Mean Vector Length Research Articles

High accuracy of positioning custom triflange acetabular components in tumour and total hip arthroplasty revision surgery.

Custom triflange acetabular components (CTACs) play an important role in reconstructive orthopaedic surgery, particularly in revision total hip arthroplasty (rTHA) and pelvic tumour resection procedures. Accurate CTAC positioning is essential to successful surgical outcomes. While prior studies have explored CTAC positioning in rTHA, research focusing on tumour cases and implant flange positioning precision remains limited. Additionally, the impact of intraoperative navigation on positioning accuracy warrants further investigation. This study assesses CTAC positioning accuracy in tumour resection and rTHA cases, focusing on the differences between preoperative planning and postoperative implant positions. A multicentre observational cohort study in Australia between February 2017 and March 2021 included consecutive patients undergoing acetabular reconstruction with CTACs in rTHA (Paprosky 3A/3B defects) or tumour resection (including Enneking P2 peri-acetabular area). Of 103 eligible patients (104 hips), 34 patients (35 hips) were analyzed. CTAC positioning was generally accurate, with minor deviations in cup inclination (mean 2.7°; SD 2.84°), anteversion (mean 3.6°; SD 5.04°), and rotation (mean 2.1°; SD 2.47°). Deviation of the hip centre of rotation (COR) showed a mean vector length of 5.9 mm (SD 7.24). Flange positions showed small deviations, with the ischial flange exhibiting the largest deviation (mean vector length of 7.0 mm; SD 8.65). Overall, 83% of the implants were accurately positioned, with 17% exceeding malpositioning thresholds. CTACs used in tumour resections exhibited higher positioning accuracy than rTHA cases, with significant differences in inclination (1.5° for tumour vs 3.4° for rTHA) and rotation (1.3° for tumour vs 2.4° for rTHA). The use of intraoperative navigation appeared to enhance positioning accuracy, but this did not reach statistical significance. This study demonstrates favourable CTAC positioning accuracy, with potential for improved accuracy through intraoperative navigation. Further research is needed to understand the implications of positioning accuracy on implant performance and long-term survival.

Theta‐Gamma Phase‐Amplitude Coupling Deficit in Streptozotocin AD Rat Model

AbstractBackgroundTheta rhythms are known to encode sensory information and reflect their effect into gamma oscillations through a modulation process known as theta‐gamma phase‐amplitude coupling (PAC) (Amemiya et al., Cell Reports 2018). The role of the PAC as a network‐level indicator of cognitive impairment in disorders such as dementia and Alzheimer’s disease has received much attention recently (Zheng et al. Nature communication 2020).Injection of Streptozotocin (STZ) in animals is reported to cause resistance to insulin uptake in the brain, leading to memory and cognitive impairment (Kamat, Neural Regeneration Research 2015). The current study examines the induced deficit in the PAC as an early indicator of neurodegenerative effects of STZ.Method3 adult male Wistar rats were included in this study (270 – 300 g). Intraventricular injection of STZ was performed at a dose of 3 mg / Kg with a volume of 10 μl. Two stainless steel electrodes were implanted in the hippocampus (CA1) and medial prefrontal cortex (mPFC). The rats were free to move during recording. LFP data were recorded and segmented into windows of 20 s. Preprocessing and noisy trial rejection were employed for artifact removal, and the theta‐gamma PAC was measured using the mean vector length (tf‐MVL) method (Munia et al., Scientific Reports 2019).ResultOne week after STZ injection, the theta‐gamma PAC values did not show a significant change but after two weeks variation was observed. During this period, the power of different frequency bands was also measured and no significant change was observed even after two weeks. Theta‐gamma PAC deficiency was observed in both regions (CA1 and mPFC).ConclusionSTZ’s intracerebro‐ventricular injection is known to produce cognitive deficits along with an increase in Aβ deposition. This study reports that cross‐frequency coupling deficiency is also observed in this AD mouse model. Moreover, the PAC deficit was detected earlier than any change was observed in the spectral analysis of the data, suggesting that it can serve as a diagnosis tool for memory impairment due to neurodegeneration in the STZ mouse model of AD.

