Department of Radiation Oncology, Center of Molecular Imaging and Experimental Radiotherapy, Université Catholique de Louvain, Brussels, Belgium.
Radiother Oncol. 2011 Jan;98(1):117-25. doi: 10.1016/j.radonc.2010.10.006. Epub 2010 Nov 11.
The aim of this study was to validate a gradient-based segmentation method for GTV delineation on FDG-PET in NSCLC through surgical specimen, in comparison with threshold-based approaches and CT.
Ten patients with stage I-II NSCLC were prospectively enrolled. Before lobectomy, all patients underwent contrast enhanced CT and gated FDG-PET. Next, the surgical specimen was removed, inflated with gelatin, frozen and sliced. The digitized slices were used to reconstruct the 3D macroscopic specimen. GTVs were manually delineated on the macroscopic specimen and on CT images. GTVs were automatically segmented on PET images using a gradient-based method, a source to background ratio method and fixed threshold values at 40% and 50% of SUV(max). All images were finally registered. Analyses of raw volumes and logarithmic differences between GTVs and GTV(macro) were performed on all patients and on a subgroup excluding the poorly defined tumors. A matching analysis between the different GTVs was also conducted using Dice's similarity index.
Considering all patients, both lung and mediastinal windowed CT overestimated the macroscopy, while FDG-PET provided closer values. Among various PET segmentation methods, the gradient-based technique best estimated the true tumor volume. When analysis was restricted to well defined tumors without lung fibrosis or atelectasis, the mediastinal windowed CT accurately assessed the macroscopic specimen. Finally, the matching analysis did not reveal significant difference between the different imaging modalities.
FDG-PET improved the GTV definition in NSCLC including when the primary tumor was surrounded by modifications of the lung parenchyma. In this context, the gradient-based method outperformed the threshold-based ones in terms of accuracy and robustness. In other cases, the conventional mediastinal windowed CT remained appropriate.
本研究旨在通过手术标本验证一种基于梯度的 NSCLC 肿瘤体积（GTV）勾画方法，与基于阈值的方法和 CT 进行比较。
前瞻性纳入 10 例 I-II 期非小细胞肺癌（NSCLC）患者。在肺叶切除术前，所有患者均行增强 CT 和门控 FDG-PET 检查。随后，切除手术标本，用明胶充气、冷冻并切片。对数字化切片进行 3D 重建以构建宏观标本。在宏观标本和 CT 图像上手动勾画 GTV。在 PET 图像上，使用基于梯度的方法、源与背景比方法以及 SUV(max)的 40%和 50%固定阈值自动分割 GTV。所有图像最终均进行了配准。对所有患者和排除边界不清晰肿瘤的亚组患者进行了 GTV 原始体积和 GTV（大体）对数差的分析。还使用 Dice 相似性指数对不同 GTV 之间进行了匹配分析。
考虑所有患者，肺窗和纵隔窗 CT 均高估了大体肿瘤，而 FDG-PET 则提供了更接近的数值。在各种 PET 分割方法中，基于梯度的技术最能准确估计肿瘤的真实体积。当分析仅限于无肺纤维化或肺不张的边界清晰的肿瘤时，纵隔窗 CT 准确评估了大体标本。最后，匹配分析未显示不同成像方式之间存在显著差异。
FDG-PET 改善了 NSCLC 的 GTV 定义，包括原发性肿瘤周围伴有肺实质改变的情况。在此背景下，基于梯度的方法在准确性和稳健性方面优于基于阈值的方法。在其他情况下，传统的纵隔窗 CT 仍然适用。
