Cargando…

Review of Radiomics- and Dosiomics-based Predicting Models for Rectal Cancer

By breaking the traditional medical image analysis framework, precision medicine–radiomics has attracted much attention in the past decade. The use of various mathematical algorithms offers radiomics the ability to extract vast amounts of detailed features from medical images for quantitative analys...

Descripción completa

Detalles Bibliográficos
Autores principales:	Qin, Yun, Zhu, Li-Hua, Zhao, Wei, Wang, Jun-Jie, Wang, Hao
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2022
Materias:	Oncology
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9395725/ https://www.ncbi.nlm.nih.gov/pubmed/36016617 http://dx.doi.org/10.3389/fonc.2022.913683

Ejemplares similares

CT-based dosiomics and radiomics model predicts radiation-induced lymphopenia in nasopharyngeal carcinoma patients
por: Huang, Qingfang, et al.
Publicado: (2023)

Radiomic and Dosiomic Features for the Prediction of Radiation Pneumonitis Across Esophageal Cancer and Lung Cancer
por: Puttanawarut, Chanon, et al.
Publicado: (2022)

Dosiomics and radiomics to predict pneumonitis after thoracic stereotactic body radiotherapy and immune checkpoint inhibition
por: Kraus, Kim Melanie, et al.
Publicado: (2023)

Design and Selection of Machine Learning Methods Using Radiomics and Dosiomics for Normal Tissue Complication Probability Modeling of Xerostomia
por: Gabryś, Hubert S., et al.
Publicado: (2018)

Impact of Interfractional Error on Dosiomic Features
por: Puttanawarut, Chanon, et al.
Publicado: (2022)

Radiomics and dosiomics for predicting radiation-induced hypothyroidism and guiding intensity-modulated radiotherapy
por: Yang, Shan-Shan, et al.
Publicado: (2023)

Radiomics and Dosiomics for Predicting Local Control after Carbon-Ion Radiotherapy in Skull-Base Chordoma
por: Buizza, Giulia, et al.
Publicado: (2021)

Dosiomics: Extracting 3D Spatial Features From Dose Distribution to Predict Incidence of Radiation Pneumonitis
por: Liang, Bin, et al.
Publicado: (2019)

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

Radiation pneumonitis prediction after stereotactic body radiation therapy based on 3D dose distribution: dosiomics and/or deep learning-based radiomics features
por: Huang, Ying, et al.
Publicado: (2022)

Computed Tomography-Based Radiomics for Preoperative Prediction of Tumor Deposits in Rectal Cancer
por: Jin, Yumei, et al.
Publicado: (2021)

Preoperative prediction of tumor deposits in rectal cancer with clinical-magnetic resonance deep learning-based radiomic models
por: Fu, Chunlong, et al.
Publicado: (2023)

MRI-Based Radiomics Predicts Tumor Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer
por: Yi, Xiaoping, et al.
Publicado: (2019)

Dosiomics-Based Prediction of Radiation-Induced Valvulopathy after Childhood Cancer
por: Chounta, Stefania, et al.
Publicado: (2023)

A Novel Multimodal Radiomics Model for Preoperative Prediction of Lymphovascular Invasion in Rectal Cancer
por: Zhang, Yiying, et al.
Publicado: (2020)

Establishment and validation of novel MRI radiomic feature-based prognostic models to predict progression-free survival in locally advanced rectal cancer
por: Xie, Fei, et al.
Publicado: (2022)

Prognostic value of (18)F-FDG PET/CT-based radiomics combining dosiomics and dose volume histogram for head and neck cancer
por: Wang, Bingzhen, et al.
Publicado: (2023)

DCE-MRI radiomics models predicting the expression of radioresistant-related factors of LRP-1 and survivin in locally advanced rectal cancer
por: Li, Zhiheng, et al.
Publicado: (2022)

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

MRI Radiomics Signature as a Potential Biomarker for Predicting KRAS Status in Locally Advanced Rectal Cancer Patients
por: Zhang, ZhiYuan, et al.
Publicado: (2021)

