Pfefferle Matthew, Shahub Sarah, Shahedi Maysam, Gahan Jeffrey, Johnson Brett, Le Phuc, Vargas Jose, Judson Blake O, Alshara Yasmeen, Li Qinmei, Fei Baowei
Department of Bioengineering, The Univ. of Texas at Dallas, TX.
Dept. of Urology, University of Texas Southwestern Medical Center, Dallas, TX.
Proc SPIE Int Soc Opt Eng. 2020 Feb;11315. doi: 10.1117/12.2550593. Epub 2020 Mar 16.
Kidney biopsies are currently performed using preoperative imaging to identify the lesion of interest and intraoperative imaging used to guide the biopsy needle to the tissue of interest. Often, these are not the same modalities forcing the physician to perform a mental cross-modality fusion of the preoperative and intraoperative scans. This limits the accuracy and reproducibility of the biopsy procedure. In this study, we developed an augmented reality system to display holographic representations of lesions superimposed on a phantom. This system allows the integration of preoperative CT scans with intraoperative ultrasound scans to better determine the lesion's real-time location. An automated deformable registration algorithm was used to increase the accuracy of the holographic lesion locations, and a magnetic tracking system was developed to provide guidance for the biopsy procedure. Our method achieved a targeting accuracy of 2.9 ± 1.5 mm in a renal phantom study.
目前，肾活检采用术前成像来识别感兴趣的病变，并使用术中成像来引导活检针到达感兴趣的组织。通常，这些并非相同的模态，这迫使医生在脑海中对术前和术中扫描进行跨模态融合。这限制了活检程序的准确性和可重复性。在本研究中，我们开发了一种增强现实系统，以显示叠加在体模上的病变全息表示。该系统允许将术前CT扫描与术中超声扫描相结合，以更好地确定病变的实时位置。使用自动可变形配准算法来提高全息病变位置的准确性，并开发了一种磁跟踪系统为活检程序提供指导。在肾脏体模研究中，我们的方法实现了2.9±1.5毫米的靶向精度。
