Focused Ultrasound Central Lateral Thalamotomy for the Treatment of Refractory Neuropathic Pain: Phase I Trial

BACKGROUND AND OBJECTIVES

Magnetic resonance-guided focused ultrasound (MRgFUS) central lateral thalamotomy (CLT) has not yet been validated for treating refractory neuropathic pain (NP). Our aim was to assess the safety and potential efficacy of MRgFUS CLT for refractory NP.

METHODS

In this prospective, nonrandomized, single-arm, investigator-initiated phase I trial, patients with NP for more than 6 months related to phantom limb pain, spinal cord injury, or radiculopathy/radicular injury and who had undergone at least one previous failed intervention were eligible. The main outcomes were safety profile and pain as assessed using the brief pain inventory, the pain disability index, and the numeric rating scale. Medication use and the functional connectivity of the default mode network (DMN) were also assessed.

RESULTS

Ten patients were enrolled, with nine achieving successful ablation. There were no serious adverse events and 12 mild/moderate severity events. The mean age was 50.9 years (SD: 12.7), and the mean symptom duration was 12.3 years (SD: 9.7). Among eight patients with a 1-year follow-up, the brief pain inventory decreased from 7.6 (SD: 1.1) to 3.8 (SD: 2.8), with a mean percent decrease of 46.3 (SD: 40.6) (paired t -test, P = .017). The mean pain disability index decreased from 43.0 (SD: 7.5) to 25.8 (SD: 16.8), with a mean percent decrease of 39.3 (SD: 41.6) ( P = .034). Numeric rating scale scores decreased from a mean of 7.2 (SD: 1.8) to 4.0 (SD: 2.8), with a mean percent decrease of 42.8 (SD: 37.8) ( P = .024). Patients with predominantly intermittent pain or with allodynia responded better than patients with continuous pain or without allodynia, respectively. Some patients decreased medication use. Resting-state functional connectivity changes were noted, from disruption of the DMN at baseline to reactivation of connectivity between DMN nodes at 3 months.

CONCLUSION

MRgFUS CLT is feasible and safe for refractory NP and has potential utility in reducing symptoms as measured by validated pain scales.

The University of Pennsylvania glioblastoma (UPenn-GBM) cohort: advanced MRI, clinical, genomics, & radiomics

Glioblastoma is the most common aggressive adult brain tumor. Numerous studies have reported results from either private institutional data or publicly available datasets. However, current public datasets are limited in terms of: a) number of subjects, b) lack of consistent acquisition protocol, c) data quality, or d) accompanying clinical, demographic, and molecular information. Toward alleviating these limitations, we contribute the "University of Pennsylvania Glioblastoma Imaging, Genomics, and Radiomics" (UPenn-GBM) dataset, which describes the currently largest publicly available comprehensive collection of 630 patients diagnosed with de novo glioblastoma. The UPenn-GBM dataset includes (a) advanced multi-parametric magnetic resonance imaging scans acquired during routine clinical practice, at the University of Pennsylvania Health System, (b) accompanying clinical, demographic, and molecular information, (d) perfusion and diffusion derivative volumes, (e) computationally-derived and manually-revised expert annotations of tumor sub-regions, as well as (f) quantitative imaging (also known as radiomic) features corresponding to each of these regions. This collection describes our contribution towards repeatable, reproducible, and comparative quantitative studies leading to new predictive, prognostic, and diagnostic assessments.

Technical Comparison of Treatment Efficiency of Magnetic Resonance-Guided Focused Ultrasound Thalamotomy and Pallidotomy in Skull Density Ratio-Matched Patient Cohorts

Objective

MR-guided focused ultrasound (MRgFUS) is increasingly being used to treat patients with essential tremor (ET) and Parkinson's disease (PD) with thalamotomy and pallidotomy, respectively. Pallidotomy is performed off-center within the cranium compared to thalamotomy and may present challenges to therapeutic lesioning due to this location. However, the impact of target location on treatment efficiency and ability to create therapeutic lesions has not been studied. This study aimed to compare the physical efficiency of MRgFUS thalamotomy and pallidotomy.

Methods

Treatment characteristics were compared between patients treated with thalamotomy (n = 20) or pallidotomy (n = 20), matched by skull density ratios (SDR). Aspects of treatment efficiency were compared between these groups. Demographic and comparative statistics were conducted to assess these differences. Acoustic field simulations were performed to compare and validate the simulated temperature profile for VIM and GPi ablation.

Results

Lower SDR values were associated with greater energy requirement for thalamotomy (R² = 0.197, p = 0.049) and pallidotomy (R² = 0.342, p = 0.007). The impact of low SDR on efficiency reduction was greater for pallidotomy, approaching significance (p = 0.061). A nearly two-fold increase in energy was needed to reach 50°C in pallidotomy (10.9kJ) than in thalamotomy (5.7kJ), (p = 0.002). Despite lower energy requirement, the maximum average temperature reached was higher in thalamotomy (56.7°C) than in pallidotomy (55.0°C), (p = 0.017). Mean incident angle of acoustic beams was lesser in thalamotomy (12.7°) than in pallidotomy (18.6°), (p < 0.001). For all patients, a lesser mean incident angle correlated with a higher maximum average temperature reached (R² = 0.124, p = 0.026), and less energy needed to reach 50°C (R²=0.134, p = 0.020). Greater skull thickness was associated with a higher maximum energy for a single sonication for thalamotomy (R² = 0.206, p = 0.045) and pallidotomy (R² = 0.403, p = 0.003). An acoustic and temperature field simulation validated similar findings for thalamotomy and pallidotomy in a single patient.

Conclusion

The centrally located VIM offers a more efficient location for therapeutic lesioning compared to GPi pallidotomy in SDR matched cohort of patients. The impact on therapeutic lesioning with lower SDR may be greater for pallidotomy patients. As newer off-center targets are investigated, these findings can inform patient selection and treatment requirements for lesion production.

Improving Sensitivity of Arterial Spin Labeling Perfusion MRI in Alzheimer's Disease Using Transfer Learning of Deep Learning-Based ASL Denoising

BACKGROUND

Arterial spin labeling (ASL) perfusion magnetic resonance imaging (MRI) denoising through deep learning (DL) often faces insufficient training data from patients. One solution is to train DL models using healthy subjects' data which are more widely available and transfer them to patients' data.

PURPOSE

To evaluate the transferability of a DL-based ASL MRI denoising method (DLASL).

STUDY TYPE

Retrospective.

SUBJECTS

Four hundred and twenty-eight subjects (189 females) from three cohorts.

FIELD STRENGTH/SEQUENCE

3 T two-dimensional (2D) echo-planar imaging (EPI)-based pseudo-continuous ASL (PCASL) and 2D EPI-based pulsed ASL (PASL) sequences.

ASSESSMENT

DLASL was trained using young healthy adults' PCASL data (Dataset 1: 250/30 subjects as training/validation set) and was directly transferred (DTF) to PCASL data from Dataset 2 (45 subjects test set) of normal controls (NC) and Alzheimer's disease (AD) groups. DLASL was fine-tuned (DLASLFT) and tested on PASL data from Dataset 3 (103 subjects test set) of NC and AD. An existing non-DL method (NonDL) was used for comparison. Cerebral blood flow (CBF) images from ASL MRI were compared between NC and AD to assess characteristic hypoperfusion (lower CBF) patterns in AD. CBF image quality and CBF map sensitivity for detecting hypoperfusion using peak t-value and suprathreshold cluster size are outcome measures.

STATISTICAL TESTS

Paired t-test, two-sample t-test, one-way analysis of variance, and Tukey honestly significant difference, and linear mixed-effects models were used. P < 0.05 was considered statistically significant.

RESULTS

Mean contrast-to-noise ratio (CNR) of Dataset 2 showed that DTF outperformed NonDL (AD: 3.38 vs. 2.64, NC: 3.80 vs. 3.36). On Dataset 3, DLASLFT outperformed NonDL measured by mean CNR (AD: 2.45 vs. 1.87, NC: 2.54 vs. 2.17) and mean radiologic score (2.86 vs. 2.44). Image quality improvement was significant on both test sets. DTF and DLASLFT improved sensitivity for detecting AD-related hypoperfusion patterns compared with NonDL.

