Effect of Different EndoAnchor Configurations on Aortic Endograft Displacement Resistance: An Experimental Study.

Purpose: This study investigated the effect of different EndoAnchor configurations on aortic endograft displacement resistance in an in vitro model. Materials and Methods: An in vitro model was developed and validated to perform displacement force measurements on different EndoAnchor configurations within an endograft and silicone tube. Five EndoAnchor configurations were created: (1) 6 circumferentially deployed EndoAnchors, (2) 5 EndoAnchors within 120° of the circumference and 1 additional, contralateral EndoAnchor, (3) 4 circumferentially deployed EndoAnchors, (4) 2 rows of 4 circumferentially deployed EndoAnchors, and (5) a configuration of 2 columns of 3 EndoAnchors. An experienced vascular surgeon deployed EndoAnchors under C-arm guidance at the proximal sealing zone of the endograft. A constant force with increments of 1 newton (N) was applied to the distal end of the endograft. The force necessary to displace a part of the endograft by 3 mm was defined as the endograft displacement force (EDF). Two video cameras recorded the measurements. Videos were examined to determine the exact moment 3-mm migration had occurred at part of the endograft. Five measurements were performed after each deployed EndoAnchor for each configuration. Measurements are given as the median and interquartile range (IQR) Q1, Q3. Results: Baseline displacement force measurement of the endograft without EndoAnchors resulted in a median EDF of 5.1 N (IQR 4.8, 5.2). The circumferential distribution of 6 EndoAnchors resulted in a median EDF of 53.7 N (IQR 49.0, 59.0), whereas configurations 2 through 5 demonstrated substantially lower EDFs of 29.0 N (IQR 28.5, 30.1), 24.6 N (IQR 21.9, 27.2), 36.7 N, and 9.6 N (IQR 9.4, 10.0), respectively. Decreasing the distance between the EndoAnchors over the circumference of the endograft increased the displacement resistance. Conclusion: This in vitro study demonstrates the influence EndoAnchor configurations have on the displacement resistance of an aortic endograft. Parts of the endograft where no EndoAnchor has been deployed remain sensitive to migration. In the current model, the only configuration that rivaled a hand-sewn anastomosis was the one with 6 EndoAnchors. A circumferential distribution of EndoAnchors with small distances between EndoAnchors should be pursued, if possible. This study provides a quantification of different EndoAnchor configurations that clinicians may have to adopt in clinical practice, which can help them make a measured decision on where to deploy EndoAnchors to ensure good endograft fixation.

Development of an in vitro setup for flow studies in a stented carotid artery bifurcation.

To investigate flow conditions in a double-layered carotid artery stent, a bench-top in vitro flow setup including a bifurcation phantom was designed and fabricated. The geometry of the tissue-mimicking phantom was based on healthy individuals. Two identical phantoms were created using 3D-printing techniques and molding with PVA-gel. In one of them, a clinically available CGuard double-layer stent was inserted. Measurements were performed using both continuous and pulsatile flow conditions. Blood flow studies were performed using echoPIV: a novel ultrasound-based technique combined with particle image velocimetry. A maximum deviation of 3% was visible between desired and measured flow patterns. The echoPIV measurements showed promising results on visualization and quantification of blood flow in and downstream the stent. Further research could demonstrate the effects of a double-layered stent on blood flow patterns in a carotid bifurcation in detail.

The influence of electrocardiogram-gated computed tomography reconstruction into 8 or 10 cardiac phases on cardiac-pulsatility-induced motion quantification of stent grafts in the aorta.

Objective: The goal of this study was to determine to what extent aortic stent graft motion quantification is comparable between electrocardiogram (ECG)-gated computed tomography (CT) scans with reconstructions into 8 and 10 cardiac phases on CT scanners from two different vendors. Methods: An experimental setup that induces motion of an aortic stent graft, according to a predefined aortic blood pressure wave, was placed in two CT scanners of different vendors. The stent graft motion was captured using an ECG-gated CT technique and quantified using dedicated analysis algorithms. The calculated motion amplitudes and total traveled path lengths of stent segmentations were compared between scans reconstructed into 8 and 10 phases and between the scanners, after validation with sensor measurements and repeated measurements. Results: No difference in motion amplitudes in z-direction (craniocaudal direction) was observed between the reconstructions into 8 and 10 phases (0.02 mm; 95% confidence interval [CI], -0.01 to 0.05 mm; P = .358). The z-amplitudes differed by 0.04 mm (95% CI, 0.01-0.07 mm; P = .003) between the different CT scanners. Path lengths differed 0.07 mm (95% CI, 0.01-to 0.13 mm; P = .013) between the reconstructions into 8 and 10 phases and 0.13 mm (95% CI, 0.06-0.17 mm; P < .001) between the different scanners. Conclusions: The motion amplitudes can accurately be compared between 8 and 10 phases and between the two scanners, without differences larger than the voxel size of 0.3 × 0.3 × 0.5 mm. Clinical motion analysis results of different ECG-gated CT scans and CT scanners can be compared up to the accuracy of the CT scan.

Development of a dynamic myocardial perfusion phantom model for tracer kinetic measurements.

