Objective: The aim of this study was to investigate the imaging features of salivary duct carcinoma (SDC) with multiphase contrast-enhanced computed tomography (CECT) and to compare them with those of mucoepidermoid carcinoma (MEC), adenoid cystic carcinoma (ACC), and acinic cell carcinoma.
Study Design: A total of 63 patients with histologically diagnosed salivary gland malignancies underwent preoperative multiphase CECT. Clinical information, location, size, mass pattern, enhancement pattern, borders, invasion of adjacent tissues, and lymph node metastasis were evaluated. Computed tomography (CT) number attenuation patterns were calculated.
Results: SDCs were significantly more common in males and in the parotid gland (P ≤ .018). They were more likely to invade into adjacent tissues and metastasize to lymph nodes (P ≤ .032). Six SDCs (66.7%) had comedonecrosis, as detected on histopathologic examination, and 3 lesions presented cribriform necrosis on CECT. CT numbers during delayed-phase scanning were significantly higher in SDC than in ACC (P = .031). Significant differences were discovered between MEC and ACC for CT numbers during arterial-phase scanning (P = .047) and in the ratio of CT numbers (P = .018).
Conclusions: SDC exhibits some specific CT features, and multiphase CECT imaging is useful in the differential diagnosis of salivary gland malignancies.
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http://dx.doi.org/10.1016/j.oooo.2019.05.011 | DOI Listing |
Anesth Analg
February 2025
SC Terapia Intensiva Neurochirurgica, Ospedale San Carlo Borromeo, ASST Santi Paolo e Carlo, Milano, Italy.
Background: Computed tomography (CT)-derived low muscle mass is associated with adverse outcomes in critically ill patients. Muscle ultrasound is a promising strategy for quantitating muscle mass. We evaluated the association between baseline ultrasound rectus femoris cross-sectional area (RF-CSA) and intensive care unit (ICU) mortality.
View Article and Find Full Text PDF3D Print Med
January 2025
Department of Surgical & Interventional Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Background: Penile implant surgery is the standard surgical treatment for end-stage erectile dysfunction. However, the growing complexity of modern high-tech penile prostheses has increased the demand for more practical training opportunities. The most advanced contemporary training methods involve simulation training using cadavers, with costs exceeding $5,000 per cadaver, inclusive of biohazard fees.
View Article and Find Full Text PDFRheumatol Int
January 2025
Copenhagen Research Center for Autoimmune Connective Tissue Diseases (COPEACT), Copenhagen University Hospital, Rigshospitalet, Denmark.
To investigate if progression of coronary artery calcification (CAC) in patients with systemic lupus erythematosus (SLE) is associated with renal and traditional cardiovascular risk factors as well as incidence of myocardial infarctions. CAC progression was evaluated by cardiac computed tomography (CT) at baseline and after 5 years. Multivariable Poisson regression was applied to investigate associations between CAC progression and baseline values for traditional cardiovascular risk factors, CAC, SLE disease duration, lupus nephritis, and renal function.
View Article and Find Full Text PDFInt J Cardiovasc Imaging
January 2025
Artificial Intelligence Center, China Medical University Hospital, China Medical University, Taichung, Taiwan.
Coronary artery calcification (CAC) is a key marker of coronary artery disease (CAD) but is often underreported in cancer patients undergoing non-gated CT or PET/CT scans. Traditional CAC assessment requires gated CT scans, leading to increased radiation exposure and the need for specialized personnel. This study aims to develop an artificial intelligence (AI) method to automatically detect CAC from non-gated, freely-breathing, low-dose CT images obtained from positron emission tomography/computed tomography scans.
View Article and Find Full Text PDFClin Oral Investig
January 2025
Department of Periodontology, Semmelweis University, Budapest, Hungary.
Objectives: To investigate the performance of a deep learning (DL) model for segmenting cone-beam computed tomography (CBCT) scans taken before and after mandibular horizontal guided bone regeneration (GBR) to evaluate hard tissue changes.
Materials And Methods: The proposed SegResNet-based DL model was trained on 70 CBCT scans. It was tested on 10 pairs of pre- and post-operative CBCT scans of patients who underwent mandibular horizontal GBR.
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