DATA CONCLUSION

We demonstrated the DLASL's transferability across different ASL sequences and different populations.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

MRI Guided Focused Ultrasound-Mediated Delivery of Therapeutic Cells to the Brain: A Review of the State-of-the-Art Methodology and Future Applications

Stem cell and immune cell therapies are being investigated as a potential therapeutic modality for CNS disorders, performing functions such as targeted drug or growth factor delivery, tumor cell destruction, or inflammatory regulation. Despite promising preclinical studies, delivery routes for maximizing cell engraftment, such as stereotactic or intrathecal injection, are invasive and carry risks of hemorrhage and infection. Recent developments in MRI-guided focused ultrasound (MRgFUS) technology have significant implications for treating focal CNS pathologies including neurodegenerative, vascular and malignant processes. MRgFUS is currently employed in the clinic for treating essential tremor and Parkinson's Disease by producing precise, incisionless, transcranial lesions. This non-invasive technology can also be modified for non-destructive applications to safely and transiently open the blood-brain barrier (BBB) to deliver a range of therapeutics, including cells. This review is meant to familiarize the neuro-interventionalist with this topic and discusses the use of MRgFUS for facilitating cellular delivery to the brain. A detailed and comprehensive description is provided on routes of cell administration, imaging strategies for targeting and tracking cellular delivery and engraftment, biophysical mechanisms of BBB enhanced permeability, supportive proof-of-concept studies, and potential for clinical translation.

Enhancing Metabolic Imaging of Energy Metabolism in Traumatic Brain Injury Using Hyperpolarized [1-13C]Pyruvate and Dichloroacetate

Hyperpolarized magnetic resonance spectroscopic imaging (MRSI) of [1-¹³C]pyruvate metabolism has previously been used to assess the effects of traumatic brain injury (TBI) in rats. Here, we show that MRSI can be used in conjunction with dichloroacetate to measure the phosphorylation state of pyruvate dehydrogenase (PDH) following mild-to-moderate TBI, and that measurements can be repeated in a longitudinal study to monitor the course of injury progression and recovery. We found that the level of ¹³C-bicarbonate and the bicarbonate-to-lactate ratio decreased on the injured side of the brain four hours after injury and continued to decrease through day 7. Levels recovered to normal by day 28. Measurements following dichloroacetate administration showed that PDH was inhibited equally by PDH kinase (PDK) on both sides of the brain. Therefore, the decrease in aerobic metabolism is not due to inhibition by PDK.

Transcranial MR Imaging-Guided Focused Ultrasound Interventions Using Deep Learning Synthesized CT

BACKGROUND AND PURPOSE

Transcranial MR imaging-guided focused ultrasound is a promising novel technique to treat multiple disorders and diseases. Planning for transcranial MR imaging-guided focused ultrasound requires both a CT scan for skull density estimation and treatment-planning simulation and an MR imaging for target identification. It is desirable to simplify the clinical workflow of transcranial MR imaging-guided focused ultrasound treatment planning. The purpose of this study was to examine the feasibility of deep learning techniques to convert MR imaging ultrashort TE images directly to synthetic CT of the skull images for use in transcranial MR imaging-guided focused ultrasound treatment planning.

MATERIALS AND METHODS

The U-Net neural network was trained and tested on data obtained from 41 subjects (mean age, 66.4 ± 11.0 years; 15 women). The derived neural network model was evaluated using a k-fold cross-validation method. Derived acoustic properties were verified by comparing the whole skull-density ratio from deep learning synthesized CT of the skull with the reference CT of the skull. In addition, acoustic and temperature simulations were performed using the deep learning CT to predict the target temperature rise during transcranial MR imaging-guided focused ultrasound.

RESULTS

The derived deep learning model generates synthetic CT of the skull images that are highly comparable with the true CT of the skull images. Their intensities in Hounsfield units have a spatial correlation coefficient of 0.80 ± 0.08, a mean absolute error of 104.57 ± 21.33 HU, and a subject-wise correlation coefficient of 0.91. Furthermore, deep learning CT of the skull is reliable in the skull-density ratio estimation (r = 0.96). A simulation study showed that both the peak target temperatures and temperature distribution from deep learning CT are comparable with those of the reference CT.

CONCLUSIONS

The deep learning method can be used to simplify workflow associated with transcranial MR imaging-guided focused ultrasound.

Predicting final lesion characteristics during MR-guided focused ultrasound pallidotomy for treatment of Parkinson's disease

OBJECTIVE

Magnetic resonance-guided focused ultrasound (MRgFUS) ablation of the globus pallidus interna (GPi) is being investigated for the treatment of advanced Parkinson's disease symptoms. However, GPi lesioning presents unique challenges due to the off-midline location of the target. Furthermore, it remains uncertain whether intraprocedural MR thermometry data can predict final lesion characteristics.

METHODS

The authors first performed temperature simulations of GPi pallidotomy and compared the results with those of actual cases and the results of ventral intermediate nucleus (VIM) thalamotomy performed for essential tremor treatment. Next, thermometry data from 13 MRgFUS pallidotomy procedures performed at their institution were analyzed using 46°C, 48°C, 50°C, and 52°C temperature thresholds. The resulting thermal models were compared with resulting GPi lesions noted on postprocedure days 1 and 30. Finally, the treatment efficiency (energy per temperature rise) of pallidotomy was evaluated.

RESULTS

The authors' modeled acoustic intensity maps correctly demonstrate the elongated, ellipsoid lesions noted during GPi pallidotomy. In treated patients, the 48°C temperature threshold maps most accurately predicted postprocedure day 1 lesion size, while no correlation was found for day 30 lesions. The average energy/temperature rise of pallidotomy was higher (612 J/°C) than what had been noted for VIM thalamotomy and varied with the patients' skull density ratios (SDRs).

CONCLUSIONS

The authors' acoustic simulations accurately depicted the characteristics of thermal lesions encountered following MRgFUS pallidotomy. MR thermometry data can predict postprocedure day 1 GPi lesion characteristics using a 48°C threshold model. Finally, the lower treatment efficiency of pallidotomy may make GPi lesioning challenging in patients with a low SDR.

Targeting of the dentato-rubro-thalamic tract for MR-guided focused ultrasound treatment of essential tremor

BACKGROUND

Magnetic resonance-guided focused ultrasound ablation of the thalamic ventral intermediate nucleus is a safe and effective treatment for medically refractory essential tremor. However, indirect targeting of the ventral intermediate nucleus using stereotactic coordinates from normal neuroanatomy can be inefficient. We therefore evaluated the feasibility of supplementing this method with direct targeting of the dentato-rubro-thalamic tract.

METHODS

We retrospectively identified four patients undergoing magnetic resonance-guided focused ultrasound ablation for essential tremor in which preoperative diffusion tractography imaging of the dentato-rubro-thalamic tract was fused with T2 weighted-imaging and utilized for intra-procedural targeting. The size and location of the dentato-rubro-thalamic tract and 24-hour lesion, as well as the center of the stereotactic coordinates, was evaluated. Finally, the amount of overlap between the dentato-rubro-thalamic tract and the lesion was calculated.

RESULTS

The 24-hour lesion size was homogeneous in the cohort (mean 31.3 mm², range 30-32 mm²), while there was substantial variation in the dentato-rubro-thalamic tract area (mean 14.3 mm², range 3-24 mm²). The center of the stereotactic coordinates and dentato-rubro-thalamic tract diverged by more than 1 mm in mediolateral and anterposterior directions in all patients, while the dentato-rubro-thalamic tract and lesion centers were in close proximity (mean mediolateral separation 1 mm, range 0.1-2.2 mm; mean anteroposterior separation 0.75 mm, range 0.4-1.2 mm). There was greater than 50% coverage of the dentato-rubro-thalamic tract by the lesion in all patients (mean 82.9%, range 66.7-100%). All patients experienced durable tremor relief.

CONCLUSION

Direct targeting of the dentato-rubro-thalamic tract using diffusion tractography imaging fused to T2 weighted-imaging may be a useful strategy for focused ultrasound treatment of essential tremor. Further investigation of the technique is warranted.

