Hemodynamics-driven mathematical model of first and second heart sound generation.

NEW & NOTEWORTHY: To the best of our knowledge, this is the first hemodynamic-based heart sound generation model embedded in a complete real-time computational model of the cardiovascular system. Simulated heart sounds are similar to experimental and clinical measurements, both quantitatively and qualitatively. Our model can be used to investigate the relationships between heart sound acoustic features and hemodynamic factors/anatomical parameters.

The 'Digital Twin' to enable the vision of precision cardiology.

Providing therapies tailored to each patient is the vision of precision medicine, enabled by the increasing ability to capture extensive data about individual patients. In this position paper, we argue that the second enabling pillar towards this vision is the increasing power of computers and algorithms to learn, reason, and build the 'digital twin' of a patient. Computational models are boosting the capacity to draw diagnosis and prognosis, and future treatments will be tailored not only to current health status and data, but also to an accurate projection of the pathways to restore health by model predictions. The early steps of the digital twin in the area of cardiovascular medicine are reviewed in this article, together with a discussion of the challenges and opportunities ahead. We emphasize the synergies between mechanistic and statistical models in accelerating cardiovascular research and enabling the vision of precision medicine.

Heart Failure with Preserved Ejection Fraction Trials Have Heterogeneous Control Groups: a Comparison of Kaplan-Meier Curves.

PURPOSE: Previous studies have evaluated intra-study heterogeneities of heart failure with preserved ejection fraction (HFpEF), but inter-study heterogeneities remain poorly understood. We investigate the heterogeneities of outcomes among control groups of HFpEF trials. METHODS: We included randomized controlled trials recruiting HFpEF patients with ejection fraction ≥ 40% and reporting Kaplan-Meier curves for at least 36 months. The Kaplan-Meier curves of control groups were extracted and calculated for hazard ratios and 95% confidence intervals. Two virtual trials were developed to validate the reliability and accuracy of our method. RESULTS: Of 4161 studies, we included six trials containing 7682 HFpEF patients in control groups. The DIG trial had the highest all-cause mortality, cardiovascular mortality, heart failure mortality, and composite endpoints of cardiovascular mortality and heart failure hospitalization (all p < 0.001). The TOPCAT trial had the lowest all-cause mortality, cardiovascular mortality, heart failure hospitalization, and composite of cardiovascular mortality and heart failure hospitalization (all p < 0.001). Adoption of different ejection fraction cut-off values for HFpEF diagnosis did not significantly change the outcomes of control groups in the DIG trial (45% vs. 50%: hazard ratio, 1.05, 95% confidence interval, 0.97-1.13, p = 0.271), or in the CHARM-Preserved trial (40% vs. 50%: hazard ratio, 1.01, 95% confidence interval, 0.93-1.09, p = 0.864) during 36-month follow-up. CONCLUSIONS: The control groups of HFpEF trials have heterogeneous outcomes. Future trials should consider these heterogeneities when designing protocols.

Is a Three-Dimensional Printing Model Better Than a Traditional Cardiac Model for Medical Education? A Pilot Randomized Controlled Study.

BACKGROUND: Three-dimensional (3D) printing is a newly-emerged technology converting a series of two-dimensional images to a touchable 3D model, but no studies have investigated whether or not a 3D printing model is better than a traditional cardiac model for medical education. METHODS: A 3D printing cardiac model was generated using multi-slice computed tomography datasets. Thirty-four medical students were randomized to either the 3D Printing Group taught with the aid of a 3D printing cardiac model or the Traditional Model Group with a commonly used plastic cardiac model. Questionnaires with 10 medical questions and 3 evaluative questions were filled in by the students. RESULTS: A 3D printing cardiac model was successfully generated. Students in the 3D Printing Group were slightly quicker to answer all questions when compared with the Traditional Model Group (224.53 ± 44.13 s vs. 238.71 ± 68.46 s, p = 0.09), but the total score was not significantly different (6.24 ± 1.30 vs. 7.18 ± 1.70, p = 0.12). Neither the students'satisfaction (p = 0.48) nor their understanding of cardiac structures (p = 0.24) was significantly different between two groups. More students in the 3D Printing Group believed that they had understood at least 90% of teaching content (6 vs. 1). Both groups had 12 (70.6%) students who preferred a 3D printing model for medical education. CONCLUSIONS: A 3D printing model was not significantly superior to a traditional model in teaching cardiac diseases in our pilot randomized controlled study, yet more studies may be conducted to validate the real effect of 3D printing on medical education.

