomography (CT) or radioactive tracers (SPECT/PET), which deliver considerable radiation dose and can lead to radiation-induced malignancies, thus limiting their use in radiosensitive and pediatric populations. This project aims to develop next-generation MRI techniques for lung imaging that require no ionizing radiation, improving safety, and also provide new types of image contrast to improve the assessment of lung disease.!