Lack of choline elevation on proton magnetic resonance spectroscopy in grade I-III gliomas

Elevated levels of choline are generally emphasized as marker of increased cellularity and cell membrane turnover in gliomas. In this study, we investigated the incidence rate of lack of choline/creatine and choline/water elevation in a population of grade I-III gliomas. A cohort of 41 patients with histopathologically confirmed gliomas underwent multi-voxel proton magnetic resonance spectroscopy on a 3 T magnetic resonance system prior to treatment. Peak areas for choline and myoinositol were measured from all voxels that exhibited hyperintensity on fluid-attenuated inversion recovery images and were normalized to creatine and unsuppressed water from each voxel. The average metabolite/creatine and metabolite/water ratios from these voxels were then computed. Similarly, average metabolite ratios were computed from normal brain parenchyma. Gliomas were considered for lack of choline elevation when choline/creatine and choline/water ratios from neoplastic regions were less than those from normal brain parenchyma regions. Six of 41 (14.6%) grade I-III gliomas showed lack of elevation for choline/creatine and choline/water ratios compared to normal brain parenchyma. Four of these six gliomas also demonstrated elevated levels of myoinositol/creatine ratio. All other gliomas (n = 35) had elevated choline levels from neoplastic regions relative to normal parenchyma. The sensitivity of choline/creatine or choline/water in determining a grade I-III glioma was 85.4%. These findings suggest that a lack of choline/creatine or choline/water elevation may be seen in some gliomas and low choline levels should not prevent us from considering the possibility of a grade I-III glioma.

Metabolic imaging of energy metabolism in traumatic brain injury using hyperpolarized [1-13C]pyruvate

Traumatic brain injury (TBI) is known to cause perturbations in the energy metabolism of the brain, but current tests of metabolic activity are only indirect markers of energy use or are highly invasive. Here we show that hyperpolarized ¹³C magnetic resonance spectroscopic imaging (MRSI) can be used as a direct, non-invasive method for studying the effects of TBI on energy metabolism. Measurements were performed on rats with moderate TBI induced by controlled cortical impact on one cerebral hemisphere. Following injection of hyperpolarized [1-¹³C]pyruvate, the resulting ¹³C-bicarbonate signal was found to be 24 ± 6% lower in the injured hemisphere compared with the non-injured hemisphere, while the hyperpolarized bicarbonate-to-lactate ratio was 33 ± 8% lower in the injured hemisphere. In a control group, no significant difference in signal was found between sides of the brain. The results suggest an impairment in mitochondrial pyruvate metabolism, resulting in a decrease in aerobic respiration at the location of injury following TBI.

Synthetic MRI for Clinical Neuroimaging: Results of the Magnetic Resonance Image Compilation (MAGiC) Prospective, Multicenter, Multireader Trial

BACKGROUND AND PURPOSE

Synthetic MR imaging enables reconstruction of various image contrasts from 1 scan, reducing scan times and potentially providing novel information. This study is the first large, prospective comparison of synthetic-versus-conventional MR imaging for routine neuroimaging.

MATERIALS AND METHODS

A prospective multireader, multicase noninferiority trial of 1526 images read by 7 blinded neuroradiologists was performed with prospectively acquired synthetic and conventional brain MR imaging case-control pairs from 109 subjects (mean, 53.0 ± 18.5 years of age; range, 19-89 years of age) with neuroimaging indications. Each case included conventional T1- and T2-weighted, T1 and T2 FLAIR, and STIR and/or proton density and synthetic reconstructions from multiple-dynamic multiple-echo imaging. Images were randomized and independently assessed for diagnostic quality, morphologic legibility, radiologic findings indicative of diagnosis, and artifacts.

RESULTS

Clinical MR imaging studies revealed 46 healthy and 63 pathologic cases. Overall diagnostic quality of synthetic MR images was noninferior to conventional imaging on a 5-level Likert scale (P < .001; mean synthetic-conventional, -0.335 ± 0.352; Δ = 0.5; lower limit of the 95% CI, -0.402). Legibility of synthetic and conventional morphology agreed in >95%, except in the posterior limb of the internal capsule for T1, T1 FLAIR, and proton-density views (all, >80%). Synthetic T2 FLAIR had more pronounced artifacts, including +24.1% of cases with flow artifacts and +17.6% cases with white noise artifacts.

CONCLUSIONS

Overall synthetic MR imaging quality was similar to that of conventional proton-density, STIR, and T1- and T2-weighted contrast views across neurologic conditions. While artifacts were more common in synthetic T2 FLAIR, these were readily recognizable and did not mimic pathology but could necessitate additional conventional T2 FLAIR to confirm the diagnosis.

Brain morphometric analysis predicts decline of intelligence quotient in children with sickle cell disease: A preliminary study

PURPOSE

For children with sickle cell disease (SCD) and at low risk category of stroke, we aim to build a predictive model to differentiate those with decline of intelligence-quotient (IQ) from counterparts without decline, based on structural magnetic-resonance (MR) imaging volumetric analysis.

MATERIALS AND METHODS

This preliminary prospective cohort study included 25 children with SCD, homozygous for hemoglobin S, with no history of stroke and transcranial Doppler mean velocities below 170cm/s at baseline. We administered the Kaufman Brief Intelligence Test (K-BIT) to each child at yearly intervals for 2-4 years. Each child underwent MR examination within 30 days of the baseline K-BIT evaluation date. We calculated K-BIT change rates, and used rate of change in K-BIT to classify children into two groups: a decline group and a non-decline group. We then generated predictive models to predict K-BIT decline/non-decline based on regional gray-matter (GM) volumes computed from structural MR images.

RESULTS

We identified six structures (the left median cingulate gyrus, the right middle occipital gyrus, the left inferior occipital gyrus, the right fusiform gyrus, the right middle temporal gyrus, the right inferior temporal gyrus) that, when assessed for volume at baseline, are jointly predictive of whether a child would suffer subsequent K-BIT decline. Based on these six regional GM volumes and the baseline K-BIT, we built a prognostic model using the K^* algorithm. The accuracy, sensitivity and specificity were 0.84, 0.78 and 0.86, respectively.

CONCLUSIONS

GM volumetric analysis predicts subsequent IQ decline for children with SCD.

Gender-based analysis of cortical thickness and structural connectivity in Parkinson's disease

Parkinson's disease (PD) is a progressive neurological disorder and appears to have gender-specific symptoms. Studies have observed a higher frequency for development of PD in male than in female. In the current study, we evaluated the gender-based changes in cortical thickness and structural connectivity in PD patients. With informed consent, 64 PD (43 males and 21 females) patients, and 46 (12 males and 34 females) age-matched controls underwent clinical assessment including Mini-Mental State Examination (MMSE) and magnetic resonance imaging on a 1.5 Tesla clinical MR scanner. Whole brain high-resolution T1-weighted images were acquired from all subjects and used to measure cortical thickness and structural network connectivity. No significant difference in MMSE score was observed between male and female both in control and PD subjects. Male PD patients showed significantly reduced cortical thickness in multiple brain regions including frontal, parietal, temporal, and occipital lobes as compared with those in female PD patients. The graph theory-based network analysis depicted lower connection strengths, lower clustering coefficients, and altered network hubs in PD male than in PD female. Male-specific cortical thickness changes and altered connectivity in PD patients may derive from behavioral, physiological, environmental, and genetical differences between male and female, and may have significant implications in diagnosing and treating PD among genders.

Intracranial Applications of MR Imaging-Guided Focused Ultrasound

Initially used in the treatment of prostate cancer and uterine fibroids, the role of focused ultrasound has expanded as transcranial acoustic wave distortion and other limitations have been overcome. Its utility relies on focal energy deposition via acoustic wave propagation. The duty cycle and intensity of focused ultrasound influence the rate of energy deposition and result in unique physiologic and biomechanical effects. Thermal ablation via high-intensity continuous exposure generates coagulative necrosis of tissues. High-intensity, pulsed application reduces temporally averaged energy deposition, resulting in mechanical effects, including reversible, localized BBB disruption, which enhances neurotherapeutic agent delivery. While the precise mechanisms remain unclear, low-intensity, pulsed exposures can influence neuronal activity with preservation of cytoarchitecture. Its noninvasive nature, high-resolution, radiation-free features allow focused ultrasound to compare favorably with other modalities. We discuss the physical characteristics of focused ultrasound devices, the biophysical mechanisms at the tissue level, and current and emerging applications.

Limbic pathway lesions in patients with multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) is a well-known demyelinating disease to cause cognitive dysfunction. The limbic system, relevant to memory, can be easily overlooked in conventional magnetic resonance imaging (MRI).

