| [1] |
Lambin P,Rios V E,Leijenaar R,et al.Radiomics:extracting more information from medical images using advanced feature analysis[J].Eur J Cancer,2012,48(4):441-446.
|
| [2] |
Miwa K,Inubushi M,Wagatsuma K,et al.FDG uptake heterogeneity evaluated by fractal analysis improves the differential diagnosis of pulmonary nodules[J].Eur J Radiol,2014,83(4):715-719.
|
| [3] |
Dhara A K,Mukhopadhyay S,Dutta A,et al.A combination of shape and texture features for classification of pulmonary nodules in lung CT images[J].J Digit Imaging,2016,29(4):466-475.
|
| [4] |
王 敏,宋 彬,黄子星,等.基于文献计量学的近5年放射组学研究热点分析[J].中华放射学杂志,2016,50(12):974-977.
|
| [5] |
Bae J M,Jeong J Y,Lee H Y,et al.Pathologic stratification of operable lung adenoearcinoma using radiomics features extracted from dual energy CT images[J].Oncotarget,2017,8(1):523-535.
|
| [6] |
刘文涓,王全师,吴湖炳,等.以18F-FDG PET-CT和临床信息为基础的孤立性肺结节诊断模型[J].中华核医学与分子影像杂志,2016,36(3):211-215.
|
| [7] |
张永学,兰晓莉.分子核医学与多模态影像[M].北京:人民卫生出版社,2019:627-628.
|
| [8] |
Krarup M K,Nygard L,Vogelius I R,et al.Heterogeneity in tumours:Validating the use of radiomic features on 18F-FDG PET-CT scans of lung cancer patients as a prognostic tool[J].Radiother Oncol,2020,144(1):72-78.
|
| [9] |
马 圆,陈斯鹏,田思佳,等.基于PET-CT图像纹理参数的肺结节诊断模型[J].北京生物医学工程,2017,36 (3):257-260.
|
| [10] |
朱 辉,汪秀玲,李智勇,等.18F-FDG PET-CT图像纹理分析在肺部肿块诊断中的临床价值[J].临床放射学杂志,2017,36(12):1766-1770.
|
| [11] |
Kirienko M,Cozzi L,Rossi A,et al.Ability of FDG PET and CT radiomics features to differentiate between primary and metastatic lung lesions[J].Eur J Nucl Med Mol Imaging,2018,45:1649-1660.
|
| [12] |
Kim Y I,Paeng J C,Park Y S,et al.Relation of EGFR mutation status to metabolic activity in localized lung adenocarcinoma and its influence on the use of FDG PET-CT parameters in prognosis[J].AJR Am J Roentgenol,2018,210:1346-1351.
|
| [13] |
Desseroit M C,Tixier F,Weber W A,et al.Reliability of PET-CT shape and heterogeneity features in functional and morphologic components of non-small cell lung cancer tumors:a repeatability analysis in a prospective multicenter cohort[J].Nucl Med,2017,58:406-11.
|
| [14] |
Saad M,Choi T.Deciphering unclassified tumors of non-small-cell lung cancer through radiomics[J].Comput Biol Med,2017,91:222-230.
|
| [15] |
Hyun S H,Ahn M S,Koh Y W,et al.A Machine-learning approach using PET-based radiomics to predict the histological subtypes of lung cancer[J].Clin Nucl Med,2019,44(12):956-960.
|
| [16] |
Bae J M,Jeong J Y,Lee H Y,et al.Pathologic stratification of operable lung adenoearcinoma using radiomics features extracted from dual energy CT images[J].Oncotarget,2017,8(1):523-535.
|
| [17] |
Yuan M,Zhang Y D,Pu X H,et al.Comparison of a radiomic biomarker with volumetric analysis for decoding tumour phenotypes of lung adenocarcinoma with different diseasespecific survival[J].Eur Radiol,2017,27(11):4857-4865.
|
| [18] |
Gomez L O,Garcia A M,Honguero A F,et al.Heterogeneity in 18Ffluorodeoxyglucose positron emission tomography/computed tomography of non-small cell lung carcinoma and its relationship to metabolic parametersand pathologic staging[J].Mol Imaging,2014,13(4):1072-1081.
