Department of Mathematics and Statistics, Georgia State University, Atlanta, 30303, GA, USA.
Department of Computer Science, Stony Brook University, Stony Brook, 11794, NY, USA.
Comput Biol Med. 2022 Aug;147:105764. doi: 10.1016/j.compbiomed.2022.105764. Epub 2022 Jun 25.
Prevalently considered as the "gold-standard" for diagnosis of hepatic fibrosis and cirrhosis, the clinical liver needle biopsy is known to be subject to inadequate sampling and a high mis-sampling rate. However, quantifying such sampling bias has been difficult as generating a large number of needle biopsies from the same living patient is practically infeasible. We construct a three-dimension (3D) virtual liver tissue volume by spatially registered high resolution Whole Slide Images (WSIs) of serial liver tissue sections with a novel dynamic registration method. We further develop a Virtual Needle Biopsy Sampling (VNBS) method that mimics the needle biopsy sampling process. We apply the VNBS method to the reconstructed digital liver volume at different tissue locations and angles. Additionally, we quantify Collagen Proportionate Area (CPA) in all resulting virtual needle biopsies in 2D and 3D.
The staging score of the center 2D longitudinal image plane from each 3D biopsy is used as the biopsy staging score, and the highest staging score of all sampled needle biopsies is the diagnostic staging score. The Mean Absolute Difference (MAD) in reference to the Scheuer and Ishak diagnostic staging scores are 0.22 and 1.00, respectively. The absolute Scheuer staging score difference in 22.22% of sampled biopsies is 1. By the Ishak staging method, 55.56% and 22.22% of sampled biopsies present score difference 1 and 2, respectively. There are 4 (Scheuer) and 6 (Ishak) out of 18 3D virtual needle biopsies with intra-needle variations. Additionally, we find a positive correlation between CPA and fibrosis stages by Scheuer but not Ishak method. Overall, CPA measures suffer large intra- and inter- needle variations.
The developed virtual liver needle biopsy sampling pipeline provides a computational avenue for investigating needle biopsy sampling bias with 3D virtual tissue volumes. This method can be applied to other tissue-based disease diagnoses where the needle biopsy sampling bias substantially affects the diagnostic results.
作为诊断肝纤维化和肝硬化的“金标准”，临床肝穿刺活检被认为存在采样不足和高误采率的问题。然而，由于从同一个活体患者身上生成大量的肝穿刺活检样本在实际上是不可行的，因此很难量化这种采样偏差。我们通过一种新的动态注册方法，对连续肝组织切片的高分辨率全切片图像（WSI）进行空间配准，构建了一个三维（3D）虚拟肝脏组织体积。我们进一步开发了一种虚拟肝穿刺活检采样（VNBS）方法，模拟肝穿刺活检采样过程。我们将 VNBS 方法应用于不同组织位置和角度的重建数字肝体积。此外，我们在 2D 和 3D 中对所有虚拟肝穿刺活检样本的胶原比例面积（CPA）进行量化。
每个 3D 活检的中心 2D 纵向图像平面的分期评分被用作活检分期评分，所有采样肝穿刺活检的最高分期评分被用作诊断分期评分。参考 Scheuer 和 Ishak 诊断分期评分，平均绝对差（MAD）分别为 0.22 和 1.00。在采样活检中，22.22%的活检绝对 Scheuer 分期评分差异为 1。按照 Ishak 分期方法，55.56%和 22.22%的采样活检的评分差异分别为 1 和 2。在 18 个 3D 虚拟肝穿刺活检中有 4 个（Scheuer）和 6 个（Ishak）出现针内变化。此外，我们发现通过 Scheuer 方法，CPA 与纤维化分期呈正相关，但 Ishak 方法则不然。总的来说，CPA 测量值存在较大的针内和针间变化。
所开发的虚拟肝穿刺活检采样管道为使用 3D 虚拟组织体积研究肝穿刺活检采样偏差提供了一种计算方法。该方法可应用于其他基于组织的疾病诊断，其中肝穿刺活检采样偏差对诊断结果有很大影响。
