Estimation and correction of cardiac respiratory motion in SPECT in the presence of limited-angle effects due to irregular respiration.

Purpose: One issue with amplitude binning list-mode studies in SPECT for respiratory motion correction is that variation in the patient's respiratory pattern will result in binned motion states with little or no counts at various projection angles. The reduced counts result in limited-angle reconstruction artifacts which can impact the accuracy of the necessary motion estimation needed to correct the images. In this work, the authors investigate a method to overcome the effect of limited-angle reconstruction artifacts in SPECT when estimating respiratory motion.

Impact on reader performance for lesion-detection/ localization tasks of anatomical priors in SPECT reconstruction.

With increasing availability of multimodality imaging systems, high-resolution anatomical images can be used to guide the reconstruction of emission tomography studies. By measuring reader performance on a lesion detection task, this study investigates the improvement in image-quality due to use of prior anatomical knowledge, for example organ or lesion boundaries, during SPECT reconstruction. Simulated (67)Ga -citrate source and attenuation distributions were created from the mathematical cardiac-torso (MCAT) anthropomorphic digital phantom.

An Assessment of a Low-Cost Visual Tracking System (VTS) to Detect and Compensate for Patient Motion during SPECT.

Patient motion is inevitable in SPECT and PET due to the lengthy period of time patients are imaged and patient motion can degrade diagnostic accuracy. The goal of our studies is to perfect a methodology for tracking and correcting patient motion when it occurs. In this paper we report on enhancements to the calibration, camera stability, accuracy of motion tracking, and temporal synchronization of a low-cost visual tracking system (VTS) we are developing.

A method for synchronizing an external respiratory signal with a list-mode PET acquisition.

A method is proposed to synchronize positron emission tomography (PET) list-mode data with an externally recorded respiratory signal in the absence of a master clock. When the respiratory signal reaches a user-defined threshold, a trigger mark is stored in the list-mode file. After the acquisition, synchronization is achieved when the stored trigger marks are superimposed on the respiratory curve to form a horizontal line over time at the user-defined threshold.

An Adaptive Approach to Decomposing Patient-Motion Tracking Data Acquired During Cardiac SPECT Imaging.

Patient motion during cardiac SPECT imaging can cause diagnostic imaging artifacts. We have implemented a Neural Network (NN) approach to decompose monitored patient motion data, gathered during cardiac SPECT imaging, using the Polaris stereo-IR real-time motion-tracking system. Herein, we show the successful decomposition of Polaris motion data into rigid body motion (RBM) and respiratory motion (RM).