Guided biopsy of soft tissue lesions can be challenging in the presence of sensitive organs or when the lesion itself is small. Computed tomography (CT) is a frequently used modality to target soft tissue lesions. In order to aid physicians, small field of view (FOV) low dose non-contrast CT volumes are acquired prior to intervention while the patient is on the procedure table to localize the lesion and plan the best approach. However, patient motion between the end of the scan and the start of the biopsy procedure can make it difficult for a physician to translate the lesion location from the CT onto the patient body, especially for a deep-seated lesion. In addition, the needle should be managed well in three-dimensional trajectories in order to reach the lesion and avoid vital structures. This is especially challenging for less experienced interventionists. These usually result in multiple additional image acquisitions during the course of procedure to ensure accurate needle placement, especially when multiple core biopsies are required. In this work, we present an augmented reality (AR)-guided biopsy system and procedure for soft tissue and lung lesions and quantify the results using a phantom study. To increase the accuracy of soft tissue biopsies, decrease turn-around-time (TOT) of the procedure, and to decrease exposure to unnecessary radiation dose, we propose an augmented reality workflow and present a procedure to superimpose the tumor visually onto the patient using a set of augmented reality glasses and the initial CT images. In order to validate our system, we created a series of phantoms to simulate difficult biopsy conditions, where a soft tissue lesion is located in a difficult to reach location. This work presents how an augmented reality-guided system can be used to increase the biopsy accuracy and reduce the number of scans needed during the procedure. This system requires no additional tracking equipment other than the AR headset, facilitating clinical translation.
Contact
Dr. Baowei Fei
Director, Center for Imaging and Surgical InnovationDirector, Quantitative Bioimaging Laboratory (QBIL)
Cecil & Ida Green Chair in Systems Biology Science
Professor of Bioengineering, UT Dallas
Professor of Radiology, UT Southwestern
Phone: (972) 883-7239
E-mail: bfei@utdallas.edu
Website: https://fei-lab.org/baowei-fei/