The preoperative consultation in rhinoplasty involves a multitude of actions that are mandatory for the decision-making process: history taking with attention to the symptoms and specific requests of the patient, clinical evaluation of the aesthetics, the functional status of the nose and the patients' motivation for surgery, and acquisition of standardized preoperative photographs. During the last decade, computer imaging or morphing of the preoperative pictures of the nose has become much more common. This part of the consultation allows the surgeon and patient to reach a mutually agreeable set of expectations by demonstrating the planned outcome of rhinoplasty and describing the objectives of surgery. The evolving literature on computer imaging supports that the benefits for both the patients and surgeons seem to outweigh the risks. Indeed, morphing enables the surgeon to precisely explain to the patients the goal of surgery, and to postpone or even cancel surgery in the group of patients that do not appear satisfied with the proposed changes. In addition, patients may feel more prepared for surgery and have a more realistic view of the outcome of the intervention. Presently, computer imaging is progressing from 2D to 3D models, optimizing the surgeons' capacity to perform morphing in the most advantageous manner for both parties. The current review provides a state-of-the art analysis on morphing in rhinoplasty, putting morphing into a historic and relevant perspective in clinical practice.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1055/s-0035-1570125 | DOI Listing |
Eur J Radiol
January 2025
Department of Radiology Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Neurodevelopment and Cognitive Disorders, China. Electronic address:
Objective: To explore the clinical value of combining split-bolus contrast injection with dual-energy CT(DECT) scanning technology in pediatric computed tomography urography (CTU) imaging.
Methods: A total of 128 children aged 0-17 years were prospectively selected and randomly assigned to three groups: A, B, and C. For Group A, a high-pitch flash mode was employed, where a single bolus of contrast agent was followed by four-phase scanning (noncontrast, cortex, medulla, and excretory phases).
J Med Internet Res
January 2025
Department of Neurology, West China Hospital, Sichuan University, Chengdu, China.
Background: Despite the increasing popularity of electronic devices, the longitudinal effects of daily prolonged electronic device usage on brain health and the aging process remain unclear.
Objective: The aim of this study was to investigate the impact of the daily use of mobile phones/computers on the brain structure and the risk of neurodegenerative diseases.
Methods: We used data from the UK Biobank, a longitudinal population-based cohort study, to analyze the impact of mobile phone use duration, weekly usage time, and playing computer games on the future brain structure and the future risk of various neurodegenerative diseases, including all-cause dementia (ACD), Alzheimer disease (AD), vascular dementia (VD), all-cause parkinsonism (ACP), and Parkinson disease (PD).
JMIR Med Inform
January 2025
Institute of History and Ethics in Medicine, School of Medicine and Health, Technical University of Munich, Munich, Germany.
Background: In data-sparse areas such as health care, computer scientists aim to leverage as much available information as possible to increase the accuracy of their machine learning models' outputs. As a standard, categorical data, such as patients' gender, socioeconomic status, or skin color, are used to train models in fusion with other data types, such as medical images and text-based medical information. However, the effects of including categorical data features for model training in such data-scarce areas are underexamined, particularly regarding models intended to serve individuals equitably in a diverse population.
View Article and Find Full Text PDFInvest Radiol
January 2025
From the Department of Radiology, Ulsan University Hospital, Ulsan, Republic of Korea (T.Y.L.); Department of Radiology, University of Ulsan College of Medicine, Seoul, Republic of Korea (T.Y.L.); Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea (J.H.Y., H.K., J.M.L.); Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea (J.H.Y., S.H.P., J.M.L.); Department of Radiology, Inje University Busan Paik Hospital, Busan, Republic of Korea (J.Y.P.); Department of Radiology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea (S.H.P.); Department of Radiology, Hanyang University College of Medicine, Seoul, Republic of Korea (C.L.); Division of Biostatistics, Medical Research Collaborating Center, Seoul National University Hospital, Seoul, Republic of Korea (Y.C.); and Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea (J.M.L.).
Objective: The aim of this study was to intraindividually compare the conspicuity of focal liver lesions (FLLs) between low- and ultra-low-dose computed tomography (CT) with deep learning reconstruction (DLR) and standard-dose CT with model-based iterative reconstruction (MBIR) from a single CT using dual-split scan in patients with suspected liver metastasis via a noninferiority design.
Materials And Methods: This prospective study enrolled participants who met the eligibility criteria at 2 tertiary hospitals in South Korea from June 2022 to January 2023. The criteria included (a) being aged between 20 and 85 years and (b) having suspected or known liver metastases.
PLoS One
January 2025
Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China.
Background: The relationships between pectoralis muscle parameters and outcomes in patients with coronavirus disease 2019 (COVID-19) remain uncertain.
Methods: We systematically searched PubMed, Embase, Web of Science and the Cochrane Library from 1 January 2019 to 1 May 2024 to identify non-overlapping studies evaluating pectoralis muscle-associated index on chest CT scan with clinical outcome in COVID-19 patients. Random-effects and fixed-effects meta-analyses were performed, and heterogeneity between studies was quantified using the I2 statistic.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!