Enabling Automated Device Size Selection for Transcatheter Aortic Valve Implantation
المؤلفون المشاركون
De Beule, Matthieu
Astudillo, Patricio
Mortier, Peter
De Backer, Ole
de Jaegere, Peter
Dambre, Joni
Bosmans, Johan M.
المصدر
Journal of Interventional Cardiology
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-7، 7ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-11-03
دولة النشر
مصر
عدد الصفحات
7
التخصصات الرئيسية
الملخص EN
The number of transcatheter aortic valve implantation (TAVI) procedures is expected to increase significantly in the coming years.
Improving efficiency will become essential for experienced operators performing large TAVI volumes, while new operators will require training and may benefit from accurate support.
In this work, we present a fast deep learning method that can predict aortic annulus perimeter and area automatically from aortic annular plane images.
We propose a method combining two deep convolutional neural networks followed by a postprocessing step.
The models were trained with 355 patients using modern deep learning techniques, and the method was evaluated on another 118 patients.
The method was validated against an interoperator variability study of the same 118 patients.
The differences between the manually obtained aortic annulus measurements and the automatic predictions were similar to the differences between two independent observers (paired diff.
of 3.3 ± 16.8 mm2 vs.
1.3 ± 21.1 mm2 for the area and a paired diff.
of 0.6 ± 1.7 mm vs.
0.2 ± 2.5 mm for the perimeter).
The area and perimeter were used to retrieve the suggested prosthesis sizes for the Edwards Sapien 3 and the Medtronic Evolut device retrospectively.
The automatically obtained device size selections accorded well with the device sizes selected by operator 1.
The total analysis time from aortic annular plane to prosthesis size was below one second.
This study showed that automated TAVI device size selection using the proposed method is fast, accurate, and reproducible.
Comparison with the interobserver variability has shown the reliability of the strategy, and embedding this tool based on deep learning in the preoperative planning routine has the potential to increase the efficiency while ensuring accuracy.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Astudillo, Patricio& Mortier, Peter& Bosmans, Johan M.& De Backer, Ole& de Jaegere, Peter& De Beule, Matthieu…[et al.]. 2019. Enabling Automated Device Size Selection for Transcatheter Aortic Valve Implantation. Journal of Interventional Cardiology،Vol. 2019, no. 2019, pp.1-7.
https://search.emarefa.net/detail/BIM-1181225
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Astudillo, Patricio…[et al.]. Enabling Automated Device Size Selection for Transcatheter Aortic Valve Implantation. Journal of Interventional Cardiology No. 2019 (2019), pp.1-7.
https://search.emarefa.net/detail/BIM-1181225
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Astudillo, Patricio& Mortier, Peter& Bosmans, Johan M.& De Backer, Ole& de Jaegere, Peter& De Beule, Matthieu…[et al.]. Enabling Automated Device Size Selection for Transcatheter Aortic Valve Implantation. Journal of Interventional Cardiology. 2019. Vol. 2019, no. 2019, pp.1-7.
https://search.emarefa.net/detail/BIM-1181225
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1181225
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر