The vital physiological role of the pituitary gland, alongside its proximity to critical neurovascular structures, means that pituitary adenomas can cause significant morbidity or mortality. While enormous advancements have been made in the surgical care of pituitary adenomas, numerous challenges remain, such as treatment failure and recurrence. To meet these clinical challenges, there has been an enormous expansion of novel medical technologies (eg, endoscopy, advanced imaging, artificial intelligence). These innovations have the potential to benefit each step of the patient's journey, and ultimately, drive improved outcomes. Earlier and more accurate diagnosis addresses this in part. Analysis of novel patient data sets, such as automated facial analysis or natural language processing of medical records holds potential in achieving an earlier diagnosis. After diagnosis, treatment decision-making and planning will benefit from radiomics and multimodal machine learning models. Surgical safety and effectiveness will be transformed by smart simulation methods for trainees. Next-generation imaging techniques and augmented reality will enhance surgical planning and intraoperative navigation. Similarly, surgical abilities will be augmented by the future operative armamentarium, including advanced optical devices, smart instruments, and surgical robotics. Intraoperative support to surgical team members will benefit from a data science approach, utilizing machine learning analysis of operative videos to improve patient safety and orientate team members to a common workflow. Postoperatively, neural networks leveraging multimodal datasets will allow early detection of individuals at risk of complications and assist in the prediction of treatment failure, thus supporting patient-specific discharge and monitoring protocols. While these advancements in pituitary surgery hold promise to enhance the quality of care, clinicians must be the gatekeepers of the translation of such technologies, ensuring systematic assessment of risk and benefit prior to clinical implementation. In doing so, the synergy between these innovations can be leveraged to drive improved outcomes for patients of the future.

中文翻译：

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垂体腺瘤手术治疗的当前和未来进展。

垂体的重要生理作用及其邻近关键的神经血管结构意味着垂体腺瘤可导致显着的发病率或死亡率。尽管垂体腺瘤的手术治疗取得了巨大进步，但仍然存在许多挑战，例如治疗失败和复发。为了应对这些临床挑战，新型医疗技术（例如内窥镜、先进成像、人工智能）得到了巨大的发展。这些创新有可能使患者的每一步受益，并最终改善结果。更早、更准确的诊断在一定程度上解决了这个问题。对新患者数据集的分析，例如自动面部分析或医疗记录的自然语言处理，有可能实现早期诊断。诊断后，治疗决策和计划将受益于放射组学和多模态机器学习模型。受训者的智能模拟方法将改变手术的安全性和有效性。下一代成像技术和增强现实将增强手术规划和术中导航。同样，未来的手术装备将增强手术能力，包括先进的光学设备、智能仪器和手术机器人。对手术团队成员的术中支持将受益于数据科学方法，利用手术视频的机器学习分析来提高患者安全并使团队成员适应共同的工作流程。术后，利用多模态数据集的神经网络将能够及早发现有并发症风险的个体，并协助预测治疗失败，从而支持患者特定的出院和监测方案。虽然垂体手术的这些进步有望提高护理质量，但临床医生必须成为此类技术转化的看门人，确保在临床实施之前对风险和收益进行系统评估。在此过程中，可以利用这些创新之间的协同作用来改善未来患者的治疗结果。