Tsujikawa Tetsuya, Yamamoto Makoto, Shono Kunihiro, Yamada Shizuka, Tsuyoshi Hideaki, Kiyono Yasushi, Kimura Hirohiko, Okazawa Hidehiko, Yoshida Yoshio
Biomedical Imaging Research Center, University of Fukui, 23-3 Matsuoka-Shimoaizuki, Eiheiji-cho, Fukui, 910-1193, Japan.
Department of Obstetrics and Gynecology, Faculty of Medical Sciences, University of Fukui, Fukui, Japan.
Ann Nucl Med. 2017 Dec;31(10):752-757. doi: 10.1007/s12149-017-1208-x. Epub 2017 Sep 13.
The aim of this study was to retrospectively evaluate the clinical significance of F-FDG PET/CT textural features for discriminating uterine sarcoma from leiomyoma.
Fifty-five patients with suspected uterine sarcoma based on ultrasound and MRI findings who underwent pretreatment F-FDG PET/CT were included. Fifteen patients were histopathologically proven to have uterine sarcoma, 14 patients by surgical operation and one by biopsy, and 40 patients were diagnosed with leiomyoma by surgical operation or in a follow-up for at least 2 years. A texture analysis was performed on PET/CT images from which second- and higher order textural features were extracted in addition to standardized uptake values (SUVs) and other first-order features. The accuracy of PET features for differentiating between uterine sarcoma and leiomyoma was evaluated using a receiver-operating-characteristic (ROC) analysis.
The intratumor distribution of F-FDG was more heterogeneous in uterine sarcoma than in leiomyoma. Entropy, correlation, and uniformity calculated from normalized gray-level co-occurrence matrices and SUV standard deviation derived from histogram statistics showed greater area under the ROC curves (AUCs) than did maximum SUV for differentiating between sarcoma and leiomyoma. Entropy, as a single feature, yielded the greatest AUC of 0.974 and the optimal cut-off value of 2.85 for entropy provided 93% sensitivity, 90% specificity, and 92% accuracy. When combining conventional features with textural ones, maximum SUV (cutoff: 6.0) combined with entropy (2.85) and correlation (0.73) provided the best diagnostic performance (100% sensitivity, 94% specificity, and 95% accuracy).
In combination with the conventional histogram statistics and/or volumetric parameters, F-FDG PET/CT textural features reflecting intratumor metabolic heterogeneity are useful for differentiating between uterine sarcoma and leiomyoma.
本研究旨在回顾性评估F-FDG PET/CT纹理特征在鉴别子宫肉瘤和平滑肌瘤方面的临床意义。
纳入55例基于超声和MRI检查结果怀疑子宫肉瘤且接受了治疗前F-FDG PET/CT检查的患者。15例经组织病理学证实患有子宫肉瘤,其中14例通过手术,1例通过活检;40例经手术或至少2年随访诊断为平滑肌瘤。对PET/CT图像进行纹理分析,除标准化摄取值(SUV)和其他一阶特征外,还提取了二阶及更高阶纹理特征。使用受试者操作特征(ROC)分析评估PET特征区分子宫肉瘤和平滑肌瘤的准确性。
子宫肉瘤中F-FDG的瘤内分布比平滑肌瘤更不均匀。从归一化灰度共生矩阵计算得出的熵、相关性和均匀性,以及从直方图统计得出的SUV标准差,在区分肉瘤和平滑肌瘤方面,其ROC曲线下面积(AUC)均大于最大SUV。熵作为单一特征,AUC最大为0.974,熵的最佳截断值为2.85时,敏感性为93%,特异性为90%,准确性为92%。当将传统特征与纹理特征相结合时,最大SUV(截断值:6.0)与熵(2.85)和相关性(0.73)相结合提供了最佳诊断性能(敏感性100%,特异性94%,准确性95%)。
结合传统的直方图统计和/或体积参数,反映瘤内代谢异质性的F-FDG PET/CT纹理特征有助于鉴别子宫肉瘤和平滑肌瘤。