Artificial intelligence, regenerative surgery, robotics? What is realistic for the future of surgery?

Emerging molecules, tools, technology, and future of surgical knife in gastroenterology

The 21st century has started with several innovations in the medical sciences, with wide applications in health care management. This development has taken in the field of medicines (newer drugs/molecules), various tools and technology which has completely changed the patient management including abdominal surgery. Surgery for abdominal diseases has moved from maximally invasive to minimally invasive (laparoscopic and robotic) surgery. Some of the newer medicines have its impact on need for surgical intervention. This article focuses on the development of these emerging molecules, tools, and technology and their impact on present surgical form and its future effects on the surgical intervention in gastroenterological diseases.

Future regenerative medicine developments and their therapeutic applications

Although the currently available pharmacological assays can cure most pathological disorders, they have limited therapeutic value in relieving certain disorders like myocardial infarct, peripheral vascular disease, amputated limbs, or organ failure (e.g. renal failure). Pilot studies to overcome such problems using regenerative medicine (RM) delivered promising data. Comprehensive investigations of RM in zebrafish or reptilians are necessary for better understanding. However, the precise mechanisms remain poorly understood despite the tremendous amount of data obtained using the zebrafish model investigating the exact mechanisms behind their regenerative capability. Indeed, understanding such mechanisms and their application to humans can save millions of lives from dying due to potentially life-threatening events. Recent studies have launched a revolution in replacing damaged human organs via different approaches in the last few decades. The newly established branch of medicine (known as Regenerative Medicine aims to enhance natural repair mechanisms. This can be done through the application of several advanced broad-spectrum technologies such as organ transplantation, tissue engineering, and application of Scaffolds technology (support vascularization using an extracellular matrix), stem cell therapy, miRNA treatment, development of 3D mini-organs (organoids), and the construction of artificial tissues using nanomedicine and 3D bio-printers. Moreover, in the next few decades, revolutionary approaches in regenerative medicine will be applied based on artificial intelligence and wireless data exchange, soft intelligence biomaterials, nanorobotics, and even living robotics capable of self-repair. The present work presents a comprehensive overview that summarizes the new and future advances in the field of RM.

Augmented Reality-Based Surgery on the Human Cadaver Using a New Generation of Optical Head-Mounted Displays: Development and Feasibility Study

Background

Although nearly one-third of the world’s disease burden requires surgical care, only a small proportion of digital health applications are directly used in the surgical field. In the coming decades, the application of augmented reality (AR) with a new generation of optical-see-through head-mounted displays (OST-HMDs) like the HoloLens (Microsoft Corp) has the potential to bring digital health into the surgical field. However, for the application to be performed on a living person, proof of performance must first be provided due to regulatory requirements. In this regard, cadaver studies could provide initial evidence.

Objective

The goal of the research was to develop an open-source system for AR-based surgery on human cadavers using freely available technologies.

Methods

We tested our system using an easy-to-understand scenario in which fractured zygomatic arches of the face had to be repositioned with visual and auditory feedback to the investigators using a HoloLens. Results were verified with postoperative imaging and assessed in a blinded fashion by 2 investigators. The developed system and scenario were qualitatively evaluated by consensus interview and individual questionnaires.

Results

The development and implementation of our system was feasible and could be realized in the course of a cadaver study. The AR system was found helpful by the investigators for spatial perception in addition to the combination of visual as well as auditory feedback. The surgical end point could be determined metrically as well as by assessment.

Conclusions

The development and application of an AR-based surgical system using freely available technologies to perform OST-HMD–guided surgical procedures in cadavers is feasible. Cadaver studies are suitable for OST-HMD–guided interventions to measure a surgical end point and provide an initial data foundation for future clinical trials. The availability of free systems for researchers could be helpful for a possible translation process from digital health to AR-based surgery using OST-HMDs in the operating theater via cadaver studies.

Advancements of Artificial Intelligence in Liver-Associated Diseases and Surgery

Background and Objectives: The advancement of artificial intelligence (AI) based technologies in medicine is progressing rapidly, but the majority of its real-world applications has not been implemented. The establishment of an accurate diagnosis with treatment has now transitioned into an artificial intelligence era, which has continued to provide an amplified understanding of liver cancer as a disease and helped to proceed better with the method of procurement. This article focuses on reviewing the AI in liver-associated diseases and surgical procedures, highlighting its development, use, and related counterparts. Materials and Methods: We searched for articles regarding AI in liver-related ailments and surgery, using the keywords (mentioned below) on PubMed, Google Scholar, Scopus, MEDLINE, and Cochrane Library. Choosing only the common studies suggested by these libraries, we segregated the matter based on disease. Finally, we compiled the essence of these articles under the various sub-headings. Results: After thorough review of articles, it was observed that there was a surge in the occurrence of liver-related surgeries, diagnoses, and treatments. Parallelly, advanced computer technologies governed by AI continue to prove their efficacy in the accurate screening, analysis, prediction, treatment, and recuperation of liver-related cases. Conclusions: The continual developments and high-order precision of AI is expanding its roots in all directions of applications. Despite being novel and lacking research, AI has shown its intrinsic worth for procedures in liver surgery while providing enhanced healing opportunities and personalized treatment for liver surgery patients.

