document

Automated Assessment of T2-Weighted MRI to Differentiate Malignant and Benign Primary Solid Liver Lesions in Noncirrhotic Livers Using Radiomics

Starmans, M.P.A. (author), Miclea, Razvan L. (author), Vilgrain, Valerie (author), Ronot, Maxime (author), Purcell, Yvonne (author), Verbeek, Jef (author), Niessen, W.J. (author), Klein, Stefan (author), Thomeer, Maarten G. (author)

Rationale and Objectives: Distinguishing malignant from benign liver lesions based on magnetic resonance imaging (MRI) is an important but often challenging task, especially in noncirrhotic livers. We developed and externally validated a radiomics model to quantitatively assess T2-weighted MRI to distinguish the most common malignant and...

journal article 2024

document

Computer-Aided Diagnosis and Prediction in Brain Disorders

Venkatraghavan, Vikram (author), Voort, Sebastian R.van der (author), Bos, Daniel (author), Smits, M. (author), Barkhof, Frederik (author), Niessen, W.J. (author), Klein, Stefan (author), Bron, Esther E. (author)

Computer-aided methods have shown added value for diagnosing and predicting brain disorders and can thus support decision making in clinical care and treatment planning. This chapter will provide insight into the type of methods, their working, their input data –such as cognitive tests, imaging, and genetic data– and the types of output they...

book chapter 2023

document

Combined molecular subtyping, grading, and segmentation of glioma using multi-task deep learning

van der Voort, Sebastian R. (author), Incekara, Fatih (author), Wijnenga, Maarten M.J. (author), Kapsas, Georgios (author), Schouten, J.W. (author), French, P.J. (author), Niessen, W.J. (author), Smits, M. (author), Klein, Stefan (author)

BACKGROUND: Accurate characterization of glioma is crucial for clinical decision making. A delineation of the tumor is also desirable in the initial decision stages but is time-consuming. Previously, deep learning methods have been developed that can either non-invasively predict the genetic or histological features of glioma, or that can...

journal article 2023

document

Differential Diagnosis and Molecular Stratification of Gastrointestinal Stromal Tumors on CT Images Using a Radiomics Approach

Starmans, Martijn P.A. (author), Timbergen, Milea J.M. (author), Vos, Melissa (author), Renckens, Michel (author), Grünhagen, Dirk J. (author), van Leenders, Geert J.L.H. (author), Niessen, W.J. (author), Visser, Jacob J. (author), Klein, Stefan (author)

Treatment planning of gastrointestinal stromal tumors (GISTs) includes distinguishing GISTs from other intra-abdominal tumors and GISTs’ molecular analysis. The aim of this study was to evaluate radiomics for distinguishing GISTs from other intra-abdominal tumors, and in GISTs, predict the c-KIT, PDGFRA, BRAF mutational status, and mitotic...

journal article 2022

document

A multi-center, multi-vendor study to evaluate the generalizability of a radiomics model for classifying prostate cancer: High grade vs. low grade

Castillo, J.M. (author), Starmans, M.P.A. (author), Arif, M. (author), Niessen, W.J. (author), Klein, Stefan (author), Bangma, Chris H. (author), Schoots, Ivo G. (author), Veenland, J.F. (author)

Radiomics applied in MRI has shown promising results in classifying prostate cancer lesions. However, many papers describe single-center studies without external validation. The issues of using radiomics models on unseen data have not yet been sufficiently addressed. The aim of this study is to evaluate the generalizability of radiomics...

journal article 2021

document

Cross-cohort generalizability of deep and conventional machine learning for MRI-based diagnosis and prediction of Alzheimer's disease

Bron, Esther E. (author), Klein, Stefan (author), Papma, Janne M. (author), Jiskoot, Lize C. (author), Venkatraghavan, Vikram (author), Linders, Jara (author), Aalten, Pauline (author), De Deyn, Peter Paul (author), Niessen, W.J. (author)

This work validates the generalizability of MRI-based classification of Alzheimer's disease (AD) patients and controls (CN) to an external data set and to the task of prediction of conversion to AD in individuals with mild cognitive impairment (MCI). We used a conventional support vector machine (SVM) and a deep convolutional neural network ...

journal article 2021

document

Progression along data-driven disease timelines is predictive of Alzheimer's disease in a population-based cohort