PURPOSE

To investigate the distribution and frequency of demyelinating lesions affecting white matter connections of the limbic system based on localization with diffusion tensor imaging (DTI)-derived fractional anisotropy (FA) color maps compared to three-dimensional T2-weighted (T2W) and FLAIR volumes in MS patients.

MATERIAL AND METHODS

One hundred and fifty patients with a known diagnosis of MS were identified for this Health Insurance Portability and Accountability (HIPAA)-compliant retrospective cross-sectional study. DTI-derived FA color maps, co-registered to T2W and FLAIR images, were analyzed for lesions affecting the three white matter tracts of the limbic system including cingulum, fornix, and mammilothalamic tracts by two investigators. The approximate location of the lesions on FLAIR was always confirmed on the co-registered DTI-derived FA color maps.

RESULTS

Of the 150 patients analyzed, 14.6% had cingulum lesions, 2.6% had fornix lesions, and 2.6% had mammilothalamic tract lesions; 21.3% of patients had at least one of the three tracts affected.

CONCLUSION

A relatively high frequency of lesions involving the limbic tracts may explain memory deficits and emotional dysfunction commonly experienced by patients with MS. The combined information from T2W, FLAIR, and DTI-derived FA color map allowed for more accurate localization of lesions affecting the major white matter tracts of the limbic system.

Metabolic, endocrine, and other genetic disorders

Metabolic, endocrine, and genetic diseases of the brain include a very large array of disorders caused by a wide range of underlying abnormalities and involving a variety of brain structures. Often these disorders manifest as recognizable, though sometimes overlapping, patterns on neuroimaging studies that may enable a diagnosis based on imaging or may alternatively provide enough clues to direct further diagnostic evaluation. The diagnostic workup can include various biochemical laboratory or genetic studies. In this chapter, after a brief review of normal white-matter development, we will describe a variety of leukodystrophies resulting from metabolic disorders involving the brain, including mitochondrial and respiratory chain diseases. We will then describe various acidurias, urea cycle disorders, disorders related to copper and iron metabolism, and disorders of ganglioside and mucopolysaccharide metabolism. Lastly, various other hypomyelinating and dysmyelinating leukodystrophies, including vanishing white-matter disease, megalencephalic leukoencephalopathy with subcortical cysts, and oculocerebrorenal syndrome will be presented. In the following section on endocrine disorders, we will examine various disorders of the hypothalamic-pituitary axis, including developmental, inflammatory, and neoplastic diseases. Neonatal hypoglycemia will also be briefly reviewed. In the final section, we will review a few of the common genetic phakomatoses. Throughout the text, both imaging and brief clinical features of the various disorders will be discussed.

T1rho MRI and CSF biomarkers in diagnosis of Alzheimer's disease

In the current study, we have evaluated the performance of magnetic resonance (MR) T1rho (T_1ρ) imaging and CSF biomarkers (T-tau, P-tau and Aβ-42) in characterization of Alzheimer's disease (AD) patients from mild cognitive impairment (MCI) and control subjects. With informed consent, AD (n = 27), MCI (n = 17) and control (n = 17) subjects underwent a standardized clinical assessment and brain MRI on a 1.5-T clinical-scanner. T_1ρ images were obtained at four different spin-lock pulse duration (10, 20, 30 and 40 ms). T_1ρ maps were generated by pixel-wise fitting of signal intensity as a function of the spin-lock pulse duration. T_1ρ values from gray matter (GM) and white matter (WM) of medial temporal lobe were calculated. The binary logistic regression using T_1ρ and CSF biomarkers as variables was performed to classify each group. T_1ρ was able to predict 77.3% controls and 40.0% MCI while CSF biomarkers predicted 81.8% controls and 46.7% MCI. T_1ρ and CSF biomarkers in combination predicted 86.4% controls and 66.7% MCI. When comparing controls with AD, T_1ρ predicted 68.2% controls and 73.9% AD, while CSF biomarkers predicted 77.3% controls and 78.3% for AD. Combination of T_1ρ and CSF biomarkers improved the prediction rate to 81.8% for controls and 82.6% for AD. Similarly, on comparing MCI with AD, T_1ρ predicted 35.3% MCI and 81.9% AD, whereas CSF biomarkers predicted 53.3% MCI and 83.0% AD. Collectively CSF biomarkers and T_1ρ were able to predict 59.3% MCI and 84.6% AD. On receiver operating characteristic analysis T_1ρ showed higher sensitivity while CSF biomarkers showed greater specificity in delineating MCI and AD from controls. No significant correlation between T_1ρ and CSF biomarkers, between T_1ρ and age, and between CSF biomarkers and age was observed. The combined use of T_1ρ and CSF biomarkers have promise to improve the early and specific diagnosis of AD. Furthermore, disease progression form MCI to AD might be easily tracked using these two parameters in combination.

•

Increased T1rho was observed in MCI and AD compared to controls.

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Increased T-tau and P-tau and decreased Aβ1-42 were observed in MCI and AD.

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Combined biomarkers have promise to improve early and specific diagnosis of AD.

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MCI to AD progression might be tracked using these two biomarkers in combination.

A prospective longitudinal brain morphometry study of children with sickle cell disease

BACKGROUND AND PURPOSE

Age-related changes in brain morphology are crucial to understanding the neurobiology of sickle cell disease. We hypothesized that the growth trajectories for total GM volume, total WM volume, and regional GM volumes are altered in children with sickle cell disease compared with controls.

MATERIALS AND METHODS

We analyzed T1-weighted images of the brains of 28 children with sickle cell disease (mean baseline age, 98 months; female/male ratio, 15:13) and 28 healthy age- and sex-matched controls (mean baseline age, 99 months; female/male ratio, 16:12). The total number of MR imaging examinations was 141 (2-4 for each subject with sickle cell disease, 2-3 for each control subject). Total GM volume, total WM volume, and regional GM volumes were measured by using an automated method. We used the multilevel-model-for-change approach to model growth trajectories.

RESULTS

Total GM volume in subjects with sickle cell disease decreased linearly at a rate of 411 mm(3) per month. For controls, the trajectory of total GM volume was quadratic; we did not observe a significant linear decline. For subjects with sickle cell disease, we found 35 brain structures that demonstrated age-related GM volume reduction. Total WM volume in subjects with sickle cell disease increased at a rate of 452 mm(3) per month, while the trajectory of controls was quadratic.

CONCLUSIONS

There was a significant age-related decrease in total GM volume in children with sickle cell disease. The GM volume reduction was spatially distributed widely across the brain, primarily in the frontal, parietal, and occipital lobes. Total WM volume in subjects with sickle cell disease increased at a lower rate than for controls.

Linear associations between clinically assessed upper motor neuron disease and diffusion tensor imaging metrics in amyotrophic lateral sclerosis

Objective

To assess the relationship between clinically assessed Upper Motor Neuron (UMN) disease in Amyotrophic Lateral Sclerosis (ALS) and local diffusion alterations measured in the brain corticospinal tract (CST) by a tractography-driven template-space region-of-interest (ROI) analysis of Diffusion Tensor Imaging (DTI).

Methods

This cross-sectional study included 34 patients with ALS, on whom DTI was performed. Clinical measures were separately obtained including the Penn UMN Score, a summary metric based upon standard clinical methods. After normalizing all DTI data to a population-specific template, tractography was performed to determine a region-of-interest (ROI) outlining the CST, in which average Mean Diffusivity (MD) and Fractional Anisotropy (FA) were estimated. Linear regression analyses were used to investigate associations of DTI metrics (MD, FA) with clinical measures (Penn UMN Score, ALSFRS-R, duration-of-disease), along with age, sex, handedness, and El Escorial category as covariates.

Results

For MD, the regression model was significant (p = 0.02), and the only significant predictors were the Penn UMN Score (p = 0.005) and age (p = 0.03). The FA regression model was also significant (p = 0.02); the only significant predictor was the Penn UMN Score (p = 0.003).

Conclusions

Measured by the template-space ROI method, both MD and FA were linearly associated with the Penn UMN Score, supporting the hypothesis that DTI alterations reflect UMN pathology as assessed by the clinical examination.

