We report initial surgical planning computed tomographic protocols for composite tissue allotransplantation of the face. This complex procedure replaces missing facial structures with anatomically identical tissues, restoring form and function. Achieved results are superior to those accomplished with conventional techniques. As a growing number of patients/recipients have undergone multiple reconstructions, vascular imaging plays an increasingly critical role in surgical planning and successful execution of the operation.
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http://dx.doi.org/10.1097/RCT.0b013e3181e9c133 | DOI Listing |
J Neurol Sci
January 2025
Department of Neurological Surgery, Thomas Jefferson University Hospital, Philadelphia, PA, USA. Electronic address:
Background: Craniocervical junction dural arteriovenous fistulas (CCJ-DAVFs) are rare and complex vascular malformations that are challenging to diagnose and treat. This study aims to compare surgical and endovascular treatments for CCJ-DAVFs through a systematic review and meta-analysis.
Methods: A systematic review and meta-analysis was conducted according to the PRISMA guidelines.
J Cardiovasc Pharmacol
January 2025
Maria Cecilia Hospital, GVM Care & Research, Cotignola, Italy.
Patient-reported outcome measures (PROMs) are vital tools in cardiovascular disease (CVD) research and care, providing insights that complement traditional clinical outcomes like mortality and morbidity. PROMs capture patient experiences with CVD, such as quality of life, functional capacity, and emotional well-being, allowing clinicians to assess how interventions impact daily life. PROMs are integral to cardiovascular investigations as well as management, especially in chronic conditions and rehabilitation, where they inform on the impact of personalized care plans by tracking symptom progression and patient adherence.
View Article and Find Full Text PDFRadiographics
February 2025
From the Department of Radiology, Nihon University School of Dentistry at Matsudo, 2-870-1 Sakaecho-Nishi, Matsudo, Chiba 271-8587, Japan (K.I., K.O., T.K.); Department of Diagnostic Radiology, National Cancer Center Hospital East, Chiba, Japan (H.K.); Department of Radiology, VA Boston Health Care System, Boston, Mass (V.C.A.A.); and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (O.S.).
Various new dental treatment methods have been introduced in dental clinics, and many new materials have been used in recent years for dental treatments. Dentistry is divided into several specialties, each offering unique treatments, such as endodontics, implantology, oral surgery, and orthodontics. CT and MR images after dental treatment reveal a variety of hard- and soft-tissue changes and dental materials, which often cause image artifacts.
View Article and Find Full Text PDFMethods Protoc
January 2025
Medical Faculty Heidelberg, Department of Anesthesiology, Heidelberg University, 69120 Heidelberg, Germany.
Background: Advanced airway management is of fundamental importance in almost all areas of anesthesiology, emergency medicine, and critical care. Securing the airway is of the utmost importance, as this is a prerequisite for the oxygenation of the human organism. The clinical relevance of airway management is particularly evident in the fact that the primary cause of significant anesthesia-related complications can be attributed to this field.
View Article and Find Full Text PDFEur J Obstet Gynecol Reprod Biol X
March 2025
Mother and Newborn Health Research Center, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
This review examines the emerging applications of machine learning (ML) and radiomics in the diagnosis and prediction of placenta accreta spectrum (PAS) disorders, addressing a significant challenge in obstetric care. It highlights recent advancements in ML algorithms and radiomic techniques that utilize medical imaging modalities like magnetic resonance imaging (MRI) and ultrasound for effective classification and risk stratification of PAS. The review discusses the efficacy of various deep learning models, such as nnU-Net and DenseNet-PAS, which have demonstrated superior performance over traditional diagnostic methods through high AUC scores.
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