A Novel Method to Detect Pulmonary Thromboembolic Events With Non-Contrast 4DCT

The standard test to diagnose PE is the Pulmonary Computed Tomography Angiogram (CTA). This can be prohibitive with some patients due to the amount of radiation exposure as well as the complications associated with the need to use intravenous (IV) contrast. CTA can detect acute PE with a sensitivity of 99 percent and specificity of 95 percent when combined with CT venography. In patients not medically eligible for CTA, the other option for diagnosis is a ventilation-perfusion (V/Q) single photon emission computed tomography (SPECT) scan. Though this is often prohibitive due to transport to Nuclear Medicine dept., prolonged test time, no test during off hours, etc. In this study the investigators are looking at an alternative method of diagnosing PE's in the Emergency Department where the investigators look at ventilation and perfusion images thru respiratory gated non-contrast CT (commonly called 4DCT).

Technetium-99 m macroaggregated albumin (99mTc-MAA) imaged with single photon emission computed tomography (SPECT) is considered the standard method for the quantitative determination of pulmonary perfusion. Magnetic resonance imaging (MRI) with contrast agents have been utilized experimentally to image the pulmonary vasculature and tissue perfusion. Quantification of SPECT images requires correction of the acquired data for attenuation and attenuation correction, which has lead to the development of SPECT/CT scanners. The low-dose CT can be utilized to evaluate the lung airway architecture, lung parenchyma, and pleural space in conjunction with the registered perfusion images rivaling CTA in sensitivity and specificity.

In a study comparing CT attenuation with SPECT perfusion defects, patients were found to have hypo-attenuated pulmonary regions corresponding to regions with decreased perfusion in 57 percent of acute pulmonary emboli and 88 percent of chronic emboli cases. In the same study, hyper-attenuated regions were found to correspond to regions with hyperperfusion. A method to measure pulmonary perfusion based on subtraction digital fluoroscopy without contrast has been reported. In that study, subtraction images were generated between chest projection images at systole and diastole generating an image representing the perfusion difference. These perfusion projection images were correlate with 99mTc-MAA scintigraphy. Thus, changes in the amount and distribution of pulmonary perfusion throughout the respiratory cycle can be expected and these changes may be apparent on dynamic CT.

Simon described a technique to calculate the change in fractional content of air within pulmonary tissue between anatomically matched CT regions based on a simple model that assumes the density changes were solely due to air content. The investigators successfully applied that model to inhale and exhale breath-hold CT image pairs as well as 4DCT images to create ventilation images. However, the amount of blood in the thorax and lungs varies with the respiratory cycle, thus violating the assumption of this model. The investigators found a cyclic variation in the apparent weight of the lung on 4DCT and others have reported respiratory induced variations in pulmonary perfusion of the lung on MRI. The pulmonary density changes found on 4DCT thus result from both changes in air and blood content.

4DCT derived ventilation images can also be inferred from the respiratory motion induced local tissue volume changes independent of the 4DCT density values. The Jacobian determinant of the deformation field, calculated from the result of images depicting different respiratory phases of the lungs, is used to estimate the local volume changes or ventilation. There is a discrepancy between the density based and the Jacobian based ventilation images suggesting a method to extract respiratory induced blood mass change from 4DCT images. The investigators hypothesize the respiratory induced blood mass changed (RIBMC) will only occur within perfused lung regions. Each image set will contain information representing the density change resulting from both ventilation and RIBMC. Extracting both ventilation and perfusion-like image from the 4DCT image intensities, referred to as Hounsfield Units (HU) is our goal.