A data-driven respiratory motion estimation approach for PET based on time-of-flight weighted positron emission particle tracking.

Purpose: Respiratory motion of patients during positron emission tomography (PET)/computed tomography (CT) imaging affects both image quality and quantitative accuracy. Hardware-based motion estimation, which is the current clinical standard, requires initial setup, maintenance, and calibration of the equipment, and can be associated with patient discomfort. Data-driven techniques are an active area of research with limited exploration into lesion-specific motion estimation.

Quantitative Assessment of Breast Density: Transmission Ultrasound is Comparable to Mammography with Tomosynthesis.

Elevated breast density is among the strongest independent predictors of breast cancer. Breast density scores are critical inputs in models used to calculate a patient's lifetime risk of developing breast cancer. Today, the only FDA-cleared technology for assessing breast density uses mammography.

Respiratory Motion Correction Using A Novel Positron Emission Particle Tracking Technique: A Framework Towards Individual Lesion-Based Motion Correction.

Respiratory motion during PET/CT imaging is a matter of concern due to degraded image quality and reduced quantitative accuracy caused by motion artifacts. One class of motion correction methods relies on hardware-based respiratory motion tracking systems in order to use respiratory cycles for correcting motion artifacts. Another class of hardware-free methods extract motion information from the reconstructed images or sinograms.

GATE validation of standard dual energy corrections in small animal SPECT-CT.

This paper addresses 123I and 125I dual isotope SPECT imaging, which can be challenging because of spectrum overlap in the low energy spectrums of these isotopes. We first quantify the contribution of low-energy photons from each isotope using GATE-based Monte Carlo simulations for the MOBY mouse phantom. We then describe and analyze a simple, but effective method that uses the ratio of detected low and high energy 123I activity to separate the mixed low energy 123I and 125I activities.

Development and validation of a complete GATE model of the Siemens Inveon trimodal imaging platform.

This article presents and validates a newly developed GATE model of the Siemens Inveon trimodal imaging platform. Fully incorporating the positron emission tomography (PET), single-photon emission computed tomography (SPECT), and computed tomography (CT) data acquisition subsystems, this model enables feasibility studies of new imaging applications, the development of reconstruction and correction algorithms, and the creation of a baseline against which experimental results for real data can be compared. Model validation was based on comparing simulation results against both empirical and published data.