Beyond imaging: The promise of radiomics
- PMID: 28595812
- DOI: 10.1016/j.ejmp.2017.05.071
Beyond imaging: The promise of radiomics
Abstract
The domain of investigation of radiomics consists of large-scale radiological image analysis and association with biological or clinical endpoints. The purpose of the present study is to provide a recent update on the status of this rapidly emerging field by performing a systematic review of the literature on radiomics, with a primary focus on oncologic applications. The systematic literature search, performed in Pubmed using the keywords: "radiomics OR radiomic" provided 97 research papers. Based on the results of this search, we describe the methods used for building a model of prognostic value from quantitative analysis of patient images. Then, we provide an up-to-date overview of the results achieved in this field, and discuss the current challenges and future developments of radiomics for oncology.
Keywords: Image features; Modelling; Quantitative imaging; Radiomics; Response; Segmentation; Textural.
Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
Similar articles
-
Magnetic resonance perfusion for differentiating low-grade from high-grade gliomas at first presentation.Cochrane Database Syst Rev. 2018 Jan 22;1(1):CD011551. doi: 10.1002/14651858.CD011551.pub2. Cochrane Database Syst Rev. 2018. PMID: 29357120 Free PMC article.
-
Enhancing Preoperative Diagnosis of Subscapular Muscle Injuries with Shoulder MRI-based Multimodal Radiomics.Acad Radiol. 2025 Feb;32(2):907-915. doi: 10.1016/j.acra.2024.09.049. Epub 2024 Oct 5. Acad Radiol. 2025. PMID: 39370313
-
Cost-effectiveness of using prognostic information to select women with breast cancer for adjuvant systemic therapy.Health Technol Assess. 2006 Sep;10(34):iii-iv, ix-xi, 1-204. doi: 10.3310/hta10340. Health Technol Assess. 2006. PMID: 16959170
-
Organomics: A Concept Reflecting the Importance of PET/CT Healthy Organ Radiomics in Non-Small Cell Lung Cancer Prognosis Prediction Using Machine Learning.Clin Nucl Med. 2024 Oct 1;49(10):899-908. doi: 10.1097/RLU.0000000000005400. Clin Nucl Med. 2024. PMID: 39192505
-
Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID-19.Cochrane Database Syst Rev. 2022 May 20;5(5):CD013665. doi: 10.1002/14651858.CD013665.pub3. Cochrane Database Syst Rev. 2022. PMID: 35593186 Free PMC article.
Cited by
-
Machine learning-based texture analysis for differentiation of radiologically indeterminate small adrenal tumors on adrenal protocol CT scans.Abdom Radiol (NY). 2021 Oct;46(10):4853-4863. doi: 10.1007/s00261-021-03136-2. Epub 2021 Jun 3. Abdom Radiol (NY). 2021. PMID: 34085089
-
Prognostic Nutritional Index Predicts Toxicity in Head and Neck Cancer Patients Treated with Definitive Radiotherapy in Association with Chemotherapy.Nutrients. 2021 Apr 13;13(4):1277. doi: 10.3390/nu13041277. Nutrients. 2021. PMID: 33924581 Free PMC article.
-
Reproducibility of lung nodule radiomic features: Multivariable and univariable investigations that account for interactions between CT acquisition and reconstruction parameters.Med Phys. 2021 Jun;48(6):2906-2919. doi: 10.1002/mp.14830. Epub 2021 Apr 13. Med Phys. 2021. PMID: 33706419 Free PMC article.
-
Radiomics approach based on biphasic CT images well differentiate "early stage" of adrenal metastases from lipid-poor adenomas: A STARD compliant article.Medicine (Baltimore). 2022 Sep 23;101(38):e30856. doi: 10.1097/MD.0000000000030856. Medicine (Baltimore). 2022. PMID: 36197274 Free PMC article.
-
Machine learning for predicting accuracy of lung and liver tumor motion tracking using radiomic features.Quant Imaging Med Surg. 2023 Mar 1;13(3):1605-1618. doi: 10.21037/qims-22-621. Epub 2023 Jan 9. Quant Imaging Med Surg. 2023. PMID: 36915317 Free PMC article.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources
