Improved image quality in transcatheter aortic valve implantation planning CT using deep learning-based image reconstruction.

Background: This study aims to evaluate the impact of a novel deep learning-based image reconstruction (DLIR) algorithm on the image quality in computed tomographic angiography (CTA) for pre-interventional planning of transcatheter aortic valve implantation (TAVI). Methods: We analyzed 50 consecutive patients (median age 80 years, 25 men) who underwent TAVI planning CT on a 256-dectector-row CT. Images were reconstructed with adaptive statistical iterative reconstruction V (ASIR-V) and DLIR. Intravascular image noise, edge sharpness, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were quantified for ascending aorta, descending aorta, abdominal aorta and iliac arteries. Two readers (one radiologist and one interventional cardiologist) scored task-specific subjective image quality on a five-point scale. Results: DLIR significantly reduced median image noise by 29-57% at all anatomical locations (all P<0.001). Accordingly, median SNR improved by 44-133% (all P<0.001) and median CNR improved by 44-125% (all P<0.001). DLIR significantly improved subjective image quality for all four pre-specified TAVI-specific tasks (measuring the annulus, assessing valve morphology and calcifications, the coronary ostia, and the suitability of the aorto-iliac access route) for both the radiologist and the interventional cardiologist (P≤0.001). Measurements of the aortic annulus circumference, area and diameter did not differ between ASIR-V and DLIR reconstructions (all P>0.05). Conclusions: DLIR significantly improves objective and subjective image quality in TAVI planning CT compared to a state-of-the-art iterative reconstruction without affecting measurements of the aortic annulus. This may provide an opportunity for further reductions in contrast medium volume in this population.

Expedient assessment of post-infarct remodeling by native cardiac magnetic resonance imaging in mice.

Novel therapeutic strategies aiming at improving the healing process after an acute myocardial infarction are currently under intense investigation. The mouse model plays a central role for deciphering the underlying mechanisms on a molecular and cellular level. Therefore, we intended to assess in-vivo post-infarct remodeling as comprehensively as possible using an expedient native magnetic resonance imaging (MRI) in the two most prominent infarct models, permanent ligation (PL) of the left anterior descending artery (LAD) versus ischemia reperfusion (I/R). Mice were subjected to either permanent or transient (45 min) occlusion of the LAD. After 3 weeks, examinations were performed with a 7-Tesla small animal MRI system. Data analysis was performed with the freely available software Segment. PL resulted in a massive dilation of the left ventricle, accompanied by hypertrophy of the non-infarcted myocardium and a decline of contractile function. These effects were less pronounced following I/R compared to healthy animals. Single plane assessments were not sufficient to capture the specific differences of left ventricular (LV) properties between the two infarct models. Bulls-eye plots were found to be an ideal tool for qualitative LV wall assessment, whereas a multi-slice sector-based analysis of wall regions is ideal to determine differences in hypertrophy, lateral wall thinning and wall thickening on a quantitative level. We combine the use of polar map-based analysis of LV wall properties with volumetric measurements using simple CINE CMR imaging. Our strategy represents a versatile and easily available tool for serial assessment of the LV during the remodeling process. Our study contributes to a better understanding of the effects of novel therapies targeting the healing of damaged myocardium.

Heart rate at discharge in patients with acute decompensated heart failure is a predictor of mortality.

AIMS: Heart failure is a syndrome with increasing prevalence in concordance with the aging population and better survival rates from myocardial infarction. Morbidity and mortality are high in chronic heart failure patients, particularly in those with hospital admission for acute decompensation. Several risk stratification tools and score systems have been established to predict mortality in chronic heart failure patients. However, identification of patients at risk with easy obtainable clinical factors that can predict mortality in acute decompensated heart failure (ADHF) are needed to optimize the care-path. METHODS AND RESULTS: We retrospectively analyzed electronic medical records of 78 patients with HFrEF and HFmrEF who were hospitalized with ADHF in the Heart Center of the University Hospital Cologne in the year 2011 and discharged from the ward after successful treatment. 37.6 ± 16.4 months after index hospitalization 30 (38.5%) patients had died. This mortality rate correlated well with the calculated predicted survival with the Seattle Heart Failure Model (SHFM) for each individual patient. In our cohort, we identified elevated heart rate at discharge as an independent predictor for mortality (p = 0.016). The mean heart rate at discharge was lower in survived patients compared to patients who died (72.5 ± 11.9 vs. 79.1 ± 11.2 bpm. Heart rate of 77 bpm or higher was associated with an almost doubled mortality risk (p = 0.015). Heart rate elevation of 5 bpm was associated with an increase of mortality of 25% (p = 0.022). CONCLUSIONS: Patients hospitalized for ADHF seem to have a better prognosis, when heart rate at discharge is < 77 bpm. Heart rate at discharge is an easily obtainable biomarker for risk prediction of mortality in HFrEF and HFmrEF patients treated for acute cardiac decompensation. Taking into account this parameter could be useful for guiding treatment strategies in these high-risk patients. Prospective data for validation of this biomarker and specific intervention are needed.

