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Future of Radiology Platforms: Key Trends for Medical Imaging in 2022

Future of Radiology Platforms: Key Trends for Medical Imaging in 2022

Radiologists worldwide are looking to adopt medical imaging technologies that will transform the pace and standard of healthcare delivery. With the COVID-19 pandemic exacerbating issues such as radiologist shortages, higher rates of burnout, and limited access to clinical care, there’s a great need for fast, cost-effective, efficient medical imaging technologies.

This blog will discuss five major trends in medical imaging in 2022:

  • Adoption of artificial intelligence solutions to improve clinical efficiency
  • Automation of radiology workflows for optimized scalability
  • Orchestration and coordination of radiology workflows
  • Reliance on web-based or cloud radiology systems

1. Artificial Intelligence (AI) Usage in Radiology and Medical Imaging

By adopting AI within a radiology workflow, radiologists can perform medical image analysis much faster—saving time and costs in the short and long term—and provide high-quality care to patients. 

AI provides value to radiologist practices in several ways:

  • Simplifying and Reducing Manual Tasks

Machine learning algorithms can perform routine manual tasks much faster and more effectively than radiologists. For example, Arterys’ Cardio AI clinical application improves the segmentation speed by 36%, saving up to 25 minutes per study.

  • Accurately Identifying Anomalies at Scale

Deep-learning algorithms can be trained to identify anomalies in large volumes of medical images accurately. For example, abnormal chest X-rays can be detected up to four times faster with AI than when conducted solely by an expert radiologist.

  • Identifying Subtle Changes Over Time

    Precise AI algorithms can also identify subtle changes over time, performing a longitudinal analysis on lesions and creating standardized reports. This can help radiologists, especially when analyzing large volumes of medical imaging data. Reports show that AI increases radiologist efficiency by up to 12%, improving diagnostic efficiency and overall patient outcomes.

Furthermore, when AI is seamlessly integrated into workflows, it provides greater flexibility and scalability for the needs of any radiology practice.

2. Radiology Workflow Automation in Healthcare

Automated workflows are helpful to radiologists looking to optimize work efficiency and accelerate the pace of healthcare delivery. 

By automating manual, repetitive tasks, radiologists can analyze larger volumes of images per study much faster. For example, Arterys’ Lung AI and Breast AI tools help radiologists optimize the speed of reading times on studies by up to 44% and 52.7%

However, it is critical that any automation tools you adopt in your radiology practice can:

  • Integrate seamlessly into your existing workflow
  • Align with the requirements of regulatory bodies (e.g., FDA, Health Canada, CE Marked)
  • Perform in a clinically useful and relevant way for your practice

3. Radiology Workflow Orchestration/Coordination

Although PACS served as robust diagnostics tools that increased study completion rates, there was still a pressing need to effectively distribute patient cases based on the expertise and bandwidth of radiologists. 

Workflow orchestration solutions have since optimized enterprise distribution and management of radiology cases, especially when they function intelligently—aided by AI/machine learning or other advanced computing infrastructure. 

When fully optimized, workflow orchestration can minimize inefficiencies during:

  • Acquisition of patient images
  • Matching patient records to analyzed images
  • Triaging patient cases across radiologists

As radiology workflow orchestration solutions are integrated more widely into PACS systems across radiology practices, the hope is for faster turnaround time on image analysis and higher patient and radiologist satisfaction. 

4. Web-Based Radiology Systems

Cloud-based PACS systems are becoming more common across radiology practices looking to optimize the efficiency and scalability of their clinical practice. Unlike on-prem PACS systems, cloud PACS solutions are much faster and often cost far less to install, operate, and manage.

Some of the benefits of cloud-based radiology systems include:

  • Lower overhead costs for hardware maintenance and technical support
  • One advantage of using the cloud-native solution is scalability and significantly reduced downtime for upgrades or maintenance, helping to keep security protection and functionality up to date.
  • Improves workflow efficiencies and helps reduce radiologists’ frustration by giving them one platform to connect with multiple hospitals, rather than having to constantly log in and out of individual systems
  • Allows radiologists to provide quality care and collaborate from wherever they are

Radiology practices that transition their on-prem PACS systems to web-based ones can also provide care to more patients since radiologists can read images remotely. By enabling radiologists to access patients’ images on-demand, cloud PACS are helping radiology practices scale up their operations.

The Future of Medical Imaging

A cloud-native radiology platform brings tremendous potential for enhancing radiology practice, irrespective of specialty. The future of medical imaging is looking brighter than ever with all the emerging tools on the market and the drive to innovate solutions that benefit patients in the long term.

Want to Learn More?

Check out our white paper, How Radiologists Can Improve Accuracy And Scale of Medical Diagnosis With Cloud and Artificial Intelligence, which delves into cloud and AI technologies in detail and explores how each can assist radiologists in their day-to-day operations. 

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