Automated Quality Evaluation Index for Arterial Spin Labeling Derived Cerebral Blood Flow Maps

BACKGROUND

Arterial spin labeling (ASL) derived cerebral blood flow (CBF) maps are prone to artifacts and noise that can degrade image quality.

PURPOSE

To develop an automated and objective quality evaluation index (QEI) for ASL CBF maps.

STUDY TYPE

Retrospective.

POPULATION

Data from N = 221 adults, including patients with Alzheimer's disease (AD), Parkinson's disease, and traumatic brain injury.

FIELD STRENGTH/SEQUENCE

Pulsed or pseudocontinuous ASL acquired at 3 T using non-background suppressed 2D gradient-echo echoplanar imaging or background suppressed 3D spiral spin-echo readouts.

ASSESSMENT

The QEI was developed using N = 101 2D CBF maps rated as unacceptable, poor, average, or excellent by two neuroradiologists and validated by 1) leave-one-out cross validation, 2) assessing if CBF reproducibility in N = 53 cognitively normal adults correlates inversely with QEI, 3) if iterative discarding of low QEI data improves the Cohen's d effect size for CBF differences between preclinical AD (N = 27) and controls (N = 53), 4) comparing the QEI with manual ratings for N = 50 3D CBF maps, and 5) comparing the QEI with another automated quality metric.

STATISTICAL TESTS

Inter-rater reliability and manual vs. automated QEI were quantified using Pearson's correlation. P < 0.05 was considered significant.

RESULTS

The correlation between QEI and manual ratings (R = 0.83, CI: 0.76-0.88) was similar (P = 0.56) to inter-rater correlation (R = 0.81, CI: 0.73-0.87) for the 2D data. CBF reproducibility correlated negatively (R = -0.74, CI: -0.84 to -0.59) with QEI. The effect size comparing patients and controls improved (R = 0.72, CI: 0.59-0.82) as low QEI data was discarded iteratively. The correlation between QEI and manual ratings (R = 0.86, CI: 0.77-0.92) of 3D ASL was similar (P = 0.09) to inter-rater correlation (R = 0.78, CI: 0.64-0.87). The QEI correlated (R = 0.87, CI: 0.77-0.92) significantly better with manual ratings than did an existing approach (R = 0.54, CI: 0.30-0.72).

DATA CONCLUSION

Automated QEI performed similarly to manual ratings and can provide scalable ASL quality control.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 1.

Artificial intelligence-based locoregional markers of brain peritumoral microenvironment

In malignant primary brain tumors, cancer cells infiltrate into the peritumoral brain structures which results in inevitable recurrence. Quantitative assessment of infiltrative heterogeneity in the peritumoral region, the area where biopsy or resection can be hazardous, is important for clinical decision making. Here, we derive a novel set of Artificial intelligence (AI)-based markers capturing the heterogeneity of tumor infiltration, by characterizing free water movement restriction in the peritumoral region using Diffusion Tensor Imaging (DTI)-based free water volume fraction maps. We leverage the differences in the peritumoral region of metastasis and glioblastomas, the former consisting of vasogenic versus the latter containing infiltrative edema, to extract a voxel-wise deep learning-based peritumoral microenvironment index (PMI). Descriptive characteristics of locoregional hubs of uniformly high PMI values are then extracted as AI-based markers to capture distinct aspects of infiltrative heterogeneity. The proposed markers are utilized to stratify patients' survival and IDH1 mutation status on a population of 275 adult-type diffuse gliomas (CNS WHO grade 4). Our results show significant differences in the proposed markers between patients with different overall survival and IDH1 mutation status (t test, Wilcoxon rank sum test, linear regression; p < 0.01). Clustering of patients using the proposed markers reveals distinct survival groups (logrank; p < 10^-5, Cox hazard ratio = 1.82; p < 0.005). Our findings provide a panel of markers as surrogates of infiltration that might capture novel insight about underlying biology of peritumoral microstructural heterogeneity, providing potential biomarkers of prognosis pertaining to survival and molecular stratification, with applicability in clinical decision making.

NIMG-23. AI-BASED CONNECTED COMPONENT MARKERS OF BRAIN PERITUMORAL MICROENVIRONMENT USING WATER RESTRICTION INFORMATION

PURPOSE

Glioblastoma is the most aggressive adult brain tumor, with heterogeneous neoplastic cell peritumoral infiltration. Characterization of this infiltrative peritumoral heterogeneity is an unmet clinical need that could contribute to strengthening our understanding of this disease. We propose novel AI-based markers of infiltration using deep-learning (DL) based on water restriction caused by infiltration, identified by diffusion tensor imaging (DTI). These markers could contribute to precision/personalized medicine, towards influencing clinical decision-making, including planning for biopsies, surgery, and radiation. METHOD: We automatically extracted peritumoral patches from free water volume fraction maps (FW-VF) of a retrospective cohort of 44 brain metastases and 66 glioblastomata patients and labelled them as high- and low- free water, respectively. An AI/DL model was then trained on these patches to distinguish differences in water restriction. Our trained AI/DL model was then applied on FW-VF of 264 hold-out glioblastoma patients (survival:0.43-76.9 months, age:21-88, 104 females) to generate a peritumoral microenvironment index (PMI) map quantifying infiltrative heterogeneity. Connected components (CCs) of high PMI values were calculated and their descriptive characteristics of size, number, shape, directionality, and spatial location, were extracted as AI-based markers. Gaussian mixture model clustering was then applied on these markers to determine if their representative infiltrative peritumoral heterogeneity can capture overall survival differences, by partitioning the patients into three clusters: low, moderate, and high risk.

RESULTS

The log-rank test yielded significant differences (p&lt; 10-5) between low- and high-risk patients, (HR= 0.47, 95% CI:0.34-0.65; P&lt; 0.005). Average PMI values were significantly greater in high-risk patients (P&lt; 0.05).

CONCLUSION

We introduced novel AI-based markers of infiltration in the peritumoral microenvironment, using information of water restriction extracted from DTI. Our proposed markers can capture overall survival differences, based on the patterns of infiltration using DTI-based characterization of the water restriction, that show promise as clinically relevant prognostic biomarkers.

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.

Tractography-Based Surgical Targeting for Thalamic Deep Brain Stimulation: A Comparison of Probabilistic vs Deterministic Fiber Tracking of the Dentato-Rubro-Thalamic Tract

BACKGROUND

The ventral intermediate (VIM) thalamic nucleus is the main target for the surgical treatment of refractory tremor. Initial targeting traditionally relies on atlas-based stereotactic targeting formulas, which only minimally account for individual anatomy. Alternative approaches have been proposed, including direct targeting of the dentato-rubro-thalamic tract (DRTT), which, in clinical settings, is generally reconstructed with deterministic tracking. Whether more advanced probabilistic techniques are feasible on clinical-grade magnetic resonance acquisitions and lead to enhanced reconstructions is poorly understood.

OBJECTIVE

To compare DRTT reconstructed with deterministic vs probabilistic tracking.

METHODS

This is a retrospective study of 19 patients with essential tremor who underwent deep brain stimulation (DBS) with intraoperative neurophysiology and stimulation testing. We assessed the proximity of the DRTT to the DBS lead and to the active contact chosen based on clinical response.

RESULTS

In the commissural plane, the deterministic DRTT was anterior (P < 10-4) and lateral (P < 10-4) to the DBS lead. By contrast, although the probabilistic DRTT was also anterior to the lead (P < 10-4), there was no difference in the mediolateral dimension (P = .5). Moreover, the 3-dimensional Euclidean distance from the active contact to the probabilistic DRTT was smaller vs the distance to the deterministic DRTT (3.32 ± 1.70 mm vs 5.01 ± 2.12 mm; P < 10-4).

CONCLUSION

DRTT reconstructed with probabilistic fiber tracking was superior in spatial proximity to the physiology-guided DBS lead and to the empirically chosen active contact. These data inform strategies for surgical targeting of the VIM.

NIMG-28. PROSPECTIVE HISTOPATHOLOGY-VALIDATED MACHINE LEARNING FOR DISTINGUISHING TRUE PROGRESSION FROM TREATMENT-RELATED CHANGES IN GLIOBLASTOMA PATIENTS

PURPOSE

Decision making about the best course of treatment for glioblastoma patients becomes challenging when a new enhancing lesion appears in the vicinity of the surgical bed on follow-up MRI (after maximal safe tumor resection and chemoradiation), raising concerns for tumor progression (TP). Literature indicates 30-50% of these new lesions describe primarily treatment-related changes (TRC). We hypothesize that quantitative analysis of specific and sensitive features extracted from multi-parametric MRI (mpMRI) via machine learning (ML) techniques may yield non-invasive imaging signatures that distinguish TP from TRC and facilitate better treatment personalization.

