Classification of neoplastic and inflammatory brain disease using MRI texture analysis in 119 dogs

Abstract

Magnetic resonance imaging is the primary method used to diagnose canine glial cell neoplasia and noninfectious inflammatory meningoencephalitis. Subjective differentiation of these diseases can be difficult due to overlapping imaging characteristics. This study utilizes texture analysis (TA) of intra‐axial lesions both as a means to quantitatively differentiate these broad categories of disease and to help identify glial tumor grade/cell type and specific meningoencephalitis subtype in a group of 119 dogs with histologically confirmed diagnoses. Fifty‐nine dogs with gliomas and 60 dogs with noninfectious inflammatory meningoencephalitis were retrospectively recruited and randomly split into training (n = 80) and test (n = 39) cohorts. Forty‐five of 120 texture metrics differed significantly between cohorts after correcting for multiple testing (false discovery rate < 0.05). After training the random forest algorithm, the classification accuracy for the test set was 85% (sensitivity 89%, specificity 81%). TA was only partially able to differentiate the inflammatory subtypes (granulomatous meningoencephalitis [GME], necrotizing meningoencephalitis [NME], and necrotizing leukoencephalitis [NLE]) (out‐of‐bag error rate of 35.0%) and was unable to identify metrics that could correctly classify glioma grade or cell type (out‐of‐bag error rate of 59.6% and 47.5%, respectively). Multiple demographic differences, such as patient age, sex, weight, and breed were identified between disease cohorts and subtypes which may be useful in prioritizing differential diagnoses. TA of MR images with a random forest algorithm provided classification accuracy of inflammatory and neoplastic brain disease approaching the accuracy of previously reported subjective radiologist evaluation.

A New Framework for Precise Identification of Prostatic Adenocarcinoma

“…Texture analysis (TA) is a significant field of study in medical imaging applications. TA has been utilized in the diagnosis of a variety of cancers [31,[35][36][37]. There is no precise definition of TA, however, it can be described as the analysis of the spatial distribution of patterns that gives the visual appearance of roughness, randomness, smoothness, fluency, etc.…”

Detection of blood‐brain barrier dysfunction using advanced imaging methods to predict seizures in dogs with meningoencephalitis of unknown origin

“… 1 Granulomatous meningoencephalitis, necrotizing meningoencephalomyelitis, and necrotizing leukoencephalitis are 3 distinct MUO disorders identified by histological evaluation. 2 , 3 , 4 Although the pathogenesis of MUO is unclear, it is most likely multifactorial, combining genetic predisposition with factors triggering an excessive immunologic response. 3 , 4 Tentative diagnosis is based on clinical presentation, inflammatory cerebrospinal fluid (CSF) findings, magnetic resonance imaging (MRI) abnormalities, and lack of an identified infectious agent.…”

“…Meningoencephalitis of unknown origin (MUO) is a group of idiopathic, noninfectious, central nervous system (CNS) inflammatory diseases in which a definitive histopathological diagnosis is lacking 1 . Granulomatous meningoencephalitis, necrotizing meningoencephalomyelitis, and necrotizing leukoencephalitis are 3 distinct MUO disorders identified by histological evaluation 2‐4 . Although the pathogenesis of MUO is unclear, it is most likely multifactorial, combining genetic predisposition with factors triggering an excessive immunologic response 3,4 .…”

Vascular endothelial growth factor concentrations in the cerebrospinal fluid of dogs with neoplastic or inflammatory central nervous system disorders

“…A common diagnostic dilemma is the differentiation of neoplastic from inflammatory conditions affecting the central nervous system (CNS) of dogs. 15 , 16 , 17 Several studies in dogs have found increased serum or plasma VEGF concentrations in neoplastic versus non‐neoplastic processes outside of the CNS, 7 , 18 , 19 , 20 , 21 , 22 , 23 and several reports have found that increased serum or plasma VEGF concentration suggests a higher tumor grade 18 , 21 or is a poor prognostic indicator in dogs. 7 , 24 , 25 Although plasma VEGF concentration is increased in some dogs with intracranial tumors, 11 cerebrospinal fluid (CSF) is considered to be a more sensitive indicator of CNS disease and is routinely sampled in dogs.…”

“…A common diagnostic dilemma is the differentiation of neoplastic from inflammatory conditions affecting the central nervous system (CNS) of dogs 15‐17 . Several studies in dogs have found increased serum or plasma VEGF concentrations in neoplastic versus non‐neoplastic processes outside of the CNS, 7,18‐23 and several reports have found that increased serum or plasma VEGF concentration suggests a higher tumor grade 18,21 or is a poor prognostic indicator in dogs 7,24,25 .…”