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Despite advancements in preoperative prediction of patient outcomes, determination of the most appropriate surgical treatments for patients with severely impaired cardiac function remains a challenge. "UT-Heart" is a multi-scale, multi-physics heart simulator, which can be used to assess the effects of treatment without imposing any burden on the patients. This retrospective study aimed to assess whether UT-Heart can function as a tool that aids decision making for performing mitral valve replacements (MVR) in patients with severe mitral regurgitation (MR) and impaired left ventricular (LV) function. We used preoperative clinical data to create a patient-specific heart model using UT-Heart for a patient who had dilated cardiomyopathy with severe MR. After confirming that this heart model reproduced the preoperative state of the patient, we performed an in silico MVR operation without changing any parameters, such as the end-diastolic volume of the left ventricle, systemic vascular resistance, and the number of myocardiocytes. Among the functional changes introduced by in silico surgery, we found two indices, forward flow and the mechanical efficiency of the work done to the systemic circulation, which may relate positively to the favorable outcome observed in the real world. Thus, multi-scale, multi-physics heart simulators can reproduce the pathophysiology of MR with impaired LV function. By performing in silico MVR and examining the resultant functional changes, we identified two indices, whose usefulness should be tested in future studies.

Introduction: Auscultation is a well-accepted screening method for valvular disease. However, it is not adequate for the screening because the detecting rate of valvular disease by non-cardiologist is about 43% only. Hypothesis: Artificial intelligence (AI)-assisted heart murmur analysis could detect valvular disease following a heart murmur record using a digital stethoscope. Methods: The current study included 71 patients admitted to our hospital to undergo transcatheter aortic valve replacement due to aortic stenosis (AS). We recorded preoperative and postoperative heart murmur using digital stethoscope Eko. Three of 71 cases were diagnosed with severe AS due to prosthetic valve dysfunction. After denoise processing, an acoustic analysis was done to set objective parameters of the murmur. Machine learning was performed to detect severe AS by utilizing the characteristic parameters of severe AS as essential features. A total of 142 sound sources were acquired, 100 cases were used as training data, and the remaining were used as test data to verify the detection accuracy of severe AS. Results: The prolonged duration of the first sound and the peak frequency of systolic murmur with 300 Hz or higher were important for detecting severe AS. The detection accuracy of severe AS was 98% in the support vector machine model. All were detected in PVD cases, but not in the low flow & low gradient cases. Conclusions: It was suggested that severe AS could be detected by AI-assisted heart murmur analysis. We are developing the auscultation device, which is designed to be easy for elderly outpatients, to detect severe AS and to classify the severity of AS with differences in the peak frequency of the murmur.

Introduction: iPS cell-derived cardiac cell sheet (iPS sheet) transplantation is expected to have both cytokine paracrine effect and mechanical effect on the failed heart. In order to clarify the latter effect, we utilized the cardiac simulator “UT-Heart” to quantitatively evaluate the improvement of pumping function of the left ventricle with myocardial infarction covered by the thickened iPS sheet in silico. The direct mechanical impact of iPS sheet with various thicknesses was calculated first, and then the remodeling effect of fiber orientation was investigated. Patient and Method: An infarcted heart model based on the actual patient’s data was created on the computer and an iPS sheet was virtually implanted under the following assumptions: (1) electrophysiologically synchronized with the underlying cardiac muscle, (2) covered the infarct area entirely, (3) the fiber orientation of sheet was parallel to that of the epicardial tissue when attached, (4) if remodeling occurs, the fiber orientations of myocardial tissue and the attached sheet change such that the contraction force and the fiber strains are homogenized in the heart. The UT-Heart simulation was performed while changing iPS sheet thickness from 1mm to 5mm. Results: The LVEF of 18.0 % at pre-implantation was improved to 18.5 % with 1 mm thickness, and 19.6 % with 5 mm thickness without remodeling assumption as shown in the left of the figure. If LV remodeling occurs, the LVEF was improved to 20.9 % with 1mm thickness and 22.8 % with 5mm thickness. The LVESP was 10 mmHg higher than that of pre-implantation even when 1mm thickness was implanted. Conclusion: The direct mechanical effect of the thickened iPS sheet on the distressed LV was quantitatively evaluated in silico. Because changes in fiber orientation have a significant impact on pumping function, the remodeling assumption used herein should be experimentally verified in the future.

Because the genus Corynebacterium colonize the human skin, detection of Corynebacterium striatum in a sterile blood specimen is sometimes considered as contamination. An 80-year-old man who underwent cardiovascular operation presented with high-grade fever postoperatively. Corynebacterium striatum was detected in the blood and wound exudate, and the patient was diagnosed with mediastinitis due to Corynebacterium striatum. One month earlier, a patient with similar symptoms due to C. striatum-related mediastinitis died in our care. The Corynebacterium striatum isolates from both patients had identical biochemical and genetic characteristics, suggesting that Corynebacterium striatum was acquired nosocomially. We have learnt a lesson from this negative experience: early diagnosis of Corynebacterium striatum-related infection and early administration of glycopeptide antibiotics could have saved this patient. It is notable that C. striatum can cause life-threatening infection after cardiovascular operation.

Quadricuspid aortic valve is a rare congenital abnormality often associated with valve incompetence and requires surgical correction in adulthood. However, using a standard suture technique of aortic valve replacement, postoperative complete atrioventricular block is not uncommon because of the downward displacement of the supranumerary leaflet towards the membranous septum. We describe a suture technique where the sutures on the supranumerary leaflet were passed through the aortic sinusal wall above the valvar hinge. This technique can preclude injury to the conduction system, thereby avoiding atrioventricular block.

Background Sternal wound infection is a devastating complication of cardiothoracic surgery that carries high postoperative morbidity and mortality rates. We explored whether our current program of extensive bacteriological examination including repeat blood cultures may contribute to the early diagnosis of sternal wound infection. Methods We retrospectively analyzed 112 patients who were subjected to our bacteriological examination protocol including within 90 days after cardiothoracic surgery. Univariate and multivariate analyses were made in order to identify risk factors for sternal infection. Results The median patient age was 75 years, and 65 patients were male. In 35 cases (31.2%) the blood cultures showed the presence of bacterial infection with the following frequencies: Staphylococcus aureus, 18 cases; Coagulase-negative Staphylococcus, 7 cases; other organisms, 10 cases. Eleven patients presented repeat bacteremia on at least 2 different occasions. Twenty patients (17.8%) presented sternal wound infections. There was no difference in operative mortality between the patients with and without sternal wound infection. Univariate and multivariate analyses demonstrated that bilateral mammary artery use (OR, 13.68, 95% CI, 1.09-167.36, p = 0.043), positive blood culture for Staphylococcus aureus (OR, 19.51, 95% CI, 4.46-104.33, p