Quantitative diffusion-weighted MRI response assessment in rhabdomyosarcoma: an international retrospective study on behalf of the European paediatric Soft tissue sarcoma Study Group Imaging Committee.

OBJECTIVE: To investigate the feasibility of diffusion-weighted magnetic resonance imaging (DW-MRI) as a predictive imaging marker after neoadjuvant chemotherapy in patients with rhabdomyosarcoma. MATERIAL AND METHODS: We performed a multicenter retrospective study including pediatric, adolescent and young adult patients with rhabdomyosarcoma, Intergroup Rhabdomyosarcoma Study group III/IV, treated according to the European paediatric Soft tissue sarcoma Study Group (EpSSG) RMS2005 or MTS2008 studies. DW-MRI was performed according to institutional protocols. We performed two-dimensional single-slice tumor delineation. Areas of necrosis or hemorrhage were delineated to be excluded in the primary analysis. Mean, median and 5th and 95th apparent diffusion coefficient (ADC) were extracted. RESULTS: Of 134 included patients, 82 had measurable tumor at diagnosis and response and DW-MRI scans of adequate quality and were included in the analysis. Technical heterogeneity in scan acquisition protocols and scanners was observed. Mean ADC at diagnosis was 1.1 (95% confidence interval [CI]: 1.1-1.2) (all ADC expressed in * 10-3 mm2/s), versus 1.6 (1.5-1.6) at response assessment. The 5th percentile ADC was 0.8 (0.7-0.9) at diagnosis and 1.1 (1.0-1.2) at response. Absolute change in mean ADC after neoadjuvant chemotherapy was 0.4 (0.3-0.5). Exploratory analyses for association between ADC and clinical parameters showed a significant difference in mean ADC at diagnosis for alveolar versus embryonal histology. Landmark analysis at nine weeks after the date of diagnosis showed no significant association (hazard ratio 1.3 [0.6-3.2]) between the mean ADC change and event-free survival. CONCLUSION: A significant change in the 5th percentile and the mean ADC after chemotherapy was observed. Strong heterogeneity was identified in DW-MRI acquisition protocols between centers and in individual patients.

Methodological considerations on segmenting rhabdomyosarcoma with diffusion-weighted imaging-What can we do better?

PURPOSE: Diffusion-weighted MRI is a promising technique to monitor response to treatment in pediatric rhabdomyosarcoma. However, its validation in clinical practice remains challenging. This study aims to investigate how the tumor segmentation strategy can affect the apparent diffusion coefficient (ADC) measured in pediatric rhabdomyosarcoma. MATERIALS AND METHODS: A literature review was performed in PubMed using search terms relating to MRI and sarcomas to identify commonly applied segmentation strategies. Seventy-six articles were included, and their presented segmentation methods were evaluated. Commonly reported segmentation strategies were then evaluated on diffusion-weighted imaging of five pediatric rhabdomyosarcoma patients to assess their impact on ADC. RESULTS: We found that studies applied different segmentation strategies to define the shape of the region of interest (ROI)(outline 60%, circular ROI 27%), to define the segmentation volume (2D 44%, multislice 9%, 3D 21%), and to define the segmentation area (excludes edge 7%, excludes other region 19%, specific area 27%, whole tumor 48%). In addition, details of the segmentation strategy are often unreported. When implementing and comparing these strategies on in-house data, we found that excluding necrotic, cystic, and hemorrhagic areas from segmentations resulted in on average 5.6% lower mean ADC. Additionally, the slice location used in 2D segmentation methods could affect ADC by as much as 66%. CONCLUSION: Diffusion-weighted MRI studies in pediatric sarcoma currently employ a variety of segmentation methods. Our study shows that different segmentation strategies can result in vastly different ADC measurements, highlighting the importance to further investigate and standardize segmentation.

Tracking the Corticospinal Tract in Patients With High-Grade Glioma: Clinical Evaluation of Multi-Level Fiber Tracking and Comparison to Conventional Deterministic Approaches.