METHODS

We have generated an ML model on a retrospective cohort of 58 subjects, and prospectively evaluated on an independent cohort of 58 previously unseen patients who underwent second resection for suspicious recurrence and had availability of advanced mpMRI (T1, T1-Gd, T2, T2-FLAIR, DTI, DSC). The features selected by our retrospective model, representing principal components analysis of intensity distributions, morphological, statistical, and texture descriptors, were extracted from the mpMRI of the prospective cohort. Integration of these features revealed signatures distinguishing between TP, mixed response, and TRC. Independently, a board-certified neuropathologist evaluated the resected tissue by blindly classifying it in the above three categories, based on mitotic figures, pseudopalisading necrosis, geographic necrosis, dystrophic calcification, vascular changes, and Ki67.

RESULTS

Tissues classified as TRC by the neuropathologist were associated with imaging phenotypes of lower angiogenesis (DSC-derived features), lower cellularity (DTI-derived features), and higher water concentration (T2, T2-FLAIR features). Our ML model characterized TP with 78% accuracy (sensitivity:86%, specificity:70%, AUC:0.80 (95%CI, 0.68-0.92)) and TRC with 81% accuracy (sensitivity:80%, specificity:81%, AUC:0.87 (95%CI, 0.72-1.00)).

CONCLUSION

Our proposed ML model reveals distinct non-invasive markers of TP and TRC, directly associated with histopathological changes in prospective glioblastoma patients. Reliable stratification of TP and TRC entities may help to noninvasively determine whether the course of treatment should change.

Toxicity after AAV delivery of RNAi expression constructs into nonhuman primate brain

RNA interference (RNAi) for spinocerebellar ataxia type 1 can prevent and reverse behavioral deficits and neuropathological readouts in mouse models, with safety and benefit lasting over many months. The RNAi trigger, expressed from adeno-associated virus vectors (AAV.miS1), also corrected misregulated microRNAs (miRNA) such as miR150. Subsequently, we showed that the delivery method was scalable, and that AAV.miS1 was safe in short-term pilot nonhuman primate (NHP) studies. To advance the technology to patients, investigational new drug (IND)-enabling studies in NHPs were initiated. After AAV.miS1 delivery to deep cerebellar nuclei, we unexpectedly observed cerebellar toxicity. Both small-RNA-seq and studies using AAVs devoid of miRNAs showed that this was not a result of saturation of the endogenous miRNA processing machinery. RNA-seq together with sequencing of the AAV product showed that, despite limited amounts of cross-packaged material, there was substantial inverted terminal repeat (ITR) promoter activity that correlated with neuropathologies. ITR promoter activity was reduced by altering the miS1 expression context. The surprising contrast between our rodent and NHP findings highlight the need for extended safety studies in multiple species when assessing new therapeutics for human application.

Enhanced Fiber Tractography Using Edema Correction: Application and Evaluation in High-Grade Gliomas

BACKGROUND

A limitation of diffusion tensor imaging (DTI)-based tractography is peritumoral edema that confounds traditional diffusion-based magnetic resonance metrics.

OBJECTIVE

To augment fiber-tracking through peritumoral regions by performing novel edema correction on clinically feasible DTI acquisitions and assess the accuracy of the fiber-tracks using intraoperative stimulation mapping (ISM), task-based functional magnetic resonance imaging (fMRI) activation maps, and postoperative follow-up as reference standards.

METHODS

Edema correction, using our bi-compartment free water modeling algorithm (FERNET), was performed on clinically acquired DTI data from a cohort of 10 patients presenting with suspected high-grade glioma and peritumoral edema in proximity to and/or infiltrating language or motor pathways. Deterministic fiber-tracking was then performed on the corrected and uncorrected DTI to identify tracts pertaining to the eloquent region involved (language or motor). Tracking results were compared visually and quantitatively using mean fiber count, voxel count, and mean fiber length. The tracts through the edematous region were verified based on overlay with the corresponding motor or language task-based fMRI activation maps and intraoperative ISM points, as well as at time points after surgery when peritumoral edema had subsided.

RESULTS

Volume and number of fibers increased with application of edema correction; concordantly, mean fractional anisotropy decreased. Overlay with functional activation maps and ISM-verified eloquence of the increased fibers. Comparison with postsurgical follow-up scans with lower edema further confirmed the accuracy of the tracts.

CONCLUSION

This method of edema correction can be applied to standard clinical DTI to improve visualization of motor and language tracts in patients with glioma-associated peritumoral edema.

Focused Ultrasound Thalamotomy for Essential Tremor in the Setting of a Ventricular Shunt: Technical Report

BACKGROUND

A recent randomized controlled trial of magnetic resonance imaging (MRI)-guided focused ultrasound (FUS) for essential tremor (ET) demonstrated safety and efficacy. Patients with ventricular shunts may be good candidates for FUS to minimize hardware-associated infections.

OBJECTIVE

To demonstrate feasibility of FUS in this subset of patients.

METHODS

A 74-yr-old male with medically refractory ET, and a right-sided ventricular shunt for normal pressure hydrocephalus, underwent FUS to the right ventro-intermedius (VIM) nucleus. The VIM nucleus was directly targeted using deterministic tractography. Clinical outcomes were measured using the Clinical Rating Scale for Tremor.

RESULTS

Shunt components required 6% of the total ultrasound transducer elements to be shut off. Eight therapeutic sonications were delivered (maximum temperature, 64°), leading to a 90% improvement in hand tremor and a 100% improvement in functional disability at the 3-mo follow-up. No complications were noted.

CONCLUSION

This is the first case of FUS thalamotomy in a patient with a shunt. Direct VIM targeting and achievement of therapeutic temperatures with acoustic energy is feasible in this subset of patients.

Portable gluten sensors: qualitative assessments by adults and adolescents with coeliac disease

BACKGROUND

Portable gluten sensors are now commercially available to the public, although there is genuine uncertainty within the medical community over whether they should be used for coeliac disease management. The present study described qualitatively the experience of using a portable gluten sensor for 15 adults and 15 adolescents with coeliac disease participating in a 3-month pilot clinical trial.

METHODS

Participants were 30 individuals, aged 13-70 years, with biopsy-confirmed coeliac disease on a gluten-free diet. All received a portable gluten sensor and were randomised to low, medium, and high numbers of single-use capsules. Open-ended questions addressed likes and dislikes using the portable gluten sensor after 3 months. Major themes were identified and described.

RESULTS

Participants liked that the portable gluten sensor provided extra assurance to check foods presented as gluten-free, the convenient size and portability, the added sense of control, and overall peace-of-mind. Participants disliked having attention drawn to them when using the sensor and feeling as if they were deterring others from eating. Participants also disliked the physical difficulty associated with using the capsules, questionable accuracy and the inability to test fermented foods. Adults were more enthusiastic about the sensor than adolescents.

CONCLUSIONS

Positive and negative experiences may be expected when using commercially available portable gluten sensors to help manage coeliac disease. As future versions of this and other gluten sensors become available, it will be important to investigate the relationship between users' experience with the sensors and long-term outcomes such as mucosal healing and quality of life.

Histopathology-validated machine learning radiographic biomarker for noninvasive discrimination between true progression and pseudo-progression in glioblastoma

BACKGROUND

Imaging of glioblastoma patients after maximal safe resection and chemoradiation commonly demonstrates new enhancements that raise concerns about tumor progression. However, in 30% to 50% of patients, these enhancements primarily represent the effects of treatment, or pseudo-progression (PsP). We hypothesize that quantitative machine learning analysis of clinically acquired multiparametric magnetic resonance imaging (mpMRI) can identify subvisual imaging characteristics to provide robust, noninvasive imaging signatures that can distinguish true progression (TP) from PsP.

METHODS

We evaluated independent discovery (n = 40) and replication (n = 23) cohorts of glioblastoma patients who underwent second resection due to progressive radiographic changes suspicious for recurrence. Deep learning and conventional feature extraction methods were used to extract quantitative characteristics from the mpMRI scans. Multivariate analysis of these features revealed radiophenotypic signatures distinguishing among TP, PsP, and mixed response that compared with similar categories blindly defined by board-certified neuropathologists. Additionally, interinstitutional validation was performed on 20 new patients.

RESULTS

Patients who demonstrate TP on neuropathology are significantly different (P < .0001) from those with PsP, showing imaging features reflecting higher angiogenesis, higher cellularity, and lower water concentration. The accuracy of the proposed signature in leave-one-out cross-validation was 87% for predicting PsP (area under the curve [AUC], 0.92) and 84% for predicting TP (AUC, 0.83), whereas in the discovery/replication cohort, the accuracy was 87% for predicting PsP (AUC, 0.84) and 78% for TP (AUC, 0.80). The accuracy in the interinstitutional cohort was 75% (AUC, 0.80).

CONCLUSION

Quantitative mpMRI analysis via machine learning reveals distinctive noninvasive signatures of TP versus PsP after treatment of glioblastoma. Integration of the proposed method into clinical studies can be performed using the freely available Cancer Imaging Phenomics Toolkit.

Thalamic Deep Brain Stimulation for Essential Tremor: Relation of the Dentatorubrothalamic Tract with Stimulation Parameters

BACKGROUND

In deep brain stimulation (DBS) for essential tremor, the primary target ventrointermedius (VIM) nucleus cannot be clearly visualized with structural imaging. As such, there has been much interest in the dentatorubrothalamic tract (DRTT) for target localization, but evidence for the DRTT as a putative stimulation target in tremor suppression is lacking. We evaluated proximity of the DRTT in relation to DBS stimulation parameters.

