Seyed Farzad Maroufi, Yücel Doğruel, Ahmad Pour-Rashidi, Gurkirat S Kohli, Colson Tomberlin Parker, Tatsuya Uchida, Mohamed Z Asfour, Clara Martin, Mariagrazia Nizzola, Alessandro De Bonis, Mamdouh Tawfik-Helika, Amin Tavallai, Aaron A Cohen-Gadol, Paolo Palmisciano
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This scoping review comprehensively summarizes the current status of AI/ML technologies in pituitary adenoma surgery, highlighting their strengths and limitations.</p><p><strong>Methods: </strong>PubMed, Embase, Web of Science, and Scopus were searched following the PRISMA-ScR guidelines. Studies discussing the use of AI/ML in pituitary adenoma surgery were included. Eligible studies were grouped to analyze the different outcomes of interest of current AI/ML technologies.</p><p><strong>Results: </strong>Among the 2438 identified articles, 44 studies met the inclusion criteria, with a total of seventeen different algorithms utilized across all studies. Studies were divided into two groups based on their input type: clinicopathological and imaging input. The four main outcome variables evaluated in the studies included: outcome (remission, recurrence or progression, gross-total resection, vision improvement, and hormonal recovery), complications (CSF leak, readmission, hyponatremia, and hypopituitarism), cost, and adenoma-related factors (aggressiveness, consistency, and Ki-67 labeling) prediction. Three studies focusing on workflow analysis and real-time navigation were discussed separately.</p><p><strong>Conclusion: </strong>AI/ML modeling holds promise for improving pituitary adenoma surgery by enhancing preoperative planning and optimizing surgical strategies. However, addressing challenges such as algorithm selection, performance evaluation, data heterogeneity, and ethics is essential to establish robust and reliable ML models that can revolutionize neurosurgical practice and benefit patients.</p>","PeriodicalId":20202,"journal":{"name":"Pituitary","volume":null,"pages":null},"PeriodicalIF":3.3000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Current status of artificial intelligence technologies in pituitary adenoma surgery: a scoping review.\",\"authors\":\"Seyed Farzad Maroufi, Yücel Doğruel, Ahmad Pour-Rashidi, Gurkirat S Kohli, Colson Tomberlin Parker, Tatsuya Uchida, Mohamed Z Asfour, Clara Martin, Mariagrazia Nizzola, Alessandro De Bonis, Mamdouh Tawfik-Helika, Amin Tavallai, Aaron A Cohen-Gadol, Paolo Palmisciano\",\"doi\":\"10.1007/s11102-023-01369-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>Pituitary adenoma surgery is a complex procedure due to critical adjacent neurovascular structures, variations in size and extensions of the lesions, and potential hormonal imbalances. 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引用次数: 0
摘要
目的：垂体腺瘤手术是一项复杂的手术，因为邻近的神经血管结构非常重要，病变的大小和延伸范围各不相同，而且可能存在激素失衡。人工智能（AI）和机器学习（ML）的整合在协助神经外科医生决策、优化手术效果和提供实时反馈方面已显示出相当大的潜力。这篇范围综述全面总结了人工智能/ML技术在垂体腺瘤手术中的应用现状，强调了它们的优势和局限性：方法：按照 PRISMA-ScR 指南检索了 PubMed、Embase、Web of Science 和 Scopus。方法：按照PRISMA-ScR指南检索了PubM、Embed、Web Science和Scopus，纳入了讨论垂体腺瘤手术中AI/ML使用情况的研究。对符合条件的研究进行了分组，以分析当前人工智能/ML技术的不同结果：在已确定的 2438 篇文章中，有 44 项研究符合纳入标准，所有研究共使用了 17 种不同的算法。研究根据输入类型分为两组：临床病理输入和成像输入。研究评估的四个主要结果变量包括：结果（缓解、复发或进展、大体全切除、视力改善和激素恢复）、并发症（CSF 漏、再入院、低钠血症和垂体功能减退）、成本和腺瘤相关因素（侵袭性、一致性和 Ki-67 标记）预测。另外还讨论了三项关于工作流程分析和实时导航的研究：人工智能/ML建模有望通过加强术前规划和优化手术策略来改善垂体腺瘤手术。然而，要建立稳健可靠的 ML 模型，彻底改变神经外科实践并造福患者，解决算法选择、性能评估、数据异质性和伦理等挑战至关重要。
Current status of artificial intelligence technologies in pituitary adenoma surgery: a scoping review.
Purpose: Pituitary adenoma surgery is a complex procedure due to critical adjacent neurovascular structures, variations in size and extensions of the lesions, and potential hormonal imbalances. The integration of artificial intelligence (AI) and machine learning (ML) has demonstrated considerable potential in assisting neurosurgeons in decision-making, optimizing surgical outcomes, and providing real-time feedback. This scoping review comprehensively summarizes the current status of AI/ML technologies in pituitary adenoma surgery, highlighting their strengths and limitations.
Methods: PubMed, Embase, Web of Science, and Scopus were searched following the PRISMA-ScR guidelines. Studies discussing the use of AI/ML in pituitary adenoma surgery were included. Eligible studies were grouped to analyze the different outcomes of interest of current AI/ML technologies.
Results: Among the 2438 identified articles, 44 studies met the inclusion criteria, with a total of seventeen different algorithms utilized across all studies. Studies were divided into two groups based on their input type: clinicopathological and imaging input. The four main outcome variables evaluated in the studies included: outcome (remission, recurrence or progression, gross-total resection, vision improvement, and hormonal recovery), complications (CSF leak, readmission, hyponatremia, and hypopituitarism), cost, and adenoma-related factors (aggressiveness, consistency, and Ki-67 labeling) prediction. Three studies focusing on workflow analysis and real-time navigation were discussed separately.
Conclusion: AI/ML modeling holds promise for improving pituitary adenoma surgery by enhancing preoperative planning and optimizing surgical strategies. However, addressing challenges such as algorithm selection, performance evaluation, data heterogeneity, and ethics is essential to establish robust and reliable ML models that can revolutionize neurosurgical practice and benefit patients.
期刊介绍：
Pituitary is an international publication devoted to basic and clinical aspects of the pituitary gland. It is designed to publish original, high quality research in both basic and pituitary function as well as clinical pituitary disease.
The journal considers:
Biology of Pituitary Tumors
Mechanisms of Pituitary Hormone Secretion
Regulation of Pituitary Function
Prospective Clinical Studies of Pituitary Disease
Critical Basic and Clinical Reviews
Pituitary is directed at basic investigators, physiologists, clinical adult and pediatric endocrinologists, neurosurgeons and reproductive endocrinologists interested in the broad field of the pituitary and its disorders. The Editorial Board has been drawn from international experts in basic and clinical endocrinology. The journal offers a rapid turnaround time for review of manuscripts, and the high standard of the journal is maintained by a selective peer-review process which aims to publish only the highest quality manuscripts. Pituitary will foster the publication of creative scholarship as it pertains to the pituitary and will provide a forum for basic scientists and clinicians to publish their high quality pituitary-related work.
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