Multi-cystic white matter enlarged Virchow Robin spaces in a 5-year-old boy

Giant tumefactive perivascular spaces in a pediatric patient: A rare radiological entity

Background:

Giant tumefactive perivascular spaces (TPVS) are radiological rarities and may mimic other neurological structural lesions. Fewer than 80 cases have been reported in the literature with even fewer in the pediatric population.

Case Description:

The authors present an image report showcasing a 3-year-old boy presenting with uncontrolled seizures despite multiple anti-epileptic medications. His magnetic resonance imaging showed multiple, non-contrast enhancing cyst clusters within the left parieto-occipital region that was hyperintense on T2-weighted imaging, and isointense to cerebrospinal fluid. Due to a characteristic absence of perilesional edema seen on fluid-attenuated inversion recovery imaging or diffusion restriction on diffusion-weighted imaging (DWI) sequences, this was diagnosed as a giant TPVS.

Conclusion:

Accurate diagnosis of these rare radiological entities is based on pathognomonic findings that can help prevent unnecessary surgery and guide management for patients, particularly in the pediatric population as seen in our case.

Contribution of advanced MRI to the diagnosis of giant tumefactive perivascular spaces

BACKGROUND

Giant tumefactive perivascular spaces (PVSs) are uncommon benign cystic lesions. They can imitate cystic neoplasms.

PURPOSE

To evaluate the contribution of advanced neuro magnetic resonance imaging (MRI) techniques in the diagnosis of giant tumefactive PVSs and to further characterize these unusual cerebral lesions.

MATERIAL AND METHODS

The MRI scans of patients with tumefactive PVS diagnosed between 2010 and 2019 were retrospectively reviewed. All imaging studies included three plane conventional cerebral MRI sequences as well as precontrast 3D T1 MPRAGE, post-gadolinium 3D T1 acquisitions, sagittal plane 3D T2 SPACE, diffusion-weighted imaging, and time-of-flight (TOF) angiography. Some patients received perfusion MR, MR spectroscopy, diffusion tensor imaging (DTI), and contrast-enhanced TOF MR angiography.

RESULTS

A perforating vessel was demonstrated in 16 patients (66.7%) by TOF imaging. In four patients, there were intracystic vascular collaterals on contrast-enhanced TOF MR angiography. Septal blooming was observed in four patients in susceptibility-weighted imaging. On perfusion MR, central hyperperfusion was observed in four patients, and peripheral hyperperfusion was observed in one patient. On MR spectroscopy, choline increase was observed in two patients, and there was a lactate peak in three patients, and both a choline increase and lactate peak in one patient. On DTI, there was fiber distortion in five patients and fiber deformation in one patient.

CONCLUSION

Advanced MRI techniques and 3D volumetric high-resolution MRI sequences can provide a valuable contribution to the diagnosis and can be successfully used in the management of these lesions.

Towards the automatic computational assessment of enlarged perivascular spaces on brain magnetic resonance images: a systematic review

Enlarged perivascular spaces (EPVS), visible in brain MRI, are an important marker of small vessel disease and neuroinflammation. We systematically evaluated the literature up to June 2012 on possible methods for their computational assessment and analyzed confounds with lacunes and small white matter hyperintensities. We found six studies that assessed/identified EPVS computationally by seven different methods, and four studies that described techniques to automatically segment similar structures and are potentially suitable for EPVS segmentation. T2-weighted MRI was the only sequence that identified all EPVS, but FLAIR and T1-weighted images were useful in their differentiation. Inconsistency within the literature regarding their diameter and terminology, and overlap in shape, intensity, location, and size with lacunes, conspires against their differentiation and the accuracy and reproducibility of any computational segmentation technique. The most promising approach will need to combine various MR sequences and consider all these features for accurate EPVS determination.