Thayer School of Engineering, Dartmouth College, Hanover, NH, USA.
Med Phys. 2012 Dec;39(12):7540-52. doi: 10.1118/1.4767758.
Accurate patient registration is crucial for effective image-guidance in open cranial surgery. Typically, it is accomplished by matching skin-affixed fiducials manually identified in the operating room (OR) with their counterparts in the preoperative images, which not only consumes OR time and personnel resources but also relies on the presence (and subsequent fixation) of the fiducials during the preoperative scans (until the procedure begins). In this study, the authors present a completely automatic, volumetric image-based patient registration technique that does not rely on fiducials by registering tracked (true) 3D ultrasound (3DUS) directly with preoperative magnetic resonance (MR) images.
Multistart registrations between binary 3DUS and MR volumes were first executed to generate an initial starting point without incorporating prior information on the US transducer contact point location or orientation for subsequent registration between grayscale 3DUS and MR via maximization of either mutual information (MI) or correlation ratio (CR). Patient registration was then computed through concatenation of spatial transformations.
In ten (N = 10) patient cases, an average fiducial (marker) distance error (FDE) of 5.0 mm and 4.3 mm was achieved using MI or CR registration (FDE was smaller with CR vs MI in eight of ten cases), which are comparable to values reported for typical fiducial- or surface-based patient registrations. The translational and rotational capture ranges were found to be 24.0 mm and 27.0° for binary registrations (up to 32.8 mm and 36.4°), 12.2 mm and 25.6° for MI registrations (up to 18.3 mm and 34.4°), and 22.6 mm and 40.8° for CR registrations (up to 48.5 mm and 65.6°), respectively. The execution time to complete a patient registration was 12-15 min with parallel processing, which can be significantly reduced by confining the 3DUS transducer location to the center of craniotomy in MR before registration (an execution time of 5 min is achievable).
Because common features deep in the brain and throughout the surgical volume of interest are used, intraoperative fiducial-less patient registration is possible on-demand, which is attractive in cases where preoperative patient registration is compromised (e.g., from loss∕movement of skin-affixed fiducials) or not possible (e.g., in cases of emergency when external fiducials were not placed in time). CR registration was more robust than MI (capture range about twice as big) and appears to be more accurate, although both methods are comparable to or better than fiducial-based registration in the patient cases evaluated. The results presented here suggest that 3DUS image-based patient registration holds promise for clinical application in the future.
准确的患者注册对于开放式颅脑手术中的有效图像引导至关重要。通常，这是通过将手术室（OR）中手动识别的贴附皮肤的基准与术前图像中的对应基准进行匹配来实现的，这不仅消耗了 OR 时间和人员资源，而且还依赖于基准在术前扫描期间的存在（并随后固定）（直到手术开始）。在这项研究中，作者提出了一种完全自动的、基于容积的患者注册技术，该技术不依赖于通过将跟踪的（真实的）3D 超声（3DUS）与术前磁共振（MR）图像直接注册来注册基准，而不依赖于术前的基准。
首先执行二进制 3DUS 和 MR 体积之间的多起点配准，以在不合并关于 US 换能器接触点位置或方向的先验信息的情况下生成初始起点，然后通过最大化互信息（MI）或相关比（CR）来进行灰度 3DUS 和 MR 之间的后续配准。然后通过空间变换的串联计算患者配准。
在十个（N=10）患者病例中，使用 MI 或 CR 配准分别实现了 5.0 毫米和 4.3 毫米的平均基准（标记）距离误差（FDE）（在十个病例中的八个中，CR 比 MI 的 FDE 更小），这与典型的基于基准或基于表面的患者配准报告的值相当。对于二进制配准，发现平移和旋转捕获范围分别为 24.0 毫米和 27.0°（最大为 32.8 毫米和 36.4°），MI 配准的平移和旋转捕获范围分别为 12.2 毫米和 25.6°（最大为 18.3 毫米和 34.4°），而 CR 配准的平移和旋转捕获范围分别为 22.6 毫米和 40.8°（最大为 48.5 毫米和 65.6°）。使用并行处理完成患者配准的执行时间为 12-15 分钟，通过在注册前将 3DUS 换能器的位置限制在 MR 中的颅骨切开术中心，可以显著减少执行时间（可以实现 5 分钟的执行时间）。
由于使用了大脑深处和手术感兴趣区域内的常见特征，因此可以按需进行术中无基准的患者配准，这在术前患者配准受到影响（例如，由于皮肤贴附基准的丢失/移动）或不可能进行（例如，在紧急情况下，由于没有及时放置外部基准）的情况下很有吸引力。CR 配准比 MI 更稳健（捕获范围大约大一倍），并且似乎更准确，尽管这两种方法在评估的患者病例中都与基于基准的配准相当或更好。这里提出的结果表明，基于 3DUS 的患者注册具有在未来临床应用中的潜力。
