Maria Guerrisi

Transcranial magnetic stimulation in heterogeneous brain tissue: clinical impact on focality, reproducibility and true sham stimulation.

BACKGROUND Transcranial magnetic stimulation (TMS) is an attractive research and possibly therapeutic tool for non-invasive central nervous system stimulation. However, relatively little is known about the direction, magnitude and distribution of induced electric field and current flows in tissue, and optimal setup characteristics as well as appropriate sham stimulation conditions remain largely undetermined, hampering reproducibility. METHODS We reconstruct the conductive phenomena induced by TMS by implementing digitized coil geometry and realistic stimulator parameters and solving the electromagnetic problem over an MRI-based, realistic head model of 1mm resolution. Findings are validated by recording motor evoked potentials from the right abductor pollicis brevis muscle from healthy subjects stimulated in a stereotaxic framework. RESULTS Several commonly used sham stimulation configurations elicit conductive patterns which achieve up to 40% of the strength of real stimulation. Also, variations in coil position of the order of a 7 degrees tilt, which are expected to occur in non-stereotaxic stimulation, can alter the stimulation intensity by up to 25%. CONCLUSIONS In accordance with our findings, several clinical studies observe measurable effects during sham stimulation or no significant difference between sham and real stimulation, and the sensitivity of stimulation intensity to tiny coil rotations affords a partial explanation for the poor reproducibility and partial disagreements observed across clinical TMS studies. Knowledge of coil and stimulator specifications alone is hence not sufficient to control stimulation conditions, and a stereotaxic setup coupled with individually adjusted field solvers appear essential in performing reliable TMS studies.

Physiologic autonomic arousal heralds motor manifestations of seizures in nocturnal frontal lobe epilepsy: Implications for pathophysiology

OBJECTIVE This study describes changes in heart rate (HR) and HR variability (HRV) related to clinical onset of seizures in nocturnal frontal lobe epilepsy (NFLE) in order to determine whether signs of autonomic activation precede onset of seizure motor manifestations, which was selected as seizure onset (SO). Further, to clarify the nature (epileptic or physiologic) of the changes in autonomic cardiac control presumed to precede SO, time-dependent variations in HR and HRV related to physiological cortical arousals associated with motor activity (phases of transitory activation, PAT) were also investigated. METHODS HR and HRV spectral power, quantified by means of wavelet transform, were analyzed in relation to the onset of motor manifestations in 45 NFLE seizures and 45 PAT derived from whole night video-polysomnographic recordings of ten patients and of ten control subjects, respectively. RESULTS Analysis of HRV showed a shift of sympathetic/parasympathetic cardiac control toward a sympathetic predominance in the 10s immediately preceding SO, while changes in HR were evident only one second before SO. This sympathetic activation was not associated with a sleep-wake transition or changes in respiratory activity, both of which occurred concurrently with SO. Similar changes in HR and HRV were observed in the 10s before the motor and electroencephalographic onset of PAT. CONCLUSIONS Our study demonstrates that a similar autonomic activation precedes the motor manifestations of NFLE seizures and physiological arousal. This autonomic activation could represent part of the arousal response, which could be implicated in the occurrence of both seizure and arousal motor manifestations.

Heart rate variability in untreated newly diagnosed temporal lobe epilepsy: Evidence for ictal sympathetic dysregulation

To compare heart rate variability (HRV) parameters in newly diagnosed and untreated temporal lobe epilepsy (TLE) between the interictal, preictal, ictal, and postictal states.

Globally conditioned Granger causality in brain-brain and brain-heart interactions: a combined heart rate variability/ultra-high-field (7 T) functional magnetic resonance imaging study.

