de Koning Klijs Jacob, Dankbaar Jan Willem, de Keizer Bart, Willemsen Koen, van der Toorn Annette, Breimer Gerben Eise, van Es Robert Jelle Johan, de Bree Remco, Noorlag Rob, Philippens Marielle Emile Petronella
Department of Head and Neck Surgical Oncology, University Medical Center Utrecht, Utrecht, Netherlands.
Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands.
Front Oncol. 2024 Mar 28;14:1342857. doi: 10.3389/fonc.2024.1342857. eCollection 2024.
This study explores the feasibility of ex-vivo high-field magnetic resonance (MR) imaging to create digital a three-dimensional (3D) representations of tongue cancer specimens, referred to as the "MR-based digital specimen" (MR-DS). The aim was to create a method to assist surgeons in identifying and localizing inadequate resection margins during surgery, a critical factor in achieving locoregional control.
Fresh resection specimens of nine tongue cancer patients were imaged in a 7 Tesla small-bore MR, using a high-resolution multislice and 3D T2-weighted Turbo Spin Echo. Two independent radiologists (R1 and R2) outlined the tumor and mucosa on the MR-images whereafter the outlines were configured to an MR-DS. A color map was projected on the MR-DS, mapping the inadequate margins according to R1 and R2. We compared the hematoxylin-eosin-based digital specimen (HE-DS), which is a histopathological 3D representation derived from HE stained sections, with its corresponding MR-images. In line with conventional histopathological assessment, all digital specimens were divided into five anatomical regions (anterior, posterior, craniomedial, caudolateral and deep central). Over- and underestimation 95-percentile Hausdorff-distances were calculated between the radiologist- and histopathologist-determined tumor outlines. The MR-DS' diagnostic accuracy for inadequate margin detection (i.e. sensitivity and specificity) was determined in two ways: with conventional histopathology and HE-DS as reference.
Using conventional histopathology as a reference, R1 achieved 77% sensitivity and 50% specificity, while R2 achieved 65% sensitivity and 57% specificity. When referencing to the HE-DS, R1 achieved 94% sensitivity and 61% specificity, while R2 achieved 88% sensitivity and 71% specificity. Range of over- and underestimation 95HD was 0.9 mm - 11.8 mm and 0.0 mm - 5.3 mm, respectively.
This proof of concept for volumetric assessment of resection margins using MR-DSs, demonstrates promising potential for further development. Overall, sensitivity is higher than specificity for inadequate margin detection, because of the radiologist's tendency to overestimate tumor size.
本研究探讨离体高场磁共振(MR)成像创建舌癌标本三维(3D)数字模型的可行性,该模型称为“基于MR的数字标本”(MR-DS)。目的是创建一种方法,以协助外科医生在手术过程中识别和定位切除边缘不足的情况,这是实现局部区域控制的关键因素。
对9例舌癌患者的新鲜切除标本在7特斯拉小口径MR中进行成像,使用高分辨率多层和3D T2加权快速自旋回波序列。两名独立的放射科医生(R1和R2)在MR图像上勾勒出肿瘤和黏膜轮廓,然后将轮廓构建成MR-DS。在MR-DS上投射一张彩色地图,根据R1和R2标记出边缘不足的区域。我们将基于苏木精-伊红染色的数字标本(HE-DS),即从HE染色切片得出的组织病理学3D模型,与其相应的MR图像进行比较。按照传统组织病理学评估方法,将所有数字标本分为五个解剖区域(前部、后部、颅内侧、尾外侧和深部中央)。计算放射科医生和病理科医生确定的肿瘤轮廓之间的高估和低估95%百分位豪斯多夫距离。MR-DS检测边缘不足的诊断准确性(即敏感性和特异性)通过两种方式确定:以传统组织病理学和HE-DS作为参考。
以传统组织病理学作为参考,R1的敏感性为77%,特异性为50%,而R2的敏感性为65%,特异性为57%。以HE-DS作为参考时,R1的敏感性为94%,特异性为61%,而R2的敏感性为88%,特异性为71%。高估和低估95HD的范围分别为0.9毫米至11.8毫米和0.0毫米至5.3毫米。
使用MR-DS对切除边缘进行容积评估的这一概念验证,显示出有进一步发展的潜力。总体而言,检测边缘不足时敏感性高于特异性,这是因为放射科医生有高估肿瘤大小的倾向。