Development and Clinical Evaluation of a Contrast Optimizer for Contrast-Enhanced CT Imaging of the Liver.

Objective: Patient characteristics, iodine injection, and scanning parameters can impact the quality and consistency of contrast enhancement of hepatic parenchyma in CT imaging. Improving the consistency and adequacy of contrast enhancement can enhance diagnostic accuracy and reduce clinical practice variability, with added positive implications for safety and cost-effectiveness in the use of contrast medium. We developed a clinical tool that uses patient attributes (height, weight, sex, age) to predict hepatic enhancement and suggest alternative injection/scanning parameters to optimize the procedure.

A framework to model charge sharing and pulse pileup for virtual imaging trials of photon-counting CT.

This study describes the development, validation, and integration of a detector response model that accounts for the combined effects of x-ray crosstalk, charge sharing, and pulse pileup in photon-counting detectors.The x-ray photon transport was simulated using Geant4, followed by analytical charge sharing simulation in MATLAB. The analytical simulation models charge clouds with Gaussian-distributed charge densities, which are projected on a 3×3 pixel neighborhood of interaction location to compute detected counts.

Photon-counting computed tomography versus energy-integrating computed tomography for detection of small liver lesions: comparison using a virtual framework imaging.

Purpose: Photon-counting computed tomography (PCCT) has the potential to provide superior image quality to energy-integrating CT (EICT). We objectively compare PCCT to EICT for liver lesion detection.

Approach: Fifty anthropomorphic, computational phantoms with inserted liver lesions were generated.

Multivariate signal-to-noise ratio as a metric for characterizing spectral computed tomography.

With the introduction of spectral CT techniques into the clinic, the imaging capacities of CT were expanded to multiple energy levels. Due to a variety of factors, the acquired signal in spectral CT datasets is shared between these images. Conventional image quality metrics assume independence between images which is not preserved within spectral CT datasets, limiting their utility for characterizing energy selective images.

Quantitative accuracy of lung function measurement using parametric response mapping: A virtual imaging study.

Parametric response mapping (PRM) is a voxel-based quantitative CT imaging biomarker that measures the severity of chronic obstructive pulmonary disease (COPD) by analyzing both inspiratory and expiratory CT scans. Although PRM-derived measurements have been shown to predict disease severity and phenotyping, their quantitative accuracy is impacted by the variability of scanner settings and patient conditions. The aim of this study was to evaluate the variability of PRM-based measurements due to the changes in the scanner types and configurations.

Virtual Lung Screening Trial (VLST): An Replica of the National Lung Screening Trial for Lung Cancer Detection.

Importance: Clinical imaging trials are crucial for evaluation of medical innovations, but the process is inefficient, expensive, and ethically-constrained. Virtual imaging trial (VIT) approach addresses these limitations by emulating the components of a clinical trial. An rendition of the National Lung Screening Trial (NCLS) via Virtual Lung Screening Trial (VLST) demonstrates the promise of VITs to expedite clinical trials, reduce risks to subjects, and facilitate the optimal use of imaging technologies in clinical settings.

Protocol selection formalism for minimizing detectable differences in morphological radiomics features of lung lesions in repeated CT acquisitions.

Background: The accuracy of morphological radiomic features (MRFs) can be affected by various acquisition settings and imaging conditions. To ensure that clinically irrelevant changes do not reduce sensitivity to capture the radiomics changes between successive acquisitions, it is essential to determine the optimal imaging systems and protocols to use.

Purpose: The main goal of our study was to optimize CT protocols and minimize the minimum detectable difference (MDD) in successive acquisitions of MRFs.

Technology Characterization Through Diverse Evaluation Methodologies: Application to Thoracic Imaging in Photon-Counting Computed Tomography.

Objective: Different methods can be used to condition imaging systems for clinical use. The purpose of this study was to assess how these methods complement one another in evaluating a system for clinical integration of an emerging technology, photon-counting computed tomography (PCCT), for thoracic imaging.

Methods: Four methods were used to assess a clinical PCCT system (NAEOTOM Alpha; Siemens Healthineers, Forchheim, Germany) across 3 reconstruction kernels (Br40f, Br48f, and Br56f).

Characterizing imaging radiation risk in a population of 8918 patients with recurrent imaging for a better effective dose.

An updated extension of effective dose was recently introduced, namely relative effective dose ( ), incorporating age and sex factors. In this study we extended application to a population of about 9000 patients who underwent multiple CT imaging exams, and we compared it with other commonly used radiation protection metrics in terms of their correlation with radiation risk. Using Monte Carlo methods, , dose-length-product based effective dose ( ), organ-dose based effective dose ( ), and organ-dose based risk index ( ) were calculated for each patient.

A systematic assessment and optimization of photon-counting CT for lung density quantifications.

Background: Photon-counting computed tomography (PCCT) has recently emerged into clinical use; however, its optimum imaging protocols and added benefits remains unknown in terms of providing more accurate lung density quantification compared to energy-integrating computed tomography (EICT) scanners.

Purpose: To systematically assess the performance of a clinical PCCT scanner for lung density quantifications and compare it against EICT.

