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OBJECTIVE With the recent development of various MRI-conditional cardiac implantable electronic devices (CIEDs), the accurate identification and characterization of CIEDs have become critical when performing MRI in patients with CIEDs. We aimed to develop and evaluate a deep learning-based algorithm (DLA) that performs the detection and characterization of parameters, including MRI safety, of CIEDs on chest radiograph (CR) in a single step and compare its performance with other related algorithms that were recently developed. MATERIALS AND METHODS We developed a DLA (X-ray CIED identification [XCID]) using 9912 CRs of 958 patients with 968 CIEDs comprising 26 model groups from 4 manufacturers obtained between 2014 and 2019 from one hospital. The performance of XCID was tested with an external dataset consisting of 2122 CRs obtained from a different hospital and compared with the performance of two other related algorithms recently reported, including PacemakerID (PID) and Pacemaker identification with neural networks (PPMnn). RESULTS The overall accuracies of XCID for the manufacturer classification, model group identification, and MRI safety characterization using the internal test dataset were 99.7% (992/995), 97.2% (967/995), and 98.9% (984/995), respectively. These were 95.8% (2033/2122), 85.4% (1813/2122), and 92.2% (1956/2122), respectively, with the external test dataset. In the comparative study, the accuracy for the manufacturer classification was 95.0% (152/160) for XCID and 91.3% for PPMnn (146/160), which was significantly higher than that for PID (80.0%,128/160; p < 0.001 for both). XCID demonstrated a higher accuracy (88.1%; 141/160) than PPMnn (80.0%; 128/160) in identifying model groups (p < 0.001). CONCLUSION The remarkable and consistent performance of XCID suggests its applicability for detection, manufacturer and model identification, as well as MRI safety characterization of CIED on CRs. Further studies are warranted to guarantee the safe use of XCID in clinical practice.

Objective To compare the lumen parameters measured by the location-adaptive threshold method (LATM), in which the inter- and intra-scan attenuation variabilities of coronary computed tomographic angiography (CCTA) were corrected, and the scan-adaptive threshold method (SATM), in which only the inter-scan variability was corrected, with the reference standard measurement by intravascular ultrasonography (IVUS). Materials and methods The Hounsfield unit (HU) values of whole voxels and the centerline in each of the cross-sections of the 22 target coronary artery segments were obtained from 15 patients between March 2009 and June 2010, in addition to the corresponding voxel size. Lumen volume was calculated mathematically as the voxel volume multiplied by the number of voxels with HU within a given range, defined as the lumen for each method, and compared with the IVUS-derived reference standard. Subgroup analysis of the lumen area was performed to investigate the effect of lumen size on the studied methods. Bland-Altman plots were used to evaluate the agreement between the measurements. Results Lumen volumes measured by SATM was significantly smaller than that measured by IVUS (mean difference, 14.6 mm³; 95% confidence interval [CI], 4.9-24.3 mm³); the lumen volumes measured by LATM and IVUS were not significantly different (mean difference, -0.7 mm³; 95% CI, -9.1-7.7 mm³). The lumen area measured by SATM was significantly smaller than that measured by LATM in the smaller lumen area group (mean of difference, 1.07 mm²; 95% CI, 0.89-1.25 mm²) but not in the larger lumen area group (mean of difference, -0.07 mm²; 95% CI, -0.22-0.08 mm²). In the smaller lumen group, the mean difference was lower in the Bland-Altman plot of IVUS and LATM (0.46 mm²; 95% CI, 0.27-0.65 mm²) than in that of IVUS and SATM (1.53 mm²; 95% CI, 1.27-1.79 mm²). Conclusion SATM underestimated the lumen parameters for computed lumen segmentation in CCTA, and this may be overcome by using LATM.

Objective To evaluate the impact of surgical simulation training using a three-dimensional (3D)-printed model of tetralogy of Fallot (TOF) on surgical skill development. Materials and methods A life-size congenital heart disease model was printed using a Stratasys Object500 Connex2 printer from preoperative electrocardiography-gated CT scans of a 6-month-old patient with TOF with complex pulmonary stenosis. Eleven cardiothoracic surgeons independently evaluated the suitability of four 3D-printed models using composite Tango 27, 40, 50, and 60 in terms of palpation, resistance, extensibility, gap, cut-through ability, and reusability of. Among these, Tango 27 was selected as the final model. Six attendees (two junior cardiothoracic surgery residents, two senior residents, and two clinical fellows) independently performed simulation surgeries three times each. Surgical proficiency was evaluated by an experienced cardiothoracic surgeon on a 1-10 scale for each of the 10 surgical procedures. The times required for each surgical procedure were also measured. Results In the simulation surgeries, six surgeons required a median of 34.4 (range 32.5-43.5) and 21.4 (17.9-192.7) minutes to apply the ventricular septal defect (VSD) and right ventricular outflow tract (RVOT) patches, respectively, on their first simulation surgery. These times had significantly reduced to 17.3 (16.2-29.5) and 13.6 (10.3-30.0) minutes, respectively, in the third simulation surgery (p = 0.03 and p = 0.01, respectively). The decreases in the median patch appliance time among the six surgeons were 16.2 (range 13.6-17.7) and 8.0 (1.8-170.3) minutes for the VSD and RVOT patches, respectively. Summing the scores for the 10 procedures showed that the attendees scored an average of 28.58 ± 7.89 points on the first simulation surgery and improved their average score to 67.33 ± 15.10 on the third simulation surgery (p = 0.008). Conclusion Inexperienced cardiothoracic surgeons improved their performance in terms of surgical proficiency and operation time during the experience of three simulation surgeries using a 3D-printed TOF model using Tango 27 composite.

