Inteligencia artificial en cirugía maxilofacial. ¿Futuro o presente?

Abstract

Artificial intelligence (AI) is today among the main driving forces in the field of medicine, with clear utility in the field of clinical diagnosis and with a role in improving the results obtained with the treatment of patients. Machine learning technology ("Machine learning" [ML]) arises from human capacities to feel, learn and reason 1 and is based on the training of logical algorithms by virtue of which machines make decisions in specific cases if we give them a series of general rules. AI applications are already very varied today, having been used to improve diagnostic processes, identify rare pathologies, as well as control results after treatments. In addition, the creation of databases with multiple records, thanks to the high data processing capacity of ML technology, can help us to detect the main prognostic indicators in a given entity. Without a doubt, the inclusion of elements derived from AI in healthcare is becoming more and more frequent. The main ones include: programs to improve communication with the patient, healthcare monitoring systems, drug development and, above all, in surgery, robotic systems to facilitate surgical intervention 2. Although these new technologies still have certain limitations in their application to the field of maxillofacial surgery, today's surgeon needs a correct understanding of their possibilities, limitations and future challenges. At the Mobile World Congress held in Barcelona last year, the first AI platform capable of remotely directing surgeries through connectivity with 5G technology (Advances in Surgery-TeleSurgeon platform) was presented. The system reliably reduces errors in the operating room, counting on the advice of the machine in the most critical phases of the process. These advances augur a very promising future, although it is not easy to predict when these systems will reach human capacity in the field of surgery; most predictions point to this happening in the early 2050s. One of the great applications of AI is based on its precision for the identification of radiographic alterations. These tools have already shown their usefulness in aspects of predicting results in dental implants with peri-implantitis problems 3. The operation of the ML is based on the interpretation of external data to achieve learning, achieving specific objectives and with the ability to adapt. The ability of machines to quickly analyze the data corresponding to tens of thousands of cases easily exceeds human possibilities, resulting in the detection of small changes in a radiographic study with the result of early detection of inflamma-tory pathologies in implantology. Other applications in the analysis of radiographic studies are related to the pathology of the temporomandibular joint. The automatic detection of cases with osteoarthritis based on cone beam computed tomography studies can provide important support to the clinician in the diagnosis and decision making for the management of patients in advanced stages of joint dysfunction (Figure 1) 4. Of special importance are ML systems in their application to the field of head and neck oncology. Aspects as important as the differentiation between ameloblastoma and other odontogenic lesions by virtue of panoramic radiology studies 5 or, as regards malignant lesions, the potential in terms of early diagnosis and prognostic prediction thanks to the sum and analysis of multiple variables. Additionally, computerized vision systems are used as surgical tools in the field of robotics and, with application at the present time, for guided resection by means of navigation systems pre-surgical analysis of the resection area, increasing safety in patient management and reducing human error (Figure 2). Editorial 053 Inteligencia artificial en cirugía maxilofacial. ¿Futuro o presente? Revisiones 056 Revisión sistemática de exactitud diagnóstica de la ultrasonografía en el trauma maxilofacial 063 El colgajo de músculo temporal en la cirugía de la ATM: ¿sigue siendo una opción válida? Casos clínicos 070 Planificación quirúrgica virtual en la reconstrucción de articulación temporomandibular con prótesis de stock tipo Walter-Lorenz 075 Planificación digital en tratamiento de fibroma osificante juvenil psamomatoide maxilar. Presentación de un caso 079 Alveolar soft part sarcoma of the tongue. A case report of a rare entity 083 Angiosarcoma metastásico de la cavidad oral: a propósito de un caso 087 Granuloma de células gigantes mandibular. Tratamiento de una recidiva y rehabilitación dental: presentación de un caso Artículo especial 092 Modelo de recertificación de las sociedades científico-médicas de España. FACME Volumen 44 / Número 2 2022 Abril / Junio Revista Española de Cirugía Oral y Maxilofacial