Self-supervised motion descriptor for cardiac phase detection in 4D CMR based on discrete vector field estimations

Cardiac magnetic resonance (CMR) sequences visualise the cardiac function voxel-wise over time. Simultaneously, deep learning-based deformable image registration is able to estimate discrete vector fields which warp one time step of a CMR sequence to the following in a self-supervised manner. However, despite the rich source of information included in these 3D+t vector fields, a standardised interpretation is challenging and the clinical applications remain limited so far. In this work, we show how to efficiently use a deformable vector field to describe the underlying dynamic process of a cardiac cycle in form of a derived 1D motion descriptor. Additionally, based on the expected cardiovascular physiological properties of a contracting or relaxing ventricle, we define a set of rules that enables the identification of five cardiovascular phases including the end-systole (ES) and end-diastole (ED) without the usage of labels. We evaluate the plausibility of the motion descriptor on two challenging multi-disease, -center, -scanner short-axis CMR datasets. First, by reporting quantitative measures such as the periodic frame difference for the extracted phases. Second, by comparing qualitatively the general pattern when we temporally resample and align the motion descriptors of all instances across both datasets. The average periodic frame difference for the ED, ES key phases of our approach is $0.80\pm{0.85}$, $0.69\pm{0.79}$ which is slightly better than the inter-observer variability ($1.07\pm{0.86}$, $0.91\pm{1.6}$) and the supervised baseline method ($1.18\pm{1.91}$, $1.21\pm{1.78}$). Code and labels will be made available on our GitHub repository. https://github.com/Cardio-AI/cmr-phase-detectionComment: accepted for the STACOM2022 workshop @ MICCAI202

Multivendor Evaluation of Automated MRI Postprocessing of Biventricular Size and Function for Children With and Without Congenital Heart Defects

BACKGROUND Manually segmenting cardiac structures is time-consuming and produces variability in MRI assessments. Automated segmentation could solve this. However, current software is developed for adults without congenital heart defects (CHD). PURPOSE To evaluate automated segmentation of left ventricle (LV) and right ventricle (RV) for pediatric MRI studies. STUDY TYPE Retrospective comparative study. POPULATION Twenty children per group of: healthy children, LV-CHD, tetralogy of Fallot (ToF), and univentricular CHD, aged 11.7 [8.9-16.0], 14.2 [10.6-15.7], 14.6 [11.6-16.4], and 12.2 [10.2-14.9] years, respectively. SEQUENCE/FIELD STRENGTH Balanced steady-state free precession at 1.5 T. ASSESSMENT Biventricular volumes and masses were calculated from a short-axis stack of images, which were segmented manually and using two fully automated software suites (Medis Suite 3.2, Medis, Leiden, the Netherlands and SuiteHeart 5.0, Neosoft LLC, Pewaukee, USA). Fully automated segmentations were manually adjusted to provide two further sets of segmentations. Fully automated and adjusted automated segmentation were compared to manual segmentation. Segmentation times and reproducibility for each method were assessed. STATISTICAL TESTS Bland Altman analysis and intraclass correlation coefficients (ICC) were used to compare volumes and masses between methods. Postprocessing times were compared by paired t-tests. RESULTS Fully automated methods provided good segmentation (ICC > 0.90 compared to manual segmentation) for the LV in the healthy and left-sided CHD groups (eg LV-EDV difference for healthy children 1.4 ± 11.5 mL, ICC: 0.97, for Medis and 3.0 ± 12.2 mL, ICC: 0.96 for SuiteHeart). Both automated methods gave larger errors (ICC: 0.62-0.94) for the RV in these populations, and for all structures in the ToF and univentricular CHD groups. Adjusted automated segmentation agreed well with manual segmentation (ICC: 0.71-1.00), improved reproducibility and reduced segmentation time in all patient groups, compared to manual segmentation. DATA CONCLUSION Fully automated segmentation eliminates observer variability but may produce large errors compared to manual segmentation. Manual adjustments reduce these errors, improve reproducibility, and reduce postprocessing times compared to manual segmentation. Adjusted automated segmentation is reasonable in children with and without CHD. EVIDENCE LEVEL 3. TECHNICAL EFFICACY Stage 2