Characteristics of spondylotic myelopathy on 3D driven-equilibrium fast spin echo and 2D fast spin echo magnetic resonance imaging: a retrospective cross-sectional study

In patients with spinal stenosis, magnetic resonance imaging of the cervical spine can be improved by using 3D driven-equilibrium fast spin echo sequences to provide a high-resolution assessment of osseous and ligamentous structures. However, it is not yet clear whether 3D driven-equilibrium fast spin echo sequences adequately evaluate the spinal cord itself. As a result, they are generally supplemented by additional 2D fast spin echo sequences, adding time to the examination and potential discomfort to the patient. Here we investigate the hypothesis that in patients with spinal stenosis and spondylotic myelopathy, 3D driven-equilibrium fast spin echo sequences can characterize cord lesions equally well as 2D fast spin echo sequences. We performed a retrospective analysis of 30 adult patients with spondylotic myelopathy who had been examined with both 3D driven-equilibrium fast spin echo sequences and 2D fast spin echo sequences at the same scanning session. The two sequences were inspected separately for each patient, and visible cord lesions were manually traced. We found no significant differences between 3D driven-equilibrium fast spin echo and 2D fast spin echo sequences in the mean number, mean area, or mean transverse dimensions of spondylotic cord lesions. Nevertheless, the mean contrast-to-noise ratio of cord lesions was decreased on 3D driven-equilibrium fast spin echo sequences compared to 2D fast spin echo sequences. These findings suggest that 3D driven-equilibrium fast spin echo sequences do not need supplemental 2D fast spin echo sequences for the diagnosis of spondylotic myelopathy, but they may be less well suited for quantitative signal measurements in the spinal cord.

Sickle cell anemia: intracranial stenosis and silent cerebral infarcts in children with low risk of stroke

PURPOSE

Children with sickle cell anemia (SCA), who have mean blood flow velocities <170 cm/s in the terminal internal carotid (tICA) or middle cerebral (MCA) arteries on transcranial Doppler ultrasonography (TCD), are considered to be at low risk of stroke. The prevalence of intracranial stenosis, which raises the risk of stroke, is not known in these children. Here, we estimated the prevalence of stenosis and explored its association with silent cerebral infarcts determined based on Magnetic Resonance (MR) scans.

PATIENTS/METHODS

We studied prospectively a cohort of 67 children with SCA without prior clinically overt stroke or TIA (median age 8.8 years; range limits 2.3-13.1 years; 33 females) and with TCD mean velocity <170 cm/s. They underwent MR imaging of the brain and MR angiography of intracranial arteries.

RESULTS

In 7 children (10.5%, 95% CI: 4.9-20.3%) we found 10 stenoses, including 4 with isolated left tICA stenosis and 3 with multiple stenoses. We found silent infarcts in 26 children (37.7%, 95% CI: 27.2-49.5%). The median number of infarcts in an affected child was 2 (range limits: 1-9), median volume of infarcts was 171 mm(3) (range limits: 7-1060 mm(3)), and median infarct volume in relation to total brain volume was 0.020% (range limits: 0.001-0.101%). The number and volume of infarcts were significantly higher in children with arterial stenosis (both p=0.023).

CONCLUSIONS

The prevalence of intracranial arterial stenosis in children with SCA classified as at low risk of stroke by TCD mean velocity <170 cm/s is high. Children with stenosis are at higher risk of brain parenchymal injury as they have more silent cerebral infarcts.

Diagnostic utility of diffusion tensor imaging in differentiating glioblastomas from brain metastases

BACKGROUND AND PURPOSE

Differentiation of glioblastomas and solitary brain metastases is an important clinical problem because the treatment strategy can differ significantly. The purpose of this study was to investigate the potential added value of DTI metrics in differentiating glioblastomas from brain metastases.

MATERIALS AND METHODS

One hundred twenty-eight patients with glioblastomas and 93 with brain metastases were retrospectively identified. Fractional anisotropy and mean diffusivity values were measured from the enhancing and peritumoral regions of the tumor. Two experienced neuroradiologists independently rated all cases by using conventional MR imaging and DTI. The diagnostic performances of the 2 raters and a DTI-based model were assessed individually and combined.

RESULTS

The fractional anisotropy values from the enhancing region of glioblastomas were significantly higher than those of brain metastases (P < .01). There was no difference in mean diffusivity between the 2 tumor types. A classification model based on fractional anisotropy and mean diffusivity from the enhancing regions differentiated glioblastomas from brain metastases with an area under the receiver operating characteristic curve of 0.86, close to those obtained by 2 neuroradiologists using routine clinical images and DTI parameter maps (area under the curve = 0.90 and 0.85). The areas under the curve of the 2 radiologists were further improved to 0.96 and 0.93 by the addition of the DTI classification model.

CONCLUSIONS

Classification models based on fractional anisotropy and mean diffusivity from the enhancing regions of the tumor can improve diagnostic performance in differentiating glioblastomas from brain metastases.

Brain ischemia in patients with intracranial hemorrhage: pathophysiological reasoning for aggressive diagnostic management

Patients with intracranial hemorrhage have to be managed aggressively to avoid or minimize secondary brain damage due to ischemia, which contributes to high morbidity and mortality. The risk of brain ischemia, however, is not the same in every patient. The risk of complications associated with an aggressive prophylactic therapy in patients with a low risk of brain ischemia can outweigh the benefits of therapy. Accurate and timely identification of patients at highest risk is a diagnostic challenge. Despite the availability of many diagnostic tools, stroke is common in this population, mostly because the pathogenesis of stroke is frequently multifactorial whereas diagnosticians tend to focus on one or two risk factors. The pathophysiological mechanisms of brain ischemia in patients with intracranial hemorrhage are not yet fully elucidated and there are several important areas of ongoing research. Therefore, this review describes physiological and pathophysiological aspects associated with the development of brain ischemia such as the mechanism of oxygen and carbon dioxide effects on the cerebrovascular system, neurovascular coupling and respiratory and cardiovascular factors influencing cerebral hemodynamics. Consequently, we review investigations of cerebral blood flow disturbances relevant to various hemodynamic states associated with high intracranial pressure, cerebral embolism, and cerebral vasospasm along with current treatment options.

Advanced MR imaging techniques in the evaluation of nonenhancing gliomas: perfusion-weighted imaging compared with proton magnetic resonance spectroscopy and tumor grade

A significant number of nonenhancing (NE) gliomas are reported to be malignant. The purpose of this study was to compare the value of advanced MR imaging techniques, including T2*-dynamic susceptibility contrast PWI (DSC-PWI) and proton magnetic resonance spectroscopy ((1)HMRS) in the evaluation of NE gliomas. Twenty patients with NE gliomas underwent MRI including DSC-PWI and (1)HMRS. The relative CBV (rCBV) measurements were obtained from regions of maximum perfusion. The peak ratios of choline/creatine (Cho/Cr) and myo-inositol/creatine (mIns/Cr) were measured at a TE of 30 ms. Demographic features, tumor volumes, and PWI- and (1)HMRS-derived measures were compared between low-grade gliomas (LGGs) and high-grade gliomas (HGGs). In addition, the association of initial rCBV ratio with tumor progression was evaluated in LGGs. No significant difference was noted in age, sex or tumor size between LGGs and HGGs. Cho/Cr ratios were significantly higher in HGGs (1.7±0.63) than in LGGs (1.2±0.38). The receiver operating characteristic analysis demonstrated that a Cho/Cr ratio with a cutoff value of 1.3 could differentiate between LGG and HGG with a specificity of 100% and a sensitivity of 71.4%. There was no significant difference in the rCBV ratio and the mIns/Cr ratio between LGG and HGG. However, higher rCBV ratios were observed with more rapid progressions in LGGs. The results imply that Cho/Cr ratios are useful in distinguishing NE LGG from HGG and can be helpful in preoperative grading and biopsy guidance. On the other hand, rCBV ratios do not help in the distinction.

Cerebrovascular reactivity across the menstrual cycle in young healthy women

This study evaluated the relationship of cerebrovascular reactivity in young healthy women with changes in concentrations of circulating ovarian hormones throughout the menstrual cycle. Nineteen healthy nulliparous, right-handed, regularly menstruating women (age 23-25 years) underwent color-coded duplex sonography of the common (CCA), internal (ICA) and external (ECA) carotid arteries on both sides. Mean blood flow velocity values measured before and ten minutes after intravenous administration of 1000 mg acetazolamide (ACE) were assessed in relation to the serum concentration of estrogen and progesterone on days 5, 13 and 26 of the cycle. After ACE administration flow velocity in the right CCA and ICA increased by 23% and 35% on day 5, 12% and 31% on day 13 and 30% and 47% on day 26 respectively, and the changes were significantly larger on the right side (F=6.793 and F=4.098 respectively; both p<0.05). Changes in blood flow velocity in the right CCA and ICA after ACE injection were significantly associated with ovarian hormone concentrations (F=3.828, P=0.028 and F=3.671, P=0.032 respectively). We conclude that cerebrovascular reactivity changes across the menstrual cycle are associated with ovarian steroid hormone changes, and are asymmetric. The results imply that vasculature of the right hemisphere may undergo cyclic vasodilation across the menstrual cycle and this effect should be considered in studies of cerebrovascular reactivity in women with migraine and mood disorders.

