Zehnder P, Studer UE, Skinner EC, Dorin RP, Cai J, Roth B, et al. From the Computational Imaging Research Laboratory (J.H., G.L) of the Department of Biomedical Imaging and Image-guided Therapy (S.R., F.P., H.P. Despite the promising results, radiomics faces multiple challenges . Machine Learning methods for Quantitative Radiomic Biomarkers . This is a preview of subscription content, access via your institution. The Applications of Radiomics in Precision Diagnosis and Treatment of Oncology: Opportunities and Challenges Theranostics. Can radiomics help to predict skeletal muscle response to chemotherapy in stage IV non-small cell lung cancer? 2019;49(5):1489–98. Learn more about Institutional subscriptions. J Urol. https://doi.org/10.1016/j.adro.2018.04.011. One of the major challenges lies in the optimal collection and integration of multiple data sources that can produce accurate and robust predictions… The outcome uncertainty brings additional challenges of using radiomics for cancer diagnosis and treatment outcome prognosis. Specific challenges are addressed when implementing big data concepts with high-throughput image data processing like radiomics and machine learning in a radiooncology environment to support clinical decisions. Each of these individual processes poses unique challenges. stefania.rizzo@ieo.it. CAS  An exploratory radiomics approach to quantifying pulmonary function in CT images, Radiomics nomogram analyses for differentiating pneumonia and acute paraquat lung injury, HIV-infected patients with opportunistic pulmonary infections misdiagnosed as lung cancers: the clinicoradiologic features and initial application of CT radiomics, Computed tomography-based predictive nomogram for differentiating primary progressive pulmonary tuberculosis from community-acquired pneumonia in children, Radiomic measures from chest high-resolution computed tomography associated with lung function in sarcoidosis, The utility of quantitative CT radiomics features for improved prediction of radiation pneumonitis, Lung texture in serial thoracic computed tomography scans: correlation of radiomics-based features with radiation therapy dose and radiation pneumonitis development, Radiomics-based assessment of radiation-induced lung injury after stereotactic body radiotherapy, Radiomics-based differentiation of lung disease models generated by polluted air based on x-ray computed tomography data, Serial automated quantitative CT analysis in idiopathic pulmonary fibrosis: functional correlations and comparison with changes in visual CT scores, Automated quantification of radiological patterns predicts survival in idiopathic pulmonary fibrosis, Quantitative computed tomography imaging of interstitial lung diseases, Quantitative stratification of diffuse parenchymal lung diseases, Selection of glucocorticoid-sensitive patients in interstitial lung disease secondary to connective tissue diseases population by radiomics, Chest CT texture analysis for response assessment in systemic sclerosis, Differences in texture analysis parameters between active alveolitis and lung fibrosis in chest ct of patients with systemic sclerosis: a feasibility study, Incidental findings on chest CT imaging are associated with increased COPD exacerbations and mortality, Computer-aided classification of interstitial lung diseases via MDCT: 3D adaptive multiple feature method (3D AMFM), Global burden of COPD: risk factors, prevalence, and future trends, Landmark papers in respiratory medicine: Automatic quantification of emphysema and airways disease on computed tomography, Quantitative computed tomography in COPD: possibilities and limitations, Texture-based analysis of COPD: a data-driven approach, Unsupervised discovery of emphysema subtypes in a large clinical cohort, Unsupervised discovery of spatially-informed lung texture patterns for pulmonary emphysema: the MESA COPD study, The prevalence of vertebral deformity in European men and women: the European Vertebral Osteoporosis study, Ten-year risk of osteoporotic fracture and the effect of risk factors on screening strategies, NIH consensus development panel on osteoporosis prevention, diagnosis, and therapy, March 7-29, 2000: highlights of the conference, The effect of intravertebral heterogeneity in microstructure on