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Radiomics and Deep Radiomics for precision medicine
, 2022 {"references": ["E Bertelli, L Mercatelli, C Marzi, E Pachetti, M Baccini, et al. Machine and Deep Learning Prediction Of Prostate Cancer Aggressiveness Using Multiparametric MRI., Fron in Oncology, 5515, 2021, https://doi.org/10.3389/fonc.2021.802964", "F Gioia, MA Pascali, A Greco, S Colantonio, EP Scilingo.
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Frontiers in Oncology, 2023 BackgroundFor patients with gastric cancer (GC), effective preoperative identification of peritoneal metastasis (PM) remains a severe challenge in clinical practice. Regrettably, effective early identification tools are still lacking up to now.
Fan Zhang, Guoxue Wu, Nan Chen, Ruyue Li
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Deep learning radiomics can predict axillary lymph node status in early-stage breast cancer
Nature Communications, 2020 Accurate identification of axillary lymph node (ALN) involvement in patients with early-stage breast cancer is important for determining appropriate axillary treatment options and therefore avoiding unnecessary axillary surgery and complications.
Xueyi Zheng +12 more
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Radiomics applications in cardiac imaging: a comprehensive review
La radiologia medica, 2023 Radiomics is a new emerging field that includes extraction of metrics and quantification of so-called radiomic features from medical images. The growing importance of radiomics applied to oncology in improving diagnosis, cancer staging and grading, and ...
Tiziano Polidori +12 more
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Cardiac Computed Tomography Radiomics [PDF]
Journal of Thoracic Imaging, 2018 Radiologic images are vast three-dimensional data sets in which each voxel of the underlying volume represents distinct physical measurements of a tissue-dependent characteristic. Advances in technology allow radiologists to image pathologies with unforeseen detail, thereby further increasing the amount of information to be processed.
Kolossváry, Márton József +3 more
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Frontiers in Oncology, 2021 BackgroundPostoperative cerebral edema is common in patients with meningioma. It is of great clinical significance to predict the postoperative cerebral edema exacerbation (CEE) for the development of individual treatment programs in patients with ...
Bing Xiao +10 more
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Radiomics of Lung Nodules: A Multi-Institutional Study of Robustness and Agreement of Quantitative Imaging Features. [PDF]
, 2016 Radiomics is to provide quantitative descriptors of normal and abnormal tissues during classification and prediction tasks in radiology and oncology. Quantitative Imaging Network members are developing radiomic "feature" sets to characterize tumors, in ...
Balagurunathan, Yoganand +19 more
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Criteria for the translation of radiomics into clinically useful tests
Nature Reviews Clinical Oncology, 2022 Despite tens of thousands of radiomic studies, the number of settings in which radiomics is used to guide clinical decision-making is limited, in part owing to a lack of standardization of the radiomic measurement extraction processes and the lack of ...
Erich P Huang +7 more
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Challenges and Promises of PET Radiomics [PDF]
International Journal of Radiation Oncology*Biology*Physics, 2018 Radiomics describes the extraction of multiple, otherwise invisible, features from medical images that, with bioinformatic approaches, can be used to provide additional information that can predict underlying tumor biology and behavior.Radiomic signatures can be used alone or with other patient-specific data to improve tumor phenotyping, treatment ...
Cook, Gary John Russell +4 more
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Insights into Imaging, 2022 Objective To develop and validate an 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT)-based radiomics nomogram for non-invasively prediction of bone marrow involvement (BMI) in pediatric neuroblastoma.
Lijuan Feng +8 more
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