Fully automated quantification of left ventricular volumes and function in cardiac MRI: clinical evaluation of a deep learning-based algorithm.

To investigate the performance of a deep learning-based algorithm for fully automated quantification of left ventricular (LV) volumes and function in cardiac MRI. We retrospectively analysed MR examinations of 50 patients (74% men, median age 57 years). The most common indications were known or suspected ischemic heart disease, cardiomyopathies or myocarditis. Fully automated analysis of LV volumes and function was performed using a deep learning-based algorithm. The analysis was subsequently corrected by a senior cardiovascular radiologist. Manual volumetric analysis was performed by two radiology trainees. Volumetric results were compared using Bland-Altman statistics and intra-class correlation coefficient. The frequency of clinically relevant differences was analysed using re-classification rates. The fully automated volumetric analysis was completed in a median of 8 s. With expert review and corrections, the analysis required a median of 110 s. Median time required for manual analysis was 3.5 min for a cardiovascular imaging fellow and 9 min for a radiology resident (p < 0.0001 for all comparisons). The correlation between fully automated results and expert-corrected results was very strong with intra-class correlation coefficients of 0.998 for end-diastolic volume, 0.997 for end-systolic volume, 0.899 for stroke volume, 0.972 for ejection fraction and 0.991 for myocardial mass (all p < 0.001). Clinically meaningful differences between fully automated and expert corrected results occurred in 18% of cases, comparable to the rate between the two manual readers (20%). Deep learning-based fully automated analysis of LV volumes and function is feasible, time-efficient and highly accurate. Clinically relevant corrections are required in a minority of cases.

Detection of arrhythmia using an implantable cardiac monitor following a cryptogenic stroke: a single-center observational study.

BACKGROUND: Detection of atrial fibrillation (AF) after cryptogenic stroke (CS) has therapeutic implications, but the most effective type and optimal duration of monitoring have still to be defined. This study that involved patients with CS or transient ischemic attack (TIA), all of whom carried an implantable cardiac monitor (ICM), sought to assess the incidence of AF and other arrhythmia detected using tele-monitoring or interval-based follow-up by an internal cardiologist at the university medical center of Rostock (UMR) or an external cardiologist. METHODS: The ICM implantation was performed during the inpatient stay in the neurology department, with inclusion and exclusion criteria jointly determined by the neurology and cardiology departments. Cardiologists programmed individual threshold values during ICM implantation, which were designed to instantly trigger an episode being recording and an alarm message being sent out. Outpatient care consisted of tele-monitoring of implants or interval-based follow-up care. RESULTS: The indication for ICM implantation was made for 102 patients, 88 of whom underwent ICM implantation, with full documentation available for these 88 study patients. Within a median observation period of 21.5 months, AF occurred in 19 patients, with a median observation time to the event of 7 months. In all cases, AF detection was followed by immediate medical intervention. Comparing patients with and without AF revealed that the median age of the AF group exceeded by 10 years that of the other patients. Stroke recurrence was recorded in five patients, with a median observation time to the event of 9 months. Comparing patients with and without stroke recurrence revealed that the median age in the stroke recurrence group tended to be higher by 14 years. No statistically significant between-group differences were found with regard to integration into tele-monitoring, nor were there any differences identified between outpatient care at the UMR or in the outpatient sector. CONCLUSIONS: This study confirmed the feasibility of using an interdisciplinary and intersectoral therapeutic approach for monitoring CS patients with implanted ICMs. Further randomized studies are warranted to confirm these encouraging data. An open discussion concerning optimal care forms and opportunities for introducing digitizing care pathways appears warranted.