vertebral strength and failure patterns, Inter-observer and inter-examination variability of manual vertebral bone attenuation measurements on computed tomography, Opportunistic osteoporosis screening in multi-detector CT images via local classification of textures, Vertebral body insufficiency fractures: detection of vertebrae at risk on standard CT images using texture analysis and machine learning, Feasibility of opportunistic osteoporosis screening in routine contrast-enhanced multi detector computed tomography (MDCT) using texture analysis, Prevalence and clinical implications of sarcopenic obesity in patients with solid tumours of the respiratory and gastrointestinal tracts: a population-based study, Diagnosing sarcopenia on thoracic computed tomography: quantitative assessment of skeletal muscle mass in patients undergoing transcatheter aortic valve replacement, Multicentre evaluation of multidisciplinary team meeting agreement on diagnosis in diffuse parenchymal lung disease: a case-cohort study, Deep learning for classifying fibrotic lung disease on high-resolution computed tomography: a case-cohort study, Relationship and prognostic value of modified coronary artery calcium score, FEV1, and emphysema in lung cancer screening population: the MILD trial, Estimation of cardiovascular risk on routine chest CT: Ordinal coronary artery calcium scoring as an accurate predictor of Agatston score ranges, Automatic coronary calcium scoring in low-dose chest computed tomography, Automated coronary artery calcification scoring in non-gated chest CT: agreement and reliability, Radiomics versus visual and histogram-based assessment to identify atheromatous lesions at coronary CT angiography: an ex vivo study, Measuring computed tomography scanner variability of radiomics features, Standardization of features extracted from CT images of texture phantoms, Oncology society rolls out big-data initiative, tells why radiology should care. Reasons are heterogeneous CT scanning protocols and … An important challenge is the collection and acquisition of (large amounts of) suitable imaging data, which is difficult due to evolving technology, lack of standardization protocols and differences in cohorts and protocols between institutes. https://doi.org/10.1002/jmri.25669. However, an adequate sample size as a statistical necessity for radiomics studies is often difficult to achieve in prospective trials. The aim of radiomics is aiding clinical decision-making and outcome prediction for more personalized medicine. PubMed Central  2018;9(6):915–24. Supplemental material is available for this article. The mere presence of noninvasive nature of medical images and possibility of high spatial and temporal resolution provide major benefits over using simplistic metrics that would overlook the wealth of … Google Scholar. https://doi.org/10.1007/s13244-018-0657-7. 2018;48(1):3–6. A predictive nomogram for individualized recurrence stratification of bladder cancer using multiparametric MRI and clinical risk factors. By exploiting imaging data from clinical routine, a much larger amount of data could be used than in clinical trials. Article  More studies correlating radiomic features with disease outcomes and molecular attributes are also needed … 2018;9:1474. https://doi.org/10.3389/fimmu.2018.01474. 2011;29(22):2951–2. https://doi.org/10.1016/j.eururo.2017.03.047. Clin Cancer Res. Fig 1. Promises and challenges for the implementation of computational medical imaging (radiomics) in oncology. Chest CT scans are one of the most common medical imaging procedures. PubMed Google Scholar. - 185.111.107.11. A New Challenge for Radiologists: Radiomics in Breast Cancer Paola Crivelli , 1 Roberta Eufrasia Ledda, 2 Nicola Parascandolo , 2 Alberto Fara , 2 Daniela Soro, 2 and Maurizio Conti 2 Challenges and Promises of Radiomics for Rectal Cancer. Adv Radiat Oncol. The process and challenges in radiomics. A prospective single-center study. Radiomics is an emerging translational field of research aiming to extract mineable high-dimensional data from clinical images. For example, … An important challenge is the collection and acquisition of (large amounts of) suitable imaging data, which is difficult due to evolving technology, lack of standardization protocols and differences in cohorts