Insights for the Captive Management of South China Tigers Based on a Large-Scale Genetic Survey.

There is an urgent need to find a way to improve the genetic diversity of captive South China tiger (SCT, Panthera tigris amoyensis), the most critically endangered taxon of living tigers, facing inbreeding depression. The genomes showed that 13 hybrid SCTs from Meihuashan were divided into two groups; one group included three individuals who had a closer relationship with pureblood SCTs than another group. The three individuals shared more that 40% of their genome with pureblood SCTs and might be potential individuals for genetic rescuing in SCTs. A large-scale genetic survey based on 319 pureblood SCTs showed that the mean microsatellite inbreeding coefficient of pureblood SCTs decreased significantly from 0.1789 to 0.0600 (p = 0.000009) and the ratio of heterozygous loci increased significantly from 38.5% to 43.2% (p = 0.02) after one individual of the Chongqing line joined the Suzhou line and began to breed in the mid-1980s, which is a reason why the current SCTs keep a moderate level of microsatellite heterozygosity and nucleotide diversity. However, it is important to establish a back-up population based on the three individuals through introducing one pureblood SCT into the back-up population every year. The back-up population should be an important reserve in case the pureblood SCTs are in danger in the future.

Machine learning-powered, device-embedded heart sound measurement can optimize AV delay in patients with CRT.

BACKGROUND: Continuous optimization of atrioventricular (AV) delay for cardiac resynchronization therapy (CRT) is mainly performed by electrical means. OBJECTIVE: The purpose of this study was to develop an estimation model of cardiac function that uses a piezoelectric microphone embedded in a pulse generator to guide CRT optimization. METHODS: Electrocardiogram, left ventricular pressure (LVP), and heart sounds were simultaneously collected during CRT device implantation procedures. A piezoelectric alarm transducer embedded in a modified CRT device facilitated recording of heart sounds in patients undergoing a pacing protocol with different AV delays. Machine learning (ML) was used to produce a decision-tree ensemble model capable of estimating absolute maximal LVP (LVPmax) and maximal rise of LVP (LVdP/dtmax) using 3 heart sound-based features. To gauge the applicability of ML in AV delay optimization, polynomial curves were fitted to measured and estimated values. RESULTS: In the data set of ∼30,000 heartbeats, ML indicated S1 amplitude, S2 amplitude, and S1 integral (S1 energy for LVdP/dtmax) as most prominent features for AV delay optimization. ML resulted in single-beat estimation precision for absolute values of LVPmax and LVdP/dtmax of 67% and 64%, respectively. For 20-30 beat averages, cross-correlation between measured and estimated LVPmax and LVdP/dtmax was 0.999 for both. The estimated optimal AV delays were not significantly different from those measured using invasive LVP (difference -5.6 ± 17.1 ms for LVPmax and +5.1 ± 6.7 ms for LVdP/dtmax). The difference in function at estimated and measured optimal AV delays was not statiscally significant (1 ± 3 mm Hg for LVPmax and 9 ± 57 mm Hg/s for LVdP/dtmax). CONCLUSION: Heart sound sensors embedded in a CRT device, powered by a ML algorithm, provide a reliable assessment of optimal AV delays and absolute LVPmax and LVdP/dtmax.

Association between phonocardiography and echocardiography in heart failure patients with preserved ejection fraction.

