Radiomic analysis for pretreatment prediction of response to neoadjuvant chemotherapy in locally advanced cervical cancer: A multicentre studyResearch in context

Radiomic analysis for pretreatment prediction of response to neoadjuvant chemotherapy in locally advanced cervical cancer: A multicentre studyResearch in context

Background: We aimed to investigate whether pre-therapeutic radiomic features based on magnetic resonance imaging (MRI) can predict the clinical response to neoadjuvant chemotherapy (NACT) in patients with locally advanced cervical cancer (LACC). Methods: A total of 275 patients with LACC receiving...

Full description

Bibliographic Details
Main Authors:	Caixia Sun, Xin Tian, Zhenyu Liu, Weili Li, Pengfei Li, Jiaming Chen, Weifeng Zhang, Ziyu Fang, Peiyan Du, Hui Duan, Ping Liu, Lihui Wang, Chunlin Chen, Jie Tian
Format:	Article
Language:	English
Published:	Elsevier 2019-08-01
Series:	EBioMedicine
Online Access:	http://www.sciencedirect.com/science/article/pii/S2352396419304918

Similar Items

Prediction of Response to Preoperative Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer Using Multicenter CT-Based Radiomic Analysis
by: Xin Tian, et al.
Published: (2020-02-01)

Deep learning for predicting major pathological response to neoadjuvant chemoimmunotherapy in non-small cell lung cancer: A multicentre studyResearch in context
by: Yunlang She, et al.
Published: (2022-12-01)

Deep learning radiomics-based prediction of distant metastasis in patients with locally advanced rectal cancer after neoadjuvant chemoradiotherapy: A multicentre study
by: Xiangyu Liu, et al.
Published: (2021-07-01)

CT-based radiomics signature of visceral adipose tissue for prediction of disease progression in patients with Crohn's disease: a multicentre cohort studyResearch in context
by: Xuehua Li, et al.
Published: (2023-02-01)

Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI
by: Nathaniel M. Braman, et al.
Published: (2017-05-01)

Deep learning with biopsy whole slide images for pretreatment prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer：A multicenter study
by: Bao Li, et al.
Published: (2022-12-01)

Multiparametric MRI-based radiomics analysis for the prediction of breast tumor regression patterns after neoadjuvant chemotherapy
by: Xiaosheng Zhuang, et al.
Published: (2020-11-01)

Radiomics-Based Preoperative Prediction of Lymph Node Status Following Neoadjuvant Therapy in Locally Advanced Rectal Cancer
by: Xuezhi Zhou, et al.
Published: (2020-05-01)

Erratum to: Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI
by: Nathaniel M. Braman, et al.
Published: (2017-07-01)

Radiomics analysis of placenta on T2WI facilitates prediction of postpartum haemorrhage: A multicentre study
by: Qingxia Wu, et al.
Published: (2019-12-01)

Non-invasively predicting response to neoadjuvant chemotherapy in gastric cancer via deep learning radiomics
by: Mengjie Fang, et al.
Published: (2022-04-01)

Deep radiomics-based fusion model for prediction of bevacizumab treatment response and outcome in patients with colorectal cancer liver metastases: a multicentre cohort studyResearch in context
by: Shizhao Zhou, et al.
Published: (2023-11-01)

Association of survival with adjuvant chemotherapy in patients with stage IB gastric cancer: a multicentre, observational, cohort studyResearch in context
by: Xianchun Gao, et al.
Published: (2024-04-01)

Intratumoral and peritumoral radiomics predict pathological response after neoadjuvant chemotherapy against advanced gastric cancer
by: Chenchen Liu, et al.
Published: (2024-01-01)

Multiparametric MRI radiomics fusion for predicting the response and shrinkage pattern to neoadjuvant chemotherapy in breast cancer
by: Ming Fan, et al.
Published: (2023-05-01)

Erratum to ‘Radiomics analysis of placenta on T2WI facilitates prediction of postpartum haemorrhage: A multicentre study’
by: Qingxia Wu, et al.
Published: (2020-05-01)

Automated and reusable deep learning (AutoRDL) framework for predicting response to neoadjuvant chemotherapy and axillary lymph node metastasis in breast cancer using ultrasound images: a retrospective, multicentre studyResearch in context
by: Jingjing You, et al.
Published: (2024-03-01)

Radiomics based on pretreatment MRI for predicting distant metastasis of nasopharyngeal carcinoma: A preliminary study
by: Tingting Jiang, et al.
Published: (2022-08-01)

