Results 231 to 240 of about 71,655 (241)

Predicting Microvascular Invasion in Hepatocellular Carcinoma Using CT-based Radiomics Model.

Radiology, 2023
Background Prediction of microvascular invasion (MVI) may help determine treatment strategies for hepatocellular carcinoma (HCC). Purpose To develop a radiomics approach for predicting MVI status based on preoperative multiphase CT images and to identify
Tianyi Xia, Zheng-Hao Zhou, Xiangpan Meng, J. Zha, Qian Yu, Wei-Lang Wang, Yang Song, Yuan-Cheng Wang, T. Tang, Jun Xu, Tao Zhang, Xueying Long, Yun Liang, W. Xiao, Shenghong Ju   +14 more
semanticscholar   +1 more source

A Coronary CT Angiography Radiomics Model to Identify Vulnerable Plaque and Predict Cardiovascular Events.

Radiology, 2023
Background A noninvasive coronary CT angiography (CCTA)-based radiomics technique may facilitate the identification of vulnerable plaques and patients at risk for future adverse events.
Qian Chen, Tao Pan, Y. N. Wang, U. Schoepf, Samuel L Bidwell, H. Qiao, Yun Feng, Chengyi Xu, Hui Xu, Guanghui Xie, Xiaofei Gao, Xinwei Tao, M. Lu, P. Xu, J. Zhong, Yongyue Wei, X. Yin, Junjie Zhang, L. Zhang   +18 more
semanticscholar   +1 more source

Multiparametric MRI and Radiomics for the Prediction of HER2-Zero, -Low, and -Positive Breast Cancers.

Radiology, 2023
Background Half of breast cancers exhibit low expression levels of human epidermal growth factor receptor 2 (HER2) and can be targeted by new antibody-drug conjugates.
T. Ramtohul, L. Djerroudi, Emilie Lissavalid, Caroline Nhy, Louis Redon, L. Ikni, M. Djelouah, Gabrielle Journo, E. Menet, L. Cabel, C. Malhaire, A. Tardivon   +11 more
semanticscholar   +1 more source

MRI Radiomics Model Predicts Pathologic Complete Response of Rectal Cancer Following Chemoradiotherapy.

Radiology, 2022
Background Preoperative assessment of pathologic complete response (pCR) in locally advanced rectal cancer (LARC) after neoadjuvant chemoradiotherapy (nCRT) is increasingly needed for organ preservation, but large-scale validation of an MRI radiomics ...
Jaeseung Shin, N. Seo, S. Baek, Nak-Hoon Son, J. Lim, Nam Kyu Kim, W. Koom, Sungwon Kim   +7 more
semanticscholar   +1 more source

CT Radiomics to Predict Macrotrabecular-Massive Subtype and Immune Status in Hepatocellular Carcinoma.

Radiology, 2022
Background Macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC) is an aggressive variant associated with angiogenesis and immunosuppressive tumor microenvironment, which is expected to be noninvasively identified using radiomics ...
Zhichao Feng, Huiling Li, Qianyun Liu, Junhong Duan, Wenming Zhou, Xiaoping Yu, Qian Chen, Zhenghao Liu, Wei Wang, Pengfei Rong   +9 more
semanticscholar   +1 more source

Development and Validation of a Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer.

Journal of Clinical Oncology, 2016
PURPOSE To develop and validate a radiomics nomogram for preoperative prediction of lymph node (LN) metastasis in patients with colorectal cancer (CRC).
Yanqi Huang, C. Liang, Lan He, Jie Tian, Cuishan Liang, Xin Chen, Zelan Ma, Zai-Yi Liu   +7 more
semanticscholar   +1 more source

Radiomics of CT Features May Be Nonreproducible and Redundant: Influence of CT Acquisition Parameters.

Radiology, 2018
Purpose To identify the reproducible and nonredundant radiomics features (RFs) for computed tomography (CT). Materials and Methods Two phantoms were used to test RF reproducibility by using test-retest analysis, by changing the CT acquisition parameters (
R. Berenguer, M. R. Pastor-Juan, J. Canales-Vázquez, M. Castro-García, M. V. Villas, F. Mansilla Legorburo, S. Sabater   +6 more
semanticscholar   +1 more source

Radiomics: the bridge between medical imaging and personalized medicine

Nature Reviews Clinical Oncology, 2017
P. Lambin, R. Leijenaar, T. Deist, J. Peerlings, E. D. Jong, J. V. Timmeren, S. Sanduleanu, R. Larue, A. Even, A. Jochems, Y. V. Wijk, H. Woodruff, J. V. Soest, T. Lustberg, E. Roelofs, W. V. Elmpt, A. Dekker, F. Mottaghy, J. Wildberger, S. Walsh   +19 more
semanticscholar   +1 more source

Radiomics and Radiogenomics

Machine and Deep Learning in Oncology, Medical Physics and Radiology, 2022
Ruijiang Li, L. Xing, S. Napel, D. Rubin
semanticscholar   +1 more source

A narrative review on current imaging applications of artificial intelligence and radiomics in oncology: focus on the three most common cancers

La radiologia medica, 2022
S. Vicini, C. Bortolotto, M. Rengo, D. Ballerini, D. Bellini, I. Carbone, L. Preda, A. Laghi, F. Coppola, L. Faggioni   +9 more
semanticscholar   +1 more source