Objectives: Dual-source dual-energy CT (DECT) facilitates reconstruction of virtual non-contrast images from contrast-enhanced scans within a limited field of view. This study evaluates the replacement of true non-contrast acquisition with virtual non-contrast reconstructions and investigates the limitations of dual-source DECT in obese patients.
Materials And Methods: A total of 253 oncologic patients (153 women; age 64.5 ± 16.2 years; BMI 26.6 ± 5.1 kg/m) received both multi-phase single-energy CT (SECT) and DECT in sequential staging examinations with a third-generation dual-source scanner. Patients were allocated to one of three BMI clusters: non-obese: <25 kg/m ( = 110), pre-obese: 25-29.9 kg/m ( = 73), and obese: >30 kg/m ( = 70). Radiation dose and image quality were compared for each scan. DECT examinations were evaluated regarding liver coverage within the dual-energy field of view.
Results: While arterial contrast phases in DECT were associated with a higher CTDI than in SECT (11.1 vs. 8.1 mGy; < 0.001), replacement of true with virtual non-contrast imaging resulted in a considerably lower overall dose-length product (312.6 vs. 475.3 mGy·cm; < 0.001). The proportion of DLP variance predictable from patient BMI was substantial in DECT (R = 0.738) and SECT (R = 0.620); however, DLP of SECT showed a stronger increase in obese patients ( < 0.001). Incomplete coverage of the liver within the dual-energy field of view was most common in the obese subgroup (17.1%) compared with non-obese (0%) and pre-obese patients (4.1%).
Conclusion: DECT facilitates a 30.8% dose reduction over SECT in abdominal oncologic staging examinations. Employing dual-source scanner architecture, the risk for incomplete liver coverage increases in obese patients.
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http://dx.doi.org/10.3390/diagnostics13091558 | DOI Listing |
PLoS One
January 2025
Department of Radiation Oncology, Seoul National University Hospital, Seoul, Republic of Korea.
This paper presents a novel approach for generating virtual non-contrast planning computed tomography (VNC-pCT) images from contrast-enhanced planning CT (CE-pCT) scans using a deep learning model. Unlike previous studies, which often lacked sufficient data pairs of contrast-enhanced and non-contrast CT images, we trained our model on dual-energy CT (DECT) images, using virtual non-contrast CT (VNC CT) images as outputs instead of true non-contrast CT images. We used a deterministic method to convert CE-pCT images into pseudo DECT images for model application.
View Article and Find Full Text PDFInsights Imaging
January 2025
Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China.
Objectives: This study aimed to investigate the diagnostic value of spectral parameters of dual-layer spectral detector computed tomography (DLCT) in distinguishing between low- and high-grade bladder cancer (BCa).
Methods: This single-center retrospective study included pathologically confirmed BCa patients who underwent preoperative contrast-enhanced DLCT. Patients were divided into low- and high-grade groups based on pathology.
Eur Radiol
January 2025
Diagnostic and Interventional Radiology, Heidelberg University Hospital, Heidelberg, Germany.
Sci Rep
December 2024
Health & Medical Equipment Business, Samsung Electronics Co., Ltd, 8, Gumi-ro, Bundang-gu, Seongnam- si, 13638, Gyeonggi-do, Republic of Korea.
The photon-counting detector computed tomography (PCD-CT) is a promising new technology that provides more spectral information in medical imaging. PCD-CT enables bedside imaging in the neuro intensive care unit (neuro ICU) for patients with life-threatening conditions such as brain hemorrhage and ischemic stroke. The primary purpose of this study is to evaluate a multi-material decomposition algorithm available on PCD-CT, dubbed MD Plus, to differentiate between contrast agent and hemorrhage in hyperdense lesions.
View Article and Find Full Text PDFInt J Cardiovasc Imaging
December 2024
Department of Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Str. 62, 50937, Cologne, Germany.
To evaluate dual-layer dual-energy computed tomography (dlDECT)-based characterization of thrombus composition for differentiation of acute pulmonary embolism (PE) and chronic thromboembolic pulmonary hypertension (CTEPH). This retrospective single center cohort study included 49 patients with acute PE and 33 patients with CTEPH who underwent CT pulmonary angiography on a dlDECT from 06/2016 to 06/2022. Conventional images), material specific images (virtual non-contrast [VNC], iodine density overlay [IDO], electron density [ED]), and virtual monoenergetic images (VMI) were analyzed.
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