Radiogenomic phenotyping of Overactive Bladder Syndrome
Aims: The goal of this study will be to identify genetic, radiologic, social and clinical factors that can help distinguish types of overactive bladder (OAB) from one another. Once we can distinguish types of OAB, we will attempt to determine which are most responsive to treatment with medication using artificial intelligence technology. Finally, we will attempt to distinguish OAB from other urologic and gynecologic conditions that may cause similar symptoms and create a prediction model that a healthcare provider might use in their office to help make a diagnosis.
Scientific Rationale: OAB is a very common and bothersome problem that many women encounter as they get older. It is estimated that anywhere from 10-30% of women globally suffer from OAB. OAB can be incredibly isolating to patients as they may feel they cannot leave the house due to concerns about urinary leakage. Additionally, OAB can lead to physical morbidity due to skin breakdown related to chronic urine leakage. In the US alone, it is estimated that the healthcare costs associated with OAB in 2020 will be higher than $80 billion dollars. Our understanding of this condition is limited and patients are often placed on a generic treatment pathway rather than an individualized one, resulting in many patients not receiving appropriate care. Because of the impact OAB can have on quality of life, it is important to develop a better understanding of this condition and its causes to develop treatment plans based on a woman's specific disease process and thereby increase treatment success rate and quality of life.