Novel Functional Imaging to Predict Surgical Side Effects for Lung Cancer Patients
Some patients with pre-existing lung issues can face severe complications after surgery for lung cancer. The current methods of assessing patients' suitability for surgery often misclassify patients. We plan to develop advanced imaging and computational tools to better assess suitability for surgery. The proposed tools will leverage recent advancements from the field of radiation oncology to provide a more accurate assessment of lung function before and after surgery. We will integrate novel lung-function images into the standard-of-care surgical evaluation workflow and evaluate the accuracy of post-surgical predictions of lung function, surgical complications and patient quality of life. We will also develop advanced image-processing and machine-learning techniques to analyze and predict patient-specific changes in lung function after surgery. We aim to provide a more accurate assessment of lung function after surgery, allowing clinicians to better predict outcomes and enhance patient care.
