Compliant vascular models 3D printed with the Stratasys J750: a direct characterization of model distensibility using intravascular ultrasound.

PURPOSE: The purpose of this study is to evaluate biomechanical accuracy of 3D printed anatomical vessels using a material jetting printer (J750, Stratasys, Rehovot, Israel) by measuring distensibility via intravascular ultrasound. MATERIALS AND METHODS: The test samples are 3D printed tubes to simulate arterial vessels (aorta, carotid artery, and coronary artery). Each vessel type is defined by design geometry of the vessel inner diameter and wall thickness. Vessel inner diameters are aorta = 30mm, carotid = 7mm, and coronary = 3mm. Vessel wall thickness are aorta = 3mm, carotid = 1.5mm, and coronary = 1mm. Each vessel type was printed in 3 different material options. Material options are user-selected from the J750 printer software graphical user interface as blood vessel wall anatomy elements in 'compliant', 'slightly compliant', and 'rigid' options. Three replicates of each vessel type were printed in each of the three selected material options, for a total of 27 models. The vessels were connected to a flow loop system where pressure was monitored via a pressure wire and cross-sectional area was measured with intravascular ultrasound (IVUS). Distensibility was calculated by comparing the % difference in cross-sectional area vs. pulse pressure to clinical literature values. Target clinical ranges for normal and diseased population distensibility are 10.3-44 % for the aorta, 5.1-10.1 % for carotid artery, and 0.5-6 % for coronary artery. RESULTS: Aorta test vessels had the most clinically representative distensibility when printed in user-selected 'compliant' and 'slightly compliant' material. All aorta test vessels of 'compliant' material (n = 3) and 2 of 3 'slightly compliant' vessels evaluated were within target range. Carotid vessels were most clinically represented in distensibility when printed in 'compliant' and 'slightly compliant' material. For carotid test vessels, 2 of 3 'compliant' material samples and 1 of 3 'slightly compliant' material samples were within target range. Coronary arteries were most clinically represented in distensibility when printed in 'slightly compliant' and 'rigid' material. For coronary test vessels, 1 of 3 'slightly compliant' materials and 3 of 3 'rigid' material samples fell within target range. CONCLUSIONS: This study suggests that advancements in materials and 3D printing technology introduced with the J750 Digital Anatomy 3D Printer can enable anatomical models with clinically relevant distensibility.

Assessment of computed tomography perfusion software in predicting spatial location and volume of infarct in acute ischemic stroke patients: a comparison of Sphere, Vitrea, and RAPID.

BACKGROUND: CT perfusion (CTP) infarct and penumbra estimations determine the eligibility of patients with acute ischemic stroke (AIS) for endovascular intervention. This study aimed to determine volumetric and spatial agreement of predicted RAPID, Vitrea, and Sphere CTP infarct with follow-up fluid attenuation inversion recovery (FLAIR) MRI infarct. METHODS: 108 consecutive patients with AIS and large vessel occlusion were included in the study between April 2019 and January 2020 . Patients were divided into two groups: endovascular intervention (n=58) and conservative treatment (n=50). Intervention patients were treated with mechanical thrombectomy and achieved successful reperfusion (Thrombolysis in Cerebral Infarction 2b/2 c/3) while patients in the conservative treatment group did not receive mechanical thrombectomy or intravenous thrombolysis. Intervention and conservative treatment patients were included to assess infarct and penumbra estimations, respectively. It was assumed that in all patients treated conservatively, penumbra converted to infarct. CTP infarct and penumbra volumes were segmented from RAPID, Vitrea, and Sphere to assess volumetric and spatial agreement with follow-up FLAIR MRI. RESULTS: Mean infarct differences (95% CIs) between each CTP software and FLAIR MRI for each cohort were: intervention cohort: RAPID=9.0±7.7 mL, Sphere=-0.2±8.7 mL, Vitrea=-7.9±8.9 mL; conservative treatment cohort: RAPID=-31.9±21.6 mL, Sphere=-26.8±17.4 mL, Vitrea=-15.3±13.7 mL. Overlap and Dice coefficients for predicted infarct were (overlap, Dice): intervention cohort: RAPID=(0.57, 0.44), Sphere=(0.68, 0.60), Vitrea=(0.70, 0.60); conservative treatment cohort: RAPID=(0.71, 0.56), Sphere=(0.73, 0.60), Vitrea=(0.72, 0.64). CONCLUSIONS: Sphere proved the most accurate in patients who had intervention infarct assessment as Vitrea and RAPID overestimated and underestimated infarct, respectively. Vitrea proved the most accurate in penumbra assessment for patients treated conservatively although all software overestimated penumbra.

