Assessing changes in microstructural integrity of white matter tracts in children with leukaemia following exposure to chemotherapy.

BACKGROUND: Intrathecal and intravenous chemotherapy, specifically methotrexate, might contribute to neural microstructural damage. OBJECTIVE: To assess, by diffusion tensor imaging, microstructural integrity of white matter in paediatric patients with acute lymphoblastic leukaemia (ALL) following intrathecal and intravenous chemotherapy. MATERIALS AND METHODS: Eleven children diagnosed with de novo ALL underwent MRI scans of the brain with diffusion tensor imaging (DTI) prior to commencement of chemotherapy and at 12 months after diagnosis, using a 3-tesla (T) MRI scanner. We investigated the changes in DTI parameters in white matter tracts before and after chemotherapy using tract-based spatial statistics overlaid on the International Consortium of Brain Mapping DTI-81 atlas. All of the children underwent formal neurodevelopmental assessment at the two study time points. RESULTS: Whole-brain DTI analysis showed significant changes between the two time points, affecting several white matter tracts. The tracts demonstrated longitudinal changes of decreasing mean and radial diffusivity. The neurodevelopment of the children was near compatible for age at the end of ALL treatment. CONCLUSION: The quantification of white matter tracts changes in children undergoing chemotherapy showed improving longitudinal values in DTI metrics (stable fractional anisotropy, decreasing mean and radial diffusivity), which are incompatible with deterioration of microstructural integrity in these children.

Novel application of chemical shift gradient echo in- and opposed-phase sequences in 3 T MRI for the detection of H-MRS visible lipids and grading of glioma.

OBJECTIVES: We evaluated the feasibility of using chemical shift gradient-echo (GE) in- and opposed-phase (IOP) imaging to grade glioma. METHODS: A phantom study was performed to investigate the correlation of (1)H MRS-visible lipids with the signal loss ratio (SLR) obtained using IOP imaging. A cross-sectional study approved by the institutional review board was carried out in 22 patients with different glioma grades. The patients underwent scanning using IOP imaging and single-voxel spectroscopy (SVS) using 3T MRI. The brain spectra acquisitions from solid and cystic components were obtained and correlated with the SLR for different grades. RESULTS: The phantom study showed a positive linear correlation between lipid quantification at 0.9 parts per million (ppm) and 1.3 ppm with SLR (r = 0.79-0.99, p < 0.05). In the clinical study, we found that SLR at the solid portions was the best measure for differentiating glioma grades using optimal cut-points of 0.064 and 0.086 with classification probabilities for grade II (SII = 1), grade III (SIII = 0.50) and grade IV (SIV = 0.89). CONCLUSIONS: The results underscore the lipid quantification differences in grades of glioma and provide a more comprehensive characterization by using SLR in chemical shift GE IOP imaging. SLR in IOP sequence demonstrates good performance in glioma grading. KEY POINTS: • Strong correlation was seen between lipid concentration and SLR obtained using IOP • IOP sequence demonstrates significant differences in signal loss within the glioma grades • SLR at solid tumour portions was the best measure for differentiation • This sequence is applicable in a research capacity for glioma staging armamentarium.

Evaluation of Compressed SENSE on Image Quality and Reduction of MRI Acquisition Time: A Clinical Validation Study.