METHODS

This is a retrospective analysis of 26 consecutive patients who underwent DBS with microelectrode recordings (46 leads). Fiber tracking was performed with a published deterministic technique. Clinically optimized stimulation parameters were obtained in all patients at the time of most recent follow-up (6.2 months). Volume of tissue activated (VTA) around contacts was calculated from a published model.

RESULTS

Tremor severity was reduced in all treated hemispheres, with 70% improvement in the treated hand score of the Clinical Rating Scale for Tremor. At the level of the active contact (2.9 ± 2.0 mm superior to the commissural plane), the center of the DRTT was lateral to the contacts (5.1 ± 2.1 mm). The nearest fibers of the DRTT were 2.4 ± 1.7 mm from the contacts, whereas the radius of the VTA was 2.9 ± 0.7 mm. The VTA overlapped with the DRTT in 77% of active contacts. The distance from active contact to the DRTT was positively correlated with stimulation voltage requirements (Kendall τ = 0.33, P = 0.006), whereas distance to the atlas-based VIM coordinates was not.

CONCLUSIONS

Active contacts in proximity to the DRTT had lower voltage requirements. Data from a large cohort provide support for the DRTT as an effective stimulation target for tremor control.

Prognostic value of contrast enhancement and FLAIR for survival in newly diagnosed glioblastoma treated with and without bevacizumab: results from ACRIN 6686

Background

ACRIN 6686/RTOG 0825 was a phase III trial of conventional chemoradiation plus adjuvant temozolomide with bevacizumab or without (placebo) in newly diagnosed glioblastoma. This study investigated whether changes in contrast-enhancing and fluid attenuated inversion recovery (FLAIR)-hyperintense tumor assessed by central reading prognosticate overall survival (OS).

Methods

Two hundred eighty-four patients (171 men; median age 57 y, range 19-79; 159 on bevacizumab) had MRI at post-op (baseline) and pre-cycle 4 of adjuvant temozolomide (22 wk post chemoradiation initiation). Four central readers measured bidimensional lesion enhancement (2D-T1) and FLAIR hyperintensity at both time points. Changes from baseline to pre-cycle 4 for both markers were dichotomized (increasing vs non-increasing). Cox proportional hazards model and Kaplan-Meier survival estimates were used for inference.

Results

Adjusting for treatment, increasing 2D-T1 (n = 262, hazard ratio [HR] = 2.07, 95% CI: 1.48-2.91, P < 0.0001) and FLAIR (n = 273, HR = 1.75, 95% CI: 1.26-2.41, P = 0.0008) significantly predicted worse OS. Median OS (days) was significantly shorter for patients with increasing versus non-increasing 2D-T1 for both bevacizumab (443 vs 535, P = 0.004) and placebo (526 vs 887, P = 0.001). Median OS was significantly shorter for patients with increasing versus non-increasing FLAIR for placebo (595 vs 872, P = 0.001), and trended similarly for bevacizumab (499 vs 535, P = 0.0935). Adjusting for 2D-T1 and treatment, increasing FLAIR represented significantly higher risk for death (HR = 1.59 [1.11-2.26], P = 0.01).

Conclusion

Increased 2D-T1 significantly predicts worse OS in both treatment groups, implying absence of a substantial proportion of pseudoprogression 22 weeks after initiation of standard therapy. FLAIR adds value beyond 2D-T1 in predicting OS, potentially addressing the pseudoresponse effect by substratifying bevacizumab-treated patients with non-increasing 2D-T1.

Neuroimaging Findings in US Government Personnel With Possible Exposure to Directional Phenomena in Havana, Cuba

IMPORTANCE

United States government personnel experienced potential exposures to uncharacterized directional phenomena while serving in Havana, Cuba, from late 2016 through May 2018. The underlying neuroanatomical findings have not been described.

OBJECTIVE

To examine potential differences in brain tissue volume, microstructure, and functional connectivity in government personnel compared with individuals not exposed to directional phenomena.

DESIGN, SETTING, AND PARTICIPANTS

Forty government personnel (patients) who were potentially exposed and experienced neurological symptoms underwent evaluation at a US academic medical center from August 21, 2017, to June 8, 2018, including advanced structural and functional magnetic resonance imaging analytics. Findings were compared with imaging findings of 48 demographically similar healthy controls.

EXPOSURES

Potential exposure to uncharacterized directional phenomena of unknown etiology, manifesting as pressure, vibration, or sound.

MAIN OUTCOMES AND MEASURES

Potential imaging-based differences between patients and controls with regard to (1) white matter and gray matter total and regional brain volumes, (2) cerebellar tissue microstructure metrics (eg, mean diffusivity), and (3) functional connectivity in the visuospatial, auditory, and executive control subnetworks.

RESULTS

Imaging studies were completed for 40 patients (mean age, 40.4 years; 23 [57.5%] men; imaging performed a median of 188 [range, 4-403] days after initial exposure) and 48 controls (mean age, 37.6 years; 33 [68.8%] men). Mean whole brain white matter volume was significantly smaller in patients compared with controls (patients: 542.22 cm3; controls: 569.61 cm3; difference, -27.39 [95% CI, -37.93 to -16.84] cm3; P < .001), with no significant difference in the whole brain gray matter volume (patients: 698.55 cm3; controls: 691.83 cm3; difference, 6.72 [95% CI, -4.83 to 18.27] cm3; P = .25). Among patients compared with controls, there were significantly greater ventral diencephalon and cerebellar gray matter volumes and significantly smaller frontal, occipital, and parietal lobe white matter volumes; significantly lower mean diffusivity in the inferior vermis of the cerebellum (patients: 7.71 × 10-4 mm2/s; controls: 8.98 × 10-4 mm2/s; difference, -1.27 × 10-4 [95% CI, -1.93 × 10-4 to -6.17 × 10-5] mm2/s; P < .001); and significantly lower mean functional connectivity in the auditory subnetwork (patients: 0.45; controls: 0.61; difference, -0.16 [95% CI, -0.26 to -0.05]; P = .003) and visuospatial subnetwork (patients: 0.30; controls: 0.40; difference, -0.10 [95% CI, -0.16 to -0.04]; P = .002) but not in the executive control subnetwork (patients: 0.24; controls: 0.25; difference: -0.016 [95% CI, -0.04 to 0.01]; P = .23).

CONCLUSIONS AND RELEVANCE

Among US government personnel in Havana, Cuba, with potential exposure to directional phenomena, compared with healthy controls, advanced brain magnetic resonance imaging revealed significant differences in whole brain white matter volume, regional gray and white matter volumes, cerebellar tissue microstructural integrity, and functional connectivity in the auditory and visuospatial subnetworks but not in the executive control subnetwork. The clinical importance of these differences is uncertain and may require further study.

Diminished quality of life among adolescents with coeliac disease using maladaptive eating behaviours to manage a gluten-free diet: a cross-sectional, mixed-methods study

BACKGROUND

Certain approaches to managing a strict gluten-free diet (GFD) for coeliac disease (CD) may lead to impaired psychosocial well-being, a diminished quality of life (QOL) and disordered eating. The present study aimed to understand adolescents' approaches to managing a GFD and the association with QOL.

METHODS

Thirty adolescents with CD (13-17 years old) following the GFD for at least 1 year completed the Celiac Dietary Adherence Test (CDAT) and QOL survey. Their approaches to GFD management were explored using a semi-structured interview, where key themes were developed using an iterative process, and further analysed using a psychosocial rubric to classify management strategies and QOL. CDAT ratings were compared across groups.

RESULTS

Gluten-free diet management strategies were classified on a four-point scale. Adaptive eating behaviours were characterised by greater flexibility (versus rigidity), trust (versus avoidance), confidence (versus controlling behaviour) and awareness (versus preoccupation) with respect to maintaining a GFD. Approximately half the sample (53.3%) expressed more maladaptive approaches to maintaining a GFD and those who did so were older with lower CD-Specific Pediatric Quality of Life (CDPQOL) scores, mean subscale differences ranging from 15.0 points for Isolation (t = 2.4, P = 0.03, d.f. = 28) to 23.4 points for Limitations (t = 3.0, P = 0.01, d.f. = 28).

CONCLUSIONS

Adolescents with CD who manage a GFD with maladaptive eating behaviours similar to known risk factors for feeding and eating disorders experience diminished QOL. In accordance with CD management recommendations, we recommend ongoing follow-up with gastroenterologists and dietitians and psychosocial support referrals, as needed.

