Incorporating radiomics into clinical trials: expert consensus endorsed by the European Society of Radiology on considerations for data-driven compared to biologically driven quantitative biomarkers

نویسندگان

چکیده

Abstract Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, clinical validation before incorporation into trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the data no priori assumptions on their correlation processes. The selection relevant (radiomic signature) trials therefore requires additional considerations to ensure meaningful endpoints. Also, number radiomic tested means that power calculations would result in sample sizes impossible achieve within This article examines how process standardising validating differs those based associations. Radiomic signatures best developed initially datasets represent diversity acquisition protocols as well disease normal findings, rather than standardised optimised this risk being linked pathology. Normalisation through discretisation feature harmonisation essential pre-processing steps. Biological may be performed after technical validity signature is established, but not mandatory. Feature part discovery radiomics-specific trial or exploratory endpoints an established trial; previously validated even used primary/secondary endpoint, particularly if associations demonstrated specific pathways targeted Key Points • Data-driven like radiomics false discoveries due high-dimensionality dataset compared size, making adequate data, cross-validation external mitigate risks spurious overfitting. Use multistep standardisation image acquisition, analysis mining

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Data-Driven Approaches to Improve the Quality of Clinical Processes: A Systematic Review

Background: Considering the emergence of electronic health records and their related technologies, an increasing attention is paid to data driven approaches like machine learning, data mining, and process mining. The aim of this paper was to identify and classify these approaches to enhance the quality of clinical processes. Methods: In order to determine the knowledge related to the research ...

متن کامل

Discovery Radiomics for Imaging-driven Quantitative Personalized Cancer Decision Support

In this paper, we describe the underlying methodology behind discovery radiomics, where the ultimate goal is to discover customized, abstract radiomic feature models directly from the wealth of medical imaging data to better capture highly unique tumor traits beyond what can be captured using hand-crafted radiomic feature models. We further explore the current state-of-the-art in discovery radi...

متن کامل

a study on insurer solvency by panel data model: the case of iranian insurance market

the aim of this thesis is an approach for assessing insurer’s solvency for iranian insurance companies. we use of economic data with both time series and cross-sectional variation, thus by using the panel data model will survey the insurer solvency.

American College of Cardiology/European Society of Cardiology Clinical Expert Consensus Document on Hypertrophic Cardiomyopathy

JONATHAN ABRAMS, MD, FACC ERIC R. BATES, MD, FACC BRUCE R. BRODIE, MD, FACC* PETER G. DANIAS, MD, PHD, FACC* GABRIEL GREGORATOS, MD, FACC MARK A. HLATKY, MD, FACC JUDITH S. HOCHMAN, MD, FACC *Former members of Task Force; †Former Chair of Task Force SANJIV KAUL, MBBS, FACC ROBERT C. LICHTENBERG, MD, FACC JONATHAN R. LINDNER, MD, FACC ROBERT A. O’ROURKE, MD, FACC† GERALD M. POHOST, MD, FACC RICH...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: European Radiology

سال: 2021

ISSN: ['1432-1084', '0938-7994']

DOI: https://doi.org/10.1007/s00330-020-07598-8