Personalized Brain-Computer Interface Models for Motor Rehabilitation

We propose to fuse two currently separate research lines on novel therapies for stroke rehabilitation: brain-computer interface (BCI) training and transcranial electrical stimulation (TES). Specifically, we show that BCI technology can be used to learn personalized decoding models that relate the global configuration of brain rhythms in individual subjects (as measured by EEG) to their motor performance during 3D reaching movements. We demonstrate that our models capture substantial across-subject heterogeneity, and argue that this heterogeneity is a likely cause of limited effect sizes observed in TES for enhancing motor performance. We conclude by discussing how our personalized models can be used to derive optimal TES parameters, e.g., stimulation site and frequency, for individual patients.Comment: 6 pages, 6 figures, conference submissio

How can Data Analytics Results be Exploited in the Early Phase of Product Development? 13 Design Principles for Data-Driven Product Planning

The megatrend digitalization turns mechatronic products into continuous collectors and generators of use phase data. By analyzing this data, manufacturers can uncover valuable insights about the products and the users. Especially in product planning, these insights could be used to plan promising future product generations. The systematic exploitation of data analytics results, however, represents a serious challenge, as research on the topic is still scarce. In this paper, we present 13 design principles for exploiting data analytics results in product planning. The results are based on a systematic literature review and a workshop with a research consortium. The evaluation of the design principles is demonstrated with a real case of a manufacturing company. The identified design principles represent a first contribution to a still scarcely explored research field

Towards neurofeedback training of associative brain areas for stroke rehabilitation

We propose to extend the current focus of BCI-based stroke rehabilitation beyond sensorimotor-rhythms to also include associative brain areas. In particular, we argue that neurofeedback training of brain rhythms that signal a state-of-mind beneficial for motorlearning is likely to enhance post-stroke motor rehabilitation. We propose an adaptive neurofeedback paradigm for this purpose and demonstrate its viability on EEG data recorded with five healthy subjects

Diagnostic Benefit of High b-Value Computed Diffusion-Weighted Imaging in Patients with Hepatic Metastasis

Diffusion-weighted imaging (DWI) has rapidly become an essential tool for the detection of malignant liver lesions. The aim of this study was to investigate the usefulness of high b-value computed DWI (c-DWI) in comparison to standard DWI in patients with hepatic metastases. In total, 92 patients with histopathologic confirmed primary tumors with hepatic metastasis were retrospectively analyzed by two readers. DWI was obtained with b-values of 50, 400 and 800 or 1000 s/mm2 on a 1.5 T magnetic resonance imaging (MRI) scanner. C-DWI was calculated with a monoexponential model with high b-values of 1000, 2000, 3000, 4000 and 5000 s/mm2. All c-DWI images with high b-values were compared to the acquired DWI sequence at a b-value of 800 or 1000 s/mm2 in terms of volume, lesion detectability and image quality. In the group of a b-value of 800 from a b-value of 2000 s/mm2, hepatic lesion sizes were significantly smaller than on acquired DWI (metastases lesion sizes b = 800 vs. b 2000 s/mm2: mean 25 cm3 (range 10–60 cm3) vs. mean 17.5 cm3 (range 5–35 cm3), p < 0.01). In the second group at a high b-value of 1500 s/mm2, liver metastases were larger than on c-DWI at higher b-values (b = 1500 vs. b 2000 s/mm2, mean 10 cm3 (range 4–24 cm3) vs. mean 9 cm3 (range 5–19 cm3), p < 0.01). In both groups, there was a clear reduction in lesion detectability at b = 2000 s/mm2, with hepatic metastases being less visible compared to c-DWI images at b = 1500 s/mm2 in at least 80% of all patients. Image quality dropped significantly starting from c-DWI at b = 3000 s/mm2. In both groups, almost all high b-values images at b = 4000 s/mm2 and 5000 s/mm2 were not diagnostic due to poor image quality. High c-DWI b-values up to b = 1500 s/mm2 offer comparable detectability for hepatic metastases compared to standard DWI. Higher b-value images over 2000 s/mm2 lead to a noticeable reduction in imaging quality, which could hamper diagnosis

