Imaging biomarkers in Multiple Sclerosis
Pain, depression, slurred speech and feeling of numbness, tingling, or weakness. These are just some symptoms of Multiple Sclerosis (MS) disease, a long-term condition that affects the brain and spinal cord.
In MS, the immune system confuses myelin with a foreign body and attacks it. The loss of this protective sheath that covers the nerve fibers will disrupt the messages travelling between the brain and the body. These messages may be slowed down, interrupted, or may not occur at all.
Eventually, the person sees affected the ability of controlling their own actions. The signs and symptoms of MS may vary greatly depending on the stage of the disease and the location of the affected nerve fibers. Movement affections, vision problems, altered speech and dizziness are common consequences of this condition.
It is the most widespread neurological disorder of young adults globally. The disease can be developed at any age, but its main incidence appears in the range of 20-50 years old. The National Multiple Sclerosis Society estimates that near 2.3 million people are living with this disease around the world. It also calculates that 1 million of them are placed in the United States, where 200 new cases are diagnosed every week.
Together with blood tests, medical history and neurologic exams, imaging scans have also proven to be a key element for the diagnosis of MS, concretely the Magnetic Resonance Imaging (MRI) is the reference diagnostic technique for the identification of lesions in MS.
Damaged white matter has a prolonged T2 relaxation time due to increased tissue water content and to degradation of the myelin, being well depicted on MRI and concretely on Fluid Attenuated Inversion Recovery (FLAIR) images. In this MR-sequence, MS lesions are seen as white matter hyperintensities (WMH). Nowadays, manual segmentation of WMH areas is still the gold standard to quantify the total lesion volume and to know the number of lesions in the brain. However, this methodology turns MS patient’s diagnosis and follow-up in a cumbersome and time-consuming task with high intra- and inter- observer variabilities.
Zero-click tools based on Artificial Intelligence (AI) and, more concretely, Convolutional Neural Networks (CNN) can be used to automatically segment WMH on FLAIR images in a few minutes. Novel designed architectures are composed of an ensemble of CNNs built on standard convolutional, dilated and residual layers.
These tools are capable of fine segmentation of the lesion avoiding the physiological WMH as the ependymal layer. Physicians can obtain quantitative information that helps them to achieve a more accurate and earlier diagnosis, thus reducing the workload and improving the time-efficiency while enhancing patient assessment.
What information does it provide?
Once WMH are segmented, relevant lesion statistics are quantified: lesion number, total lesion volume, dominant lesion volume, dissemination, or entropy among others. All this information can be summarized in a structured report along with the most characteristic slices. These processes will easily assist physicians in the diagnosis of MS patients not in the future, but now.