Incidental findings in youths volunteering for brain MRI research

BACKGROUND AND PURPOSE

MRIs are obtained in research in healthy and clinical populations, and incidental findings have been reported. Most studies have examined adults with variability in parameters of image acquisition and clinical measures available. We conducted a prospective study of youths and documented the frequency and concomitants of incidental findings.

MATERIALS AND METHODS

Youths (n = 1400) with an age range from 8-23 years were imaged on the same 3T scanner, with a standard acquisition protocol providing 1.0 mm(3) isotropic resolution of anatomic scans. All scans were reviewed by an experienced board-certified neuroradiologist and were categorized into 3 groups: 1) normal: no incidental findings; 2) coincidental: incidental finding(s) were noted, further reviewed with an experienced pediatric neuroradiologist, but were of no clinical significance; 3) incidental findings that on further review were considered to have potential clinical significance and participants were referred for appropriate clinical follow-up.

RESULTS

Overall, 148 incidental findings (10.6% of sample) were noted, and of these, 12 required clinical follow-up. Incidental findings were not related to age. However, whites had a higher incidence of pineal cysts, and males had a higher incidence of cavum septum pellucidum, which was associated with psychosis-related symptoms.

CONCLUSIONS

Incidental findings, moderated by race and sex, occur in approximately one-tenth of participants volunteering for pediatric research, with few requiring follow-up. The incidence supports a 2-tiered approach of neuroradiologic reading and clinical input to determine the potential significance of incidental findings detected on research MR imaging scans.

Multiple sclerosis: identification of temporal changes in brain lesions with computer-assisted detection software

Multiple sclerosis (MS) is a chronic disease with a progressing and evolving course. Serial imaging with MRI is the mainstay in monitoring and managing MS patients. In this work we demonstrate the performance of a locally developed computer-assisted detection (CAD) software used to track temporal changes in brain MS lesions. CAD tracks changes in T2-bright MS lesions between two time points on a 3D high-resolution isotropic FLAIR MR sequence of the brain acquired at 3 Tesla. The program consists of an image-processing pipeline, and displays scrollable difference maps used as an aid to the neuroradiologist for assessing lesional change. To assess the value of the software we have compared diagnostic accuracy and duration of interpretation of the CAD-assisted and routine clinical interpretations in 98 randomly chosen, paired MR examinations from 88 patients (68 women, 20 men, mean age 43.5, age range 21-75) with a diagnosis of definite MS. The ground truth was determined by a three-expert panel. In case-wise analysis, CAD interpretation showed higher sensitivity than a clinical report (87% vs 77%, respectively). Lesion-wise analysis demonstrated improved sensitivity of CAD over a routine clinical interpretation of 40%-48%. Mean software-assisted interpretation time was 2.7 min. Our study demonstrates the potential of including CAD software in the workflow of neuroradiology practice for the detection of MS lesional change. Automated quantification of temporal change in MS lesion load may also be used in clinical research, e.g., in drug trials.

A Bayesian diagnostic system to differentiate glioblastomas from solitary brain metastases

This paper aimed to construct a Bayesian network-based decision support system to differentiate glioblastomas from solitary metastases, based on multimodality MR examination. We enrolled 51 patients with solitary brain tumors (26 with glioblastomas and 25 with solitary brain metastases). These patients underwent contrast-enhanced T1-weighted magnetic resonance (MR) examination, diffusion tensor imaging (DTI), dynamic susceptibility contrast (DSC) MRI, and fluid-attenuated inversion recovery (FLAIR). We generated a set of MR biomarkers, including relative cerebral blood volume in the enhancing region, and fractional anisotropy measured in the immediate peritumoral area. We then generated a Bayesian network model to represent associations among these imaging-derived predictors, and the group membership variable, (glioblastoma or solitary metastasis). This Bayesian network can be used to classify new patients' tumors based on their MR appearance. The Bayesian network model accurately differentiated glioblastomas from solitary metastases. Prediction accuracy was 0.94 (sensitivity = 0.96, specificity = 0.92) based on leave-one-out cross-validation. The area under the receiver operating characteristic curve was 0.90. A Bayesian network-based decision support system accurately differentiates glioblastomas from solitary metastases, based on MR-derived biomarkers.

Sickle cell anemia: reference values of cerebral blood flow determined by continuous arterial spin labeling MRI

Sickle cell anemia (SCA) is a chronic illness associated with progressive deterioration in patients' quality of life. The major complications of SCA are cerebrovascular accidents (CVA) such as asymptomatic cerebral infarct or overt stroke. The risk of CVA may be related to chronic disturbances in cerebral blood flow (CBF), but the thresholds of "normal" steady-state CBF are not well established. The reference tolerance limits of CBF can be useful to estimate the risk of CVA in asymptomatic children with SCA, who are negative for hyperemia or evidence of arterial narrowing. Continuous arterial spin labeling (CASL) MR perfusion allows for non-invasive quantification of global and regional CBF. To establish such reference tolerance limits we performed CASL MR examinations on a 3-Tesla MR scanner in a carefully selected cohort of 42 children with SCA (mean age, 8.1±3.3 years; range limits, 2.3-14.4 years; 24 females), who were not on chronic transfusion therapy, had no history of overt stroke or transient ischemic attack, were free of signs and symptoms of focal vascular territory ischemic brain injury, did not have intracranial arterial narrowing on MR angiography and were at low risk for stroke as determined by transcranial Doppler ultrasonography.

Imaging of glutamate neurotransmitter alterations in Alzheimer's disease

Glutamate (Glu) is a major excitatory neurotransmitter in the brain and has been shown to decrease in the early stages of Alzheimer's disease (AD). Using a glutamate chemical (amine) exchange saturation transfer (GluCEST) method, we imaged the change in [Glu] in the APP-PS1 transgenic mouse model of AD at high spatial resolution. Compared with wild-type controls, AD mice exhibited a notable reduction in GluCEST contrast (~30%) in all areas of the brain. The change in [Glu] was further validated through (1) H MRS. A positive correlation was observed between GluCEST contrast and (1) H MRS-measured Glu/total creatine ratio. This method potentially provides a novel noninvasive biomarker for the diagnosis of the disease in preclinical stages and enables the development of disease-modifying therapies for AD.

Vascular distribution of glioblastoma multiforme at diagnosis

Treatment of high-grade gliomas with selective intra-arterial (IA) administration of chemotherapies has been proposed, and utilized as a therapeutic modality. This approach offers the conceptual benefit of providing maximal delivery of the agent to the tumor bed, while potentially reducing systemic exposure to the agent. This retrospective study was designed to determine the vascular distribution of glioblastoma multiforme (GBM) at the time of diagnosis in an effort to determine what proportion of patients would likely be candidates for this approach. The preoperative MRI scans of 50 patients with GBM were analyzed and compared to published normative data of intracranial vascular distribution. Vascular distribution was determined by analyzing post-gadolinium axial and coronal T1 images, axial T2 images, and axial T2 images with an additional 1 cm margin (T2 + 1 cm) added in all dimensions. T1 analysis demonstrated 60% of tumors in a single vascular distribution. T2 analysis of these tumors reduced that number to 34%. When the T2 + 1 cm margin was utilized, only 6% of tumors were in a single vascular distribution. 66% of tumors were limited to the anterior circulation on T1 imaging but only 34% on T2 + 1 cm imaging. 30% of tumors were also within the distribution of the anterior choroidal artery. These findings suggest that the use of selective IA administration of agents is necessarily limited to a fraction of presenting patients or will require administration via multiple cerebral arteries.