Aims: Heart failure with preserved ejection fraction (HFpEF) is associated with stiffened myocardium and elevated filling pressure that may be captured by heart sound (HS). We investigated the relationship between phonocardiography (PCG) and echocardiography in symptomatic patients suspected of HFpEF. Methods and results: Consecutive symptomatic patients with sinus rhythm and left ventricular ejection fraction >45% were enrolled. Echocardiography was performed to evaluate the patients' diastolic function, accompanied by PCG measurements. Phonocardiography features including HS amplitude, frequency, and timing intervals were calculated, and their abilities to differentiate the ratio between early mitral inflow velocity and early diastolic mitral annular velocity (E/e') were investigated. Of 45 patients, variable ratio matching was applied to obtain two groups of patients with similar characteristics but different E/e'. Patients with a higher E/e' showed higher first and second HS frequencies and more fourth HS and longer systolic time intervals. The interval from QRS onset to first HS was the best feature for the prediction of E/e' > 9 [area under the curve (AUC): 0.72 (0.51-0.88)] in the matched patients. In comparison, N-terminal pro-brain natriuretic peptide (NT-proBNP) showed an AUC of 0.67 (0.46-0.85), a value not better than any PCG feature (P > 0.05). Conclusion: Phonocardiography features stratify E/e' in symptomatic patients suspected of HFpEF with a diagnostic performance similar to NT-proBNP. Heart sound may serve as a simple non-invasive tool for evaluating HFpEF patients.

Heart sound-derived systolic time intervals for atrioventricular delay optimization in cardiac resynchronization therapy.

BACKGROUND: Phonocardiography (PCG) can be used to determine systolic time intervals (STIs) from ventricular pacing spike to the first heart sound (VS1) and from the first to the second heart sound (S1S2). OBJECTIVE: The purpose of this study was to investigate the relations between STIs and hemodynamics during atrioventricular (AV) delay optimization of biventricular pacing (BiVP) in animals and patients. METHODS: Five pigs with AV block underwent BiVP, while PCG was collected from an epicardial accelerometer. In 21 patients undergoing cardiac resynchronization therapy device implantation, PCG was recorded with a pulse generator-embedded microphone. Optimal AV delays derived from shortest VS1 and longest S1S2 were compared with AV delays derived from highest left ventricular pressure (LVP), maximal rate of rise in LVP, and stroke work. RESULTS: In pigs, VS1 and S1S2 predicted the AV delays with optimal hemodynamics (highest LVP, maximal rate of rise in LVP, and stroke work) by a median error of 2-28 ms, resulting in a median loss of <2% of pump function. In patients, VS1 and S1S2 predicted the optimal AV delay by errors of 32.5 and 37.5 ms, respectively, resulting in 0.2%-0.9% lower LVP and stroke work, which were reduced to 21 and 24 ms in 8 patients with a full-capture AV delay of >180 ms. CONCLUSION: During BiVP with varying AV delays, close relations exist between PCG-derived STIs and hemodynamic parameters. AV delays advised by PCG-derived STIs cause only a minimal loss of pump function compared with those based on invasive hemodynamic measurements. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01832493.

Hemodynamics-driven mathematical model of third heart sound generation.

The proto-diastolic third heart sound (S3) is observed in various hemodynamic conditions in both normal and diseased hearts. We propose a novel, one-degree of freedom mathematical model of mechanical vibrations of heart and blood that generates the third heart sound, implemented in a real-time model of the cardiovascular system (CircAdapt). To examine model functionality, S3 simulations were performed for conditions mimicking the normal heart as well as heart failure with preserved ejection fraction (HFpEF), atrioventricular valve regurgitation (AVR), atrioventricular valve stenosis (AVS) and septal shunts (SS). Simulated S3 showed both qualitative and quantitative agreements with measured S3 in terms of morphology, frequency, and timing. It was shown that ventricular mass, ventricular viscoelastic properties as well as inflow momentum play a key role in the generation of S3. The model indicated that irrespective of cardiac conditions, S3 vibrations are always generated, in both the left and right sides of the heart, albeit at different levels of audibility. S3 intensities increased in HFpEF, AVR and SS, but the changes of acoustic S3 features in AVS were not significant, as compared with the reference simulation. S3 loudness in all simulated conditions was proportional to the level of cardiac output and severity of cardiac conditions. In conclusion, our hemodynamics-driven mathematical model provides a fast and realistic simulation of S3 under various conditions which may be helpful to find new indicators for diagnosis and prognosis of cardiac diseases.

