Results 121 to 130 of about 52,953 (291)

Prognostic Value of Combined FDG PET and MRI Analysis of Cervical Cancer: A Systematic Review and Meta‐Analysis

Journal of Medical Radiation Sciences, EarlyView.
This systematic review and meta‐analysis synthesised FDG PET/MRWE biomarkers in cervical cancer, including a pooled analysis of the association between metabolic activity (SUV‐based metrics) and tumour diffusion characteristics (ADC measures). Prognostic evidence from the included studies was also analysed to identify PET‐ and MRI‐based parameters, as ...
William Wei, Dominic Ku, Natalie Rutherford   +2 more
wiley   +1 more source

Deep Learning and Machine Learning Algorithms for Cervical Cancer Segmentation on MRI: A Systematic Review

Journal of Medical Radiation Sciences, EarlyView.
This systematic review summarizes current evidence on machine and deep learning algorithms for MRI‐based cervical cancer segmentation, demonstrating promising diagnostic performance and potential for workflow automation. However, methodological heterogeneity, limited external validation, and low certainty of evidence highlight the need for standardized
Somayeh Haji Ahmadi, Sina Soltan Mohammadi, Abolfazl Koozari, Mohammadreza Elhaie   +3 more
wiley   +1 more source

Editorial: Imaging assessment of response to immunotherapy

Frontiers in Oncology, 2023
Mariaelena Occhipinti, Andrea R. Filippi, Andrea R. Filippi, Sean Walsh, Jan P. van Meerbeeck   +4 more
doaj   +1 more source

Machine learning-based radiomics prognostic model for patients with proximal esophageal cancer after definitive chemoradiotherapy

Insights into Imaging
Objectives To explore the role of radiomics in predicting the prognosis of proximal esophageal cancer and to investigate the biological underpinning of radiomics in identifying different prognoses.
Linrui Li, Zhihui Qin, Juan Bo, Jiaru Hu, Yu Zhang, Liting Qian, Jiangning Dong   +6 more
doaj   +1 more source

Novel Nomogram for Preoperative Prediction of Early Recurrence in Intrahepatic Cholangiocarcinoma

Frontiers in Oncology, 2018
Introduction: The emerging field of “radiomics” has considerable potential in disease diagnosis, pathologic grading, prognosis evaluation, and prediction of treatment response.
Wenjie Liang, Wenjie Liang, Lei Xu, Lei Xu, Pengfei Yang, Pengfei Yang, Lele Zhang, Lele Zhang, Lele Zhang, Dalong Wan, Qiang Huang, Tianye Niu, Feng Chen   +12 more
doaj   +1 more source

Molecular theranostics: principles, challenges and controversies

Journal of Medical Radiation Sciences, Volume 72, Issue 1, Page 156-164, March 2025.
Molecular theranostics offers a powerful tool to drive precision medicine in nuclear oncology. While theranostics is not a new principle in nuclear medicine, recent advances in instrumentation and radiopharmacy have driven a reinvigoration and a broader suite of applications.
Geoffrey Currie
wiley   +1 more source

Radiomics and Back Pain

Global Spine Journal
Study Design Narrative review. Objectives Back pain is one of the leading causes of disability worldwide. While conventional imaging interpretation remains subjective and expertise-dependent, radiomics offers quantitative, data-driven ...
Jason Lin, Vinay Duddalwar, Michael M. Safaee   +2 more
openaire   +2 more sources

A two‐stage model for precise identification and Gleason grading of clinically significant prostate cancer: a hybrid approach

Journal of Medical Radiation Sciences, Volume 72, Issue 1, Page 93-105, March 2025.
This study developed a two‐stage model using radiomics‐based multiparametric MRI and clinical indicators to help identify and grade clinically significant prostate cancer. The model showed promising levels of diagnostic accuracy and predictive performance.
Yuyan Zou, Xuechun Wang, Fen Ma, Xulun Liu, Chunyue Jiao, Zhen Kang, Jingjing Cui, Yang Zhang, Yan Xie, Lei Chen, Ronghua Tian   +10 more
wiley   +1 more source

Ki-67 Prediction in Breast Cancer: Integrating Radiomics From Automated Breast Volume Scanner and 2D Ultrasound Images via Machine Learning [PDF]

Wei Wei,1,2,* Fei Xia,3,* Wang Zhou,1,* Wenwu Lu,1 Di Zhang,1 Qianqing Ma,2 Xiangyi Xu,1 Chaoxue Zhang1 1Department of Ultrasound, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, People’s Republic of China;
Ma Q, Zhang D, Lu W, Zhou W, Wei W, Xu X, Zhang C, Xia F   +7 more
core  

Radiomics features used in PET analysis.

, 2019
Radiomics features used in PET analysis.
Skylar Gay (5982818), Rachel B. Ger (5640281), Laurence E. Court (7349003), Raymond Mumme (7348994), Raymond B. Pahlka (7348991), Clifton D. Fuller (3070920), R. Jason Stafford (1320150), Rick R. Layman (7106471), Shouhao Zhou (7349000), Osama Mawlawi (207477), Rebecca M. Howell (7348997), Heng Li (6476), Joseph G. Meier (7348988)   +12 more
core   +1 more source