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Objective: This study aims to assess the feasibility of "double-low," low radiation dosage and low contrast media dosage, CT pulmonary angiography (CTPA) based on deep-learning image reconstruction (DLIR) algorithms.
Materials And Methods: One hundred consecutive patients (41 females; average age 60.9 years, range 18-90) were prospectively scanned on multi-detector CT systems. Fifty patients in the conventional-dose group (CD group) underwent CTPA with 100 kV protocol using the traditional iterative reconstruction algorithm, and 50 patients in the low-dose group (LD group) underwent CTPA with a 70 kVp DLIR protocol. Radiation and contrast agent doses were recorded and compared between groups. Objective parameters were measured and compared. Two radiologists evaluated images for overall image quality, artifacts, and image contrast separately on a 5-point scale. The furthest visible branches were compared between groups.
Results: Compared to the control group, the study group reduced the dose-length product by 80.3% (p < 0.01) and the contrast media dose by 33.3%. CT values, SD values, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) showed no statistically significant differences (all p > 0.05) between the LD and CD groups. The overall image quality scores were comparable between the LD and CD groups (p > 0.05), with good in-reader agreement (k = 0.75). More peripheral pulmonary vessels could be assessed in the LD group compared with the CD group.
Conclusion: 70 kVp combined with DLIR reconstruction for CTPA can further reduce radiation and contrast agent dose while maintaining image quality and increasing the visibility on the pulmonary artery distal branches.
Key Points: Question Elevated radiation exposure and substantial doses of contrast media during CT pulmonary angiography (CTPA) augment patient risks. Findings The "double-low" CT pulmonary angiography protocol can diminish radiation doses by 80.3% and minimize contrast doses by one-third while maintaining image quality. Clinical relevance With deep learning algorithms, we confirmed that CTPA images maintained excellent quality despite reduced radiation and contrast dosages, helping to reduce radiation exposure and kidney burden on patients. The "double-low" CTPA protocol, complemented by deep learning image reconstruction, prioritizes patient safety.
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http://dx.doi.org/10.1007/s00330-025-11764-1 | DOI Listing |
Cureus
August 2025
Division of Thoracic and Cardiovascular Surgery, Niigata University Graduate School of Medical and Dental Sciences, Niigata, JPN.
Cerebral infarction is a rare but serious complication after pulmonary resection for lung cancer. A 78-year-old man with hypertension and diabetes underwent video-assisted thoracoscopic right middle lobectomy for stage IA2 adenocarcinoma. On postoperative day 1, he developed acute right hemiparesis and motor aphasia.
View Article and Find Full Text PDFJ Intensive Care Med
September 2025
Departamento de Medicina Intensiva, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile.
PurposeAn elevated ventilatory ratio (VR) and acute cor pulmonale (ACP) are associated with mortality in ARDS patients. The primary aim of this study was to assess the association between VR and ACP in patients with COVID-19-related ARDS (C-ARDS). The secondary objectives were to analyze the association between VR and ICU mortality, describe VR temporal behavior in survivors and non-survivors, and evaluate the association between VR and pulmonary embolism.
View Article and Find Full Text PDFJ Thorac Imaging
September 2025
Department of Radiology, the Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University.
Purpose: To establish an explainable machine learning (ML) approach using patient-related and noncontrast chest CT-derived features to predict the contrast material arrival time (TARR) in CT pulmonary angiography (CTPA).
Materials And Methods: This retrospective study included consecutive patients referred for CTPA between September 2023 to October 2024. Sixteen clinical and 17 chest CT-derived parameters were used as inputs for the ML approach, which employed recursive feature elimination for feature selection and XGBoost with SHapley Additive exPlanations (SHAP) for explainable modeling.
Front Med (Lausanne)
August 2025
Department of Radiology, Qilu Hospital of Shandong University, Jinan, Shandong, China.
Background: Abernethy malformation is a rare condition in which the portomesenteric blood drains into systemic circulation, bypassing the liver. With advancements in imaging techniques and increased awareness of this malformation, there has been a growing number of reported cases in recent years. We present a case report and literature review in an effort to further the understanding of Abernethy malformation.
View Article and Find Full Text PDFEur Heart J Cardiovasc Imaging
September 2025
Bosch Health Campus, Robert Bosch Hospital, Department of Cardiology and Angiology, Stuttgart, Germany.
Aims: For many years, visual assessment has been the mainstay of detecting obstructive coronary artery disease (CAD) by stress perfusion cardiovascular magnetic resonance (S-CMR). Recently, fully automated quantitative assessment of myocardial blood flow (MBF) has been introduced. The value of MBF quantification in patients with coronary chronic total occlusion (CTO) is unknown.
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