Three-dimensional echo planar spectroscopic imaging for differentiation of true progression from pseudoprogression in patients with glioblastoma

Accurate differentiation of true progression (TP) from pseudoprogression (PsP) in patients with glioblastomas (GBMs) is essential for planning adequate treatment and for estimating clinical outcome measures and future prognosis. The purpose of this study was to investigate the utility of three-dimensional echo planar spectroscopic imaging (3D-EPSI) in distinguishing TP from PsP in GBM patients. For this institutional review board approved and HIPAA compliant retrospective study, 27 patients with GBM demonstrating enhancing lesions within six months of completion of concurrent chemo-radiation therapy were included. Of these, 18 were subsequently classified as TP and 9 as PsP based on histological features or follow-up MRI studies. Parametric maps of choline/creatine (Cho/Cr) and choline/N-acetylaspartate (Cho/NAA) were computed and co-registered with post-contrast T₁ -weighted and FLAIR images. All lesions were segmented into contrast enhancing (CER), immediate peritumoral (IPR), and distal peritumoral (DPR) regions. For each region, Cho/Cr and Cho/NAA ratios were normalized to corresponding metabolite ratios from contralateral normal parenchyma and compared between TP and PsP groups. Logistic regression analyses were performed to obtain the best model to distinguish TP from PsP. Significantly higher Cho/NAA was observed from CER (2.69 ± 1.00 versus 1.56 ± 0.51, p = 0.003), IPR (2.31 ± 0.92 versus 1.53 ± 0.56, p = 0.030), and DPR (1.80 ± 0.68 versus 1.19 ± 0.28, p = 0.035) regions in TP patients compared with those with PsP. Additionally, significantly elevated Cho/Cr (1.74 ± 0.44 versus 1.34 ± 0.26, p = 0.023) from CER was observed in TP compared with PsP. When these parameters were incorporated in multivariate regression analyses, a discriminatory model with a sensitivity of 94% and a specificity of 87% was observed in distinguishing TP from PsP. These results indicate the utility of 3D-EPSI in differentiating TP from PsP with high sensitivity and specificity.

Multiparametric magnetic resonance imaging in the assessment of anti-EGFRvIII chimeric antigen receptor T cell therapy in patients with recurrent glioblastoma

EGFRvIII targeted chimeric antigen receptor T (CAR-T) cell therapy has recently been reported for treating glioblastomas (GBMs); however, physiology-based MRI parameters have not been evaluated in this setting. Ten patients underwent multiparametric MRI at baseline, 1, 2 and 3 months after CAR-T therapy. Logistic regression model derived progression probabilities (PP) using imaging parameters were used to assess treatment response. Four lesions from "early surgery" group demonstrated high PP at baseline suggestive of progression, which was confirmed histologically. Out of eight lesions from remaining six patients, three lesions with low PP at baseline remained stable. Two lesions with high PP at baseline were associated with large decreases in PP reflecting treatment response, whereas other two lesions with high PP at baseline continued to demonstrate progression. One patient didn't have baseline data but demonstrated progression on follow-up. Our findings indicate that multiparametric MRI may be helpful in monitoring CAR-T related early therapeutic changes in GBM patients.

Neurological Manifestations Among US Government Personnel Reporting Directional Audible and Sensory Phenomena in Havana, Cuba

IMPORTANCE

From late 2016 through August 2017, US government personnel serving on diplomatic assignment in Havana, Cuba, reported neurological symptoms associated with exposure to auditory and sensory phenomena.

OBJECTIVE

To describe the neurological manifestations that followed exposure to an unknown energy source associated with auditory and sensory phenomena.

DESIGN, SETTING, AND PARTICIPANTS

Preliminary results from a retrospective case series of US government personnel in Havana, Cuba. Following reported exposure to auditory and sensory phenomena in their homes or hotel rooms, the individuals reported a similar constellation of neurological symptoms resembling brain injury. These individuals were referred to an academic brain injury center for multidisciplinary evaluation and treatment.

EXPOSURES

Report of experiencing audible and sensory phenomena emanating from a distinct direction (directional phenomena) associated with an undetermined source, while serving on US government assignments in Havana, Cuba, since 2016.

MAIN OUTCOMES AND MEASURES

Descriptions of the exposures and symptoms were obtained from medical record review of multidisciplinary clinical interviews and examinations. Additional objective assessments included clinical tests of vestibular (dynamic and static balance, vestibulo-ocular reflex testing, caloric testing), oculomotor (measurement of convergence, saccadic, and smooth pursuit eye movements), cognitive (comprehensive neuropsychological battery), and audiometric (pure tone and speech audiometry) functioning. Neuroimaging was also obtained.

RESULTS

Of 24 individuals with suspected exposure identified by the US Department of State, 21 completed multidisciplinary evaluation an average of 203 days after exposure. Persistent symptoms (>3 months after exposure) were reported by these individuals including cognitive (n = 17, 81%), balance (n = 15, 71%), visual (n = 18, 86%), and auditory (n = 15, 68%) dysfunction, sleep impairment (n = 18, 86%), and headaches (n = 16, 76%). Objective findings included cognitive (n = 16, 76%), vestibular (n = 17, 81%), and oculomotor (n = 15, 71%) abnormalities. Moderate to severe sensorineural hearing loss was identified in 3 individuals. Pharmacologic intervention was required for persistent sleep dysfunction (n = 15, 71%) and headache (n = 12, 57%). Fourteen individuals (67%) were held from work at the time of multidisciplinary evaluation. Of those, 7 began graduated return to work with restrictions in place, home exercise programs, and higher-level work-focused cognitive rehabilitation.

CONCLUSIONS AND RELEVANCE

In this preliminary report of a retrospective case series, persistent cognitive, vestibular, and oculomotor dysfunction, as well as sleep impairment and headaches, were observed among US government personnel in Havana, Cuba, associated with reports of directional audible and/or sensory phenomena of unclear origin. These individuals appeared to have sustained injury to widespread brain networks without an associated history of head trauma.

Imaging Surrogates of Infiltration Obtained Via Multiparametric Imaging Pattern Analysis Predict Subsequent Location of Recurrence of Glioblastoma

BACKGROUND

Glioblastoma is an aggressive and highly infiltrative brain cancer. Standard surgical resection is guided by enhancement on postcontrast T1-weighted (T1) magnetic resonance imaging, which is insufficient for delineating surrounding infiltrating tumor.

OBJECTIVE

To develop imaging biomarkers that delineate areas of tumor infiltration and predict early recurrence in peritumoral tissue. Such markers would enable intensive, yet targeted, surgery and radiotherapy, thereby potentially delaying recurrence and prolonging survival.

METHODS

Preoperative multiparametric magnetic resonance images (T1, T1-gadolinium, T2-weighted, T2-weighted fluid-attenuated inversion recovery, diffusion tensor imaging, and dynamic susceptibility contrast-enhanced magnetic resonance images) from 31 patients were combined using machine learning methods, thereby creating predictive spatial maps of infiltrated peritumoral tissue. Cross-validation was used in the retrospective cohort to achieve generalizable biomarkers. Subsequently, the imaging signatures learned from the retrospective study were used in a replication cohort of 34 new patients. Spatial maps representing the likelihood of tumor infiltration and future early recurrence were compared with regions of recurrence on postresection follow-up studies with pathology confirmation.

RESULTS

This technique produced predictions of early recurrence with a mean area under the curve of 0.84, sensitivity of 91%, specificity of 93%, and odds ratio estimates of 9.29 (99% confidence interval: 8.95-9.65) for tissue predicted to be heavily infiltrated in the replication study. Regions of tumor recurrence were found to have subtle, yet fairly distinctive multiparametric imaging signatures when analyzed quantitatively by pattern analysis and machine learning.

CONCLUSION

Visually imperceptible imaging patterns discovered via multiparametric pattern analysis methods were found to estimate the extent of infiltration and location of future tumor recurrence, paving the way for improved targeted treatment.

Individualized Map of White Matter Pathways: Connectivity-Based Paradigm for Neurosurgical Planning

BACKGROUND

Advances in white matter tractography enhance neurosurgical planning and glioma resection, but white matter tractography is limited by biological variables such as edema, mass effect, and tract infiltration or selection biases related to regions of interest or fractional anisotropy values.

OBJECTIVE

To provide an automated tract identification paradigm that corrects for artifacts created by tumor edema and infiltration and provides a consistent, accurate method of fiber bundle identification.

METHODS

An automated tract identification paradigm was developed and evaluated for glioma surgery. A fiber bundle atlas was generated from 6 healthy participants. Fibers of a test set (including 3 healthy participants and 10 patients with brain tumors) were clustered adaptively with this atlas. Reliability of the identified tracts in both groups was assessed by comparison with 2 experts with the Cohen κ used to quantify concurrence. We evaluated 6 major fiber bundles: cingulum bundle, fornix, uncinate fasciculus, arcuate fasciculus, inferior fronto-occipital fasciculus, and inferior longitudinal fasciculus, the last 3 tracts mediating language function.

RESULTS

The automated paradigm demonstrated a reliable and practical method to identify white mater tracts, despite mass effect, edema, and tract infiltration. When the tumor demonstrated significant mass effect or shift, the automated approach was useful for providing an initialization to guide the expert with identification of the specific tract of interest.

CONCLUSION

We report a reliable paradigm for the automated identification of white matter pathways in patients with gliomas. This approach should enhance the neurosurgical objective of maximal safe resections.

ABBREVIATIONS

AF, arcuate fasciculusDTI, diffusion tensor imagingIFOF, inferior fronto-occipital fasciculusILF, inferior longitudinal fasciculusROI, region of interestWM, white matter.

