Table of Contents
Introduction
The Global AI in Endoscopy Market is projected to expand dramatically from USD 58.1 million in 2023 to USD 838.9 million by 2033, achieving a compound annual growth rate (CAGR) of 30.6% throughout the forecast period from 2024 to 2033. This surge is underpinned by multiple drivers aimed at improving diagnostics and treatment in gastroenterology. Enhanced diagnostic accuracy is a critical factor, as AI integration helps pinpoint and characterize gastrointestinal anomalies, including cancers. Machine learning algorithms are increasingly employed to scrutinize endoscopic images, enabling the detection of subtle lesions that might evade manual observation, thereby boosting diagnostic precision and supporting immediate decision-making during procedures.
Operational efficiency is another significant growth driver in the AI in Endoscopy market. AI’s role in facilitating quicker adjustments of endoscopic tools and navigating through procedures helps shorten operation times and potentially reduces costs at healthcare facilities. Moreover, AI’s capability in processing extensive datasets of patient histories and endoscopic images promotes the use of predictive analytics. This application forecasts potential patient outcomes and disease recurrence probabilities, assisting in the creation of personalized treatment strategies and enhancing patient care management.
AI is also revolutionizing education and training within the field. AI-powered simulations and training platforms are offering new learning opportunities for gastroenterologists and endoscopic surgeons. These advanced tools simulate a variety of clinical conditions, providing practitioners with invaluable hands-on experience in a risk-free environment. Furthermore, AI enhances collaboration among medical professionals by integrating disparate data types — like radiologic and histologic data — into a unified platform, which enhances comprehensive patient evaluations and supports multidisciplinary discussions.
Recent advancements and approvals highlight the market’s dynamic nature. For instance, in January 2023, AnX Robotica gained FDA de novo clearance for its AI-assisted tool, NaviCam ProScan, which utilizes convolutional neural networks to differentiate between normal and abnormal tissues in diverse images. Additionally, in February 2023, AI MedTech company Waycen announced a strategic sales partnership with MegaMind, a major health sector player in the Middle East. This deal involves distributing Waycen’s AI solutions across the region, further demonstrating the market’s expanding reach and the increasing trust in AI technologies to enhance healthcare outcomes. These developments underscore the robust growth trajectory of AI applications in endoscopy, supported by continuous technological innovations.
Key Takeaways
- The global AI in endoscopy market is projected to witness significant growth, with a CAGR of 30.6% from 2024 to 2033.
- Revenue in the AI in endoscopy market is anticipated to increase from USD 58.1 million in 2023 to approximately USD 838.9 million by 2033.
- Gastrointestinal Endoscopy accounted for the largest revenue share among the types of endoscopy, capturing 32.4% of the market.
- Hospitals constituted the dominant end-user segment, commanding 58.2% of the market share.
- CADx (Computer-Aided Diagnosis) retained its dominance within CAD analysis, holding a market share of 43.0%.
- North America maintained its stronghold on the market, representing 48.7% of the revenue share.
- The Services segment emerged as the leading component, contributing 39.7% to the market share.
- Stomach cancer ranks as the fifth most prevalent cancer globally, according to the World Cancer Research Firm.
- Over 40% of the population suffers from functional gastrointestinal disorders (FGIDs), as reported by research published in the Gastroenterology Journal.
- Gastrointestinal cancers are responsible for one out of every three cancer fatalities, according to the International Agency for Research on Cancer.
AI in Endoscopy Statistics
- Artificial intelligence (AI) has been increasingly applied in gastrointestinal (GI) endoscopy, showing promising advancements in various areas such as esophageal neoplasia detection, gastric cancer detection, Helicobacter pylori infection detection, colon polyp detection, capsule endoscopy, and quality control of endoscopies.
- Esophageal cancer detection using AI has demonstrated impressive accuracy rates, with systems achieving sensitivity of up to 98% and specificity of up to 95% in detecting early lesions and determining cancer invasion depth.
- AI models have shown high sensitivity (up to 92.2%) in detecting early gastric cancer (EGC) and distinguishing EGC from non-cancerous lesions, aiding in prompt treatment and improving patient prognosis.
- Detection of Helicobacter pylori infection, a risk factor for gastric cancer, has been enhanced by AI systems, with sensitivities and specificities ranging between 85% and 90%, surpassing those of endoscopists.
- In colonoscopy, AI-driven polyp detection systems have shown promising results in improving the adenoma detection rate (ADR), with studies reporting significant increases in ADR compared to standard colonoscopy alone.
- AI systems in colonoscopy can accurately predict the histopathology of colorectal lesions, distinguishing between neoplastic and non-neoplastic polyps with accuracies ranging from 78.8% to 94%.
- Capsule endoscopy (CE) aided by AI has demonstrated exceptional accuracy in detecting abnormalities such as bleeding, erosions, ulcerations, and masses, with sensitivities and specificities exceeding 90%.
- AI plays a crucial role in controlling the quality of endoscopies by reducing blind spots, improving inspection-related indicators, and enhancing the detection rate of lesions, ultimately improving the accuracy of diagnoses.
- Despite the promising advancements, AI in GI endoscopy still faces challenges such as retrospective study designs, single-center evaluations, and reliance on still images for testing. Prospective, large-scale, multi-center clinical trials are needed to validate the diagnostic accuracy of AI systems.
- The future of AI in GI endoscopy holds potential for sophisticated endoscopic therapies, improved patient outcomes, and enhanced quality control measures, paving the way for transformative advancements in the field.
