The Use of Artificial Intelligence in Head and Neck Cancers: A Multidisciplinary Survey

Caterina Giannitto ^1,2, Giorgia Carnicelli ^1,2, Stefano Lusi ^1,2

¹Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, 20072 Milan, Italy.
²Department of Diagnostic and Interventional Radiology, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089 Milan, Italy.
³Department of Computer Science "Giovanni degli Antoni", University of Milan, Via Celoria 18, 20133 Milan, Italy.
⁴Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, 717 Potter Street, Berkeley, CA 94710, USA.
⁵Otorhinolaryngology Unit, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089 Milan, Italy.
⁶Department of Diagnostic Radiology, ASST Bergamo Ovest, 24047 Treviglio, Italy.
⁷Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia ASST Spedali Civili of Brescia, 25123 Brescia, Italy.
⁸Department of Radiotherapy and Radiosurgery IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089 Milan, Italy.
⁹Department of Biomedicine, Neuroscience and Advanced Diagnostics (BIND), University Hospital of Palermo, 90127 Palermo, Italy.
¹⁰Medical Oncology and Hematology Unit IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089 Milan, Italy.
¹¹Department of Neuroradiology, University Medical Center Mainz, 55131 Mainz, Germany.
¹²Radiology Unit, Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy.

⁰Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, 20072 Milan, Italy.

Journal of Personalized Medicine +

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April 27, 2024

View abstract on PubMed

Summary

Artificial intelligence (AI) is underutilized in head and neck (H&N) cancer care. While professionals see AI potential in diagnostics and planning, concerns about control and errors limit its adoption, necessitating wider implementation.

Area Of Science

Oncology
Medical Informatics
Radiology

Background

Artificial intelligence (AI) applications are expanding across disciplines but have seen limited adoption in head and neck (H&N) cancer care.
Multidisciplinary teams are crucial for comprehensive H&N cancer management, yet AI integration remains nascent.

Purpose Of The Study

To assess the current use of and attitudes towards AI among professionals involved in H&N cancer care.
To identify factors influencing AI adoption and perceived benefits and barriers in this field.

Main Methods

A web-based questionnaire was distributed to H&N cancer professionals from November 2020 to June 2022.
The survey collected data on AI usage, professional demographics, and attitudes towards AI.
139 professionals completed the survey, with data analyzed to determine predictors and perceptions of AI.

Main Results

Only 49.7% of respondents reported AI experience, with radiologists being the most frequent users (66.2%).
Primary specialty, academic qualification, and age were significant predictors of AI use.
Key perceived benefits included improved diagnostic accuracy (72%) and surgical planning (64.7%), while concerns included 'loss of control' (27.6%) and 'diagnostic errors' (57.0%).

Conclusions

There is limited engagement with AI in multidisciplinary H&N cancer care.
Further research and broader implementation strategies are needed to enhance AI acceptance and demonstrate its benefits in H&N oncology.

Keywords:

artificial intelligence diagnostic accuracy head and neck cancers multidisciplinary care survey