While the diagnosis of high-grade glioma (HGG) is still associated with a considerably poor prognosis, neurosurgical tumor resection provides an opportunity for prolonged survival and improved quality of life for affected patients. However, successful tumor resection is dependent on a proper surgical planning to avoid surgery-induced functional deficits whilst achieving a maximum extent of resection (EOR). With diffusion magnetic resonance imaging (MRI) providing insight into individual white matter neuroanatomy, the challenge remains to disentangle that information as correctly and as completely as possible. In particular, due to the lack of sensitivity and accuracy, the clinical value of widely used diffusion tensor imaging (DTI)-based tractography is increasingly questioned. We evaluated whether the recently developed multi-level fiber tracking (MLFT) technique can improve tractography of the corticospinal tract (CST) in patients with motor-eloquent HGGs. Forty patients with therapy-naïve HGGs (mean age: 62.6 ± 13.4 years, 57.5% males) and preoperative diffusion MRI [repetition time (TR)/echo time (TE): 5000/78 ms, voxel size: 2x2x2 mm3, one volume at b=0 s/mm2, 32 volumes at b=1000 s/mm2] underwent reconstruction of the CST of the tumor-affected and unaffected hemispheres using MLFT in addition to deterministic DTI-based and deterministic constrained spherical deconvolution (CSD)-based fiber tractography. The brain stem was used as a seeding region, with a motor cortex mask serving as a target region for MLFT and a region of interest (ROI) for the other two algorithms. Application of the MLFT method substantially improved bundle reconstruction, leading to CST bundles with higher radial extent compared to the two other algorithms (delineation of CST fanning with a wider range; median radial extent for tumor-affected vs. unaffected hemisphere - DTI: 19.46° vs. 18.99°, p=0.8931; CSD: 30.54° vs. 27.63°, p=0.0546; MLFT: 81.17° vs. 74.59°, p=0.0134). In addition, reconstructions by MLFT and CSD-based tractography nearly completely included respective bundles derived from DTI-based tractography, which was however favorable for MLFT compared to CSD-based tractography (median coverage of the DTI-based CST for affected vs. unaffected hemispheres - CSD: 68.16% vs. 77.59%, p=0.0075; MLFT: 93.09% vs. 95.49%; p=0.0046). Thus, a more complete picture of the CST in patients with motor-eloquent HGGs might be achieved based on routinely acquired diffusion MRI data using MLFT.

Dose-dependent volume loss in subcortical deep grey matter structures after cranial radiotherapy.

BACKGROUND AND PURPOSE: The relation between radiotherapy (RT) dose to the brain and morphological changes in healthy tissue has seen recent increased interest. There already is evidence for changes in the cerebral cortex and white matter, as well as selected subcortical grey matter (GM) structures. We studied this relation in all deep GM structures, to help understand the aetiology of post-RT neurocognitive symptoms. MATERIALS AND METHODS: We selected 31 patients treated with RT for grade II-IV glioma. Pre-RT and 1 year post-RT 3D T1-weighted MRIs were automatically segmented, and the changes in volume of the following structures were assessed: amygdala, nucleus accumbens, caudate nucleus, hippocampus, globus pallidus, putamen, and thalamus. The volumetric changes were related to the mean RT dose received by each structure. Hippocampal volumes were entered into a population-based nomogram to estimate hippocampal age. RESULTS: A significant relation between RT dose and volume loss was seen in all examined structures, except the caudate nucleus. The volume loss rates ranged from 0.16 to 1.37%/Gy, corresponding to 4.9-41.2% per 30 Gy. Hippocampal age, as derived from the nomogram, was seen to increase by a median of 11 years. CONCLUSION: Almost all subcortical GM structures are susceptible to radiation-induced volume loss, with higher volume loss being observed with increasing dose. Volume loss of these structures is associated with neurological deterioration, including cognitive decline, in neurodegenerative diseases. To support a causal relationship between radiation-induced deep GM loss and neurocognitive functioning in glioma patients, future studies are needed that directly correlate volumetrics to clinical outcomes.