Differentiation between oligodendroglioma genotypes using dynamic susceptibility contrast perfusion-weighted imaging and proton MR spectroscopy

BACKGROUND AND PURPOSE

Oligodendrogliomas with 1p/19q chromosome LOH are more sensitive to chemoradiation therapy than those with intact alleles. The usefulness of dynamic susceptibility contrast-PWI-guided ¹H-MRS in differentiating these 2 genotypes was tested in this study.

MATERIALS AND METHODS

Forty patients with oligodendrogliomas, 1p/19q LOH (n = 23) and intact alleles (n = 17), underwent MR imaging and 2D-¹H-MRS. ¹H-MRS VOI was overlaid on FLAIR images to encompass the hyperintense abnormality on the largest cross-section of the neoplasm and then overlaid on CBV maps to coregister CBV maps with ¹H-MRS VOI. rCBVmax values were obtained by measuring the CBV from each of the selected ¹H-MRS voxels in the neoplasm and were normalized with respect to contralateral white matter. Metabolite ratios with respect to ipsilateral Cr were computed from the voxel corresponding to the rCBVmax value. Logistic regression and receiver operating characteristic analyses were performed to ascertain the best model to discriminate the 2 genotypes of oligodendrogliomas. Qualitative evaluation of conventional MR imaging characteristics (patterns of tumor border, signal intensity, contrast enhancement, and paramagnetic susceptibility effect) was also performed to distinguish the 2 groups of oligodendrogliomas.

RESULTS

The incorporation of rCBVmax value and metabolite ratios (NAA/Cr, Cho/Cr, Glx/Cr, myo-inositol/Cr, and lipid + lactate/Cr) into the multivariate logistic regression model provided the best discriminatory classification with sensitivity (82.6%), specificity (64.7%), and accuracy (72%) in distinguishing 2 oligodendroglioma genotypes. Oligodendrogliomas with 1p/19q LOH were also more associated with paramagnetic susceptibility effect (P < .05).

CONCLUSIONS

Our preliminary results indicate the potential of combing PWI and ¹H-MRS to distinguish oligodendroglial genotypes.

Whole-brain analysis of amyotrophic lateral sclerosis by using echo-planar spectroscopic imaging

PURPOSE

To detect regional metabolic differences in amyotrophic lateral sclerosis (ALS) with whole-brain echo-planar spectroscopic imaging.

MATERIALS AND METHODS

Sixteen patients with ALS (nine men, seven women; mean age, 56.6 years), five persons suspected of having ALS (four men, one woman; mean age, 62.6 years), and 10 healthy control subjects (five men, five women; mean age, 56.1 years) underwent echo-planar spectroscopic imaging after providing informed consent. The study was approved by the institutional review board and complied with HIPAA. Data were analyzed with the Metabolic Imaging and Data Analysis System software, and processed metabolite maps were coregistered and normalized to a standard brain template. Metabolite maps of creatine (Cr), choline (Cho), and N-acetylaspartate (NAA) were segmented into 81 regions with Automated Anatomical Labeling software to measure metabolic changes throughout the brains of patients with ALS. Statistical analysis involved an unpaired, uncorrected, two-sided Student t test.

RESULTS

The NAA/Cho ratio across six regions was significantly lower by a mean of 23% (P ≤ .01) in patients with ALS than in control subjects. These regions included the caudate, lingual gyrus, supramarginal gyrus, and right and left superior and right inferior occipital lobes. The NAA/Cr ratio was significantly lower (P ≤ .01) in eight regions in the patient group, by a mean of 16%. These included the caudate, cuneus, frontal inferior operculum, Heschl gyrus, precentral gyrus, rolandic operculum, and superior and inferior occipital lobes. The Cho/Cr ratio did not significantly differ in any region between patient and control groups.

CONCLUSION

Whole-brain echo-planar spectroscopic imaging permits detection of regional metabolic abnormalities in ALS, including not only the motor cortex but also several other regions implicated in ALS pathophysiologic findings.

GLISTR: glioma image segmentation and registration

We present a generative approach for simultaneously registering a probabilistic atlas of a healthy population to brain magnetic resonance (MR) scans showing glioma and segmenting the scans into tumor as well as healthy tissue labels. The proposed method is based on the expectation maximization (EM) algorithm that incorporates a glioma growth model for atlas seeding, a process which modifies the original atlas into one with tumor and edema adapted to best match a given set of patient's images. The modified atlas is registered into the patient space and utilized for estimating the posterior probabilities of various tissue labels. EM iteratively refines the estimates of the posterior probabilities of tissue labels, the deformation field and the tumor growth model parameters. Hence, in addition to segmentation, the proposed method results in atlas registration and a low-dimensional description of the patient scans through estimation of tumor model parameters. We validate the method by automatically segmenting 10 MR scans and comparing the results to those produced by clinical experts and two state-of-the-art methods. The resulting segmentations of tumor and edema outperform the results of the reference methods, and achieve a similar accuracy from a second human rater. We additionally apply the method to 122 patients scans and report the estimated tumor model parameters and their relations with segmentation and registration results. Based on the results from this patient population, we construct a statistical atlas of the glioma by inverting the estimated deformation fields to warp the tumor segmentations of patients scans into a common space.

Sickle cell disease in children: accuracy of imaging transcranial Doppler ultrasonography in detection of intracranial arterial stenosis

This study aimed to determine the accuracy of imaging transcranial Doppler sonography in detection of intracranial arterial stenosis in children with sickle cell disease using three-dimensional MR angiography as a reference standard. Sixty-one children (mean age 102±39 months, 30 males), who had no history of overt stroke, and were classified as at lowest risk of stroke by mean flow velocity criterion <170 cm/s, underwent conventional and imaging transcranial Doppler ultrasonographic examinations. We employed the area under the receiver operating characteristic curve (AUC) to determine the accuracy of flow velocity measurements obtained with imaging ultrasonography with and without correction for the angle of insonation as well as with conventional ultrasonography. We also established the most efficacious velocity thresholds for detection of the stenosis. We found ten intracranial stenoses in six patients on MR angiography, but we calculated AUC only for detection of stenosis (n=6) of the left intracranial internal carotid artery. The accuracy of flow velocity with angle correction was lower than the accuracy of velocity without angle correction (AUC=0.73, 95% CI, 0.53-0.93 versus AUC=0.87, 95% CI, 0.74-1.00; p=0.017). The accuracy of flow velocity obtained with conventional ultrasonography (AUC=0.82, 95% CI, 0.67-0.97) was not different from the accuracy of flow velocities obtained with imaging ultrasonography. We found that the threshold of 165 cm/s of mean velocity without angle correction is associated with highest efficiency for imaging (92%) and conventional ultrasonography (90%). Velocity measurements without angle-correction provide good accuracy in detection of stenosis of the terminal internal carotid artery, whereas angle-corrected velocities have lower accuracy.

Survival analysis of patients with high-grade gliomas based on data mining of imaging variables

BACKGROUND AND PURPOSE

The prediction of prognosis in HGGs is poor in the majority of patients. Our aim was to test whether multivariate prediction models constructed by machine-learning methods provide a more accurate predictor of prognosis in HGGs than histopathologic classification. The prediction of survival was based on DTI and rCBV measurements as an adjunct to conventional imaging.

MATERIALS AND METHODS

The relationship of survival to 55 variables, including clinical parameters (age, sex), categoric or continuous tumor descriptors (eg, tumor location, extent of resection, multifocality, edema), and imaging characteristics in ROIs, was analyzed in a multivariate fashion by using data-mining techniques. A variable selection method was applied to identify the overall most important variables. The analysis was performed on 74 HGGs (18 anaplastic gliomas WHO grades III/IV and 56 GBMs or gliosarcomas WHO grades IV/IV).

RESULTS

Five variables were identified as the most significant, including the extent of resection, mass effect, volume of enhancing tumor, maximum B0 intensity, and mean trace intensity in the nonenhancing/edematous region. These variables were used to construct a prediction model based on a J48 classification tree. The average classification accuracy, assessed by cross-validation, was 85.1%. Kaplan-Meier survival curves showed that the constructed prediction model classified malignant gliomas in a manner that better correlates with clinical outcome than standard histopathology.

CONCLUSIONS

Prediction models based on data-mining algorithms can provide a more accurate predictor of prognosis in malignant gliomas than histopathologic classification alone.

Automated diffusion tensor tractography: implementation and comparison to user-driven tractography

RATIONALE AND OBJECTIVES

Diffusion tensor tractography offers a unique perspective of white matter anatomy, but proper delineation of white matter tracts of interest generally requires the active involvement of an expert neuroanatomist. The investigators describe the implementation of an automated tractographic method requiring no user input and compare its results to those from user-driven tractography.

