A few years ago, I was fascinated when I observed the preliminary results of using Artificial Intelligence (AI) in Magnetic Resonance Imaging (MRI) at the largest international congress of Radiology and Imaging Diagnosis (RSNA) held in Chicago. Upon returning to Brazil, we initiated tests and evaluations of all existing products in the international market, ranging from established companies to startups, positioning ourselves as a pioneering and cutting-edge hospital in the country with the use of this technology. With surprising results, we made our choices and acquisitions, aligned with the vision of our institution, and confirmed the certainty that it would be a game-changing product in the field.
The application of AI, specifically the use of deep learning algorithms, for reducing examination times in routine MRI brings a series of advantages for both the patient and the imaging department. In addition to exam acceleration, this approach offers significant benefits that enhance the patient's experience, optimize workflow, and increase accessibility to imaging services, allowing equal access to advanced healthcare technologies. In the following text, I highlight these advantages and how they go beyond simple acceleration.
Advantages for the patient:
Time reduction: With the use of AI, MRI exams are performed faster, reducing the total time required for image acquisition. This means less time inside the machine. With faster exams and shorter time inside the equipment, there is a reduction in discomfort, anxiety, and claustrophobia associated with undergoing MRI exams. Shorter acquisition times and the possibility of greater comfort during the procedure contribute to a more pleasant experience for the patient.
Accessibility: This is perhaps the most important and underestimated topic. The application of AI in accelerating MRI exams makes imaging services more accessible. With reduced exam time, less discomfort, and overall greater efficiency, the procedure becomes more feasible and accessible to a larger number of patients. For example, patients who were not eligible for the exam due to pain, anxiety, or claustrophobia can now benefit from this technology, thanks to the reduction in physical and mental stress. We must also consider that with times like other axial imaging methods such as computed tomography, the entire protocol of exams requested in the emergency department can be reviewed, and MRI will become more considered in urgent cases.
This innovation promotes equality in access to healthcare and enables more people to benefit from advanced imaging technologies.
Reduction of motion artifacts: AI algorithms are capable of reducing motion artifacts in MRI images. This results in a lower need for sequence repetition and, consequently, reduces the total exam time.
Improved image quality: With the use of AI, the quality of MRI images is enhanced. This makes lesions more conspicuous, allowing for earlier detection of abnormalities and increasing diagnostic accuracy.
Advantages for the imaging department:
Increased productivity: AI accelerates the process of image acquisition and reconstruction, increasing the number of exams that can be performed within a given period with the same installed capacity. This results in greater productivity for the imaging sector and reduces patient waiting time for scheduling.
Improved workflow efficiency: With AI, there is optimization of the workflow and an increase in the utilization rate and occupancy of MRI equipment.
Intelligent resource allocation: The use of AI in MRI practice reduces the need for additional equipment, resulting in better resource allocation. Additionally, the reduction in exam time contributes to energy savings.
Enhanced patient journey within the institution: With faster and simplified exams, the patient journey within the institution becomes seamless. Less delay, fewer conflicts between exams, and an overall improved experience leads to greater patient satisfaction.
Improved image quality: Reduction of noise and artifacts, distortion correction, patient motion compensation, and high-resolution image reconstruction. These improvements result in sharper and more precise visualization of anatomical structures, facilitating early detection of abnormalities and increasing the reliability of diagnoses.
Research and innovation potential: The implementation of AI in MRI drives research and innovation in this field. The advancement of AI paves the way for collaborations, publications, and other opportunities for innovations that promote the field of medical imaging.
In summary, the use of AI in the practice of a major Magnetic Resonance Imaging service goes beyond mere exam acceleration. In addition to reducing the total time of care, AI improves the patient experience and increases accessibility to imaging services. With this innovative approach, more people can benefit from MRI technology, receiving faster and more accurate diagnoses, along with a more comfortable and accessible experience.