Objective: To compare the waist-to-height ratio (WHtR) agreement between synthetic data and the Smart Computerized Anthropometric NavigatioN and Evaluation Resource (SCANNER) software package.
Methods: One hundred and ten 3D digital humans (55 for each sex) were created to obtain synthetic values. WHtR was obtained through the waist circumference and height division, both in centimeters. These data were programmed and obtained directly from the synthetic models. SCANNER v0.01 was coded by the researchers using Matlab. Differences between the objective WHtR and the one the SCANNER software package estimated were quantified using standard errors, Spearman's correlation and the Bland-Altman plot.
Results: Using the Spearman correlation, an agreement level of 0.982 was identified. Using the Bland-Altman plot, the agreement level was high, with a Rho value of 0.983 (95% CI: 0.977-0.988). Finally, when the standard errors were quantified, there was an overall error (between the synthetic data created and the computed one) of 0.49%, being higher in men (0.81%) than in women (0.18%).
Conclusions: The SCANNER software package is a straightforward tool that could facilitate the estimation of WHtR in distance participants or patients.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.nut.2024.112499 | DOI Listing |
Int J Legal Med
January 2025
Unit of Forensic Medicine, Department of Diagnostics and Public Health, University of Verona, Verona, Italy.
Pathology has benefited from the rapid progress of image-digitizing technology during the last decade. However, the application of digital whole slide images (WSI) in forensic pathology still needs to be improved. WSI validation is crucial to ensure diagnostic performance, at least equivalent to glass slides and light microscopy.
View Article and Find Full Text PDFRadiol Adv
January 2025
Department of Radiology, Duke University Medical Center, Durham, NC 27710, United States.
Purpose: To assess agreement between CT volumetry change classifications derived from Quantitative Imaging Biomarker Alliance Profile cut-points (ie, QIBA CTvol classifications) and the Response Evaluation Criteria in Solid Tumors (RECIST) categories.
Materials And Methods: Target lesions in lung, liver, and lymph nodes were randomly chosen from patients in 10 historical clinical trials for various cancers, ensuring a balanced representation of lesion types, diameter ranges described in the QIBA Profile, and variations in change magnitudes. Three radiologists independently segmented these lesions at baseline and follow-up scans using 2 software tools.
Clin Neuroradiol
January 2025
Department of Radiology and Neuroradiology, University Hospital of Schleswig-Holstein, Arnold-Heller-Str. 3, Hs D (Neurozentrum), 24105, Kiel, Germany.
Purpose: Magnetic Resonance Imaging based brain segmentation and volumetry has become an important tool in clinical routine and research. However the impact of the used hardware is only barely investigated. This study aims to assess the influence of scanner manufacturer, field strength and head-coil on volumetry results.
View Article and Find Full Text PDFEJNMMI Phys
January 2025
Department of Nuclear Medicine, Rambam Health Care Campus, P.O.B. 9602, 3109601, Haifa, Israel.
Background: A recently released digital solid-state positron emission tomography/x-ray CT (PET/CT) scanner with bismuth germanate (BGO) scintillators provides an artificial intelligence (AI) based system for automatic patient positioning. The efficacy of this digital-BGO system in patient placement at the isocenter and its impact on image quality and radiation exposure was evaluated.
Method: The digital-BGO PET/CT with AI-based auto-positioning was compared (χ, Mann-Whitney tests) to a solid-state lutetium-yttrium oxyorthosilicate (digital-LYSO) PET/CT with manual patient positioning (n = 432 and 343 studies each, respectively), with results split into groups before and after the date of a recalibration of the digital-BGO auto-positioning camera.
J Esthet Restor Dent
January 2025
Department of Restorative Dentistry, University of Washington; Founder and Director, Kois Center, Seattle, Wash; and Private Practice, Seattle, WA, USA.
Objectives: The different scanning errors that can be caused by the operator handling an intraoral scanner (IOS) or the intraoral conditions of the patient being scanned have not been described. The purpose of this review was to describe and classify the scanning errors that can be identified in digital scans recorded by using IOSs.
Overview: The identification of scanning errors in an intraoral scan and understanding the cause of these scanning errors are fundamental procedures for successfully handling an IOS and integrating these digital data acquisition technologies in dental practices.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!