Advanced multiparametric magnetic resonance imaging of multinodular and vacuolating neuronal tumor

BACKGROUND AND PURPOSE

Multinodular and vacuolating neuronal tumor (MVNT) of the cerebrum is a rare brain lesion with suggestive imaging features. The aim of our study was to report the largest series of MVNTs so far and to evaluate the utility of advanced multiparametric magnetic resonance (MR) techniques.

METHODS

This multicenter retrospective study was approved by our institutional research ethics board. From July 2014 to May 2019, two radiologists read in consensus the MR examinations of patients presenting with a lesion suggestive of an MVNT. They analyzed the lesions' MR characteristics on structural images and advanced multiparametric MR imaging.

RESULTS

A total of 64 patients (29 women and 35 men, mean age 44.2 ± 15.1 years) from 25 centers were included. Lesions were all hyperintense on fluid-attenuated inversion recovery and T2-weighted imaging without post-contrast enhancement. The median relative apparent diffusion coefficient on diffusion-weighted imaging was 1.13 [interquartile range (IQR), 0.2]. Perfusion-weighted imaging showed no increase in perfusion, with a relative cerebral blood volume of 1.02 (IQR, 0.05) and a relative cerebral blood flow of 1.01 (IQR, 0.08). MR spectroscopy showed no abnormal peaks. Median follow-up was 2 (IQR, 1.2) years, without any changes in size.

CONCLUSIONS

A comprehensive characterization protocol including advanced multiparametric magnetic resonance imaging sequences showed no imaging patterns suggestive of malignancy in MVNTs. It might be useful to better characterize MVNTs.

Multinodular and Vacuolating Posterior Fossa Lesions of Unknown Significance

Multinodular and vacuolating neuronal tumor of the cerebrum is a rare supratentorial brain tumor described for the first time in 2013. Here, we report 11 cases of infratentorial lesions showing similar striking imaging features consisting of a cluster of low T1-weighted imaging and high T2-FLAIR signal intensity nodules, which we referred to as multinodular and vacuolating posterior fossa lesions of unknown significance. No relationship was found between the location of the lesion and clinical symptoms. A T2-FLAIR hypointense central dot sign was present in images of 9/11 (82%) patients. Cortical involvement was present in 2/11 (18%) of patients. Only 1 nodule of 1 multinodular and vacuolating posterior fossa lesion of unknown significance showed enhancement on postcontrast T1WI. DWI, SWI, MRS, and PWI showed no malignant pattern. Lesions did not change in size or signal during a median follow-up of 3 years, suggesting that multinodular and vacuolating posterior fossa lesions of unknown significance are benign malformative lesions that do not require surgical intervention or removal.

TIPIC Syndrome: Beyond the Myth of Carotidynia, a New Distinct Unclassified Entity

BACKGROUND AND PURPOSE

The differential diagnosis of acute cervical pain includes nonvascular and vascular causes such as carotid dissection, carotid occlusion, or vasculitis. However, some patients present with unclassified vascular and perivascular changes on imaging previously reported as carotidynia. The aim of our study was to improve the description of this as yet unclassified clinico-radiologic entity.

MATERIALS AND METHODS

From January 2009 through April 2016, 47 patients from 10 centers presenting with acute neck pain or tenderness and at least 1 cervical image showing unclassified carotid abnormalities were included. We conducted a systematic, retrospective study of their medical charts and diagnostic and follow-up imaging. Two neuroradiologists independently analyzed the blinded image datasets.

RESULTS

The median patient age was 48 years. All patients presented with acute neck pain, and 8 presented with transient neurologic symptoms. Imaging showed an eccentric pericarotidian infiltration in all patients. An intimal soft plaque was noted in 16 patients, and a mild luminal narrowing was noted in 16 patients. Interreader reproducibility was excellent. All patients had complete pain resolution within a median of 13 days. At 3-month follow-up, imaging showed complete disappearance of vascular abnormalities in 8 patients, and a marked decrease in all others.

CONCLUSIONS

Our study improved the description of an unclassified, clinico-radiologic entity, which could be described by the proposed acronym: TransIent Perivascular Inflammation of the Carotid artery (TIPIC) syndrome.

STREM: a robust multidimensional parametric method to segment MS lesions in MRI

We propose to segment Multiple Sclerosis (MS) lesions overtime in multidimensional Magnetic Resonance (MR) sequences. We use a robust algorithm that allows the segmentation of the abnormalities using the whole time series simultaneously and we propose an original rejection scheme for outliers. We validate our method using the BrainWeb simulator. To conclude, promising preliminary results on longitudinal multi-sequences of clinical data are shown.

MRI texture analysis on texture test objects, normal brain and intracranial tumors

Texture analysis was performed in three different MRI units on T1 and T2-weighted MR images from 10 healthy volunteers and 63 patients with histologically confirmed intracranial tumors. The goal of this study was a multicenter evaluation of the usefulness of this quantitative approach for the characterization of healthy and pathologic human brain tissues (white matter, gray matter, cerebrospinal fluid, tumors and edema). Each selected brain region of interest was characterized with both its mean gray level values and several texture parameters. Multivariate statistical analyses were then applied in order to discriminate each brain tissue type represented by its own set of texture parameters. Texture analysis was previously performed on test objects to evaluate the method dependence on acquisition parameters and consequently the interest of a multicenter evaluation. Even obtained on different sites with their own acquisition routine protocol, MR brain images contain textural features that can reveal discriminant factors for tissue classification and image segmentation. It can also offer additional information in case of undetermined diagnosis or to develop a more accurate tumor grading.