Effect of radiation therapy on cerebral cortical thickness in glioma patients: Treatment-induced thinning of the healthy cortex.

BACKGROUND: With overall survival of brain tumors improving, radiation induced brain injury is becoming an increasing issue. One of the effects of radiation therapy (RT) is thinning of the cerebral cortex, which could be one of the factors contributing to cognitive impairments after treatment. In healthy brain, cortex thickness varies between 1 and 4.5 mm. In this study, we assess the effect of RT on the thickness of the cerebral cortex and relate the changes to the local dose. METHODS: We identified 28 glioma patients with optimal scan quality. Clinical CTs and MRIs at baseline and 1 year post-RT were collected and coregistered. The scans were processed via an automated image processing pipeline, which enabled measuring changes of the cortical thickness, which were related to local dose. RESULTS: Three areas were identified where significant dose-dependent thinning occurred, with thinning rates of 5, 6, and 26 µm/Gy after 1 year, which corresponds to losses of 5.4%, 7.2%, and 21.6% per 30 Gy per year. The first area was largely located in the right inferior parietal, supramarginal, and superior parietal regions, the second in the right posterior cingulate and paracentral regions, and the third almost completely in the right lateral orbital frontal region. CONCLUSIONS: We have identified three areas susceptible to dose-dependent cortical thinning after radiation therapy. Should future prospective studies conclude that irradiation of these areas lead to cognitive decline, they need to be spared in order to prevent this debilitating consequence of treatment.

Data-Driven Identification of the Regions of Interest for Fiber Tracking in Patients with Brain Tumors.

BACKGROUND: We investigated the added value of combining information from direction-encoded color (DEC) maps with high-resolution structural magnetic resonance imaging scans (T1-weighted images [T1WIs]) to improve the identification of regions of interest (ROIs) for fiber tracking during preoperative planning for patients with brain tumors. METHODS: The dataset included 42 patients with gliomas and 10 healthy subjects from the Human Connectome Project. For identification of the ROIs, we combined the structural information from high-resolution T1WIs and the directional information from DEC maps. To test our hypothesis, we examined the interrater and intrarater agreement. RESULTS: We identified specific ROIs to extract the main white matter bundles. The directional information from the DEC maps combined with the T1WIs (T1WI-DEC maps) had significantly facilitated ROI identification in patients with brain tumors, especially patients in whom the tracts had been displaced by the mass effect of the tumor. Fiber tracking using the combined T1WI-DEC maps showed significantly greater inter- and intrarater agreement compared with using either T1WI or DEC maps alone. CONCLUSION: Combining the information from diffusion-derived color-encoded maps with high-resolution anatomical details from structural imaging (T1WI-DEC map), especially in patients with brain tumors, could be useful for accurate identification of the ROIs.

Perinatal thalamic injury: MRI predictors of electrical status epilepticus in sleep and long-term neurodevelopment.

OBJECTIVE: Perinatal thalamic injury is associated with epilepsy with electrical status epilepticus in sleep (ESES). The aim of this study was to prospectively quantify the risk of ESES and to assess neuroimaging predictors of neurodevelopment. METHODS: We included patients with perinatal thalamic injury. MRI scans were obtained in the neonatal period, around three months of age and during childhood. Thalamic and total brain volumes were obtained from the three months MRI. Diffusion characteristics were assessed. Sleep EEGs distinguished patients into ESES (spike-wave index (SWI) >85%), ESES-spectrum (SWI 50-85%) or no ESES (SWI < 50%). Serial Intelligence Quotient (IQ)/Developmental Quotient (DQ) scores were obtained during follow-up. Imaging and EEG findings were correlated to neurodevelopmental outcome. RESULTS: Thirty patients were included. Mean thalamic volume at three months was 8.11 (±1.67) ml and mean total brain volume 526.45 (±88.99) ml. In the prospective cohort (n = 23) 19 patients (83%) developed ESES (-spectrum) abnormalities after a mean follow-up of 96 months. In the univariate analysis, larger thalamic volume, larger total brain volume and lower SWI correlated with higher mean IQ/DQ after 2 years (Pearson's r = 0.74, p = 0.001; Pearson's r = 0.64, p = 0.005; and Spearman's rho -0.44, p = 0.03). In a multivariable mixed model analysis, thalamic volume was a significant predictor of IQ/DQ (coefficient 9.60 [p < 0.001], i.e., corrected for total brain volume and SWI and accounting for repeated measures within patients, a 1 ml higher thalamic volume was associated with a 9.6 points higher IQ). Diffusion characteristics during childhood correlated with IQ/DQ after 2 years. SIGNIFICANCE: Perinatal thalamic injury is followed by electrical status epilepticus in sleep in the majority of patients. Thalamic volume and diffusion characteristics correlate to neurodevelopmental outcome.

