Clinical experts like radiologists and orthopedic surgeons are highly trained, highly skilled workers tasked with addressing patient health and well-being. Both groups rely heavily on medical imaging to assess, measure, diagnose and even treat. As medical imaging becomes increasingly prevalent and complex, experts must keep up with the workload while maintaining and expanding their expertise.
Healthcare systems must keep up with the state of the art in diseases, medicines, medical devices and techniques to ensure that patients get the right care at the right time.
Artificial Intelligence (AI) in medicine is first and foremost automation, and automation has impacted and shaped modern society in almost every facet, including medicine. Applying AI automation should be welcomed by radiologists and orthopedic surgeons so long as the end result is better patient outcomes, because the goal of medical practice should not change when new technology arrives, but rather, that technology should be exploited to better achieve the goal.
AI can also bring about standardization, which can lead to more effective communication between radiologists and orthopedic surgeons. Take the example femoroacetabular impingement and hip dysplasia: measurements derived from pelvic radiographs require a high level of expertise to understand the patient positioning and localize anatomically relevant landmarks. Radiologists often do not carry out these measurements, or when they do, the orthopedic surgeon is not satisfied with them. AI automation of pelvic radiographs could present a standardized set of measurements which can serve as a common language between the specialists.
As the familiarity and expectation for standardized measurements on radiographs grows, so too should the expectations for more standardized radiographic acquisition and metadata. While the human experts may be more robust to imaging variability, a better way forward for all stakeholders would be to raise the quality standards at all points in the medical imaging lifecycle.