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Rapid review: radiomics and breast cancer

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Abstract

Purpose

To perform a rapid review of the recent literature on radiomics and breast cancer (BC).

Methods

A rapid review, a streamlined approach to systematically identify and summarize emerging studies was done (updated 27 September 2017). Clinical studies eligible for inclusion were those that evaluated BC using a radiomics approach and provided data on BC diagnosis (detection or characterization) or BC prognosis (response to therapy, morbidity, mortality), or provided data on technical challenges (software application: open source, repeatability of results). Descriptive statistics, results, and radiomics quality score (RQS) are presented.

Results

N = 17 retrospective studies, all published after 2015, provided BC-related radiomics data on 3928 patients evaluated with a radiomics approach. Most studies were done for diagnosis and/or characterization (65%, 11/17) or to aid in prognosis (41%, 7/17). The mean number of radiomics features considered was 100. Mean RQS score was 11.88 ± 5.8 (maximum value 36). The RQS criteria related to validation, gold standard, potential clinical utility, cost analysis, and open science data had the lowest scores. The majority of studies n = 16/17 (94%) provided correlation with histological outcomes and staging variables or biomarkers. Only 4/17 (23%) studies provided evidence of correlation with genomic data. Magnetic resonance imaging (MRI) was used in most studies n = 14/17 (82%); however, ultrasound (US), mammography, or positron emission tomography with 2-deoxy-2-[fluorine-18]fluoro-d-glucose integrated with computed tomography (18F FDG PET/CT) was also used. Much heterogeneity was found for software usage.

Conclusions

The study of radiomics in BC patients is a new and emerging translational research topic. Radiomics in BC is frequently done to potentially improve diagnosis and characterization, mostly using MRI. Substantial quality limitations were found; high-quality prospective and reproducible studies are needed to further potential application.

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Abbreviations

BC:

Breast cancer

RQS:

Radiomics quality score

MRI:

Magnetic resonance imaging

US:

Ultrasound

18F FDG PET/CT:

Positron emission tomography with 2-deoxy-2-[fluorine-18]fluoro-d-glucose integrated with computed tomography

CT:

Computed tomography

PET:

Positron emission tomography

CT/PET:

Computed tomography integrated with positron emission tomography

LABC:

Locally advanced breast cancer

NAC:

Neoadjuvant chemotherapy

TCGA:

The cancer genome atlas

TCIA:

The cancer imaging archive

ER:

Estrogen receptor

PR:

Progesterone receptor

HER2:

Human epidermal growth factor receptor 2

BPE:

Background parenchymal enhancement

DCE-MRI:

Dynamic contrast-enhanced magnetic resonance imaging

SLN:

Sentinel lymph node

pCR:

Pathological complete response

ADC:

Apparent diffusion coefficient

CoLlAGe:

Co-occurrence of local anisotropic gradient orientations

PAM50:

Prediction analysis of microarray 50

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Funding

Alberto Stefano Tagliafico received funding under grants: AIRC Associazione Italiana Ricerca sul Cancro IG 15697. N. Houssami received research support through a National Breast Cancer Foundation (NBCF Australia), Breast Cancer Research Leadership Fellowship.

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Authors and Affiliations

  1. Department of Health Sciences, University of Genova, Via L.B. Alberti 2, 16132, Genoa, Italy

    Francesca Valdora, Federica Rossi & Alberto Stefano Tagliafico

  2. Sydney School of Public Health, Sydney Medical School, University of Sydney, Sydney, NSW, Australia

    Nehmat Houssami

  3. Ospedale Policlinico San Martino IST, Genoa, Italy

    Massimo Calabrese & Alberto Stefano Tagliafico

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  1. Francesca Valdora
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  2. Nehmat Houssami
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Correspondence to Alberto Stefano Tagliafico.

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Valdora, F., Houssami, N., Rossi, F. et al. Rapid review: radiomics and breast cancer. Breast Cancer Res Treat 169, 217–229 (2018). https://doi.org/10.1007/s10549-018-4675-4

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