Ultra-High-Resolution Photon-Counting-Detector CT with a Dedicated Denoising Convolutional Neural Network for Enhanced Temporal Bone Imaging.

Background And Purpose: Ultra-high-resolution (UHR) photon-counting-detector (PCD) CT improves image resolution but increases noise, necessitating use of smoother reconstruction kernels that reduce resolution below the system's 0.110 mm maximum spatial resolution. To address this, a denoising convolutional neural network (CNN) was developed to reduce noise in images reconstructed with the available sharpest reconstruction kernel while preserving resolution for enhanced temporal bone visualization.

A Generalizable Framework for Kidney Stone Composition Characterization Using Dual-Energy CT.

Rationale And Objectives: Classification of non-uric acid (NUA) renal stones in dual-energy CT (DECT) is difficult due to their similar CT number ratios (CTRs) and because the CTRs change with patient size and acquisition protocol. In this work, we developed a generalizable framework to estimate correct CTR threshold for different stone types, protocols, and patient sizes and validated the results on two DECT scanners.

Materials And Methods: Our framework assumes generic x-ray spectra, estimates the added filtration to match half-value-layer (HVL) measurements, and predicts the CTR of each stone type from the chemical composition and patient size.

Quantitative assessment of areal bone mineral density using multi-energy localizer radiographs from photon-counting detector CT.

To assess the accuracy and stability of areal bone-mineral-density (aBMD) measurements from multi-energy CT localizer radiographs acquired using photon-counting detector (PCD) CT.A European Spine Phantom (ESP) with hydroxyapatite (HA 0.5, 1.

Opportunistic Bone Mineral Density Measurement Using Photon-Counting Detector CT Spectral Localizer Images: A Prospective Study.

Spectral localizer images from photon-counting detector (PCD) CT can be used for bone mineral density (BMD) evaluation given their 2D-projectional nature and material decomposition capability. As all CT examinations include localizer images, this approach could allow opportunistic osteoporosis screening in patients undergoing clinically indicated imaging by PCD CT. To assess the utility of PCD-CT spectral localizer images for opportunistic derivation of area BMD (aBMD) values and T-scores, using dual-energy X-ray absorptiometry (DXA) as the reference standard.

Impact of Photon-counting Detector Computed Tomography on a Quantitative Interstitial Lung Disease Machine Learning Model.

Purpose: Compare the impact of photon-counting detector computed tomography (PCD-CT) to conventional CT on an interstitial lung disease (ILD) quantitative machine learning (QML) model.

Materials And Methods: A QML model analyzed 52 CT exams from patients who underwent same-day conventional and PCD-CT for suspected ILD. Lin's concordance correlation coefficient (CCC) assessed agreement between conventional and PCD-CT QML results.