Results 81 to 90 of about 89,335 (330)

Radiomics analysis of contrast-enhanced computed tomography in predicting the International Neuroblastoma Pathology Classification in neuroblastoma

Insights into Imaging, 2023
Purpose To predict the International Neuroblastoma Pathology Classification (INPC) in neuroblastoma using a computed tomography (CT)-based radiomics approach.
Haoru Wang, Mingye Xie, Xin Chen, Jin Zhu, Li Zhang, Hao Ding, Zhengxia Pan, Ling He   +7 more
doaj   +1 more source

An Improvement of Survival Stratification in Glioblastoma Patients via Combining Subregional Radiomics Signatures

Frontiers in Neuroscience, 2021
PurposeTo investigate whether combining multiple radiomics signatures derived from the subregions of glioblastoma (GBM) can improve survival prediction of patients with GBM.MethodsIn total, 129 patients were included in this study and split into training
Yang Yang, Yang Yang, Yu Han, Xintao Hu, Wen Wang, Guangbin Cui, Lei Guo, Lei Guo, Xin Zhang   +8 more
doaj   +1 more source

Highly accurate model for prediction of lung nodule malignancy with CT scans [PDF]

, 2018
Computed tomography (CT) examinations are commonly used to predict lung nodule malignancy in patients, which are shown to improve noninvasive early diagnosis of lung cancer.
Causey, Jason L., Huang, Xiuzhen, Jiang, Bo, Ma, Shiqian, Politte, David G., Prior, Fred, Qualls, Jake A., Zhang, Junyu, Zhang, Shuzhong   +8 more
core   +3 more sources

METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII

Insights into Imaging
Purpose To propose a new quality scoring tool, METhodological RadiomICs Score (METRICS), to assess and improve research quality of radiomics studies. Methods We conducted an online modified Delphi study with a group of international experts.
Burak Koçak, Tugba Akinci D'Antonoli, Nathaniel D. Mercaldo, Á. Alberich-Bayarri, Bettina Baessler, Ilaria Ambrosini, A. Andreychenko, S. Bakas, Regina G H Beets-Tan, K. Bressem, I. Buvat, Roberto Cannella, L. Cappellini, Armando Ugo Cavallo, Leonid L Chepelev, L. Chu, Aydin Demircioğlu, N M deSouza, Matthias Dietzel, S. C. Fanni, Andrey Fedorov, Laure S Fournier, Valentina Giannini, R. Girometti, Kevin B W Groot Lipman, Georgios Kalarakis, B. S. Kelly, M. Klontzas, D. Koh, E. Kotter, H. Lee, M. Maas, L. Martí-Bonmatí, H. Müller, Nancy Obuchowski, Fanny Orlhac, Nikolaos Papanikolaou, E. Petrash, Elisabeth A. G. Pfaehler, Daniel Pinto dos Santos, A. Ponsiglione, S. Sabater, F. Sardanelli, Philipp Seeböck, N. Sijtsema, A. Stanzione, Alberto Traverso, L. Ugga, M. Vallières, L. V. van Dijk, Joost J. M. van Griethuysen, R. V. van Hamersvelt, P. V. van Ooijen, Federica Vernuccio, Alan Wang, Stuart Williams, J. Witowski, Zhongyi Zhang, A. Zwanenburg, Renato Cuocolo   +59 more
semanticscholar   +1 more source

Radiomics and Delta-Radiomics Signatures to Predict Response and Survival in Patients with Non-Small-Cell Lung Cancer Treated with Immune Checkpoint Inhibitors

Cancers, 2023
Simple Summary Accurate and early selection of patients with advanced non-small-cell lung cancer (NSCLC) who would benefit from immunotherapy is of the utmost clinical importance.
F. Cousin, Thomas Louis, Sophie Dheur, F. Aboubakar, B. Ghaye, M. Occhipinti, W. Vos, F. Bottari, A. Paulus, A. Sibille, F. Vaillant, B. Duysinx, J. Guiot, R. Hustinx   +13 more
semanticscholar   +1 more source

