Zhuang Mingzan, Qiu Zhifen, Lou Yunlong
Department of Nuclear Medicine, Meizhou People's Hospital, Meizhou, China.
EJNMMI Phys. 2023 Mar 13;10(1):18. doi: 10.1186/s40658-023-00538-7.
The aim of this study is to explore the robustness and accuracy of consensus contours with 225 nasopharyngeal carcinoma (NPC) clinical cases and 13 extended cardio-torso simulated lung tumors (XCAT) based on 2-deoxy-2-[F]fluoro-D-glucose (F-FDG) PET imaging.
Primary tumor segmentation was performed with two different initial masks on 225 NPC F-FDG PET datasets and 13 XCAT simulations using methods of automatic segmentation with active contour, affinity propagation (AP), contrast-oriented thresholding (ST), and 41% maximum tumor value (41MAX), respectively. Consensus contours (ConSeg) were subsequently generated based on the majority vote rule. The metabolically active tumor volume (MATV), relative volume error (RE), Dice similarity coefficient (DSC) and their respective test-retest (TRT) metrics between different masks were adopted to analyze the results quantitatively. The nonparametric Friedman and post hoc Wilcoxon tests with Bonferroni adjustment for multiple comparisons were performed with 0.05 considered to be significant.
AP presented the highest variability for MATV in different masks, and ConSeg presented much better TRT performances in MATV compared with AP, and slightly poorer TRT in MATV compared with ST or 41MAXin most cases. Similar trends were also found in RE and DSC with the simulated data. The average of four segmentation results (AveSeg) showed better or comparable results in accuracy for most cases with respect to ConSeg. AP, AveSeg and ConSeg presented better RE and DSC in irregular masks as compared with rectangle masks. Additionally, all methods underestimated the tumour boundaries in relation to the ground truth for XCAT including respiratory motion.
The consensus method could be a robust approach to alleviate segmentation variabilities, but did not seem to improve the accuracy of segmentation results on average. Irregular initial masks might be at least in some cases attributable to mitigate the segmentation variability as well.
本研究旨在基于2-脱氧-2-[F]氟-D-葡萄糖（F-FDG）PET成像，通过225例鼻咽癌（NPC）临床病例和13例扩展型心肺模拟肺肿瘤（XCAT）来探讨一致性轮廓的稳健性和准确性。
分别使用主动轮廓自动分割法、亲和传播（AP）、对比度导向阈值法（ST）和41%最大肿瘤值法（41MAX），对225例NPC的F-FDG PET数据集和13例XCAT模拟数据采用两种不同的初始掩码进行原发肿瘤分割。随后根据多数投票规则生成一致性轮廓（ConSeg）。采用代谢活性肿瘤体积（MATV）、相对体积误差（RE）、骰子相似系数（DSC）及其各自的重测（TRT）指标对不同掩码之间的结果进行定量分析。采用非参数Friedman检验和事后Wilcoxon检验，并进行Bonferroni校正以进行多重比较，P<0.05被认为具有统计学意义。
在不同掩码中，AP在MATV方面表现出最高的变异性，与AP相比，ConSeg在MATV方面的TRT性能要好得多，在大多数情况下，与ST或41MAX相比，ConSeg在MATV方面的TRT性能略差。在RE和DSC方面，模拟数据也呈现出类似趋势。对于大多数情况，四种分割结果的平均值（AveSeg）在准确性方面显示出与ConSeg相当或更好的结果。与矩形掩码相比，AP、AveSeg和ConSeg在不规则掩码中呈现出更好的RE和DSC。此外，对于包括呼吸运动在内的XCAT，所有方法相对于真实情况均低估了肿瘤边界。
一致性方法可能是减轻分割变异性的一种稳健方法，但平均而言似乎并未提高分割结果的准确性。不规则的初始掩码在某些情况下至少也可能有助于减轻分割变异性。