The aim of this study was to investigate the relationship between extracellular volume fraction (ECV), a noninvasive parameter that quantifies the degree of diffuse myocardial fibrosis on cardiac magnetic resonance (CMR), and left ventricular diastolic dysfunction (LVDD) in patients with aortic stenosis (AS).Myocardial fibrosis on invasive myocardial biopsy is associated with LVDD. However, there is a paucity of data on the association between noninvasively quantified diffuse myocardial fibrosis and the degree of LVDD and how these are related to symptoms and long-term prognosis in patients with AS.Patients with moderate or severe AS (n = 191; mean age 68.4 years) and 30 control subjects without cardiovascular risk factors underwent CMR. LVDD grade was evaluated using echocardiography according to the 2016 American Society of Echocardiography/European Association of Cardiovascular Imaging guidelines. Clinical outcomes were defined as a composite of all-cause mortality or hospitalization for heart failure aggravation.Patients in higher ECV quintiles had a significantly higher prevalence of LVDD. Higher ECV was particularly associated with decreased myocardial relaxation (septal e' 7 cm/s) and increased LV filling pressure (E/e' ratio ≥15). Although both impaired diastolic function and higher ECV were significantly associated with a worse degree of dyspnea, patients with higher ECV showed greater dyspnea within the same grade of LVDD. During a median follow-up period of 5.6 years, 37 clinical events occurred. Increased ECV, as well as lower septal e' and higher E/septal e' ratio, were independent predictors of clinical events, irrespective of age, AS severity, aortic valve replacement, and left ventricular (LV) ejection fraction. ECV provided incremental prognostic value on top of clinical factors and LV systolic and diastolic function.Diffuse myocardial fibrosis, assessed using ECV on CMR, was associated with LVDD in patients with AS, but both ECV and LV diastolic function parameters provided a complementary explanation for dyspnea and clinical outcomes. Concomitant assessment of both LVDD and diffuse myocardial fibrosis may further identify patients with AS with greater symptoms and worse prognosis.

To investigate the diagnostic performance of 70-kVp stress dynamic myocardial CT perfusion (CTP) as a low-dose, one-stop cardiac CT examination in clinical application. Consecutive symptomatic patients were prospectively recruited and scanned with stress dynamic myocardial CTP. The CTP phase with the best enhancement of the coronary arteries was selected and extracted as the CTP-derived single-phase coronary CT angiography (SP-CTA). The diagnostic performance of CTP and CTP+SP-CTA for functionally significant CAD was assessed. Invasive coronary angiography and fractional flow reserve were used as the reference standard for the myocardial ischemia evaluation. In total, 71 patients (43 men and 28 women; 63.6 ± 8.8 years old) underwent the stress dynamic myocardial CTP; 63 vessels (36.2%) from 42 of the patients (59.2%) were identified as causing ischemia. On a per-vessel basis, the sensitivity, specificity, PPV, NPV, and diagnostic accuracy for CTP and CTP+SP-CTA were 77.8%, 93.7%, 87.5%, 88.1%, and 87.9% and 84.1%, 93.7%, 88.3%, 91.2%, and 90.2%, respectively. The area under the curve (AUC) of CTP+SP-CTA (AUC = 0.963; 95%CI, 0.938–0.989) was significantly superior to that of CTP (AUC = 0.922; 95%CI, 0.880–0.964) and that of SP-CTA (AUC = 0.833; 95%CI, 0.765–0.900) alone (all p