BACKGROUND: Absolute myocardial perfusion imaging (MPI) is beneficial in the diagnosis and prognosis of patients with suspected or known coronary artery disease. However, validation and standardization of perfusion estimates across centers is needed to ensure safe and adequate integration into the clinical workflow. Physical myocardial perfusion models can contribute to this clinical need as these can provide ground-truth validation of perfusion estimates in a simplified, though controlled setup. This work presents the design and realization of such a myocardial perfusion phantom and highlights initial performance testing of the overall phantom setup using dynamic single photon emission computed tomography. RESULTS: Due to anatomical and (patho-)physiological representation in the 3D printed myocardial perfusion phantom, we were able to acquire 22 dynamic MPI datasets in which 99mTc-labelled tracer kinetics was measured and analyzed using clinical MPI software. After phantom setup optimization, time activity curve analysis was executed for measurements with normal myocardial perfusion settings (1.5 mL/g/min) and with settings containing a regional or global perfusion deficit (0.8 mL/g/min). In these measurements, a specific amount of activated carbon was used to adsorb radiotracer in the simulated myocardial tissue. Such mimicking of myocardial tracer uptake and retention over time satisfactorily matched patient tracer kinetics. For normal perfusion levels, the absolute mean error between computed myocardial blood flow and ground-truth flow settings ranged between 0.1 and 0.4 mL/g/min. CONCLUSION: The presented myocardial perfusion phantom is a first step toward ground-truth validation of multimodal, absolute MPI applications in the clinical setting. Its dedicated and 3D printed design enables tracer kinetic measurement, including time activity curve and potentially compartmental myocardial blood flow analysis.

Development of a dedicated 3D printed myocardial perfusion phantom: proof-of-concept in dynamic SPECT.

We aim to facilitate phantom-based (ground truth) evaluation of dynamic, quantitative myocardial perfusion imaging (MPI) applications. Current MPI phantoms are static representations or lack clinical hard- and software evaluation capabilities. This proof-of-concept study demonstrates the design, realisation and testing of a dedicated cardiac flow phantom. The 3D printed phantom mimics flow through a left ventricular cavity (LVC) and three myocardial segments. In the accompanying fluid circuit, tap water is pumped through the LVC and thereafter partially directed to the segments using adjustable resistances. Regulation hereof mimics perfusion deficit, whereby flow sensors serve as reference standard. Seven phantom measurements were performed while varying injected activity of 99mTc-tetrofosmin (330-550 MBq), cardiac output (1.5-3.0 L/min) and myocardial segmental flows (50-150 mL/min). Image data from dynamic single photon emission computed tomography was analysed with clinical software. Derived time activity curves were reproducible, showing logical trends regarding selected input variables. A promising correlation was found between software computed myocardial flows and its reference ([Formula: see text]= - 0.98; p = 0.003). This proof-of-concept paper demonstrates we have successfully measured first-pass LV flow and myocardial perfusion in SPECT-MPI using a novel, dedicated, myocardial perfusion phantom. This proof-of-concept study focuses on the development of a novel, dedicated myocardial perfusion phantom, ultimately aiming to contribute to the evaluation of quantitative myocardial perfusion imaging applications.

A Multimodality Myocardial Perfusion Phantom: Initial Quantitative Imaging Results.

This proof-of-concept study explores the multimodal application of a dedicated cardiac flow phantom for ground truth contrast measurements in dynamic myocardial perfusion imaging with CT, PET/CT, and MRI. A 3D-printed cardiac flow phantom and flow circuit mimics the shape of the left ventricular cavity (LVC) and three myocardial regions. The regions are filled with tissue-mimicking materials and the flow circuit regulates and measures contrast flow through LVC and myocardial regions. Normal tissue perfusion and perfusion deficits were simulated. Phantom measurements in PET/CT, CT, and MRI were evaluated with clinically used hardware and software. The reference arterial input flow was 4.0 L/min and myocardial flow 80 mL/min, corresponding to myocardial blood flow (MBF) of 1.6 mL/g/min. The phantom demonstrated successful completion of all processes involved in quantitative, multimodal myocardial perfusion imaging (MPI) applications. Contrast kinetics in time intensity curves were in line with expectations for a mimicked perfusion deficit (38 s vs. 32 s in normal tissue). Derived MBF in PET/CT and CT led to under- and overestimation of reference flow of 0.9 mL/g/min and 4.5 mL/g/min, respectively. Simulated perfusion deficit (0.8 mL/g/min) in CT resulted in MBF of 2.8 mL/g/min. We successfully performed initial, quantitative perfusion measurements with a dedicated phantom setup utilizing clinical hardware and software. These results showcase the multimodal phantom's potential.

A 3D-printed anatomical pancreas and kidney phantom for optimizing SPECT/CT reconstruction settings in beta cell imaging using 111In-exendin.

BACKGROUND: Quantitative single photon emission computed tomography (SPECT) is challenging, especially for pancreatic beta cell imaging with 111In-exendin due to high uptake in the kidneys versus much lower uptake in the nearby pancreas. Therefore, we designed a three-dimensionally (3D) printed phantom representing the pancreas and kidneys to mimic the human situation in beta cell imaging. The phantom was used to assess the effect of different reconstruction settings on the quantification of the pancreas uptake for two different, commercially available software packages. METHODS: 3D-printed, hollow pancreas and kidney compartments were inserted into the National Electrical Manufacturers Association (NEMA) NU2 image quality phantom casing. These organs and the background compartment were filled with activities simulating relatively high and low pancreatic 111In-exendin uptake for, respectively, healthy humans and type 1 diabetes patients. Images were reconstructed using Siemens Flash 3D and Hermes Hybrid Recon, with varying numbers of iterations and subsets and corrections. Images were visually assessed on homogeneity and artefacts, and quantitatively by the pancreas-to-kidney activity concentration ratio. RESULTS: Phantom images were similar to clinical images and showed comparable artefacts. All corrections were required to clearly visualize the pancreas. Increased numbers of subsets and iterations improved the quantitative performance but decreased homogeneity both in the pancreas and the background. Based on the phantom analyses, the Hybrid Recon reconstruction with 6 iterations and 16 subsets was found to be most suitable for clinical use. CONCLUSIONS: This work strongly contributed to quantification of pancreatic 111In-exendin uptake. It showed how clinical images of 111In-exendin can be interpreted and enabled selection of the most appropriate protocol for clinical use.