Use Cases
- Enhanced Detection and Diagnosis: AI’s integration into colonoscopy procedures exemplifies its capability to boost the detection rates of preneoplastic lesions, such as polyps, and assist in the management of upper digestive tract diseases including gastroesophageal reflux disease, Barrett’s esophagus, and gastric cancer. This is achieved through advanced image analysis and pattern recognition capabilities of AI algorithms, significantly augmenting the diagnostic precision of endoscopists.
- Quality Control in Gastrointestinal Endoscopy: AI systems have been developed to identify the cecum automatically, monitor the speed of endoscopic withdrawal, and accurately measure the size of polyps, aiding endoscopists in decision-making processes regarding polyp management. These systems can also identify endoscopic equipment with high accuracy, sensitivity, and specificity, improving procedural efficiency and safety.
- Reducing Blind Spot Rates: AI-powered systems like WISENSE have shown remarkable efficiency in reducing blind spot rates during Esophagogastroduodenoscopy (EGD) by detecting hidden spots in the gastric mucosa with high accuracy. This is crucial for early cancer detection, as the survival rate of gastric cancer is highly dependent on the stage at diagnosis. By significantly lowering the blind spot rates, AI assists in enhancing the thoroughness of examinations, especially in regions with limited training and low disease incidence.
- Guided Biopsy and Optical Biopsies: AI technologies facilitate a transition from random biopsy approaches to targeted biopsies, thus improving the detection rates of endoscopic lesions. This includes the development of Computer-Aided Detection (CADe) systems for early tumor detection and Computer-Aided Diagnosis (CADx) systems for predicting lesion histology without the need for physical biopsies. Such systems demonstrate high accuracy, sensitivity, and specificity, making them invaluable tools for precise lesion characterization and management.
- Assessing Depth and Boundary of Invasion: In the context of gastric and esophageal cancers, AI applications have shown promise in accurately predicting the depth of cancer invasion. This is achieved through algorithms capable of analyzing endoscopic images to distinguish various stages of cancer invasion with high sensitivity and accuracy. By enabling precise assessments, AI aids in appropriate treatment planning and could potentially improve patient survival rates.
Key Players Analysis
Medtronic
Medtronic has made significant strides in the AI in endoscopy sector with their GI Genius™ intelligent endoscopy module. This system is a trailblazer as the first computer-aided polyp detection system powered by AI, designed to enhance visualization during colonoscopy and improve the detection rates of colorectal polyps. Studies have demonstrated that it can increase adenoma detection rates (ADR) by up to 14.4%, with each percentage increase in ADR decreasing the risk of interval cancer by 3%. Its introduction marks a significant advancement in the field, offering potentially life-saving improvements in the early detection of colorectal cancer.
Wision AI
Wision AI, in partnership with Micro-Tech Endoscopy, has introduced the EndoScreener, an AI-assisted polyp detection software used during colonoscopy procedures. This FDA-cleared technology has shown to identify about 32% more adenomas than standard procedures, marking a significant advancement in early colorectal cancer detection and patient outcomes.
Olympus Corporation
Olympus Corporation has made a significant move in the AI in endoscopy sector by acquiring London-based Odin Vision, a pioneer in cloud-AI endoscopy. This acquisition, valued at up to GBP 66 million, enhances Olympus’s portfolio with Odin Vision’s commercially available computer-aided detection/diagnostic (CAD) solutions and a promising pipeline of cloud-enabled applications. Olympus’s strategy aims to integrate AI into endoscopy suites to support clinical procedures like colonoscopy and esophagogastroduodenoscopy, driving advancements in patient care through improved diagnostic accuracy and procedural efficiency.
Fujifilm
Fujifilm is enhancing the AI in endoscopy sector with its “CAD EYE” technology, focusing on early disease detection and diagnosis in gastrointestinal health. At the Asia Pacific Digestive Week 2023, Fujifilm highlighted its commitment to providing comprehensive healthcare solutions, demonstrating its pioneering AI solution for endoscopy. This effort is part of Fujifilm’s broader initiative to utilize advanced medical solutions for improving patient outcomes and diagnostic accuracy, particularly in detecting gastrointestinal cancers.
Pentax Medical
Pentax Medical has received CE mark approval for its Discovery AI-assisted polyp detector, designed to aid endoscopists in detecting potential polyps during colorectal examinations. This innovation is part of Pentax Medical’s broader initiative to integrate artificial intelligence into the operating room, aiming to enhance clinical outcomes and patient care by leveraging advanced technology for early and accurate detection of potential polyps.
NEC Corporation
NEC Corporation has taken a significant step forward in the AI in endoscopy sector with the development and release of “WISE VISION Endoscopy,” a cutting-edge AI diagnosis-support medical device software for colonoscopies. This innovation was first introduced in Japan and is anticipated to expand into the European market shortly. The software seamlessly integrates with existing endoscopy systems, leveraging artificial intelligence to identify potential lesions from images captured during colonoscopy procedures automatically. This capability aims to enhance the early detection of colorectal cancer, which is notably prevalent in Japan and ranks as the second most common cancer in Europe. By employing AI to learn from a comprehensive dataset of over 10,000 lesion images and expert physician insights, the software marks a significant advancement in medical diagnostics. It supports the detection of early-stage colorectal cancer and precancerous lesions with a user-friendly interface and simple operation, thereby contributing to improved medical care and supporting the quality of life.
Conclusion
The Endoscopy Market is experiencing a rapid growth with the help of technological advancements, increasing demands from the healthcare sector, and strategic collaborations. Although the market faces challenges such as high implementation costs and regulatory hurdles, it provides numerous opportunities, especially in improving diagnostic accuracy and expanding minimally invasive procedures. As the market progresses, it is crucial for stakeholders to closely monitor trends and leverage AI’s potential to revolutionize endoscopic diagnostics and treatment.
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