A Novel Machine Learning Method for the Early Detection Of

Predictive Diagnosis: A Novel Machine Learning Method for the Early Detection of Parkinson's Disease Literature Review Chaitanya Krishna Tej Suraparaju Table of contents: Introduction………….………….…………………………….…….………………………….………...1 Parkinson’s Disease: An Overview……………………………….……………………………….…….1 Dopaminergic Neurons…………………………….…………………………………………….1 Disease Pathophysiology ………….………………….………………………………………….2 Current Diagnostic methods ………….………………….…………………………………………….3 Clinical Examination………….…………………………………………………………………3 DaTscans ……………………………….………………..…………………………………….....5 Newly Emerging Diagnostic Methods ……………………………….……………….………..……….6 MRI Scans and Voxel Based Morphometry………………………………………...………….6 Predictive Models – An Overview ……………………………….……………….…………....……….7 Statistical models vs. Machine Learning Methods.……………………………………...…….7 Accuracy Evaluation ……………………………….……………………………………..…….8 Conclusion……………………………………………….….…………………………………………..10 Suraparaju 1 Introduction Parkinson’s Disease (PD) is categorized as a chronic and progressive disease that affects millions of people worldwide. Some of the most prominent symptoms of PD include bradykinesia, tremors, muscle stiffness, and cognitive decline, all of which can worsen over time (Williams-Gray & Worth, 2020). As of 2020, there are approximately 60,000 Americans diagnosed with PD, and this number is projected to rise to 1.2 million Americans by the year 2030 (Marras, Beck, Bower, Robert, Ritz, Ross et al., 2018). Parkinson’s is best treated if detected early; however, even as the prevenance of PD increases in our population, there is still no diagnostic method that will accurately predict the presence of the disease. Current methods revolve around a neurologist that conducts a physical examination of the patient and evaluates the presented symptoms (Kassubek, 2014). The issue with this method is that the patient will get a diagnosis, and subsequently a treatment, only after they start showing symptoms, at which point it is too late to reverse the damage done by the disease. In order to address this concern, the project described here aims to develop a novel machine learning algorithm that can accurately predict the presence of PD in a patient before they even start showing symptoms. This is done by training the algorithm to recognize the tell-tale signs of Parkinson’s as seen on an MRI scan. The algorithm will also be trained to determine the probability of developing PD in the future if the current patient scans do not indicate any signs of the disease. This will allow for the early detection of Parkinson’s, and the patient will receive the right medication at the right time. Parkinson’s Disease: An Overview Dopaminergic Neurons Parkinson’s disease (PD) is a disorder of the nervous system that is categorized by death of dopaminergic neurons (DNs) in the diencephalon, mesencephalon, and the basal ganglia of the brain. DNs are a structurally similar group of neurons that release dopamine, which is a neurotransmitter involved in several cognitive as well as motor pathways. They are mostly found in parts of the midbrain Suraparaju 2 that are responsible for receiving and processing information from sensory as well as motor neurons (Campbell & Reece, 2012). Special structures found in the Mesencephalon known as the Substantia Nigra (SN) and Basal Ganglia (BG) contain large amounts of dopaminergic neurons. The neuronal pathways found in the Substantia Nigra and the Basal Ganglia play an essential role in the proper control of voluntary motor movement like walking, riding a bicycle, or even talking. Furthermore, the neurons found in the mesolimbic and mesocortical pathways are involved in facilitating cognitive and emotion- based behavior such as motivation, reward, and perception of relationships. In structures such as the hippocampus, amygdala, and the septum pellucidum, dopamine is involved in the formation/storage of generic and emotional memories (Chinta & Andersen, 2005). Refer to Figure 1 in order to get a better understanding of the anatomy of these neuronal pathways. Figure 1: Dopaminergic pathways in the brain. This figure depicts the meso-cortic, meso-limbic, as well as the nigrostriatal pathway. Chinta, S. J., & Andersen, J. K. (2005). Dopaminergic neurons. The International Journal of Biochemistry & Cell Biology, 37(5), 942–946. https://doi.org/10.1016/j.biocel.2004.09.009 Disease Pathophysiology Although PD can be caused by several factors, symptoms are mainly experienced because of the degeneration of dopaminergic neurons. Although the exact reason as to why these neurons degenerate is unclear, prior research has revealed that DNs are more prone to oxidative stress because of their high rate of oxygen metabolism, low levels of antioxidants, and high iron content (Chinta, et