Academic 2018-2019 year was exciting for Yale Radiology Medical Student Thesis Program. Four medical student candidates successfully completed their thesis requirements this year; the quality of the scientific work led to multiple journal publications. There was an emphasis on artificial intelligence (AI) methodology. Praneeth Sadda (mentor Xenophon Papademetris, thesis “Visualization of Placental Vasculature in Fetoscopic Surgery”) developed computer vision pipeline for the enhancement of images acquired by fetal endoscopes, with the automatic detection of blood vessels with a trained convolutional neural network, with the potential to improve the outcome in challenging twin-to-twin syndrome surgeries. Praneeth’s thesis was one of the five (out of all graduating Yale Medical Student Theses) selected for oral presentation during Student Research Day. Cortland Sellers (mentor Kevin Kim, thesis “Inflammatory Markers as Predictors in Primary Liver Cancers with Emphasis on Chronic Viral Hepatitis”) demonstrated the prognostic value of inflammatory markers in Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma. Tafadzwa Chaunzwa (mentor James Duncan, thesis “On technology and innovations in cancer imaging and image-guided therapy”) developed AI-based radiomics approach to predict histology and outcome of non-small cell lung cancer. Mansur Ghani (mentor Todd Schlachter, thesis “Identifying Quantitative Enhancement-based Imaging Biomarkers in Patients with Colorectal Cancer Liver Metastases undergoing Loco-regional Tumor Therapy”) demonstrated that enhancing tumor burdearcan is a superior outcome predictor in patients with liver-dominant colorectal cancer metastases undergoing loco-regional tumor therapies. In summary, Yale Radiology Medical Student Thesis Program had a great year and remains an excellent opportunity for medical student to enter the field of academic radiology. The enthusiasm and participation of radiology faculty is critical in this regard.
Submitted by Angel Machon on August 22, 2019