Using neighborhood gray tone difference matrix texture features on dual time point PET/CT images to differentiate malignant from benign FDG-avid solitary pulmonary nodules
Using neighborhood gray tone difference matrix texture features on dual time point PET/CT images to differentiate malignant from benign FDG-avid solitary pulmonary nodules
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DOI：
10.1186/s40644-019-0243-3
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发表时间：
2019-08-16
期刊：
影响因子：
4.9
通讯作者：
Jeraj, Robert
中科院分区：
文献类型：
--
作者：
Chen, Song;Harmon, Stephanie;Jeraj, Robert
目的肺癌早期影像学表现为孤立性肺结节（SPN）。由于肺癌的早期诊断对治疗非常重要，因此对孤立性肺结节的准确诊断非常重要。本研究的目的是评估双时间点成像（DTPI）PET/CT的鉴别能力的恶性和良性FDG-亲孤立性肺结节使用相邻灰度差异矩阵（NGTDM）纹理特征。方法回顾性分析2005年1月至2015年5月间116例孤立性肺结节患者（良性35例，恶性81例）的DTPI F-18-FDG PET/CT检查结果。在注射后1 h和3 h采集PET和CT图像。在双时间点图像上计算每个结节的SUVmax和NGTDM纹理特征（粗糙度、对比度和繁忙度）。患者被随机分为训练和验证数据集。对训练数据集中的所有纹理特征进行受试者工作特征（ROC）曲线分析，以计算区分恶性SPN和良性SPN的最佳阈值。对于测试数据集中的所有病变，由两名核医学医师基于PET/CT图像（参考和不参考纹理特征）确定两个视觉判读评分。结果在训练数据集中，延迟忙碌、延迟粗糙、早期忙碌和早期SUVmax的AUC分别为0.87、0.85、0.75和0.75。在验证数据集中，有和没有纹理特征的视觉解释的AUC分别为0.89和0.80。结论DTPI PET/CT图像的NGTDM纹理特征较SUVmax或目视判读更能预测SPN的恶性程度。通过增加从延迟PET/CT图像中提取的繁忙度，可以改善使用SUVmax和视觉解释区分良性和恶性结节的效果。
Objective Lung cancer usually presents as a solitary pulmonary nodule (SPN) on diagnostic imaging during the early stages of the disease. Since the early diagnosis of lung cancer is very important for treatment, the accurate diagnosis of SPNs has much importance. The aim of this study was to evaluate the discriminant power of dual time point imaging (DTPI) PET/CT in the differentiation of malignant and benign FDG-avid solitary pulmonary nodules by using neighborhood gray-tone difference matrix (NGTDM) texture features. Methods Retrospective analysis was carried out on 116 patients with SPNs (35 benign and 81 malignant) who had DTPI F-18-FDG PET/CT between January 2005 and May 2015. Both PET and CT images were acquired at 1 h and 3 h after injection. The SUVmax and NGTDM texture features (coarseness, contrast, and busyness) of each nodule were calculated on dual time point images. Patients were randomly divided into training and validation datasets. Receiver operating characteristic (ROC) curve analysis was performed on all texture features in the training dataset to calculate the optimal threshold for differentiating malignant SPNs from benign SPNs. For all the lesions in the testing dataset, two visual interpretation scores were determined by two nuclear medicine physicians based on the PET/CT images with and without reference to the texture features. Results In the training dataset, the AUCs of delayed busyness, delayed coarseness, early busyness, and early SUVmax were 0.87, 0.85, 0.75 and 0.75, respectively. In the validation dataset, the AUCs of visual interpretations with and without texture features were 0.89 and 0.80, respectively. Conclusion Compared to SUVmax or visual interpretation, NGTDM texture features derived from DTPI PET/CT images can be used as good predictors of SPN malignancy. Improvement in discriminating benign from malignant nodules using SUVmax and visual interpretation can be achieved by adding busyness extracted from delayed PET/CT images.