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1.
IEEE Trans Med Imaging ; 40(12): 3543-3554, 2021 12.
Article in English | MEDLINE | ID: mdl-34138702

ABSTRACT

The emergence of deep learning has considerably advanced the state-of-the-art in cardiac magnetic resonance (CMR) segmentation. Many techniques have been proposed over the last few years, bringing the accuracy of automated segmentation close to human performance. However, these models have been all too often trained and validated using cardiac imaging samples from single clinical centres or homogeneous imaging protocols. This has prevented the development and validation of models that are generalizable across different clinical centres, imaging conditions or scanner vendors. To promote further research and scientific benchmarking in the field of generalizable deep learning for cardiac segmentation, this paper presents the results of the Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation (M&Ms) Challenge, which was recently organized as part of the MICCAI 2020 Conference. A total of 14 teams submitted different solutions to the problem, combining various baseline models, data augmentation strategies, and domain adaptation techniques. The obtained results indicate the importance of intensity-driven data augmentation, as well as the need for further research to improve generalizability towards unseen scanner vendors or new imaging protocols. Furthermore, we present a new resource of 375 heterogeneous CMR datasets acquired by using four different scanner vendors in six hospitals and three different countries (Spain, Canada and Germany), which we provide as open-access for the community to enable future research in the field.


Subject(s)
Heart , Magnetic Resonance Imaging , Cardiac Imaging Techniques , Heart/diagnostic imaging , Humans
2.
J Cardiovasc Echogr ; 30(Suppl 1): S33-S37, 2020 Apr.
Article in English | MEDLINE | ID: mdl-32566464

ABSTRACT

Nonvalvular atrial fibrillation (AF) is a relatively frequent arrhythmia in cancer patients; it is possibly due to direct effect of cancer or consequence of cancer therapies. AF creates important problems for both therapeutic management and prognosis in cancer patients. The anticoagulation of cancer patients presenting AF is a main issue because of the difficult balance between thromboembolic and bleeding risks, both elevated in this clinical setting. A comprehensive echo Doppler examination is mandatory to identify the eventual sources of emboli in left atrial (LA) cavity, mainly the transesophageal echocardiography (TEE), but also to predict the subsequent development of heart failure. This evaluation is particularly important to graduate anticoagulation and to prevent and manage symptoms/signs of heart failure. The performance of a TEE precardioversion is highly encouraged to detect possible thrombi in LA appendage. A careful assessment of LA size (LA volume index) and function (LA emptying fraction and/or LA strain) should always be planned to predict the possible recurrence of AF paroxysmal episodes. This is in fact a key action, not only from the cardiologic point of view but also for the oncologic perspectives in individual situations. Patients with larger left atrium and more impaired LA function should be addressed toward a less aggressive cancer treatment, with drugs which are not associated or are poorly related with the risk of AF development. A correct and comprehensive echocardiographic assessment could even induce the oncologist to change the cancer management balancing the oncologic and the cardiac risk.

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