Left Ventricular Pressure Estimation Using Machine Learning-Based Heart Sound Classification.

Objective: A method to estimate absolute left ventricular (LV) pressure and its maximum rate of rise (LV dP/dtmax) from epicardial accelerometer data and machine learning is proposed. Methods: Five acute experiments were performed on pigs. Custom-made accelerometers were sutured epicardially onto the right ventricle, LV, and right atrium. Different pacing configurations and contractility modulations, using isoflurane and dobutamine infusions, were performed to create a wide variety of hemodynamic conditions. Automated beat-by-beat analysis was performed on the acceleration signals to evaluate amplitude, time, and energy-based features. For each sensing location, bootstrap aggregated classification tree ensembles were trained to estimate absolute maximum LV pressure (LVPmax) and LV dP/dtmax using amplitude, time, and energy-based features. After extraction of acceleration and pressure-based features, location specific, bootstrap aggregated classification ensembles were trained to estimate absolute values of LVPmax and its maximum rate of rise (LV dP/dtmax) from acceleration data. Results: With a dataset of over 6,000 beats, the algorithm narrowed the selection of 17 predefined features to the most suitable 3 for each sensor location. Validation tests showed the minimal estimation accuracies to be 93% and 86% for LVPmax at estimation intervals of 20 and 10 mmHg, respectively. Models estimating LV dP/dtmax achieved an accuracy of minimal 93 and 87% at estimation intervals of 100 and 200 mmHg/s, respectively. Accuracies were similar for all sensor locations used. Conclusion: Under pre-clinical conditions, the developed estimation method, employing epicardial accelerometers in conjunction with machine learning, can reliably estimate absolute LV pressure and its first derivative.

Smartphone as an electronic stethoscope: factors influencing heart sound quality.

Aims: Smartphones are equipped with a high-quality microphone which may be used as an electronic stethoscope. We aim to investigate the factors influencing quality of heart sound recorded using a smartphone by non-medical users. Methods and results: An app named Echoes was developed for recording heart sounds using iPhone. Information on phone version and users' characteristics including sex, age, and body mass index (BMI) was collected. Heart sound quality was visually assessed and its relation to phone version and users' characteristics was analysed. A total of 1148 users contributed to 7597 heart sound recordings. Over 80% of users were able to make at least one good-quality recording. Good-, unsure- and bad-quality recordings amounted to 5647 (74.6%), 466 (6.2%) and 1457 (19.2%), respectively. Most good recordings were collected in the first three attempts of the users. Phone version did not significantly change the users' success rate of making a good recording, neither was sex in the first attempt (P = 0.41) or the first three attempts (P = 0.21). Success rate tended to decrease with age in the first attempt (P = 0.06) but not the first three attempts (P = 0.70). BMI did not significantly affect the heart sound quality in a single attempt (P = 0.73) or in three attempts (P = 0.14). Conclusion: Smartphone can be used by non-medical users to record heart sounds in good quality. Age may affect heart sound recording, but hardware, sex, and BMI do not alter the recording.

Second heart sound splitting as an indicator of interventricular mechanical dyssynchrony using a novel splitting detection algorithm.

