Harmonization of Quantitative Parenchymal Enhancement in <scp>T<sub>1</sub></scp>‐Weighted Breast <scp>MRI</scp>

Velden, Bas H. M. van der; Rijssel, Michael J. van; Lena, Beatrice; Philippens, M.E.P.; Loo, Claudette E.; Ragusi, Max A A; Elias, Sjoerd G.; Sutton, Elizabeth; Morris, Elizabeth A.; Bartels, Lambertus W.; Gilhuijs, Kenneth G. A.

doi:10.1002/jmri.27244

Cited by 4 publications

(4 citation statements)

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“… 22 To account for MRI intensity non-uniformity, inter- and intra-site scanner variability, image processing routines, such as intensity normalisation, voxel intensity calibration and bias field correction, are used as a precursor to radiomic feature extraction. 23 – 25 The segmentation of the regions of interest (ROI) can be achieved by manual, semi-automated or fully-automated methods. 19 , 26 – 29 Radiomic features are then extracted from the identified ROIs.…”

Section: Overview Of Radiomics and Radiogenomics Workflowmentioning

confidence: 99%

Radiomics and radiogenomics in gliomas: a contemporary update

et al. 2021

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The natural history and treatment landscape of primary brain tumours are complicated by the varied tumour behaviour of primary or secondary gliomas (high-grade transformation of low-grade lesions), as well as the dilemmas with identification of radiation necrosis, tumour progression, and pseudoprogression on MRI. Radiomics and radiogenomics promise to offer precise diagnosis, predict prognosis, and assess tumour response to modern chemotherapy/immunotherapy and radiation therapy. This is achieved by a triumvirate of morphological, textural, and functional signatures, derived from a high-throughput extraction of quantitative voxel-level MR image metrics. However, the lack of standardisation of acquisition parameters and inconsistent methodology between working groups have made validations unreliable, hence multi-centre studies involving heterogenous study populations are warranted. We elucidate novel radiomic and radiogenomic workflow concepts and state-of-the-art descriptors in sub-visual MR image processing, with relevant literature on applications of such machine learning techniques in glioma management.

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Section: Overview Of Radiomics and Radiogenomics Workflowmentioning

confidence: 99%

Radiomics and radiogenomics in gliomas: a contemporary update

et al. 2021

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“…Quantification of BPE volume and intensity on MRI may be feasible in the future, but we await publication of robust data on that topic before endorsing percentage recommendations'' [1]. Several different quantitative approaches have been investigated since the publication of the fifth edition of the BI-RADS Atlas, with numerous studies in the past five years [21][22][23][24][25][26][27][28][29][30][31][32][33][34].…”

Section: Quantitative Assessmentmentioning

confidence: 99%

Background Parenchymal Enhancement on Breast MRI: Assessment and Clinical Implications

2021

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Purpose of Review To present recent literature regarding the assessment and clinical implications of background parenchymal enhancement on breast MRI. Recent Findings The qualitative assessment of BPE remains variable within the literature, as well as in clinical practice. Several different quantitative approaches have been investigated in recent years, most commonly region of interest-based and segmentation-based assessments. However, quantitative assessment has not become standard in clinical practice to date. Numerous studies have demonstrated a clear association between higher BPE and future breast cancer risk. While higher BPE does not appear to significantly impact cancer detection, it may result in a higher abnormal interpretation rate. BPE is also likely a marker of pathologic complete response after neoadjuvant chemotherapy, with decreases in BPE during and after neoadjuvant chemotherapy correlated with pCR. In contrast, pre-treatment BPE does not appear to be predictive of pCR. The association between BPE and prognosis is less clear, with heterogeneous results in the literature. Summary Assessment of BPE continues to evolve, with heterogeneity in approaches to both qualitative and quantitative assessment. The level of BPE has important clinical implications, with associations with future breast cancer risk and treatment response. BPE may also be an imaging marker of prognosis, but future research is needed on this topic.

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“…We included a large number of patients from multiple centers based on a sample size analysis. We used state-of-the-art techniques to pool data from 10 centers that had different MRI acquisitions (21). Our estimates take into consideration intercenter variability and reflect the clinical reality (hospitals use MRI systems from different vendors and different acquisition protocols), leading to realistic expectations for clinical implementation.…”

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confidence: 99%

“…We were unable to accurately estimate the effect of endocrine therapy on survival after multivariable adjustment; due to this, we were also unable to reliably estimate a possible association between endocrine therapy efficacy and CPE. Although we were able to pool MRI data from 10 centers, we were only able to correct for repetition time and flip angle (21). Remaining intercenter variability (eg, differences in contrast timing or contrast T1 relaxation times) may still have affected the results.…”

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confidence: 99%