Clinical trial NCT05484713: Feasibility of 3D Printed Models of Aortic Stenosis in Guiding TAVI Procedure
Official title: Feasibility of 3D Printed Models of Aortic Stenosis in Guiding TAVI Procedure -the 3DP-FAST Study
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Aortic Stenosis
Valvular Cardiomyopathy
Aortic Valve Disease
Keywords: aortic stenosis
3D printing
interventional planning
cardiovascular models
TAVI
Accuracy
Lead sponsor: Cardio Med Medical Center
Sponsor class: INDUSTRY
Collaborators: name: George Emil Palade University of Medicine, Pharmacy, Sciences and Technology of Targu Mures
name: University Hospital of Targu Mures, Romania
First posted: 2022-08-02
Enrollment: 20
Sex: ALL
Minimum age (years): 60
Standard ages: ADULT
OLDER_ADULT
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients with a minimum age of 60 years old, with severe degenerative aortic stenosis who present the criteria for transcatheter aortic valve intervention, who undergo coronary CCTA and CT angiography of the abdominal aorta and lower limbs, and who do not require the criteria for surgical aortic valve replacement.

Brief summary: • The aim of 3DP-FAST study is to analyze the accuracy of replicating cardiovascular anatomical structures using different techniques and to evaluate the feasibility of 3D printed models of aortic stenosis in guiding TAVI procedure. By conducting a comparative analysis of measurements achieved on CCTA images versus measurements obtained with a specialized projection platform by photogrammetry vs 3D printed models of various aortic valvular and perivalvular structures will be evaluated the accuracy of each step of image dataset processing. Furthermore, the study will evaluate the rate of valvular leak or peri-procedural complications such as embolic events or atrio-ventricular conduction block based on coronary computed tomography angiographic and ECG assessment at 1 year after enrollment.

Detailed description: The project is a prospective, cohort, mono-centric study which will be carried out in CardioMed Medical Center in collaboration with the University of Medicine, Pharmacy, Science and Technology "George Emil Palade" of Târgu Mureș.

The project will include 20 subjects who present severe aortic stenosis prior to study enrollment.

Diagnosis of severe aortic stenosis (AS) as determined by echocardiography, who are deemed eligible for TAVI by the Center of Advanced Research in Multimodal Cardiac Imaging Cardiomed Heart Valve Team.

All patients will undergo coronary CT angiography, cardiac perfusion CT and peripheral CT angiography at the moment of enrollment in the study, for complex assessment of aortic valvular and perivalvular structures as well as for peripheral vascular approach.

The study will be conducted over a period of 1 year, in which patients will be examined at baseline, and during follow-up visit. At the one-year follow-up, the study subjects will undergo CT coronary angiography for re-evaluation of the aortic valve, in the prospects of analyzing the rate of valvular leak or peri-procedural complications such as embolic events or atrio-ventricular conduction block. In case of non-presentation for the follow-up visit, patients will be contacted via telephone by one of the investigators, and questioned about the general health status, occurrence of cardiovascular or cerebrovascular symptoms and interventions, for possible non-cardiovascular related hospitalizations, as well as regarding the presence of aortic valvular disease rates/repeated interventions.

All patients will sign an informed written consent prior to being enrolled in the study. After the screening process, patients that do not present exclusion criteria will be enrolled in the study.

Study objectives:

Primary: to analyze the accuracy of replicating cardiovascular anatomical structures using different techniques and to evaluate the feasibility of 3D printed models of aortic stenosis in guiding TAVI procedure

Secondary: re-evaluation of the aortic valve, in the prospects of analyzing the rate of valvular leak or peri-procedural complications such as embolic events or atrio-ventricular conduction block.