The causal, directed interactions between brain regions at rest (brain–brain networks) and between resting-state brain activity and autonomic nervous system (ANS) outflow (brain–heart links) have not been completely elucidated. We collected 7 T resting-state functional magnetic resonance imaging (fMRI) data with simultaneous respiration and heartbeat recordings in nine healthy volunteers to investigate (i) the causal interactions between cortical and subcortical brain regions at rest and (ii) the causal interactions between resting-state brain activity and the ANS as quantified through a probabilistic, point-process-based heartbeat model which generates dynamical estimates for sympathetic and parasympathetic activity as well as sympathovagal balance. Given the high amount of information shared between brain-derived signals, we compared the results of traditional bivariate Granger causality (GC) with a globally conditioned approach which evaluated the additional influence of each brain region on the causal target while factoring out effects concomitantly mediated by other brain regions. The bivariate approach resulted in a large number of possibly spurious causal brain–brain links, while, using the globally conditioned approach, we demonstrated the existence of significant selective causal links between cortical/subcortical brain regions and sympathetic and parasympathetic modulation as well as sympathovagal balance. In particular, we demonstrated a causal role of the amygdala, hypothalamus, brainstem and, among others, medial, middle and superior frontal gyri, superior temporal pole, paracentral lobule and cerebellar regions in modulating the so-called central autonomic network (CAN). In summary, we show that, provided proper conditioning is employed to eliminate spurious causalities, ultra-high-field functional imaging coupled with physiological signal acquisition and GC analysis is able to quantify directed brain–brain and brain–heart interactions reflecting central modulation of ANS outflow.

MR Scanner Systems Should Be Adequately Characterized in Diffusion-MRI of the Breast

Breast imaging represents a relatively recent and promising field of application of quantitative diffusion-MRI techniques. In view of the importance of guaranteeing and assessing its reliability in clinical as well as research settings, the aim of this study was to specifically characterize how the main MR scanner system-related factors affect quantitative measurements in diffusion-MRI of the breast. In particular, phantom acquisitions were performed on three 1.5 T MR scanner systems by different manufacturers, all equipped with a dedicated multi-channel breast coil as well as acquisition sequences for diffusion-MRI of the breast. We assessed the accuracy, inter-scan and inter-scanner reproducibility of the mean apparent diffusion coefficient measured along the main orthogonal directions () as well as of diffusion-tensor imaging (DTI)-derived mean diffusivity (MD) measurements. Additionally, we estimated spatial non-uniformity of (NU) and MD (NUMD) maps. We showed that the signal-to-noise ratio as well as overall calibration of high strength diffusion gradients system in typical acquisition sequences for diffusion-MRI of the breast varied across MR scanner systems, introducing systematic bias in the measurements of diffusion indices. While and MD values were not appreciably different from each other, they substantially varied across MR scanner systems. The mean of the accuracies of measured and MD was in the range [−2.3%,11.9%], and the mean of the coefficients of variation for and MD measurements across MR scanner systems was 6.8%. The coefficient of variation for repeated measurements of both and MD was < 1%, while NU and NUMD values were <4%. Our results highlight that MR scanner system-related factors can substantially affect quantitative diffusion-MRI of the breast. Therefore, a specific quality control program for assessing and monitoring the performance of MR scanner systems for diffusion-MRI of the breast is highly recommended at every site, especially in multicenter and longitudinal studies.

Differences in Gaussian diffusion tensor imaging and non-Gaussian diffusion kurtosis imaging model-based estimates of diffusion tensor invariants in the human brain.