Methods: This cross-sectional study involved a retrospective analysis of subjects scanned (August-December 2021) using a clinical PCCT system.

Development of physiologically-informed computational coronary artery plaques for use in virtual imaging trials.

Background: As a leading cause of death, worldwide, cardiovascular disease is of great clinical importance. Among cardiovascular diseases, coronary artery disease (CAD) is a key contributor, and it is the attributed cause of death for 10% of all deaths annually. The prevalence of CAD is commensurate with the rise in new medical imaging technologies intended to aid in its diagnosis and treatment.

Deep silicon photon-counting CT: A first simulation-based study for assessing perceptual benefits across diverse anatomies.

Objectives: To assess perceptual benefits provided by the improved spatial resolution and noise performance of deep silicon photon-counting CT (Si-PCCT) over conventional energy-integrating CT (ECT) using polychromatic images for various clinical tasks and anatomical regions.

Materials And Methods: Anthropomorphic, computational models were developed for lungs, liver, inner ear, and head-and-neck (H&N) anatomies. These regions included specific abnormalities such as lesions in the lungs and liver, and calcified plaques in the carotid arteries.

Coronary stenosis quantification in cardiac computed tomography angiography: multi-factorial optimization of image quality and radiation dose.

Background: The accuracy and variability of quantification in computed tomography angiography (CTA) are affected by the interplay of imaging parameters and patient attributes. The assessment of these combined effects has been an open engineering challenge.

Purpose: In this study, we developed a framework that optimizes imaging parameters for accurate and consistent coronary stenosis quantification in cardiac CTA while accounting for patient-specific variables.

Surface-based anthropomorphic bone structures for use in high-resolution simulated medical imaging.

Virtual imaging trials enable efficient assessment and optimization of medical image devices and techniques via simulation rather than physical studies. These studies require realistic, detailed ground-truth models or phantoms of the relevant anatomy or physiology. Anatomical structures within computational phantoms are typically based on medical imaging data; however, for small and intricate structures (e.

Pulsed wave Doppler ultrasound: Accuracy, variability, and impact of acquisition parameters on flow measurements.

Background: Pulsed wave Doppler ultrasound is a useful modality for assessing vascular health as it quantifies blood flow characteristics. To facilitate accurate diagnosis, accuracy and consistency of this modality should be assessed through Doppler quality assurance (QA).

Purpose: The purpose of this study was to characterize the accuracy, reproducibility, and inter-scanner variability of ultrasound flow velocity measurements via a flow phantom, with a focus on the effect of systematic acquisition parameters on measured flow velocity accuracy.

Exploration of the pulse pileup effects in a clinical CdTe-based photon-counting computed tomography.

Background: High tube current generates a high flux of x-rays to photon counting detectors (PCDs) that can potentially result in the piling up of pulses formed by concurrent photons, which can cause count loss and energy resolution degradation.

Purpose: To evaluate the performance of clinical photon-counting CT (PCCT) systems in high flux, potentially influenced by pulse pileup effects, in terms of task-generic image quality metrics.

Methods: A clinical phantom was scanned on a commercial PCCT scanner (NAEOTOM Alpha, Siemens) at 120 kV under fourteen different tube current levels (40-1000 mA) with a rotation time of 0.

A systematic task-based image quality assessment of photon-counting and energy integrating CT as a function of reconstruction kernel and phantom size.

Background: Image quality of photon-counting and energy integrating CT scanners changes with object size, dose to the object, and kernel selection.

Purpose: To comprehensively compare task-generic image quality of photon-counting CT (PCCT) and energy integrating CT (EICT) systems as a function of phantom size, dose, and reconstruction kernel.

Methods: A size-variant phantom (Mercury Phantom 3.

MCR toolkit: A GPU-based toolkit for multi-channel reconstruction of preclinical and clinical x-ray CT data.

Background: The advancement of x-ray CT into the domains of photon counting spectral imaging and dynamic cardiac and perfusion imaging has created many new challenges and opportunities for clinicians and researchers. To address challenges such as dose constraints and scanning times while capitalizing on opportunities such as multi-contrast imaging and low-dose coronary angiography, these multi-channel imaging applications require a new generation of CT reconstruction tools. These new tools should exploit the relationships between imaging channels during reconstruction to set new image quality standards while serving as a platform for direct translation between the preclinical and clinical domains.

Harmonizing CT Images via Physics-based Deep Neural Networks.

The rendition of medical images influences the accuracy and precision of quantifications. Image variations or biases make measuring imaging biomarkers challenging. The objective of this paper is to reduce the variability of computed tomography (CT) quantifications for radiomics and biomarkers using physics-based deep neural networks (DNNs).

A systematic assessment of photon-counting CT for bone mineral density and microarchitecture quantifications.

Photon-counting CT (PCCT) is an emerging imaging technology with potential improvements in quantification and rendition of micro-structures due to its smaller detector sizes. The aim of this study was to assess the performance of a new PCCT scanner (NAEOTOM Alpha, Siemens) in quantifying clinically relevant bone imaging biomarkers for characterization of common bone diseases. We evaluated the ability of PCCT in quantifying microarchitecture in bones compared to conventional energy-integrating CT.