Purpose: A prototype QC phantom system and analysis process were developed to characterize the spectral capabilities of a fast kV-switching dual-energy computed tomography (DECT) scanner. This work addresses the current lack of quantitative oversight for this technology, with the goal of identifying relevant scan parameters and test metrics instrumental to the development of a dual-energy quality control (DEQC).
Methods: A prototype elliptical phantom (effective diameter: 35 cm) was designed with multiple material inserts for DECT imaging. Inserts included tissue equivalent and material rods (including iodine and calcium at varying concentrations). The phantom was scanned on a fast kV-switching DECT system using 16 dual-energy acquisitions (CTDIvol range: 10.3-62 mGy) with varying pitch, rotation time, and tube current. The circular head phantom (22 cm diameter) was scanned using a similar protocol (12 acquisitions; CTDIvol range: 36.7-132.6 mGy). All acquisitions were reconstructed at 50, 70, 110, and 140 keV and using a water-iodine material basis pair. The images were evaluated for iodine quantification accuracy, stability of monoenergetic reconstruction CT number, noise, and positional constancy. Variance component analysis was used to identify technique parameters that drove deviations in test metrics. Variances were compared to thresholds derived from manufacturer tolerances to determine technique parameters that had a nominally significant effect on test metrics.
Results: Iodine quantification error was largely unaffected by any of the technique parameters investigated. Monoenergetic HU stability was found to be affected by mAs, with a threshold under which spectral separation was unsuccessful, diminishing the utility of DECT imaging. Noise was found to be affected by CTDIvol in the DEQC body phantom, and CTDIvol and mA in the DEQC head phantom. Positional constancy was found to be affected by mAs in the DEQC body phantom and mA in the DEQC head phantom.
Conclusion: A streamlined scan protocol was developed to further investigate the effects of CTDIvol and rotation time while limiting data collection to the DEQC body phantom. Further data collection will be pursued to determine baseline values and statistically based failure thresholds for the validation of long-term DECT scanner performance.
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http://dx.doi.org/10.1002/mp.12812 | DOI Listing |
Chem Pharm Bull (Tokyo)
January 2025
Drug Discovery Research Department, Kyoto Pharmaceutical Industries, Ltd.
Osteoporosis is caused by an imbalance between bone resorption and formation, which decreases bone mass and strength and increases the risk of fracture. Therefore, osteoporosis is treated with oral resorption inhibitors, such as bisphosphonates, and parenteral osteogenic drugs, including parathyroid hormone and antisclerostin antibodies. However, orally active osteogenic drugs have not yet been developed.
View Article and Find Full Text PDFPhys Imaging Radiat Oncol
October 2024
Université Paris-Saclay, Gustave Roussy, Inserm, Molecular Radiotherapy and Therapeutic Innovation, U1030, 94800 Villejuif, France.
Background And Purpose: Deep-learning-based automatic segmentation is widely used in radiation oncology to delineate organs-at-risk. Dual-energy CT (DECT) allows the reconstruction of enhanced contrast images that could help with manual and auto-delineation. This paper presents a performance evaluation of a commercial auto-segmentation software on image series generated by a DECT.
View Article and Find Full Text PDFCurr Obes Rep
January 2025
Metabolism and Body Composition, Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA.
Background: Recent technological advances have introduced novel methods for measuring body composition, each with unique benefits and limitations. The choice of method often depends on the trade-offs between accuracy, cost, participant burden, and the ability to measure specific body composition compartments.
Objective: To review the considerations of cost, accuracy, portability, and participant burden in reference and emerging body composition assessment methods, and to evaluate their clinical applicability.
Diagnostics (Basel)
December 2024
Department of Nuclear Medicine and Molecular Imaging, Institut de Cancérologie de Strasbourg Europe (ICANS), University Hospitals of Strasbourg, University of Strasbourg, 67200 Strasbourg, France.
Patients diagnosed with multiple endocrine neoplasia type-1 (MEN1) often initially present with primary hyperparathyroidism (pHPT), and typically undergo surgical intervention. While laboratory tests are fundamental for diagnosis, imaging is crucial for localizing pathological parathyroids to aid in precise surgical planning. In this pictorial review, we will begin by comprehensively examining key imaging techniques and their established protocols, evaluating their effectiveness in detecting abnormal parathyroid glands.
View Article and Find Full Text PDFInsights 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.
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