Study Timeline:

Baseline (day 0)

* Obtain and document consent from participant on study consent form.
* Verify inclusion/exclusion criteria.
* Obtain demographic information, medical history, medication history, alcohol and tobacco use history.
* Record results of physical examinations and 12-lead ECG.
* Imaging procedures: transthoracic 2-D echocardiography, 128-multislice CT angiography (CCTA)
* 3d printed model by FDM technique based on CCTA
* Evaluation of 3D printing workflow accuracy Visit 2 (month 6)
* Follow-up after TAVI procedure
* Record results of physical examinations, 12-lead ECG and medical history.
* Imaging procedures: transthoracic 2-D echocardiography Final study visit (month 12)
* Record results of physical examinations, 12-lead ECG and medical history.
* Imaging procedures: transthoracic 2-D echocardiography, 128-multisclice CCTA
* End-point evaluation.

Study procedures:

* Clinical examination, medical history
* 12-lead ECG
* 2D transthoracic echocardiography with measurement of: cardiac diameters, volumes, valvular function and regurgitation, pressure gradients, pericardial fat thickness, pericardial effusion, left ventricular global and regional function and ejection fraction.
* 128-multislice CT coronary angiography with the evaluation of: epicardial fat volume, coronary plaque burden, total and local calcium score, aortic valve, perivalvular aortic structures, peripheral iliac vessels, ascending and descending segments of aorta.
* Processing of DICOM image dataset by performing segmentation and STL adjustments
* Processing STL image dataset by performing CAD analysis and adjustments
* Processing G-code image dataset and sending to 3d printing station
* 3D printing of aortic model including perivalvular aortic structures using fused filaments method

Data collection: In a dedicated database that includes all patient information, demographics, medical history, medication, therapeutic procedures, information derived from imaging techniques (echocardiography, CT angiography, CT imaging post-processing and shear stress evaluation).

Eligibility criteria: Inclusion Criteria:

* patients with degenerative aortic stenosis who present the criteria for transcatheter aortic valve intervention, who undergo coronary CCTA and CT angiography of the abdominal aorta and lower limbs.

Exclusion Criteria:

* contraindications for TAVI procedures
* patients that undergo surgical aortic valve replacement for aortic stenosis
* patients with contraindications for iodine contrast agent administration (acute renal failure, allergy, thyroid dysfunction).
* other conditions associated with suboptimal CCTA image acquisition which could interfere with CT image postprocessing for creation of 3D printed models.

Primary outcomes:
measure: Feasibility of 3D printed models of aortic valves in guiding TAVI procedure
timeFrame: at baseline
measure: Rate of complications during 12 months follow-up of patients undergoing TAVI for aortic stenosis
timeFrame: 12 months
Secondary outcomes:
Other outcomes:
Locations:
city: Targu Mures
country: Romania
facility: Cardio Med Medical Center
Study officials:
affiliation: CardioMed Medical Center
name: Daniel Cernica, MD
role: STUDY_DIRECTOR
References:
citation: Cernica D, Benedek I, Polexa S, Tolescu C, Benedek T. 3D Printing-A Cutting Edge Technology for Treating Post-Infarction Patients. Life (Basel). 2021 Sep 1;11(9):910. doi: 10.3390/life11090910.
citation: Benedek A, Cernica D, Mester A, Opincariu D, Hodas R, Rodean I, Keri J, Benedek T. Modern Concepts in Regenerative Therapy for Ischemic Stroke: From Stem Cells for Promoting Angiogenesis to 3D-Bioprinted Scaffolds Customized via Carotid Shear Stress Analysis. Int J Mol Sci. 2019 May 25;20(10):2574. doi: 10.3390/ijms20102574.
citation: Wang DD, Qian Z, Vukicevic M, Engelhardt S, Kheradvar A, Zhang C, Little SH, Verjans J, Comaniciu D, O'Neill WW, Vannan MA. 3D Printing, Computational Modeling, and Artificial Intelligence for Structural Heart Disease. JACC Cardiovasc Imaging. 2021 Jan;14(1):41-60. doi: 10.1016/j.jcmg.2019.12.022. Epub 2020 Aug 26.
citation: Vukicevic M, Mosadegh B, Min JK, Little SH. Cardiac 3D Printing and its Future Directions. JACC Cardiovasc Imaging. 2017 Feb;10(2):171-184. doi: 10.1016/j.jcmg.2016.12.001.