Rigid motion correction of dual opposed planar projections in single photon imaging.

Awake and/or freely moving small animal single photon emission imaging allows the continuous study of molecules exhibiting slow kinetics without the need to restrain or anaesthetise the animals. Estimating motion free projections in freely moving small animal planar imaging can be considered as a limited angle tomography problem, except that we wish to estimate the 2D planar projections rather than the 3D volume, where the angular sampling in all three axes depends on the rotational motion of the animal. In this study, we hypothesise that the motion corrected planar projections estimated by reconstructing an estimate of the 3D volume using an iterative motion compensating reconstruction algorithm and integrating it along the projection path, will closely match the true, motion-less, planar distribution regardless of the object motion. We tested this hypothesis for the case of rigid motion using Monte-Carlo simulations and experimental phantom data based on a dual opposed detector system, where object motion was modelled with 6 degrees of freedom. In addition, we investigated the quantitative accuracy of the regional activity extracted from the geometric mean of opposing motion corrected planar projections. Results showed that it is feasible to estimate qualitatively accurate motion-corrected projections for a wide range of motions around all 3 axes. Errors in the geometric mean estimates of regional activity were relatively small and within 10% of expected true values. In addition, quantitative regional errors were dependent on the observed motion, as well as on the surrounding activity of overlapping organs. We conclude that both qualitatively and quantitatively accurate motion-free projections of the tracer distribution in a rigidly moving object can be estimated from dual opposed detectors using a correction approach within an iterative reconstruction framework and we expect this approach can be extended to the case of non-rigid motion.

Attenuation correction for freely moving small animal brain PET studies based on a virtual scanner geometry.

Attenuation correction in positron emission tomography brain imaging of freely moving animals is a very challenging problem since the torso of the animal is often within the field of view and introduces a non negligible attenuating factor that can degrade the quantitative accuracy of the reconstructed images. In the context of unrestrained small animal imaging, estimation of the attenuation correction factors without the need for a transmission scan is highly desirable. An attractive approach that avoids the need for a transmission scan involves the generation of the hull of the animal's head based on the reconstructed motion corrected emission images. However, this approach ignores the attenuation introduced by the animal's torso. In this work, we propose a virtual scanner geometry which moves in synchrony with the animal's head and discriminates between those events that traversed only the animal's head (and therefore can be accurately compensated for attenuation) and those that might have also traversed the animal's torso. For each recorded pose of the animal's head a new virtual scanner geometry is defined and therefore a new system matrix must be calculated leading to a time-varying system matrix. This new approach was evaluated on phantom data acquired on the microPET Focus 220 scanner using a custom-made phantom and step-wise motion. Results showed that when the animal's torso is within the FOV and not appropriately accounted for during attenuation correction it can lead to bias of up to 10% . Attenuation correction was more accurate when the virtual scanner was employed leading to improved quantitative estimates (bias < 2%), without the need to account for the attenuation introduced by the extraneous compartment. Although the proposed method requires increased computational resources, it can provide a reliable approach towards quantitatively accurate attenuation correction for freely moving animal studies.

Microstructural white matter changes are correlated with the stage of psychiatric illness.

Microstructural white matter changes have been reported in the brains of patients across a range of psychiatric disorders. Evidence now demonstrates significant overlap in these regions in patients with affective and psychotic disorders, thus raising the possibility that these conditions share common neurobiological processes. If affective and psychotic disorders share these disruptions, it is unclear whether they occur early in the course or develop gradually with persistence or recurrence of illness. Utilisation of a clinical staging model, as an adjunct to traditional diagnostic practice, is a viable mechanism for measuring illness progression. It is particularly relevant in young people presenting early in their illness course. It also provides a suitable framework for determining the timing of emergent brain alterations, including disruptions of white matter tracts. Using diffusion tensor imaging, we investigated the integrity of white matter tracts in 74 patients with sub-syndromal psychiatric symptoms as well as in 69 patients diagnosed with established psychosis or affective disorder and contrasted these findings with those of 39 healthy controls. A significant disruption in white matter integrity was found in the left anterior corona radiata and in particular the anterior thalamic radiation for both the patients groups when separately contrasted with healthy controls. Our results suggest that patients with sub-syndromal symptoms exhibit discernable early white matter changes when compared with healthy control subjects and more significant disruptions are associated with clinical evidence of illness progression.