Abnormal gamma frequency phase‐amplitude coupling associated with network hyperexcitability in Alzheimer’s Disease

AbstractBackgroundAlzheimer’s disease (AD) carries an increased risk of seizures and subclinical epileptiform activity (Vossel et al. 2016). Network hyperexcitability which is the underlying phenomenon of epileptic manifestations is thought to contribute to AD pathophysiological processes. Recently we demonstrated that greater degree of neural synchronization deficits within 2‐8Hz range of frequency oscillations are sensitive indicators of network hyperexcitability (Ranasinghe et al. 2021). Here, we sought to examine the high frequency gamma band deficits associated with network hyperexcitability in AD patients.MethodsSpecifically, we quantified Phase Amplitude Coupling (PAC) between the amplitude of gamma oscillations (30‐40Hz); with the phase of 2‐8Hz oscillations) (Figure 1). We used 60s resting‐state magnetoencephalography (MEG) recordings from 48 AD patients (n = 22, with subclinical epileptiform activity, AD‐EPI+; n = 28 without subclinical epileptiform activity, AD‐EPI‐), and 35 age‐matched controls. We computed PAC for each of 68 cortical regions (Desikan et al. 2006) on source‐space reconstructed MEG signal using the mean vector length (Canolty et al. 2006).ResultsPermutation cluster test was performed for statistical comparisons between AD patients vs. age matched controls, and AD‐EPI+ vs. AD‐EPI‐. Patients with AD showed significantly higher theta (4‐8 Hz)‐gamma coupling in the left parahippocampal and right caudal‐middle frontal regions. Importantly, this increased left parahippocampal theta‐gamma coupling was significantly higher in AD‐EPI+ patients than in AD‐EPI‐. AD‐EPI+ also showed higher alpha (8‐12Hz)‐gamma coupling in the right parahippocampal region compared to AD‐EPI‐ (Figure 2).ConclusionThese results not only identify gamma band coupling deficits specifically localized to medial temporal regions which are the earliest affected regions in AD pathophysiology but also delineate the associated vulnerabilities of network hyperexcitability in AD.

Direct modulation index: A measure of phase amplitude coupling for neurophysiology data.

Neural communication across different spatial and temporal scales is a topic of great interest in clinical and basic science. Phase-amplitude coupling (PAC) has attracted particular interest due to its functional role in a wide range of cognitive and motor functions. Here, we introduce a novel measure termed the direct modulation index (dMI). Based on the classical modulation index, dMI provides an estimate of PAC that is (1) bound to an absolute interval between 0 and +1, (2) resistant against noise, and (3) reliable even for small amounts of data. To highlight the properties of this newly-proposed measure, we evaluated dMI by comparing it to the classical modulation index, mean vector length, and phase-locking value using simulated data. We ascertained that dMI provides a more accurate estimate of PAC than the existing methods and that is resilient to varying noise levels and signal lengths. As such, dMI permits a reliable investigation of PAC, which may reveal insights crucial to our understanding of functional brain architecture in key contexts such as behaviour and cognition. A Python toolbox that implements dMI and other measures of PAC is freely available at https://github.com/neurophysiological-analysis/FiNN.

Seizure onset zone identification using phase-amplitude coupling and multiple machine learning approaches for interictal electrocorticogram

Automatic seizure onset zone (SOZ) localization using interictal electrocorticogram (ECoG) improves the diagnosis and treatment of patients with medically refractory epilepsy. This study aimed to investigate the characteristics of phase-amplitude coupling (PAC) extracted from interictal ECoG and the feasibility of PAC serving as a promising biomarker for SOZ identification. We employed the mean vector length modulation index approach on the 20-s ECoG window to calculate PAC features between low-frequency rhythms (0.5–24 Hz) and high frequency oscillations (HFOs) (80–560 Hz). We used statistical measures to test the significant difference in PAC between the SOZ and non-seizure onset zone (NSOZ). To overcome the drawback of handcraft feature engineering, we established novel machine learning models to learn automatically the characteristics of the obtained PAC features and classify them to identify the SOZ. Besides, to handle imbalanced dataset classification, we introduced novel feature-wise/class-wise re-weighting strategies in conjunction with classifiers. In addition, we proposed a time-series nest cross-validation to provide more accurate and unbiased evaluations for this model. Seven patients with focal cortical dysplasia were included in this study. The experiment results not only showed that a significant coupling at band pairs of slow waves and HFOs exists in the SOZ when compared with the NSOZ, but also indicated the effectiveness of the PAC features and the proposed models in achieving better classification performance .

