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Erschienen in:

06.01.2024

Current status of artificial intelligence technologies in pituitary adenoma surgery: a scoping review

verfasst von: 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

Erschienen in: Pituitary | Ausgabe 2/2024

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Abstract

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.

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Titel: Current status of artificial intelligence technologies in pituitary adenoma surgery: a scoping review
verfasst von: 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
Publikationsdatum: 06.01.2024
Verlag: Springer US
Erschienen in: Pituitary / Ausgabe 2/2024
Print ISSN: 1386-341X
Elektronische ISSN: 1573-7403
DOI: https://doi.org/10.1007/s11102-023-01369-6

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