Division of Urologic Oncology, New York University Langone Medical Center, New York, NY, USA; Department of Urology and Renal Transplantation, Côte de Nacre University Hospital, Caen, France; CNRS, UMR 6301 ISTCT, CERVOxy Group, GIP CYCERON, France; CEA, DSV/I2BM, UMR 6301 ISTCT, France; UNICAEN, UMR 6301 ISTCT, F-14074 Caen, France; Normandie University, France.
Clin Radiol. 2013 Dec;68(12):e652-8. doi: 10.1016/j.crad.2013.07.010. Epub 2013 Aug 28.
To assess a novel method of three-dimensional (3D) co-registration of prostate cancer digital histology and in-vivo multiparametric magnetic resonance imaging (mpMRI) image sets for clinical usefulness.
A software platform was developed to achieve 3D co-registration. This software was prospectively applied to three patients who underwent radical prostatectomy. Data comprised in-vivo mpMRI [T2-weighted, dynamic contrast-enhanced weighted images (DCE); apparent diffusion coefficient (ADC)], ex-vivo T2-weighted imaging, 3D-rebuilt pathological specimen, and digital histology. Internal landmarks from zonal anatomy served as reference points for assessing co-registration accuracy and precision.
Applying a method of deformable transformation based on 22 internal landmarks, a 1.6 mm accuracy was reached to align T2-weighted images and the 3D-rebuilt pathological specimen, an improvement over rigid transformation of 32% (p = 0.003). The 22 zonal anatomy landmarks were more accurately mapped using deformable transformation than rigid transformation (p = 0.0008). An automatic method based on mutual information, enabled automation of the process and to include perfusion and diffusion MRI images. Evaluation of co-registration accuracy using the volume overlap index (Dice index) met clinically relevant requirements, ranging from 0.81-0.96 for sequences tested. Ex-vivo images of the specimen did not significantly improve co-registration accuracy.
This preliminary analysis suggests that deformable transformation based on zonal anatomy landmarks is accurate in the co-registration of mpMRI and histology. Including diffusion and perfusion sequences in the same 3D space as histology is essential further clinical information. The ability to localize cancer in 3D space may improve targeting for image-guided biopsy, focal therapy, and disease quantification in surveillance protocols.
评估一种新的前列腺癌数字组织学与体内多参数磁共振成像（mpMRI）图像集三维（3D）配准方法的临床实用性。
开发了一种软件平台来实现 3D 配准。该软件前瞻性地应用于 3 例接受根治性前列腺切除术的患者。数据包括体内 mpMRI（T2 加权、动态对比增强加权图像（DCE）；表观扩散系数（ADC））、离体 T2 加权成像、3D 重建病理标本和数字组织学。区域解剖学的内部标志作为评估配准准确性和精度的参考点。
应用基于 22 个内部标志的变形变换方法，达到了 T2 加权图像与 3D 重建病理标本配准的 1.6 毫米精度，比刚性变换提高了 32%（p=0.003）。22 个区域解剖学标志使用变形变换比刚性变换更准确地映射（p=0.0008）。基于互信息的自动方法能够实现该过程的自动化，并包括灌注和扩散 MRI 图像。使用体积重叠指数（Dice 指数）评估配准精度，满足临床相关要求，所测试的序列范围为 0.81-0.96。标本的离体图像并未显著提高配准精度。
初步分析表明，基于区域解剖学标志的变形变换在 mpMRI 和组织学配准中具有较高的准确性。将扩散和灌注序列与组织学一起包含在同一 3D 空间中是提供进一步临床信息的关键。在 3D 空间中定位癌症的能力可能会改善图像引导活检、局灶性治疗和监测方案中疾病定量的靶向性。
