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Alzheimer's disease (AD), the most common cause of dementia in the elderly, is a neurodegenerative disorder associated with neurovascular dysfunction and cognitive decline. While the deposition of amyloid β peptide (Aβ) and the formation of neurofibrillary tangles (NFTs) are the pathological hallmarks of AD-affected brains, the majority of cases exhibits a combination of comorbidities that ultimately lead to multi-organ failure. Of particular interest, it can be demonstrated that Aβ pathology is present in the hearts of patients with AD, while the formation of NFT in the auditory system can be detected much earlier than the onset of symptoms. Progressive hearing impairment may beget social isolation and accelerate cognitive decline and increase the risk of developing dementia. The current review discusses the concept of a brain–ear–heart axis by which Aβ and NFT inhibition could be achieved through targeted supplementation of neurotrophic factors to the cochlea and the brain. Such amyloid inhibition might also indirectly affect amyloid accumulation in the heart, thus reducing the risk of developing AD-associated amyloid cardiomyopathy and cardiovascular disease.
We aimed to elucidate the diagnostic potential of the C-X-C motif chemokine receptor 4 (CXCR4)-directed positron emission tomography (PET) tracer \(^{68}\)Ga-Pentixafor in patients with poorly differentiated neuroendocrine carcinomas (NEC), relative to the established reference standard \(^{18}\)F-FDG PET/computed tomography (CT). In our database, we retrospectively identified 11 treatment-naïve patients with histologically proven NEC, who underwent \(^{18}\)F-FDG and CXCR4-directed PET/CT for staging and therapy planning. The images were analyzed on a per-patient and per-lesion basis and compared to immunohistochemical staining (IHC) of CXCR4 from PET-guided biopsies. \(^{68}\)Ga-Pentixafor visualized tumor lesions in 10/11 subjects, while \(^{18}\)F-FDG revealed sites of disease in all 11 patients. Although weak to moderate CXCR4 expression could be corroborated by IHC in 10/11 cases, \(^{18}\)F-FDG PET/CT detected significantly more tumor lesions (102 vs. 42; total lesions, n = 107; p < 0.001). Semi-quantitative analysis revealed markedly higher 18F-FDG uptake as compared to \(^{68}\)Ga-Pentixafor (maximum and mean standardized uptake values (SUV) and tumor-to-background ratios (TBR) of cancerous lesions, SUVmax: 12.8 ± 9.8 vs. 5.2 ± 3.7; SUVmean: 7.4 ± 5.4 vs. 3.1 ± 3.2, p < 0.001; and, TBR 7.2 ± 7.9 vs. 3.4 ± 3.0, p < 0.001). Non-invasive imaging of CXCR4 expression in NEC is inferior to the reference standard \(^{18}\)F-FDG PET/CT.
Purpose
Artificial neural networks show promising performance in automatic segmentation of cardiac MRI. However, training requires large amounts of annotated data and generalization to different vendors, field strengths, sequence parameters, and pathologies is limited. Transfer learning addresses this challenge, but specific recommendations regarding type and amount of data required is lacking. In this study, we assess data requirements for transfer learning to experimental cardiac MRI at 7T where the segmentation task can be challenging. In addition, we provide guidelines, tools, and annotated data to enable transfer learning approaches by other researchers and clinicians.
Methods
A publicly available segmentation model was used to annotate a publicly available data set. This labeled data set was subsequently used to train a neural network for segmentation of left ventricle and myocardium in cardiac cine MRI. The network is used as starting point for transfer learning to 7T cine data of healthy volunteers (n = 22; 7873 images) by updating the pre-trained weights. Structured and random data subsets of different sizes were used to systematically assess data requirements for successful transfer learning.
Results
Inconsistencies in the publically available data set were corrected, labels created, and a neural network trained. On 7T cardiac cine images the model pre-trained on public imaging data, acquired at 1.5T and 3T, achieved DICE\(_{LV}\) = 0.835 and DICE\(_{MY}\) = 0.670. Transfer learning using 7T cine data and ImageNet weight initialization improved model performance to DICE\(_{LV}\) = 0.900 and DICE\(_{MY}\) = 0.791. Using only end-systolic and end-diastolic images reduced training data by 90%, with no negative impact on segmentation performance (DICE\(_{LV}\) = 0.908, DICE\(_{MY}\) = 0.805).
