[1] Traditional inversion techniques applied to the problem of characterizing the thermal and compositional structure of the upper mantle are not well suited to deal with the nonlinearity of the problem, the trade-off between temperature and compositional effects on wave velocities, the nonuniqueness of the compositional space, and the dissimilar sensitivities of physical parameters to temperature and composition. Probabilistic inversions, on the other hand, offer a powerful formalism to cope with all these difficulties, while allowing for an adequate treatment of the intrinsic uncertainties associated with both data and physical theories. This paper presents a detailed analysis of the two most important elements controlling the outputs of probabilistic (Bayesian) inversions for temperature and composition of the Earth's mantle, namely the a priori information on model parameters, (m), and the likelihood function, L(m). The former is mainly controlled by our current understanding of lithosphere and mantle composition, while the latter conveys information on the observed data, their uncertainties, and the physical theories used to relate model parameters to observed data.[2] The benefits of combining specific geophysical datasets (Rayleigh and Love dispersion curves, body wave tomography, magnetotelluric, geothermal, petrological, gravity, elevation, and geoid), and their effects on L(m), are demonstrated by analyzing their individual and combined sensitivities to composition and temperature as well as their observational uncertainties. The dependence of bulk density, electrical conductivity, and seismic velocities to major-element composition is systematically explored using Monte Carlo simulations. We show that the dominant source of uncertainty in the identification of compositional anomalies within the lithosphere is the intrinsic nonuniqueness in compositional space. A general strategy for defining (m) is proposed based on statistical analyses of a large database of natural mantle samples collected from different tectonic settings (xenoliths, abyssal peridotites, ophiolite samples, etc.). This strategy relaxes more typical and restrictive assumptions such as the use of local/limited xenolith data or compositional regionalizations based on age-composition relations. We demonstrate that the combination of our (m) with a L(m) that exploits the differential sensitivities of specific geophysical observables provides a general and robust inference platform to address the thermochemical structure of the lithosphere and sublithospheric upper mantle. An accompanying paper deals with the integration of these two functions into a general 3-D multiobservable Bayesian inversion method and its computational implementation.

S U M M A R YIn this study, we test the adequacy of 2-D sensitivity kernels for fundamental-mode Rayleigh waves based on the single-scattering (Born) approximation to account for the effects of heterogeneous structure on the wavefield in a regional surface wave study. The calculated phase and amplitude data using the 2-D sensitivity kernels are compared to phase and amplitude data obtained from seismic waveforms synthesized by the pseudo-spectral method for plane Rayleigh waves propagating through heterogeneous structure. We find that the kernels can accurately predict the perturbation of the wavefield even when the size of anomaly is larger than one wavelength. The only exception is a systematic bias in the amplitude within the anomaly itself due to a site response.An inversion method of surface wave tomography based on the sensitivity kernels is developed and applied to synthesized data obtained from a numerical simulation modelling Rayleigh wave propagation over checkerboard structure. By comparing recovered images to input structure, we illustrate that the method can almost completely recover anomalies within an array of stations when the size of the anomalies is larger than or close to one wavelength of the surface waves. Surface wave amplitude contains important information about Earth structure and should be inverted together with phase data in surface wave tomography.

SCC was associated with a significantly higher pCR rate than adenocarcinoma. Recurrence pattern and survival outcomes were significantly different between the 2 histology subtypes in non-pCR patients.

CT-guided radioactive seed (125)I implantation procedure is safe and well tolerated in treating locally advanced NSCLC, with few complications. It has good local control rate and can relieve symptoms without increasing side effects.

Background and purposeTo investigate effects of radiotherapy on normal brain tissue using in vivo neuroimaging in patients with nasopharyngeal carcinoma (NPC).Methods and materialsWe used longitudinal MRI to monitor structural brain changes during standard radiotherapy in patients newly diagnosed with NPC. We assessed volumetric measures in 63 patients at 2–3 time points before and after radiotherapy, with 20 NPC-free participants as normal controls. Images were processed using validated software (FreeSurfer). Automated results were inspected visually for accuracy. We examined changes in volume of the whole brain, gray matter, white matter, and ventricles, as well as in cerebral volumes partitioned into temporal, frontal, parietal, and occipital lobes. A linear mixed model was used to evaluate longitudinal changes in these measurements. Statistical significance was evaluated at p < 0.05, which was corrected for multiple comparisons.ResultsVolumes of the gray matter, and bilateral temporal lobes decreased in a time-dependent manner, whereas ventricle volume showed a time-dependent increase after radiotherapy. No volume changes were detected in NPC patients before radiotherapy when compared normal controls. No volume changes were detected in the subcohort of patients after completion of induction chemotherapy but prior to initiation of radiotherapy. Changes of bilateral temporal lobe volume correlated with irradiation dose in this region. Expansion of the ventricles correlated with a reduction in cognition assessment.ConclusionsWe detected significant and progressive radiotherapy-associated structural changes in the brains of patients with NPC who were treated with standard radiotherapy, especially in the bilateral temporal lobe in which the effect was dose-dependent. Expansion of the ventricles can serve as an imaging marker for treatment-related reduction in cognitive function. Future studies with longer follow-ups are needed to evaluate morphometric changes long-term after radiotherapy.