Second heart sound (S2) splitting results from nonsimultaneous closures between aortic (A2) and pulmonic valves (P2) and may be used to detect timing differences (dyssynchrony) in relaxation between right (RV) and left ventricle (LV). However, overlap of A2 and P2 and the change in heart sound morphologies have complicated detection of the S2 splitting interval. This study introduces a novel S-transform amplitude ridge tracking (START) algorithm for estimating S2 splitting interval and investigates the relationship between S2 splitting and interventricular relaxation dyssynchrony (IRD). First, the START algorithm was validated in a simulated model of heart sound. It showed small errors (<5 ms) in estimating splitting intervals from 10 to 70 ms, with A2/P2 amplitude ratios from 0.2 to 5, and signal-to-noise ratios from 10 to 30 dB. Subsequently, the START algorithm was evaluated in a porcine model employing a wide range of paced RV-LV delays. IRD was quantified by the time difference between invasively measured LV and RV pressure downslopes. Between LV pre-excitation to RV pre-excitation, mean S2 splitting interval decreased from 47 ms to 23 ms (p < .001), accompanied by a decrease in mean IRD from 8 ms to -18 ms (p < .001). S2 splitting interval was significantly correlated with IRD in each experiment (p < .001). In conclusion, the START algorithm can accurately assess S2 splitting and may serve as a useful tool to assess interventricular dyssynchrony.

Surveillance of COVID-19 in the General Population Using an Online Questionnaire: Report From 18,161 Respondents in China.

BACKGROUND: The recent outbreak of the coronavirus disease (COVID-19) has become an international pandemic. So far, little is known about the role of an internet approach in COVID-19 participatory surveillance. OBJECTIVE: The aim of this study is to investigate whether an online survey can provide population-level information for observing prevalence trends during the early phase of an outbreak and identifying potential risk factors of COVID-19 infection. METHODS: A 10-item online questionnaire was developed according to medical guidelines and relevant publications. It was distributed between January 24 and February 17, 2020. The characteristics of respondents and temporal changes of various questionnaire-derived indicators were analyzed. RESULTS: A total of 18,161 questionnaires were returned, including 6.45% (n=1171) from Wuhan City. Geographical distributions of the respondents were consistent with the population per province (R2=0.61, P<.001). History of contact significantly decreased with time, both outside Wuhan City (R2=0.35, P=.002) and outside Hubei Province (R2=0.42, P<.001). The percentage of respondents reporting a fever peaked around February 8 (R2=0.57, P<.001) and increased with a history of contact in the areas outside Wuhan City (risk ratio 1.31, 95% CI 1.13-1.52, P<.001). Male sex, advanced age, and lung diseases were associated with a higher risk of fever in the general population with a history of contact. CONCLUSIONS: This study shows the usefulness of an online questionnaire for the surveillance of outbreaks like COVID-19 by providing information about trends of the disease and aiding the identification of potential risk factors.

Human umbilical cord mesenchymal stem cells polarize RAW264.7 macrophages to an anti-inflammatory subpopulation.

OBJECTIVE: To investigate the effects of human umbilical cord mesenchymal stem cells (hUCMSCs) on the polarization of lipopolysaccharide-stimulated RAW264.7 macrophages. METHODS: Lipopolysaccharide-stimulated RAW264.7 macrophages were co-cultured with hUCMSCs in a Transwell system for 4 d, and then labelled with anti-F4/80, anti-CD86, and anti-CD206 antibodies for flow cytometry. The co-cultured supernatants were detected by enzyme-linked immunosorbent assay for prostaglandin E2. The co-cultured RAW264.7 macrophages were also lysed to measure the intracellular level of inducible nitric oxide synthase. RESULTS: There were significantly more F4/80+CD86+CD206+ RAW264.7 macrophages in the hUCMSCs-treated groups than the control group (P<0.001). The secretion of prostaglandin E2 by lipopolysaccharide-stimulated RAW264.7 macrophages was significantly inhibited in a dose-dependent manner with the addition of hUCMSCs (P<0.001). The expression of iNOS, the intracellular marker of M1 cells, was also significantly inhibited by hUCMSCs (P<0.05). CONCLUSION: hUCMSCs significantly polarize the lipopolysaccharide-stimulated RAW264.7 macrophages from a pro-inflammatory M1 subpopulation to an intermediate subpopulation of anti-inflammatory M2 macrophages, which are associated with a gradual decrease of iNOS and PGE2 levels.

