Valuable contribution of magnetic resonance spectroscopy in differentiation of brain abscess from glioma

Differentiation of Brain Abscess From Cystic Glioma Using Conventional MRI Based on Deep Transfer Learning Features and Hand-Crafted Radiomics Features

Objectives: To develop and validate the model for distinguishing brain abscess from cystic glioma by combining deep transfer learning (DTL) features and hand-crafted radiomics (HCR) features in conventional T1-weighted imaging (T1WI) and T2-weighted imaging (T2WI).

Methods: This single-center retrospective analysis involved 188 patients with pathologically proven brain abscess (102) or cystic glioma (86). One thousand DTL and 105 HCR features were extracted from the T1WI and T2WI of the patients. Three feature selection methods and four classifiers, such as k-nearest neighbors (KNN), random forest classifier (RFC), logistic regression (LR), and support vector machine (SVM), for distinguishing brain abscess from cystic glioma were compared. The best feature combination and classifier were chosen according to the quantitative metrics including area under the curve (AUC), Youden Index, and accuracy.

Results: In most cases, deep learning-based radiomics (DLR) features, i.e., DTL features combined with HCR features, contributed to a higher accuracy than HCR and DTL features alone for distinguishing brain abscesses from cystic gliomas. The AUC values of the model established, based on the DLR features in T2WI, were 0.86 (95% CI: 0.81, 0.91) in the training cohort and 0.85 (95% CI: 0.75, 0.95) in the test cohort, respectively.

Conclusions: The model established with the DLR features can distinguish brain abscess from cystic glioma efficiently, providing a useful, inexpensive, convenient, and non-invasive method for differential diagnosis. This is the first time that conventional MRI radiomics is applied to identify these diseases. Also, the combination of HCR and DTL features can lead to get impressive performance.

Advanced multimodality MR imaging of a cerebral nocardiosis abscess in an immunocompetent patient with a focus on Amide Proton Transfer weighted imaging

Cerebral nocardiosis abscess is a very rare entity in an immunocompetent patient. In this case report multiparametric and multimodality MR imaging characteristics of a pyogenic brain abscess caused by Nocardia Farcinica are discussed with a specific focus on amide proton transfer weighted imaging as a modern non-invasive, molecular MR imaging method which detects endogenous mobile protein and peptide concentration and tissue pH changes in pathologic brain lesions. The imaging characteristics are reviewed and discussed in respect to possible differential diagnoses, especially malignant tumorous lesions.