To investigate performance of 1-mm, sharp kernel, low-dose chest computed tomography (LDCT) for coronary artery calcium scoring (CACS) using deep learning (DL)-based denoising technique.This retrospective, intra-individual comparative study consisted of four image datasets of 131 participants who underwent LDCT and calcium CT on the same day between January and February 2020; 1-mm LDCT with DL, 1-mm LDCT with iterative reconstruction (IR), 3-mm LDCT, and calcium CT. CACS from calcium CT were considered as reference and CACS were categorized as 0, 1-10, 11-100, 101-400, and400. We compared CACS from LDCTs with that from calcium CT.Mean CACS was 104.8 ± 249.1 and proportion of positive CACS was 45% (59/131). CACS from LDCT images tended to be underestimated than those from calcium CT: 1-mm LDCT with DL (93.5 ± 249.6, p = 0.002), 1-mm LDCT with IR (94.7 ± 249.9, p0.001), and 3-mm LDCT (90.3 ± 245.3, p = 0.004). All LDCT datasets showed excellent agreement with calcium CT: intraclass correlation coefficient (ICC) = 0.961 (95% confidence interval (CI), 0.945-0.972) for DL, 0.969 (95% CI, 0.956-0.978) for IR, and 0.952 (95% CI, 0.932-0.966) for 3-mm LDCT; weighted kappa for CACS classification, 0.930 (95% CI, 0.893-0.966) for 1-mm LDCT with DL, 0.908 (95% CI, 0.866-0.950) for 1-mm LDCT with IR, and 0.846 (95% CI, 0.780-0.912) for 3-mm LDCT. The accuracy of CACS classification of 1-mm LDCT with DL (90%) tended to be better than 1-mm LDCT with IR (87%) and 3-mm LDCT (84.7%) (p = 0.10).DL-based noise reduction algorithm can offer reliable calcium scores in 1-mm LDCT reconstructed with sharp kernel.• Deep learning (DL)-based noise reduction enables calcium scoring at 1-mm, sharp kernel reconstructed low-dose chest CT (LDCT). • Both iterative reconstruction and DL-based noise reduction underestimated calcium score, but agreement were excellent with those from calcium CT. • Accuracy of categorical classification of calcium scoring tended to be highest in 1-mm LDCT with DL compared to 1-mm LDCT with IR and 3-mm LDCT (90%, 87%, and 84.7%, p = 0.10).

The intraluminal thrombus (ILT) has been shown to negatively impact the progression of the abdominal aortic aneurysms (AAAs). The formation of this thrombus layer has been connected to the local flow environment within AAAs, but the specific mechanisms leading to thrombus formation are still not fully understood. Our study investigated the association between vortical structures, near-wall hemodynamic metrics (e.g., time averaged wall shear stress (TAWSS) and oscillatory shear index (OSI)), and ILT accumulation in a longitudinal cohort of 14 AAAs (53 scans total). Vortices and hemodynamic parameters were estimated using hemodynamic simulations performed to each scan of each patient and compared to local 3D changes of ILT thickness between two consecutive scans (∆ILT). Results showed that vortices formed and remained strong and close to the lumen surface in AAAs without an ILT, while in AAAs with ILTs these detached from the lumen surface and dissipated nearby wall region where an increase in ILT thickness was observed. Although low TAWSS was observed in regions with and without ILT accumulation, an inverse correlation between ∆ILT and TAWSS was observed within the regions that experienced a thrombus growth. Our results support the idea that vortical structures might be playing a role modulating ILT accumulation into specific wall regions. Also, it submits the idea that the low TAWSS will be modulating the growth of thrombus within these preferred ILT accumulated regions. This article is protected by copyright. All rights reserved.

Three-dimensional (3D) printed models are widely accepted for use in training of various surgical procedures for congenital heart disease; however, their physical properties have been considered suboptimum for procedures. We created silicone molded models produced using a novel "parting and assembly" strategy and compared their suitability for hands-on training with that of conventional 3D printed models.Computed tomography imaging data from 2 patients with transposition of the great arteries were used. The heart was divided into multiple parts (atria, ventricles, great arteries, coronary arteries, and valves), and molds of each part were created. The parts reproduced by silicone molding were assembled using an adhesive agent. In an online course, 2 silicone molded models and 1 3D printed model were used for training of 34 surgeons. A questionnaire was distributed to these surgeons aimed at assessing the suitability of the models for the arterial switch operation (ASO).The silicone molded models showed excellent anatomic detail, high elasticity, and high resistance to tearing. The cost per model, based on the production of 50 models, was slightly higher for the silicone molded models compared with the 3D printed models. All 26 surgeons who completed the questionnaire reported that the silicone molded models provided sufficient anatomic information, but only 19% said the same for the 3D printed models. All surgeons also considered the silicone models to be realistic when passing a needle, cutting vessels, suturing, and excision of the coronary buttons, as opposed to46% for the 3D printed models.Silicone molding of models for the ASO is feasible by applying a "parting and assembly" strategy. Silicone molded models provide excellent physical properties that are far superior to those of 3D printed models for surgical simulation.

According to the reports presented at the Fourth Asian Oceanian Radiology Forum (AORF) 2018, organized by the Korean Society of Radiology during the Korean Congress of Radiology in September 2018 in Seoul, there is an increasing demand for the Asian Oceanian Society of Radiology and its member societies for international education in radiology in the Asian Oceanian region. In AORF 2018, the national delegates of the Asian Oceanian radiological partner societies primarily discussed their societies' activities and current status of international education in radiology.

