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Can artificial intelligence overtake human intelligence on the bumpy road towards glioma therapy?

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Abstract

Gliomas are one of the most devastating primary brain tumors which impose significant management challenges to the clinicians. The aggressive behaviour of gliomas is mainly attributed to their rapid proliferation, unravelled genomics and the blood–brain barrier which protects the tumor cells from chemotherapeutic regimens. Suspects of brain tumors are usually assessed by magnetic resonance imaging and computed tomography. These images allow surgeons to decide on the tumor grading, intra-operative pathology, feasibility of surgery, and treatment planning. All these data are compiled manually by physicians, wherein it takes time for the validation of results and concluding the treatment modality. In this context, the arrival of artificial intelligence in this era of personalized medicine, has proven promising performance in the diagnosis and management of gliomas. Starting from grading prediction till outcome evaluation, artificial intelligence-based forefronts have revolutionized oncological research. Interestingly, this approach has also been able to precisely differentiate tumor lesion from healthy tissues. However, till date, their utility in neuro-oncological field remains limited due to the issues pertaining to their reliability and transparency. Hence, to shed novel insights on the “clinical utility of this novel approach on glioma management” and to reveal “the black-boxes that have to be solved for fruitful application of artificial intelligence in neuro-oncology research”, we provide in this review, a succinct description of the potential gear of artificial intelligence-based avenues in glioma treatment and the barriers that impede their rapid implementation in neuro-oncology.

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Acknowledgement

We would like to thank the Faculty of Central Inter-Disciplinary Research Facility, Sri Balaji Vidyapeeth for giving us constant support in drafting this review article.

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This review did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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  1. Central Inter-Disciplinary Research Facility, School of Biological Sciences, Sri Balaji Vidyapeeth (Deemed to-be University), Pillaiyarkuppam, Puducherry, India

    Precilla S Daisy & T. S. Anitha

  2. Central Inter-Disciplinary Research Facility, School of Biological Sciences, Sri Balaji Vidyapeeth, Mahatma Gandhi Medical College and Research Institute Campus, Pillaiyarkuppam, Puducherry, 607403, India

    T. S. Anitha

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  1. Precilla S Daisy
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All the authors contributed equally to the conception and design of this review article. TSA: Conceptualization and Critical Evaluation of the work. PSD: Literature search and original draft preparation.

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Correspondence to T. S. Anitha.

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The authors Daisy Precilla S and Anitha T.S declare that they have no conflict of interest.

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Daisy, P.S., Anitha, T.S. Can artificial intelligence overtake human intelligence on the bumpy road towards glioma therapy?. Med Oncol 38, 53 (2021). https://doi.org/10.1007/s12032-021-01500-2

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