Accurate reconstruction of transcatheter aortic valve (TAV) geometries and other stented cardiac devices from computed tomography (CT) images is challenging, mainly associated with blooming artifacts caused by the metallic stents. In addition, bioprosthetic leaflets of TAVs are difficult to segment due to the low signal strengths of the tissues. This paper describes a method that exploits the known device geometry and uses an image registration-based reconstruction method to accurately recover the in vivo stent and leaflet geometries from patient-specific CT images. Error analyses have shown that the geometric error of the stent reconstruction is around 0.1mm, lower than 1/3 of the stent width or most of the CT scan resolutions. Moreover, the method only requires a few human inputs and is robust to input biases. The geometry and the residual stress of the leaflets can be subsequently computed using finite element analysis (FEA) with displacement boundary conditions derived from the registration. Finally, the stress distribution in self-expandable stents can be reasonably estimated by an FEA-based simulation. This method can be used in pre-surgical planning for TAV-in-TAV procedures or for in vivo assessment of surgical outcomes from post-procedural CT scans. It can also be used to reconstruct other medical devices such as coronary stents.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s10439-022-02962-9 | DOI Listing |
Cureus
December 2024
Department of Radiological Technology, Fujieda Municipal General Hospital, Fujieda, JPN.
Purpose This study aimed to clarify which positions are beneficial for patients with pathological lung diseases, such as acute respiratory distress syndrome, by obtaining lung ventilation and deformable vector field (DVF) images using Deformable Image Registration (DIR). Methods Thirteen healthy volunteers (5 female, 8 male) provided informed consent to participate to observe changes in normal lungs. DIR imaging was processed using the B-spline algorithm to obtain BH-CTVI (inhale, exhale) in four body positions (supine, prone, right lateral, left lateral) using DIR-based breath-hold CT ventilation imaging (BH-CTVI).
View Article and Find Full Text PDFClin Transl Oncol
January 2025
Department of Radiation Oncology, HM Hospitales, Madrid, Spain.
Introduction: SRS for the treatment of limited brain metastases (BM) is widely accepted, but there are still limitations in the management of numerous BM. Frameless single-isocenter multitarget SRS is a novel technique that allows for rapid treatment delivery to multiple BM. We report our preliminary clinical, dosimetric, and patient´s shifts outcomes with this technique.
View Article and Find Full Text PDFTohoku J Exp Med
January 2025
Tohoku Medical Megabank Organization, Tohoku University.
Med Biol Eng Comput
December 2024
School of Mechanical and Vehicle Engineering, Hunan University, Changsha, 410082, People's Republic of China.
Finite element human body models (HBMs) are the primary method for predicting human biological responses in vehicle collisions, especially personalized HBMs that allow accounting for diverse populations. Yet, creating personalized HBMs from a single image is a challenging task. This study addresses this challenge by providing a framework for HBM personalization, starting from a single image used to estimate the subject's skin point cloud, the skeletal point cloud, and the relative positions of the skeletons.
View Article and Find Full Text PDFJ Biomech
January 2025
Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Western Australia, Australia.
A search in Scopus within "Article title, Abstract, Keywords" unveils 2,444 documents focused on the biomechanics of Abdominal Aortic Aneurysm (AAA), mostly on AAA wall stress. Only 24 documents investigated AAA kinematics, an important topic that could potentially offer significant insights into the biomechanics of AAA. In this paper, we present an image-based approach for patient-specific, in vivo, and non-invasive AAA kinematic analysis using patient's time-resolved 3D computed tomography angiography (4D-CTA) images, with an objective to measure wall displacement and strain during the cardiac cycle.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!