Venkatraghavan, Vikram (author), Vinke, Elisabeth J. (author), Bron, Esther E. (author), Niessen, W.J. (author), Arfan Ikram, M. (author), Klein, S. (author), Vernooij, Meike W. (author)

Data-driven disease progression models have provided important insight into the timeline of brain changes in AD phenotypes. However, their utility in predicting the progression of pre-symptomatic AD in a population-based setting has not yet been investigated. In this study, we investigated if the disease timelines constructed in a case...

journal article 2021

document

Longitudinal diffusion MRI analysis using Segis-Net: A single-step deep-learning framework for simultaneous segmentation and registration

Li, Bo (author), Niessen, W.J. (author), Klein, Stefan (author), de Groot, Marius (author), Ikram, M. Arfan (author), Vernooij, Meike W. (author), Bron, Esther E. (author)

This work presents a single-step deep-learning framework for longitudinal image analysis, coined Segis-Net. To optimally exploit information available in longitudinal data, this method concurrently learns a multi-class segmentation and nonlinear registration. Segmentation and registration are modeled using a convolutional neural network and...

journal article 2021

document

Differences Between MR Brain Region Segmentation Methods: Impact on Single-Subject Analysis

Huizinga, W. (author), Poot, D.H.J. (author), Vinke, E. J. (author), Wenzel, F. (author), Bron, E. E. (author), Ikram, M. A. (author), Niessen, W.J. (author), Vernooij, M.N.A. (author), Klein, S. (author)

For the segmentation of magnetic resonance brain images into anatomical regions, numerous fully automated methods have been proposed and compared to reference segmentations obtained manually. However, systematic differences might exist between the resulting segmentations, depending on the segmentation method and underlying brain atlas. This...

journal article 2021

document

Recurrent inference machines as inverse problem solvers for MR relaxometry

Sabidussi, E. R. (author), Klein, S. (author), Caan, M. W.A. (author), Bazrafkan, S. (author), den Dekker, A. J. (author), Sijbers, J. (author), Niessen, W.J. (author), Poot, D.H.J. (author)

In this paper, we propose the use of Recurrent Inference Machines (RIMs) to perform T₁ and T₂ mapping. The RIM is a neural network framework that learns an iterative inference process based on the signal model, similar to conventional statistical methods for quantitative MRI (QMRI), such as the Maximum Likelihood...

journal article 2021

document

The BRAF P.V600E Mutation Status of Melanoma Lung Metastases Cannot Be Discriminated on Computed Tomography by LIDC Criteria nor Radiomics Using Machine Learning

Angus, Lindsay (author), Starmans, M.P.A. (author), Rajicic, Ana (author), Odink, Arlette E. (author), Jalving, Mathilde (author), Niessen, W.J. (author), Visser, Jacob J. (author), Sleijfer, Stefan (author), Klein, Stefan (author), van der Veldt, Astrid A.M. (author)

Patients with BRAF mutated (BRAF-mt) metastatic melanoma benefit significantly from treatment with BRAF inhibitors. Currently, the BRAF status is determined on archival tumor tissue or on fresh tumor tissue from an invasive biopsy. The aim of this study was to evaluate whether radiomics can predict the BRAF status in a non-invasive manner....

journal article 2021

document

Analyzing the effect of APOE on Alzheimer's disease progression using an event-based model for stratified populations

Venkatraghavan, Vikram (author), Klein, S. (author), Fani, Lana (author), Ham, Leontine S. (author), Vrooman, Henri (author), Ikram, M. Kamran (author), Niessen, W.J. (author), Bron, Esther E. (author)

Alzheimer's disease (AD) is the most common form of dementia and is phenotypically heterogeneous. APOE is a triallelic gene which correlates with phenotypic heterogeneity in AD. In this work, we determined the effect of APOE alleles on the disease progression timeline of AD using a discriminative event-based model (DEBM). Since DEBM is a data...

journal article 2020

document

Predicting Global Cognitive Decline in the General Population Using the Disease State Index

Cremers, Lotte G.M. (author), Huizinga, Wyke (author), Niessen, W.J. (author), Krestin, Gabriel P. (author), Poot, D.H.J. (author), Ikram, M. Arfan (author), Lötjönen, Jyrki (author), Klein, S. (author), Vernooij, Meike W. (author)