Neural Signatures of Motor Skill in the Resting Brain

Stroke-induced disturbances of large-scale cortical networks are known to be associated with the extent of motor deficits. We argue that identifying brain networks representative of motor behavior in the resting brain would provide significant insights for current neurorehabilitation approaches. Particularly, we aim to investigate the global configuration of brain rhythms and their relation to motor skill, instead of learning performance as broadly studied. We empirically approach this problem by conducting a three-dimensional physical space visuomotor learning experiment during electroencephalographic (EEG) data recordings with thirty-seven healthy participants. We demonstrate that across-subjects variations in average movement smoothness as the quantified measure of subjects' motor skills can be predicted from the global configuration of resting-state EEG alpha-rhythms (8-14 Hz) recorded prior to the experiment. Importantly, this neural signature of motor skill was found to be orthogonal to (independent of) task -- as well as to learning-related changes in alpha-rhythms, which we interpret as an organizing principle of the brain. We argue that disturbances of such configurations in the brain may contribute to motor deficits in stroke, and that reconfiguring stroke patients' brain rhythms by neurofeedback may enhance post-stroke neurorehabilitation.Comment: 2019 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2019

CT Texture Analysis of Pulmonary Neuroendocrine Tumors—Associations with Tumor Grading and Proliferation

Texture analysis derived from computed tomography (CT) might be able to provide clinically relevant imaging biomarkers and might be associated with histopathological features in tumors. The present study sought to elucidate the possible associations between texture features derived from CT images with proliferation index Ki-67 and grading in pulmonary neuroendocrine tumors. Overall, 38 patients (n = 22 females, 58%) with a mean age of 60.8 ± 15.2 years were included into this retrospective study. The texture analysis was performed using the free available Mazda software. All tumors were histopathologically confirmed. In discrimination analysis, “S(1,1)SumEntrp” was significantly different between typical and atypical carcinoids (mean 1.74 ± 0.11 versus 1.79 ± 0.14, p = 0.007). The correlation analysis revealed a moderate positive association between Ki-67 index with the first order parameter kurtosis (r = 0.66, p = 0.001). Several other texture features were associated with the Ki-67 index, the highest correlation coefficient showed “S(4,4)InvDfMom” (r = 0.59, p = 0.004). Several texture features derived from CT were associated with the proliferation index Ki-67 and might therefore be a valuable novel biomarker in pulmonary neuroendocrine tumors. “Sumentrp” might be a promising parameter to aid in the discrimination between typical and atypical carcinoids

Magnetic Resonance Imaging of Peritoneal Carcinomatosis: Evaluation of High b-Value Computed Diffusion-Weighted Imaging

Over the last few years, diffusion-weighted imaging (DWI) has become increasingly relevant in the diagnostic assessment of peritoneal carcinomatosis. The aim of this study was to investigate the benefits of high-b DWI (c-DWI) compared to standard DWI in patients with peritoneal carcinomatosis. A cohort of 40 patients with peritoneal carcinomatosis were included in this retrospective study. DWI was performed with b-values of 50, 400, and 800 or 1000 s/mm2 on a 1.5-T magnetic resonance imaging (MRI) scanner. C-DWI was calculated using a mono-exponential model with high b-values of 1000, 2000, 3000, 4000, and 5000 s/mm2. All c-DWI images with high b-values were compared in terms of volume, detectability of peritoneal lesions, and image quality with the DWI sequence acquired with a b-value of 800 or 1000 s/mm2 by two readers. In the group with a b-value of 800 s/mm2, there was no statistically significant difference in terms of lesion volume. In the second group with a b-value of 1000 s/mm2, peritoneal carcinomatosis lesions were statistically significantly larger than in the c-DWI with a- high b-value of 2000 s/mm2 (median 7 cm3, range 1–26 cm3vs. median 6 cm3, range 1–83 cm3, p < 0.05). In both groups, there was a marked decrease in the detectability of peritoneal lesions starting at b = 2000 s/mm2. In addition, image quality decreased noticeably from c-DWI at b = 3000 s/mm2. In both groups, all images with high b-values at b = 4000 s/mm2 and 5000 s/mm2 were not diagnostically valuable due to poor image quality. The c-DWI technique offers good diagnostic performance without additional scanning time. High c-DWI b-values up to b = 1000 s/mm2 provide comparable detectability of peritoneal carcinomatosis compared to standard DWI. Higher b-values over 1500 s/mm2 result in lower image quality, which might lead to misdiagnosis

