Optimisation of reconstruction, volumetry and dosimetry for 99mTc-SPECT and 90Y-PET images: Towards reliable dose-volume histograms for selective internal radiation therapy with 90Y-microspheres.

PURPOSE: In Selective Internal Radiation Therapy (SIRT), 99mTc-MAA SPECT images are commonly used to predict microspheres distribution but recent works used 90Y-microspheres PET images. Nevertheless, evaluation of the predictive power of 99mTc-MAA has been hampered by the lack of reliable comparisons between 99mTc-SPECT and 90Y-PET images. Our aim was to determine the "in situ" optimisation procedure in order to reliably compare 99mTc-SPECT and 90Y-PET images and achieve optimal personal dosimetry. METHODS: We acquired 99mTc-SPECT/CT and 90Y-PET/CT images of NEMA and Jaszczak phantoms. We found the best reconstruction parameters for quantification and for volume estimations. We determined adaptive threshold curves on the volumetric reconstruction. We copied the optimised volumes on the quantitative reconstruction, named here the "cross volumes" technique. Finally, we compared 99mTc-SPECT and 90Y-PET Dose Volume Histograms. RESULTS: Our "in situ" optimisation procedure decreased errors on volumes and quantification (from -44.2% and -15.8% to -3.4% and -3.28%, respectively, for the 26.5mL PET phantom sphere). Moreover, 99mTc-SPECT and 90Y-PET DVHs were equivalent only after the optimisation procedure (difference in mean dose <5% for the three biggest spheres). CONCLUSIONS: This work showed that a preliminary "in situ" phantom study was necessary to optimise volumes and quantification of 99mTc-SPECT and 90Y-PET images and allowed to achieve a reliable comparison between patient treatment planning and post implant dosimetry, notably by the use of the "cross volumes" technique. Methodology developed in this work will enable robust evaluations of the predictive power of 99mTc-SPECT, as well as dose-response relationship and side effects in SIRT treatments.

Single-epoch analysis of interleaved evoked potentials and fMRI responses during steady-state visual stimulation.

OBJECTIVE: Aim of the study was to record BOLD-fMRI interleaved with evoked potentials for single-epochs of visual stimulation and to investigate the possible relationship between these two measures. METHODS: Sparse recording of fMRI and EEG allowed us to measure BOLD responses and evoked potentials on an epoch-by-epoch basis. To obtain robust estimates of evoked potentials, we used blocks of contrast-reversing visual stimuli eliciting steady-state visual evoked potentials (SSVEPs). For each block we acquired one volume of fMRI data and we then tested for co-variations between SSVEPs and fMRI signals. Our analyses tested for frequency-specific co-variation between the two measurements that could not be explained by the mere presence/absence of the visual stimulation. RESULTS: Condition-specific single-epoch SSVEPs and fMRI responses were observed at occipital sites. Combined SSVEPs-fMRI analysis at the single-epoch level did not reveal any significant correlation between the two recordings. However, both signals contained stimulation-specific linear decreases that may relate to neuronal habituation. CONCLUSIONS: Our findings demonstrate robust estimation of single-epoch evoked potentials and fMRI responses during interleaved recording, using visual steady-state stimulation. SIGNIFICANCE: Single-epochs analysis of evoked potentials and fMRI signals is feasible for interleaved SSVEPs-fMRI recordings.

Realistic simulations of neuronal activity: a contribution to the debate on direct detection of neuronal currents by MRI.

Many efforts have been done in order to preview the properties of the magnetic resonance (MR) signals produced by the neuronal currents using simulations. In this paper, starting with a detailed calculation of the magnetic field produced by the neuronal currents propagating over single hippocampal CA1 pyramidal neurons placed inside a cubic MR voxel of length 1.2 mm, we proceeded on the estimation of the phase and magnitude MR signals. We then extended the results to layers of parallel and synchronous similar neurons and to ensembles of layers, considering different echo times, voxel volumes and neuronal densities. The descriptions of the neurons and of their electrical activity took into account the real neuronal morphologies and the physiology of the neuronal events. Our results concern: (a) the expected time course of the MR signals produced by the neuronal currents in the brain, based on physiological and anatomical properties; (b) the different contributions of post-synaptic potentials and of action potentials to the MR signals; (c) the estimation of the equivalent current dipole and the influence of its orientation with respect to the external magnetic field on the observable MR signal variations; (d) the size of the estimated neuronal current induced phase and magnitude MR signal changes with respect to the echo time, voxel-size and neuronal density. The inclusion of realistic neuronal properties into the simulation introduces new information that can be helpful for the design of MR sequences for the direct detection of neuronal current effects and the testing of bio-electromagnetic models.