Changes in cortical thickness and volume after cranial radiation treatment: A systematic review.

Cognitive decline has a clear impact on quality of life in patients who have received cranial radiation treatment. The pathophysiological process is most likely multifactorial, with a possible role for decreased cortical thickness and volume. As radiotherapy treatment systems are becoming more sophisticated, precise sparing of vulnerable regions and tissue is possible. This allows radiation oncologists to make treatment more patient-tailored. A systematic search was performed to collect and review all available evidence regarding the effect of cranial radiation treatment on cortical thickness and volume. We searched the Pubmed, Embase and Cochrane databases, with an additional reference check in the Scopus database. Studies that examined cortical changes on MRI within patients as well as between treated and non-treated patients were included. The quality of the studies was assessed with a checklist specially designed for this review. No meta-analysis was performed due to the lack of randomised trials. Out of 1915 publications twenty-one papers were selected, of which fifteen observed cortical changes after radiation therapy. Two papers reported radiation-dependent decrease in cortical thickness within patients one year after radiation treatment, suggesting a clear relation between the two. However, study quality was considered mostly suboptimal, and there was great inhomogeneity between the included studies. This means that, although there has been increasing interest in the effects of radiation treatment on cortex morphology, no reliable conclusion can be drawn based on the currently available evidence. This calls for more research, preferably with a sufficiently large patient population, and adequate methodology.

Diffusion MRI fiber tractography of the brain.

The ability of fiber tractography to delineate non-invasively the white matter fiber pathways of the brain raises possibilities for clinical applications and offers enormous potential for neuroscience. In the last decade, fiber tracking has become the method of choice to investigate quantitative MRI parameters in specific bundles of white matter. For neurosurgeons, it is quickly becoming an invaluable tool for the planning of surgery, allowing for visualization and localization of important white matter pathways before and even during surgery. Fiber tracking has also claimed a central role in the field of "connectomics," a technique that builds and studies comprehensive maps of the complex network of connections within the brain, and to which significant resources have been allocated worldwide. Despite its unique abilities and exciting applications, fiber tracking is not without controversy, in particular when it comes to its interpretation. As neuroscientists are eager to study the brain's connectivity, the quantification of tractography-derived "connection strengths" between distant brain regions is becoming increasingly popular. However, this practice is often frowned upon by fiber-tracking experts. In light of this controversy, this paper provides an overview of the key concepts of tractography, the technical considerations at play, and the different types of tractography algorithm, as well as the common misconceptions and mistakes that surround them. We also highlight the ongoing challenges related to fiber tracking. While recent methodological developments have vastly increased the biological accuracy of fiber tractograms, one should be aware that, even with state-of-the-art techniques, many issues that severely bias the resulting structural "connectomes" remain unresolved.

Recovery from chemotherapy-induced white matter changes in young breast cancer survivors?