RATIONALE AND OBJECTIVES: To evaluate the effect of compressed SENSE (CS) in clinical settings on scan time reduction and image quality. MATERIALS AND METHODS: Ninety-five magnetic resonance imaging (MRI) scans from different anatomical regions were acquired, consisting of a standard protocol sequence (SS) and sequence accelerated with CS. Anonymized paired sequences were randomly displayed and rated by six blinded subspecialty radiologists. Side-by-side evaluation on perceived sharpness, perceived signal-to-noise-ratio (SNR), lesion conspicuity, and artifacts were compared and scored on a five-point Likert scale, and individual image quality was evaluated on a four-point Likert scale. RESULTS: CS reduced overall scan time by 32% while maintaining acceptable MRI quality for all regions. The largest time savings were seen in the spine (mean = 68 seconds, 44% reduction) followed by the brain (mean = 86 seconds, 37% reduction). The sequence with maximum time savings was intracranial 3D-time-of-flight magnetic resonance angiography (202 seconds, 56% reduction). CS was mildly inferior to SS on perceived sharpness, perceived SNR, and lesion conspicuity (mean scores = 2.32-2.96, P < .001 [1: SS superior; 3: equivalent; 5: CS superior]). CS was equivalent to SS for joint and body scans on overall image quality (CS = 3.02-3.37, SS = 3.04-3.68, P > .05, [1: lowest quality and 4: highest quality]). The overall image quality of CS was slightly less for brain and spine scans (mean CS = 2.79-3.05, mean SS = 3.13-3.43, P = .021) but still diagnostic. Good overall clinical acceptance for CS (88%) was noted with full clinical acceptance for body scans (100%) and high acceptance for other regions (68%-95%). CONCLUSION: CS significantly reduced MR acquisition time while maintaining acceptable image quality. The implementation of CS may improve departmental workflows and enhance patient care.

Neural Fiber Integrity in High- Versus Low-Grade Glioma using Probabilistic Fiber Tracking.

RATIONALE AND OBJECTIVES: Gliomatous tumors are known to affect neural fiber integrity, either by displacement or destruction. The aim of this study is to investigate the integrity and distribution of the white matter tracts within and around the glioma regions using probabilistic fiber tracking. MATERIAL AND METHODS: Forty-two glioma patients were subjected to MRI using a standard tumor protocol with diffusion tensor imaging (DTI). The tumor and peritumor regions were delineated using snake model with reference to structural and diffusion MRI. A preprocessing pipeline of the structural MRI image, DTI data, and tumor regions was implemented. Tractography was performed to delineate the white matter (WM) tracts in the selected tumor regions via probabilistic fiber tracking. DTI indices were investigated through comparative mapping of WM tracts and tumor regions in low-grade gliomas (LGG) and high-grade gliomas (HGG). RESULTS: Significant differences were seen in the planar tensor (Cp) in peritumor regions; mean diffusivity, axial diffusivity and pure isotropic diffusion in solid-enhancing tumor regions; and fractional anisotropy, axial diffusivity, pure anisotropic diffusion (q), total magnitude of diffusion tensor (L), relative anisotropy, Cp and spherical tensor (Cs) in solid nonenhancing tumor regions for affected WM tracts. In most cases of HGG, the WM tracts were not completely destroyed, but found intact inside the tumor. DISCUSSION: Probabilistic fiber tracking revealed the existence and distribution of WM tracts inside tumor core for both LGG and HGG groups. There were more DTI indices in the solid nonenhancing tumor region, which showed significant differences between LGG and HGG.

Lipid Fraction Derived From MRI In- and Opposed-Phase Sequence as a Novel Biomarker for Predicting Survival Outcome of Glioma.

RATIONALE AND PURPOSE: Our study evaluated the capability of magnetic resonance imaging in- and opposed-phase (IOP) derived lipid fraction as a novel prognostic biomarker of survival outcome in glioma. MATERIALS AND METHODS: We analyzed 46 histologically proven glioma (WHO grades II-IV) patients using standard 3T magnetic resonance imaging brain tumor protocol and IOP sequence. Lipid fraction was derived from the IOP sequence signal-loss ratio. The lipid fraction of solid nonenhancing region of glioma was analyzed, using a three-group analysis approach based on volume under surface of receiver-operating characteristics to stratify the prognostic factors into three groups of low, medium, and high lipid fraction. The survival outcome was evaluated, using Kaplan-Meier survival analysis and Cox regression model. RESULTS: Significant differences were seen between the three groups (low, medium, and high lipid fraction groups) stratified by the optimal cut-off point for overall survival (OS) (p ≤ 0.01) and time to progression (p ≤ 0.01) for solid nonenhancing region. The group with high lipid fraction had five times higher risk of poor survival and earlier time to progression compared to the low lipid fraction group. The OS plot stratified by lipid fraction also had a strong correlation with OS plot stratified by WHO grade (R = 0.61, p < 0.01), implying association to underlying histopathological changes. CONCLUSION: The lipid fraction of solid nonenhancing region showed potential for prognostication of glioma. This method will be a useful adjunct in imaging protocol for treatment stratification and as a prognostic tool in glioma patients.

