Multi-person Implicit Reconstruction from a Single Image

We present a new end-to-end learning framework to obtain detailed and spatially coherent reconstructions of multiple people from a single image. Existing multi-person methods suffer from two main drawbacks: they are often model-based and therefore cannot capture accurate 3D models of people with loose clothing and hair; or they require manual intervention to resolve occlusions or interactions. Our method addresses both limitations by introducing the first end-to-end learning approach to perform model-free implicit reconstruction for realistic 3D capture of multiple clothed people in arbitrary poses (with occlusions) from a single image. Our network simultaneously estimates the 3D geometry of each person and their 6DOF spatial locations, to obtain a coherent multi-human reconstruction. In addition, we introduce a new synthetic dataset that depicts images with a varying number of inter-occluded humans and a variety of clothing and hair styles. We demonstrate robust, high-resolution reconstructions on images of multiple humans with complex occlusions, loose clothing and a large variety of poses and scenes. Our quantitative evaluation on both synthetic and real world datasets demonstrates state-of-the-art performance with significant improvements in the accuracy and completeness of the reconstructions over competing approaches

Haemolysis as a first sign of thromboembolic event and acute pump thrombosis in patients with the continuous-flow

Background Despite advances in pump technology, thromboembolic events/acute pump thrombosis remain potentially life-threatening complications in patients with continuous-flow left ventricular assist devices (CF-LVAD). We sought to determine early signs of thromboembolic event/ pump thrombosis in patients with CF-LVAD, which could lead to earlier intervention. Methods We analysed all HeartMate II recipients (n = 40) in our centre between December 2006 and July 2013. Thromboembolic event/pump thrombosis was defined as a transient ischaemic attack (TIA), ischaemic cerebrovascular accident (CVA), or pump thrombosis. Results During median LVAD support of 336 days [IQR: 182–808], 8 (20%) patients developed a thromboembolic event/pump thrombosis (six TIA/CVA, two pump thromboses). At the time of the thromboembolic event/pump thrombosis, significantly higher pump power was seen compared with the no-thrombosis group (8.2 ± 3.0 vs. 6.4 ± 1.4 W, p = 0.02), as well as a trend towards a lower pulse index (4.1 ± 1.5 vs. 5.0 ± 1.0, p = 0.05) and a trend towards higher pump flow (5.7 ± 1.0 vs. 4.9 ± 1.9 L m, p = 0.06). The thrombosis group had a more than fourfold higher lactate dehydrogenase (LDH) median 1548 [IQR: 754– 2379] vs. 363 [IQR: 325–443] U/L, p = 0.0001). Bacterial (n = 4) or viral (n = 1) infection was present in 5 out of 8 patients. LDH > 735 U/L predicted thromboembolic events/ pump thrombosis with a positive predictive value of 88%. Conclusions In patients with a CF-LVAD (HeartMate II), thromboembolic events and/or pump thrombosis are associated with symptoms and signs of acute haemolysis as manifested by a high LDH, elevated pump power and decreased pulse index, especially in the context of an infection

Causes and predictors of early mortality in patients treated with left ventricular assist device implantation in the European Registry of Mechanical Circulatory Support (EUROMACS)

Purpose: The aim of the study was to analyze early mortality after continuous-flow left ventricular assist device (LVAD) implantation which remains high. Methods: We analyzed consecutive (n = 2689) patients from the European Registry for Patients with Mechanical Circulatory Support (EUROMACS) undergoing continuous-flow LVAD implantation. The primary outcome was early (< 90 days) mortality. Secondary outcomes were differential causes of early post-operative death following LVAD implantation. Results: Univariable and multivariable analysis as well as regression analysis were used to examine determinants and differential causes of early (< 90 days) mortality after LVAD implantation. During the first 90 days, 2160 (80%) patients were alive with ongoing LVAD support, 40(2%) patients underwent heart transplantation, and 487(18%) deceased. The main causes of early death were MOF (36%), sepsis (28%), cardiopulmonary failure (CPF; 10%), CVA (9%), and right-sided heart failure (RHF, 8%). Furthermore, MOF and sepsis are 70% of causes of death in the first week. Independent clinical predictors of early death were age, female sex, INTERMACS profile 1 to 3, and ECMO. Laboratory predictors included elevated serum creatinine, total bilirubin, lactate, and low hemoglobin. Furthermore, hemodynamic predictors included elevated RA-to-PCWP ratio, pulmonary vascular resistance, and low systemic vascular resistance. Longer total implantation time was also independent predictor of early mortality. A simple model of 12 variables predicts early mortality following LVAD implantation with a good discriminative power with area under the curve of 0.75. Conclusions: In the EUROMACS registry, approximately one out of five patients die within 90 days after LVAD implantation. Early mortality is primarily dominated by multiorgan failure followed by sepsis. A simple model identifies important parameters which are associated with early mortality following LVAD implantation