How to describe and measure phenology? An investigation on the diversity of metrics using phenology of births in large herbivores

Proposed in 1849 by Charles Morren to depict periodical phenomena governed by seasons, the term ‘phenology' has spread in many fields of biology. With the wide adoption of the concept of phenology flourished a large number of metrics with different meaning and interpretation. Here, we first a priori classified 52 previously published metrics used to characterise the phenology of births in large herbivores according to four biological characteristics of interest: timing, synchrony, rhythmicity and regularity of births. We then applied each metric retrieved on simulation data, considering normal and non‐normal distributions of births, and varying distributions of births in time. We then evaluated the ability of each metric to capture the variation of the four phenology characteristics via a sensitivity analysis. Finally, we scored each metric according to eight criteria we considered important to describe phenology correctly. The high correlation we found among the many metrics we retrieved suggests that such diversity of metrics is unnecessary. We further show that the best metrics are not the most commonly used, and that simpler is often better. Circular statistics with the mean vector orientation and mean vector length seems, respectively, particularly suitable to describe the timing and synchrony of births in a wide range of phenology patterns. Tests designed to compare statistical distributions, like Mood and Kolmogorov–Smirnov tests, allow a first and easy quantification of rhythmicity and regularity of birth phenology respectively. By identifying the most relevant metrics our study should facilitate comparative studies of phenology of births or of any other life‐history event. For instance, comparative studies of the phenology of mating or migration dates are particularly important in the context of climate change.

New Methodology of Designation the Precise Aircraft Position Based on the RTK GPS Solution.

The paper presents the results of research on improving the accuracy of aircraft positioning using RTK-OTF (Real Time Kinematic–On The Fly) technique in air navigation. The paper shows a new solution of aircraft positioning for the application of the differential RTK-OTF technique in air navigation. In particular, a new mathematical model is presented which makes it possible to determine the resultant position of an aircraft based on the solution for the method of least squares in a stochastic process. The developed method combines in the process of alignment of GPS (Global Positioning System) observations, three independent solutions of the aircraft position in OTF mode for geocentric coordinates XYZ of the aircraft. Measurement weights as a function of the vector length and the mean vector length error, respectively, were used in the calculations. The applied calculation method makes it possible to determine the resultant position of the aircraft with high accuracy: better than 0.039 m with using the measurement weight as a function of the vector length and better than 0.009 m with the measurement weight as a function of the mean error of the vector length, respectively. In relation to the classical RTK-OTF solution as a model of the arithmetic mean, the proposed method makes it possible to increase the accuracy of determination of the aircraft position by 45–46% using the measurement weight as a function of the vector length, and 86–88% using the measurement weight as a function of the mean error of the vector length, respectively. The obtained test results show that the developed method improves to significantly improve the accuracy of the RTK-OTF solution as a method for determining the reference position in air navigation.

Theta‐gamma phase‐amplitude coupling explains the advantage of auditory plus visual gamma entrainment in Alzheimer’s therapy

AbstractBackgroundImpairment of gamma oscillations has been observed in cognitive disorders like Alzheimer’s disease (AD). Gamma entrainment using 40Hz auditory or visual stimulation has been proposed as a potential treatment for AD (Adaikkan et al., Trends in Neuroscience 2020; Sedghizadeh et al. Alzheimer’s and Dementia 2020), while simultaneous use of both modalities has been reported to show superior therapeutic results (Martorell et al., Cell 2019; Suk et al. Alzheimer’s and Dementia 2020). Gamma and theta oscillations are both produced in the hippocampal area and interact with each other. Evidence shows that the interaction between these bands leads to their phase‐amplitude coupling (PAC) in the frontal cortex (Amemiya et al., Cell Reports 2018). The current study assesses the effects of 40Hz auditory and visual stimulation on the theta‐gamma PAC, and suggests that the superior performance of multimodal entrainment can be explained by this marker.Method10 cognitively healthy participants were included in this study. Each participant was seated in a dark and quiet room and underwent three sessions of sensory stimulation (visual, auditory, and simultaneous (multimodal) visual and auditory) in a randomized order. Each session consisted of 60 trials of 5s stimulation and 5s rest. The auditory stimulation consisted of a 40Hz clicking sound modulated with a career frequency of 5kHz. The visual stimulation was generated using white LEDs flickering at 40Hz. EEG data were acquired and the theta‐gamma PAC was calculated using the time‐frequency mean vector length (tf‐MVL) method (Munia et al., Scientific Reports 2019).ResultThe PAC value for theta (4‐8Hz) and gamma oscillations near the stimulation frequency (39‐41Hz) on the Fz channel showed a significant increase during the multimodal stimulation intervals compared to the resting state, whereas the increase was not significant during the single‐modal stimulations compared to rest. The multimodal stimulation also involved more brain areas and resulted in a higher PAC compared to single‐modal stimulation.ConclusionEntraining gamma oscillations using simultaneous auditory and visual stimulation results in markedly superior theta‐gamma PAC compared to entrainment with single modalities. This superiority can explain the advantages reported for multimodal entrainment in AD therapy experiments.