Currently, the prevention of recurrent immediate hypersensitivity reactions (HSRs) to contrast media (CM) requests premedication and changing the culprit contrast agent. However, strategies for the prevention of immediate HSRs to gadolinium-based magnetic resonance contrast agents (GBCAs) have not yet been established. This study aimed to evaluate the effectiveness of changing the contrast agent and single-dose premedication for HSR recurrence prevention in patients with a history of mild immediate HSR to GBCA.The outcomes of patients with mild immediate HSR to GBCA who subsequently underwent enhanced magnetic resonance imaging between October 2012 and July 2017 were analyzed. The institutional CM monitoring system was retrospectively reviewed, and data on the application of premedication and choice of CM were obtained. Gadolinium-based magnetic resonance contrast agents were classified into 3 classes according to their molecular structure (macrocyclic ionic, macrocyclic nonionic, and linear ionic). Intravenous chlorpheniramine 4 mg, 30 minutes before the GBCA administration, or intravenous methylprednisolone sodium succinate 40 mg plus chlorpheniramine 4 mg, 1 hour before the GBCA administration, was administrated as premedication regimen. Recurrence rates of immediate HSR were compared according to prevention strategies.A total of 185 patients with a history of mild immediate HSR to GBCA were re-exposed to GBCA 397 times during the study period. The overall recurrence rate was 19.6% (78/397). Changing the culprit GBCA significantly reduced the recurrence rate, compared with reusing the culprit GBCA (6.9%, 9/130 and 25.8%, 69/267; P0.001). The recurrence rate was lowest when the GBCA was changed to a different molecular structure class from the culprit agent, followed by changing to CM with the same molecular structure and reusing the culprit GBCA (6.2%, 7/113 vs 11.8%, 2/17 vs 25.8%, 69/267; P0.001 with χ test for trend). Single-dose premedication demonstrated no significant prophylactic effect on recurrence (20.4%, 17/98 vs 17.3%, 61/299 with and without premedication, respectively; P = 0.509). Premedication in addition to changing CM also showed no additional prophylactic effect (7.2%, 7/97 and 6.1%, 2/33, respectively; P = 0.821).Changing the CM from the culprit agent could reduce the chance of HSR recurrence in patients with prior mild immediate HSR to GBCA, especially when the CM was changed to one of a different molecular structure class. However, single-dose premedication administration did not show significant HSR recurrence rate difference.

OBJECTIVE To investigate the diagnostic validity of coronary computed tomography angiography (cCTA) in vasospastic angina (VA) and factors associated with discrepant results between invasive coronary angiography with the ergonovine provocation test (iCAG-EPT) and cCTA. MATERIALS AND METHODS Of the 1397 patients diagnosed with VA from 2006 to 2016, 33 patients (75 lesions) with available cCTA data from within 6 months before iCAG-EPT were included. The severity of spasm (% diameter stenosis [%DS]) on iCAG-EPT and cCTA was assessed, and the difference in %DS (Δ%DS) was calculated. Δ%DS was compared after classifying the lesions according to pre-cCTA-administered sublingual nitroglycerin (SL-NG) or beta-blockers. The lesions were further categorized with %DS ≥ 50% on iCAG-EPT or cCTA defined as a significant spasm, and the diagnostic performance of cCTA on identifying significant spasm relative to iCAG-EPT was assessed. RESULTS Compared to lesions without SL-NG treatment, those with SL-NG treatment showed a higher Δ%DS (39.2% vs. 22.1%, p = 0.002). However, there was no difference in Δ%DS with or without beta-blocker treatment (35.1% vs. 32.6%, p = 0.643). The significant difference in Δ%DS associated with SL-NG was more prominent in patients who were aged < 60 years, were male, had body mass index < 25 kg/m², and had no history of hypertension, diabetes, or dyslipidemia. Based on iCAG-EPT as the reference, the per-lesion-based sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of cCTA for VA diagnosis were 7.5%, 94.0%, 60.0%, 47.1%, and 48.0%, respectively. CONCLUSION For patients with clinically suspected VA, confirmation with iCAG-EPT needs to be considered without completely excluding the diagnosis of VA simply based on cCTA results, although further prospective studies are required for confirmation.

Objective: We propose a novel approach to predict the Abdominal Aortic Aneurysm (AAA) growth in future time, using longitudinal computer tomography (CT) scans of AAAs that are captured at different times in a patient-specific way. Methods : We adopt a formulation that considers a surface of the AAA as a manifold embedded in a scalar field over the three dimensional (3D) space. For this formulation, we develop our Dynamical Gaussian Process Implicit Surface (DGPIS) model based on observed surfaces of 3D AAAs as visible variables while the scalar fields are hidden . In particular, we use Gaussian process regression to construct the field as an observation model from CT training image data. We then learn a dynamic model to represent the evolution of the field. Finally, we derive the predicted AAA surface from the predicted field along with uncertainty quantified in future time. Results : A dataset of 7 subjects (4–7 scans) was collected and used to evaluate the proposed method by comparing its prediction Hausdorff distance errors against those of simple extrapolation. In addition, we evaluate the prediction results with respect to a conventional shape analysis technique such as Principal Component Analysis (PCA). All comparative results show the superior prediction performance of the proposed approach. Conclusion : We introduce a novel approach to predict the AAA growth and its predicted uncertainty in future time, using longitudinal CT scans in a patient-specific fashion. Significance: The capability to predict the AAA shape and its confidence region by our approach establish the potential for guiding clinicians with informed decision in conducting medical treatment and monitoring of AAAs.

