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Open Access 01-01-2021 | Editorial

A decade of radiomics research: are images really data or just patterns in the noise?

Authors: Daniel Pinto dos Santos, Matthias Dietzel, Bettina Baessler

Published in: European Radiology | Issue 1/2021

Key Points

• Although radiomics is potentially a promising approach to analyze medical image data, many pitfalls need to be considered to avoid a reproducibility crisis.

• There is a translation gap in radiomics research, with many studies being published but so far little to no translation into clinical practice.

• Going forward, more studies with higher levels of evidence are needed, ideally also focusing on prospective studies with relevant clinical impact.

Lambin P, Rios-Velazquez E, Leijenaar R et al (2012) Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer 48(4):441–446CrossRef

Lambin P, Leijenaar RTH, Deist TM et al (2017) Radiomics: the bridge between medical imaging and personalized medicine. Nat Rev Clin Oncol 14(12):749–762CrossRef

Gillies RJ, Kinahan PE, Hricak H (2016) Radiomics: images are more than pictures, they are data. Radiology 278(2):563–577CrossRef

Savadjiev P, Chong J, Dohan A et al (2019) Image-based biomarkers for solid tumor quantification. Eur Radiol 29(10):5431–5440CrossRef

Cui Y, Yang X, Shi Z et al (2019) Radiomics analysis of multiparametric MRI for prediction of pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. Eur Radiol 29(3):1211–1220CrossRef

Baessler B, Nestler T, Pinto dos Santos D et al (2020) Radiomics allows for detection of benign and malignant histopathology in patients with metastatic testicular germ cell tumors prior to post-chemotherapy retroperitoneal lymph node dissection. Eur Radiol 30(4):2334–2345CrossRef

Zwanenburg A (2019) Radiomics in nuclear medicine: robustness, reproducibility, standardization, and how to avoid data analysis traps and replication crisis. Eur J Nucl Med Mol Imaging 46(13):2638–2655CrossRef

Park JE, Kim D, Kim HS, et al (2019) Quality of science and reporting of radiomics in oncologic studies: room for improvement according to radiomics quality score and TRIPOD statement. Eur Radiol 30(1):523–536

Mongan J, Moy L, Kahn CE (2020) Checklist for artificial intelligence in medical imaging (CLAIM): a guide for authors and reviewers. Radiol Artif Intell 2(2):e200029CrossRef

10.

Molina D, Pérez-Beteta J, Martínez-González A, et al (2017) Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization. PLoS One 12(6):e0178843

11.

Berenguer R, del Rosario Pastor Juan M, Canales-Vázquez J et al (2018) Radiomics of CT features may be nonreproducible and redundant: influence of CT acquisition parameters. Radiology. 288(2):407–415CrossRef

12.

Foster KR, Koprowski R, Skufca JD (2014) Machine learning, medical diagnosis, and biomedical engineering research - commentary. Biomed Eng Online 13(1):94CrossRef

13.

Molina-García D, Vera-Ramírez L, Pérez-Beteta J, Arana E, Pérez-García VM (2019) Prognostic models based on imaging findings in glioblastoma: human versus machine. Sci Rep 9(1):5982CrossRef

14.

Di Leo G, Sardanelli F (2020) Statistical significance: p value, 0.05 threshold, and applications to radiomics—reasons for a conservative approach. Eur Radiol Exp 4(1):18CrossRef

15.

Dewey M, Bosserdt M, Dodd JD, Thun S, Kressel HY (2019) Clinical imaging research: higher evidence, global collaboration, improved reporting, and data sharing are the grand challenges. Radiology. 291(3):547–552CrossRef

16.

Sardanelli F, Alì M, Hunink MG, Houssami N, Sconfienza LM, Di Leo G (2018) To share or not to share? Expected pros and cons of data sharing in radiological research. Eur Radiol 28(6):2328–2335CrossRef

17.

Ter-Pogossian M, Weiss E, Coleman R, Sobel B (1976) Computed tomography of the heart. AJR Am J Roentgenol 127(1):79–90CrossRef

Title: A decade of radiomics research: are images really data or just patterns in the noise?
Authors: Daniel Pinto dos Santos
Matthias Dietzel
Bettina Baessler
Publication date: 01-01-2021
Publisher: Springer Berlin Heidelberg
Published in: European Radiology / Issue 1/2021
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-020-07108-w

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A decade of radiomics research: are images really data or just patterns in the noise?

Key Points

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Key Points

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