Maximizing detection and optimal characterization of local abnormal ventricular activity in nonischemic cardiomyopathy: LAVAMAX & LAVAFLOW.

BackgroundSites of local abnormal ventricular activation (LAVA) are ventricular tachycardia (VT) ablation targets. In nonischemic cardiomyopathy (NICM), minute and sparse LAVA potentials are mapped with difficulty with direction-sensitive bipolar electrograms (EGM). A method for its optimal characterization independent of electrode orientation has not been explored.ObjectiveMaximize voltages and calculate overall activation direction at LAVA sites, independent of catheter and wave direction, using omnipolar technology (OT) in NICM.MethodsFour diseased isolated human hearts from NICM patients were mapped epicardially using a high-density grid. Bipolar EGMs with at least 2 activation segments separated by at least 25 ms were identified. We used OT to maximize voltages (LAVAMAX) and measured overall wave direction (LAVAFLOW) for both segments. Clinically relevant voltage proportion (CRVP) was used to estimate the proportion of directionally corrected bipoles. Concordance and changes in direction vectors were measured via mean vector length and angular change.ResultsOT provides maximal LAVA voltages (OT: 0.83 ± 0.09 mV vs Bi: 0.61 ± 0.06 mV, P < .05) compared to bipolar EGMs. OT optimizes LAVA voltages, with 32% (CRVP) of LAVA bipoles directionally corrected by OT. OT direction vectors at LAVA sites demonstrate general concordance, with an average of 62% ± 5%. A total of 72% of direction vectors change by more than 35° at LAVA sites.ConclusionThe omnipolar mapping approach allows maximizing voltage and determining the overall direction of wavefront activity at LAVA sites in NICM.

Soybean Productivity and Agrometeorological Variables Assessed from the perspective of Spatial and Circular Statistics

Climate change can affect the development of soybean cultivation, impacting your productivity. Thus, agrometeorological information is essential in order to improve productivity strategies. The objective of the paper was to analyze the influence and occurrence of seasonality of the following agrometeorological variables on soybean productivity: mean air temperature [TMean] (ºC), accumulated rainfall value [Rain] (mm), global solar radiation [Sr] (MJ m-2 day-1), and potential evapotranspiration [ETp] (mm), in ten-day variations of the the maximum vegetative development date (MVDD), in the 2011/2012 and 2013/2014 harvest years in the state of Paraná. The study was based on spatial distribution of variables, using univariate and bivariate Global Moran’s Indexes, and multivariate clustering analysis. To verify seasonality in the time distribution of the agrometeorological variables in the ten-day variations close to soybean MVDD, we used the circular statistics, through the mean vector length (R). Result it was identified regions of the state that have higher and lower rainfall and seasonality, also have higher and lowest productivity, respectively. That the variation in soybean productivity between harvest years was correlated with the agrometeorological variables, and rainfall volume is an important factor in productivity. The other agrometeorological variables occurred uniformly, especially in 2011/2012 harvest year, in the Northwest, Central-northern and West mesoregions. Furthermore, there was clustering of regions with similar spatial distribution of the evapotranspiration and rainfall variables in 2aDMDV2d in the 2011/2012 and 2013/2014 harvest year, showed the same spatial distribution of the agrometeorological variables and the productivity variable.