Conclusions
This work demonstrates and quantifies the benefits of transfer learning for cardiac cine image segmentation. We provide practical guidelines for researchers planning transfer learning projects in cardiac MRI and make data, models, and code publicly available.
Purpose
To fully automatically derive quantitative parameters from late gadolinium enhancement (LGE) cardiac MR (CMR) in patients with myocardial infarction and to investigate if phase sensitive or magnitude reconstructions or a combination of both results in best segmentation accuracy.
Methods
In this retrospective single center study, a convolutional neural network with a U-Net architecture with a self-configuring framework (“nnU-net”) was trained for segmentation of left ventricular myocardium and infarct zone in LGE-CMR. A database of 170 examinations from 78 patients with history of myocardial infarction was assembled. Separate fitting of the model was performed, using phase sensitive inversion recovery, the magnitude reconstruction or both contrasts as input channels.
Manual labelling served as ground truth. In a subset of 10 patients, the performance of the trained models was evaluated and quantitatively compared by determination of the Sørensen-Dice similarity coefficient (DSC) and volumes of the infarct zone compared with the manual ground truth using Pearson’s r correlation and Bland-Altman analysis.
Results
The model achieved high similarity coefficients for myocardium and scar tissue. No significant difference was observed between using PSIR, magnitude reconstruction or both contrasts as input (PSIR and MAG; mean DSC: 0.83 ± 0.03 for myocardium and 0.72 ± 0.08 for scars). A strong correlation for volumes of infarct zone was observed between manual and model-based approach (r = 0.96), with a significant underestimation of the volumes obtained from the neural network.
Conclusion
The self-configuring nnU-net achieves predictions with strong agreement compared to manual segmentation, proving the potential as a promising tool to provide fully automatic quantitative evaluation of LGE-CMR.
Objectives. This study is aimed at investigating the impact of frame numbers in preclinical electrocardiogram- (ECG-) gated \(^{18}\)F-fluorodeoxyglucose (\(^{18}\)F-FDG) positron emission tomography (PET) on systolic and diastolic left ventricular (LV) parameters in rats. Methods. \(^{18}\)F-FDG PET imaging using a dedicated small animal PET system with list mode data acquisition and continuous ECG recording was performed in diabetic and control rats. The list-mode data was sorted and reconstructed with different numbers of frames (4, 8, 12, and 16) per cardiac cycle into tomographic images. Using an automatic ventricular edge detection software, left ventricular (LV) functional parameters, including ejection fraction (EF), end-diastolic (EDV), and end-systolic volume (ESV), were calculated. Diastolic variables (time to peak filling (TPF), first third mean filling rate (1/3 FR), and peak filling rate (PFR)) were also assessed. Results. Significant differences in multiple parameters were observed among the reconstructions with different frames per cardiac cycle. EDV significantly increased by numbers of frames (353.8 & PLUSMN; 57.7 mu l*, 380.8 & PLUSMN; 57.2 mu l*, 398.0 & PLUSMN; 63.1 mu l*, and 444.8 & PLUSMN; 75.3 mu l at 4, 8, 12, and 16 frames, respectively; *P < 0.0001 vs. 16 frames), while systolic (EF) and diastolic (TPF, 1/3 FR and PFR) parameters were not significantly different between 12 and 16 frames. In addition, significant differences between diabetic and control animals in 1/3 FR and PFR in 16 frames per cardiac cycle were observed (P < 0.005), but not for 4, 8, and 12 frames. Conclusions. Using ECG-gated PET in rats, measurements of cardiac function are significantly affected by the frames per cardiac cycle. Therefore, if you are going to compare those functional parameters, a consistent number of frames should be used.
