Objective: In this study, we aimed to utilize computed tomography (CT)-derived radiomics and various machine learning approaches to differentiate between invasive mucinous adenocarcinoma (IMA) and invasive non-mucinous adenocarcinoma (INMA) preoperatively in solitary pulmonary nodules (SPN) ≤3 cm.
Methods: A total of 538 patients with SPNs measuring ≤3 cm were enrolled, categorized into either the IMA group (n = 50) or INMA group (n = 488) based on postoperative pathology. Radiomic features were extracted from non-contrast-enhanced CT scans and identified using the least absolute shrinkage and selection operator (LASSO) algorithm.
To evaluate the diagnostic performance of dual-layer spectral detector CT for differentiation of breast cancer molecular subtypes. This study was done in a retrospective approach including 104 female patients histopathologically proven to have breast cancer. These patients underwent chest arterial and venous phase dual-layer SDCT.
View Article and Find Full Text PDFBackground: The identification of anthracycline-induced cardiotoxicity holds significant importance in guiding subsequent treatment strategies, and recent research has demonstrated the efficacy of cardiac magnetic resonance (CMR) global strain analysis for its diagnosis. On the other hand, it is noteworthy that abnormal global myocardial strain may exhibit a temporal delay due to different cardiac movement in each segment of the left ventricle. To address this concern, this study aims to assess the diagnostic utility of CMR segmental strain analysis as an early detection method for cardiotoxicity.
View Article and Find Full Text PDFObjectives: To evaluate the early prevalence of anthracycline-induced cardiotoxicity (AIC) and anthracycline-induced liver injury (AILI) using T2 and T2* mapping and to explore their correlations.
Materials And Methods: The study included 17 cardiotoxic rabbits that received weekly injections of doxorubicin and magnetic resonance imaging (MRI) every 2 weeks for 10 weeks. Cardiac function and T2 and T2* values were measured on each period.
Purpose: This study systematically evaluated the potential influences of diffusion- weighted imaging (DWI) on the initial diagnosis, clinical decision making and diagnostic accuracy of ovarian cancer in the follow-up period.
Methods: Literature on the correlation between DWI and diagnosis of ovarian cancer were searched from PubMed, Embase, Cochrane Library, and Web of Science published before January 1, 2019. References in enrolled eligible literature were manually reviewed.