转化分子遗传学脊柱肿瘤学实验室
脊柱和神经肿瘤研究小组专注于了解潜在的机制, 脊柱和周围神经肿瘤的病理生理及危险因素. 我们还致力于开发和完善这些肿瘤的诊断工具和新的治疗范例.
早期检测, accurate diagnosis and evaluation of the effectiveness and safety of these therapies can lead to identifying the most effective treatment strategies, 改善预后,提高患者生活质量.
我们的主要研究领域之一是使用人工智能算法来:
- 开发新的预测工具, such as our clinical prediction calculators that use patient data to generate risk assessment scores or predictive models. 潜在的好处包括允许临床医生:
- 更好地理解某种干预的风险和收益
- 就治疗方案和手术方法做出明智的决定, 制定量身定制的治疗方案
- 预测个别患者的预后
- 与患者一起设定切合实际的期望
- 与患者分享决策,促进以患者为中心的护理
- Analyze patient medical imaging data to aid in interpretation and informed decision-making regarding diagnosis and treatment. 这些系统可以提供基于证据的建议, suggest appropriate treatment options or help in surgical planning based on the patient’s condition and medical history.
主要研究者
临床研究项目
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肿瘤学:对在脊柱和周围神经中生长的肿瘤的研究, 包括神经鞘瘤, 神经纤维瘤, 脑膜瘤, 脊索瘤, 肉瘤, 室管膜瘤, 和星形细胞瘤, 等, 是我们实验室的关键努力吗. 除了在约翰·霍普金斯医学院对患有此类肿瘤的患者进行跟踪研究之外, we work in a multidisciplinary fashion with multiple national and international institutions better understand these pathologies. 这些项目旨在增进我们对这些肿瘤的了解, 改进诊断方法, 探索治疗方案, 并最终改善推荐十大正规网赌平台的治疗效果. 这个项目包括研究各种成像技术, 比如核磁共振和CT扫描, 识别有助于准确检测肿瘤的成像特征, 本地化, 和表征. 另外, our team explores the utility of molecular and genetic markers that could serve as diagnostic biomarkers for these tumors. Our research also focuses on evaluating and optimizing treatment options for these tumors and identifying the prognostic factors associated with disease progression, 递归式, 或者对特定疗法有良好的反应. 这包括调查手术技术, 放射治疗, 化疗, 靶向治疗, 以及新兴的治疗方式,比如免疫疗法. Such information aids in developing predictive models and personalized treatment plans tailored to individual patients.
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1型神经纤维瘤病(NF1), 2型神经纤维瘤病(NF2), and Schwannomatosis (SWN) are three related but clinically distinct tumor syndromes with a shared predisposition to develop peripheral and central nervous system tumors. NF1的疾病表达及并发症, NF2, 和SWN变化很大, 需要多学科的方法来护理和优化结果. 在我们的实验室, 我们对这些症状的患者进行随访以评估其临床特征, 诊断检查, 管理策略, NF和SWN的预后. 除了, 该项目包括使用来自国家医疗数据库的大数据, 里面有大量的推荐十大正规网赌平台健康记录, 诊断信息, 治疗结果, 为研究提供了巨大的潜力, 分析, 改善医疗服务. 通过了解这些肿瘤综合征的细微差别, 医生可以为个别推荐十大正规网赌平台量身定制治疗计划和干预措施, 结果改善了结果,降低了发病率. 而对于有症状的或正在生长的肿瘤,可以考虑手术治疗, it is not always the first-line treatment due to the potential risk of nerve damage and the high likelihood of tumor 递归式. 因此, we aim to investigate the post-surgical clinical outcomes and their predictors among patients with NF or SWN.
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Advances in smartphone technology have enabled us to passively collect movement and activity data to better understand patients’ preoperative and postoperative functions. 创造这种数字表型, 除了经过验证的患者报告的结果测量, lets us better evaluate patient function and 生活质量 to determine the optimal treatments for different pathologies.