Functional evaluation of sublingual microcirculation indicates successful weaning from VA-ECMO in cardiogenic shock

Background: Veno-arterial extracorporeal membrane oxygenation (VA-ECMO) is increasingly adopted for the treatment of cardiogenic shock (CS). However, a marker of successful weaning remains largely unknown. Our hypothesis was that successful weaning is associated with sustained microcirculatory function during ECMO flow reduction. Therefore, we sought to test the usefulness of microcirculatory imaging in the same sublingual spot, using incident dark field (IDF) imaging in assessing successful weaning from VA-ECMO and compare IDF imaging with echocardiographic parameters. Methods: Weaning was performed by decreasing the VA-ECMO flow to 50% (F50) from the baseline

Evaluation of patients with a HeartMate 3 left ventricular assist device using echocardiographic particle image velocimetry

Purpose: Poor left ventricular (LV) function may affect the physiological intraventricular blood flow and physiological vortex formation. The aim of this study was to investigate the pattern of intraventricular blood flow dynamics in patients with LV assist devices (LVADs) using echocardiographic particle image velocimetry. Materials and methods: This prospective study included 17 patients (mean age 57 ± 11 years, 82% male) who had received an LVAD (HeartMate 3, Abbott Laboratories, Chicago, Illinois, USA) because of end-stage heart failure and poor LV function. Eleven (64%) patients had ischemic cardiomyopathy, and six patients (36%) had nonischemic cardiomyopathy. All patients underwent echocardiography, including intravenous administration of an ultrasound-enhancing agent (SonoVue, Bracco, Milan, Italy). Echocardiographic particle image velocimetry was used to quantify LV blood flow dynamics, including vortex formation (Hyperflow software, Tomtec imaging systems Gmbh, Unterschleissheim, Germany). Results: Contrast-enhanced ultrasound was well tolerated in all patients and was performed without adverse reactions or side effects. The LVAD function parameters did not change during or after the ultrasound examination. The LVAD flow was on average 4.3 ± 0.3 L/min, and the speed was 5247 ± 109 rotations/min. The quantification of LV intraventricular flow demonstrated substantial impairment of vortex parameters. The energy dissipation, vorticity, and kinetic energy fluctuation indices were severely impaired. Conclusions: Echo particle velocimetry is safe and feasible for the quantitative assessment of intraventricular flow in patients with an LVAD. The intraventricular LV flow and vortex parameters are severely impaired in these patients

Preoperative right heart hemodynamics predict postoperative acute kidney injury after heart transplantation

Purpose: Acute kidney injury (AKI) frequently occurs after heart transplantation (HTx), but its relation to preoperative right heart hemodynamic (RHH) parameters remains unknown. Therefore, we aimed to determine their predictive properties for postoperative AKI severity within 30 days after HTx. Methods: From 1984 to 2016, all consecutive HTx recipients (n = 595) in our tertiary referral center were included and analyzed for the occurrence of postoperative AKI staged by the kidney disease improving global outcome criteria. The effects of preoperative RHH parameters on postoperative AKI were calculated using logistic regression, and predictive accuracy was assessed using integrated discrimination improvement (IDI), net reclassification improvement (NRI), and area under the receiver operating characteristic curves (AUC). Results: Postoperative AKI occurred in 430 (72%) patients including 278 (47%) stage 1, 66 (11%) stage 2, and 86 (14%) stage 3 cases. Renal replacement therapy (RRT) was administered in 41 (7%) patients. Patients with higher AKI stages had also higher baseline right atrial pressure (RAP; median 7, 7, 8, and in RRT 11 mmHg, p trend = 0.021), RAP-to-pulmonary capillary wedge pressure ratio (median 0.37, 0.36, 0.40, 0.47, p trend = 0.009), and lower pulmonary artery pulsatility index (PAPi) values (median 2.83, 3.17, 2.54, 2.31, p trend = 0.012). Higher RAP and lower PAPi values independently predicted AKI severity [adjusted odds ratio (OR) per doubling of RAP 1.16 (1.02–1.32), p = 0.029; of PAPi 0.85 (0.75–0.96), p = 0.008]. Based on IDI, NRI, and delta AUC, inclusion of these parameters improved the models’ predictive accuracy. Conclusions: Preoperative PAPi and RAP strongly predict the development of AKI early after HTx and can be used as early AKI predictors

Drawing: Towards an Intelligence of Seeing

Changes in the microcirculatory parameters in the survivor and non-survivor groups at the following time points: initiation of the VA-ECMO insertion (T1); 48–72 h after VA-ECMO initiation (T2); and 5–6 days after (T3). (DOCX 15 kb