Background: Identifying persons at risk for cognitive decline may aid in early detection of persons at risk of dementia and to select those that would benefit most from therapeutic or preventive measures for dementia. Objective: In this study we aimed to validate whether cognitive decline in the general population can be predicted with...

journal article 2020

document

Differential diagnosis and mutation stratification of desmoid-type fibromatosis on MRI using radiomics

Timbergen, Milea J.M. (author), Starmans, Martijn P.A. (author), Padmos, Guillaume A. (author), Grünhagen, Dirk J. (author), van Leenders, Geert J.L.H. (author), Hanff, D. F. (author), Niessen, W.J. (author), Klein, S. (author), Visser, J.J. (author)

Purpose: Diagnosing desmoid-type fibromatosis (DTF) requires an invasive tissue biopsy with β-catenin staining and CTNNB1 mutational analysis, and is challenging due to its rarity. The aim of this study was to evaluate radiomics for distinguishing DTF from soft tissue sarcomas (STS), and in DTF, for predicting the CTNNB1 mutation types....

journal article 2020

document

Disease progression timeline estimation for Alzheimer's disease using discriminative event based modeling

Venkatraghavan, Vikram (author), Bron, Esther E. (author), Niessen, W.J. (author), Klein, S. (author)

Alzheimer's Disease (AD) is characterized by a cascade of biomarkers becoming abnormal, the pathophysiology of which is very complex and largely unknown. Event-based modeling (EBM) is a data-driven technique to estimate the sequence in which biomarkers for a disease become abnormal based on cross-sectional data. It can help in understanding...

journal article 2019

document

Trajectories of imaging markers in brain aging: the Rotterdam Study

Vinke, Elisabeth J. (author), de Groot, Marius (author), Venkatraghavan, Vikram (author), Klein, S. (author), Niessen, W.J. (author), Ikram, M. Arfan (author), Vernooij, Meike W. (author)

With aging, the brain undergoes several structural changes. These changes reflect the normal aging process and are therefore not necessarily pathologic. In fact, better understanding of these normal changes is an important cornerstone to also disentangle pathologic changes. Several studies have investigated normal brain aging, both cross...

journal article 2018

document

Intrasubject multimodal groupwise registration with the conditional template entropy

Polfliet, Mathias (author), Klein, S. (author), Huizinga, W. (author), Paulides, Margarethus M. (author), Niessen, W.J. (author), Vandemeulebroucke, Jef (author)

Image registration is an important task in medical image analysis. Whereas most methods are designed for the registration of two images (pairwise registration), there is an increasing interest in simultaneously aligning more than two images using groupwise registration. Multimodal registration in a groupwise setting remains difficult, due to...

journal article 2018

document

A spatio-temporal reference model of the aging brain

huizinga, w (author), Poot, D.H.J. (author), Vernooij, Meike W. (author), Roshchupkin, G.V. (author), bron, E.E. (author), Ikram, M.A. (author), Rueckert, D. (author), Niessen, W.J. (author), Klein, S. (author)

Both normal aging and neurodegenerative disorders such as Alzheimer's disease (AD) cause morphological changes of the brain. It is generally difficult to distinguish these two causes of morphological change by visual inspection of magnetic resonance (MR) images. To facilitate making this distinction and thus aid the diagnosis of...

journal article 2018

document

Classification of malignant and benign liver tumors using a radiomics approach

Starmans, Martijn P.A. (author), Miclea, Razvan L. (author), van der Voort, S.R. (author), Niessen, W.J. (author), Thomeer, Maarten G. (author), Klein, S. (author)

Correct diagnosis of the liver tumor phenotype is crucial for treatment planning, especially the distinction between malignant and benign lesions. Clinical practice includes manual scoring of the tumors on Magnetic Resonance (MR) images by a radiologist. As this is challenging and subjective, it is often followed by a biopsy. In this study,...

conference paper 2018

document

Groupwise image registration based on a total correlation dissimilarity measure for quantitative MRI and dynamic imaging data

Guyader, Jean Marie (author), Huizinga, W. (author), Poot, D.H.J. (author), van Kranenburg, Matthijs (author), Uitterdijk, André (author), Niessen, W.J. (author), Klein, S. (author)

The most widespread technique used to register sets of medical images consists of selecting one image as fixed reference, to which all remaining images are successively registered. This pairwise scheme requires one optimization procedure per pair of images to register. Pairwise mutual information is a common dissimilarity measure applied to a...

journal article 2018