Determination of the accuracy and sensitivity of infrared sensors for anthropometric lymphedema assessment in clinical environments

Abstract

Lymphedema is one of most feared side effects of cancer treatments in the United States. This disease leads to swelling of the affected limb and is associated with physical and psychological distress. Disease onset has no clear timeline. At risk patients may develop lymphedema immediately post-treatment or may wait decades before developing lymphedema. Current medical care for at risk patients does not provide the continuous surveillance necessary for early lymphedema detection. Therefore, more often than not, patients diagnosed with lymphedema are subjected to a lifetime of maintenance, costing thousands of dollars per year in clinical visits and compression garments. In this dissertation, implementation of infrared sensor systems was explored and evaluated against the standard volume measurement tools used in specialized lymphedema clinics. The infrared sensor with the LymphaTech software resulted in good correlation and agreement with current measurement tools while being easier to use and more cost-effective than commercially available systems. Additionally, the efficacy of utilizing local arm geometries for the detection of arm lymphedema was determined. Anthropometric based features were extracted from a 3D point cloud using custom code and applied to train classification models for lymphedema. The features detected subtle changes in the arm of lymphedema patients with a sensitivity of 61% compared to the current standard volume difference measurement, which has a sensitivity of 33.3%. Clinics not equipped to detect lymphedema could integrate this infrared system and model as a screening tool to improve referral rates to lymphedema clinics.