Prediction of pathological response after neoadjuvant chemotherapy using baseline FDG PET heterogeneity features in breast cancer

被引:11
作者
Oliveira, Carla [1 ]
Oliveira, Francisco [1 ]
Vaz, Sofia C. [1 ]
Marques, Hugo Pinto [2 ]
Cardoso, Fatima [3 ]
机构
[1] Champalimaud Fdn, Champalimaud Clin Ctr, Nucl Med Radiopharmacol, Lisbon, Portugal
[2] NOVA Med Sch, Lisbon, Portugal
[3] Champalimaud Fdn, Champalimaud Clin Ctr, Breast Unit, Lisbon, Portugal
关键词
TEXTURAL FEATURES; F-18-FDG PET; RADIOMICS;
D O I
10.1259/bjr.20220655
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Complete pathological response to neoadjuvant systemic treatment (NAST) in some subtypes of breast cancer (BC) has been used as a surrogate of long- term outcome. The possibility of predicting BC pathological response to NAST based on the baseline 18F- Fluorodeoxyglucose positron emission tomography (FDG PET), without the need of an interim study, is a focus of recent discussion. This review summarises the characteristics and results of the available studies regarding the potential impact of heterogeneity features of the primary tumour burden on baseline FDG PET in predicting pathological response to NAST in BC patients. Literature search was conducted on PubMed database and relevant data from each selected study were collected. A total of 13 studies were eligible for inclusion, all of them published over the last 5 years. Eight out of 13 analysed studies indicated an association between FDG PET- based tumour uptake heterogeneity features and prediction of response to NAST. When features associated with predicting response to NAST were derived, these varied between studies. Therefore, definitive reproducible findings across series were difficult to establish. This lack of consensus may reflect the heterogeneity and low number of included series. The clinical relevance of this topic justifies further investigation about the predictive role of baseline FDG PET.
引用
收藏
页数:10
相关论文
共 50 条
[21]   Intratumoral and peritumoral radiomics for preoperative prediction of neoadjuvant chemotherapy effect in breast cancer based on 18F-FDG PET/CT [J].
Hou, Xuefeng ;
Chen, Kun ;
Wan, Xing ;
Luo, Huiwen ;
Li, Xiaofeng ;
Xu, Wengui .
JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY, 2024, 150 (11)
[22]   18F-FDG PET/CT radiomic predictors of pathologic complete response (pCR) to neoadjuvant chemotherapy in breast cancer patients [J].
Li, Panli ;
Wang, Xiuying ;
Xu, Chongrui ;
Liu, Cheng ;
Zheng, Chaojie ;
Fulham, Michael J. ;
Feng, Dagan ;
Wang, Lisheng ;
Song, Shaoli ;
Huang, Gang .
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2020, 47 (05) :1116-1126
[23]   Clinical value of SUVpeak-to-tumor centroid distance on FDG PET/CT for predicting neoadjuvant chemotherapy response in patients with breast cancer [J].
Hong, Sun-pyo ;
Lee, Sang Mi ;
Yoo, Ik Dong ;
Lee, Jong Eun ;
Han, Sun Wook ;
Kim, Sung Yong ;
Lee, Jeong Won .
CANCER IMAGING, 2024, 24 (01)
[24]   Co-clinical FDG-PET radiomic signature in predicting response to neoadjuvant chemotherapy in triple-negative breast cancer [J].
Sudipta Roy ;
Timothy D. Whitehead ;
Shunqiang Li ;
Foluso O. Ademuyiwa ;
Richard L. Wahl ;
Farrokh Dehdashti ;
Kooresh I. Shoghi .
European Journal of Nuclear Medicine and Molecular Imaging, 2022, 49 :550-562
[25]   Co-clinical FDG-PET radiomic signature in predicting response to neoadjuvant chemotherapy in triple-negative breast cancer [J].
Roy, Sudipta ;
Whitehead, Timothy D. ;
Li, Shunqiang ;
Ademuyiwa, Foluso O. ;
Wahl, Richard L. ;
Dehdashti, Farrokh ;
Shoghi, Kooresh I. .
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2022, 49 (02) :550-562
[26]   18F-FDG PET/CT radiomic predictors of pathologic complete response (pCR) to neoadjuvant chemotherapy in breast cancer patients [J].
Panli Li ;
Xiuying Wang ;
Chongrui Xu ;
Cheng Liu ;
Chaojie Zheng ;
Michael J Fulham ;
Dagan Feng ;
Lisheng Wang ;
Shaoli Song ;
Gang Huang .
European Journal of Nuclear Medicine and Molecular Imaging, 2020, 47 :1116-1126
[27]   Prediction of the Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer Patients With MRI-Radiomics: A Systematic Review and Meta-analysis [J].
Pesapane, Filippo ;
Agazzi, Giorgio Maria ;
Rotili, Anna ;
Ferrari, Federica ;
Cardillo, Andrea ;
Penco, Silvia ;
Dominelli, Valeria ;
D'Ecclesiis, Oriana ;
Vignati, Silvano ;
Raimondi, Sara ;
Bozzini, Anna ;
Pizzamiglio, Maria ;
Petralia, Giuseppe ;
Nicosia, Luca ;
Cassano, Enrico .
CURRENT PROBLEMS IN CANCER, 2022, 46 (05)
[28]   Predicting Tumour Response to Neoadjuvant Chemotherapy Using MRI Radiomic Features in Breast Cancer: a preliminary, bicentric analysis [J].
de Bari, Berardino .
RADIOTHERAPY AND ONCOLOGY, 2025, 206 :S641-S641
[29]   Multimodal deep learning models for the prediction of pathologic response to neoadjuvant chemotherapy in breast cancer [J].
Joo, Sunghoon ;
Ko, Eun Sook ;
Kwon, Soonhwan ;
Jeon, Eunjoo ;
Jung, Hyungsik ;
Kim, Ji-Yeon ;
Chung, Myung Jin ;
Im, Young-Hyuck .
SCIENTIFIC REPORTS, 2021, 11 (01)
[30]   Radiomic model based on magnetic resonance imaging for predicting pathological complete response after neoadjuvant chemotherapy in breast cancer patients [J].
Yu, Yimiao ;
Wang, Zhibo ;
Wang, Qi ;
Su, Xiaohui ;
Li, Zhenghao ;
Wang, Ruifeng ;
Guo, Tianhui ;
Gao, Wen ;
Wang, Haiji ;
Zhang, Biyuan .
FRONTIERS IN ONCOLOGY, 2024, 13