Cardiac MRI-Update 2020.

PURPOSE: To review emerging techniques in cardiac magnetic resonance imaging (CMR) and their clinical applications with a special emphasis on new technologies, recent trials, and updated guidelines. TECHNOLOGICAL INNOVATIONS: The utility of CMR has expanded with the development of new MR sequences, postprocessing techniques, and artificial intelligence-based technologies, which have substantially increased the spectrum, quality, and reliability of information that can be obtained by CMR. ESTABLISHED AND EMERGING INDICATIONS: The CMR modality has become an irreplaceable tool for diagnosis, treatment guidance and follow-up of patients with ischemic heart disease, myocarditis, and cardiomyopathies. Its role has been further strengthened by recent trials and guidelines. Quantitative mapping techniques are increasingly used for tissue characterization and detection of diffuse myocardial changes including myocardial storage diseases. PRACTICAL RECOMMENDATIONS: With state-of-the-art CMR sequences, postprocessing techniques and understanding of their interpretation, CMR makes invaluable contributions to provide state-of-the-art diagnostics and care for cardiac patients in a multidisciplinary team.

Impact of transcatheter aortic valve implantation on the risk of mortality in patients with severe aortic valve diseases: a health insurance-based analysis.

Background: Transcatheter aortic valve implantation (TAVI) is a minimally invasive treatment for aortic valve patients who are inoperable or have a prohibitively high surgical risk for surgical aortic valve replacement (SAVR). Most studies compare the efficacy of TAVI and SAVR, yet the assessment of TAVI for this group of patients requires more study. Methods: This quasiexperimental study compares TAVI cases (ages of 75-90 years, n=187) ex-post with a control group without implantation (n=728, 4:1 ratio intended). The control group was drawn randomly on the condition that it matches the TAVI cases based on age at aortic valve disease incidence, gender and comorbidity index. The mortality risk is analysed from incident diagnosis. Data were taken from three random samples of health claims data in Germany's largest public health insurance (Allgemeine Ortskrankenkassen) and cover the years 2004-2013 (n=750 000). Results: Compared with the medically treated control group with 6+ comorbidities, medically treated patients with fewer comorbidities have half the mortality risk (HR 0.48, 95% CI 0.34 to 0.69, p<0.001). TAVI patients with fewer than six comorbidities show a mortality risk half that (HR 0.23, 95% CI 0.09 to 0.63, p=0.004). TAVI patients with 6+ comorbidities do not benefit from TAVI compared with the control group with 6+ comorbidities (HR 0.99, 95% CI 0.71 to 1.36, p=0.93). Conclusion: TAVI is an effective therapy for aortic valve disease patients with few comorbidities; it is not effective for patients with a high comorbidity burden. Careful assessment of the individual patient in terms of comorbidities is important for a beneficial outcome.

A new technique to implant a transcatheter inflatable, fully repositionable prosthesis in aortic stenosis with severe asymmetric calcification.

OBJECTIVES: In contrast to stented transcatheter aortic valves, the Direct Flow Medical (DFM) valve is a stentless bovine aortic bioprosthesis mounted in a non-metallic inflatable frame. Hence, severe asymmetric annular calcification may result in residually elevated transaortic pressure gradients after DFM implantation. We present a novel intraprocedural dilatation (IDIL) technique for successful implantation of the DFM valve in the presence of complex annular calcification. METHODS: Between January 2014 and May 2015, 55 patients underwent DFM valve-based transcatheter aortic valve implantation at our institution. Of these, 5 patients required an IDIL technique due to a residual intraoperative transaortic pressure mean gradient above 15 mmHg. The mean patient age was 73 ± 8.2 years; the mean logistic EuroSCORE was 24.5 ± 8.2% and the mean Society of Thoracic Surgeons score was 6.3 ± 4.3%. RESULTS: The IDIL technique immediately attenuated transvalvular mean pressure gradients from 20 ± 2 mmHg to 6 ± 1 mmHg. The results remained stable during the 30-day observation period at 10 ± 3 mmHg. Minimal paravalvular aortic regurgitation (trace) was detected in 2 patients. No in-hospital deaths were observed. CONCLUSIONS: The IDIL technique facilitates safe DFM valve implantation in patients with complex asymmetric annular calcification without adverse side effects on valve structure or performance in short-term follow-up.