Predicting Treatment Response to Neoadjuvant Chemoradiotherapy in Rectal Mucinous Adenocarcinoma Using an MRI-Based Radiomics Nomogram
por: Li, Zhihui, et al.
Publicado: (2021)

MRI-based multiregional radiomics for predicting lymph nodes status and prognosis in patients with resectable rectal cancer
por: Li, Hang, et al.
Publicado: (2023)

MRI-Based Radiomics Features to Predict Treatment Response to Neoadjuvant Chemotherapy in Locally Advanced Rectal Cancer: A Single Center, Prospective Study
por: Chen, Bi-Yun, et al.
Publicado: (2022)

Biological dosiomic features for the prediction of radiation pneumonitis in esophageal cancer patients
por: Puttanawarut, Chanon, et al.
Publicado: (2021)

Preoperative prediction of tumor budding in rectal cancer using multiple machine learning algorithms based on MRI T2WI radiomics
por: Qu, Xueting, et al.
Publicado: (2023)

Predicting the risk of distant metastasis in patients with locally advanced rectal cancer using model based on pre-treatment T2WI-based radiomic features plus postoperative pathological stage
por: Wang, Chen, et al.
Publicado: (2023)

Preoperative Prediction of Perineural Invasion Status of Rectal Cancer Based on Radiomics Nomogram of Multiparametric Magnetic Resonance Imaging
por: Zhang, Yang, et al.
Publicado: (2022)

A Novel Model Based on CXCL8-Derived Radiomics for Prognosis Prediction in Colorectal Cancer
por: Chu, Yanpeng, et al.
Publicado: (2020)

Stability of dosiomic features against variations in dose calculation: An analysis based on a cohort of prostate external beam radiotherapy patients
por: Sun, Lingyue, et al.
Publicado: (2023)

Comparable Performance of Deep Learning–Based to Manual-Based Tumor Segmentation in KRAS/NRAS/BRAF Mutation Prediction With MR-Based Radiomics in Rectal Cancer
por: Zhang, Guangwen, et al.
Publicado: (2021)

MRI-Based Radiomics Models for Predicting Risk Classification of Gastrointestinal Stromal Tumors
por: Mao, Haijia, et al.
Publicado: (2021)

The application of radiomics in esophageal cancer: Predicting the response after neoadjuvant therapy
por: Guo, Hai, et al.
Publicado: (2023)

Radiomics for the Prediction of Epilepsy in Patients With Frontal Glioma
por: Gao, Ankang, et al.
Publicado: (2021)

Intra- and Peritumoral Radiomics Model Based on Early DCE-MRI for Preoperative Prediction of Molecular Subtypes in Invasive Ductal Breast Carcinoma: A Multitask Machine Learning Study
por: Zhang, Shuhai, et al.
Publicado: (2022)

Machine Learning-Based Radiomics Nomogram for Detecting Extramural Venous Invasion in Rectal Cancer
por: Liu, Siye, et al.
Publicado: (2021)

Prediction of Locoregional Recurrence-Free Survival of Oesophageal Squamous Cell Carcinoma After Chemoradiotherapy Based on an Enhanced CT-Based Radiomics Model
por: Kong, Jie, et al.
Publicado: (2021)

Machine and Deep Learning Based Radiomics Models for Preoperative Prediction of Benign and Malignant Sacral Tumors
por: Yin, Ping, et al.
Publicado: (2020)

An MRI-Based Radiomics Model for Predicting the Benignity and Malignancy of BI-RADS 4 Breast Lesions
por: Zhang, Renzhi, et al.
Publicado: (2022)

Delta Radiomics Can Predict Distant Metastasis in Locally Advanced Rectal Cancer: The Challenge to Personalize the Cure
por: Chiloiro, Giuditta, et al.
Publicado: (2020)

Radiomics Analysis of Multi-Sequence MR Images For Predicting Microsatellite Instability Status Preoperatively in Rectal Cancer
por: Li, Zongbao, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_704vf8198fj4vqenjmkekmtv9g