This study aimed to evaluate the effect of implementing the consensus statement from the Asian Society of Cardiovascular Imaging-Practical Tutorial 2020 (ASCI-PT 2020) on the reliability of cardiac MR with late gadolinium enhancement (CMR-LGE) myocardial viability scoring between observers in the context of ischemic cardiomyopathy.A total of 17 cardiovascular imaging experts from five different countries evaluated CMR obtained in 26 patients (male:female, 23:3; median age [interquartile range], 55.5 years [50-61.8]) with ischemic cardiomyopathy. For LGE scoring, based on the 17 segments, the extent of LGE in each segment was graded using a five-point scoring system ranging from 0 to 4 before and after exposure according to the consensus statement. All scoring was performed via web-based review. Scores for slices, vascular territories, and total scores were obtained as the sum of the relevant segmental scores. Interobserver reliability for segment scores was assessed using Fleiss' kappa, while the intraclass correlation coefficient (ICC) was used for slice score, vascular territory score, and total score. Inter-observer agreement was assessed using the limits of agreement from the mean (LoA).Interobserver reliability (Fleiss' kappa) in each segment ranged 0.242-0.662 before the consensus and increased to 0.301-0.774 after the consensus. The interobserver reliability (ICC) for each slice, each vascular territory, and total score increased after the consensus (slice, 0.728-0.805 and 0.849-0.884; vascular territory, 0.756-0.902 and 0.852-0.941; total score, 0.847 and 0.913, before and after implementing the consensus statement, respectively. Interobserver agreement in scoring also improved with the implementation of the consensus for all slices, vascular territories, and total score. The LoA for the total score narrowed from ± 10.36 points to ± 7.12 points.The interobserver reliability and agreement for CMR-LGE scoring for ischemic cardiomyopathy improved when following guidance from the ASCI-PT 2020 consensus statement.

Aims We investigated the prognostic role of left ventricular global longitudinal strain (LV-GLS) and its incremental value to established risk models for predicting sudden cardiac death (SCD) in patients with hypertrophic cardiomyopathy (HCM). Methods and results LV-GLS was measured with vendor-independent software at a core laboratory in a cohort of 835 patients with HCM (aged 56.3 ± 12.2 years) followed-up for a median of 6.4 years. The primary endpoint was SCD events, including appropriate defibrillator therapy, within 5 years after the initial evaluation. The secondary endpoint was a composite of SCD events, heart failure admission, heart transplantation, and all-cause mortality. Twenty (2.4%) and 85 (10.2%) patients experienced the primary and secondary endpoints, respectively. Lower absolute LV-GLS quartiles, especially those worse than the median (−15.0%), were associated with progressively higher SCD event rates (P = 0.004). LV-GLS was associated with an increased risk for the primary endpoint, independent of the LV ejection fraction, apical aneurysm, and 2014 European Society of Cardiology (ESC) risk score [adjusted hazard ratio (aHR) 1.14, 95% confidence interval (CI) 1.02–1.28] or 2011 American College of Cardiology/American Heart Association (ACC/AHA) risk factors (aHR 1.18, 95% CI 1.05–1.32). LV-GLS was also associated with a higher risk for the composite secondary endpoint (aHR 1.06, 95% CI 1.01–1.12). The addition of LV-GLS enhanced the performance of the ESC risk score (C-statistic 0.756 vs. 0.842, P = 0.007) and the 2011 ACC/AHA risk factor strategy (C-statistic 0.743 vs. 0.814, P = 0.007) for predicting SCD. Conclusion LV-GLS is an important prognosticator in patients with HCM and provides additional information to established risk stratification strategies for predicting SCD.

Background Cardiovascular magnetic resonance (CMR) is increasingly used for risk stratification in aortic stenosis (AS). However, the relative prognostic power of CMR markers and their respective thresholds remains undefined. Objectives Using machine learning, the study aimed to identify prognostically important CMR markers in AS and their thresholds of mortality. Methods Patients with severe AS undergoing AVR (n = 440, derivation; n = 359, validation cohort) were prospectively enrolled across 13 international sites (median 3.8 years’ follow-up). CMR was performed shortly before surgical or transcatheter AVR. A random survival forest model was built using 29 variables (13 CMR) with post-AVR death as the outcome. Results There were 52 deaths in the derivation cohort and 51 deaths in the validation cohort. The 4 most predictive CMR markers were extracellular volume fraction, late gadolinium enhancement, indexed left ventricular end-diastolic volume (LVEDVi), and right ventricular ejection fraction. Across the whole cohort and in asymptomatic patients, risk-adjusted predicted mortality increased strongly once extracellular volume fraction exceeded 27%, while late gadolinium enhancement >2% showed persistent high risk. Increased mortality was also observed with both large (LVEDVi >80 mL/m2) and small (LVEDVi ≤55 mL/m2) ventricles, and with high (>80%) and low (≤50%) right ventricular ejection fraction. The predictability was improved when these 4 markers were added to clinical factors (3-year C-index: 0.778 vs 0.739). The prognostic thresholds and risk stratification by CMR variables were reproduced in the validation cohort. Conclusions Machine learning identified myocardial fibrosis and biventricular remodeling markers as the top predictors of survival in AS and highlighted their nonlinear association with mortality. These markers may have potential in optimizing the decision of AVR.

