Publications by authors named "P Douek"
Objectives: To assess the image quality of ultra-high-resolution (UHR) virtual monoenergetic images (VMIs) at 40 keV compared to 70 keV, using spectral photon-counting CT (SPCCT) and dual-layer dual-energy CT (DECT) for coronary computed tomography angiography (CCTA).
Methods And Materials: In this prospective IRB-approved study, 26 high-risk patients were included. CCTA was performed both with an SPCCT in UHR mode and with one of two DECT scanners (iQOn or CT7500) within 3 days.
3D printed biomaterial implants are revolutionizing personalized medicine for tissue repair, especially in orthopedics. In this study, a radiopaque bismuth oxide (BiO) doped polycaprolactone (PCL) composite is developed and implemented to enable the use of diagnostic X-ray technologies, especially spectral photon counting X-ray computed tomography (SPCCT), for comprehensive tissue engineering scaffold (TES) monitoring. PCL filament with homogeneous BiO nanoparticle (NP) dispersion (0.
View Article and Find Full Text PDFPurpose: The purpose of this study was to compare lung image quality obtained with ultra-high resolution (UHR) spectral photon-counting CT (SPCCT) with that of dual-layer CT (DLCT), at standard and low dose levels using an image quality phantom and an anthropomorphic lung phantom.
Methods: An image quality phantom was scanned using a clinical SPCCT prototype and an 8 cm collimation DLCT from the same manufacturer at 10 mGy. Additional acquisitions at 6 mGy were performed with SPCCT only.
Article Synopsis
- The study aimed to assess the effectiveness of spectral photon-counting computed tomography (SPCCT) compared to conventional CT for evaluating coronary artery blockages in high-risk patients.
- It involved 26 patients who underwent both types of scans before invasive coronary angiography (ICA) to confirm findings.
- Results showed that SPCCT had higher accuracy, sensitivity, and specificity for detecting stenosis, reclassifying a significant number of cases compared to conventional CT.
Background: Recent advancements in anomaly detection have paved the way for novel radiological reading assistance tools that support the identification of findings, aimed at saving time. The clinical adoption of such applications requires a low rate of false positives while maintaining high sensitivity.
Purpose: In light of recent interest and development in multi pathology identification, we present a novel method, based on a recent contrastive self-supervised approach, for multiple chest-related abnormality identification including low lung density area ("LLDA"), consolidation ("CONS"), nodules ("NOD") and interstitial pattern ("IP").