Quality of inclusion criteria in the registered clinical trials of heart failure with preserved ejection fraction: Is it time for a change?

BACKGROUND: No uniform diagnostic criteria have been developed for heart failure with preserved ejection fraction (HFpEF), resulting in huge discrepancies in the patient recruitments of HFpEF trials. This study aims to assess the quality of inclusion criteria in HFpEF trials. METHODS: We systematically searched the International Clinical Trials Registry Platform for HFpEF trials and extracted the basic characteristics and inclusion criteria. We then scored and compared the quality of inclusion criteria using an adapted 5-point scoring system of ejection fraction (EF), symptoms, signs, natriuretic peptides and other tests. RESULTS: A total of 121 trials and 19,494 patients were finally included for statistical analyses. More than half (67/121, 55.4%) of the trials employed 50% as the cut-off value for diagnosing HFpEF. Symptoms (102/121, 84.3%) are mostly provided by trial registrars, followed by natriuretic peptides (46/121, 38.0%) and signs (32/121, 26.4%). Average total scores of inclusion criteria wavily increased from 2.00 in 2002 to 3.00 in 2016 (P=0.04). Interventional trials were not significantly different from observational trials (3.00±1.18 vs. 2.75±1.53, P=0.45), but ongoing trials were higher in total score than completed trials (3.28±1.24 vs. 2.72±1.17, P=0.01). Published trials were not significantly different from the unpublished trials at registration (2.76±1.13 vs. 2.69±1.20, P=0.82), but their total scores significantly increased to 3.48±0.96 at publication (P<0.01). CONCLUSIONS: The qualities of inclusion criteria are heterogeneous and significantly improved with time in registered HFpEF clinical trials. EF, symptoms and signs should be specified at trial registration to make a more reliable diagnosis and to recruit a more homogenous population.

Prognostic value of new-onset right bundle-branch block in acute myocardial infarction patients: a systematic review and meta-analysis.

BACKGROUND: Patients with acute myocardial infarction (AMI) and bundle-branch block have poor prognoses. The new European Society of Cardiology guideline suggests a primary percutaneous coronary intervention strategy when persistent ischemic symptoms occur in patients with persistent ischemic symptoms and right bundle-branch block (RBBB), but the level of evidence is not high. In fact, the presence of RBBB may lead to the misdiagnosis of transmural ischemia and mask the early diagnosis of ST-elevation myocardial infarction. Moreover, new-onset RBBB is occasionally caused by AMI. Our study aims to investigate the prognostic value of new-onset RBBB in AMI. METHODS AND RESULTS: We conducted a meta-analysis of studies to evaluate the prognostic value of RBBB in AMI patients. Of 914 primary records, five studies and 874 MI patients were included for meta-analysis. Compared with previous RBBB, AMI patients with new-onset RBBB had a higher risk of long-term mortality (RR, 1.66, 95% CI [1.31-2.09], I2 = 0.0%, p = 0.000, n = 2), ventricular arrhythmia (RR, 4.86, 95% CI [2.10-11.27], I2 = 0.0%, p = 0.000, n = 3), and cardiogenic shock (RR, 2.76, 95% CI [1.66-4.59], I2 = 0.0%, p = 0.000, n = 3), but a lower risk of heart failure (RR, 0.66, 95% CI [0.52-0.85], I2 = 2.50%, p = 0.001, n = 4). Compared with AMI patients with new-onset permanent RBBB, patients with new-onset transient RBBB had a lower risk of short-term mortality (RR, 0.20, 95% CI [0.11-0.37], I2 = 44.1%, p = 0.000, n = 4). CONCLUSION: New-onset RBBB is likely to increase long-term mortality, ventricular arrhythmia, and cardiogenic shock, but not heart failure in AMI patients. AMI patients with new-onset transient RBBB have a lower risk of short-term mortality than those with new-onset permanent RBBB. Revascularization therapies should be considered when persistent ischemic symptoms occur in patients with RBBB, especially new-onset RBBB.

