Non-parametric deconvolution using Bézier curves for quantification of cerebral perfusion in dynamic susceptibility contrast MRI

Objective Deconvolution is an ill-posed inverse problem that tends to yield non-physiological residue functions R(t) in dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI). In this study, the use of Bézier curves is proposed for obtaining physiologically reasonable residue functions in perfusion MRI. Materials and methods Cubic Bézier curves were employed, ensuring R(0) = 1, bounded-input, bounded-output stability and a non-negative monotonically decreasing solution, resulting in 5 parameters to be optimized. Bézier deconvolution (BzD), implemented in a Bayesian framework, was tested by simulation under realistic conditions, including effects of arterial delay and dispersion. BzD was also applied to DSC-MRI data from a healthy volunteer. Results Bézier deconvolution showed robustness to different underlying residue function shapes. Accurate perfusion estimates were observed, except for boxcar residue functions at low signal-to-noise ratio. BzD involving corrections for delay, dispersion, and delay with dispersion generally returned accurate results, except for some degree of cerebral blood flow (CBF) overestimation at low levels of each effect. Maps of mean transit time and delay were markedly different between BzD and block-circulant singular value decomposition (oSVD) deconvolution. Discussion A novel DSC-MRI deconvolution method based on Bézier curves was implemented and evaluated. BzD produced physiologically plausible impulse response, without spurious oscillations, with generally less CBF underestimation than oSVD.

Tuberculoma mimicking postoperative VP shunt seeding of craniopharyngioma: A rare case report

Background: Tuberculosis (TB) is still a big problem in developing and TB endemic countries such as Indonesia. The most common manifestations of TB in the central nervous system are tuberculous meningitis and tuberculoma. In developing and TB endemic countries, tuberculomas account for 33% of intracranial space-occupying lesions. Isolated tuberculoma without systemic TB is rarely seen. On physical and radiological examination, tuberculoma often gives an atypical appearance. From imaging, tuberculoma often mimics another intracranial tumor. Oftentimes the accurate diagnosis can only be made after postoperative histopathological and microbiology examination. Case Description: An 11-year-old, Indonesian girl has been complaining persistent headache in the past 3 years. The patient had a history of surgical excision of craniopharyngioma 8 years ago, and placement of ventriculoperitoneal shunt due to postoperative hydrocephalus. Patient was immunocompetent with no sign of systemic TB nor tuberculous meningitis. Brain magnetic resonance imaging (MRI) revealed a 4 × 2.3 × 2.1 cm mass surrounding the ventricular drain which was attached in the anterior horn of the right lateral ventricle to the right frontal cortex. From dynamic susceptibility contrast MRI perfusion and MR Spectroscopy suggested a process of seeding metastases surrounding the ventricular drain. Postoperative histopathological examination results were consistent with tuberculoma. Conclusion: Tuberculoma should always be considered as one of the differential diagnoses along with primary and secondary intracranial neoplasm, particularly in developing and TB endemic countries, and inpatient with immunocompromised state.

A novel approach for assessing hypoperfusion in stroke using spatial independent component analysis of resting-state fMRI data

ObjectiveTo identify, characterize, and automatically classify hypoperfusion-related changes in the blood oxygenation level dependent (BOLD) signal in acute stroke using spatial independent component analysis of resting-state functional MRI data.MethodsWe applied spatial independent component analysis to resting-state functional MRI data of 37 stroke patients scanned within 24 hours of symptom onset, 17 of whom received follow-up scans the next day. All patients also received dynamic susceptibility contrast MRI. After denoising and manually classifying the components, we extracted a set of temporal and spatial features from each independent component and used a generalized linear model to automatically identify components related to tissue hypoperfusion.ResultsOur analysis revealed “Hypoperfusion spatially-Independent Components” (HICs) whose BOLD signal spatial patterns resembled regions of delayed perfusion depicted by dynamic susceptibility contrast MRI. These HICs were detected even in the presence of excessive patient motion, and disappeared following successful tissue reperfusion. The unique spatial and temporal features of HICs allowed them to be distinguished with high accuracy from other components in a user-independent manner (AUC = 0.95, accuracy = 0.96, sensitivity = 1.00, specificity = 0.96).InterpretationOur study presents a new, non-invasive method for assessing blood flow in acute stroke that minimizes interpretative subjectivity and is robust to severe patient motion.

Dynamic contrast-enhanced QSM for perfusion imaging: a systematic comparison of ΔR2*- and QSM-based contrast agent concentration time curves in blood and tissue

Objective In dynamic susceptibility contrast MRI (DSC-MRI), an arterial input function (AIF) is required to quantify perfusion. However, estimation of the concentration of contrast agent (CA) from magnitude MRI signal data is challenging. A reasonable alternative would be to quantify CA concentration using quantitative susceptibility mapping (QSM), as the CA alters the magnetic susceptibility in proportion to its concentration. Material and methods AIFs with reasonable appearance, selected on the basis of conventional criteria related to timing, shape, and peak concentration, were registered from both ΔR2* and QSM images and mutually compared by visual inspection. Both ΔR2*- and QSM-based AIFs were used for perfusion calculations based on tissue concentration data from ΔR2*as well as QSM images. Results AIFs based on ΔR2* and QSM data showed very similar shapes and the estimated cerebral blood flow values and mean transit times were similar. Analysis of corresponding ΔR2* versus QSM-based concentration estimates yielded a transverse relaxivity estimate of 89 s−1 mM−1, for voxels identified as useful AIF candidate in ΔR2* images according to the conventional criteria. Discussion Interestingly, arterial concentration time curves based on ΔR2* versus QSM data, for a standard DSC-MRI experiment, were generally very similar in shape, and the relaxivity obtained in voxels representing blood was similar to tissue relaxivity obtained in previous studies.