Rationale And Objectives: This study aimed to determine the optimal tube potential for unenhanced chest computed tomographies (CTs) with age-related phantoms.
Materials And Methods: Three physical anthropomorphic phantoms (newborn, 5-year-old child, and adult) were scanned on a third-generation dual-source CT using CAREkV in semi-mode and CAREDose4D (ref. KV: 120; ref. mAs 50). Scans were performed with all available tube potentials (70-150 kV and Sn150 kV). The lowest volume computed tomography dose index (CTDI) was selected to perform additional Sn100-kV scans with matched and half (Sn100-half) CTDI value. Image quality was evaluated on the basis of contrast-to-noise ratio (CNR).
Results: For the newborn phantom, 70-110 kV was selected as the optimal range (0.36-0.37 mGy). Using Sn150 kV led to an increase in radiation dose (0.75 mGy) without improving CNR (96.9 vs 101.5). Sn100-half showed a decrease in CNR (73.1 vs 101.5). The lowest CTDI for the child phantom was achieved between 100 and 120 kV (0.78-0.80 mGy). Using Sn150 kV increased radiation dose (1.02 mGy) without improvement of CNR (92.4 vs 95.8). At Sn100-half CNR was decreased (61.4 vs 95.8). For adults, 140 and 150 kV revealed the lowest CTDI (2.68 and 2.67 mGy). The Sn150 kV scan delivered comparable CNR (54.4 vs 56.6), but a lower CTDI (2.08 mGy). At Sn100-half CNR was comparable to the 150 kV scan (58.1 vs 56.6).
Conclusion: Unenhanced chest CT performed at 100 kV or 150 kV with tin filtration enables radiation dose reduction for the adult phantom, but not for the pediatric phantoms.
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http://dx.doi.org/10.1016/j.acra.2017.08.011 | DOI Listing |
Insights Imaging
January 2025
Department of Orthopaedics, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, China.
Introduction: A large number of middle-aged and elderly patients have an insufficient understanding of osteoporosis and its harm. This study aimed to establish and validate a convolutional neural network (CNN) model based on unenhanced chest computed tomography (CT) images of the vertebral body and skeletal muscle for opportunistic screening in patients with osteoporosis.
Materials And Methods: Our team retrospectively collected clinical information from participants who underwent unenhanced chest CT and dual-energy X-ray absorptiometry (DXA) examinations between January 1, 2022, and December 31, 2022, at four hospitals.
J Comput Assist Tomogr
November 2024
From the Department of Radiology and Radiological Science, Divisions of Cardiovascular and Thoracic Imaging, Medical University of South Carolina. Charleston, SC.
Background: The latest generation of computed tomography (CT) systems based on photon-counting detector promises significant improvements in several clinical applications, including chest imaging.
Purpose: The aim of the study is to evaluate the image quality of ultra-high-resolution (UHR) photon-counting detector CT (PCD-CT) of the lung using four sharp reconstruction kernels.
Material And Methods: This retrospective study included 25 patients (11 women and 14 men; median age, 71 years) who underwent unenhanced chest CT from April to May 2023.
Cureus
December 2024
Radiology, Azadi Teaching Hospital, Duhok, IRQ.
Background CT is among the most widely used diagnostic imaging techniques worldwide, providing significant advantages and invaluable diagnostic insights for detecting a wide range of diseases across various organs. However, it involves exposing patients to relatively high levels of ionizing radiation. Objective This study aims to document the radiation doses from chest CT scans performed at Azadi Teaching Hospital in Duhok Province and compare them with those recorded at the 3-Tesla Center for Advanced MRI and CT Scanning, also located in Duhok, using diagnostic reference levels (DRLs) as a benchmark.
View Article and Find Full Text PDFEur J Radiol
December 2024
Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea.
Objective: To assess whether CT style conversion between different CT vendors using a routable generative adversarial network (RouteGAN) could minimize variation in ILD quantification, resulting in improved functional correlation of quantitative CT (QCT) measures.
Methods: Patients with idiopathic pulmonary fibrosis (IPF) who underwent unenhanced chest CTs with vendor A and a pulmonary function test (PFT) were retrospectively evaluated. As deep-learning based ILD quantification software was mainly developed using vendor B CT, style-converted images from vendor A to B style were generated using RouteGAN.
Eur J Radiol
December 2024
The First Clinical College of Jinan University, Guangzhou 510630, Guangdong, China; Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China. Electronic address:
Purpose: To develop a nomogram based on liver CT and clinical features to preoperatively predict lung metastasis (LM) secondary to hepatic alveolar echinococcosis (HAE).
Methods: A total of 291 consecutive HAE patients from Institution A undergoing preoperative abdominal contrast-enhanced CT and chest unenhanced CT were retrospectively reviewed, and were randomly divided into the training and internal validation sets at the 7:3 ratio. 82 consecutive patients from Institution B were enrolled as an external validation set.
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