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Objective: Among the advancements in computed tomography (CT) technology, photon-counting computed tomography (PCCT) stands out as a significant innovation, providing superior spectral imaging capabilities while simultaneously reducing radiation exposure. Its long-term stability is important for clinical care, especially longitudinal studies, but is currently unknown. This study sets out to comprehensively analyze the long-term stability of a first-generation clinical PCCT scanner.
Methods: Over a two-year period, from November 2021 to November 2023, we conducted weekly identical experiments utilizing the same multi-energy CT protocol. Throughout this period, notable software and hardware modifications were meticulously recorded. Various tissue-mimicking inserts were scanned weekly to rigorously assess the stability of Hounsfield Units (HU) and image noise in Virtual Monochromatic Images (VMIs) and iodine density maps.
Results: Spectral results consistently demonstrated the quantitative stability of PCCT. VMIs exhibited stable HU values, such as variation in relative error for VMI 70 keV measuring 0.11% and 0.30% for single-source and dual-source modes, respectively. Similarly, noise levels remained stable with slight fluctuations linked to software changes for VMI 40 and 70 keV that corresponded to changes of 8 and 1 HU, respectively. Furthermore, iodine density quantification maintained stability and showed significant improvement with software and hardware changes, especially in dual-source mode with nominal errors decreasing from 1.44 to 0.03 mg/mL. Conclusion This study provides the first long-term reproducibility assessment of quantitative PCCT imaging, highlighting its potential for the clinical arena.
Key Points: Photon-counting CT (PCCT) provides critical spectral imaging for improved diagnostic accuracy, but its long-term quantitative stability over time is still unknown. The clinical PCCT system demonstrated stable Hounsfield Units (HU) and image noise over two years, ensuring reliable quantitative imaging and improving diagnostic accuracy. This study showcased the exceptional value of PCCT in diagnostic radiology, particularly for its application in longitudinal studies.
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http://dx.doi.org/10.1101/2024.06.05.24308046 | DOI Listing |
Ann Intern Med
September 2025
Department of Medicine, St Michael's Hospital, University of Toronto, Toronto, Ontario, Canada (J.G.R.).
Background: Animal studies show ovarian follicle damage and mutagenesis after ionizing radiation exposure. Computed tomography (CT) imaging is commonly done outside pregnancy, but risks to future pregnancy are unknown.
Objective: To evaluate the risk for spontaneous pregnancy loss and congenital anomalies in offspring of women exposed to CT ionizing radiation before conception.
Ann Intern Med
September 2025
Associate Professor of Radiology, Penn State Health, Hershey, Pennsylvania.
J Infect Dev Ctries
August 2025
Department of Emergency, Changhai Hospital, Naval Medical University, Shanghai, China.
Introduction: Nocardia spp. are Gram-positive, aerobic actinomycetes, which can cause pulmonary, primary cutaneous, and lymphocutaneous infections. However, severe pneumonia caused by Nocardia otitidiscaviarum has rare reported.
View Article and Find Full Text PDFPLoS One
September 2025
Department of Radiology, the Third Affiliated Hospital of Kunming Medical University, Yunnan, Kunming, China.
Purpose: Bronchiolar adenoma (BA) is a rare benign pulmonary neoplasm originating from the bronchial mucosal epithelium and mimics lung adenocarcinoma (LAC) both radiographically and microscopically. This study aimed to develop a nomogram for distinguishing BA from LAC by integrating clinical characteristics and artificial intelligence (AI)-derived histogram parameters across two medical centers.
Methods: This retrospective study included 215 patients with diagnoses confirmed by postoperative pathology from two medical centers.
JAMA Neurol
September 2025
Department of Radiology, University of Washington, Seattle.
Importance: Recent longitudinal studies in patients with unruptured intracranial aneurysms (UIAs) suggested that aneurysm wall enhancement (AWE) on magnetic resonance imaging (MRI) predicts growth and rupture. However, because these studies were limited by small sample size and short follow-up duration, it remains unclear whether this radiological biomarker has predictive value for UIA instability.
Objective: To determine the 4-year risk of instability of UIAs with AWE and investigate whether AWE is an independent predictor of UIA instability.