In recent times, there are advances in the hardware as well as software in the MRI systems. These advances are helping the clinical radiologist in improved localization and diagnosis and of the disease process. There are few important developments that need a mention and are:
Artificial Intelligence (AI). AI is being used in radiology equipment for streamlining workflow, automatic scanning, motion sensors, etc., for the last few years. However, now AI is there to stay in radiology decision-making process and is being adopted by the radiologist in image interpretation that is likely to make an impact on healthcare outcome. It is being used in all modalities in radiology including MRI. Typically, an MRI machine takes 2D images and stacks them to make 3D versions. It is possible for machine learning to enhance less-detailed MRI images by intelligently filling in the gaps eventually cutting down MRI scan times by up to 90 percent. The current goal is to run the MRI machine faster than usual but achieve an image quality level on par with conventional methods. Faster MRI will help the patient to spend less time in the machine. Another benefit suggested by this research is that if an MRI could run fast enough, a physician could order one of those scans instead of a traditional X-ray or CT study and save the patient from radiation dose they’d get otherwise.
Many companies in the manufacturing sector use AI tools that predict maintenance needs before total breakdowns happen. The associated executives understand even an equipment malfunction lasting a few minutes can disrupt operations and cost hundreds of thousands of rupees. AI algorithms could make predictions about maintenance for proactive prevention. Researchers in China developed an AI algorithm using with fMRIs of people with severe brain damage those may regain consciousness. It assesses the level of awareness a person has and uses that information related to disorders of consciousness to give a suggested prognosis for recovery. There is also an attempt to reduce the contrast dose by using deep learning tool and produce a similar quality image as obtained by full dose contrast with any loss of diagnostic information to avoid any possible side effect of MRI contrast agents.
Development of Helium free MRI. First time introduced by Philips, the Netherlands at the RSNA 2018, the model called Ingenia Ambition 1.5T is a blue sealed magnet that is virtually Helium free and about 800 kg lighter than regular 1.5T MRI but does not compromise on image quality. Such Helium free magnet opens up the possibility to build up true mobile MRI in the near future.
Flexible MRI coils. Development of flexible adoptive image receive (AIR) MRI coils by the major vendor in the field of MRI have helped to mold the anatomy of patients over the current stand of hard coils, bringing these close to the area of interest and enables in better signal to noise ratio and improved image quality. These coils are light and can be used on any body part giving high-resolution images and will also be helpful in reducing imaging time.
Development of compressed SENSE technology. Introduced by Philips for all anatomies and for all 2D, 3D, and 4D scans that have helped to reduce the scan time in MRI and has also able accurately perform quantitative MRI with improved resolution and temporality. Faster MRIs would be a good thing as patients would spend less time in machines, and imaging centers and hospitals could do more tests per day that will help them to recover the machine cost faster.
Development of ultrashort TE technology. This technology has helped to image the bone as efficiently on MRI as CT, thereby eliminating the need for side effects of radiation based techniques and also helps in reducing the gradient sound of MRI which is the major reason for non-compliance of some of the patients.
We can conclude that continued development in the hardware and software technology has helped to improve clinical decision making and is likely to impact the healthcare in future.