P 40. β-γ phase-amplitude coupling during movements in Parkinson's disease

Question. Enhanced phase amplitude coupling (PAC) between β (13–30 Hz) and broadband γ (50–150 Hz) activities has been found in surface EEG recordings from Parkinson patients at rest [1]. However, the dynamics of PAC during voluntary movement and its relationship with motor impairment of Parkinson“s disease (PD) remain unclear. Methods. Experimental design : We recorded 64-channel EEG signals from 19 PD patients and 20 sex- and age-matched healthy controls at rest, during a repetitive pressing task and during repetitive index finger tapping performed at the patients“ own pace and at their fastest pace. Source analysis : We obtained source signals by projecting EEG sensor signals to the individual cortical surfaces. Independent component analysis (ICA) was applied for separating temporally independent subnetworks of each task in each of the 4 brain regions: premotor cortex, primary motor cortex, primary somatosensory cortex and primary somatosensory complex. PAC analysis: Pairwise transient PAC values were calculated among ICA components of each region by zscore-normalized mean vector length [2] in 300ms windows shifted with 50ms time steps in 3s epochs which included an interval of 1s before, and 2s after the onset of the movement. Statistics : We applied a non-parametric three-way ANOVA [3] to test the effects of the disease state, tasks and different brain regions on PAC. For post-hoc testing, a two tailed Wilcoxon ranksum test was used between groups and Wilcoxon signrank test within groups. Results. As expected, maximum tapping rate was lower, and fastest movements were executed more irregularly in patients compared to controls. ANOVA performed on the β-γ PAC values averaged over the entire 3s-epoch revealed an interaction of disease state and tasks ( p < 0.001). Post-hoc testing showed enhanced PAC in patients compared with controls in the resting state ( p = 0.018), in agreement with previous findings, but not in any of the tapping tasks. However, PAC during the pressing task remained elevated in the patients compared to controls ( p = 0.020). Analysis of the temporal dynamics revealed reduction of PAC after the onset of the movement (0–0.25 s) compared with that of the pre-onset period (−0.5 to −0.25 s). The reduction of PAC relative to pre-onset period correlated with the desynchronization in the β power. However, the PAC reduction relative to the resting state was not correlated with the β power reduction. Discussion. Persistence of PAC differences during the pressing task on one hand, and disappearance of PAC differences during the tapping tasks on the other hand, suggest that exaggerated β-broadband γ PAC, as detected in the resting EEG, is not necessarily directly related to impaired motor behavior in PD patients. As our previous findings [1] have shown that abnormal PAC at rest is unrelated to the β band power, partial renormalization of PAC by movement-related β band desynchronization may suggest that mechanisms modulating β activity during movement may selectively affect β activity involved in abnormal coupling.

Addressing Pitfalls in Phase-Amplitude Coupling Analysis with an Extended Modulation Index Toolbox

Phase-amplitude coupling (PAC) is proposed to play an essential role in coordinating the processing of information on local and global scales. In recent years, the methods able to reveal trustworthy PAC has gained considerable interest. However, the intrinsic features of some signals can lead to the identification of spurious or waveform-dependent coupling. This prompted us to develop an easily accessible tool that could be used to differentiate spurious from authentic PAC. Here, we propose a new tool for more reliable detection of PAC named the Extended Modulation Index (eMI) based on the classical Modulation Index measure of coupling. eMI is suitable both for continuous and epoched data and allows estimation of the statistical significance of each pair of frequencies for phase and for amplitude in the whole comodulogram in the framework of extreme value statistics. We compared eMI with the reference PAC measures—direct PAC estimator (a modification of Mean Vector Length) and standard Modulation Index. All three methods were tested using computer-simulated data and actual local field potential recordings from freely moving rats. All methods exhibited similar properties in terms of sensitivity and specificity of PAC detection. eMI proved to be more selective in the dimension of frequency for phase. One of the novelty’s offered by eMI is a heuristic algorithm for classification of PAC as Reliable or Ambiguous. It relies on analysis of the relation between the spectral properties of the signal and the detected coupling. Moreover, eMI generates visualizations that support further evaluation of the coupling properties. It also introduces the concept of the polar phase-histogram to study phase relations of coupled slow and fast oscillations. We discuss the extent to which eMI addresses the known problems of interpreting PAC. The Matlab® toolbox implementing eMI framework, and the two reference PAC estimators is freely available as EEGLAB plugin at https://github.com/GabrielaJurkiewicz/ePAC.