Quantification and visualization of lipid landscape in glioma using in -and opposed-phase imaging.

Objectives: This study maps the lipid distributions based on magnetic resonance imaging (MRI) in-and opposed-phase (IOP) sequence and correlates the findings generated from lipid map to histological grading of glioma. Methods: Forty histologically proven glioma patients underwent a standard MRI tumour protocol with the addition of IOP sequence. The regions of tumour (solid enhancing, solid non-enhancing, and cystic regions) were delineated using snake model (ITK-SNAP) with reference to structural and diffusion MRI images. The lipid distribution map was constructed based on signal loss ratio (SLR) obtained from the IOP imaging. The mean SLR values of the regions were computed and compared across the different glioma grades. Results: The solid enhancing region of glioma had the highest SLR for both Grade II and III. The mean SLR of solid non-enhancing region of tumour demonstrated statistically significant difference between the WHO grades (grades II, III & IV) (mean SLRII = 0.04, mean SLRIII = 0.06, mean SLRIV = 0.08, & p < .01). A strong positive correlation was seen between WHO grades with mean SLR on lipid map of solid non-enhancing (ρ=0.68, p < .01). Conclusion: Lipid quantification via lipid map provides useful information on lipid landscape in tumour heterogeneity characterisation of glioma. This technique adds to the surgical diagnostic yield by identifying biopsy targets. It can also be used as an adjunct grading tool for glioma as well as to provide information about lipidomics landscape in glioma development.

Neurometabolites Alteration in the Acute Phase of Mild Traumatic Brain Injury (mTBI): An In Vivo Proton Magnetic Resonance Spectroscopy (1H-MRS) Study.

RATIONALE AND OBJECTIVES: Magnetic resonance spectroscopy is a noninvasive imaging technique that allows for reliable assessment of microscopic changes in brain cytoarchitecture, neuronal injuries, and neurochemical changes resultant from traumatic insults. We aimed to evaluate the acute alteration of neurometabolites in complicated and uncomplicated mild traumatic brain injury (mTBI) patients in comparison to control subjects using proton magnetic resonance spectroscopy (1H magnetic resonance spectroscopy). MATERIAL AND METHODS: Forty-eight subjects (23 complicated mTBI [cmTBI] patients, 12 uncomplicated mTBI [umTBI] patients, and 13 controls) underwent magnetic resonance imaging scan with additional single voxel spectroscopy sequence. Magnetic resonance imaging scans for patients were done at an average of 10 hours (standard deviation 4.26) post injury. The single voxel spectroscopy adjacent to side of injury and noninjury regions were analysed to obtain absolute concentrations and ratio relative to creatine of the neurometabolites. One-way analysis of variance was performed to compare neurometabolite concentrations of the three groups, and a correlation study was done between the neurometabolite concentration and Glasgow Coma Scale. RESULTS: Significant difference was found in ratio of N-acetylaspartate to creatine (NAA/Cr + PCr) (χ2(2) = 0.22, P < .05) between the groups. The sum of NAA and N-acetylaspartylglutamate (NAAG) also shows significant differences in both the absolute concentration (NAA + NAAG) and ratio to creatine (NAA + NAAG/Cr + PCr) between groups (χ2(2) = 4.03, P < .05and (χ2(2) = 0.79, P < .05)). NAA values were lower in cmTBI and umTBI compared to control group. A moderate weak positive correlation were found between Glasgow Coma Scale with NAA/Cr + PCr (ρ = 0.36, P < .05 and NAA + NAAG/Cr + PCr (ρ = 0.45, P < .05)), whereas a moderate correlation was seen with NAA + NAAG (ρ = 0.38, P < .05). CONCLUSION: Neurometabolite alterations were already apparent at onset of both complicated and uncomplicated traumatic brain injury. The ratio of NAA and NAAG has potential to serve as a biomarker reflecting injury severity in a quantifiable manner as it discriminates between the complicated and uncomplicated cases of mTBI.

