Comparing the Accuracy of Close-Range Photogrammetry to microCT Scanning via Surface Deviation Analysis of 3D Digital Models of Hominin Molars

The purpose of this study is to assess whether close-range photogrammetry is a viable alternative to microCT scanning for the construction of 3D models of isolated teeth. Photogrammetric scanning is more cost-effective and less time-consuming than CT scanning, and in paleoanthropological contexts eliminates the possibility of exposing fossils to doses of radiation that affect ESR dating. Samples of fossil (Homo naledi), archaeological, and contemporary human molars were scanned via microCT scanning and close-range photogrammetric scanning. The photogrammetric scans included 96 digital images per tooth which were used to construct a 3D triangular mesh. The resulting models of the tooth crowns were compared to their corresponding CT models using point-to-point surface deviation analysis, which measures the distance between analogous points on each mesh. Surface deviation analysis was also conducted in order to compare the surface difference between the CT meshes before and after processing functions such as smoothing and retriangulation. Paired t-tests comparing the surface difference between processed CT and photogrammetric meshes and the surface difference between processed and unprocessed CT meshes show no significant difference in the level of deviation within the archaeological and contemporary molar samples. A threshold range of acceptable surface difference was devised and applied to the H. naledi sample. A total of 73% of the H. naledi teeth and 70% of all three samples provided photogrammetric meshes that fell into this range of acceptable difference. The majority of molars that fell outside the established range had crown surfaces that were unstained and reflective. The results of this study therefore indicate that close range-photogrammetry provides an accessible alternative to microCT scanning for generating 3D surface models of isolated teeth when sufficient texture and color contrast data is present to aid in photogrammetric scanning accuracy

Towards Precision Medicine in Psychosis: Benefits and Challenges of Multimodal Multicenter Studies-PSYSCAN: Translating Neuroimaging Findings From Research into Clinical Practice

In the last 2 decades, several neuroimaging studies investigated brain abnormalities associated with the early stages of psychosis in the hope that these could aid the prediction of onset and clinical outcome. Despite advancements in the field, neuroimaging has yet to deliver. This is in part explained by the use of univariate analytical techniques, small samples and lack of statistical power, lack of external validation of potential biomarkers, and lack of integration of nonimaging measures (eg, genetic, clinical, cognitive data). PSYSCAN is an international, longitudinal, multicenter study on the early stages of psychosis which uses machine learning techniques to analyze imaging, clinical, cognitive, and biological data with the aim of facilitating the prediction of psychosis onset and outcome. In this article, we provide an overview of the PSYSCAN protocol and we discuss benefits and methodological challenges of large multicenter studies that employ neuroimaging measures