Multimodality molecular imaging of the lung

Abstract

Lung diseases cause significant morbidity and mortality and lead to high healthcare utilization. However, few lung disease-specific biomarkers are available to accurately monitor disease activity for the purposes of clinical management or drug development. Advances in cross-modal imaging technologies, such as combined positron emission tomography (PET) and magnetic resonance (MR) imaging scanners and PET or single-photon emission computed tomography (SPECT) combined with computed tomography (CT), may aid in the development of noninvasive, molecular-based biomarkers for lung disease. However, the lungs pose particular challenges in obtaining accurate quantification of imaging data due to the low density of the organ and breathing motion. This review covers the basic physics underlying PET, SPECT, CT, and MR lung imaging and presents technical considerations for multimodal imaging with regard to PET and SPECT quantification. It also includes a brief review of the current and potential clinical applications for these hybrid imaging technologies.

Keywords: Lung cancer; Lung disease; Magnetic resonance imaging; Molecular imaging; Multimodality imaging; Positron emission tomography; Single photon emission computed tomography.

Fig. 1

PET/CT vs PET/MR images in a patient imaged by PET/CT at approximately 1 h after injection of 15 mCi of ¹⁸F-FDG followed by PET/MR imaging at 1 h and 10 min after PET/CT imaging. Note that the PET images from the PET/MR scanner demonstrate better resolution of the vertebrae compared to the PET/CT images. In comparing the CT and MRI images, the bones on the MRI are similar in signal intensity to the fat due to the fat in the marrow, thus limiting the accuracy of using MRI-based values for generating an appropriate attenuation correction map. The tumor appears brighter on the PET/MR images because of the longer delay in imaging after tracer injection as the scans were performed serially on the same day in the same patient. Images courtesy of Akash Sharma and Jonathan McConathy, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO (color figure online)

Fig. 2

T2-weighted MRI (a) and (b) CT images of the thorax of the same patient showing the lack of similarity of the physical properties measured [29]. (With kind permission from Springer Science + Business Media)

Fig. 3

a PET attenuation image formed by segmentation of MRI images. b CT-based attenuation map of same patient. This research was originally published in [30]. ^©By the Society of Nuclear Medicine and Molecular Imaging, Inc

Fig. 4

SPECT/CT imaging of perfusion and ventilation for functional lung definition. Top three patients display non-uniform uptake of 99mTc-MAA lung perfusion. Middle 99mTc-DTPA lung ventilation. Bottom avoidance regions were defined by a gradient search algorithm and show variable overlap between high perfusion (transparent contour) and high ventilation (opaque contour). Courtesy of Steven Bowen and Jing Zeng, Departments of Radiology and Radiation Oncology, University of Washington (color figure online)