al., 2005). This Suraparaju 3 prolonged stress might eventually result in cell death, and since neurons do not undergo mitosis, the damage done to the brain tissue is never repaired. Hence, as significant amounts of brain tissue start to die, the patient will begin to experience severe symptoms. The voluntary motor control center is especially affected, which is why bradykinesia, defined as a generalized slowness of movement, is the most common symptom of Parkinson’s. Additionally, the mesolimbic and mesocortical pathways are also negatively affected, resulting in a lack of emotional awareness in the patient. Lastly, destruction of brain matter in the hippocampus and amygdala causes dementia, resulting in the patients being unable to access old memories and form new ones effectively. Current Diagnostic methods Clinical Examination As of right now, the standard test for PD is for a neurologist to conduct a physical examination and evaluate the presented symptoms (Kassubek, 2014). Essentially, a physician will observe the presented neurological symptoms, as well as the patient’s family history, and produce a diagnosis. When conducting the exam, the neurologist will specifically look for the following symptoms: bradykinesia, rigidity, tremors, and gait/balance abnormalities. Bradykinesia is defined as a generalized slowness of movement, and it can especially be seen when patients struggle to initiate a particular action of motion. This symptom is observed in almost every patient with Parkinson’s disease, which makes it an essential marker for diagnosis (Stanford Medicine 25, 2020). In order to determine the presence of bradykinesia, the neurologist will instruct the patient perform rapid alternating movements. If the range of motion and/or the speed of motion appears to reduce over time, it is likely that the patient is showing signs of bradykinesia (Stanford Medicine 25, 2020). Next, the physician will check if the patient is exhibiting signs relating to muscle rigidity. This is defined as increased resistance to passive movement within multiple joints, and usually starts on one half of the lateral plan and later spreads to the other half. To determine if a patient is showing symptoms of muscle rigidity, the examiner will passively rotate the Suraparaju 4 patient’s wrist and evaluate the subjective amount of resistance given by the patient’s joint (Stanford Medicine 25, 2020). If they feel that rigidity is present, then they will mark this symptom off as being present. After checking for muscle rigidity, the physician will then observe the presence of tremors, which are categorized as an involuntary contractions and relaxations in the patient’s voluntary muscles. To test for the presence of this symptom, the neurologist will ask the patient to remain seated and not to make any movements. If the patient’s appendages begin to involuntarily shake, then the existence of tremors is likely observed (Sandford Medicine 25, 2020). Lastly, the examiner will evaluate the patient’s gait and balance abilities. Patients with PD usually develop alterations in the postural reflexes that causes stability in gait and balance control. Such alterations are documented to develop later in the course of the illness and have high potential to cause serious injuries or even death. To perform this part of the clinical exam, the neurologist asks the patient to walk back and forth several times, ideally, in a hallway that is at least 10 feet long. While the patient is walking, the neurologist will look for any signs of loss of balance on the turns, reduced step length, loss of heel strike, and loss of arm swings. If any of these signs are present, the neurologist will finally produce a Parkinson’s diagnosis for the patient. Although conducting a clinical test has been an industry standard ever since the discovery of PD, conducting exams as described above actually have several drawbacks. It is clear that such a method for disease diagnosis is extremely subjective, which means that diagnostic results vary based on the individual physician. For example, a doctor might dismiss some subtle Parkinson’s symptoms, such as muscle rigidity, as simply a sign of fatigue if the patient admits that they are sleep deprived when detailing their family history. This will result in a misdiagnosis and may be fatal to the patient. Furthermore, a clinical examination can diagnose the patient only after they start showing the major symptoms of Parkinson’s. Once a patient begins to show severe motor or cognitive deficiencies, it means that PD has already started running its destructive course, and there is not much that can be done Suraparaju 5 to slow it down. As a result, clinical examinations are an extremely poor tool to use for the early detection of Parkinson’s

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