PET/CT background noise and its effect on speech recognition

Positron emission tomography (PET) has been successfully used to investigate central nervous processes, including the central auditory pathway. Unlike early water-cooled PET-scanners, novel PET/CT scanners employ air cooling and include a CT system, both of which result in higher background noise levels. In the present study, we describe the background noise generated by two state-of-the-art air-cooled PET/CT scanners. We measured speech recognition in background noise: recorded PET noise and a speech-shaped noise applied in clinical routine to subjects with normal hearing. Background noise produced by air-cooled PET/CT is considerable: 75.1 dB SPL (64.5 dB(A)) for the Philips Gemini TF64 and 76.9 dB SPL (68.4 dB(A)) for the Philips Vereos PET/CT (Philips Healthcare, The Netherlands). Subjects with normal hearing exhibited better speech recognition in recorded PET background noise compared with clinically applied speech-shaped noise. Speech recognition in both background noises correlated significantly. Background noise generated by PET/CT scanners should be considered when PET is used for the investigation of the central auditory pathway. Speech in PET noise is better than in speech-shaped noise because of the minor masking effect of the background noise of the PET/CT.

Dual-Energy Heart CT: Beyond Better Angiography—Review

Heart CT has undergone substantial development from the use of calcium scores performed on electron beam CT to modern 256+-row CT scanners. The latest big step in its evolution was the invention of dual-energy scanners with much greater capabilities than just performing better ECG-gated angio-CT. In this review, we present the unique features of dual-energy CT in heart diagnostics.

StyroStone: A protocol for scanning and extracting three-dimensional meshes of stone artefacts using Micro-CT scanners v1

This protocol presents the first detailed step-by-step pipeline for the 3D scanning and post processing of large batches of lithic artefacts using a micro-computed tomography (micro-CT) scanner (i.e., a Phoenix v-tome-x S model by General Electronics MCC, Boston MA) and an Artec Space Spider scanner (Artec Inc., Luxembourg). This protocol was used to scan and analyze ca. 700 lithic artefacts from the Protoaurignacian layers at Fumane Cave in north-eastern Italy (Falcucci et al., in preparation). For this study several costly scanners and proprietary software packages were employed. Although it is not easy to find a low-budget alternative for the scanners, it is possible to use free and open-source software programs, such as 3D-Slicer (https://www.slicer.org/) or MorphoDig (https://morphomuseum.com/morphodig), to process CT data as well as MeshLab (Cignoni et al. 2008) to interact with the 3D models in general. However, if alternative software is used, the steps and their order described in this protocol might diverge significantly. A cost-effective alternative to create 3D models is digital photogrammetry using commercial cameras and freely available software like Meshroom (https://alicevision.org). Although photogrammetry is an affordable technique to create accurate 3D models of objects, this method might not be useful when scanning large batches of artefacts, as it will require a lot of computation time and processing capacity. Likewise, it could be difficult to generate accurate 3D models of very small and/or detailed tool shapes using 3D surface scanners because stone tools are often much smaller than the recommended minimum field of view. Similarly, the resolution of conventional medical CT scanners might not be sufficient to capture minor details of stone tools, such as the outline or dorsal scars. Thus, high-resolution micro-CT technology is the only reliable way to accurately capture the overall morphology of small stone tools. This protocol aims at providing the first detailed procedure dedicated to the scanning of small lithic implements for further three-dimensional analysis. Note that some of the steps must be repeated at different working stages throughout this protocol. In cases where a task must be done in the exact same way as described in a previous step, a reference to that step is provided. When slight changes were made, the step was modified and reported entirely. This protocol contains a few red and green colours (e.g., arrows or within-program colours) which might be perceived differently by people with dyschromatopsia. However, the display of these colours has been kept to a minimum. We recommend the reader to go over the entire protocol carefully, even if only some specific parts are required. A few points are in fact interdependent, and some of them must be applied simultaneously. Content: Part 1 – Styrofoam preparation Part 2 – Micro-CT scanning Part 3 – 3D model extraction of CT scanned stone artifacts using Avizo Part 4 – Cropping extracted surface model to separate Face A and B in Artec Studio Part 5 – Cropping Face A to separate the lines in Artec Studio Part 6 – Cropping each stone artefact from the lines in Artec Studio Part 7 – Virtually control measurements in MeshLab Part 8 – Artec scanning of larger artifacts Part 9 – Export meshes as non-binary ply models for successive analysis in geomorph Three-dimensional example (in ply format) of the effectivity of the StyroStone Protocol: You can download an example of one Styrofoam line in 3D obtained using our protocol to appreciate the result that can be achieved. We have selected a line where objects are characterized by different metric and morphological attributes. Notice the retouching well visible in the last five smaller artifacts (counting from the left when artifact are oriented with the dorsal face in front of the observer and the butt down), as well as the platforms and bulbs of all artifacts. For more information and examples, feel free to contact us!

Differences in the gray-to-white matter ratio according to different computed tomography scanners for outcome prediction in post-cardiac arrest patients receiving target temperature management

The gray-to-white matter ratio (GWR) has been used to identify brain damage in comatose patients after cardiac arrest. However, Hounsfield units (HUs), the measurement of brain density on computed tomography (CT) images, may vary depending on the machine type or parameter. Therefore, differences in CT scanners may affect the GWR in post-cardiac arrest patients. We performed a retrospective study on comatose post-cardiac arrest patients who visited the hospital from 2007 to 2017. Two CT, Lightspeed and SOMATOM, scanners were used. Two observers independently measured the HUs of the caudate nucleus, putamen, posterior internal capsule, and corpus callosum using regions of interest. We compared the GWR calculated from the HUs measured at different CT scanners. The analysis of different scanners showed statistically significant differences in the measured HUs and GWR. The HUs and GWR of Lightspeed were measured lower than SOMATOM. The difference between the two CT scanners was also evident in groups divided by neurological prognosis. The area under the curve of the receiver operating characteristic curve to predict poor outcomes of Lightspeed was 0.798, and the cut-off value for 100% specificity was 1.172. The SOMATOM was 0.855, and the cut-off value was 1.269. The difference in scanners affects measurements and performance characteristics of the GWR in post-cardiac arrest patients. Therefore, when applying the results of the GWR study to clinical practice, reference values for each device should be presented, and an integrated plan should be prepared.

A New Statistical Reconstruction Method for the Computed Tomography Using an X-Ray Tube with Flying Focal Spot

This paper presents a new image reconstruction method for spiral cone- beam tomography scanners in which an X-ray tube with a flying focal spot is used. The method is based on principles related to the statistical model-based iterative reconstruction (MBIR) methodology. The proposed approach is a continuous-to-continuous data model approach, and the forward model is formulated as a shift-invariant system. This allows for avoiding a nutating reconstruction-based approach, e.g. the advanced single slice rebinning methodology (ASSR) that is usually applied in computed tomography (CT) scanners with X-ray tubes with a flying focal spot. In turn, the proposed approach allows for significantly accelerating the reconstruction processing and, generally, for greatly simplifying the entire reconstruction procedure. Additionally, it improves the quality of the reconstructed images in comparison to the traditional algorithms, as confirmed by extensive simulations. It is worth noting that the main purpose of introducing statistical reconstruction methods to medical CT scanners is the reduction of the impact of measurement noise on the quality of tomography images and, consequently, the dose reduction of X-ray radiation absorbed by a patient. A series of computer simulations followed by doctor’s assessments have been performed, which indicate how great a reduction of the absorbed dose can be achieved using the reconstruction approach presented here.