Annals of translational medicine最新文献

Background: Robotic assistance has become increasingly prevalent in spinal surgery in recent years, emerging as a tool to increase accuracy and precision and lower complication rates and radiation exposure. The 7^th and 8^th Annual Seattle Science Foundation (SSF) Robotics Courses showcased presentations and demonstrations from some of the field's most experiences leaders on latest topics in robotics and spinal surgery, including cutting-edge preoperative planning technologies, augmented reality (AR) in the operating room, cervical fusion with transpedicular screws, and neuro-oncologic management. We provide a scoping review of the use of robotics technology in spinal surgery featuring highlights from the 7^th and 8^th Annual SSF Robotics Courses.

Methods: A scoping review of the literature was conducted (last search conducted in July 2024). Key search terms included "robotic assistance", "spine surgery", and "robotic technology" on the PubMed database. Additionally, highlights are included from the 7^th and 8^th Annual SSF Robotics Courses.

Results: Applications of navigation robotics span subspecialties of spine surgery including deformity correction, minimally invasive approaches, lateral single position operations, spinal oncology, and cervical fusion. Tips on overcoming traditional obstacles of robotics integration such as streamlining staff workflow and adoption while financing robotic-assisted technology are shared. Future directions of robotics enhanced with AR may further guide surgeon decision-making, assist in more practical fashion intraoperatively, and optimize patient outcomes.

Conclusions: While improved precision and accuracy, less radiation, and standardization of procedures represent current advantages of robotic-assistance across spine surgery, robotics in spine surgery will usher more transformative changes to patient care and operative skill in coming years.

[This corrects the article DOI: 10.21037/atm-22-2672.].

Background and objective: Lipedema is a commonly underdiagnosed chronic condition. This study aimed to evaluate liposuction techniques for lipedema by conducting a systematic review and presenting our experience. A case series study and a comprehensive review were conducted.

Methods: We assessed surgical outcomes among patients with lipedema who underwent liposuction. Descriptive and inferential statistics were implemented. In our case series, we used tumescent liposuction, vibration amplification of sound energy at resonance (VASER) liposuction, and waterjet-assisted liposuction (WAL). We also performed a literature review of current concepts and state-of-the-art treatment for lipedema.

Key content and findings: Twenty-four female patients were included in this study with a median age of 37 years [interquartile range (IQR), 10 years]. A statistically significant difference between preoperative (29.65 kg/m²) and postoperative body mass index (BMI) (26.95 kg/m²; P<0.05) of patients was evidenced. The amount of total fat removal between surgical techniques was statistically different (P<0.001). A statistically significant difference in the amount of total fat removal between surgical techniques was found (P=0.0015). Post-hoc analysis with Dunn's test evidenced a significant difference only between tumescent suction-assisted lipectomy and WAL (P<0.001). Nineteen studies were included in this review. Low complication rates, improvement in patient-reported outcomes, and reduction in conservative therapy requirements were found when evaluating multiple studies in this review.

Conclusions: Liposuction has been shown to be a safe and effective alternative in patients with lipedema. It positively impacts clinical and patient-reported outcomes.

[This corrects the article DOI: 10.21037/atm-20-8093.].

[This corrects the article DOI: 10.21037/atm-22-2043.].

Background and objective: Sarcopenia, characterized by the progressive loss of skeletal muscle mass (MM) and muscle function, is a common and debilitating condition in cancer patients, significantly impacting their quality of life, treatment outcomes, and overall survival. The pathophysiology of sarcopenia is multifactorial, involving metabolic, hormonal, and inflammatory changes. Recent research highlights the role of chronic inflammation in the development and progression of sarcopenia, with pro-inflammatory cytokines being key mediators of muscle catabolism. The primary objective of this study was to assess the role of pro-inflammatory cytokines in identifying sarcopenia among cancer patients. As a secondary objective, we aim to investigate whether the methods used for assessing sarcopenia, both imaging and functional, align with established guidelines.

Methods: A search of the Web of Science was conducted for English-language articles published since 2005, with the following terms: "Cancer" AND "Sarcopenia" AND "Pro-inflammatory cytokine*" OR "Interleukin*". Inclusion criteria included peer-reviewed controlled trials, observational studies, case reports, and case series. To avoid redundancy, articles with results which were included in systematic reviews, narrative reviews, or scoping reviews were excluded from this review.

Key content and findings: The analysis of 10 selected papers, including 1,138 cancer patients, revealed a lack of assessment of muscle strength (MS) and muscle functional performance in most of the studies on sarcopenia, contradicting the comprehensive nature of sarcopenia that includes MM, MS, and muscle functionality. There is no standardization of pro-inflammatory mediators for sarcopenia identification.

Conclusions: Future research should focus on establishing cutoff points for inflammatory mediators and identifying which cytokines are linked to sarcopenia. Given the complexity of sarcopenia in different cancers, new projects should investigate whether cytokine expression depends on the tumor type. Moreover, considering that the majority of the study population comprised elderly individuals with primary sarcopenia, it is crucial to discern the extent to which the findings are influenced by age versus cancer-related factors.

Background and objective: Patients with thoracic aortic aneurysm and dissection (TAAD) are often asymptomatic but present acutely with life threatening complications that necessitate emergency intervention. Aortic diameter measurement using computed tomography (CT) is considered the gold standard for diagnosis, surgical planning, and monitoring. However, manual measurement can create challenges in clinical workflows due to its time-consuming, labour-intensive nature and susceptibility to human error. With advancements in artificial intelligence (AI), several models have emerged in recent years for automated aortic diameter measurement. This article aims to review the performance and clinical relevance of these models in relation to clinical workflows.

Methods: We performed literature searches in PubMed, Scopus, and Web of Science to identify relevant studies published between 2014 and 2024, with the focus on AI and deep learning aortic diameter measurements in screening and diagnosis of TAAD.

Key content and findings: Twenty-four studies were retrieved in the past ten years, highlighting a significant knowledge gap in the field of translational medicine. The discussion included an overview of AI-powered models for aortic diameter measurement, as well as current clinical guidelines and workflows.

Conclusions: This article provides a thorough overview of AI and deep learning models designed for automatic aortic diameter measurement in the screening and diagnosis of thoracic aortic aneurysms (TAAs). We emphasize not only the performance of these technologies but also their clinical significance in enabling timely interventions for high-risk patients. Looking ahead, we envision a future where AI and deep learning-powered automatic aortic diameter measurement models will streamline TAAD clinical management.