Quantitative magnetic resonance imaging and radiogenomic biomarkers for glioma characterisation: a systematic review.

OBJECTIVE:: The diversity of tumour characteristics among glioma patients, even within same tumour grade, is a big challenge for disease outcome prediction. A possible approach for improved radiological imaging could come from combining information obtained at the molecular level. This review assembles recent evidence highlighting the value of using radiogenomic biomarkers to infer the underlying biology of gliomas and its correlation with imaging features. METHODS:: A literature search was done for articles published between 2002 and 2017 on Medline electronic databases. Of 249 titles identified, 38 fulfilled the inclusion criteria, with 14 articles related to quantifiable imaging parameters (heterogeneity, vascularity, diffusion, cell density, infiltrations, perfusion, and metabolite changes) and 24 articles relevant to molecular biomarkers linked to imaging. RESULTS:: Genes found to correlate with various imaging phenotypes were EGFR, MGMT, IDH1, VEGF, PDGF, TP53, and Ki-67. EGFR is the most studied gene related to imaging characteristics in the studies reviewed (41.7%), followed by MGMT (20.8%) and IDH1 (16.7%). A summary of the relationship amongst glioma morphology, gene expressions, imaging characteristics, prognosis and therapeutic response are presented. CONCLUSION:: The use of radiogenomics can provide insights to understanding tumour biology and the underlying molecular pathways. Certain MRI characteristics that show strong correlations with EGFR, MGMT and IDH1 could be used as imaging biomarkers. Knowing the pathways involved in tumour progression and their associated imaging patterns may assist in diagnosis, prognosis and treatment management, while facilitating personalised medicine. ADVANCES IN KNOWLEDGE:: Radiogenomics can offer clinicians better insight into diagnosis, prognosis, and prediction of therapeutic responses of glioma.

Microstructural integrity of white matter tracts amongst older fallers: A DTI study.

OBJECTIVES: This study assesses the whole brain microstructural integrity of white matter tracts (WMT) among older individuals with a history of falls compared to non-fallers. METHODS: 85 participants (43 fallers, 42 non-fallers) were evaluated with conventional MRI and diffusion tensor imaging (DTI) sequences of the brain. DTI metrics were obtained from selected WMT using tract-based spatial statistics (TBSS) method. This was followed by binary logistic regression to investigate the clinical variables that could act as confounding elements on the outcomes. The TBSS analysis was then repeated, but this time including all significant predictor variables from the regression analysis as TBSS covariates. RESULTS: The mean diffusivity (MD) and axial diffusivity (AD) and to a lesser extent radial diffusivity (RD) values of the projection fibers and commissural bundles were significantly different in fallers (p < 0.05) compared to non-fallers. However, the final logistic regression model obtained showed that only functional reach, white matter lesion volume, hypertension and orthostatic hypotension demonstrated statistical significant differences between fallers and non-fallers. No significant differences were found in the DTI metrics when taking into account age and the four variables as covariates in the repeated analysis. CONCLUSION: This DTI study of 85 subjects, do not support DTI metrics as a singular factor that contributes independently to the fall outcomes. Other clinical and imaging factors have to be taken into account.