Literature DB >> 32500316

ESR Statement on the Validation of Imaging Biomarkers.

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Abstract

Medical imaging capable of generating imaging biomarkers, specifically radiology and nuclear medicine image acquisition and analysis processes, differs from frequently used comparators like blood or urine biomarkers. This difference arises from the sample acquisition methodology. While different analysis methodologies and equipment provide slightly different results in any analytical domain, unlike blood or urine analysis where the samples are obtained by simple extraction or excretion, in radiology the acquisition of the sample is heterogeneous by design, since complex equipment from different vendors is used. Therefore, with this additional degree of freedom in medical imaging, there is still risk of persistent heterogeneity of image quality through time, due to different technological implementations across vendors and protocols used in different centres. Quantitative imaging biomarkers have yet to demonstrate an impact on clinical practice due to this lack of comprehensive standardisation in terms of technical aspects of image acquisition, analysis algorithms, processes and clinical validation.The aim is establishing a standard methodology based on metrology for the validation of image acquisition and analysis methods used in the extraction of biomarkers and radiomics data. The appropriate implementation of the guidelines herein proposed by radiology departments, research institutes and industry will allow for a significant reduction in inter-vendor & inter-centre variability in imaging biomarkers and determine the measurement error obtained, enabling them to be used in imaging-based criteria for diagnosis, prognosis or treatment response, ultimately improving clinical workflows and patient care. The validation of developed analytical methods must be based on a technical performance validation and clinical validation.

Entities:  

Keywords:  Accuracy; Imaging biomarkers; Metrology; Precision; Validation

Year:  2020        PMID: 32500316     DOI: 10.1186/s13244-020-00872-9

Source DB:  PubMed          Journal:  Insights Imaging        ISSN: 1869-4101


  7 in total

1.  Standardised lesion segmentation for imaging biomarker quantitation: a consensus recommendation from ESR and EORTC.

Authors:  Nandita M deSouza; Aad van der Lugt; Christophe M Deroose; Angel Alberich-Bayarri; Luc Bidaut; Laure Fournier; Lena Costaridou; Daniela E Oprea-Lager; Elmar Kotter; Marion Smits; Marius E Mayerhoefer; Ronald Boellaard; Anna Caroli; Lioe-Fee de Geus-Oei; Wolfgang G Kunz; Edwin H Oei; Frederic Lecouvet; Manuela Franca; Christian Loewe; Egesta Lopci; Caroline Caramella; Anders Persson; Xavier Golay; Marc Dewey; James P B O'Connor; Pim deGraaf; Sergios Gatidis; Gudrun Zahlmann
Journal:  Insights Imaging       Date:  2022-10-04

2.  Machine learning for the prediction of pathologic pneumatosis intestinalis.

Authors:  Kadie Clancy; Esmaeel Reza Dadashzadeh; Robert Handzel; Caroline Rieser; J B Moses; Lauren Rosenblum; Shandong Wu
Journal:  Surgery       Date:  2021-04-27       Impact factor: 4.348

Review 3.  Biomarkers of Response to Biologic Therapy in Juvenile Idiopathic Arthritis.

Authors:  Varvara Choida; Margaret Hall-Craggs; Bethany R Jebson; Corinne Fisher; Maria Leandro; Lucy R Wedderburn; Coziana Ciurtin
Journal:  Front Pharmacol       Date:  2021-02-02       Impact factor: 5.810

Review 4.  Quantitative Imaging and Radiomics in Multiple Myeloma: A Potential Opportunity?

Authors:  Alberto Stefano Tagliafico; Alida Dominietto; Liliana Belgioia; Cristina Campi; Daniela Schenone; Michele Piana
Journal:  Medicina (Kaunas)       Date:  2021-01-21       Impact factor: 2.430

5.  Multivariable Diagnostic Prediction Model to Detect Hormone Secretion Profile From T2W MRI Radiomics with Artificial Neural Networks in Pituitary Adenomas.

Authors:  Begumhan Baysal; Mehmet Bilgin Eser; Mahmut Bilal Dogan; Muhammet Arif Kursun
Journal:  Medeni Med J       Date:  2022-03-18

6.  Radiomics Features Based on MRI-ADC Maps of Patients with Breast Cancer: Relationship with Lesion Size, Features Stability, and Model Accuracy.

Authors:  Begumhan Baysal; Hakan Baysal; Mehmet Bilgin Eser; Mahmut Bilal Dogan; Orhan Alimoglu
Journal:  Medeni Med J       Date:  2022-09-21

Review 7.  Why did European Radiology reject my radiomic biomarker paper? How to correctly evaluate imaging biomarkers in a clinical setting.

Authors:  Steve Halligan; Yves Menu; Sue Mallett
Journal:  Eur Radiol       Date:  2021-05-18       Impact factor: 5.315

  7 in total

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