Evaluation of mixed effects in event-related fMRI studies: impact of first-level design and filtering.

With the introduction of event-related designs in fMRI, it has become crucial to optimize design efficiency and temporal filtering to detect activations at the 1st level with high sensitivity. We investigate the relevance of these issues for fMRI population studies, that is, 2nd-level analysis, for a set of event-related fMRI (er-fMRI) designs with different 1st-level efficiencies, adopting three distinct 1st-level filtering strategies as implemented in SPM99, SPM2, and FSL3.0. By theory, experiments, and simulations using physiological fMRI noise, we show that both design and filtering impact the outcome of the statistical analysis, not only at the 1st but also at the 2nd level. There are several reasons behind this finding. First, sensitivity is affected by both design and filtering, since the scan-to-scan variance, that is the fixed effect, is not negligible with respect to the between-subject variance, that is the random effect, in er-fMRI population studies. The impact of the fixed effects error on the sensitivity of the mixed effects analysis can be mitigated by an optimal choice of er-fMRI design and filtering. Moreover, the accuracy of the 1st- and 2nd-level parameter estimates also depend on design and filtering; especially, we show that inaccuracies caused by the presence of residual noise autocorrelations can be constrained by designs that have hemodynamic responses with a Gaussian distribution. In conclusion, designs with both good efficiency and decorrelating properties, for example, such as the geometric or Latin square probability distributions, combined with the "whitening" filters of SPM2 and FSL3.0, give the best result, both for 1st- and 2nd-level analysis of er-fMRI studies.

The aerobic brain: lactate decrease at the onset of neural activity.

The metabolic events of neuronal energetics during functional activity are still partially unexplained. In particular, lactate (and not glucose) was recently proposed as the main substrate for neurons during activity. By means of proton magnetic resonance spectroscopy, lactate was reported to increase during the first minutes of prolonged stimulation, but the studies reported thus far suffered from low temporal resolution. In the present study we used a time-resolved proton magnetic resonance spectroscopy strategy in order to analyse the evolution of lactate during the early seconds following a brief visual stimulation (event-related design). A significant decrease in lactate concentration was observed 5 s after the stimulation, while a recovering of the baseline was observed at 12 s.

Issues concerning the construction of a metabolic model for neuronal activation.

The metabolic events underlying neuronal activity still remain the object of intense debate, in spite of the considerable amount of information provided from different experimental techniques. Indeed, several attempts at linking the cellular metabolic phenomena with the macroscopic physiological changes have not yet attained foolproof conclusions. The difficulties in drawing definitive conclusions are due primarily to the heterogeneity of the experimental procedures used in different laboratories, and also given the impossibility of extrapolating the findings obtained under stationary conditions (prolonged stimulation) to dynamic and transient phenomena. Recently, lactate has received much attention, following its proposal by Pellerin and Magistretti (1994; Proc. Natl. Acad. Sci. USA 91:10625-10629), instead of glucose, as the main substrate for neurons during activity. Several challenging aspects suggest the return to a more conventional view of neuronal metabolism, in which neurons are able to metabolize ambient glucose directly as their major substrate, also during activation.

The physiology and metabolism of neuronal activation: in vivo studies by NMR and other methods.

In this article, a review is made of the current knowledge concerning the physiology and metabolism of neuronal activity, as provided by the application of NMR approaches in vivo. The evidence furnished by other functional spectroscopic and imaging techniques, such as PET and optical methods, are also discussed. In spite of considerable amounts of studies presented in the literature, several controversies concerning the mechanisms underlying brain function still remain, mainly due to the difficult assessment of the single vascular and metabolic dynamics which generally influence the functional signals. In this framework, methodological and technical improvements are required to provide new and reliable experimental elements, which can support or eventually modify the current models of activation.