Related Experiment Video
Updated: Jan 19, 2026

A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds
Published on: April 6, 2016
Factors predictive of the presence of a CSF1R mutation in patients with leukoencephalopathy
Y Kondo1,2, A Matsushima3, S Nagasaki1
1Department of Medicine (Neurology and Rheumatology), Shinshu University School of Medicine, Matsumoto, Japan.
Background And Purpose:
The purpose was to identify statistically factors that correlate with the presence of a colony-stimulating factor 1 receptor (CSF1R) mutation and to reevaluate the accuracy of the current diagnostic criteria for CSF1R-related leukoencephalopathy.
Methods:
CSF1R testing was conducted on 145 consecutive leukoencephalopathy cases who were clinically suspected of having adult-onset leukoencephalopathy with axonal spheroids and pigmented glia. From these, 135 cases whose detailed clinical information was available were enrolled. Forward logistic stepwise regression was performed to generate a probability model to predict a positive CSF1R mutation result. The current diagnostic criteria were also applied to our cohort and their sensitivity and specificity were calculated.
Results:
Twenty-eight CSF1R-mutation-positive cases and 107 CSF1R-mutation-negative cases were identified. Our probability model suggested that factors raising the probability of a CSF1R-mutation-positive result were younger onset, parkinsonism, thinning of the corpus callosum and diffusion-restricted lesions. It also showed that involuntary movements and brainstem or cerebellar atrophy were negative predictors of a CSF1R-mutation-positive result. In our cohort, the sensitivity and specificity for 'probable' or 'possible' CSF1R-related leukoencephalopathy were 81% and 14%, respectively.
Conclusions:
Clinical and brain imaging features predictive of the presence of a CSF1R mutation are proposed. Consideration of these factors will help prioritize patients for CSF1R testing.
More Related Videos
04:01Author Spotlight: Modeling Brain Tumors In Vivo Using Electroporation-Based Delivery of Plasmid DNA Representing Patient Mutation Signatures
Published on: June 23, 2023
05:51A Strategy to Identify de Novo Mutations in Common Disorders such as Autism and Schizophrenia
Published on: June 15, 2011
Related Concept Videos
13:34A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds
Factors Affecting Protein-Drug Binding: Patient-Related Factors
Age stands as a key determinant in protein-drug binding. Neonates, characterized by low albumin content, experience heightened concentrations of unbound drugs such as phenytoin and...
04:01Modeling Brain Tumors In Vivo Using Electroporation-Based Delivery of Plasmid DNA Representing Patient Mutation Signatures
Mutations
05:51A Strategy to Identify de Novo Mutations in Common Disorders such as Autism and Schizophrenia
07:42Patient-Derived Tumor Explants As a "Live" Preclinical Platform for Predicting Drug Resistance in Patients