Heart failure with preserved ejection fraction (HFpEF) is highly prevalent in patients on maintenance haemodialysis (HD) and lacks effective treatment. We investigated the effect of spironolactone on cardiac structure and function with a specific focus on diastolic function parameters. The MiREnDa trial examined the effect of 50 mg spironolactone once daily versus placebo on left ventricular mass index (LVMi) among 97 HD patients during 40 weeks of treatment. In this echocardiographic substudy, diastolic function was assessed using predefined structural and functional parameters including E/e'. Changes in the frequency of HFpEF were analysed using the comprehensive 'HFA-PEFF score'. Complete echocardiographic assessment was available in 65 individuals (59.5 ± 13.0 years, 21.5% female) with preserved left ventricular ejection fraction (LVEF > 50%). At baseline, mean E/e' was 15.2 ± 7.8 and 37 (56.9%) patients fulfilled the criteria of HFpEF according to the HFA-PEFF score. There was no significant difference in mean change of E/e' between the spironolactone group and the placebo group (+ 0.93 ± 5.39 vs. + 1.52 ± 5.94, p = 0.68) or in mean change of left atrial volume index (LAVi) (1.9 ± 12.3 ml/m\(^{2}\) vs. 1.7 ± 14.1 ml/m\(^{2}\), p = 0.89). Furthermore, spironolactone had no significant effect on mean change in LVMi (+ 0.8 ± 14.2 g/m\(^{2}\) vs. + 2.7 ± 15.9 g/m\(^{2}\); p = 0.72) or NT-proBNP (p = 0.96). Treatment with spironolactone did not alter HFA-PEFF score class compared with placebo (p = 0.63). Treatment with 50 mg of spironolactone for 40 weeks had no significant effect on diastolic function parameters in HD patients.
Background
Right ventricular dysfunction after CABG is associated with poor peri- and postoperative outcomes. We aimed to identify clinical and experimental predictors for preoperative inapparent right ventricular dysfunction and therefore hypothesized that reduced myofilament force development as well as altered levels of biomarkers might predict inapparent right ventricular dysfunction.
Methods
From 08/2016 to 02/2018, 218 patients scheduled for CABG were divided into two groups (TAPSE ≥ 20 mm, n = 178; TAPSE < 20 mm, n = 40). Baseline serum samples for biomarkers (Galectin, TGFß1, N Acyl-SDMA, Arginine, ADMA and Pentraxin-3), clinical laboratory and transthoracic echocardiographic parameters were evaluated. To examine the myocardial apparatus of the right ventricle intraoperative right auricular tissue was harvested for stepwise skinned fiber force measurements.
Results
Patients with TAPSE < 20 mm had a higher incidence of DM (55 vs. 34%, p = 0.018), preoperative AFib (43 vs. 16%, p < 0.001), reduced GFR (67 ± 18 vs. 77 ± 24 ml/min/1.73 m\(^2\), p = 0.013), larger LA area (22 ± 6 vs. 20 ± 5 cm\(^2\), p = 0.005) and reduced LVEF (50 vs. 55%, p = 0.008). Furthermore, higher serum ADMA (0.70 ± 0.13 vs. 0.65 ± 0.15 µmol/l, p = 0.046) and higher serum Pentraxin-3 levels (3371 ± 1068 vs. 2681 ± 1353 pg/dl, p = 0.004) were observed in these patients. Skinned fiber force measurements showed significant lower values at almost every step of calcium concentration (pCa 4.52 to pCa 5.5, p < 0.01 and pCa 5.75–6.0, p < 0.05). Multivariable analysis revealed DM (OR 2.53, CI 1.12–5.73, Euro Score II (OR 1.34, CI 1.02–1.78), preoperative AF (OR 4.86, CI 2.06–11.47), GFR (OR 7.72, CI 1.87–31.96), albumin (OR 1.56, CI 0.52–2.60), Pentraxin-3 (OR 19.68, CI 14.13–25.24), depressed LVEF (OR 8.61, CI 6.37–10.86), lower force values: (pCa 5.4; OR 2.34, CI 0.40–4.29 and pCa 5.2; OR 2.00, CI 0.39–3.60) as predictors for clinical inapparent right heart dysfunction.
Conclusions
These preliminary data showed that inapparent right heart dysfunction in CAD is already associated with reduced force development of the contractile apparatus.
