Participants began by choosing anonymized CT scans that they wanted to work with. Using DICOM Director’s Intravision XR technology, the participants were able to generate 3D models from the scans using threshold and seed grow methodologies.
Each participant was allowed to submit 3 models for judging, which included an explanation of a clinical use case for the model and which methodology was used to produce the result. All submissions were anonymized and judged blindly.
Victor Lee is a fourth-year medical student at Yale and is pursuing a career in radiation oncology. He is currently spending his research year in the Aneja lab to explore methods to predict the generalizability gap in artificial intelligence models used in the analysis of medical images. He has been an early, avid user of virtual reality software and is excited to see the technology being adopted for medical applications.
Use Case: This model is a representation of the lungs with non-small cell lung cancer. The tumor is located on the lateral portion of the right upper lobe where an indentation can be observed in the model. The Lung CT images were obtained from The Cancer Imaging Archive. This model was produced using the seed grow method. The tumor was of a similar density with surrounding tissue so extra negative seeds were placed around the tumor to distinguish it from the chest wall.
A 3D reconstruction of cancer models can aid radiologists in diagnosing and staging cancer. These models could also help surgical oncologists in pre-operative planning and radiation oncologists in contouring.
My name is Samuel Liburd Jr., a MD/PhD student studying at Yale University. I am originally from the U.S.V.I. and did my undergraduate studies at the University of the Virgin Islands. My time at Yale has helped me nurture my interests in biomedical research and medicine, and as a result, I plan to pursue my PhD in biomedical engineering and surgery for my medical career. I believe that this combination of career interests can help me find research applications that leverage the strengths of biomedical technology in clinical medicine.
Use Case: This model highlights more detailed abdominal arterial vasculature including mesenteric vessels, vessels of the celiac trunk, the liver. spleen, and pancreas. In medicine this model can be used for surgical planning as it specifically highlights relation of vasculature with respect to the kidneys, (This particular patient has dual renal artery blood supplies) and potentially other organs. It also provides information about the vascular supply of the pancreas, liver, and spleen with minimal tissue obstruction, as well as smaller branches of the superior and inferior mesenteric arteries. This could be useful in identifying thrombosis or occlusion leading to organ ischemia.
Hi, my name is Raj Saggu. I’m a current second-year medical student at St. George’s University. I graduated from Virginia Commonwealth University in 2017 with a degree in Biomedical Engineering and have experience working in the field designing models for the EpiPen and spinal implants for Styker. I realized I wanted to further my knowledge in the clinical and medical aspects of the field, so I pursued medicine. I aim to incorporate all my skills in my future medical career.
Use Case This model can be used for orthopedic surgeons to see a model of the patient before performing a surgery. It can also be used to teach medical students about how similar surgeries would be performed. This can be a better teaching model and safer for the patient.”