Enhancing performance of a computed tomography perfusion software for improved prediction of final infarct volume in acute ischemic stroke patients.

Computed tomography perfusion (CTP) is crucial for acute ischemic stroke (AIS) patient diagnosis. To improve infarct prediction, enhanced image processing and automated parameter selection have been implemented in Vital Images' new CTP+ software. We compared CTP+ with its previous version, commercially available software (RAPID and Sphere), and follow-up diffusion-weighted imaging (DWI). Data from 191 AIS patients between March 2019 and January 2020 was retrospectively collected and allocated into endovascular intervention (n = 81) and conservative treatment (n = 110) cohorts. Intervention patients were treated for large vessel occlusion, underwent mechanical thrombectomy, and achieved successful reperfusion of thrombolysis in cerebral infarction 2b/2c/3. Conservative treatment patients suffered large or small vessel occlusion and did not receive intravenous thrombolysis or mechanical thrombectomy. Infarct and penumbra were assessed using intervention and conservative treatment patients, respectively. Infarct and penumbra volumes were segmented from CTP+ and compared with 24-h DWI along with RAPID, Sphere, and Vitrea. Mean infarct differences (95% confidence intervals) and Spearman correlation coefficients (SCCs) between DWI and each CTP software product for intervention patients are: CTP+ = (5.8 ± 5.9 ml, 0.62), RAPID = (10.0 ± 5.2 ml, 0.73), Sphere = (3.0 ± 6.0 ml, 0.56), Vitrea = (7.2 ± 4.9 ml, 0.66). For conservative treatment patients, mean infarct differences and SCCs are: CTP+ = (-8.0 ± 5.4 ml, 0.64), RAPID = (-25.6 ± 11.5 ml, 0.60), Sphere = (-25.6 ± 8.0 ml, 0.66), Vitrea = (1.3 ± 4.0 ml, 0.72). CTP+ performed similarly to RAPID and Sphere in addition to its semi-automated predecessor, Vitrea, when assessing intervention patient infarct volumes. For conservative treatment patients, CTP+ outperformed RAPID and Sphere in assessing penumbra. Semi-automated Vitrea remains the most accurate in assessing penumbra, but CTP+ provides an improved workflow from its predecessor.

Effect of computed tomography perfusion post-processing algorithms on optimal threshold selection for final infarct volume prediction.

In acute ischemic stroke (AIS) patients, eligibility for endovascular intervention is commonly determined through computed tomography perfusion (CTP) analysis by quantifying ischemic tissue using perfusion parameter thresholds. However, thresholds are not uniform across all analysis methods due to dependencies on patient demographics and computational algorithms. This study aimed to investigate optimal perfusion thresholds for quantifying infarct and penumbra volumes using two post-processing CTP algorithms: Vitrea Bayesian and singular value decomposition plus (SVD+). We utilized 107 AIS patients (67 non-intervention patients and 40 successful reperfusion of thrombolysis in cerebral infarction (2b/3) patients). Infarct volumes were predicted for both post-processing algorithms through contralateral hemisphere comparisons using absolute time-to-peak (TTP) and relative regional cerebral blood volume (rCBV) thresholds ranging from +2.8 seconds to +9.3 seconds and -0.23 to -0.56 respectively. Optimal thresholds were determined by minimizing differences between predicted CTP and 24-hour fluid-attenuation inversion recovery magnetic resonance imaging infarct. Optimal thresholds were tested on 60 validation patients (30 intervention and 30 non-intervention) and compared using RAPID CTP software. Among the 67 non-intervention and 40 intervention patients, the following optimal thresholds were determined: intervention Bayesian: TTP = +4.8 seconds, rCBV = -0.29; intervention SVD+: TTP = +5.8 seconds, rCBV = -0.29; non-intervention Bayesian: TTP = +5.3 seconds, rCBV = -0.32; non-intervention SVD+: TTP = +6.3 seconds, rCBV = -0.26. When comparing SVD+ and Bayesian post-processing algorithms, optimal thresholds for TTP were significantly different for intervention and non-intervention patients. rCBV optimal thresholds were equal for intervention patients and significantly different for non-intervention patients. Comparison with commercially utilized software indicated similar performance.