Aliskiren for heart failure: a systematic review and meta-analysis of randomized controlled trials.

OBJECTIVE: To systematically review and synthesize the currently available evidence of aliskiren for the treatment of heart failure. MATERIALS AND METHODS: We systematically searched the Cochrane, Embase and PubMed databases to identify the randomized controlled trials (RCT) on the effects of aliskiren on heart failure. Data were synthesized with random effects model and presented in forest plot. Publication bias was evaluated with funnel plot. Heterogeneity was evaluated with Begg's test and Egger's test. RESULTS: Of 124 studies, 6 RCT of 9845 heart failure patients were included for meta-analysis, including 3727 patients receiving aliskiren. Compared with the controls, aliskiren did not significantly reduce the all-cause mortality (1.02 [0.91-1.14], I2 = 0%) or cardiovascular mortality (1.02 [0.88-1.17], I2 = 7.3%) of heart failure patients. Total adverse events, renal dysfunction, hypotension and hyperkalaemia were not significantly different between the aliskiren group and control group. Begg's test and Egger's test indicated low heterogeneity. Funnel plots indicated low publication bias. CONCLUSIONS: Aliskiren, either used alone or combined with standard medical therapy, does not significantly reduce the all-cause mortality or cardiovascular mortality of heart failure patients. Although aliskiren does not cause statistically higher adverse events, its adverse events may not be neglected.

Three-dimensional printing in cardiology: Current applications and future challenges.

Three-dimensional (3D) printing has attracted a huge interest in recent years. Broadly speaking, it refers to the technology which converts a predesigned virtual model to a touchable object. In clinical medicine, it usually converts a series of two-dimensional medical images acquired through computed tomography, magnetic resonance imaging or 3D echocardiography into a physical model. Medical 3D printing consists of three main steps: image acquisition, virtual reconstruction and 3D manufacturing. It is a promising tool for preoperative evaluation, medical device design, hemodynamic simulation and medical education, it is also likely to reduce operative risk and increase operative success. However, the most relevant studies are case reports or series which are underpowered in testing its actual effect on patient outcomes. The decision of making a 3D cardiac model may seem arbitrary since it is mostly based on a cardiologist's perceived difficulty in performing an interventional procedure. A uniform consensus is urgently necessary to standardize the key steps of 3D printing from imaging acquisition to final production. In the future, more clinical trials of rigorous design are possible to further validate the effect of 3D printing on the treatment of cardiovascular diseases. (Cardiol J 2017; 24, 4: 436-444).

Three-dimensional printing-guided percutaneous transcatheter closure of secundum atrial septal defect with rim deficiency: First-in-human series.

BACKGROUND: This study aimed to prospectively evaluate the use of 3-dimensional printing (3DP) for the percutaneous transcatheter closure of a secundum atrial septal defect (ASD) with rim deficiency less than 5 mm. METHODS: Patients with ASD were scanned using multi-slice computed tomography to acquire raw data for virtual 3DP reconstruction models. Different ASD occluders were tried on the 3DP models to select the optimal size for intraoperative use. The patients were followed up 1 month postoperatively, and 3DP models were again manufactured to observe the operative effects. RESULTS: From January to April 2016, 6 patients (5 females and 1 male) were recruited. Their average age was 29.5 ± 17.6 years, and the mean ASD size was 13.4 ± 1.3 mm. ASD occlusion succeeded in 5 of 6 cases. There were 1, 2, and 3 cases with 0-mm distance from the defect rim to the aorta, inferior vena cava, and superior vena cava, respectively. ASD occluder sizes were consistent between preoperative simulation and intraoperative placement in 4 cases. One case had occluder size change from 30 mm to 34 mm. CONCLUSIONS: A 3DP model presents ASD in a more visible way and allows more direct preoperative simulation to choose the most appropriate size of occluder, as compared with conventional imaging techniques. This technique is likely to extend the current indications for ASD with an insufficient rim.