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Article
Can we predict pathology without surgery? Weighing the added value of multiparametric MRI and whole prostate radiomics in integrative machine learning models
To test the ability of high-performance machine learning (ML) models employing clinical, radiological, and radiomic variables to improve non-invasive prediction of the pathological status of prostate cancer (P...
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Article
Open AccessQuality assurance for automatically generated contours with additional deep learning
Deploying an automatic segmentation model in practice should require rigorous quality assurance (QA) and continuous monitoring of the model’s use and performance, particularly in high-stakes scenarios such as ...
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Article
Open AccessWhole-body magnetic resonance imaging (WB-MRI) for cancer screening: recommendations for use
Whole-body magnetic resonance imaging (WB-MRI) is currently recommended for cancer screening in adult and paediatric subjects with cancer predisposition syndromes, representing a substantial aid for prolonging...
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Article
MRI-based radiomics signature for localized prostate cancer: a new clinical tool for cancer aggressiveness prediction? Sub-study of prospective phase II trial on ultra-hypofractionated radiotherapy (AIRC IG-13218)
Radiomic involves testing the associations of a large number of quantitative imaging features with clinical characteristics. Our aim was to extract a radiomic signature from axial T2-weighted (T2-W) magnetic r...
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Article
Open AccessLow PI-RADS assessment category excludes extraprostatic extension (≥pT3a) of prostate cancer: a histology-validated study including 301 operated patients
To evaluate whether low PI-RADS v2 assessment categories are effective at excluding extraprostatic extension (EPE) of prostate cancer (≥pT3a PCa).
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Article
Whole-body magnetic resonance imaging (WB-MRI) in oncology: recommendations and key uses
The past decade has witnessed a growing role and increasing use of whole-body magnetic resonance imaging (WB-MRI). Driving these successes are developments in both hardware and software that have reduced overa...