Perventricular pulmonary valve implantation (PPVI) of a xenograft valve can be a less invasive technique that avoids cardiopulmonary bypass in patients who require pulmonary valve replacement. We compared the hemodynamics, durability, and histologic changes between two different xenogenic valves (pericardial vs. aortic valve porcine xenografts) implanted into the pulmonary valve position using a PPVI technique and evaluated the safety and efficacy of PPVI as a preclinical study. In 18 sheep, pericardial (group porcine pericardial [PP], n = 9) or aortic valve (group porcine aortic valve [PAV], n = 9) xenogenic porcine valves manufactured as a stented valve were implanted using a PPVI technique. The porcine tissues were decellularized, alpha-galactosidase treated, fixed with glutaraldehyde after space-filler treatment, and detoxified to improve durability. Hemodynamic and immunohistochemical studies were performed after the implantation; radiologic and histologic studies were performed after a terminal procedure. All stented valves were positioned properly after the implantation, and echocardiography and cardiac catheterization demonstrated good hemodynamic state and function of the valves. All the anti-α-Gal IgM and IgG titers were below 0.3 optical density. Computed tomography of extracted valves demonstrated no significant differences in the degree of calcification between the two groups (P = .927). Microscopic findings revealed a minimal amount of calcification and no significant infiltration of macrophage or T-cell in both groups, regardless of the implantation duration. The PPVI is a feasible technique. Both stented valves made of PP and PAV showed no significant differences in hemodynamic profile, midterm durability, and degree of degenerative dystrophic calcification.

Various congenital heart diseases are associated with malalignment of a part of the ventricular septum. Most commonly, the outlet septum is malaligned toward the right or left ventricle. Less commonly, the whole or a major part of the ventricular septum is malaligned in relation to the atrial septal plane. Although the pathological conditions associated with ventricular septal malalignment have been well recognized, the descriptions are often confusing and sometimes incorrect. In this pictorial essay, we introduce our systematic approach to the assessment of malalignment type ventricular septal defects with typical case examples. The systematic approach comprises description of the essential features of malalignment, including the following: (1) the malaligned part of the ventricular septum, (2) the reference structure, (3) the mechanism of malalignment, (4) the direction of malalignment, and (5) the severity of malalignment.

Background Cardiovascular magnetic resonance (CMR) demonstrates promise in improving patient risk stratification in aortic stenosis (AS). We explored whether machine learning might provide further insights into the prognostic capability of CMR parameters. Methods Severe AS patients (n=440) undergoing AVR were prospectively enrolled across 10 international sites, and CMR performed prior to AVR. A machine learning prediction model using a random survival forest (RSF) was trained with 29 variables, including 13 CMR, 4 echocardiography, and 12 clinical parameters, using post-AVR mortality as an outcome. The impact of the important variables on the outcome (partial dependency) was examined. Results The most predictive CMR parameters in the RSF model were the extracellular volume fraction (ECV%), followed by right ventricular ejection fraction (RVEF), late gadolinium enhancement (LGE%), and indexed left ventricular end-diastolic volume (LVEDVi). Regarding the partial effects, the predicted mortality increased strongly once the ECV% exceeded 26.5% (Figure 1A). The LGE% was associated with an increased risk of mortality, which reached a plateau beyond the level of 2% (Figure 1C). There were U-shaped relationships between mortality and both RVEF and LVEDVi, with the lowest mortality seen at RVEF 70% and LVEDVi 68ml/m2 (Figure 1B, D). These trends of predicted outcomes by each variable were verified in the Kaplan-Meier curves and Cox analyses (Table). In both Cox and RSF models, the predictability was substantially increased when these four CMR parameters were added to conventional clinical risk factors. An AS-CMR risk score comprised of these four parameters presented a stepwise increase in mortality with increasing adverse CMR features (p Conclusions Our machine learning analysis using RSF has identified ECV%, RVEF, LGE%, and LVEDVi as key prognostic markers in severe AS with a nonlinear influence of each parameter on mortality post-AVR. Figure 1 Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): This study was supported by grants from the Korean Health Technology R & D Project, Ministry of Health, Welfare & Family Affairs, Republic of Korea (HI16C0225 and HI15C0399) and the National Institute for Health Research (NIHR) infrastructure at Leeds.