Population-based MRI atlases of spatial distribution are specific to patient and tumor characteristics in glioblastoma

Background and purpose

In treating glioblastoma (GB), surgical and chemotherapeutic treatment guidelines are, for the most part, independent of tumor location. In this work, we compiled imaging data from a large cohort of GB patients to create statistical atlases illustrating the disease spatial frequency as a function of patient demographics as well as tumor characteristics.

Materials and methods

Two-hundred-six patients with pathology-proven glioblastoma were included. Of those, 65 had pathology-proven recurrence and 113 had molecular subtype and genetic information. We used validated software to segment the tumors in all patients and map them from patient space into a common template. We then created statistical maps that described the spatial location of tumors with respect to demographics and tumor characteristics. We applied a chi-square test to determine whether pattern differences were statistically significant.

Results

The most frequent location for glioblastoma in our patient population is the right temporal lobe. There are statistically significant differences when comparing patterns using demographic data such as gender (p = 0.0006) and age (p = 0.006). Small and large tumors tend to occur in separate locations (p = 0.0007). The tumors tend to occur in different locations according to their molecular subtypes (p < 10^− 6). The classical subtype tends to spare the frontal lobes, the neural subtype tend to involve the inferior right frontal lobe. Although the sample size is limited, there was a difference in location according to EGFR VIII genotype (p < 10^− 4), with a right temporal dominance for EFGR VIII negative tumors, and frontal lobe dominance in EGFR VIII positive tumors.

Conclusions

Spatial location of GB is an important factor that correlates with demographic factors and tumor characteristics, which should therefore be considered when evaluating a patient with GB and might assist in personalized treatment.

•

Atlases of spatial distribution of glioblastoma are created.

•

Atlases are specific to patient characteristics such as age and gender.

•

Atlases are specific to tumor characteristics such as size and molecule subtype.

•

Atlases are specific to tumor genetics.

•

Spatial location should be considered when evaluating a patient with glioblastoma.

Differentiating Tumor Progression from Pseudoprogression in Patients with Glioblastomas Using Diffusion Tensor Imaging and Dynamic Susceptibility Contrast MRI

BACKGROUND AND PURPOSE

Early assessment of treatment response is critical in patients with glioblastomas. A combination of DTI and DSC perfusion imaging parameters was evaluated to distinguish glioblastomas with true progression from mixed response and pseudoprogression.

MATERIALS AND METHODS

Forty-one patients with glioblastomas exhibiting enhancing lesions within 6 months after completion of chemoradiation therapy were retrospectively studied. All patients underwent surgery after MR imaging and were histologically classified as having true progression (>75% tumor), mixed response (25%-75% tumor), or pseudoprogression (<25% tumor). Mean diffusivity, fractional anisotropy, linear anisotropy coefficient, planar anisotropy coefficient, spheric anisotropy coefficient, and maximum relative cerebral blood volume values were measured from the enhancing tissue. A multivariate logistic regression analysis was used to determine the best model for classification of true progression from mixed response or pseudoprogression.

RESULTS

Significantly elevated maximum relative cerebral blood volume, fractional anisotropy, linear anisotropy coefficient, and planar anisotropy coefficient and decreased spheric anisotropy coefficient were observed in true progression compared with pseudoprogression (P < .05). There were also significant differences in maximum relative cerebral blood volume, fractional anisotropy, planar anisotropy coefficient, and spheric anisotropy coefficient measurements between mixed response and true progression groups. The best model to distinguish true progression from non-true progression (pseudoprogression and mixed) consisted of fractional anisotropy, linear anisotropy coefficient, and maximum relative cerebral blood volume, resulting in an area under the curve of 0.905. This model also differentiated true progression from mixed response with an area under the curve of 0.901. A combination of fractional anisotropy and maximum relative cerebral blood volume differentiated pseudoprogression from nonpseudoprogression (true progression and mixed) with an area under the curve of 0.807.

CONCLUSIONS

DTI and DSC perfusion imaging can improve accuracy in assessing treatment response and may aid in individualized treatment of patients with glioblastomas.

Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques

BACKGROUND

MRI characteristics of brain gliomas have been used to predict clinical outcome and molecular tumor characteristics. However, previously reported imaging biomarkers have not been sufficiently accurate or reproducible to enter routine clinical practice and often rely on relatively simple MRI measures. The current study leverages advanced image analysis and machine learning algorithms to identify complex and reproducible imaging patterns predictive of overall survival and molecular subtype in glioblastoma (GB).

METHODS

One hundred five patients with GB were first used to extract approximately 60 diverse features from preoperative multiparametric MRIs. These imaging features were used by a machine learning algorithm to derive imaging predictors of patient survival and molecular subtype. Cross-validation ensured generalizability of these predictors to new patients. Subsequently, the predictors were evaluated in a prospective cohort of 29 new patients.

RESULTS

Survival curves yielded a hazard ratio of 10.64 for predicted long versus short survivors. The overall, 3-way (long/medium/short survival) accuracy in the prospective cohort approached 80%. Classification of patients into the 4 molecular subtypes of GB achieved 76% accuracy.

CONCLUSIONS

By employing machine learning techniques, we were able to demonstrate that imaging patterns are highly predictive of patient survival. Additionally, we found that GB subtypes have distinctive imaging phenotypes. These results reveal that when imaging markers related to infiltration, cell density, microvascularity, and blood-brain barrier compromise are integrated via advanced pattern analysis methods, they form very accurate predictive biomarkers. These predictive markers used solely preoperative images, hence they can significantly augment diagnosis and treatment of GB patients.

Pattern analysis of dynamic susceptibility contrast-enhanced MR imaging demonstrates peritumoral tissue heterogeneity

PURPOSE

To augment the analysis of dynamic susceptibility contrast material-enhanced magnetic resonance (MR) images to uncover unique tissue characteristics that could potentially facilitate treatment planning through a better understanding of the peritumoral region in patients with glioblastoma.

MATERIALS AND METHODS

Institutional review board approval was obtained for this study, with waiver of informed consent for retrospective review of medical records. Dynamic susceptibility contrast-enhanced MR imaging data were obtained for 79 patients, and principal component analysis was applied to the perfusion signal intensity. The first six principal components were sufficient to characterize more than 99% of variance in the temporal dynamics of blood perfusion in all regions of interest. The principal components were subsequently used in conjunction with a support vector machine classifier to create a map of heterogeneity within the peritumoral region, and the variance of this map served as the heterogeneity score.

RESULTS

The calculated principal components allowed near-perfect separability of tissue that was likely highly infiltrated with tumor and tissue that was unlikely infiltrated with tumor. The heterogeneity map created by using the principal components showed a clear relationship between voxels judged by the support vector machine to be highly infiltrated and subsequent recurrence. The results demonstrated a significant correlation (r = 0.46, P < .0001) between the heterogeneity score and patient survival. The hazard ratio was 2.23 (95% confidence interval: 1.4, 3.6; P < .01) between patients with high and low heterogeneity scores on the basis of the median heterogeneity score.

CONCLUSION

Analysis of dynamic susceptibility contrast-enhanced MR imaging data by using principal component analysis can help identify imaging variables that can be subsequently used to evaluate the peritumoral region in glioblastoma. These variables are potentially indicative of tumor infiltration and may become useful tools in guiding therapy, as well as individualized prognostication.

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.

Migraine with aura is associated with an incomplete circle of willis: results of a prospective observational study

Objective

To compare the prevalence of an incomplete circle of Willis in patients with migraine with aura, migraine without aura, and control subjects, and correlate circle of Willis variations with alterations in cerebral perfusion.

Methods

Migraine with aura, migraine without aura, and control subjects were prospectively enrolled in a 1∶1∶1 ratio. Magnetic resonance angiography was performed to examine circle of Willis anatomy and arterial spin labeled perfusion magnetic resonance imaging to measure cerebral blood flow. A standardized template rating system was used to categorize circle of Willis variants. The primary pre-specified outcome measure was the frequency of an incomplete circle of Willis. The association between circle of Willis variations and cerebral blood flow was also analyzed.

Results

170 subjects were enrolled (56 migraine with aura, 61 migraine without aura, 53 controls). An incomplete circle of Willis was significantly more common in the migraine with aura compared to control group (73% vs. 51%, p = 0.02), with a similar trend for the migraine without aura group (67% vs. 51%, p = 0.08). Using a quantitative score of the burden of circle of Willis variants, migraine with aura subjects had a higher burden of variants than controls (p = 0.02). Compared to those with a complete circle, subjects with an incomplete circle had greater asymmetry in hemispheric cerebral blood flow (p = 0.05). Specific posterior cerebral artery variants were associated with greater asymmetries of blood flow in the posterior cerebral artery territory.

Conclusions

An incomplete circle of Willis is more common in migraine with aura subjects than controls, and is associated with alterations in cerebral blood flow.

Differentiation between glioblastomas, solitary brain metastases, and primary cerebral lymphomas using diffusion tensor and dynamic susceptibility contrast-enhanced MR imaging

BACKGROUND AND PURPOSE

Glioblastomas, brain metastases, and PCLs may have similar enhancement patterns on MR imaging, making the differential diagnosis difficult or even impossible. The purpose of this study was to determine whether a combination of DTI and DSC can assist in the differentiation of glioblastomas, solitary brain metastases, and PCLs.

