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Emission-based attenuation correction (AC) meth-ods offer the possibility of overcoming quantification errors induced by conventional MR-based approaches in PET/MR imaging. However, the joint problem of determining AC and the activity of interest is strongly ill-posed in non-TOF PET. This can be improved by exploiting the extra information arising from low energy window photons, but the feasibility of this approach has only been studied with relatively simplistic analytic simulations so far. This manuscript aims to address some of the remaining challenges needed to handle realistic measurements; in particular, the detection efficiency (“normalisation”) estimation for each energy window is investigated. An energy-dependent detection efficiency model is proposed, accounting for the presence of unscattered events in the lower energy window due to detector scatter. Geometric calibration factors are estimated prior to the reconstruction for both scattered and unscattered events. Different reconstruction methods are also compared. Results show that geometric factors differ markedly between the energy windows and that our analytical model correspond in good approximation to Monte Carlo simulation; the multiple energy window reconstruction appears sensitive to input/model mismatch. Our method applies to Monte Carlo generated data but can be extended to measured data. This study is restricted to single scatter events.

Positron emission tomography/computed tomography (PET/CT) lung imaging is highly sensitive to motion. Although several techniques exist to diminish motion artifacts, a few accounts for both tissue displacement and changes in density due to the compression and dilation of the lungs, which cause quantification errors. This article presents an experimental framework for joint activity image reconstruction and motion estimation in PET/CT, where the PET image and the motion are directly estimated from the raw data. Direct motion estimation methods for motion-compensated PET/CT are preferable as they require a single attenuation map only and result in optimal signal-to-noise ratio (SNR). Previous implementations, however, failed to address changes in density during respiration. We propose to account for such changes using the Jacobian determinant of the deformation fields. In a feasibility study, we demonstrate on a modified extended cardiac-torso (XCAT) phantom with breathing motion—where the lung density and activity vary—that our approach achieved better quantification in the lungs than conventional PET/CT joint activity image reconstruction and motion estimation that does not account for density changes. The proposed method resulted in lower bias and variance in the activity images, reduced mean relative activity error in the lung at the reference gate (−4.84% to −3.22%) and more realistic Jacobian determinant values.

Estimation of attenuation from positron emission tomography (PET) data only is of interest for hybrid PET-MR and systems where CT is not available or recommended. However, when using data from a single energy window, emission-based non-time-of-flight (TOF) PET attenuation correction (AC) methods suffer from “cross-talk” artifacts. Based on earlier work, this article explores the hypothesis that cross-talk can be reduced by using more than one energy window. We propose an algorithm for the simultaneous estimation of both activity and attenuation images, as well as, the scatter component of the measured data from a PET acquisition, using multiple energy windows. The model for the measurements is 3-D and accounts for the finite energy resolution of PET detectors; it is restricted to single scatter. The proposed energy-based simultaneous maximum likelihood reconstruction of activity and attenuation with photopeak scatter re-estimation algorithm is compared with simultaneous estimation from a single energy window simultaneous maximum likelihood reconstruction of activity and attenuation with photopeak scatter re-estimation. The evaluation is based on simulations using the characteristics of the Siemens mMR scanner. Phantoms of different complexity were investigated. In particular, a 3-D XCAT torso phantom was used to assess the inpainting of attenuation values within the lung region. Results show that the cross-talk present in non-TOF maximum likelihood reconstruction of activity and attenuation reconstructions is significantly reduced when using multiple energy windows and indicate that the proposed approach warrants further investigation.