Current trends in three-dimensional visualization and real-time navigation as well as robot-assisted technologies in hepatobiliary surgery

With the continuous development of digital medicine, minimally invasive precision and safety have become the primary development trends in hepatobiliary surgery. Due to the specificity and complexity of hepatobiliary surgery, traditional preoperative imaging techniques such as computed tomography and magnetic resonance imaging cannot meet the need for identification of fine anatomical regions. Imaging-based three-dimensional (3D) reconstruction, virtual simulation of surgery and 3D printing optimize the surgical plan through preoperative assessment, improving the controllability and safety of intraoperative operations, and in difficult-to-reach areas of the posterior and superior liver, assistive robots reproduce the surgeon’s natural movements with stable cameras, reducing natural vibrations. Electromagnetic navigation in abdominal surgery solves the problem of conventional surgery still relying on direct visual observation or preoperative image assessment. We summarize and compare these recent trends in digital medical solutions for the future development and refinement of digital medicine in hepatobiliary surgery.

The role of artificial intelligence in healthcare: a structured literature review

BACKGROUND/INTRODUCTION

Artificial intelligence (AI) in the healthcare sector is receiving attention from researchers and health professionals. Few previous studies have investigated this topic from a multi-disciplinary perspective, including accounting, business and management, decision sciences and health professions.

METHODS

The structured literature review with its reliable and replicable research protocol allowed the researchers to extract 288 peer-reviewed papers from Scopus. The authors used qualitative and quantitative variables to analyse authors, journals, keywords, and collaboration networks among researchers. Additionally, the paper benefited from the Bibliometrix R software package.

RESULTS

The investigation showed that the literature in this field is emerging. It focuses on health services management, predictive medicine, patient data and diagnostics, and clinical decision-making. The United States, China, and the United Kingdom contributed the highest number of studies. Keyword analysis revealed that AI can support physicians in making a diagnosis, predicting the spread of diseases and customising treatment paths.

CONCLUSIONS

The literature reveals several AI applications for health services and a stream of research that has not fully been covered. For instance, AI projects require skills and data quality awareness for data-intensive analysis and knowledge-based management. Insights can help researchers and health professionals understand and address future research on AI in the healthcare field.

Radiomics and Machine Learning in Oral Healthcare

The increasing storage of information, data, and forms of knowledge has led to the development of new technologies that can help to accomplish complex tasks in different areas, such as in dentistry. In this context, the role of computational methods, such as radiomics and Artificial Intelligence (AI) applications, has been progressing remarkably for dentomaxillofacial radiology (DMFR). These tools bring new perspectives for diagnosis, classification, and prediction of oral diseases, treatment planning, and for the evaluation and prediction of outcomes, minimizing the possibilities of human errors. A comprehensive review of the state-of-the-art of using radiomics and machine learning (ML) for imaging in oral healthcare is presented in this paper. Although the number of published studies is still relatively low, the preliminary results are very promising and in a near future, an augmented dentomaxillofacial radiology (ADMFR) will combine the use of radiomics-based and AI-based analyses with the radiologist's evaluation. In addition to the opportunities and possibilities, some challenges and limitations have also been discussed for further investigations.

Target Eccentricity and Form Influences Disparity Vergence Eye Movements Responses: A Temporal and Dynamic Analysis

This study sought to investigate whether stimulation to the fovea or the parafovea with different color combinations influenced the temporal and dynamic features of 4° disparity vergence step responses. Twelve unique types of stimuli were displayed within a haploscope presented along the participant's midsagittal plane. Vergence eye movement responses from fifteen naïve participants were recorded using video-based infrared eye tracking instrumentation. Latency and peak velocity from left and right eye movement responses were quantified. Results show that the type of stimulus projection (foveal versus parafoveal) significantly (p<0.001) influences the vergence response latency but did not impact peak velocity. Vergence responses to eccentric circles with 6° eccentricity targeting the parafovea resulted in a significantly faster response latency compared to vergence responses to a cross with 2° eccentricity stimuli targeting the fovea. Results have implications for the stimulus design of a variety of applications from virtual reality to vision therapy interventions.

Target Eccentricity and Form Influences Disparity Vergence Eye Movements Responses: A Temporal and Dynamic Analysis

This study sought to investigate whether stimulation to the fovea or the parafovea with different color combinations influenced the temporal and dynamic features of 4° disparity vergence step responses. Twelve unique types of stimuli were displayed within a haploscope presented along the participant's midsagittal plane. Vergence eye movement responses from fifteen naïve participants were recorded using video-based infrared eye tracking instrumentation. Latency and peak velocity from left and right eye movement responses were quantified. Results show that the type of stimulus projection (foveal versus parafoveal) significantly (p<0.001) influences the vergence response latency but did not impact peak velocity. Vergence responses to eccentric circles with 6° eccentricity targeting the parafovea resulted in a significantly faster response latency compared to vergence responses to a cross with 2° eccentricity stimuli targeting the fovea. Results have implications for the stimulus design of a variety of applications from virtual reality to vision therapy interventions.