MATERIALS AND METHODS

Twenty-six glioblastomas, 25 brain metastases, and 16 PCLs were retrospectively identified. DTI metrics, including FA, ADC, CL, CP, CS, and rCBV were measured from the enhancing, immediate peritumoral and distant peritumoral regions. A 2-level decision tree was designed, and a multivariate logistic regression analysis was used at each level to determine the best model for classification.

RESULTS

From the enhancing region, significantly elevated FA, CL, and CP and decreased CS values were observed in glioblastomas compared with brain metastases and PCLs (P < .001), whereas ADC, rCBV, and rCBV(max) values of glioblastomas were significantly higher than those of PCLs (P < .01). The best model to distinguish glioblastomas from nonglioblastomas consisted of ADC, CS (or FA) from the enhancing region, and rCBV from the immediate peritumoral region, resulting in AUC = 0.938. The best predictor to differentiate PCLs from brain metastases comprised ADC from the enhancing region and CP from the immediate peritumoral region with AUC = 0.909.

CONCLUSIONS

The combination of DTI metrics and rCBV measurement can help in the differentiation of glioblastomas from brain metastases and PCLs.

Role of proton magnetic resonance spectroscopy in differentiating oligodendrogliomas from astrocytomas

BACKGROUND AND PURPOSE

Preoperative differentiation of astrocytomas from oligodendrogliomas is clinically important, as oligodendrogliomas are more sensitive to chemotherapy. The purpose of this study was to assess the role of proton magnetic resonance spectroscopy in distinguishing astrocytomas from oligodendrogliomas.

METHODS

Forty-six patients [astrocytomas (n= 17) and oligodendrogliomas (n= 29)] underwent magnetic resonance imaging and multi voxel proton magnetic resonance spectroscopic imaging before treatment. Peak areas for N-acetylaspartate (NAA), creatine (Cr), choline (Cho), myo-inositol (mI), glutamate/glutamine (Glx), and lipids + lactate (Lip+Lac) were analyzed from voxels that exhibited hyperintensity on fluid-attenuated inversion recovery images and were normalized to Cr from each voxel. The average metabolite/Cr ratios from these voxels were then compared between astrocytomas and oligodendrogliomas. Receiver-operating curve analyses were used as measures of differentiation accuracy of metabolite ratios. A threshold value for a metabolite ratio was estimated by maximizing the sum of sensitivity and specificity.

RESULTS

A significant difference in mI/Cr was observed between astrocytomas and oligodendrogliomas (.50 +/- .18 vs. 0.66 +/- 0.20, P < .05). Using a threshold value of .56 for mI/Cr ratio, it was possible to differentiate oligodendrogliomas from astrocytomas with a sensitivity of 72.4% and specificity of 76.4%.

CONCLUSION

These results suggest that mI/Cr might aid in distinguishing oligodendrogliomas from astrocytomas.

Unenhanced dynamic MR angiography: high spatial and temporal resolution by using true FISP-based spin tagging with alternating radiofrequency

PURPOSE

To present an unenhanced four-dimensional time-resolved dynamic magnetic resonance (MR) angiography technique with true fast imaging with steady-state precession-based spin tagging with alternating radiofrequency (STAR), also called TrueSTAR.

MATERIALS AND METHODS

This study received Institutional Review Board approval and was HIPAA compliant. Informed consent was obtained from all study subjects. In eight healthy volunteers, the spatial and temporal resolution of the TrueSTAR technique were optimized. In another six healthy volunteers, the contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of the TrueSTAR dynamic MR angiography images were compared with those acquired by using a standard Look-Locker echo-planar technique by using the Wilcoxon signed rank test. Finally, one patient with an arteriovenous malformation (AVM) was studied by using this technique.

RESULTS

The SNR and CNR of the TrueSTAR dynamic MR angiography images were 29% and 39% higher, respectively, compared with those acquired by using a standard Look-Locker echo-planar imaging sequence (both P = .028). In the AVM patient, TrueSTAR dynamic MR angiography delineated the dynamic course of labeled blood flowing through feeding arteries into the nidus and draining veins.

CONCLUSION

The results suggest that TrueSTAR is a promising unenhanced dynamic MR angiography technique for clinical evaluation of cerebrovascular disorders such as AVM, steno-occlusive disease, and aneurysm.

Noninvasive measurement of cerebral blood flow and blood oxygenation using near-infrared and diffuse correlation spectroscopies in critically brain-injured adults

BACKGROUND

This study assesses the utility of a hybrid optical instrument for noninvasive transcranial monitoring in the neurointensive care unit. The instrument is based on diffuse correlation spectroscopy (DCS) for measurement of cerebral blood flow (CBF), and near-infrared spectroscopy (NIRS) for measurement of oxy- and deoxy-hemoglobin concentration. DCS/NIRS measurements of CBF and oxygenation from frontal lobes are compared with concurrent xenon-enhanced computed tomography (XeCT) in patients during induced blood pressure changes and carbon dioxide arterial partial pressure variation.

METHODS

Seven neurocritical care patients were included in the study. Relative CBF measured by DCS (rCBF(DCS)), and changes in oxy-hemoglobin (DeltaHbO(2)), deoxy-hemoglobin (DeltaHb), and total hemoglobin concentration (DeltaTHC), measured by NIRS, were continuously monitored throughout XeCT during a baseline scan and a scan after intervention. CBF from XeCT regions-of-interest (ROIs) under the optical probes were used to calculate relative XeCT CBF (rCBF(XeCT)) and were then compared to rCBF(DCS). Spearman's rank coefficients were employed to test for associations between rCBF(DCS) and rCBF(XeCT), as well as between rCBF from both modalities and NIRS parameters.

RESULTS

rCBF(DCS) and rCBF(XeCT) showed good correlation (r (s) = 0.73, P = 0.010) across the patient cohort. Moderate correlations between rCBF(DCS) and DeltaHbO(2)/DeltaTHC were also observed. Both NIRS and DCS distinguished the effects of xenon inhalation on CBF, which varied among the patients.

CONCLUSIONS

DCS measurements of CBF and NIRS measurements of tissue blood oxygenation were successfully obtained in neurocritical care patients. The potential for DCS to provide continuous, noninvasive bedside monitoring for the purpose of CBF management and individualized care is demonstrated.

Pseudopathologic brain parenchymal enhancement due to venous reflux from left-sided injection and brachiocephalic vein narrowing

In this report, we present a case of a patient with CT angiographic artifacts related to left-sided venous injection resulting in a striking pattern of enhancement simulating vascular abnormalities, which prompted additional diagnostic imaging. To our knowledge, no similar case has been reported in the published literature to date.

Hippocampal volumetry and functional MRI of memory in temporal lobe epilepsy

This study examined the utility of structural and functional MRI at 1.5 and 3T in the presurgical evaluation and prediction of postsurgical cognitive outcome in temporal lobe epilepsy (TLE). Forty-nine patients undergoing presurgical evaluation for temporal lobe (TL) resection and 25 control subjects were studied. Patients completed standard presurgical evaluations, including the intracarotid amobarbital test (IAT) and neuropsychological testing. During functional imaging, subjects performed a complex visual scene-encoding task. High-resolution structural MRI scans were used to quantify hippocampal volumes. Both structural and functional imaging successfully lateralized the seizure focus and correlated with IAT memory lateralization, with improvement for functional imaging at 3T as compared with 1.5 T. Ipsilateral structural and functional MRI data were related to cognitive outcome, and greater functional asymmetry was related to earlier age at onset. These findings support continued investigation of the utility of MRI and fMRI in the presurgical evaluation of TLE.

Combination antiretroviral therapy modulates the blood oxygen level-dependent amplitude in human immunodeficiency virus-seropositive patients

Combination antiretroviral therapy (cART) limits human immunodeficiency virus (HIV) replication in the central nervous system (CNS) and prevents progressive neurological dysfunction. We examined if the degree of CNS penetration by cART, as estimated by the CNS penetration effectiveness (CPE) score, affects brain activity as measured by the amplitude of the blood oxygen level-dependent functional magnetic resonance imaging (BOLD fMRI) response. HIV+ patients on low-CPE cART (n=12) had a significantly greater BOLD fMRI response amplitude than HIV+ patients on high-CPE cART (n=12) or seronegative controls (n=10). An increase in the BOLD fMRI response in HIV patients on low-CPE cART may reflect continued HIV replication in the CNS leading to increased oxidative stress and associated metabolic demands.

