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Resection-induced brain-shift compensation using vessel-based methods

机译：使用基于血管的方法切除诱导的脑移补偿

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Most brain-shift compensation methods address the problem of updating preoperative images to reflect brain deformations following the craniotomy and dura opening. However, fewer enable to take into account the resection-induced deformations occuring all along the tumor removal procedure. This paper evaluates the use of two existing methods to tackle that problem. Both techniques rely on blood vessels segmented then skeletonized from preoperative MR Angiography and navigated Doppler Ultrasound images acquired during resection. While the first one proposes to register the vascular trees using a rigid modified ICP algorithm, the second method relies on a non-rigid constrained-based biomechanical approach. Quantitative results are provided, based on distances between paired landmarks set on blood vessels then anatomical structures delineated on medical images. A qualitative evaluation of the compensation is also presented using initial and updated images. An analysis on three cases of surface tumor shows both methods, especially the biomechanical one, can compensate up to 63% of the brain-shift, with an error in the range of 2 mm. However, these results are not reproduced on a more complex case of deep tumor. While more patients must be included, these preliminary results show that vessel-based methods are well suited to compensate for resection-induced brain-shift, but better outcomes in complex cases still require to improve the methods to take the resection into account.
机译：大多数脑班补偿方法​​解决了更新术前图像的问题，以反映Craniotomy和Dura开口后的脑变形。然而，更少的能够考虑到沿肿瘤去除过程的切除诱导的变形。本文评估了使用两个现有方法来解决这个问题。两种技术依赖于血管分割，然后从术前MR血管造影和在切除期间获得的导航多普勒超声图像骨架。虽然第一个提出使用刚性修改的ICP算法注册血管树，但是第二种方法依赖于基于非刚性受限的生物力学方法。基于对血管上设置的配对地标之间的距离，提供定量结果，然后在医学图像上描绘的解剖结构。还使用初始和更新的图像呈现对补偿的定性评估。表面肿瘤三种情况分析表明，两种方法，尤其是生物力学，可以弥补高达63％的脑移，误差在2毫米的范围内。然而，这些结果不会在更复杂的深肿瘤中复制。虽然必须包括更多患者，但这些初步结果表明，血管基方法非常适合于补偿切除诱导的脑移，但复杂病例中的更好的结果仍然需要改善考虑切除的方法。

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