A New Method for Improved Targeting in Image-guided Abdominal Interventions

描述（由申请人提供）： 这是一项R 01赠款申请，为期五年，用于应用新的先进图像分析技术，并引入技术，以提高CT引导干预的靶向性。CT是目前在美国用于引导活检和肿瘤消融的最常见的成像模式。大多数肝脏肿瘤，如肝细胞癌，在手术前获得的对比增强CT或MRI上可见。然而，这些肿瘤在手术过程中获得的非增强CT图像上可能看不到或边缘明显性差。这可能会增加手术时间，和/或导致非诊断性细胞病理学评估，需要重复活检或次优消融施源器放置。我们的目标是通过将高分辨率术前图像与低质量术中图像配准来增强介入放射科医生可用的当前信息。术前图像上可见的解剖细节（包括肿瘤边缘）将叠加在术中图像上。因此，消融施加器和活检针的精确位置将相对于出现在程序前扫描上的肿瘤的真实的轮廓来估计。非刚性配准被证明是一种技术，即使在器官运动的存在下，也能以良好的精度实现图像对准。然而，到目前为止，它还没有被用于在临床套件中的CT引导的介入期间融合术前和术中数据，因为它需要大量的计算基础设施，并且这些方法通常不够鲁棒。我们已经开发了一种新的非刚性配准方法的生物力学模型的基础上，在图像引导神经外科领域的前瞻性研究中进行了验证。最近，这项新技术也在RFA患者的回顾性数据中得到了验证。术前MRI和未增强术中CT图像在5分钟内对齐，精度为2 mm。本提案旨在证明该技术在影像引导腹部介入期间在介入放射学套件中的可行性，而不会影响医疗决策。我们对活检和消融的预测将与术后MRI上的组织学结果和消融面积进行比较。在评估结果时，将采用数学方法和两名独立放射科医生对结果的目视检查。成功与否取决于非刚性配准算法的准确性、稳健性和执行时间。该提案将通过开发和评估关键技术，使图像引导活检和消融期间的导航增强，从而有益于公共卫生。在整个手术过程中可视化肿瘤和肿瘤边缘的能力将更好地使介入放射科医生能够实现更好的诊断，并使整个肿瘤块凝固坏死，而不会出现意外的部位效应。 公共卫生相关性： 这项工作将导致新技术的精确定位在CT引导的干预。这些技术将有助于更好地诊断和治疗肝肿瘤，使介入放射科医生能够更准确地放置（i）活检针和（ii）消融施源器，因此，它们可以（i）提高检测小肿瘤的特异性，（ii）实现完全的肿瘤消融，降低切除肿瘤附近健康肝组织的风险。

DESCRIPTION (provided by applicant): This is an R01 grant application for five years of funding to apply novel advanced image analysis techniques and introducing technology that would improve the targeting in CT guided interventions. CT is currently in the United States the most common imaging modality used to guide biopsy and tumor ablation. The majority of liver tumors such as hepatocellular carcinomas are visible on contrast-enhanced CT or MRI obtained prior to the procedure. Yet, these tumors may not be seen or may have poor margin conspicuity on unenhanced CT images acquired during the procedure. This may increase the procedure time, and/or lead to non-diagnostic cytopathologic assessment, requiring repeat biopsy or sub-optimal ablation applicator placement. We aim to enhance the current information available to the interventional radiologist, by registering the high-resolution pre-procedural images with low quality intra-procedural images. Anatomical details (including the tumor margin) visible on the pre-procedural images will be superimposed on the intra- procedural images. The precise position of ablation applicator and biopsy needle would be thus estimated with respect to the real contour of the tumor as appearing on the pre-procedural scan. Non-rigid registration is demonstrated as a technology to achieve alignment of images with good accuracy, even in the presence of organ motion. However, up to date it has not been used for fusing pre- and intra- procedural data during CT guided interventions in a clinical suite, since it requires significant computational infrastructure and often these methods are not sufficient robust. We have developed a new non-rigid registration method based on biomechanical model, validated in a prospective study in the area of image-guide neurosurgery. Recently, this new technique is also validated on retrospective data from RFA patients. Pre-procedural MRI and unenhanced intra-procedural CT images are aligned within 5 minutes, with 2mm accuracy. This proposal aims to demonstrate the feasibility of this technology in an interventional radiology suite during image-guided abdominal interventions, without impact on the medical decision. Our predictions for biopsy and ablation will be compared with the histological findings and ablated area on post- procedural MRI. Both mathematical methods and visual inspection by two independent radiologists of results will be employed in assessing the results. The success will be determined by the accuracy, robustness, execution time of the non-rigid registration algorithms. This proposal will benefit public health by developing and assessing key technologies to enable enhanced navigation during the image guided biopsy and ablation. The capacity to visualize the tumor and tumor margin throughout the procedure will better enable the interventional radiologists to achieve better diagnosis, and coagulation necrosis for the entire tumor mass, without unexpected site effects. PUBLIC HEALTH RELEVANCE: This work will lead to new technologies for precise targeting in CT guided interventions. These technologies will facilitate better diagnosis and treatment of liver neoplasms, by enabling the interventional radiologists to more accurately place (i) the biopsy needle and (ii) the ablation applicator, and so, they can (i) improve the specificity in detecting even small tumors and (ii) achieve complete tumor ablation with less risk of removing healthy liver tissue located adjacent to the tumor.