PURPOSE An increasing number of studies have aimed to compare diffusion tensor imaging (DTI)-related parameters [e.g., mean diffusivity (MD), fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD)] to complementary new indexes [e.g., mean kurtosis (MK)/radial kurtosis (RK)/axial kurtosis (AK)] derived through diffusion kurtosis imaging (DKI) in terms of their discriminative potential about tissue disease-related microstructural alterations. Given that the DTI and DKI models provide conceptually and quantitatively different estimates of the diffusion tensor, which can also depend on fitting routine, the aim of this study was to investigate model- and algorithm-dependent differences in MD/FA/RD/AD and anisotropy mode (MO) estimates in diffusion-weighted imaging of human brain white matter. METHODS The authors employed (a) data collected from 33 healthy subjects (20-59 yr, F: 15, M: 18) within the Human Connectome Project (HCP) on a customized 3 T scanner, and (b) data from 34 healthy subjects (26-61 yr, F: 5, M: 29) acquired on a clinical 3 T scanner. The DTI model was fitted to b-value =0 and b-value =1000 s/mm(2) data while the DKI model was fitted to data comprising b-value =0, 1000 and 3000/2500 s/mm(2) [for dataset (a)/(b), respectively] through nonlinear and weighted linear least squares algorithms. In addition to MK/RK/AK maps, MD/FA/MO/RD/AD maps were estimated from both models and both algorithms. Using tract-based spatial statistics, the authors tested the null hypothesis of zero difference between the two MD/FA/MO/RD/AD estimates in brain white matter for both datasets and both algorithms. RESULTS DKI-derived MD/FA/RD/AD and MO estimates were significantly higher and lower, respectively, than corresponding DTI-derived estimates. All voxelwise differences extended over most of the white matter skeleton. Fractional differences between the two estimates [(DKI - DTI)/DTI] of most invariants were seen to vary with the invariant value itself as well as with MK/RK/AK values, indicating substantial anatomical variability of these discrepancies. In the HCP dataset, the median voxelwise percentage differences across the whole white matter skeleton were (nonlinear least squares algorithm) 14.5% (8.2%-23.1%) for MD, 4.3% (1.4%-17.3%) for FA, -5.2% (-48.7% to -0.8%) for MO, 12.5% (6.4%-21.2%) for RD, and 16.1% (9.9%-25.6%) for AD (all ranges computed as 0.01 and 0.99 quantiles). All differences/trends were consistent between the discovery (HCP) and replication (local) datasets and between estimation algorithms. However, the relationships between such trends, estimated diffusion tensor invariants, and kurtosis estimates were impacted by the choice of fitting routine. CONCLUSIONS Model-dependent differences in the estimation of conventional indexes of MD/FA/MO/RD/AD can be well beyond commonly seen disease-related alterations. While estimating diffusion tensor-derived indexes using the DKI model may be advantageous in terms of mitigating b-value dependence of diffusivity estimates, such estimates should not be referred to as conventional DTI-derived indexes in order to avoid confusion in interpretation as well as multicenter comparisons. In order to assess the potential and advantages of DKI with respect to DTI as well as to standardize diffusion-weighted imaging methods between centers, both conventional DTI-derived indexes and diffusion tensor invariants derived by fitting the non-Gaussian DKI model should be separately estimated and analyzed using the same combination of fitting routines.

Assessment of spontaneous cardiovascular oscillations in Parkinson's disease

Parkinsons disease (PD) has been reported to involve postganglionic sympathetic failure and a wide spectrum of autonomic dysfunctions including cardiovascular, sexual, bladder, gastrointestinal and sudo-motor abnormalities. While these symptoms may have a significant impact on daily activities, as well as quality of life, the evaluation of autonomic nervous system (ANS) dysfunctions relies on a large and expensive battery of autonomic tests only accessible in highly specialized laboratories. In this paper we aim to devise a comprehensive computational assessment of disease-related heartbeat dynamics based on instantaneous, time-varying estimates of spontaneous (resting state) cardiovascular oscillations in PD. To this end, we combine standard ANS-related heart rate variability (HRV) metrics with measures of instantaneous complexity (dominant Lyapunov exponent and entropy) and higher-order statistics (bispectra). Such measures are computed over 600-s recordings acquired at rest in 29 healthy subjects and 30 PD patients. The only significant group-wise differences were found in the variability of the dominant Lyapunov exponent. Also, the best PD vs. healthy controls classification performance (balanced accuracy: 73.47%) was achieved only when retaining the time-varying, non-stationary structure of the dynamical features, whereas classification performance dropped significantly (balanced accuracy: 61.91%) when excluding variability-related features. Additionally, both linear and nonlinear model features correlated with both clinical and neuropsychological assessments of the considered patient population. Our results demonstrate the added value and potential of instantaneous measures of heartbeat dynamics and its variability in characterizing PD-related disabilities in motor and cognitive domains.

