Sahovaler Axel, Daly Michael J, Chan Harley H L, Nayak Prakash, Tzelnick Sharon, Arkhangorodsky Michelle, Qiu Jimmy, Weersink Robert, Irish Jonathan C, Ferguson Peter, Wunder Jay S
Guided Therapeutics (GTx) Program, TECHNA Institute, University Health Network, Toronto, Ontario, Canada.
Head & Neck Surgery Unit, University College London Hospitals, London, United Kingdom.
JB JS Open Access. 2022 May 5;7(2). doi: 10.2106/JBJS.OA.21.00140. eCollection 2022 Apr-Jun.
Computer-assisted surgery (CAS) can improve surgical precision in orthopaedic oncology. Accurate alignment of the patient's imaging coordinates with the anatomy, known as registration, is one of the most challenging aspects of CAS and can be associated with substantial error. Using intraoperative, on-the-table, cone-beam computed tomography (CBCT), we performed a pilot clinical study to validate a method for automatic intraoperative registration.
Patients who were ≥18 years of age, had benign bone tumors, and underwent resection were prospectively enrolled. In addition to inserting a navigation tracking tool into the exposed bone adjacent to the surgical field, 2 custom plastic ULTEM tracking tools (UTTs) were attached to each patient's skin adjacent to the tumor using an adhesive. These were automatically localized within the 3-dimensional CBCT volume to be used as image landmarks for registration, and the corresponding tracker landmarks were captured using an infrared camera. The main outcomes were the fiducial registration error (FRE) and the target registration error (TRE). The navigation time was recorded.
Thirteen patients with benign tumors in the femur (n = 10), tibia (n = 2), and humerus (n = 1) underwent navigation-assisted resections. The mean values were 0.67 ± 0.15 mm (range, 0.47 to 0.97 mm) for FRE and 0.83 ± 0.51 mm (range, 0.42 to 2.28 mm) for TRE. Registration was successful in all cases. The mean time for CBCT imaging and tracker registration was 7.5 minutes.
We present a novel automatic registration method for CAS exploiting intraoperative CBCT capabilities, which provided improved accuracy and reduced operative times compared with more traditional methods.
This proof-of-principle study validated a novel process for automatic registration to improve the accuracy of resecting bone tumors using a surgical navigation system.
计算机辅助手术（CAS）可提高骨肿瘤手术的精准度。将患者影像坐标与解剖结构精确对齐，即配准，是CAS最具挑战性的方面之一，且可能伴有显著误差。我们利用术中在手术台上进行的锥形束计算机断层扫描（CBCT）开展了一项初步临床研究，以验证一种自动术中配准方法。
前瞻性纳入年龄≥18岁、患有良性骨肿瘤且接受切除术的患者。除了在手术区域附近暴露的骨中插入导航跟踪工具外，还使用粘合剂将2个定制的塑料ULTEM跟踪工具（UTT）附着在每位患者肿瘤附近的皮肤上。这些工具在三维CBCT容积中自动定位，用作配准的图像标记，相应的跟踪器标记通过红外相机捕获。主要结果是基准配准误差（FRE）和目标配准误差（TRE）。记录导航时间。
13例股骨（n = 10）、胫骨（n = 2）和肱骨（n = 1）良性肿瘤患者接受了导航辅助切除术。FRE的平均值为0.67±0.15毫米（范围为0.47至0.97毫米），TRE的平均值为0.83±0.51毫米（范围为0.42至2.28毫米）。所有病例配准均成功。CBCT成像和跟踪器配准的平均时间为7.5分钟。
我们提出了一种利用术中CBCT功能的CAS新型自动配准方法，与更传统的方法相比，该方法提高了准确性并缩短了手术时间。
这项原理验证研究验证了一种新型自动配准过程，以提高使用手术导航系统切除骨肿瘤的准确性。
