Background: Three-dimensional (3D) imaging enhances surgical planning and documentation in plastic surgery, but high costs limit accessibility. Mobile Light Detection and Ranging (LiDAR) technology offers a potential cost-effective alternative.
Objectives: To evaluate the accuracy and clinical utility of iPhone-based LiDAR scanning for breast measurements compared to traditional methods, and to establish standardized protocols for clinical implementation.
Methods: In this prospective validation study, 25 consecutive patients (mean age: 44 years; range: 32-64 years; mean BMI: 23.2 kg/m²) undergoing breast procedures were evaluated using the "3D Scanner App" on iPhone 15 Pro (Apple Inc., Cupertino, CA). Three standardized measurements (sternal notch-to-nipple, nipple-to-midline, nipple-to-inframammary fold) were compared between LiDAR and manual techniques. Technical error of measurement (TEM) and relative TEM (rTEM) were calculated. Inter-rater reliability, learning curve assessment, and cost-effectiveness analysis were performed.
Results: LiDAR measurements showed very good accuracy for sternal notch-to-nipple (rTEM 1.43%, 95% CI: 1.21-1.65) and nipple-to-midline distances (rTEM 3.45%, 95% CI: 3.12-3.78). Nipple-to-inframammary fold measurements showed moderate accuracy (rTEM 8.80%, 95% CI: 8.21-9.39). Inter-rater reliability was excellent (ICC=0.92). Learning curve analysis demonstrated measurement stability after 5 cases. Cost analysis revealed 97.8% reduction in initial investment compared to commercial 3D imaging systems.
Conclusions: Mobile LiDAR technology provides accurate breast measurements for most anatomical landmarks at a fraction of the cost of traditional 3D imaging systems. The technology shows excellent reliability after a short learning curve, offering an accessible solution for surgical planning and documentation.
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http://dx.doi.org/10.1093/asj/sjae251 | DOI Listing |
Sci Rep
January 2025
Cardiovascular Research Center, Rajaie Cardiovascular, Medical, and Research Center, University of Medical Sciences, Tehran, Iran.
Assessing myocardial viability is crucial for managing ischemic heart disease. While late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) is the gold standard for viability evaluation, it has limitations, including contraindications in patients with renal dysfunction and lengthy scan times. This study investigates the potential of non-contrast CMR techniques-feature tracking strain analysis and T1/T2 mapping-combined with machine learning (ML) models, as an alternative to LGE-CMR for myocardial viability assessment.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Rheumatology and Immunology, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
Developing a new diagnostic prediction model for osteoarthritis (OA) to assess the likelihood of individuals developing OA is crucial for the timely identification of potential populations of OA. This allows for further diagnosis and intervention, which is significant for improving patient prognosis. Based on the NHANES for the periods of 2011-2012, 2013-2014, and 2015-2016, the study involved 11,366 participants, of whom 1,434 reported a diagnosis of OA.
View Article and Find Full Text PDFBMC Musculoskelet Disord
January 2025
Division of Orthopaedic Surgery, Department of Surgery, McMaster University, Hamilton, ON, Canada.
Background: To summarize the statistical performance of machine learning in predicting revision, secondary knee injury, or reoperations following anterior cruciate ligament reconstruction (ACLR), and to provide a general overview of the statistical performance of these models.
Methods: Three online databases (PubMed, MEDLINE, EMBASE) were searched from database inception to February 6, 2024, to identify literature on the use of machine learning to predict revision, secondary knee injury (e.g.
World Neurosurg
January 2025
Department of Neurology, The First People's Hospital of Jingzhou, The First Affiliated Hospital of Yangtze University, Jingzhou 434000, China. Electronic address:
Objective: This study was to explore the factors associated with prolonged hospital length of stay (LOS) in patients with intracranial aneurysms (IAs) undergoing endovascular interventional embolization and construct prediction model machine learning algorithms.
Methods: Employing a retrospective cohort study design, this study collected patients with ruptured IA who received endovascular treatment at Jingzhou First People's Hospital during the inclusion period from September 2022 to December 2023. The entire dataset was randomly split into training and testing dataset with a 7:3 ratio.
J Clin Neurosci
January 2025
Division of Neurosurgery, Department of Surgery, National University Hospital, National University Health System, Singapore.
Ventriculoperitoneal shunt (VPS) insertion is a neurosurgical procedure done routinely for managing hydrocephalus. However, the technique of shunt insertion remains controversial. In this study, we retrospectively compared the accuracy of shunt placement using ultrasound (US) guidance to freehand insertion.
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