To evaluate the role of 2D myocardial strain (rate) imaging in the detection of early subclinical cardiotoxicity in breast cancer survivors treated with an anthracycline-based chemotherapeutic regimen. 57 adult breast cancer survivors were analyzed 1 year after therapy. All patients underwent biomarker analysis and 2D echocardiography consisting of conventional echocardiographic and strain (rate) parameters. Conventional echocardiographic values were normal. Global longitudinal strain was normal, but 18 % of patients showed a >2 SD decrease when individually compared to reference values. This subgroup showed a decrease in end-systolic and end-diastolic volumes and an increase in left ventricular mass. Radial and circumferential strain rates were significantly decreased in the whole study group. 2D myocardial strain (rate) imaging showed abnormalities in breast cancer survivors, while conventional echocardiographic values remained normal, rendering 2D myocardial strain (rate) imaging an interesting tool for the early detection of anthracycline-induced cardiotoxicity.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1007/s10549-014-2997-4 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
NGR-poly(2-ethyl-2-oxazoline)-cholesteryl methyl carbonate enhances the antitumor effect of quercetin liposomes in triple-negative breast cancer.
Pharm Dev Technol
January 2025
Department of Pharmacy, School of Chemistry and Chemical Engineering, Liaoning Normal University, Dalian 116029, China.
In this paper, the pH-sensitive targeting functional material NGR-poly(2-ethyl-2-oxazoline)-cholesteryl methyl carbonate (NGR-PEtOz-CHMC, NPC) modified quercetin (QUE) liposomes (NPC-QUE-L) was constructed. The structure of NPC was confirmed by infrared spectroscopy (IR) and nuclear magnetic resonance hydrogen spectrum (H-NMR). Pharmacokinetic results showed that the accumulation of QUE in plasma of the NPC-QUE-L group was 1.
View Article and Find Full Text PDFUsing system dynamics modeling approach to strengthen health systems to combat cancer: a systematic literature review.
J Med Econ
January 2025
UNESCO-TWAS, The World Academy of Sciences, Trieste, Italy.
Aim: Dynamic cancer control is a current health system priority, yet methods for achieving it are lacking. This study aims to review the application of system dynamics modeling (SDM) on cancer control and evaluate the research quality.
Methods: Articles were searched in PubMed, Web of Science, and Scopus from the inception of the study to November 15th, 2023.
Artificial Intelligence Predicts Multiclass Molecular Signatures and Subtypes Directly From Breast Cancer Histology: a Multicenter Retrospective Study.
Int J Surg
January 2025
Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China.
Detection of biomarkers of breast cancer incurs additional costs and tissue burden. We propose a deep learning-based algorithm (BBMIL) to predict classical biomarkers, immunotherapy-associated gene signatures, and prognosis-associated subtypes directly from hematoxylin and eosin stained histopathology images. BBMIL showed the best performance among comparative algorithms on the prediction of classical biomarkers, immunotherapy related gene signatures, and subtypes.
View Article and Find Full Text PDFSarcopenia as a Prognostic Factor and Multimodal Interventions in Breast Cancer.
Int J Gen Med
December 2024
Department of Thyroid and Breast Surgery, Quzhou People's Hospital, Quzhou, 324000, People's Republic of China.
Objective: This study aims to demonstrate the impact of sarcopenia on the prognosis of early breast cancer and its role in early multimodal intervention.
Methods: The clinical data of patients (n=285) subjected to chemotherapy for early-stage breast cancer diagnosed pathologically between January 1, 2016, and December 31, 2020, in our hospital were retrospectively analyzed. Accordingly, the recruited subjects were divided into sarcopenia (n=85) and non-sarcopenia (n=200) groups according to CT diagnosis correlating with single-factor and multifactorial logistic regression analyses.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!