Radiomics Analysis for Multiple Myeloma: A Systematic Review with Radiomics Quality Scoring

Diagnostics, 2023
Multiple myeloma (MM) is one of the most common hematological malignancies affecting the bone marrow. Radiomics analysis has been employed in the literature in an attempt to evaluate the bone marrow of MM patients. This manuscript aimed to systematically review radiomics research on MM while employing a radiomics quality score (RQS) to accurately ...
Michail Klontzas, Matthaios Triantafyllou, Dimitrios Leventis, Emmanouil Koltsakis, Georgios Kalarakis, Antonios Tzortzakakis, Apostolos Karantanas   +6 more
openaire   +3 more sources

Radiomics and dosiomics for predicting radiation-induced hypothyroidism and guiding intensity-modulated radiotherapy

iScience, 2023
Summary: To guide individualized intensity-modulated radiotherapy (IMRT), we developed and prospectively validated a multiview radiomics risk model for predicting radiation-induced hypothyroidism in patients with nasopharyngeal carcinoma.
Shan-Shan Yang, Qing-He Peng, Ai-Qian Wu, Bao-Yu Zhang, Zhi-Qiao Liu, En-Ni Chen, Fang-Yun Xie, Pu-Yun OuYang, Chun-Yan Chen   +8 more
doaj   +1 more source

Kupffer Phase Radiomics Signature in Sonazoid Contrast-Enhanced Ultrasound Predicts Immunohistochemistry Marker Expression in Hepatocellular Carcinoma. [PDF]

Cancer Med
ABSTRACT Purpose Few studies have explored the value of radiomics signatures in predicting immunohistochemical (IHC) staining markers. This study aimed to investigate and validate radiomics models based on the Kupffer phase of Sonazoid contrast‐enhanced intraoperative ultrasonography (S‐CEUS) images for predicting IHC marker expression in ...
Li C, Liu Y, Wu M, Dai W, Song J, Wang Y.   +5 more
europepmc   +2 more sources

The Image Biomarker Standardization Initiative: Standardized Convolutional Filters for Reproducible Radiomics and Enhanced Clinical Insights.

Radiology
Filters are commonly used to enhance specific structures and patterns in images, such as vessels or peritumoral regions, to enable clinical insights beyond the visible image using radiomics.
P. Whybra, A. Zwanenburg, V. Andrearczyk, Roger Schaer, Aditya Apte, Alexandre Ayotte, B. Baheti, S. Bakas, A. Bettinelli, Ronald Boellaard, Luca Boldrini, I. Buvat, Gary J R Cook, Florian Dietsche, N. Dinapoli, H. Gabryś, V. Goh, M. Guckenberger, Mathieu Hatt, Mahdi Hosseinzadeh, A. Iyer, J. Lenkowicz, M. A. L. Loutfi, Steffen Löck, F. Marturano, Olivier Morin, C. Nioche, Fanny Orlhac, Sarthak Pati, Arman Rahmim, S. M. Rezaeijo, Christopher G Rookyard, Mohammad R. Salmanpour, Andreas Schindele, I. Shiri, E. Spezi, S. Tanadini-Lang, F. Tixier, T. Upadhaya, Vincenzo Valentini, Joost J. M. van Griethuysen, F. Yousefirizi, H. Zaidi, H. Müller, M. Vallières, A. Depeursinge   +45 more
semanticscholar   +1 more source

Head and neck cancer treatment outcome prediction: a comparison between machine learning with conventional radiomics features and deep learning radiomics

Frontiers in Medicine, 2023
Background Radiomics can provide in-depth characterization of cancers for treatment outcome prediction. Conventional radiomics rely on extraction of image features within a pre-defined image region of interest (ROI) which are typically fed to a ...
B. Huynh, A. R. Groendahl, O. Tomic, K. H. Liland, I. Knudtsen, F. Hoebers, W. van Elmpt, E. Malinen, E. Dale, C. Futsaether   +9 more
semanticscholar   +1 more source