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» Authors » Kenneth G A Gilhuijs

Kenneth G A Gilhuijs

Explore the profile of Kenneth G A Gilhuijs including associated specialties, affiliations and a list of published articles. Areas
Snapshot
Articles 67
Citations 980
Followers 0
Related Specialties
Radiology
Oncology
Biophysics
Top 10 Co-Authors
Claudette E Loo
Bas H M van der Velden
Jelle Wesseling
Emiel J Th Rutgers
Marie-Jeanne T F D Vrancken Peeters
Ruud M Pijnappel
Max A Viergever
Wouter B Veldhuis
Eline E Deurloo
Erik Verburg
Published In
Radiology
Med Phys
Eur Radiol
Invest Radiol
Eur J Nucl Med Mol Imaging
Affiliations
Soon will be listed here.
Recent Articles
1.
Automated rating of background parenchymal enhancement in MRI of extremely dense breasts without compromising the association with breast cancer in the DENSE trial
Wang H, H M van der Velden B, Verburg E, Bakker M, Pijnappel R, Veldhuis W, et al.
Eur J Radiol . 2024 Apr; 175:111442. PMID: 38583349
Objectives: Background parenchymal enhancement (BPE) on dynamic contrast-enhanced MRI (DCE-MRI) as rated by radiologists is subject to inter- and intrareader variability. We aim to automate BPE category from DCE-MRI. Methods:...
2.
High-dose alkylating chemotherapy in BRCA-altered triple-negative breast cancer: the randomized phase III NeoTN trial
Vliek S, Hilbers F, van Werkhoven E, Mandjes I, Kessels R, Kleiterp S, et al.
NPJ Breast Cancer . 2023 Sep; 9(1):75. PMID: 37689749
Exploratory analyses of high-dose alkylating chemotherapy trials have suggested that BRCA1 or BRCA2-pathway altered (BRCA-altered) breast cancer might be particularly sensitive to this type of treatment. In this study, patients...
3.
Assessing Quantitative Parenchymal Features at Baseline Dynamic Contrast-enhanced MRI and Cancer Occurrence in Women with Extremely Dense Breasts
Wang H, H M van der Velden B, Verburg E, Bakker M, Pijnappel R, Veldhuis W, et al.
Radiology . 2023 Aug; 308(2):e222841. PMID: 37552061
Background Automated identification of quantitative breast parenchymal enhancement features on dynamic contrast-enhanced (DCE) MRI scans could provide added value in assessment of breast cancer risk in women with extremely dense...
4.
Long-term Survival in Breast Cancer Patients Is Associated with Contralateral Parenchymal Enhancement at MRI: Outcomes of the SELECT Study
Ragusi M, H M van der Velden B, Meeuwis C, Tetteroo E, Coerkamp E, van Nijnatten T, et al.
Radiology . 2023 Mar; 307(4):e221922. PMID: 36975820
Background Several single-center studies found that high contralateral parenchymal enhancement (CPE) at breast MRI was associated with improved long-term survival in patients with estrogen receptor (ER)-positive and human epidermal growth...
5.
Deep Learning-Based Segmentation of Locally Advanced Breast Cancer on MRI in Relation to Residual Cancer Burden: A Multi-Institutional Cohort Study
Janse M, Janssen L, H M van der Velden B, Moman M, Wolters-van der Ben E, Kock M, et al.
J Magn Reson Imaging . 2023 Mar; 58(6):1739-1749. PMID: 36928988
Background: While several methods have been proposed for automated assessment of breast-cancer response to neoadjuvant chemotherapy on breast MRI, limited information is available about their performance across multiple institutions. Purpose:...
6.
Validation of Combined Deep Learning Triaging and Computer-Aided Diagnosis in 2901 Breast MRI Examinations From the Second Screening Round of the Dense Tissue and Early Breast Neoplasm Screening Trial
Verburg E, van Gils C, H M van der Velden B, Bakker M, Pijnappel R, Veldhuis W, et al.
Invest Radiol . 2022 Oct; 58(4):293-298. PMID: 36256783
Objectives: Computer-aided triaging (CAT) and computer-aided diagnosis (CAD) of screening breast magnetic resonance imaging have shown potential to reduce the workload of radiologists in the context of dismissing normal breast...
7.
Improving prediction of response to neoadjuvant treatment in patients with breast cancer by combining liquid biopsies with multiparametric MRI: protocol of the LIMA study - a multicentre prospective observational cohort study
Janssen L, Suelmann B, Elias S, Janse M, van Diest P, van der Wall E, et al.
BMJ Open . 2022 Sep; 12(9):e061334. PMID: 36127090
Introduction: The response to neoadjuvant chemotherapy (NAC) in breast cancer has important prognostic implications. Dynamic prediction of tumour regression by NAC may allow for adaption of the treatment plan before...
8.
Explainable artificial intelligence (XAI) in deep learning-based medical image analysis
H M van der Velden B, Kuijf H, Gilhuijs K, Viergever M
Med Image Anal . 2022 May; 79:102470. PMID: 35576821
With an increase in deep learning-based methods, the call for explainability of such methods grows, especially in high-stakes decision making areas such as medical image analysis. This survey presents an...
9.
Contralateral parenchymal enhancement on MRI is associated with tumor proteasome pathway gene expression and overall survival of early ER+/HER2-breast cancer patients
Ragusi M, Bismeijer T, H M van der Velden B, Loo C, Canisius S, Wesseling J, et al.
Breast . 2021 Nov; 60:230-237. PMID: 34763270
Purpose: To assess whether contralateral parenchymal enhancement (CPE) on MRI is associated with gene expression pathways in ER+/HER2-breast cancer, and if so, whether such pathways are related to survival. Methods:...
10.
Deep Learning for Automated Triaging of 4581 Breast MRI Examinations from the DENSE Trial
Verburg E, van Gils C, H M van der Velden B, Bakker M, Pijnappel R, Veldhuis W, et al.
Radiology . 2021 Oct; 302(1):29-36. PMID: 34609196
Background Supplemental screening with MRI has proved beneficial in women with extremely dense breasts. Most MRI examinations show normal anatomic and physiologic variation that may not require radiologic review. Thus,...