A Proof-of-Concept Solution for Co-locating 2D Histology Images in 3D for Histology-to-CT and MR Image Registration: Closing the Loop for Bone Sarcoma Treatment Planning.

Robert Phillips, Constantine Zakkaroff, Keren Dittmer, Nicholas Robilliard, Kenzie Baer, Anthony Butler
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Abstract

This work presents a proof-of-concept solution designed to facilitate more accurate radiographic feature characterisation in pre-surgical CT/MR volumes. The solution involves 3D co-location of 2D digital histology slides within ex-vivo, tumour tissue CT volumes. Initially, laboratory dissection measurements seed the placement of histology slices in corresponding CT volumes, followed by in-plane point-based registration of bone in histology images to the bone in CT. Validation using six bisected canine humerus ex-vivo CT datasets indicated a plane misalignment of 0.19 ± 1.8 mm. User input sensitivity was assessed at 0.08 ± 0.2 mm for plane translation and 0-1.6° deviation. These results show a similar magnitude of error to related prostate histology co-location work. Although demonstrated with a femoral canine sarcoma tumour, this solution can be generalised to various orthopaedic geometries and sites. It supports high-fidelity histology image co-location to improve understanding of tissue characterisation accuracy in clinical radiology. This solution requires only minimal adjustment to routine workflows. By integrating histology insights earlier in the presentation-diagnosis-planning-surgery-recovery loop, this solution guides data co-location to support the continued evaluation of safe pre-surgical margins.

用于组织- ct和MR图像配准的2D组织学图像在3D中共定位的概念验证解决方案:闭合骨肉瘤治疗计划的循环。
这项工作提出了一种概念验证解决方案,旨在促进术前CT/MR体积中更准确的放射学特征表征。该解决方案涉及在离体肿瘤组织CT体积内的2D数字组织学切片的3D共定位。最初,实验室解剖测量将组织切片放置在相应的CT体积中,然后将组织图像中的骨与CT中的骨进行平面内点配准。使用6个犬肱骨离体CT数据集进行验证,显示平面偏差为0.19±1.8 mm。用户输入灵敏度评估为0.08±0.2 mm平面平移和0-1.6°偏差。这些结果显示了与相关前列腺组织学共定位工作相似的误差幅度。虽然在股骨犬肉瘤肿瘤中得到证实,但该方法可以推广到各种骨科几何形状和部位。它支持高保真组织学图像共定位,以提高对临床放射学中组织表征准确性的理解。这个解决方案只需要对日常工作流程进行最小的调整。通过在早期的表现-诊断-计划-手术-恢复循环中整合组织学见解,该解决方案指导数据协同定位,以支持安全手术前边缘的持续评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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