A deep integration of routine care and research remains challenging in many respects. We aimed to show the feasibility of an automated transformation and transfer process feeding deeply structured data with a high level of granularity collected for a clinical prospective cohort study from our hospital information system to the study's electronic data capture system, while accounting for study-specific data and visits. We developed a system integrating all necessary software and organizational processes then used in the study. The process and key system components are described together with descriptive statistics to show its feasibility in general and to identify individual challenges in particular. Data of 2051 patients enrolled between 2014 and 2020 was transferred. We were able to automate the transfer of approximately 11 million individual data values, representing 95% of all entered study data. These were recorded in n = 314 variables (28% of all variables), with some variables being used multiple times for follow-up visits. Our validation approach allowed for constant good data quality over the course of the study. In conclusion, the automated transfer of multi-dimensional routine medical data from HIS to study databases using specific study data and visit structures is complex, yet viable.
Genetic deficiency for acid sphingomyelinase or its pharmacological inhibition has been shown to increase Foxp3\(^+\) regulatory T-cell frequencies among CD4\(^+\) T cells in mice. We now investigated whether pharmacological targeting of the acid sphingomyelinase, which catalyzes the cleavage of sphingomyelin to ceramide and phosphorylcholine, also allows to manipulate relative CD4\(^+\) Foxp3\(^+\) regulatory T-cell frequencies in humans. Pharmacological acid sphingomyelinase inhibition with antidepressants like sertraline, but not those without an inhibitory effect on acid sphingomyelinase activity like citalopram, increased the frequency of Foxp3\(^+\) regulatory T cell among human CD4\(^+\) T cells in vitro. In an observational prospective clinical study with patients suffering from major depression, we observed that acid sphingomyelinase-inhibiting antidepressants induced a stronger relative increase in the frequency of CD4\(^+\) Foxp3\(^+\) regulatory T cells in peripheral blood than acid sphingomyelinase-non- or weakly inhibiting antidepressants. This was particularly true for CD45RA\(^-\) CD25\(^{high}\) effector CD4\(^+\) Foxp3\(^+\) regulatory T cells. Mechanistically, our data indicate that the positive effect of acid sphingomyelinase inhibition on CD4\(^+\) Foxp3\(^+\) regulatory T cells required CD28 co-stimulation, suggesting that enhanced CD28 co-stimulation was the driver of the observed increase in the frequency of Foxp3+ regulatory T cells among human CD4\(^+\) T cells. In summary, the widely induced pharmacological inhibition of acid sphingomyelinase activity in patients leads to an increase in Foxp3+ regulatory T-cell frequencies among CD4\(^+\) T cells in humans both in vivo and in vitro.
Purpose
Inhomogeneities of the static magnetic B\(_{0}\) field are a major limiting factor in cardiac MRI at ultrahigh field (≥ 7T), as they result in signal loss and image distortions. Different magnetic susceptibilities of the myocardium and surrounding tissue in combination with cardiac motion lead to strong spatio‐temporal B\(_{0}\)‐field inhomogeneities, and their homogenization (B0 shimming) is a prerequisite. Limitations of state‐of‐the‐art shimming are described, regional B\(_{0}\) variations are measured, and a methodology for spherical harmonics shimming of the B\(_{0}\) field within the human myocardium is proposed.
Methods
The spatial B\(_{0}\)‐field distribution in the heart was analyzed as well as temporal B\(_{0}\)‐field variations in the myocardium over the cardiac cycle. Different shim region‐of‐interest selections were compared, and hardware limitations of spherical harmonics B\(_{0}\) shimming were evaluated by calibration‐based B0‐field modeling. The role of third‐order spherical harmonics terms was analyzed as well as potential benefits from cardiac phase–specific shimming.
Results
The strongest B\(_{0}\)‐field inhomogeneities were observed in localized spots within the left‐ventricular and right‐ventricular myocardium and varied between systolic and diastolic cardiac phases. An anatomy‐driven shim region‐of‐interest selection allowed for improved B\(_{0}\)‐field homogeneity compared with a standard shim region‐of‐interest cuboid. Third‐order spherical harmonics terms were demonstrated to be beneficial for shimming of these myocardial B\(_{0}\)‐field inhomogeneities. Initial results from the in vivo implementation of a potential shim strategy were obtained. Simulated cardiac phase–specific shimming was performed, and a shim term‐by‐term analysis revealed periodic variations of required currents.
Conclusion
Challenges in state‐of‐the‐art B\(_{0}\) shimming of the human heart at 7 T were described. Cardiac phase–specific shimming strategies were found to be superior to vendor‐supplied shimming.