Early preventative care minimizes patient morbidity and MS and TBI treatment costs

Neurological conditions that result from traumatic brain injury (TBI) and multiple sclerosis (MS) carry a significant economic burden.

In mild cases, the process of diagnosing, treating, and monitoring patients after traumatic brain injury has an overall economic cost per case of between $40,804 to $44,078. In moderate cases, this rises to an upper limit of $99,490^[1] (adjusted for inflation^[2]). Therefore, early preventative care or treatment is essential in reducing these costs and improving outcomes for patients.

Multiple sclerosis is more complicated in pathology and treatment, leading to even higher costs than TBI. MS is a long-term condition, leading to recurrent annual costs. The lifetime economic cost per case is currently estimated in excess of $4 million per MS patient,^[3] due to a combination of follow-up monitoring and ongoing prescriptions for disease-modifying therapies (DMT). These DMTs help to prevent relapses of inflammation and subsequent immune responses, both key drivers of negative MS outcomes.

How AI-enabled apps are assisting monitoring and treatment

Two new artificial intelligence (AI)-enabled applications are now available to assist with monitoring and treating multiple sclerosis (MS) and traumatic brain injuries (TBI). This new technology, now available on the Edison Ecosystem, is transforming outcomes and quality of life in neurological care.

Icometrix has partnered with the Edison™ Developer Program to transform TBI and MS imaging workflows with its icobrain tbi and icobrain ms AI applications. The goal is to improve the quality of decision-making with early interventions, mitigating as much damage as possible to deliver better TBI and MS outcomes for patients. Healthcare providers can deploy these AI applications to their existing device fleet with ease through the Edison™ Ecosystem, augmenting clinician workflows with market-ready AI algorithms to improve efficiency and quality of care.^[4]

Icobrain tbi and icobrain ms introduce more proactive monitoring and detection of TBI and MS risk factors. Catching these signs early can prevent disease progression and ease the health burden for patients. This is possible thanks to AI, which leverages real-world evidence (RWE) generated via real-world data (RWD) to accurately analyze and detect discrepancies in images.

Objective Assessment of Lesion Dissemination with icobrain ms

Icobrain ms assists clinicians with objectively assessing MS-related lesion dissemination in-vivo. The application detects, quantifies, and tracks the evolution of fluid-attenuated inversion recovery (FLAIR) white matter hyperintensities, which is visible in images as white areas that increase in brightness over the patient monitoring period. This could represent multiple sclerosis plaques, and identification is necessary to treat these plaques before they cause irreversible damage.

The white matter is colored white in images due to the presence of myelin which surrounds the nerve fibers (axons). An increase in brightness could correlate with MS-driven damage, making detection vital for improving long-term outcomes. Icobrain ms can intelligently adjust T1 hypointensities contrast levels to increase the visibility of these white matter changes. It also reports FLAIR lesion distribution following the McDonald criteria^[5]: a common framework for confirming MS diagnoses.

For long-term monitoring, icobrain ms can track annualized brain volume changes for the whole brain, as well as gray matter in isolation. These changes are weighted against a normalized reference dataset which is both age- and sex-matched to the patient. Healthcare providers benefit from automatically generated reports containing color-coded visualizations of the patient brain. icometrix ms also generates reports automatically^[6], highlighting high-risk changes to FLAIR hyperintensities and T1 hypointensities to focus the scope of treatment.

Uncovering CT mass effects caused by traumatic brain injuries

The icobrain tbi application is designed to detect, quantify, and classify brain hyperdensities. A hyperdensity refers to an unexpected increase in the density of the brain tissue, through trauma or mineral deposits. This includes epidural, subdural, and intra-parenchymal hyperdensities—typically caused by leftover clots or hemoglobin content after brain hemorrhages, or calcification of the brain’s soft tissues.

icobrain tbi can also assess for abnormalities in cerebrospinal fluid (CSF) spaces and ventricular asymmetry. CSF abnormalities can lead to conditions like hydrocephalus (water on the brain), which results in intracranial hypertension. Ventricular asymmetry is present when there is a greater-than-2mm difference between lateral ventricles and presents as a risk factor for midline shift of the brain at the level of the septum pellucidum (SP): a thin membrane in the central brain between both cerebral hemispheres. This midline shift can increase intracranial pressure leading to hypertension, thus increasing morbidity and mortality particularly when coupled with a TBI.

Both CSF spacing abnormalities and ventricular asymmetry can occur after a TBI, and icobrain tbi offers fast and standardized assessment of these occurrences. It generates visualized reports with color-coded segmentations in the DICOM format, simplifying image analysis for clinical staff. Icobrain tbi uses a normalized reference dataset that is both age- and sex-matched to the patient, improving relevance in the context of particular patient circumstances. The end result for clinicians and patients is more accurate diagnoses, increasing the likelihood of correct and early intervention, thus improving treatment outcomes and reducing overall mortality from TBIs.

Improving TBI and MS outcomes

Icobrain ms and tbi applications are integrated with the GE Healthcare’s Edison™ Open AI Orchestrator which facilitates the swift and seamless adoption of Icometrix applications, enabling full integration across existing radiology workflows through the GE Healthcare CPACS V7 and Universal Viewer.

This greatly simplifies AI application adoption for healthcare providers, unlocking innovative functionality that will help medical teams to deliver better clinical outcomes and overall efficiency.