and protocols between institutes. Rutman AM, Kuo MD. 2016;42(2):561–8. A systematic review of neoadjuvant and adjuvant chemotherapy for muscle-invasive bladder cancer. Wu S, Zheng J, Li Y, Yu H, Shi S, Xie W, et al. Challenges and Prospects for Radiomics. Lancet Oncol. Nat Rev Clin Oncol. https://doi.org/10.6004/jnccn.2017.0156. Since the concept of radiomics was proposed in 2012, the research using radiomics has been increasing year by year, and good research results have been achieved in various fields. CAS  2017;15(10):1240–67. Siegel RL, Miller KD, Jemal A. This study was funded by the Fundamental Research Funds for the Central Universities (Grant No. Article  Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, et al. Test-retest data for radiomics feature stability analysis: generalizable or study-specific? 2005;11(11):4044–55. Eur Urol. PubMed  Radiomics: the facts and the challenges of image analysis. Wang H, Hu D, Yao H, Chen M, Li S, Chen H, et al. Radiomics analysis has had remarkable progress along with advances in medical imaging, most notability in central nervous system malignancies. Google Scholar. https://doi.org/10.1016/S1470-2045(10)70296-5. 2014;5:4006. https://doi.org/10.1038/ncomms5006. Lambin P, Rios-Velazquez E, Leijenaar R, et al. Radiomics-guided therapy for bladder cancer: using an optimal biomarker approach to determine extent of bladder cancer invasion from t2-weighted magnetic resonance images. The methods presented may, in principle, aid clinicians with the appropriate treatment planning options. Radiomics is a quantitative approach to medical image analysis targeted at deciphering the morphologic and functional features of a lesion. https://doi.org/10.1097/RCT.0000000000000664. José Maria Moreira 1, Inês Santiago 2, João Santinha 1, Nuno Figueiredo 3, Kostas Marias 4, Mário Figueiredo 5, Leonardo Vanneschi 6 & Nickolas Papanikolaou 1 Current Colorectal Cancer Reports volume 15, pages 175 – 180 (2019)Cite this article. Eur Urol. New discoveries and technologies have begun to change paradigms of urothelial cancer therapy in recent years. Purpose of Review. https://doi.org/10.1038/nrclinonc.2017.141. J Clin Oncol. Fig 1. Enter your email address below and we will send you your username, If the address matches an existing account you will receive an email with instructions to retrieve your username. Gatenby RA et al. However, the application of radiomics is hampered by several challenges such as lack of image acquisition/analysis method standardization, impeding generalizability. Int J Urol. Eur Urol. 2019 Feb 12;9(5):1303-1322. doi: 10.7150/thno.30309. Med Phys. Eur Radiol Exp. Purpose of Review. eCollection 2019. In recent years, we have witnessed the progress of radiomics in methodologies and clinical applications. Metrics details. 7. Challenges and Prospects for Radiomics. 2009;70(2):232–41. / Magnetic Resonance Imaging 30 (2012) 1234–1248 1235. institutions and vendors. outlines this challenge in detail, specifically describing the impact of Pesapane F et al. https://doi.org/10.1016/j.eururo.2005.04.006, https://doi.org/10.1007/s11912-018-0693-y, https://doi.org/10.1016/j.ebiom.2018.01.044, https://doi.org/10.1016/j.ejca.2011.11.036, https://doi.org/10.1038/nrclinonc.2017.141, https://doi.org/10.1007/s13244-018-0657-7, https://doi.org/10.1007/s00261-016-0897-2, https://doi.org/10.1097/RCT.0000000000000664, https://doi.org/10.1007/s00330-019-06222-8, https://doi.org/10.1016/j.adro.2018.04.011, https://doi.org/10.1016/j.eururo.2011.05.062, https://doi.org/10.1016/j.juro.2011.06.004, https://doi.org/10.1016/j.ebiom.2018.07.029, https://doi.org/10.1158/1078-0432.Ccr-17-1510, https://doi.org/10.1016/j.euf.2018.11.005, https://doi.org/10.1016/j.eururo.2012.05.048, https://doi.org/10.1038/s41598-017-09315-w, https://doi.org/10.1016/j.ejrad.2009.01.050, https://doi.org/10.1158/1078-0432.CCR-05-0177, https://doi.org/10.1158/1078-0432.CCR-04-2409, https://doi.org/10.1016/j.eururo.2009.09.013, https://doi.org/10.1016/j.eururo.2009.10.029, https://doi.org/10.1016/S1470-2045(10)70296-5, https://doi.org/10.1016/j.eururo.2017.03.047, https://doi.org/10.1016/j.eururo.2017.06.012, https://doi.org/10.1016/s1470-2045(18)30413-3, https://doi.org/10.1007/s42058-019-00021-2. 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