Medical imaging has been a crucial part of patient care since the invention of the X-ray in 1895. In today’s healthcare system, it’s almost impossible to imagine how doctors could make accurate diagnoses and treat patients without the invaluable insight provided by medical imaging devices.
From X-ray to CT, MRI to ultrasound and PET, imaging devices have proven indispensable for screening, diagnosis and follow-up. Not only this, they play a crucial role in guiding physicians during surgical procedures. For more than 100 years, medical imaging has facilitated the practise of modern medicine, simultaneously supporting physicians and improving outcomes for patients.
Estimates suggest that over 3.5 billion diagnostic X-rays and over 40 million MRIs are performed around the world every year. As demand for radiology services increases, so does the urgent need to provide fast and accurate diagnoses for patients. With a limited number of skilled radiologists and an expanding global population, digitisation holds the key to achieving this.
The benefits of digitising radiology
The massive demand for radiology services simply cannot be met using manual systems. Traditionally, the discipline has relied on manual handling of radiology films. However, this approach is no longer optimal in a modern healthcare system.
One of the primary advantages of digitising radiology is the integration of information and patient files. As healthcare services move towards a more digital approach, it’s easier for clinicians to access to patient information and diagnostics. This facilitates collaboration and better communication between departments, whilst ensuring electronic storage of all relevant information, meaning it is available to all departments, at all times. This has massive implications in terms of improved efficiency and better operational practises. Ultimately, it also drives better outcomes for patients who benefit from a more joined-up approach to their healthcare journey.
The development of artificial intelligence (AI) is facilitating this process, bringing a whole new dimension to radiology. An increasing number of healthcare systems are now employing AI software to support radiologists in their work.
AI brings the following advantages to radiology:
- Increased processing capability due to algorithms based on vast data sets (often thousands or hundreds of thousands of images). Human labour would be unable to process this volume manually
- Algorithms can be trained continuously, learning from new observations and incorporating that data into constantly-evolving machine learning models
- AI can often make observations that humans cannot see, based on optical microscopy, which the human eye is unable to detect
- By improving accuracy, AI helps radiologists to reduce the number of false positives and false negatives in routine screening
- Nurses and non-skilled clinicians can utilise advanced software, opening up the field and reducing patient waiting times for imaging procedures
- Provides reliable second opinions for clinicians, which may otherwise be unavailable or would result in unnecessary delays
The future of radiology
AI and machine learning are tools that can help radiologists by improving accuracy, workflow and efficiency. In other words, they won’t replace the role of the skilled radiologist. On the contrary, by streamlining the interpretation of digital imaging in healthcare, AI tools can actually provide radiologists with more time to take on more cognitively challenging tasks. Whilst this will inevitably lead to some redefining of traditional radiology roles, the radiologist remains a key player in the process.