Differentiation between glioblastomas and solitary brain metastases using diffusion tensor imaging

The purpose of this study is to determine whether diffusion tensor imaging (DTI) metrics including tensor shape measures such as linear and planar anisotropy coefficients (CL and CP) can help differentiate glioblastomas from solitary brain metastases. Sixty-three patients with histopathologic diagnosis of glioblastomas (22 men, 16 women, mean age 58.4 years) and brain metastases (13 men, 12 women, mean age 56.3 years) were included in this study. Contrast-enhanced T1-weighted, fluid-attenuated inversion recovery (FLAIR) images, fractional anisotropy (FA), apparent diffusion coefficient (ADC), CL and CP maps were co-registered and each lesion was semi-automatically subdivided into four regions: central, enhancing, immediate peritumoral and distant peritumoral. DTI metrics as well as the normalized signal intensity from the contrast-enhanced T1-weighted images were measured from each region. Univariate and multivariate logistic regression analyses were employed to determine the best model for classification. The results demonstrated that FA, CL and CP from glioblastomas were significantly higher than those of brain metastases from all segmented regions (p<0.05), and the differences from the enhancing regions were most significant (p<0.001). FA and CL from the enhancing region had the highest prediction accuracy when used alone with an area under the curve of 0.90. The best logistic regression model included three parameters (ADC, FA and CP) from the enhancing part, resulting in 92% sensitivity, 100% specificity and area under the curve of 0.98. We conclude that DTI metrics, used individually or combined, have a potential as a non-invasive measure to differentiate glioblastomas from metastases.

Arteriovenous shunt visualization in arteriovenous malformations with arterial spin-labeling MR imaging

BACKGROUND AND PURPOSE

A reliable quantitative technique for measuring arteriovenous (AV) shunt in vascular malformations is not currently available. Here, we evaluated the hypothesis that continuous arterial spin-labeled (CASL) perfusion MR imaging can be used to detect and measure AV shunt in patients with arteriovenous malformations (AVMs).

MATERIALS AND METHODS

CASL perfusion MR imaging was performed in 7 patients with AVMs. Semiquantitative AV shunt estimates were generated based on a thresholding strategy by using signal-intensity difference (DeltaM) images to avoid potential errors in cerebral blood flow (CBF) calculation related to abnormal transit times and nonphysiologic blood-tissue water exchange in and around the AVMs. The potential for measuring CBF in regions distant from and near the AVM was explored, as was the relationship of CBF changes related to the size of the shunt.

RESULTS

In all 7 cases, striking increased intensity was seen on CASL perfusion DeltaM maps in the nidus and venous structures draining the AVM. Shunt estimates ranged from 30% to 0.6%. Mean CBF measurements in structures near the AVMs were not significantly different from the contralateral measurements. However, CBF in adjacent ipsilateral white matter increased relative to the contralateral side as the percent shunt increased (P = .02). Cortical gray matter CBF Delta (contralateral-ipsilateral) values demonstrated the same effect, but the correlation was weak and not significant. Thalamic CBF decreased ipsilaterally with increasing percent AV shunt (P = .01), indicating a possible steal effect. Basal ganglia Delta values showed little change in CBF with the size of the AV shunt.

CONCLUSION

CASL perfusion MR imaging can demonstrate AV shunting, providing high lesion conspicuity and a novel means for evaluating AVM physiology.

Prediction of oligodendroglial tumor subtype and grade using perfusion weighted magnetic resonance imaging

OBJECT

Treatment of patients with oligodendrogliomas relies on histopathological grade and characteristic cytogenetic deletions of 1p and 19q, shown to predict radio- and chemosensitivity and prolonged survival. Perfusion weighted magnetic resonance (MR) imaging allows for noninvasive determination of relative tumor blood volume (rTBV) and has been used to predict the grade of astrocytic neoplasms. The aim of this study was to use perfusion weighted MR imaging to predict tumor grade and cytogenetic profile in oligodendroglial neoplasms.

METHODS

Thirty patients with oligodendroglial neoplasms who underwent preoperative perfusion MR imaging were retrospectively identified. Tumors were classified by histopathological grade and stratified into two cytogenetic groups: 1p or 1p and 19q loss of heterozygosity (LOH) (Group 1), and 19q LOH only on intact alleles (Group 2). Tumor blood volume was calculated in relation to contralateral white matter. Multivariate logistic regression analysis was used to develop predictive models of cytogenetic profile and tumor grade.

RESULTS

In World Health Organization Grade II neoplasms, the rTBV was significantly greater (p < 0.05) in Group 1 (mean 2.44, range 0.96-3.28; seven patients) compared with Group 2 (mean 1.69, range 1.27-2.08; seven patients). In Grade III neoplasms, the differences between Group 1 (mean 3.38, range 1.59-6.26; four patients) and Group 2 (mean 2.83, range 1.81-3.76; 12 patients) were not significant. The rTBV was significantly greater (p < 0.05) in Grade III neoplasms (mean 2.97, range 1.59-6.26; 16 patients) compared with Grade II neoplasms (mean 2.07, range 0.96-3.28; 14 patients). The models integrating rTBV with cytogenetic profile and grade showed prediction accuracies of 68 and 73%, respectively.

CONCLUSIONS

Oligodendroglial classification models derived from advanced imaging will improve the accuracy of tumor grading, provide prognostic information, and have potential to influence treatment decisions.

Arterial spin-labeling and MR spectroscopy in the differentiation of gliomas

BACKGROUND AND PURPOSE

Noninvasive grading of gliomas remains a challenge despite its important role in the prognosis and management of patients with intracranial neoplasms. In this study, we evaluated the ability of cerebral blood flow (CBF)-guided voxel-by-voxel analysis of multivoxel proton MR spectroscopic imaging ((1)H-MRSI) to differentiate low-grade from high-grade gliomas.

MATERIALS AND METHODS

A total of 35 patients with primary gliomas (22 high grade and 13 low grade) underwent continuous arterial spin-labeling perfusion-weighted imaging (PWI) and (1)H-MRSI. Different regions of the gliomas were categorized as "hypoperfused," "isoperfused," and "hyperperfused" on the basis of the average CBF obtained from contralateral healthy white matter. (1)H-MRSI indices were computed from these regions and compared between low- and high-grade gliomas. Using a similar approach, we applied a subgroup analysis to differentiate low- from high-grade oligodendrogliomas because they show different physiologic and genetic characteristics.

RESULTS

Cho(glioma (G)/white matter (WM)), Glx(G/WM), and Lip+Lac(G)/Cr(WM) were significantly higher in the "hyperperfused" regions of high-grade gliomas compared with low-grade gliomas. Cho(G/WM) and Lip+Lac(G)/Cr(WM) were also significantly higher in the "hyperperfused" regions of high-grade oligodendrogliomas. However, metabolite ratios from the "hypoperfused" or "isoperfused" regions did not exhibit any significant differences between high-grade and low-grade gliomas.

CONCLUSION

The results suggest that (1)H-MRSI indices from the "hyperperfused" regions of gliomas, on the basis of PWI, may be helpful in distinguishing high-grade from low-grade gliomas including oligodendrogliomas.

Magnetic resonance imaging for detection and determination of tumor volume in a genetically engineered mouse model of ovarian cancer

Our laboratory developed a transgenic mouse model of spontaneous epithelial ovarian cancer (EOC) in which tumors are initiated by expression of the early region of the Simian Virus 40 (SV40) under transcriptional control of the 5' upstream regulatory region of the Müllerian inhibiting substance type II receptor (MISIIR) gene. Female TgMISIIR-Tag-DR26 transgenic mice develop bilateral ovarian tumors with variable latency and survive an average of 152 days. In the absence of reliable methods for disease detection and evaluation of therapeutic response, preclinical studies of this transgenic mouse model of EOC would be limited to longitudinal experiments involving large numbers of animals with euthanasia as the endpoint. Therefore, a non-invasive method for detecting tumors, measuring tumor volume and calculating parameters relevant to the evaluation of therapeutic or preventive interventions (i.e., tumor growth rates, tumor initiation, tumor regression and the time for tumors to reach a given size) is required. We developed and optimized a non-invasive Magnetic Resonance Imaging (MRI) scanning protocol to obtain high resolution abdominal images that is well tolerated by mice. Superior contrast and contrast to noise ratio (CNR) was found with Gd-DTPA contrast enhanced T(1)-weighted sequences. Image sets in both the axial and coronal orientations for redundant measurements of normal ovary and ovarian tumor volume can be acquired in approximately 20 minutes. Accuracy of MRI-based ovary and tumor volume determinations was verified by standard volume measurements at necropsy. Serial imaging studies were performed on 41 ovarian cancer bearing TgMISIIR-Tag-DR26 transgenic mice to quantitate tumor progression over time in this model. A chemotherapy study was conducted on TgMISIIR-Tag-DR26 transgenic mice using a standard combination therapy consisting of cisplatin and paclitaxel. Our results demonstrate that MRI is well tolerated and can be repeated in serial imaging studies, permitting quantitative analysis of tumor growth and progression and response to therapeutic interventions.

Detection of human immunodeficiency virus induced inflammation and oxidative stress in lenticular nuclei with magnetic resonance spectroscopy despite antiretroviral therapy

BACKGROUND

Single-voxel magnetic resonance spectroscopy measurements of N-acetyl aspartate, choline, and creatine (Cr) are affected in patients with human immunodeficiency virus (HIV) and neurocognitive impairment. However, these metabolic markers are often normalized in affected central nervous system regions, such as the lenticular nuclei, after initiation of highly active antiretroviral therapy (HAART).

