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Digital Technology Innovations in Preoperative Surgical Planning

  • Report

  • 60 Pages
  • November 2021
  • Region: Global
  • Frost & Sullivan
  • ID: 5513652

Novel AI Applications Transforming Current Surgical Practices through Automation, Navigation, and Imaging

Rising healthcare and surgery costs are increasing the burden on healthcare systems, making it difficult for hospitals to offer high-quality care at affordable prices. Time-consuming manual processes that significantly impact surgeon time and workload, hospital cost increases due to delayed surgery, and low patient satisfaction levels due to human error are the current challenges in surgery.

Artificial intelligence technologies are increasingly critical in preoperative surgical planning to help surgeons create accurate surgical plans, assess patient risks of intraoperative and postoperative complications, and improve patient outcomes. AI refers to the capability of a computer program to perform tasks and processes associated with human intelligence. AI enables risk assessment, systems scheduling, segmentation of anatomical structure, and automation in the preoperative phase during a surgical procedure. The growing adoption of AI and ML technologies in surgical planning will accelerate due to their potential to reduce costs, shorten patient wait times, generate precise data for clinical decision-making, and improve surgical outcomes.

Key Questions This Research Will Answer

  • What is the role of AI/ML in preoperative surgical planning?
  • What are the benefits of preoperative surgical planning?
  • What are the novel AI/ML technologies for preoperative planning of orthopedic surgery and neurosurgery?
  • What are the key challenges in preoperative surgical planning and the adoption of AI/ML in surgical planning?
  • What are industry patent publication trends?
  • What are key growth opportunities for industry players?

Table of Contents

1. Strategic Imperatives
1.1 Why Is It Increasingly Difficult to Grow? The Strategic Imperative 8™: Factors Creating Pressure on Growth
1.2 The Strategic Imperative 8™
1.3 The Impact of the Top Three Strategic Imperatives on AI in the Preoperative Surgical Planning Industry
1.4 About the Growth Pipeline Engine™
1.5 Growth Opportunities Fuel the Growth Pipeline Engine™

2. Key Findings
2.1 Research Methodology
2.2 Key Findings

3. Growth Environment and Market Segmentation
3.1 Scope of Analysis
3.2 Market Segmentation
3.3 Application Segmentation
3.4 High Healthcare Expenditure and Costly Surgical Procedures are Key Challenges
3.5 Artificial Intelligence has the Potential to Address Preoperative Surgery Challenges

4. Technology Snapshot
4.1 AI Mimics Intelligent Human Behavior and Analyzes Large and Complex Datasets to Identify Patterns and Make Accurate Predictions
4.2 AI Offers Anatomical Classification, Alignment, and Automation at High Speed with Accuracy
4.3 Growth Drivers for AI Innovation in Preoperative Surgical Planning
4.4 Growth Restraints for AI Innovation in Preoperative Surgical Planning
4.5 AI is Transforming Current Surgical Practices with Advances in Automation, Navigation, Imaging, and Robots
4.6 AI/ML Supports Automating Routine Tasks in Preoperative Surgical Planning Phase to Improve Patient Outcomes and Save Surgery Time and Costs

5. Technology Snapshot - Orthopedics
5.1 AI Technologies Reduce the Surgeon’s Time Spent on Manual Image Analysis and Healthcare Costs, and Improve Patient Outcomes
5.2 AI Technologies Enable Surgeons to Study the Granularity of Anatomical Structure to Improve Preoperative Surgical Planning
5.3 Novel AI Technologies in Research Optimize the Selection of Implants in Preoperative Surgical Planning
5.4 Accuracy of Large Datasets and Data Privacy are Major Challenges Affecting the Implementation of AI in Orthopedics

6. Technology Snapshot - Neurology
6.1 AI Technologies Support Surgeons to Identify Patients Requiring Immediate Surgical Intervention and with Preoperative Planning
6.2 Novel AI Technologies in Research Build AI Algorithms and Deep Learning Models to Automate the Segmentation of Brain Structure
6.3 Large Dataset Requirements for Model Training, Slow Program Development, and Regulatory Approvals are Crucial Challenges Affecting AI Implementation in Neurosurgery
6.4 Market Participants Developing AI/ML Technologies Should Evaluate the Features on Various Statistical Measures to Prove Their Utility

7. Companies to Action
7.1 Formus Labs
7.2 PeekMed
7.3 Omniscient Neurotechnology
7.4 Numex GmbH
7.5 Enhatch

8. Patent Landscape
8.1 China is the Innovation Hub for AI-based Technologies in Preoperative Surgical Planning
8.2 Key Patents

9. Growth Opportunity Universe
9.1 Growth Opportunity 1: National and International Partnerships Among Institutions to Build Large Databases to Train AI/ML Algorithms
9.2 Growth Opportunity 2: Data Scientist-Program Developer Community Ecosystem to Build Innovative and Reliable AI/ML Models or Algorithms
9.3 Growth Opportunity 3: Building Innovative AI/ML Technologies for Complete Automation in Preoperative Neurosurgery Planning

10. Key Industry Participants

11. Next Steps
11.1 Your Next Steps

Companies Mentioned

A selection of companies mentioned in this report includes:

  • Enhatch
  • Formus Labs
  • Numex GmbH
  • Omniscient Neurotechnology
  • PeekMed