Phase-amplitude coupling of delta brush unveiling neuronal modulation development in the neonatal brain

IntroductionDelta brushes are an indicator of brain maturity on a neonatal EEG. We investigated phase-amplitude coupling (PAC) between slow delta waves and superimposed alpha–beta activity in delta brushes to elucidate the spatiotemporal developments of the delta brush with post-menstrual weeks (PMW). MethodsThe subjects were 18 neurologically intact patients (seven girls). We analyzed EEG within 42 PMW. Patients were divided into four age groups as follows: PMW ≤30w; 31–34 w; 35–38 w; and 39–42 w. We selected up to three epochs of 2-minute EEG segments including delta brushes. We calculated the modulation index (MI), direct mean vector length (dMVL), and mean of phase angle of coupling by PAC between slow waves (0.5–1.5 Hz) and fast activities (8–25 Hz) in four regions (F: Fp1 and Fp2, C: C3 and C4, T: T3 and T4, O: O1 and O2). ResultsWe collected data from 18 patients and 31 epochs between 29 and 42 PMW, which comprised one, four, five, and eight patients, and two, seven, eight, and 14 epochs in the ≤30w, 31–34 w, 35–38 w, and 39–42 w groups, respectively. There were significant differences in the dMVL between the four regions in age groups ≤30w (P = 0.033) and 31–34w (0.017). Both MI and dMVL showed that delta brushes became higher in the occipital region from 32 to 36 PMW. The mean phase angle of coupling concentrated around either 0° or 180° for all age groups. ConclusionsPAC analysis revealed the spatiotemporal relations of alpha–beta activities that are modulated by slow delta waves in neonatal delta brushes. The delta brushes appeared to be at a maximum around 32–36 PMW with the predominant occipital distribution. The PAC of the delta brush might represent the cortical neuronal fast activity that is modulated by slow delta waves of subcortical regions during a particular neonatal period.

Assessing Epileptogenicity Using Phase-Locked High Frequency Oscillations: A Systematic Comparison of Methods.

High frequency oscillations (HFOs) are traditional biomarkers to identify the epileptogenic tissue during presurgical evaluation in pharmacoresistant epileptic patients. Recently, the resection of brain tissue exhibiting coupling between the amplitude of HFOs and the phase of low frequencies demonstrated a more favorable surgical outcome. Here we compare the predictive value of ictal HFOs and four methods for quantifying the ictal phase-amplitude coupling, namely mean vector length, phase-locked high gamma, phase locking value, and modulation index (MI). We analyzed 32 seizures from 16 patients to identify the channels that exhibit HFOs and phase-locked HFOs during seizures. We compared the resection ratio, defined as the percentage of channels exhibiting coupling located in the resected tissue, with the postsurgical outcome. We found that the MI is the only method to show a significant difference between the resection ratios of patients with good and poor outcomes. We further show that the whole seizure, not only the onset, is critical to assess epileptogenicity using the phase-locked HFOs. We postulate that the superiority of MI stems from its capacity to assess coupling of discrete HFO events and its independence from the HFO power. These results confirm that quantitative analysis of HFOs can boost presurgical evaluation and indicate the paramount importance of algorithm selection for clinical applications.

Quantification of Phase-Amplitude Coupling in Neuronal Oscillations: Comparison of Phase-Locking Value, Mean Vector Length, Modulation Index, and Generalized-Linear-Modeling-Cross-Frequency-Coupling

Phase-amplitude coupling is a promising construct to study cognitive processes in electroencephalography (EEG) and magnetencephalography (MEG). Due to the novelty of the concept, various measures are used in the literature to calculate phase-amplitude coupling. Here, performance of the three most widely used phase-amplitude coupling measures – phase-locking value (PLV), mean vector length (MVL), and modulation index (MI) – and of the generalized linear modeling cross-frequency coupling (GLM-CFC) method is thoroughly compared with the help of simulated data. We combine advantages of previous reviews and use a realistic data simulation, examine moderators and provide inferential statistics for the comparison of all four indices of phase-amplitude coupling. Our analyses show that all four indices successfully differentiate coupling strength and coupling width when monophasic coupling is present. While the MVL was most sensitive to modulations in coupling strengths and width, only the MI and GLM-CFC can detect biphasic coupling. Coupling values of all four indices were influenced by moderators including data length, signal-to-noise-ratio, and sampling rate when approaching Nyquist frequencies. The MI was most robust against confounding influences of these moderators. Based on our analyses, we recommend the MI for noisy and short data epochs with unknown forms of coupling. For high quality and long data epochs with monophasic coupling and a high signal-to-noise ratio, the use of the MVL is recommended. Ideally, both indices are reported simultaneously for one data set.

