[HTML][HTML] Radiomics in medical imaging—“how-to” guide and critical reflection

JE Van Timmeren, D Cester, S Tanadini-Lang… - Insights into …, 2020 - Springer
Radiomics is a quantitative approach to medical imaging, which aims at enhancing the
existing data available to clinicians by means of advanced mathematical analysis. Through …

Machine and deep learning methods for radiomics

M Avanzo, L Wei, J Stancanello, M Vallieres… - Medical …, 2020 - Wiley Online Library
Radiomics is an emerging area in quantitative image analysis that aims to relate large‐scale
extracted imaging information to clinical and biological endpoints. The development of …

Radiomics: the bridge between medical imaging and personalized medicine

P Lambin, RTH Leijenaar, TM Deist… - Nature reviews Clinical …, 2017 - nature.com
Radiomics, the high-throughput mining of quantitative image features from standard-of-care
medical imaging that enables data to be extracted and applied within clinical-decision …

[HTML][HTML] Deep learning for lung cancer prognostication: a retrospective multi-cohort radiomics study

A Hosny, C Parmar, TP Coroller, P Grossmann… - PLoS …, 2018 - journals.plos.org
Background Non-small-cell lung cancer (NSCLC) patients often demonstrate varying clinical
courses and outcomes, even within the same tumor stage. This study explores deep …

Guidelines for management of incidental pulmonary nodules detected on CT images: from the Fleischner Society 2017

H MacMahon, DP Naidich, JM Goo, KS Lee… - Radiology, 2017 - pubs.rsna.org
The Fleischner Society Guidelines for management of solid nodules were published in
2005, and separate guidelines for subsolid nodules were issued in 2013. Since then, new …

Monitoring immune-checkpoint blockade: response evaluation and biomarker development

M Nishino, NH Ramaiya, H Hatabu… - Nature reviews Clinical …, 2017 - nature.com
Cancer immunotherapy using immune-checkpoint blockade (ICB) has created a paradigm
shift in the treatment of advanced-stage cancers. The promising antitumour activity of …

[PDF][PDF] Reproducibility and generalizability in radiomics modeling: possible strategies in radiologic and statistical perspectives

JE Park, SY Park, HJ Kim… - Korean journal of …, 2019 - synapse.koreamed.org
Radiomics, which involves the use of high-dimensional quantitative imaging features for
predictive purposes, is a powerful tool for developing and testing medical hypotheses …

The potential of radiomic-based phenotyping in precision medicine: a review

HJWL Aerts - JAMA oncology, 2016 - jamanetwork.com
Importance Advances in genomics have led to the recognition that tumors are populated by
distinct genotypic subgroups that drive tumor development and progression. The spatial and …

[HTML][HTML] Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach

HJWL Aerts, ER Velazquez, RTH Leijenaar… - Nature …, 2014 - nature.com
Human cancers exhibit strong phenotypic differences that can be visualized noninvasively
by medical imaging. Radiomics refers to the comprehensive quantification of tumour …

Beyond imaging: the promise of radiomics

M Avanzo, J Stancanello, I El Naqa - Physica Medica, 2017 - Elsevier
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 …