OBJECTIVE

To examine whether lactate (Lac), a marker of inflammation and anaerobic glycolysis, and lipid, an indicator of cell membrane turnover resulting from oxidative stress, could serve as surrogate biomarkers within the lenticular nuclei of HIV-positive patients with different degrees of neurocognitive impairment.

DESIGN

Three-tesla 2-dimensional-chemical shift imaging magnetic resonance spectroscopy at echo times of 30 milliseconds and 135 milliseconds was performed in voxels overlapping the lenticular nuclei of seronegative controls and a spectrum of HIV-positive patients (neurocognitively normal, mildly impaired, or moderately to severely impaired).

SETTING

University of Pennsylvania, Philadelphia.

PARTICIPANTS

Ten seronegative controls and 45 HIV-positive patients with different degrees of neurocognitive impairment (15 neurocognitively normal patients, 12 mildly impaired patients, and 18 moderately to severely impaired patients).

MAIN OUTCOME MEASURES

In vivo 2-dimensional-chemical shift imaging magnetic resonance spectroscopy analysis of N-acetyl aspartate:Cr, choline:Cr, Lac:Cr, and (lipid + Lac):Cr ratios among the various groups. In addition, the effect of the degree of HAART central nervous system penetration (high vs low) on these ratios was studied.

RESULTS

No significant lenticular nuclei atrophy was detected with volumes similar across all of the groups. Both N-acetyl aspartate:Cr and choline:Cr ratios were similar across all of the groups at either echo time. In contrast, the Lac:Cr ratio was significantly greater in HIV-positive patients with moderate to severe impairment compared with seronegative controls. The (lipid + Lac):Cr ratio was significantly elevated within each HIV-positive subgroup compared with seronegative controls. Within HIV-positive patients receiving HAART, the degree of central nervous system penetration (high vs low) did not affect metabolic ratios.

CONCLUSIONS

As seen with 2-dimensional-chemical shift imaging magnetic resonance spectroscopy, HIV induces inflammation and oxidative stress in HIV-positive patients despite HAART. Lipid and Lac are more sensitive inflammatory biomarkers that may be used to differentiate HIV-positive subgroups. However, no significant difference in efficacy, as measured by metabolic ratios, exists for high- vs low-central nervous system-penetrating HAART.

Clinical neuroimaging using arterial spin-labeled perfusion magnetic resonance imaging

The two most common methods for measuring perfusion with MRI are based on dynamic susceptibility contrast (DSC) and arterial spin labeling (ASL). Although clinical experience to date is much more extensive with DSC perfusion MRI, ASL methods offer several advantages. The primary advantages are that completely noninvasive absolute cerebral blood flow (CBF) measurements are possible with relative insensitivity to permeability, and that multiple repeated measurements can be obtained to evaluate one or more interventions or to perform perfusion-based functional MRI. ASL perfusion and perfusion-based functional MRI methods have been applied in many clinical settings, including acute and chronic cerebrovascular disease, CNS neoplasms, epilepsy, aging and development, neurodegenerative disorders, and neuropsychiatric diseases. Recent technical advances have improved the sensitivity of ASL perfusion MRI, and increasing use is expected in the coming years. The present review focuses on ASL perfusion MRI and applications in clinical neuroimaging.

Intraaxial brain masses: MR imaging-based diagnostic strategy--initial experience

PURPOSE

To develop and retrospectively determine the accuracy of a magnetic resonance (MR) imaging strategy to differentiate intraaxial brain masses, with histologic findings or clinical diagnosis as the reference standard.

MATERIALS AND METHODS

The study was HIPAA compliant and was approved by the institutional review board. A waiver of informed consent was obtained. A strategy was developed on the basis of conventional MR imaging, diffusion-weighted MR imaging, perfusion MR imaging, and proton MR spectroscopy to classify intraaxial masses as low-grade primary neoplasms, high-grade primary neoplasms, metastatic neoplasms, abscesses, lymphomas, tumefactive demyelinating lesions (TDLs), or encephalitis. The strategy was evaluated by using data from 111 patients (46 women, 65 men; mean age, 48.9 years) with imaging results available on a departmental picture archiving and communication system from a 5-year search period. Bayesian statistics of the strategy elements and three clinical tasks were calculated.

RESULTS

Search results identified 44 patients with high-grade and 14 with low-grade primary neoplasms, 24 with abscesses, 12 with lymphoma, 11 with TDLs, five with metastases, and one with encephalitis who had undergone conventional and advanced MR imaging. However, only 40 patients (25 women, 15 men; mean age, 45 years) had undergone all studies and had data to allow completion of the entire strategy. Accuracy, sensitivity, and specificity of the strategy, respectively, were 90%, 97%, and 67% for discrimination of neoplastic from nonneoplastic diseases, 90%, 88%, and 100% for discrimination of high-grade from low-grade neoplasms, and 85%, 84%, and 87% for discrimination of high-grade neoplasms and lymphoma from low-grade neoplasms and nonneoplastic diseases.

CONCLUSION

An integrated MR imaging-based strategy, which is accurate in differentiation of several intraaxial brain masses, was proposed.

Actinomycotic brain infection: registered diffusion, perfusion MR imaging and MR spectroscopy

INTRODUCTION

Actinomycotic brain infection is caused by an organism of the Actinomyces genus. We report here one such case.

METHODS

The methods used included coregistered diffusion, perfusion and spectroscopic magnetic resonance (MR) imaging.

RESULTS

Decreased apparent diffusion coefficient, markedly elevated fractional anisotropy (FA) and reduced cerebral blood flow were observed. MR spectroscopy demonstrated elevated amino acids, acetate and succinate.

CONCLUSION

Elevated FA values may be due to the microstructure of this special brain infection.

Structural MRI of carotid artery atherosclerotic lesion burden and characterization of hemispheric cerebral blood flow before and after carotid endarterectomy

Collateral circulation plays a major role in maintaining cerebral blood flow (CBF) in patients with internal carotid artery (ICA) stenosis. CBF can remain normal despite severe ICA stenosis, making the benefit of carotid endarterectomy (CEA) or stenting difficult to assess. Before and after surgery, we assessed CBF supplied through the ipsilateral (stenotic) or contralateral ICA individually with a novel hemisphere-selective arterial spin-labeling (ASL) perfusion MR technique. We further explored the relationship between CBF and ICA obstruction ratio (OR) acquired with a multislice black-blood imaging sequence. For patients with unilateral ICA stenosis (n = 19), conventional bilateral labeling did not reveal interhemispheric differences. With unilateral labeling, CBF in the middle cerebral artery (MCA) territory on the surgical side from the ipsilateral supply (53.7 +/- 3.3 ml/100 g/min) was lower than CBF in the contralateral MCA territory from the contralateral supply (58.5 +/- 2.7 ml/100 g/min), although not statistically significant (p = 0.09). The ipsilateral MCA territory received significant (p = 0.02) contralateral supply (7.0 +/- 2.7 ml/100 g/min), while ipsilateral supply to the contralateral side was not reciprocated. After surgery (n = 11), ipsilateral supply to the MCA territory increased from 57.3 +/- 5.7 to 67.3 +/- 5.4 ml/100 g/min (p = 0.03), and contralateral supply to the ipsilateral MCA territory decreased. The best predictor of increased CBF on the side of surgery was normalized presurgical ipsilateral supply (r(2) = 0.62, p = 0.004). OR was less predictive of change, although the change in normalized contralateral supply was negatively correlated with OR(excess) (=OR(ipsilateral) - OR(contralateral)) (r(2) = 0.58, p = 0.006). The results demonstrate the effect of carotid artery stenosis on blood supply to the cerebral hemispheres, as well as the relative role of collateral pathways before surgery and redistribution of blood flow through these pathways after surgery. Unilateral ASL may better predict hemodynamic surgical outcome (measured by improved perfusion) than ICA OR.

Artificial Multiple Sclerosis Lesions on Simulated FLAIR Brain MR Images: Echo Time and Observer Performance in Detection

The institutional review board approved the described HIPAA-compliant study, which was performed to prospectively evaluate observer performance in the detection of artificial multiple sclerosis (MS) lesions that were randomly distributed supra- and infratentorially on simulated fluid-attenuated inversion-recovery (FLAIR) magnetic resonance (MR) images obtained at different echo times (TEs). MR parametric maps were derived from mixed multi-echo inversion-recovery images obtained in a 40-year-old healthy male volunteer and in a patient with MS, both of whom gave informed consent. Pseudo-randomly distributed artificial MS lesions of varying size, number, and location were equally represented on the FLAIR images (11 000/100-200/2600 [repetition time msec/TE msec/inversion time msec]). Twelve images obtained in both regions at each of 11 TEs spaced 10 msec apart were rated by seven neuroradiologists by using a four-point scale. Observer performance in the detection of MS lesions on the FLAIR images, as estimated by using areas under the alternative free-response receiver operating characteristic curve, was highest and most consistent at the 100-msec TE, both supratentorially (93.0% +/- 8.6 [standard error of the mean]) and infratentorially (87.4% +/- 10.0).