MATERIALS AND METHODS

Fourteen healthy volunteers underwent diffusion tensor imaging at 3 T. Images were registered to a standard template, and predefined seed regions containing tract termini were transformed into subject space for use in unsupervised probabilistic tractography. The output was compared to the results of user-driven tractography performed on the same subjects.

RESULTS

After the selection of suitable smoothing kernels and thresholds, the results of automated tractography closely approximated those of user-driven tractography. The main bodies of the cingulum, inferior fronto-occipital fasciculus, and inferior longitudinal fasciculus were depicted equally well by both methods. Discrepancies mainly arose at the periphery of these tracts, where anatomic uncertainty tends to be greatest.

CONCLUSIONS

Automated tractography can be used to depict white matter anatomy without need for user intervention, particularly if the main body of the tract is of greatest interest.

Use of magnetic perfusion-weighted imaging to determine epidermal growth factor receptor variant III expression in glioblastoma

Identification of the epidermal growth factor receptor variant III (EGFRvIII) mutation in glioblastoma has become increasingly relevant in the optimization of therapy. Traditionally, determination of tumor EGFRvIII-expression has relied on tissue-based diagnostics. Here, we assess the accuracy of magnetic resonance perfusion-weighted imaging (MR-PWI) in discriminating the EGFRvIII-expressing glioblastoma subtype. We analyzed RNA from 132 primary human glioblastoma tissue samples by reverse-transcription polymerase chain reaction (RT-PCR) for the EGFRvIII and EGFR wild-type mutations and by quantitative RT-PCR for expression of vascular endothelial growth factor (VEGF). Concurrently, 3 independent observers reviewed preoperative 1.5-Tesla (T)/SE or 3.0-Tesla (T)/GE MR perfusion images to determine the maximum relative tumor blood volume (rTBV) of each of these tumors. EGFRvIII-expressing glioblastomas showed significantly higher rTBV, compared with those tumors lacking EGFRvIII expression. This association was observed in both the 1.5T/SE (P = .000) and 3.0T/GE (P = .001) cohorts. By logistic regression analysis, combining the 2 MR system cohorts, rTBV was a very strong predictor of EGFRvIII mutation (odds ratio [rTBV] = 2.70; P = .000; McFadden's ρ(2) = 0.23). Furthermore, by receiver-operating characteristic curve analysis, rTBV discriminated EGFRvIII with very high accuracy (A(z) = 0.81). In addition, we found that VEGF upregulation was associated, although without reaching statistical significance, with EGFRvIII expression (P = .16) and with increased rTBV (F-ratio = 2.71; P = .102). These trends suggest that VEGF-mediated angiogenesis may be a potential mediator of angiogenesis to increase perfusion in EGFRvIII-expressing glioblastomas, but there are likely several other contributing factors. This study demonstrates the potential to use rTBV, a MR-PWI-derived parameter, as a noninvasive surrogate of the EGFRvIII mutation.

A validation study of multicenter diffusion tensor imaging: reliability of fractional anisotropy and diffusivity values

BACKGROUND AND PURPOSE

DTI is increasingly being used as a measure to study tissue damage in several neurologic diseases. Our aim was to investigate the comparability of DTI measures between different MR imaging magnets and platforms.

MATERIALS AND METHODS

Two healthy volunteers underwent DTI on five 3T MR imaging scanners (3 Trios and 2 Signas) by using a matched 33 noncollinear diffusion-direction pulse sequence. Within each subject, a total of 16 white matter (corpus callosum, periventricular, and deep white matter) and gray matter (cortical and deep gray) ROIs were drawn on a single image set and then were coregistered to the other images. Mean FA, ADC, and longitudinal and transverse diffusivities were calculated within each ROI. Concordance correlations were derived by comparing ROI DTI values among each of the 5 magnets.

RESULTS

Mean concordance for FA was 0.96; for both longitudinal and transverse diffusivities, it was 0.93; and for ADC, it was 0.88. Mean scan-rescan concordance was 0.96-0.97 for all DTI measures. Concordance correlations within platforms were, in general, better than those between platforms for all DTI measures (mean concordance of 0.96).

CONCLUSIONS

We found that a 3T magnet and high-angular-resolution pulse sequence yielded comparable DTI measurements across different MR imaging magnets and platforms. Our results indicate that FA is the most comparable measure across magnets, followed by individual diffusivities. The comparability of DTI measures between different magnets supports the feasibility of multicentered clinical trials by using DTI as an outcome measure.

Determination of grade and subtype of meningiomas by using histogram analysis of diffusion-tensor imaging metrics

PURPOSE

To determine whether histogram analysis of diffusion-tensor (DT) magnetic resonance (MR) imaging metrics, including tensor shape measurements, can help determine the grades and subtypes of meningiomas.

MATERIALS AND METHODS

The institutional review board approved this HIPAA-compliant study. Nine atypical, three anaplastic, and 39 typical meningiomas were retrospectively studied. The 39 typical meningiomas included one secretory meningioma and 11 fibroblastic, 11 transitional, 14 meningothelial, and two angiomatous meningiomas. DT imaging metrics, including fractional anisotropy, mean diffusivity, linear anisotropy coefficient, planar anisotropy coefficient (CP), spherical anisotropy coefficient (CS), and eigenvalue skewness (SK), as well as normalized signal intensity from contrast-enhanced T1- and T2-weighted images, were measured from the enhancing region of the tumor. Mean, variance, skewness, and kurtosis were extracted from the histograms. A two-level decision tree was designed, and a multivariate logistic regression analysis was used at each level to determine the best model for classification.

RESULTS

Histogram skewness of SK and kurtosis of SK were significantly higher in atypical and anaplastic meningiomas than in typical meningiomas (P<.01). Among typical meningiomas, significant differences in histogram measures of CP and CS between fibroblastic meningiomas and other subtypes were observed (P<.01). The best model for differentiating atypical and anaplastic meningiomas from typical meningiomas consisted of mean and skewness of SK and kurtosis of T1 signal intensity, with an area under the receiver operating characteristic curve (AUC) of 0.946. The best model for differentiating fibroblastic meningiomas from other subtypes consisted of skewness of T2 signal intensity and kurtosis of CP (AUC, 0.970).

CONCLUSION

Histogram analysis of DT imaging metrics can help determine the grades and subtypes of meningiomas, which can better assist in surgical planning.

Diffusion MR imaging: basic principles

From their origin as simple techniques primarily used for detecting acute cerebral ischemia, diffusion MR imaging techniques have rapidly evolved into a versatile set of tools that provide the only noninvasive means of characterizing brain microstructure and connectivity, becoming a mainstay of both clinical and investigational brain MR imaging. In this article, the basic principles required for understanding diffusion MR imaging techniques are reviewed with clinical neuroradiologists in mind.

T(1ρ) MRI in Alzheimer's disease: detection of pathological changes in medial temporal lobe

BACKGROUND

The need of an early and noninvasive diagnosis of AD requires the development of imaging-based techniques. As an alternative, the magnetic resonance image (MRI) relaxation time constant (T1ρ) was measured in brains of Alzheimer's disease (AD), mild-cognitive impairment (MCI), and age-matched controls in order to determine whether T1ρ values correlated with the neurological diagnosis.

METHODS

MRI was performed on AD (n=48), MCI (n=45), and age-matched control (n=41), on a 1.5 Tesla Siemens clinical MRI scanner. T1ρ maps were generated by fitting each pixel's intensity as a function of the duration of the spin-lock pulse. T1ρ values were calculated from the gray matter (GM) and white matter (WM) of medial temporal lobe (MTL).

RESULTS

GM and WM T1ρ values were 87.5±1.2 ms and 80.5±1.4 ms, respectively, in controls, 90.9±1.3 ms and 84.1±1.7 ms in MCI, and 91.9±.8 ms and 88.3±1.3 ms in AD cohorts. Compared to control, AD patients showed 9% increased WM T1ρ and 5% increased GM T1ρ. Compared to control, MCI individuals showed 4% increased T1ρ both in WM and GM. A 5% increased T1ρ was found in WM of AD over MCI.

CONCLUSION

The increased T1ρ in WM and GM of MTL in AD may be associated with the pathological changes that are not evident on conventional MRI.