First clinical retrospective investigation of limited projection CBCT for lung tumor localization in patients receiving SBRT treatment

To clinically investigate the limited-projection CBCT (LP-CBCT) technology for daily positioning of patients receiving breath-hold lung SBRT radiation treatment and to investigate the feasibility of reconstructing fast 4D-CBCT from 1 min 3D-CBCT scan.Eleven patients who underwent breath-hold lung SBRT radiation treatment were scanned daily with on-board full-projection CBCT (CBCT) using half-fan scan. A subset of the CBCT projections and the prior planning CT were used to estimate the LP-CBCT images using the weighted free-form deformation method. The limited projections are clusteringly sampled within fifteen sub-angles in 360° in order to simulate the fast 1 min scan for 4D-CBCT. The estimated LP-CBCTs were rigidly registered to the planning CT to determine the clinical shifts needed for patient setup corrections, which were compared with shifts determined by the CBCT for evaluation. Both manual and automatic registrations were performed in order to compare the systematic registration errors. Fifty CBCT volumes were obtained from the eleven patients in fifty fractions for this pilot clinical study.For the CBCT images, the mean (±standard deviation) shifts between CBCT and planning CT from manual registration in left–right (LR), anterior–posterior (AP), and superior–inferior (SI) directions are 1.1 ± 1.2 mm, 2.1 ± 1.9 mm, 5.2 ± 3.6 mm, respectively. The mean deviation difference between shifts determined by CBCT and LP-CBCT images are 0.3 ± 0.5 mm, 0.5 ± 0.8 mm, 0.4 ± 0.3 mm, in LR, AP, and SI directions, respectively. The mean vector length of CBCT shift for all fractions is 6.1 ± 3.6 mm, and the mean vector length difference between CBCT and LP-CBCT for all fractions studied is 1.0 ± 0.9 mm. The automatic registrations yield similar results as manual registrations.The pilot clinical study shows that LP-CBCT localization offers comparable accuracy to CBCT localization for daily tumor positioning while reducing the projection number to 1/10 for patients receiving breath hold lung radiation treatment. The cluster projection sampling in this study also shows the feasibility of reconstructing fast 4D-CBCT from 1 min 3D-CBCT scan.

Bioelectrical Impedance Analysis Measures and Clinical Outcomes in CKD

Bioelectrical impedance analysis (BIA) provides a noninvasive assessment of body composition. BIA measures of cell integrity (phase angle) and hydration (vector length) have been associated with mortality among patients receiving dialysis. Whether these measures are associated with clinical outcomes in patients with chronic kidney disease (CKD) is unknown. Observational study. We studied 3,751 participants with CKD in the prospective multicenter Chronic Renal Insufficiency Cohort (CRIC) who had baseline single-frequency BIA performed. Predictors included phase angle and vector length, which were calculated from measurements of resistance and reactance from BIA. We ranked phase angle and vector length into quartiles and compared the 2 narrower quartiles of phase angle and shorter quartiles of vector length with the 2 upper quartiles. Mortality, heart failure, atherosclerotic cardiovascular disease, and progression of CKD (30% decline in estimated glomerular filtration rate or end-stage kidney disease). We tested associations of phase angle and vector length with risks for mortality and progression of CKD using Cox proportional hazard models and the association with heart failure and atherosclerotic cardiovascular disease using Fine and Gray models. All models were adjusted for demographics, comorbidconditions, and kidney function. Mean phase angle and vector length were 6.6°±1.8° and 470 ± 96 Ω/m, respectively. Relative to phase angle≥ 6.40o, narrower phase angle (<5.59o) was significantly associated with mortality (HR, 1.31; 95% CI, 1.09-1.58). Relative to vector length≥ 459 Ω/m, shorter vector length (<401 Ω/m) was significantly associated with heart failure (HR, 1.28; 95% CI, 1.01-1.61). Neither measure was associated with atherosclerotic cardiovascular disease or a composite renal end point. Observational study. Adjusted for key confounders, BIA-derived measures of cellular integrity and tissue hydration were significantly associated with death and incident heart failure, respectively.

Coronary capillary blood flow in a rat model of congestive heart failure.