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Artificial intelligence (AI) algorithms are rapidly being developed for the automated reading of medical images. The AI algorithms can automatically recognize complex patterns in imaging data and provide quantitative assessments of radiographic characteristics. 人工智能已经很容易地融入了许多医学领域, 包括在肺癌筛查中识别结节和评估脑肿瘤. 我们希望将人工智能算法扩展到各种脊柱疾病, 包括创伤, 退化性疾病, 感染, 和癌症. 我们收集放射图像来训练机器学习(ML)模型来识别脊柱病理. This may ultimately obviate certain diagnostic interventions and expedite treatments to improve patient satisfaction and outcomes.
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脊柱肿瘤患者非常虚弱, 脊柱肿瘤切除手术有许多并发症, 包括出血, 静脉血栓栓塞, 非常规排放, 逗留时间延长, 伤口感染, 和再次手术. We are working on identifying the risk factors and predictors associated with these adverse events and thereby developing predictive calculators that can be used as comprehensive tools by surgeons to estimate the potential risk of each of their patients. 这些专门的工具将有助于改善患者的讨论, 导致更准确的期望, 并潜在地确定有助于加快和加强术后护理的途径.
相关研究论文:
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Optimal patient selection can reduce postoperative 并发症 and mitigate the high costs of spine surgery. 因此, 我们的实验室正在开发预测工具来提高手术的价值, 最大化利益, 最小化成本. 这些工具是根据手术类型而个性化的, 它们可以在床边用来评估推荐十大正规网赌平台的具体术后结果, 生活质量, 以及根据患者复杂的临床表现而产生不良后果的可能性. These prediction models enable spine surgeons to provide their patients with personalized expectations regarding the clinical outcomes, 并发症, 不利的结果, 以及脊柱手术后的住院时间.
相关研究论文:
- Preoperative nomograms predict patient-specific cervical spine surgery clinical and 生活质量 outcomes
- 腰椎手术后临床和生活质量预后的患者特异性预测模型
- 预测计算器的非常规出院和脊柱手术后的住院时间
- 基于网络的计算器预测胸腰椎手术后手术部位感染
- Incidental durotomy: predictive risk model and external validation of natural language process identification algorithm
- A novel predictive model of intraoperative blood loss in patients undergoing elective lumbar surgery for degenerative pathologies
- 新风险计算方法用于成人颅尖部畸形枕下减压
- Prediction of 生活质量 improvements in patients with lumbar stenosis following use of membrane stabilizing agents
- The F2RaD score: A novel prediction score and calculator tool to identify patients at risk of postoperative C5 palsy
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Postoperative C5 and C6 nerve root palsy is an adverse outcome after posterior cervical decompression and fusion surgery. 其特征是三角肌和/或二头肌麻痹, 伴有异常感觉症状和肩部疼痛. 因此, 这种术后并发症会对患者的生活质量产生负面影响,并增加医疗保健费用. 在我们的实验室, 我们正在调查C5麻痹的危险因素,并确定这种并发症的病因. 我们也在研究影响C5麻痹后恢复时间和几率的因素, 还有治疗方法. This project aims to provide spine surgeons with landmarks for better patient counseling about postoperative C5 palsy occurrence risk and recovery and potential treatment options.
相关研究论文:
- The F2RaD score: A novel prediction score and calculator tool to identify patients at risk of postoperative C5 palsy
- 术后C5麻痹严重程度预测恢复时间
- Spinal cord float back is not an independent predictor of postoperative C5 palsy in patients undergoing posterior cervical decompression
- 术前临床和影像学变量预测术后C5麻痹
- 颈椎术后C5麻痹:59例多中心回顾性分析
- 颈椎后路减压融合术后C5麻痹:成本和生活质量影响
- 通过术前解剖测量预测C5麻痹
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良好的骨骼质量是避免脊柱手术后骨折和硬件问题的关键. 而DEXA筛查是目前评估骨矿物质密度的方法, many patients do not have DEXA measurements before surgical instrumentation creating a barrier for this evaluation. 在这个项目中, we developed and evaluated a simple tool that estimates the Vertebral Bone Quality (VBQ) based on magnetic resonance imaging (MRI). This tool significantly differentiates between healthy versus osteopenic/osteoporotic bones in both patients with degenerative disease as well as in the cancer population.
相关研究论文: