(Re)organisation of the somatosensory system after early brain lesion: A lateralization index fMRI study

ObjectiveTo evaluate the relationship between neural (re)organization of the somatosensory cortex and impairment of sensory function (2-point discrimination [2PD]) in individuals with unilateral cerebral palsy.MethodsWe included 21 individuals with unilateral cerebral palsy. 2PD thresholds were evaluated on thumb pads, and activation of the somatosensory cortex was recorded by functional MRI (fMRI) during passive movements of the affected hand. A lateralization index (LI) was calculated for the primary sensory (S1) and secondary sensory (S2) cortices and the correlation between the LI and 2PD thresholds was analysed.ResultsWe found a significant negative correlation between the 2PD thresholds and the S2 LI (r = −0.5, one-tailed P-value = 0.01) and a trend towards a negative correlation with the S1 LI (r = −0.4, one-tailed P-value = 0.05).ConclusionHigh levels of activation in the contralesional hemisphere were associated with high levels of sensory impairment in individuals with unilateral cerebral palsy. The interhemispheric (re)organization of the somatosensory system may not effectively compensate for somatosensory impairment.     

Effect of Day Optimizing Throughput (Dot) Knee Software Implementation on Magnetic Resonance Imaging Workflow Efficiency

PurposeAttempts by magnetic resonance (MR) manufacturers to help imaging centres improve patient throughput has led to the development of more automated acquisition. This software is capable of customizing individual scan alignment; potentially improving imaging efficiency and standardizing protocols. However, substantial investments are required to introduce such systems, potentially deterring their widespread application. This study assessed the implementation costs and reduction in examination durations for automated knee MR imaging (MRI) software.Materials and MethodsResearch activities were performed at a community-based academic centre on a 3-Tesla (3-T) system using Siemens' Day Optimizing Throughput (Dot) knee software. Examination acquisition times were extracted from the system before and after software implementation. Fiscal year 2012/13 finances were used to determine the average hourly cost of MRI utilization. Costs associated with automated software implementation were also calculated. Finally, the number of knee scans required to achieve a positive return on investment using the software was established.Results and DiscussionThe mean (standard deviation, sample size) pre- and post-Dot software scan times were 23.20 (4.18, n = 266) and 21.94 (4.51, n = 59) minutes, respectively, for a routine knee scan and 11.88 (1.60, n = 74) and 11.24 (1.51, n = 27) minutes, respectively, for a fast knee scan. The overall weighted average resulted in a 64-second time savings per automated knee examination. This negligible time savings would be extremely difficult to make use of clinically. Dot simplified 29 unique knee protocols to two, improving the consistency of knee examinations. Current Dot software is not compatible with all patients and therefore has limitations that are a concern among MR technologists.ConclusionAdoption of automated knee systems could assist in standardizing protocols; however, the cost of implementation and difficulty in modifying patient scheduling to reflect the minimal time savings would make a financial return unlikely to occur at small- and medium-sized institutions.     

Preparation and identification of multifunctional mesoporous silica nanoparticles for in vitro and in vivo dual-mode imaging,theranostics, and targeted tracking

Mesoporous silica nanoparticles (MSNs) can provide a structural foundation for a new generation of nanocarriers with a broad range of functionalities. Multifunctional MSNs can serve as all-in-one diagnostic and therapeutic tools that can be used to simultaneously visualize and treat various diseases, such as cancer. This research study is the first time that two lanthanide-based imaging systems have been combined to incorporate controlled drug release and targeted tracing into a single MSN-based nano-platform for a novel theranostic drug delivery system. Doping lanthanide ions, i.e., europium (Eu) and gadolinium (Gd) ions, into an MSN structure (EuGd-MSNs) imparts fluorescence and magnetism to the nanostructure that can be used to develop magnetic resonance imaging (MRI) and biological fluorescence tools. Current cancer research has revealed that most human cancer cells express a large number of folate receptors on their surface. Grafting folic acid (FA) onto the EuGd-MSN surface (EuGd-FA-MSNs) imparts a targeting function to the MSN because of the specificity of the binding of FA to cell surface receptors. Furthermore, grafting anticancer drugs, such as camptothecin (CPT), onto the surface of these MSNs by forming disulfide bonds (EuGd-SS-CPT-FA-MSNs) enables intracellular controlled drug release. A high concentration of intracellular glutathione cleaves the disulfide bond to release the drug and treat the disease. The results of in vitro and in vivo studies show that the functionalized MSNs can be successfully used as a platform to integrate dual-imaging, targeting, and therapeutic treatment in multifunctional diagnosis drug delivery systems.     