The morphology of CHF capillaries is significantly disordered and tortuous compared with control (CSI: 0.35 ± 0.02 for 61 images from 7 CHF rats; 0.58 ± 0.02 for 32 images from 7 control rats; P < 0.01). Estimated capillary resistance in CHF is elevated by 173% relative to control, while blood flow rate and blood velocity are 56 and 43% slower than control. Capillary resistance increased 67% due to the significantly narrower capillary diameter in CHF, while it increased an additional 105% due to tortuosity. The significant structural abnormalities of CHF coronary capillaries may drastically stagnate hemodynamics in myocardium and increase resistance to blood flow. This could play a role in the development of CHF. NEW & NOTEWORTHY In the present study, coronary capillary tortuosity was measured by applying Matrix Laboratory software to scanning electron microscope images of capillaries in a rat model of congestive heart failure. Stagnant blood flow in coronary capillaries may play a role in the development of congestive heart failure. The application of computer modeling to histological and physiological data to characterize the hemodynamics of coronary microcirculation is a new area of study.

Permutation Mutual Information: A Novel Approach for Measuring Neuronal Phase-Amplitude Coupling

Cross-frequency phase-amplitude coupling (PAC) in neuronal oscillations network plays an important functional role in large scale neuronal communication and neuronal encoding. In the present study, a novel approach named permutation mutual information (PMI) was applied in measuring PAC. It is derived from the permutation entropy based on the mutual information theory, by which the mutual information of permutations of two time series can be evaluated. In order to verify the ability of PMI, a numerical test was performed by using both simulation data and experimental data. The performances of PMI were compared with that of two well-known methods, which were the mean vector length (MVL) and the modulation index (MI). It was found that the performance of PMI was similar to that of MI when measuring PAC intensity, but the coupling sensitivity of PMI was the highest among all these three approaches. Moreover, there was the lowest sensitivity in the MVL measurement, suggesting that MVL was a more conservative approach in detecting the existence of PAC. In addition, an ROC analysis showed that PMI performed better in measuring PAC compared to that of others. Furthermore, the experimental data, obtained from rats' hippocampal CA3 regions, were analyzed by using the three approaches. The result was essentially in line with that of the simulation performances. In a word, the results suggest that PMI is a better choice for assessing PAC under the certain conditions.

PB 11 Phase-coupling optimization (PCO) – a new algorithm for the analysis and localization of phase-coupling in multivariate data

Introduction Phase-coupling between neuronal oscillations in the brain has been hypothesized as a mechanism for interactions between brain areas; moreover, phases of neuronal oscillations were found related to performance in memory and perception tasks. However, in multivariate data, such as multi-channel EEG or MEG, the analysis of phase-coupling remains challenging. Sensor-space analysis is suboptimal regarding the signal-to-noise ratio (SNR) and might fail to localize the sources of phase-coupling appropriately. Here, we introduce phase-coupling optimization (PCO), an algorithm seeking spatial filters that maximize the coupling of oscillatory phases to an independent variable (e.g., detected vs. undetected events in a perception task). The resulting spatial filters/patterns can then be used for inverse source modeling. Methods Due to its simplicity, the “mean vector length” measure was chosen to quantify the degree of phase-coupling and is being maximized using the quasi-Newton Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm. To avoid local minima, the optimization is restarted several times from low-discrepancy pseudo-random initial starting points. As regularization, spatio-spectral decomposition (SSD) reduces the search-space while maximizing the SNR in the selected frequency band. The performance of the algorithm was verified using realistic forward-model EEG simulations. Results Simulations demonstrated that PCO, together with SSD as pre-processing, can reliably localize the sources of phase-coupling in multi-channel EEG and characterize the coupling relation down to a SNR of −10 dB (i.e., a power ratio of 0.1) using 500 simulated task repetitions. Additionally, PCO is superior to a multiple regression approach and by a large margin outperforms sensor-space analysis based on a current source density estimation. Discussion The analysis of phase-coupling in sensor space is suboptimal due to the SNR of the signal and might even lead to erroneous source localization. Techniques such as beamforming on the other hand, require a well-founded a priori assumption on the spatial origin of phase-coupling and complex inverse problem solvers. PCO seeks the optimal spatial projection for the analysis of phase-coupling and demonstrated its reliability even for very low SNR. Hence, we regard it as a promising tool for the analysis of neuronal oscillations. Significance PCO increases the sensitivity and reliability of phase-coupling analyses. The obtained spatial patterns can be used for inverse source modeling.