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宫颈癌 T2 及弥散加权 MRI 中的体积勾画:观察者间体积勾画的一致性。

Volume Delineation in Cervical Cancer With T2 and Diffusion-weighted MRI: Agreement on Volumes Between Observers.

机构信息

Department of Radiation Oncology, SS. Annunziata Hospital, G. D'Annunzio University, Chieti, Italy

Department of Neuroscience, Imaging and Clinical Sciences, G. D'Annunzio University, Chieti, Italy.

出版信息

In Vivo. 2020 Jul-Aug;34(4):1981-1986. doi: 10.21873/invivo.11995.

DOI:10.21873/invivo.11995
PMID:32606170
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7439893/
Abstract

AIM

To delineate cervical cancer gross tumor volume (GTV) on T2-magnetic resonance imaging (MRI) and apparent diffusion coefficient (ADC) maps, assessing volumes and inter-observer agreement between two observers.

PATIENTS AND METHODS

A radiologist and a radiation oncologist delineated GTV on T2 (T2) and ADC (ADC) sequences. Dice similarity index (DICE) and Bland-Altman analysis were used to estimated concordance.

RESULTS

Mean T2 and ADC volumes were 43.84±71.47 cc and 37.28±68.92 cc according to the radiologist, and 43.4±70.44 cc and 36.65±69.21 cc according to the radiation oncologist. ADC led to statistically significantly smaller volumes compared to T2. The mean DICE index was 0.86 for T2 and 0.84 for ADC The Bland-Altman plots globally showed concordance.

CONCLUSION

GTV delineation was smaller in the ADC maps compared to T2-MRI, reaching an almost perfect agreement between observers. Thanks to this acceptable variability, adding functional imaging might provide more information for tumor delineation, improving reproducibility for image-guided adaptive radiotherapy.

摘要

目的

在 T2 磁共振成像(MRI)和表观扩散系数(ADC)图上描绘宫颈癌大体肿瘤体积(GTV),评估两位观察者之间的体积和观察者间一致性。

患者和方法

一名放射科医生和一名放射肿瘤学家在 T2(T2)和 ADC(ADC)序列上描绘 GTV。使用 Dice 相似性指数(DICE)和 Bland-Altman 分析来估计一致性。

结果

根据放射科医生的测量,T2 和 ADC 的平均体积分别为 43.84±71.47cc 和 37.28±68.92cc,根据放射肿瘤学家的测量,T2 和 ADC 的平均体积分别为 43.4±70.44cc 和 36.65±69.21cc。与 T2 相比,ADC 导致的体积明显更小。T2 的平均 DICE 指数为 0.86,ADC 为 0.84。Bland-Altman 图总体上显示出一致性。

结论

与 T2-MRI 相比,ADC 图上的 GTV 描绘更小,观察者之间达到几乎完美的一致性。由于这种可接受的变异性,添加功能成像可能为肿瘤描绘提供更多信息,提高图像引导自适应放疗的可重复性。