Regional fractional ventilation mapping in spontaneously breathing mice using hyperpolarized 129Xe MRI

The feasibility of ventilation imaging with hyperpolarized (HP) ¹²⁹Xe MRI has been investigated for quantitative and regional assessment of ventilation in spontaneously breathing mice. The multiple breath ventilation imaging technique was modified to the protocol of spontaneous inhalation of HP ¹²⁹Xe delivered continuously from a ¹²⁹Xe polarizer. A series of ¹²⁹Xe ventilation images was obtained by varying the number of breaths before the ¹²⁹Xe lung imaging. The fractional ventilation, r, was successfully evaluated for spontaneously breathing mice. An attempt was made to detect ventilation dysfunction in the emphysematous mouse lung induced by intratracheal administration of porcine pancreatic elastase (PPE). As a result, the distribution of fractional ventilation could be visualized by the r map. Significant dysfunction of ventilation was quantitatively identified in the PPE‐treated group. The whole‐lung r value of 0.34 ± 0.01 for control mice (N = 4) was significantly reduced, to 0.25 ± 0.07, in PPE‐treated mice (N = 4) (p = 0.038). This study is the first application of multiple breath ventilation imaging to spontaneously breathing mice, and shows that this methodology is sensitive to differences in the pulmonary ventilation. This methodology is expected to improve simplicity as well as noninvasiveness when assessing regional ventilation in small rodents. Copyright © 2014 John Wiley & Sons, Ltd.     

Clinical equivalence assessment of T2 synthesized pediatric brain magnetic resonance imaging

Background and purposeAutomated synthetic magnetic resonance imaging (MRI) provides qualitative, weighted image contrasts as well as quantitative information from one scan and is well-suited for various applications such as analysis of white matter disorders. However, the synthesized contrasts have been poorly evaluated in pediatric applications. The purpose of this study was to compare the image quality of synthetic T2 to conventional turbo spin-echo (TSE) T2 in pediatric brain MRI.Materials and methodsThis was a mono-center prospective study. Synthetic and conventional MRI acquisitions at 1.5 Tesla were performed for each patient during the same session using a prototype accelerated T2 mapping sequence package (TA_synthetic = 3:07 min, TA_conventional = 2:33 min). Image sets were blindly and randomly analyzed by pediatric neuroradiologists. Global image quality, morphologic legibility of standard structures and artifacts were assessed using a 4-point Likert scale. Inter-observer kappa agreements were calculated. The capability of the synthesized contrasts and conventional TSE T2 to discern normal and pathologic cases was evaluated.ResultsSixty patients were included. The overall diagnostic quality of the synthesized contrasts was non-inferior to conventional imaging scale (P = 0.06). There was no significant difference in the legibility of normal and pathological anatomic structures of synthetized and conventional TSE T2 (all P > 0.05) as well as for artifacts except for phase encoding (P = 0.008). Inter-observer agreement was good to almost perfect (kappa between 0.66 and 1).ConclusionsT2 synthesized contrasts, which also provides quantitative T2 information that could be useful, could be suggested as an equivalent technique in pediatric neuro-imaging, compared to conventional TSE T2.     

Multimodal fusion of structural and functional brain imaging in depression using linked independent component analysis

Previous structural and functional neuroimaging studies have implicated distributed brain regions and networks in depression. However, there are no robust imaging biomarkers that are specific to depression, which may be due to clinical heterogeneity and neurobiological complexity. A dimensional approach and fusion of imaging modalities may yield a more coherent view of the neuronal correlates of depression. We used linked independent component analysis to fuse cortical macrostructure (thickness, area, gray matter density), white matter diffusion properties and resting‐state functional magnetic resonance imaging default mode network amplitude in patients with a history of depression (n = 170) and controls (n = 71). We used univariate and machine learning approaches to assess the relationship between age, sex, case–control status, and symptom loads for depression and anxiety with the resulting brain components. Univariate analyses revealed strong associations between age and sex with mainly global but also regional specific brain components, with varying degrees of multimodal involvement. In contrast, there were no significant associations with case–control status, nor symptom loads for depression and anxiety with the brain components, nor any interaction effects with age and sex. Machine learning revealed low model performance for classifying patients from controls and predicting symptom loads for depression and anxiety, but high age prediction accuracy. Multimodal fusion of brain imaging data alone may not be sufficient for dissecting the clinical and neurobiological heterogeneity of depression. Precise clinical stratification and methods for brain phenotyping at the individual level based on large training samples may be needed to parse the neuroanatomy of depression.