Purpose: The aim of this investigation was to evaluate the accuracy of various skeletal and dental cephalometric parameters as produced by different commercial providers that make use of artificial intelligence (AI)-assisted automated cephalometric analysis and to compare their quality to a gold standard established by orthodontic experts.
Methods: Twelve experienced orthodontic examiners pinpointed 15 radiographic landmarks on a total of 50 cephalometric X‑rays. The landmarks were used to generate 9 parameters for orthodontic treatment planning. The "humans' gold standard" was defined by calculating the median value of all 12 human assessments for each parameter, which in turn served as reference values for comparisons with results given by four different commercial providers of automated cephalometric analyses (DentaliQ.ortho [CellmatiQ GmbH, Hamburg, Germany], WebCeph [AssembleCircle Corp, Seongnam-si, Korea], AudaxCeph [Audax d.o.o., Ljubljana, Slovenia], CephX [Orca Dental AI, Herzliya, Israel]). Repeated measures analysis of variances (ANOVAs) were calculated and Bland-Altman plots were generated for comparisons.
Results: The results of the repeated measures ANOVAs indicated significant differences between the commercial providers' predictions and the humans' gold standard for all nine investigated parameters. However, the pairwise comparisons also demonstrate that there were major differences among the four commercial providers. While there were no significant mean differences between the values of DentaliQ.ortho and the humans' gold standard, the predictions of AudaxCeph showed significant deviations in seven out of nine parameters. Also, the Bland-Altman plots demonstrate that a reduced precision of AI predictions must be expected especially for values attributed to the inclination of the incisors.
Conclusion: Fully automated cephalometric analyses are promising in terms of timesaving and avoidance of individual human errors. At present, however, they should only be used under supervision of experienced clinicians.
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http://dx.doi.org/10.1007/s00056-023-00491-1 | DOI Listing |
J Transl Med
January 2025
Department of Laboratory Medicine, Seoul National University College of Medicine, 103, Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
Background: This study investigated the oral microbiome signatures associated with upper gastrointestinal (GI) and pancreaticobiliary cancers.
Methods: Saliva samples from cancer patients and age- and sex-matched healthy controls were analyzed using 16S rRNA-targeted sequencing, followed by comprehensive bioinformatics analysis.
Results: Significant dissimilarities in microbial composition were observed between cancer patients and controls across esophageal cancer (EC), gastric cancer (GC), biliary tract cancer (BC), and pancreatic cancer (PC) groups (R = 0.
BMJ Open Qual
January 2025
Rectorate, University of Health Sciences, Phnom Penh, Cambodia.
Rapid antigen diagnostic tests (Ag-RDTs) that quickly and accurately identify SARS-CoV-2 are an essential part of the COVID-19 response, but multiple factors can affect the validity of Ag-RDTs results. In Cambodia, several commercial Ag-RDTs have become available since the COVID-19 outbreak, but quality control (QC) and external quality assurance (EQA) of these rapid tests have yet to be fully and systematically implemented. We collaborated with laboratory experts in Australia and piloted an EQA programme of the commonly used COVID-19 Ag-RDTs at the University of Health Sciences' MERIEUX Laboratory (Tier 1 site-responsible for the in-country receipt and distribution of QA material) and four other participating laboratories (Tier 2-healthcare facility based) between November 2021 and November 2022.
View Article and Find Full Text PDFCrit Rev Oncol Hematol
January 2025
Department of Respiratory and Critical Care Medicine, Institute of Respiratory Health, State Key Laboratory of Respiratory Health and Multimorbidity, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Institute of Respiratory Health, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Precision Medicine Center, Precision Medicine Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, Sichuan, China. Electronic address:
Lung cancer is the leading cause of cancer-related mortality worldwide, highlighting the urgent need for more accurate and minimally invasive diagnostic tools to improve early detection and patient outcomes. While low-dose computed tomography (LDCT) is effective for screening in high-risk individuals, its high false-positive rate necessitates more precise diagnostic strategies. Liquid biopsy, particularly ctDNA methylation analysis, represents a promising alternative for non-invasive classification of indeterminate pulmonary nodules (IPNs).
View Article and Find Full Text PDFPhys Med Biol
January 2025
Department of Electrical and Electronic Engineering, The University of Hong Kong, Chow Yei Ching 506, Hong Kong, 999077, HONG KONG.
. The propagation speed of a shear wave, whether externally or internally induced, in biological tissues is directly linked to the tissue's stiffness. The group shear wave speed (SWS) can be estimated using a class of time-of-flight (TOF) methods in the time-domain or phase speed-based methods in the frequency domain.
View Article and Find Full Text PDFJ Transl Med
January 2025
Tumour Biology and Immunology Laboratory, Research Branch, Sidra Medicine, Doha, Qatar.
Background: FFPE tissue samples are commonly used in biomedical research and are a valuable source for next-generation sequencing in oncology, however, extracting RNA from these samples can be difficult the quantity and quality achieved can impact the downstream analysis. This study compared the effectiveness of seven different commercially available RNA extraction kits specifically designed for use with FFPE samples in terms of the quantity and quality of RNA recovered.
Methods: This study used 9 samples of FFPE tissue from three different types of tissue (Tonsil, Appendix and lymph node of B-cell lymphoma) to evaluate RNA extraction methods.
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