ObjectiveThe maximum diameter measurement of an abdominal aortic aneurysm (AAA), which depends on orthogonal and axial cross-sections or maximally inscribed spheres within the AAA, plays a significant role in the clinical decision making process. This study aims to build a large dataset of morphological parameters from longitudinal CT scans and analyze their correlations. Furthermore, this work explores the existence of a “master curve” of AAA growth, and tests which parameters serve to enhance its predictability for clinical use.Methods106 CT scan images from 25 Korean AAA patients were retrospectively obtained. We subsequently computed morphological parameters, growth rates, and pair-wise correlations, and attempted to enhance the predictability of the growth for high-risk aneurysms using non-linear curve fitting and least-square minimization.ResultsAn exponential AAA growth model was fitted to the maximum spherical diameter, as the best representative of the growth among all parameters (r-square: 0.985) and correctly predicted to 74 of 79 scans based on a 95% confidence interval. AAA volume expansion rateswere highly correlated (r=0.80) with thrombus accumulation rates.ConclusionsThe exponential growth model using spherical diameter provides useful information about progression of aneurysm size and enables AAA growth rate extrapolation during a given surveillance period.

Objective To investigate the relationship between the characteristics of intraluminal thrombus (ILT) with abdominal aortic aneurysm (AAA) expansion. Methods This retrospective clinical study applied homogeneous multistate continuous-time Markov chain models to longitudinal computed tomography (CT) data from Korean patients with AAA. Four AAA states were considered (early, mild, severe, fatal) and the maximal thickness of the ILT (maxILT), the fraction of the wall area covered by the ILT (areafrac) and the fraction of ILT volume (volfrac) were used as covariates. Results The analysis reviewed longitudinal CT images from 26 patients. Based on likelihood-ratio statistics, the areafrac was the most significant biomarker and maxILT was the second most significant. In addition, within AAAs that developed an ILT layer, the analysis found that the AAA expands relatively quickly during the early stage but the rate of expansion reduces once the AAA has reached a larger size. Conclusion The results recommend surgical intervention when a patient has an areafrac more than 60%. Although this recommendation should be considered with caution given the limited sample size, physicians can use the proposed model as a tool to find such recommendations with their own data.

Objective Transcatheter aortic valve implantation (TAVI) procedures are increasing rapidly, but the durability of tissue valve and periprocedural complications are not satisfactory. Immune reaction to the galactose-α-1,3 galactose β-1,4-N-acetylglucosamine (α-Gal) and conventional processing protocols of cardiac xenografts lead to calcification. Next-generation TAVI needs to be made with α-Gal–free xenografts by multiple anticalcification therapies to avoid immune rejection and enhance durability, and three-dimensional (3D) printing technology to improve the procedural safety. Methods Porcine pericardia were decellularized and immunologically modified with α-galactosidase. The pericardia were treated by space filler, crosslinked with glutaraldehyde in organic solvent, and detoxified. The sheep-specific nitinol (nickel–titanium memory alloy) wire backbone was made from a 3D-printed model for ovine aortic root. After it passed the fitting test, we manufactured a self-expandable stented valve with the porcine pericardia mounted on the customized nitinol wire–based stent. After in vitro circulation using customized silicone aortic root, we performed TAVI in 9 sheep and obtained hemodynamic, radiological, immunohistopathological, and biochemical results. Results The valve functioned well, with excellent stent fitting and good coronary flow under in vitro circulation. Sheep were sequentially scheduled to be humanely killed until 238 days after TAVI. Echocardiography and cardiac catheterization demonstrated good hemodynamic status and function of the aortic valve. The xenografts were well preserved without α-Gal immune reaction or calcification based on the immunological, radiographic, microscopic, and biochemical examinations. Conclusions We proved preclinical safety and efficacy for next-generation α-Gal–free TAVI with multiple anticalcification therapies and 3D-printing technology. A future clinical study is warranted based on these promising preclinical results.

BACKGROUND The incidence of severe reaction induced by iodinated contrast media (ICM) has increased over the years with an increasing use of imaging modalities. Although ICM anaphylaxis is rare, it can be life-threatening, but currently, there is no biomarker that can identify individuals at risk of ICM anaphylaxis. OBJECTIVE The aim of this study is to investigate the genetic susceptibility of ICM anaphylaxis. METHODS Patients who had ICM anaphylaxis were enrolled in the study, and their blood samples were collected for genotyping of human leukocyte antigen (HLA)-A, -B, -C, and -DR. The results were compared with those of healthy Korean general population. MRGPRX2 gene in ICM anaphylaxis group was also sequenced and compared with the Korean standard database of genetic polymorphism. RESULTS The frequencies of 3 HLA alleles (B*52:01, C*12:02, and DRB1*15:02) were significantly higher in 47 patients with ICM anaphylaxis. In particular, HLA-DRB1*15:02 was 5 times more frequent in the ICM anaphylaxis group than the Korean general population (34.0% vs 6.6%; odds ratio, 7.306; 95% confidence interval, 3.622-14.740), and this difference was most pronounced in subjects with iohexol-induced anaphylaxis (odds ratio, 16.516; 95% CI, 5.241-52.047; P < 0.0001). Eight single nucleotide polymorphisms were identified in MRGPRX2 gene, but their frequencies were not different in those with ICM anaphylaxis compared with the general Korean population. CONCLUSIONS HLA-DRB1*15:02 is associated with ICM anaphylaxis in the Korean population.