|
| [19] |
Flechsig P,Frank P,Kratochwil C,et al.Radiomic analysis using density threshold for FDG PET-CT based N-staging in lung cancer patients[J].Mol Imaging Biol,2017,19(2):315-322.
|
| [20] |
Giesel F L,Schneider F,Kratochwil C,et al.Correlation between SUVmax and CT radiomic analysis using lymph node density in PET-CT based lymph node staging[J].J Nucl Med,2017,58(2):282-287.
|
| [21] |
Lu W,Chen W.Positron emission tomography/computerized tomography for tumor response assessment a review of clinical practices and radiomics studies[J].Transl Cancer Res,2016,5(4):364-370.
|
| [22] |
Lu L,Lv W,Jiang J,et al.Robustness of radiomic features in 11C-Choline and 18F-FDG PET-CT imaging of nasopharyngeal carcinoma:impact of segmentation and discretization[J].Mol Imaging Biol,2016,18(6):935-945.
|
| [23] |
Cook G J,Yip C,Siddique M,et al.Are pretreatment 18F-FDG PET tumor textural features in non-small cell lung cancer associated with response and survival after chemoradiotherapy?[J].J Nucl Med,2013,54(1):19-26.
|
| [24] |
Coroller T P,Agrawal V,Narayan V,et al.Radiomic phenotype features predict pathological response in non-small cell lung cancer[J].Radiother Oncol,2016,119(3):480-486.
|
| [25] |
张利文,方梦捷,臧亚丽,等.影像组学的发展与应用[J].中华放射学杂志,2017,51(1):75-77.
|
| [26] |
Lovinfosse P,Janvary Z L,Coucke P,et al.FDG PET-CT texture analysis for predicting the outcome of lung cancer treated by stereotactic body radiation therapy[J].Eur J Nucl Med Mol Imaging,2016,43(8):1453-1460.
|
| [27] |
Fried D V,Mawlawi O,Zhang L,et al.Stage Ⅲ non-small cell lung cancer:prognostic value of FDG PET quantitative imaging features combined with clinical prognostic factors[J].Radiology,2016,278(1):214-222.
|
| [28] |
Coroller T P,Grossmann P,Hou Y,et al.CT-based radiomic signature predicts distant metastasis in lung adenocarcinoma[J].Radiother Oncol,2015,114(3):345-350.
|
| [29] |
罗居东,马长升,赵 睿,等.PET特征改变对非小细胞肺癌放射治疗的预测价值[J].中国医学物理学杂志,2019,36(6):677-681.
|
| [30] |
Yoon H J,Sohn I,Cho J H,et al.Decoding tumor phenotypes for ALK,ROS1,and RET fusions in lung adenocarcinoma using a radiomics approach[J].Medicine(Baltimore),2015,94(41):e1753.
|
| [31] |
杨 洋,黄世明,刚 波,等.18F-FDG PET-CT对非小细胞肺癌EGFR基因突变诊断价值的Meta分析[J].武警医学,2018,29(5):448-452.
|
| [32] |
黄世明,杨 洋,尹 亮,等.18F-FDG PET-CT代谢参数联合肿瘤标志物对肺腺癌EGFR基因突变的预测价值[J].武警医学,2020,31(6):503-508.
|
| [33] |
Liu Y,Kim J,Balagurunathan Y,et al.Radiomic features are associated with EGFR mutation status in lung adenocarcinomas[J].Clin Lung Cancer,2016,17(5):441-448.
|
| [34] |
Zhang J Y,Zhao X M,Zhao Y,et al.Value of pre-therapy 18F-FDG PET-CT radiomics in predicting EGFR mutation status in patients with non-small cell lung cancer[J].Eur J Nucl Med Mol Imaging,2019,46(11):1431-1443.
|
| [1] |
. [J]. Med. J. Chin. Peop. Armed Poli. Forc., 2020, 31(9): 819-822. |
|
|
|
2021, Vol. 32 
