上海交通大学学报（医学版）

上海交通大学学报(医学版) ›› 2020, Vol. 40 ›› Issue (10): 1408-1413.doi: 10.3969/j.issn.1674-8115.2020.10.019

• 论著·临床研究 • 上一篇    下一篇

3D打印切片盒在骨盆肿瘤边界三维定位中的应用初探

李小敏1，曲 扬1，武 文2，赵 亮3，张少霆3，郝永强2，戴尅戎2，艾松涛1   

  1. 1. 上海交通大学医学院附属第九人民医院放射科，上海 200011；2. 上海交通大学医学院附属第九人民医院骨科，上海 200011; 3. 上海商汤智能科技有限公司，上海 200030
  • 出版日期:2020-10-28 发布日期:2020-11-27
  • 通讯作者: 艾松涛，电子信箱：ai.songtao@qq.com。
  • 作者简介:李小敏（1994—），女，硕士生；电子信箱：lxm549496172@163.com。
  • 基金资助:
    上海市科学技术委员会科研计划项目（19441902700，18441903100）；上海市教育委员会高峰高原学科建设计划（20152221）；上海交通大学医工交叉面上项目（YG2017MS03）。

Preliminary application of MR imaging-pathology co-localization by 3D printing box in pelvic tumor assessment

LI Xiao-min1, QU Yang1, WU Wen2, ZHAO Liang3, ZHANG Shao-ting3, HAO Yong-qiang2, DAI Ke-rong2, AI Song-tao1   

  1. 1. Department of Radiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China; 2. Department of Orthopedics, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China; 3. Shanghai SenseTime Intelligent Technology Co., Ltd, Shanghai 200030, China
  • Online:2020-10-28 Published:2020-11-27
  • Supported by:
    Scientific Research Project of Shanghai Science and Technology Commission (19441902700, 18441903100); Shanghai Municipal Education Commission—Gaofeng Clinical Medicine Grant Support (20152221); Shanghai Jiao Tong University Medical Engineering Cross Grant (YG2017MS03).

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摘要： 目的·探讨基于影像后处理及3D打印技术设计的个体化病理切片盒应用于骨盆肿瘤术前磁共振成像（magnetic resonance imaging，MRI）与三维病理图像共定位研究的可行性。方法·收集于2019年7月—2020年7月间以骨盆肿瘤收治并行半骨盆切除重建术的患者，术前及术后切除肿瘤标本行CT和MRI检查，以骨盆肿瘤的骨性结构为标志点，实现术前患者CT、MRI图像及术后肿瘤标本CT图像间的配准，设计个体化骨肿瘤病理切片盒并3D打印，指导病理大切片方向，并行苏木精-伊红染色，与术前肿瘤影像边界共定位比较。结果·5例骨盆肿瘤患者（软骨肉瘤3例、骨软骨瘤1例、浆细胞瘤1例），男4例，女1例，平均年龄（46.40±15.66）岁（26～65岁）。骨盆肿瘤累及范围Enneking分区：Ⅰ区1例、Ⅰ+Ⅱ区2例、Ⅰ+Ⅱ+Ⅲ区1例，累及股骨1例。肿瘤最大直径平均值为（13.96±2.42）cm。肿瘤标本在切片盒中贴合良好，完整获得肿瘤三维病理边界，并能与术前影像肿瘤边界共定位。平均每个切片盒重约2 500 g，成本约为人民币2 500元。结论·个体化3D打印病理切片盒可实现骨盆肿瘤的术前MRI边界和病理边界精确对应，获得完整术后三维病理信息，为进一步规范骨盆肿瘤诊疗和改善预后提供数据支持。

关键词: 磁共振成像, 3D打印, 骨盆肿瘤, 病理图像, 配准融合, 共定位

Abstract:

Objective · To explore the feasibility of applying patient-specific pathological section boxes based on image post-processing and 3D printing technology to the study of correlating in vivo magnetic resonance imaging (MRI) with whole mount histology of the pelvic tumors. Methods · Patients who were with pelvic tumor and underwent pelvic tumor resection from July 2019 to July 2020 were enrolled. CT and MRI were performed in both patients and postoperative tumor specimens. The skeletal anatomical landmarks were used to achieve the registration between the preoperative CT, MRI images and the postoperative CT images, and the patient-specific pathological section boxes were designed and printed, which was to ensure the consistency between in vivo MRI images and postoperative pathological images. Then, the whole pelvic tumors were stained with hematoxylin-eosin staining with the whole mount section technique to obtain the pathological boundaries. Results · A total of 5 cases with bone tumors (3 chondrosarcoma, 1 osteochondroma, and 1 plasmacytoma; 4 males and 1 female) were included in this study with an average age of (46.40±15.66) years (26–65 years). According to the Enneking's classification, there were 1 in typeⅠ, 2 in typeⅠ+Ⅱ, and 1 in typeⅠ+Ⅱ+Ⅲ. The mean maximum tumor diameter was (13.96±2.42) cm. The tumor specimens within the 3D box were adequately fitted in all tumors. The pathological boundary can be completely obtained. Distinct in vivo image features corresponded to unique pathologic characteristics in the same tumor. The average weight of each box was about 2 500 g, and the average cost was about 2 500 yuan. Conclusion · The patient-specific 3D printing pathological section box can effectively achieve the co-localization between the in vivo MRI and pathology images of pelvic tumors, which will have great value in understanding the correlation between MRI and pathology images and can provide support for further standardizing the diagnosis and treatment of pelvic tumors and improving the prognosis.

Key words: magnetic resonance imaging (MRI), 3D printing, pelvic tumor, pathology image, registration fusion, co-localization

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