An abdominal aortic aneurysm (AAA) is a gradual enlargement of the aorta that can cause a life-threatening event when a rupture occurs. Aneurysmal geometry has been proved to be a critical factor in determining when to surgically treat AAAs, but, it is challenging to predict the patient-specific evolution of an AAA with biomechanical or statistical models. The recent success of deep learning in biomedical engineering shows promise for predictive medicine. However, a deep learning model requires a large dataset, which limits its application to the prediction of the patient-specific AAA expansion. In order to cope with the limited medical follow-up dataset of AAAs, a novel technique combining a physical computational model with a deep learning model is introduced to predict the evolution of AAAs. First, a vascular Growth and Remodeling (G&R) computational model, which is able to capture the variations of actual patient AAA geometries, is employed to generate a limited in silico dataset. Second, the Probabilistic Collocation Method (PCM) is employed to reproduce a large in silico dataset by approximating the G&R simulation outputs. A Deep Belief Network (DBN) is then trained to provide fast predictions of patient-specific AAA expansion, using both in silico data and patients' follow-up data. Follow-up Computer Tomography (CT) scan images from 20 patients are employed to demonstrate the effectiveness and the feasibility of the proposed model. The test results show that the DBN is able to predict the enlargements of AAAs with an average relative error of 3.1%, which outperforms the classical mixed-effect model by 65%.

Objective For small abdominal aortic aneurysms (AAAs), a regular follow-up examination is recommended every 12 months for AAAs of 30–39 mm and every six months for AAAs of 40–55 mm. Follow-up diameters can determine if a patient follows the common growth model of the population. However, the rapid expansion of an AAA, often associated with higher rupture risk, may be overlooked even though it requires surgical intervention. Therefore, the prognosis of abdominal aortic aneurysm growth is clinically important for planning treatment. This study aims to build enhanced Bayesian inference methods to predict maximum aneurysm diameter. Methods 106 CT scans from 25 Korean AAA patients were retrospectively obtained. A two-step approach based on Bayesian calibration was used, and an exponential abdominal aortic aneurysm growth model (population-based) was specified according to each individual patient's growth (patient-specific) and morphologic characteristics of the aneurysm sac (enhanced). The distribution estimates were obtained using a Markov Chain Monte Carlo (MCMC) sampler. Results The follow-up diameters were predicted satisfactorily (i.e. the true follow-up diameter was in the 95% prediction interval) for 79% of the scans using the population-based growth model, and 83% of the scans using the patient-specific growth model. Among the evaluated geometric measurements, centerline tortuosity was a significant (p = 0.0002) predictor of growth for AAAs with accelerated and stable expansion rates. Using the enhanced prediction model, 86% of follow-up scans were predicted satisfactorily. The average prediction errors of population-based, patient-specific, and enhanced models were ±2.67, ±2.61 and ± 2.79 mm, respectively. Conclusion A computational framework using patient-oriented growth models provides useful tools for per-patient basis treatment and enables better prediction of AAA growth.

To evaluate the incidence and risk factors of late adverse reactions (ARs) to non-ionic low-osmolar contrast media (LOCM).The occurrence of late AR was monitored on day 1 and from day 7 to day 28 in all patients who received enhanced computed tomography using LOCM during a 5-week study period in a single tertiary hospital. Patients who experienced late AR were followed up for three years.Among the total 10,540 LOCM exposures, 315 ARs (3.0%) were reported; acute ARs occurred in 108 LOCM exposures (1.0%) and late ARs occurred in 207 LOCM exposures (2.0%) (90.9% within one week, 9.1% developed afterwards by day 20). Previous history of drug allergy (odds ratio [OR] = 4.59; 95% confidence interval [CI] 2.17-9.71) and allergic diseases (OR = 2.54; 95% CI 1.32-4.91) were risk factors of late ARs to LOCM. Although the recurrence rate was lowered with premedication from 8.5% to 1.7% (8/94 vs. 3/178; p = 0.016), LOCM change did not make difference compared to reuse of the culprit LOCM (2/38 vs. 9/234; p = 0.655). In patients with a history of late AR to LOCM, the risk of recurrent reactions decreased with longer time intervals between exposures (OR = 0.86; 95% CI: 0.77-0.97; p = 0.025) and with the use of antihistamine premedication (OR = 0.27; 95% CI: 0.06-0.99; p = 0.049).Late ARs to LOCM occurred mostly within one week. The use of premedication may be helpful in reducing the recurrence of late ARs.