Craniosynostosis, a medical condition characterized by premature fusion of one or multiple cranial sutures, has historically been treated through surgical correction. Computerized Surgical Planning (CSP) and three-dimensional (3D) modeling have gained significant popularity across craniofacial surgery. Through a collaborative effort between surgeons and engineers, it is now possible to virtually execute a surgical plan based on preoperative imaging using computed tomography scans. The CSP workflow involves several elements including virtual 3D modeling, CSP computer-aided surgical guide design, manufacturing of guides and templates, and intraoperative implementation. Through the gradual optimization of this workflow, it has been possible to achieve significant progress in the surgical process including improvements in the preoperative planning of complex craniosynostosis cases and reduction of intraoperative time. Furthermore, CSP and 3D modeling have had a positive impact on surgical simulation and residency training, along with patient education and counseling. This article summarizes the CSP workflow in the treatment of craniosynostosis and the implications of this treatment modality on medical trainee education and patient management.
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http://dx.doi.org/10.1055/s-0044-1786803 | DOI Listing |
JACC Case Rep
December 2024
Tel Aviv University, Tel Aviv, Israel.
We present 2 cases of caseous mitral annulus calcification (MAC) in which one patient was asymptomatic whereas the second experienced left hemianopsia. Both patients underwent transthoracic and transesophageal echocardiography exams which revealed severe MAC with a mass consistent with caseous MAC. A mobile component of the caseous MAC was observed in the patient with left hemianopsia.
View Article and Find Full Text PDFTunis Med
January 2025
Department of urology, Fattouma Bourguiba Hospital, Monastir,Tunisia.
Introduction: Varicocele has a detrimental effect on testicular growth and spermatogenesis, hence the importance of its management. This management remains controversial among Tunisian urologists; diagnostic and therapeutic choices tend to vary from one urologist to another.
Aim: The aim of this survey is to evaluate the practices of Tunisian urologists regarding varicocele management compared to the latest international guidelines.
BMC Oral Health
January 2025
Sub-Institute of Public Safety Standardization, China National Institute of Standardization, No.4 Zhichun Road, Haidian District, Beijing, 100191, PR China.
Background: This study aimed to establish a model for predicting the difficulty of mandibular third molar extraction based on a Bayesian network to meet following requirements: (1) analyse the interaction of the primary risk factors; (2) output quantitative difficulty-evaluation results based on the patient's personal situation; and (3) identify key surgical points and propose surgical protocols to decrease complications.
Methods: Relevant articles were searched to identify risk factors. Clinical knowledge and experience were used to analyse the risk factors to establish the Bayesian network.
Diabetes Obes Metab
January 2025
Department of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, People's Republic of China.
Background: The body weight following bariatric surgery is a primary concern for both healthcare professionals and surgical candidates. However, it remains unclear whether variations in preoperative fat distribution influence weight loss outcomes.
Objective: The aim of this study was to evaluate the effect of abdominal fat distribution on postoperative weight loss and body mass index (BMI) reduction, and to clarify the role of different fat depots in weight loss outcomes.
BMJ Open Gastroenterol
January 2025
Histopathology, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK.
Objective: Artificial intelligence (AI) tools for histological diagnosis offer great potential to healthcare, yet failure to understand their clinical context is delaying adoption. IGUANA (Interpretable Gland-Graphs using a Neural Aggregator) is an AI algorithm that can effectively classify colonic biopsies into normal versus abnormal categories, designed to automatically report normal cases. We performed a retrospective pathological and clinical review of the errors made by IGUANA.
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