5 Major Key Trends of Brain Disease Modalities and Software Market| 2021–2031
Brain imaging modalities include traditional modalities such as magnetic resonance imaging (MRI) and computed tomography (CT) scans, as well as other emerging imaging technologies such as positron emission tomography (PET) and combined functionality of PET with MRI or CT.
While magnetic resonance imaging (MRI) is a traditional technology due to its long history of use, advanced MRI techniques such as diffusion tensor imaging (DTI), diffusion-weighted imaging (DWI), susceptibility-weighted imaging (SWI), and dynamic susceptibility contrast (DSC) imaging are becoming more widely used in regions such as North America and Europe.
In terms of quantitative analysis, brain imaging software complements the scanned images produced through these modalities. Quantitative insights into the structure, biomarkers, and other minor abnormalities in the brain are a helpful tool in assisting in the more accurate identification of neurological dysfunctions.
The market for brain imaging modalities and software is being pushed by reasons such as the rising incidence of neurological dysfunction, the increasing integration of AI in the area of medical imaging, and the growing desire for safer and non-invasive medical imaging technologies.
According to BIS Research, the global brain disease modalities and software market report highlights that the market was valued at $13,055.7 million in 2021 and is expected to reach $21,867.6 million by the end of 2031.
Key Trends of Brain Disease Modalities and Software Market
Various technological trends have influenced the global brain disease modalities and software market.
1. Imaging Hardware and Software Integration: Due to their non-invasive qualities, standalone hardware imaging devices such as magnetic resonance imaging (MRI) and computed tomography (CT) scanners are commonly employed for medical imaging.
However, there is a growing interest in integrating software solutions with scanning devices for a variety of reasons, including viewing and storing scanned medical images, analyzing and interpreting scanned images obtained from MRI, CT, and PET-CT scans. They detect minor abnormalities to aid in more accurate diagnosis, identifying degrees of abnormality and flagging images indicative of disease, allowing clinicians to prioritize problematic patients.
2. Investigation of Ensemble Models with Multiple Classifiers, such as Biomarkers and Patient Characteristics: In comparison to individual models that only focus on one of the two, ensemble models that combine biomarkers in the blood with analysis of the patient’s cognitive tests provide a more accurate diagnosis of neurological problems. Such models can better classify normal and abnormal brain scans based on the interpretation of various qualitative and quantitative data by applying machine learning.
A combination of different classifiers, such as biomarkers and cognitive test scores, and their weighted analysis, as provided by ensemble models, has significant promise in terms of identifying and treating neurological disorders.
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3. Increase in Demand for Portable Brain Scanners and Wearables: Current medical imaging technologies, such as MRI and CT scan machines, need significant investment and are only available in large clinical institutions, such as hospitals. The high initial cost of these devices makes it difficult for smaller clinical facilities to deploy them.
Furthermore, while MRI, CT, and positron emission tomography (PET) scans provide useful information in terms of visualization of organ systems for diagnosis, their expensive cost is a major issue in the low adoption of such equipment in emerging countries and rural areas.
In recent years, there has been an increase in the adoption of portable brain scanners, which provide benefits such as making MRI scans less expensive and more accessible, improving accessibility to MRI, and providing greater convenience due to their compact size.
4. Augmented Reality and Medical Imaging Integration: In the medical imaging industry, there is a growing interest in the application of augmented reality. Echopixel, for example, provides a software platform that allows clinicians to view medical images obtained from MRI and CT scans in four dimensions as an interactive hologram.
While the company’s current offering is restricted to cardiology, increased interest in the subject of augmented reality (AR) and its implementation in medical imaging is expected to expand into additional clinical applications such as neurology and gastrointestinal, among others.
Three- and four-dimensional representations of brain MRI and CT scans can help surgeons in the operating room and aid in the identification of neurological disorders.
5. Increased Focus on the Pediatric Population: The amount of hazardous radiation emitted by scanners is one of the key factors influencing the use of imaging modalities in the pediatric population.
According to a paper published in BMC Pediatrics in January 2020 titled, ‘Rapid Brain MRI Protocols Reduce Head Computerized Tomography Use in the Pediatric Emergency Department,’ despite the diagnostic limitations associated with rapid MRI, the imaging modality held strong influence in pediatric imaging than head computerized tomography (HCT) due to lower radiation exposure.
To summarize, the adoption of brain imaging software is an emerging trend owing to rising technology integration and digital transformation in healthcare. The increasing prevalence of neurological disorders and the ongoing digital transformation in healthcare are driving significant growth in advanced brain imaging methods and software solutions.
