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Magnetic resonance imaging (MRI) produces detailed images of the body in order to detect diseases and abnormalities that could lead to disease. They are becoming increasingly popular in healthcare due to being safe, non-invasive, and providing information on almost any part of the body (including soft tissue). MRI add-ons are additional techniques, accessories, and software that improve the abilities and applications of standard MRI.
This article will discuss the role of MRI add-ons in improving treatments, how MRI add-ons contribute to more accurate diagnosis, examples of MRI add-ons and how they impact healthcare, and challenges that need to be overcome for their widespread use.
MRI software upgrades and deep learning algorithms can enhance image quality, reduce scan times, and provide more detailed clinical insights, potentially accelerating drug development by enabling faster and more accurate evaluation of treatment efficacy in preclinical and clinical trials.
The increasing use of AI in MRI scans is enhancing their diagnostic abilities. AI can detect patterns and abnormalities faster and with more accuracy than before. For example, the Google-produced AI was able to outperform human radiologists by more accurately detecting breast cancer from mammograms. Ezra uses AI in their full-body scans to enhance image quality and improve diagnostic ability. AI-powered image analysis enables earlier detection of disease which allows for early intervention and subsequently to improved outcomes.
MRI add-ons can improve image quality in multiple ways. Enhanced MRIs allow imaging in regions that are difficult to image using normal MRI techniques. For example, lung parenchyma requires the use of UTE (ultra-short echo time) imaging to produce an image of good enough quality for small tumors to be detected. Normal MRI imaging cannot produce images of good quality, which could result in tumors being missed. MRI add-ons can also reduce the effects that breathing and heart-pumping movements can have on decreasing image quality, such as by using HASTE sequences (Half-Fourier single-shot TSE).
MRI add-ons contribute to diagnostic accuracy, using tools such as AI to more accurately assess whether diseases are present in the body. AI reduces human error in diagnoses as it is not affected by issues such as fatigue or oversight. Add-ons, such as advanced imaging techniques, can also improve diagnoses by confirming whether a tumor is benign or malignant.
For example, multiparametric MRIs use different imaging techniques above and beyond a standard MRI to assess tissue stiffness (characteristic of aggressive tumors) and blood flow patterns (appear increased and abnormal in aggressive tumors) to distinguish between benign and malignant cancers. Different add-ons can be used in combination to further increase accuracy, as seen by the use of dynamic contrast-enhanced (DCE) MRI and AI to distinguish between benign and malignant breast cancer.
Clinical trials typically take a long time, not only to set up and run but also to obtain and analyze results. MRI add-ons can first play a role in obtaining detailed information about disease characteristics in different patients. For example, MRI biomarkers can be used to select patients most likely to respond to the treatment, allowing more targeted treatments and improved trial outcomes. MRI add-ons can speed up obtaining results from the trial by providing real-time data as the trial progresses to monitor how well the therapeutic intervention is working and allow adjustments to be made to improve patient outcomes.
The use of enhanced MRI technology enables personalized medical treatments. Diseases will develop in different ways in different people, MRI enables the tailoring of therapy to an individual - delivering the right treatment at the right time - which results in improved outcomes. MRI add-ons, such as DSC MRIs (dynamic susceptibility contrast), can be used to differentiate different types of tumors, distinguish between post-treatment effects and the re-growing of a tumor, and predict how the tumor will react to treatment, all of which will allow for precision treatments and improved patient outcome.
MRI add-ons can assist in the earlier detection of diseases. The use of different MRI techniques to improve image quality combined with enhanced image analysis using AI results in earlier and more accurate diagnoses. These advanced techniques can detect abnormalities before symptoms even occur. Early diagnosis allows for early intervention - diseases are caught when they are less severe and can be treated more effectively.
Functional MRI is a type of MRI that allows real-time visualization of brain activity. Medical professionals can see how the brain responds to specific inputs by observing different regions ‘lighting up’ when performing different tasks. This has been used in the study of diseases such as Alzheimer’s, where changes in brain function over time and the effects of therapeutic intervention can be monitored. fMRIs are also used before brain surgery to identify the target area and important areas to avoid (such as those controlling movement or language).
Diffusion tensor imaging uses the random movement of water molecules to assess the presence and density of cell membranes and organelles and, from this, form an image. These features of DTI allow its use in characterizing tumors, grading tumors high or low (analysis of tumor cells under a microscope is required for the specific levels), predicting prognosis, and monitoring treatment. DTI has been shown to improve diagnosis accuracy and distinguish benign and malignant tissue. In addition, by using this method, a tumor can be followed over time, and real-time analysis can be carried out to identify changes to the tumor as a biomarker for treatment response.
As AI and machine learning continue to be optimized for roles in healthcare, their effectiveness increases. AI used with MRI can make diagnosis faster and more accurate. For example, Ezra uses Flash AI to further enhance the resolution of their MRI images and screen for small abnormalities at the earliest stage possible. Ezra also uses FDA-cleared AI to measure regions of interest and produce a 3D visualization of the prostate to assist in screening.
Although MRI add-ons are becoming increasingly important to the early diagnosis of diseases such as cancer, they are not available everywhere. The equipment needed for general MRIs can be difficult to come by, particularly for those living in rural and remote areas where healthcare provision may not be as extensive. This is amplified when looking for MRI add-ons where further equipment is required. In addition, while general MRIs are expensive, MRIs with add-ons can substantially increase the price - further decreasing widespread accessibility.
Skilled radiologists are required to both use and interpret MRI scans and will have to undergo extensive training for each MRI add-on. Although AI plays an increasing role in the interpretation of MRI scans, it is imperative that this development is used alongside experienced radiologists - one study has shown that a combination of AI and radiologist evaluation showed improved diagnostic accuracy than a radiologist or AI on their own. Ezra partners with leading imaging centers and expert radiologists to provide the best quality images and accurate results.
Each MRI add-on has to undergo similar regulatory hurdles to a brand-new medical device and test to ensure compatibility with existing MRI technologies. These hurdles ensure a patient’s safety and that the product acts as it has been claimed—i.e., with sufficient diagnostic ability. This is particularly important where AI is used in diagnosis as it faces limitations, including a lack of transparency (many AI models cannot ‘explain’, meaning that clinicians cannot see how AI reached its conclusions).
MRI add-ons increase diagnostic accuracy by improving image quality and reducing false positives and negatives. They are speeding up the development of treatments by providing real-time data throughout clinical trials. This allows therapeutic intervention to be monitored for the duration of the trial and adjustments to be put in place as needed, improving patient response and the success of the trial.
The wealth of data provided by using MRI add-ons is also improving patient outcomes by enabling personalized medical treatments - the right drug given at the right time. The level of detail provided by add-ons, such as diffusion tensor imaging, results in anomalies being spotted earlier in disease progression and, thus, treatments being started as early as possible.
MRI add-ons are revolutionizing personalized medicine. If you want to be proactive about your health and are interested in exploring advanced MRI solutions, why not book an Ezra full-body MRI? Our annual scan catches potential cancer earlier, leveraging AI through the screening process to make it more efficient, affordable, and faster.
