Performance of Spectral Photon-Counting Coronary CT Angiography and Comparison with Energy-Integrating-Detector CT: Objective Assessment with Model Observer

Aims: To evaluate spectral photon-counting CT’s (SPCCT) objective image quality characteristics in vitro, compared with standard-of-care energy-integrating-detector (EID) CT. Methods: We scanned a thorax phantom with a coronary artery module at 10 mGy on a prototype SPCCT and a clinical dual-layer EID-CT under various conditions of simulated patient size (small, medium, and large). We used filtered back-projection with a soft-tissue kernel. We assessed noise and contrast-dependent spatial resolution with noise power spectra (NPS) and target transfer functions (TTF), respectively. Detectability indices (d’) of simulated non-calcified and lipid-rich atherosclerotic plaques were computed using the non-pre-whitening with eye filter model observer. Results: SPCCT provided lower noise magnitude (9–38% lower NPS amplitude) and higher noise frequency peaks (sharper noise texture). Furthermore, SPCCT provided consistently higher spatial resolution (30–33% better TTF10). In the detectability analysis, SPCCT outperformed EID-CT in all investigated conditions, providing superior d’. SPCCT reached almost perfect detectability (AUC ≈ 95%) for simulated 0.5-mm-thick non-calcified plaques (for large-sized patients), whereas EID-CT had lower d’ (AUC ≈ 75%). For lipid-rich atherosclerotic plaques, SPCCT achieved 85% AUC vs. 77.5% with EID-CT. Conclusions: SPCCT outperformed EID-CT in detecting simulated coronary atherosclerosis and might enhance diagnostic accuracy by providing lower noise magnitude, markedly improved spatial resolution, and superior lipid core detectability.

Do prior knowledge, model-observer similarity and social comparison influence the effectiveness of eye movement modeling examples for supporting multimedia learning?

We investigated in an experiment with 180 university students the joint role of prior knowledge, alleged model competence, and social comparison orientation regarding the effectiveness of Eye Movement Modeling Examples (EMME) for supporting multimedia learning. EMME consisted of short videos with gaze replays of an instructed model demonstrating effective multimedia processing strategies. Participants were either instructed that the model in the EMME-videos was a successful learner (competent model) or another participant (peer model). Participants in a control condition received no EMME. Furthermore, we activated domain-relevant prior knowledge in half of the participants before watching the EMME. Against our expectations, we found no influence of either prior knowledge activation or model-observer similarity. As expected, our results indicated that EMME fostered multimedia learning. This was also supported by findings from small-scale meta-analyses that were conducted with the focus on the effect of EMME for multimedia learning and potential moderators of the effect. Moreover, results showed first evidence that social comparison orientation interacts with (alleged) model competence regarding the effectiveness of EMME. Further research is needed to follow up on the influence of individual factors as well as social cues on the effectiveness of EMME.

Design of a lateral velocity observer based on synthesis of different sources

This paper is mainly devoted to estimating the lateral velocity of vehicle with an observer synthesis method using a cost-effective 6D inertial measurement unit. The four sources of observer to be synthesized come from the dynamics model, the kinematics model, and a LuGre tire model, respectively. The weight of each source is calculated by considering the nonlinear extent of each tire by means of the adaptation of tire cornering stiffness, which is adapted and updated using the dynamics model observer with the information obtained from the kinematics model observer. Then using the weighted sum of the four sources as the reference information for a modified kinematics observer, the final estimation can provide smooth and accurate results that are robust to sensor drifts and measurement noise, which is verified with several dSPACE based hardware-in-the-loop simulations.