Predicting Response to Neoadjuvant Chemotherapy in Patients With Breast Cancer Combined Statistical Modeling Using Clinicopathological Factors and FDG PET/CT Texture Parameters

Lee Hyunjong; Lee Dong-eun; Park Sohyun; Kim Tae Sung; Jung So-Youn; Lee Seeyoun; Kang Han Sung; Lee Eun Sook; Sim Sung Hoon; Park In Hae; Lee Keun Seok; Kwon Young Mi; Kong Sun Young; Joo Jungnam; Jeong Hae Jeong; Kim Seok-ki

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Predicting Response to Neoadjuvant Chemotherapy in Patients With Breast Cancer Combined Statistical Modeling Using Clinicopathological Factors and FDG PET/CT Texture Parameters

机译：使用临床病理因子和FDG PET / CT纹理参数预测对乳腺癌患者乳腺癌联合统计建模患者的新辅助化疗的反应

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Supplemental digital content is available in the text.

机译：文本中提供了补充数字内容。

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《Clinical nuclear medicine》 |2019年第1期|共9页
作者
Lee Hyunjong; Lee Dong-eun; Park Sohyun; Kim Tae Sung; Jung So-Youn; Lee Seeyoun; Kang Han Sung; Lee Eun Sook; Sim Sung Hoon; Park In Hae; Lee Keun Seok; Kwon Young Mi; Kong Sun Young; Joo Jungnam; Jeong Hae Jeong; Kim Seok-ki;
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作者单位

Natl Canc Ctr Dept Nucl Med 323 Ilsan Ro Goyang 10408 South Korea;

Natl Canc Ctr Biometr Res Branch Goyang South Korea;

Natl Canc Ctr Dept Nucl Med 323 Ilsan Ro Goyang 10408 South Korea;

Natl Canc Ctr Dept Nucl Med 323 Ilsan Ro Goyang 10408 South Korea;

Natl Canc Ctr Ctr Breast Canc Goyang South Korea;

Natl Canc Ctr Ctr Breast Canc Goyang South Korea;

Natl Canc Ctr Ctr Breast Canc Goyang South Korea;

Natl Canc Ctr Ctr Breast Canc Goyang South Korea;

Natl Canc Ctr Ctr Breast Canc Goyang South Korea;

Natl Canc Ctr Ctr Breast Canc Goyang South Korea;

Natl Canc Ctr Ctr Breast Canc Goyang South Korea;

Natl Canc Ctr Ctr Breast Canc Goyang South Korea;

Natl Canc Ctr Ctr Hematol Malignancy Goyang South Korea;

Natl Canc Ctr Biometr Res Branch Goyang South Korea;

Natl Canc Ctr Ctr Breast Canc Goyang South Korea;

Natl Canc Ctr Dept Nucl Med 323 Ilsan Ro Goyang 10408 South Korea;

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原文格式 PDF
正文语种 eng
中图分类放射医学;
关键词
breast cancer; neoadjuvant chemotherapy; FDG PET/CT; texture analysis;

机译：乳腺癌;Neoadjuvant化疗;FDG PET / CT;纹理分析;

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专利

1. Predicting Response to Neoadjuvant Chemotherapy in Patients With Breast Cancer Combined Statistical Modeling Using Clinicopathological Factors and FDG PET/CT Texture Parameters [J] . Lee Hyunjong, Lee Dong-eun, Park Sohyun, Clinical nuclear medicine . 2019,第1期

机译：使用临床病理因子和FDG PET / CT纹理参数预测对乳腺癌患者乳腺癌联合统计建模患者的新辅助化疗的反应
2. Biomarkers from in vivo molecular imaging of breast cancer: pretreatment F-18-FDG PET predicts patient prognosis, and pretreatment DWI-MR predicts response to neoadjuvant chemotherapy [J] . Gallivanone Francesca, Panzeri Marta Maria, Canevari Carla, Magma: Magnetic resonance materials in physics, biology, and medicine . 2017,第4期

机译：来自体内分子成像的生物标志物的乳腺癌：预处理F-18-FDG宠物预测患者预后，预处理DWI-MR预测对新辅助化疗的反应
3. Textural features of F-18-FDG PET after two cycles of neoadjuvant chemotherapy can predict pCR in patients with locally advanced breast cancer [J] . Cheng Lin, Zhang Jianping, Wang Yujie, Annals of nuclear medicine . 2017,第7期

机译：新辅助化疗两次循环后F-18-FDG PET的纹理特征可以预测局部晚期乳腺癌患者的PCR
4. Analysing PET scans data for predicting response to chemotherapy in breast cancer patients [C] . Elias Gyftodimos, Laura Moss, Derek Sleeman, SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence . 2008

机译：分析宠物扫描数据以预测乳腺癌患者化疗的反应
5. Combining biomarkers and clinicopathologic factors for prediction of response to adjuvant chemotherapy for breast cancer: Cox model and Support Vector Machine (SVM) methods. [D] . Liu, Xudong. 2010

机译：结合生物标志物和临床病理因素预测乳腺癌对辅助化疗的反应：Cox模型和支持向量机（SVM）方法。
6. 18FDG-PET/CT for predicting the outcome in ER+/HER2- breast cancer patients: comparison of clinicopathological parameters and PET image-derived indices including tumor texture analysis [O] . David Groheux, Antoine Martineau, Luis Teixeira, 2017

机译：18FDG-PET / CT预测ER + / HER2-乳腺癌患者的预后：比较临床病理参数和PET图像衍生指标包括肿瘤纹理分析
7. FDG-PET/CT for predicting the outcome in ER+/HER2- breast cancer patients: comparison of clinicopathological parameters and PET image-derived indices including tumor texture analysis [O] . 2017

机译：FDG-PET / CT预测ER + / HER2-乳腺癌患者的预后：比较临床病理参数和PET图像衍生指标，包括肿瘤纹理分析

Predicting Response to Neoadjuvant Chemotherapy in Patients With Breast Cancer Combined Statistical Modeling Using Clinicopathological Factors and FDG PET/CT Texture Parameters

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