Increasing evidence indicates that radiation-induced injury to the hippocampus may play a critical role in neurocognitive dysfunction in patients with nasopharyngeal carcinoma (NPC). However, few studies have assessed RT-induced hippocampal structural alterations in these patients early after radiotherapy (RT). In this study, 58 NPC patients were longitudinally followed up prior to treatment initiation as well as 3 and 6 months after RT, respectively. Twenty comparable normal controls were recruited and followed up in parallel. A novel magnetic resonance imaging (MRI)-based automated method was used to label hippocampal subfields. The linear mixed model was employed to evaluate longitudinal changes in the volumes of the whole hippocampus and seven hippocampal subfields. Time-dependent volume reduction was observed in the bilateral hippocampus, as well as in the bilateral granule cell layer (GCL), bilateral cornu ammonis 1 (CA1), bilateral molecular layer (ML), and bilateral subiculum (SUB) in NPC patients, but not in controls. Moreover, volume deficits in the bilateral hippocampus, bilateral GCL, and right ML showed dose-dependent patterns, and high volume losses in the bilateral hippocampus, bilateral GCL, left SUB, and right ML were associated with a rapid decline in cognitive function. Our findings demonstrated that the hippocampal subfields were selectively injured by irradiation-related early neurotoxic effects, which might account for cognitive impairment in NPC patients at an early stage after RT. Further, structural MRI could serve as a potential noninvasive imaging biomarker for the early detection of radiation effects on the hippocampus in NPC patients after RT.

In this study, we seek to longitudinally investigate the network-level functional connectivity (FC) alternations and its association with irradiation dose and cognition changes in the early stage post radiotherapy (RT) in nasopharyngeal carcinoma (NPC) patients. We performed independent component analysis (ICA) of resting state blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI) from 39 newly diagnosed NPC patients before receiving treatment (baseline), and 3 months post-RT. the default mode network (DMN), salience network (SN), and executive control network (ECN) were extracted with well-validated software (GIFT). Inter-network connectivity was assessed using the functional network connectivity (FNC) toolbox. The inter- and intra-network FC was compared between time points, and the z value of FC alternation was correlated with the RT dose value and cognitive changes. Compared with baseline, the FC of the left anterior cingulate cortex (ACC) within the DMN, and the right insular within the SN, significantly reduced 3 months post-RT, with greater effects at higher doses in the right insular. Bilateral ECN FC was also significantly lower 3 months post-RT compared to the baseline. Chemotherapy was not associated with inter- and intra- network FC change. We found intra- and inter-network FC disruption in NPC patients 3 months post-RT, with the right insular showing a dose-dependent effect. Thus, this network-level FC may serve as a potential biomarker of the RT-induced brain functional impairments, and provide valuable targets for further functional recovery treatment.

A standard technique for locating events with T phases is to pick the peak energy of T phases as the arrival time, then proceed as if it was an unscattered phase originating at the epicenter. The peak energy arrival time, however, can shift to different parts of the wave train due to incoherent scattering. We show that a 50% reduction in variance relative to picks of peak arrival times can be achieved by fitting an assumed functional shape to the log of the entire envelope of the T phase. We test the stability of this approach by comparing relative event locations based on this method with those determined by cross-correlating waveforms of Rayleigh and Love surface waves recorded teleseismically using a swarm of earthquakes at the northern end of the Easter microplate as an example. Relative event locations show that there is no systematic bias in T-phase locations. The T-phase location and detection can be extended to much smaller events than are detectable by surface waves. We estimate T-phase maximum amplitudes of about 50 events within the swarm from the amplitude of the fitted functions rather than directly from the seismograms. Twenty-four of these events are large enough to estimate their magnitudes by surfacewave analysis. The empirical analysis shows the log of T-phase maximum amplitude and surface-wave magnitude (M S) exhibit a relatively uniform linear relationship with much less scatter than in previously published studies of T-phase amplitude versus magnitude. The reduction in scatter is due to both the stability of the functional estimate of amplitude and the use of a swarm of earthquakes with similar depth, mechanism, and source-receiver geometry. The observed T-phase coda for shallow earthquakes can be synthesized using a simple model of multiple-reverberation seafloor scattering. The results show that scattering of energy at a rough seafloor from multiple reverberations in the water column is significant in T-phase generation even where the water depths are relatively uniform.