Takanori Masuda, Yasutaka Baba, Takeshi Nakaura, Yoshinori Funama, Tomoyasu Sato, Shouko Masuda, Rumi Gotanda, Keiko Arao, Hiromasa Imaizumi, Shinichi Arao, Atsushi Ono, Junichi Hiratsuka, Kazuo Awai
To predict endoleaks after thoracic endovascular aneurysm repair (TEVAR) we submitted patient characteristics and vessel features observed on pre- operative computed tomography angiography (CTA) to machine-learning. We evaluated 1-year follow-up CT scans (arterial and delayed phases) in patients who underwent TEVAR for the presence or absence of an endoleak. We evaluated the effect of machine learning of the patient age, sex, weight, and height, plus 22 vascular features on the ability to predict post-TEVAR endoleaks...
May 2, 2024: Physical and engineering sciences in medicine