Combined Prospective Seroconversion and PCR Data of Selected Cohorts Indicate a High Rate of Subclinical SARS-CoV-2 Infections—an Open Observational Study in Lower Saxony, Germany

Despite lockdown measures, intense symptom-based PCR, and antigen testing, the SARS-CoV-2 pandemic spread further. In this open observational study conducted in Lower Saxony, Germany, voluntary SARS-CoV-2 PCR tests were performed from April 2020 until June 2021, supported by serum antibody testing to prove whether PCR testing in subjects with none or few symptoms of COVID-19 is a suitable tool to manage the pandemic. In different mobile stations, 4,817 subjects from three different working fields participated in the PCR testing. Serum antibody screening using the SARS-CoV-2 ViraChip IgG (Viramed, Germany) and the Elecsys Anti-SARS-CoV-2 assay (Roche, Germany) was performed alongside virus neutralization testing. Subjects were questioned regarding comorbidities and COVID-19 symptoms. Fifty-one subjects with acute SARS-CoV-2 infection were detected of which 31 subjects did not show any symptoms possibly characteristic for COVID-19. An additional 37 subjects reported a previous SARS-CoV-2 infection (total prevalence 1.82%). Seroconversion was discovered in 58 subjects with known SARS-CoV-2 infection and in 58 subjects that never had a positive PCR test. The latter had a significantly lower Charlson Comorbidity Index, and one third of them were asymptomatic. In 50% of all seroconverted subjects, neutralizing serum antibodies (NAbs) were detectable in parallel to N/S1 (n = 16) or N/S1/S2 antigen specific antibodies (n = 40) against SARS-CoV-2. NAb titers decreased within 100 days after PCR-confirmed SARS-CoV-2 acute infection by at least 2.5-fold. A relatively high rate of subclinical SARS-CoV-2 infections may contribute to the spread of SARS-CoV-2, suggesting that in addition to other intervention strategies, systematic screening of asymptomatic persons by PCR testing may significantly enable better pandemic control

Matched comparison of decellularized homografts and bovine jugular vein conduits for pulmonary valve replacement in congenital heart disease

For decades, bovine jugular vein conduits (BJV) and classic cryopreserved homografts have been the two most widely used options for pulmonary valve replacement (PVR) in congenital heart disease. More recently, decellularized pulmonary homografts (DPH) have provided an alternative avenue for PVR. Matched comparison of patients who received DPH for PVR with patients who received bovine jugular vein conduits (BJV) considering patient age group, type of heart defect, and previous procedures. 319 DPH patients were matched to 319 BJV patients; the mean age of BJV patients was 15.3 (SD 9.5) years versus 19.1 (12.4) years in DPH patients (p = 0.001). The mean conduit diameter was 24.5 (3.5) mm for DPH and 20.3 (2.5) mm for BJV (p < 0.001). There was no difference in survival rates between the two groups after 10 years (97.0 vs. 98.1%, p = 0.45). The rate of freedom from endocarditis was significantly lower for BJV patients (87.1 vs. 96.5%, p = 0.006). Freedom from explantation was significantly lower for BJV at 10 years (81.7 vs. 95.5%, p = 0.001) as well as freedom from any significant degeneration at 10 years (39.6 vs. 65.4%, p < 0.001). 140 Patients, matched for age, heart defect type, prior procedures, and conduit sizes of 20–22 mm (± 2 mm), were compared separately; mean age BJV 8.7 (4.9) and DPH 9.5 (7.3) years (p = n.s.). DPH showed 20% higher freedom from explantation and degeneration in this subgroup (p = 0.232). Decellularized pulmonary homografts exhibit superior 10-year results to bovine jugular vein conduits in PVR