Adaptive neurofeedback on parieto-occipital cortex for motor learning performance (Motor öğrenme performansı için parieto-oksipital korteks üzerinde uyarlamalı nörogeribesleme)

Numerous electroencephalogram (EEG) based Brain-Computer Interface (BCI) systems are being used as alternative means of communication for locked-in patients. Beyond these, BCIs are also considered in the context of post-stroke motor rehabilitation. Such research usually focuses on exploiting information decoded from sensorimotor activity of the brain. Here, we propose to extend this current focus beyond sensorimotor to also include associative brain areas. In this pilot study, we present an adaptive neurofeedback training paradigm to up-regulate particular EEG activity that is likely to enhance post-stroke motor rehabilitation. Our experimental results support the interpretation that the neurofeedback paradigm enables subjects to up-regulate intended activity and sustain that modulation in inter-trial resting periods in a state that we believe can support motor learning performance. These results serve as a beginning on viability of our claim on integrating a neurofeedback approach to BCI-based motor rehabilitation protocols

Prevention of DNA Replication Stress by CHK1 Leads to Chemoresistance Despite a DNA Repair Defect in Homologous Recombination in Breast Cancer

Chromosomal instability not only has a negative effect on survival in triple-negative breast cancer, but also on the well treatable subgroup of luminal A tumors. This suggests a general mechanism independent of subtypes. Increased chromosomal instability (CIN) in triple-negative breast cancer (TNBC) is attributed to a defect in the DNA repair pathway homologous recombination. Homologous recombination (HR) prevents genomic instability by repair and protection of replication. It is unclear whether genetic alterations actually lead to a repair defect or whether superior signaling pathways are of greater importance. Previous studies focused exclusively on the repair function of HR. Here, we show that the regulation of HR by the intra-S-phase damage response at the replication is of overriding importance. A damage response activated by Ataxia telangiectasia and Rad3 related-checkpoint kinase 1 (ATR-CHK1) can prevent replication stress and leads to resistance formation. CHK1 thus has a preferred role over HR in preventing replication stress in TNBC. The signaling cascade ATR-CHK1 can compensate for a double-strand break repair error and lead to resistance of HR-deficient tumors. Established methods for the identification of HR-deficient tumors for Poly(ADP-Ribose)-Polymerase 1 (PARP1) inhibitor therapies should be extended to include analysis of candidates for intra-S phase damage response

Hyperspectral Imaging (HSI)—A New Tool to Estimate the Perfusion of Upper Abdominal Organs during Pancreatoduodenectomy

Hyperspectral imaging (HSI) in abdominal surgery is a new non-invasive tool for the assessment of the perfusion and oxygenation of various tissues and organs. Its benefit in pancreatic surgery is still unknown. The aim of this study was to evaluate the key impact of using HSI during pancreatoduodenectomy (PD). In total, 20 consecutive patients were included. HSI was recorded during surgery as part of a pilot study approved by the local Ethics Committee. Data were collected prospectively with the TIVITA® Tissue System. Intraoperative HS images were recorded before and after gastroduodenal artery (GDA) clamping. We detected four patients with celiac artery stenosis (CAS) caused by a median arcuate ligament (MAL). In two of these patients, a reduction in liver oxygenation (StO2) was discovered 15 and 30 min after GDA clamping. The MAL was divided in these patients. HSI showed an improvement of liver StO2 after MAL division (from 61% to 73%) in one of these two patients. There was no obvious decrease in liver StO2 in the other two patients with CAS. HSI, as a non-invasive procedure, could be helpful in evaluating liver and gastric perfusion during PD, which might assist surgeons in choosing the best surgical approach and in improving patients’ outcomes