Automatic Assessment of Transcatheter Aortic Valve Implantation Results on Four-Dimensional Computed Tomography Images Using Artificial Intelligence.
Laura BustoCésar VeigaJosé A González-NóvoaSilvia CampanioniPablo Juan-SalvadoresVíctor Alfonso Jiménez DíazJosé Antonio BazJosé Luis Alba-CastroMaximilian KüttingAndrés ÍñiguezPublished in: Bioengineering (Basel, Switzerland) (2023)
Transcatheter aortic valve implantation (TAVI) is a procedure to treat severe aortic stenosis. There are several clinical concerns related to potential complications after the procedure, which demand the analysis of computerized tomography (CT) scans after TAVI to assess the implant's result. This work introduces a novel, fully automatic method for the analysis of post-TAVI 4D-CT scans to characterize the prosthesis and its relationship with the patient's anatomy. The method enables measurement extraction, including prosthesis volume, center of mass, cross-sectional area (CSA) along the prosthesis axis, and CSA difference between the aortic root and prosthesis, all the variables studied throughout the cardiac cycle. The method has been implemented and evaluated with a cohort of 13 patients with five different prosthesis models, successfully extracting all the measurements from each patient in an automatic way. For Allegra patients, the mean of the obtained inner volume values ranged from 10,798.20 mm 3 to 18,172.35 mm 3 , and CSA in the maximum diameter plane varied from 396.35 mm 2 to 485.34 mm 2 . The implantation of this new method could provide information of the important clinical value that would contribute to the improvement of TAVI, significantly reducing the time and effort invested by clinicians in the image interpretation process.
Keyphrases
- transcatheter aortic valve implantation
- aortic stenosis
- ejection fraction
- aortic valve
- deep learning
- computed tomography
- aortic valve replacement
- artificial intelligence
- transcatheter aortic valve replacement
- left ventricular
- dual energy
- machine learning
- contrast enhanced
- positron emission tomography
- image quality
- magnetic resonance imaging
- coronary artery disease
- end stage renal disease
- convolutional neural network
- case report
- newly diagnosed
- chronic kidney disease
- patient reported outcomes
- peritoneal dialysis
- clinical decision support
- pulmonary hypertension
- optical coherence tomography
- pulmonary artery
- coronary artery