Diffusion tensor imaging in SPG11- and SPG4-linked hereditary spastic paraplegia

The aim of this study was to identify potential diagnostic markers of Hereditary Spastic Paraplegia (HSP). We investigated the white matter features of spastic gait (SPG)11- and SPG4-linked HSP, using diffusion tensor imaging performed with a 3-Tesla (3T) scanner. We examined four patients with SPG11 mutations, three with SPG4 mutations, and 26 healthy controls. We obtained maps of fractional anisotropy (FA) and mean diffusivity (MD), which we analyzed through both region of interest -based approach and tract-based spatial statistics (TBSS). Compared with healthy controls, SPG11 patients presented increased MD and decreased FA in the semioval centers, frontal and peritrigonal white matter, posterior limb of the internal capsule, and throughout the corpus callosum. Similar alterations were seen in the SPG4 patients at the levels of the semioval centers, the posterior limb of the internal capsule, the left cerebral pedicle, the genu and trunk of the corpus callosum, and the peritrigonal white matter on the left. No MD or FA alterations were observed in the cerebellar white matter. In a direct comparison, white matter alterations were more pronounced and widespread in HSP-SPG11 than in HSP-SPG4 patients. Joint TBSS analysis of all three groups confirmed significant widespread alterations of FA and MD values in the supratentorial white matter. This noninvasive study documented the presence of altered diffusivity in white matter in both forms of HSP, which could represent an important diagnostic marker of HSP. The association of reduced FA and increased MD in this patient population supports the interpretation of HPG as a neurodegenerative disorder.

Intraoperative haemodynamic monitoring: A pilot study on integrated data collection, processing and modelling for extracting vital signs and beyond

In this paper we illustrate an ongoing project focused on intraoperative monitoring of haemodynamic stability and cardiorespiratory interactions, and present an example analysis of vital signs recorded synchronously from multiple monitoring devices through a LabView©-based acquisition software termed “Global Collect”. We present two moving average models for the black box estimation of the gains of the cardiopulmonary baroreflex control of arterial resistance and of ventricular contractility, based on invasive, continuous measurements of arterial blood pressure and central venous pressure. As a proof-of-concept, we analyze the effects of a fluid-challenge maneuver performed during major surgery, quantifying the mechanisms through which such maneuvers are able to increase cardiac performance and hence enhance venous return. These preliminary results of a pilot case study demonstrate the potential of investigating autonomic nervous system control of circulation under general anesthesia in advancing intraoperative patient monitoring and aiding maintenance of haemodynamic stability in patients undergoing major surgery.

Differential response of peripheral arterial compliance-related indices to a vasoconstrictive stimulus

Peripheral arterial elastic properties are greatly affected by cardiovascular as well as other pathologies, and their assessment can provide useful diagnostic indicators. The photoplethysmographic technique can provide finger blood volume and pressure waveforms non-invasively, which can then be processed statically or beat-to-beat to characterize parameters of the vessel wall mechanics. We employ an occlusion-deflation protocol in 48 healthy volunteers to study peripheral artery compliance-related indices over positive and negative transmural pressure values as well as under the influence of a valid vasoconstrictor (cigarette smoking). We calculate beat-to-beat indices (compliance index CI, distensibility index DI, three viscoelastic model parameters (compliance C, viscosity R and inertia L), pressure-volume loop areas A and damping factor DF as well as symmetrical (C(max)) and asymmetrical (C(A)(max)) static compliance estimates, and their distributions over transmural pressure. All distributions are bell-shaped and centred on negative transmural pressure values. Distribution heights were significantly lower in the smoking group (w.r.t. the non-smoking group) for C, CI, DI and significantly higher in R and DF. The estimated volume signal time lag was also significantly lower in the smoking group. Left and right distribution widths were significantly different in all parameters/groups but DI (both groups), C(A)(max), A (smoking group) and L (non-smoking group), and positions of maxima/minima were significantly altered in C(A)(max), R and DF. C, DF and CI are seen to be most sensitive under this protocol, while C(max) and C(A)(max) are seen to be insensitive. These quantities provide complementary, time- and transmural pressure-dependent information about arterial wall mechanics, and the choice of index should depend on the physiological conditions at hand as well as relevant time resolution and transmural pressure range.