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| http://dx.doi.org/10.1136/thx.5.3.207 | DOI Listing |
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Feasibility of occlusal plane in predicting the changes in anteroposterior mandibular position: a comprehensive analysis using deep learning-based three-dimensional models.
BMC Oral Health
January 2025
Department of Stomatology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde, Foshan), Foshan, 528308, Guangdong, China.
Background: A comprehensive analysis of the occlusal plane (OP) inclination in predicting anteroposterior mandibular position (APMP) changes is still lacking. This study aimed to analyse the relationships between inclinations of different OPs and APMP metrics and explore the feasibility of OP inclination in predicting changes in APMP.
Methods: Overall, 115 three-dimensional (3D) models were reconstructed using deep learning-based cone-beam computed tomography (CBCT) segmentation, and their accuracy in supporting cusps was compared with that of intraoral scanning models.
The association between rapid antiretroviral therapy initiation and brain structure and function based on multimodal magnetic resonance imaging in HIV-positive men who have sex with men.
BMC Infect Dis
January 2025
Postgraduate Union Training Base of Jinzhou Medical University, PLA Rocket Force Characteristic Medical Center, Beijing, China.
An increasing number of treatment guidelines recommend rapid initiation of antiretroviral therapy (ART) after the diagnosis of human immunodeficiency virus (HIV) infection. However, data on the association between rapid ART initiation and alterations in brain structure and function remain limited in people with HIV (PWH). A cross-sectional analysis was conducted on HIV-positive men who have sex with men (MSM) undergoing ART.
View Article and Find Full Text PDFBiopsy location and tumor-associated macrophages in predicting malignant glioma recurrence using an in-silico model.
NPJ Syst Biol Appl
January 2025
Center for Interdisciplinary Digital Sciences (CIDS), Department Information Services and High-Performance Computing (ZIH), Dresden University of Technology, 01062, Dresden, Germany.
Predicting the biological behavior and time to recurrence (TTR) of high-grade diffuse gliomas (HGG) after maximum safe neurosurgical resection and combined radiation and chemotherapy plays a pivotal role in planning clinical follow-up, selecting potentially necessary second-line treatment and improving the quality of life for patients diagnosed with a malignant brain tumor. The current standard-of-care (SoC) for HGG includes follow-up neuroradiological imaging to detect recurrence as early as possible and relies on several clinical, neuropathological, and radiological prognostic factors, which have limited accuracy in predicting TTR. In this study, using an in-silico analysis, we aim to improve predictive power for TTR by considering the role of (i) prognostically relevant information available through diagnostics used in the current SoC, (ii) advanced image-based information not currently part of the standard diagnostic workup, such as tumor-normal tissue interface (edge) features and quantitative data specific to biopsy positions within the tumor, and (iii) information on tumor-associated macrophages.
View Article and Find Full Text PDFMulti-site, multi-vendor development and validation of a deep learning model for liver stiffness prediction using abdominal biparametric MRI.
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Imaging Research Center, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Background: Chronic liver disease (CLD) is a substantial cause of morbidity and mortality worldwide. Liver stiffness, as measured by MR elastography (MRE), is well-accepted as a surrogate marker of liver fibrosis.
Purpose: To develop and validate deep learning (DL) models for predicting MRE-derived liver stiffness using routine clinical non-contrast abdominal T1-weighted (T1w) and T2-weighted (T2w) data from multiple institutions/system manufacturers in pediatric and adult patients.
Decoding Periorbital Aging: A Multilayered Analysis of Anatomical Changes.
Aesthetic Plast Surg
January 2025
Division of Plastic and Maxillofacial Surgery, Department of Surgery, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
Background: Periorbital aging is a complex phenomenon that involves multiple layers of facial anatomy, including bone, fat, and globe. While previous studies have predominantly focused on age-related changes in facial fat compartments, this research aims to provide a comprehensive understanding of all periorbital components, including upper and lower orbital fat, orbital cavity volume, globe volume, and globe position, in the context of aging.
Methods: We conducted a retrospective study involving 118 patients (236 subjects) aged 18-99 years who underwent brain MRI using a 3 Tesla MR system.
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