Predicting the response to neoadjuvant chemotherapy for breast cancer: wavelet transforming radiomics in MRI
by: Jiali Zhou, et al.
Published: (2020-02-01)

DCE-MRI radiomics nomogram can predict response to neoadjuvant chemotherapy in esophageal cancer
by: Jinrong Qu, et al.
Published: (2022-01-01)

Artificial intelligence-assisted ultrasound image analysis to discriminate early breast cancer in Chinese population: a retrospective, multicentre, cohort studyResearch in context
by: Jianwei Liao, et al.
Published: (2023-06-01)

Machine Learning-Based Radiomics Nomogram Using Magnetic Resonance Images for Prediction of Neoadjuvant Chemotherapy Efficacy in Breast Cancer Patients
by: Shujun Chen, et al.
Published: (2020-08-01)

A multicentre, prospective, double-blind study comparing the accuracy of autoantibody diagnostic assays in myasthenia gravis: the SCREAM studyResearch in context
by: Zhiguo Li, et al.
Published: (2023-09-01)

A radiomics model for preoperative prediction of brain invasion in meningioma non-invasively based on MRI: A multicentre study
by: Jing Zhang, et al.
Published: (2020-08-01)

Extraction parameter optimized radiomics for neoadjuvant chemotherapy response prognosis in advanced nasopharyngeal carcinoma
by: Yiling Wang, et al.
Published: (2022-03-01)

Integration of Clinical and CT-Based Radiomic Features for Pretreatment Prediction of Pathologic Complete Response to Neoadjuvant Systemic Therapy in Breast Cancer
by: Huei-Yi Tsai, et al.
Published: (2022-12-01)

A radiomic model to classify response to neoadjuvant chemotherapy in breast cancer
by: Peter McAnena, et al.
Published: (2022-12-01)

Development and validation of a radiomics signature for clinically significant portal hypertension in cirrhosis (CHESS1701): a prospective multicenter studyResearch in context
by: Fuquan Liu, et al.
Published: (2018-10-01)

ABVS-Based Radiomics for Early Predicting the Efficacy of Neoadjuvant Chemotherapy in Patients with Breast Cancers
by: Jiang W, et al.
Published: (2023-08-01)

Radiomics of Tumor Heterogeneity in Longitudinal Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Predicting Response to Neoadjuvant Chemotherapy in Breast Cancer
by: Ming Fan, et al.
Published: (2021-03-01)

The application of radiomics in esophageal cancer: Predicting the response after neoadjuvant therapy
by: Hai Guo, et al.
Published: (2023-04-01)

Prediction of neoadjuvant chemotherapy pathological complete response for breast cancer based on radiomics nomogram of intratumoral and derived tissue
by: Guangying Zheng, et al.
Published: (2024-01-01)

CT-Based Radiomics Showing Generalization to Predict Tumor Regression Grade for Advanced Gastric Cancer Treated With Neoadjuvant Chemotherapy
by: Yong Chen, et al.
Published: (2022-02-01)

MRI-based pre-Radiomics and delta-Radiomics models accurately predict the post-treatment response of rectal adenocarcinoma to neoadjuvant chemoradiotherapy
by: Likun Wang, et al.
Published: (2023-02-01)

Surgical outcomes of gallbladder cancer: the OMEGA retrospective, multicentre, international cohort studyResearch in context
by: Anita Balakrishnan, et al.
Published: (2023-05-01)

Clinical characteristics and outcomes in neonates with perinatal acute respiratory distress syndrome in China: A national, multicentre, cross-sectional studyResearch in context
by: Long Chen, et al.
Published: (2023-01-01)

Computed tomography-based radiomic model at node level for the prediction of normal-sized lymph node metastasis in cervical cancer
by: Yujia Liu, et al.
Published: (2021-08-01)

Comparing three-dimensional and two-dimensional deep-learning, radiomics, and fusion models for predicting occult lymph node metastasis in laryngeal squamous cell carcinoma based on CT imaging: a multicentre, retrospective, diagnostic studyResearch in context
by: Wenlun Wang, et al.
Published: (2024-01-01)

Long COVID is associated with severe cognitive slowing: a multicentre cross-sectional studyResearch in context
by: Sijia Zhao, et al.
Published: (2024-02-01)

The international experience of in-situ recovery of the DCD heart: a multicentre retrospective observational studyResearch in context
by: John Louca, et al.
Published: (2023-04-01)