In a previous longitudinal diffusion tensor imaging (DTI) study, we observed cerebral white matter (WM) alterations (reduced fractional anisotropy (FA)) related to decreased cognitive performance 3-5 months after chemotherapy-treatment (t2) when compared to baseline (t1) (Deprez et al. in Journal of Clinical Oncology: Official Journal of the American Society of Clinical Oncology, 30(3), 274-281. doi:10.1200/JCO.2011.36.8571, 2012). The current study investigates the evolution and the nature of these previously observed microstructural changes. Twenty-five young women with early-stage breast cancer who received chemotherapy treatment (C+), 14 who did not receive chemotherapy (C-) and 15 healthy controls (HC) previously studied, underwent reassessment 3-4 years after treatment (t3). We assessed (1) longitudinal changes of cognitive performance and FA and (2) cross-sectional group differences in myelin-water-imaging and multishell diffusion MRI metrics at t3. MRI metrics were assessed on a voxel-by-voxel basis and in regions-of-interest (ROI) in which previous WM injury was detected. Longitudinal results: Mixed-effects modeling revealed significant group-time interactions for verbal memory and processing speed (p < 0.05) reflecting regained performance in the C+ group at t3. Furthermore, in chemotherapy-treated patients, FA returned to baseline levels at t3 in all ROIs (p < 0.002), whereas no FA changes were seen in controls. Additionally, FA increase from t2 to t3 correlated with time since treatment in two of the four regions (r = 0.40, p < 0.05). Cross-sectional results: Advanced diffusion MRI and myelin-water imaging metrics in the ROIs did not differ between groups. Similarly, no whole-brain voxelwise differences were detected. Initial WM alterations and reduced cognitive performance following chemotherapy-treatment were found to recover in a group of young breast cancer survivors three to four years after treatment.

Changes in Brain Structural Networks and Cognitive Functions in Testicular Cancer Patients Receiving Cisplatin-Based Chemotherapy.

Background: Cisplatin-based chemotherapy may have neurotoxic effects within the central nervous system. The aims of this study were 1) to longitudinally investigate the impact of cisplatin-based chemotherapy on whole-brain networks in testicular cancer patients undergoing treatment and 2) to explore whether possible changes are related to decline in cognitive functioning. Methods: Sixty-four newly orchiectomized TC patients underwent structural magnetic resonance imaging (T1-weighted and diffusion-weighted imaging) and cognitive testing at baseline prior to further treatment and again at a six-month follow-up. At follow-up, 22 participants had received cisplatin-based chemotherapy (CT) while 42 were in active surveillance (S). Brain structural networks were constructed for each participant, and network properties were investigated using graph theory and longitudinally compared across groups. Cognitive functioning was evaluated using standardized neuropsychological tests. All statistical tests were two-sided. Results: Compared with the S group, the CT group demonstrated altered global and local brain network properties from baseline to follow-up as evidenced by decreases in important brain network properties such as small-worldness (P = .04), network clustering (P = .04), and local efficiency (P = .02). In the CT group, poorer overall cognitive performance was associated with decreased small-worldness (r = -0.46, P = .04) and local efficiency (r = -0.51, P = .02), and verbal fluency was associated with decreased local efficiency (r = -0.55, P = .008). Conclusions: Brain structural networks may be disrupted following treatment with cisplatin-based chemotherapy. Impaired brain networks may underlie poorer performance over time on both specific and nonspecific cognitive functions in patients undergoing chemotherapy. To the best of our knowledge, this is the first study to longitudinally investigate changes in structural brain networks in a cancer population, providing novel insights regarding the neurobiological mechanisms of cancer-related cognitive impairment.

Hierarchical non-negative matrix factorization to characterize brain tumor heterogeneity using multi-parametric MRI.

Tissue characterization in brain tumors and, in particular, in high-grade gliomas is challenging as a result of the co-existence of several intra-tumoral tissue types within the same region and the high spatial heterogeneity. This study presents a method for the detection of the relevant tumor substructures (i.e. viable tumor, necrosis and edema), which could be of added value for the diagnosis, treatment planning and follow-up of individual patients. Twenty-four patients with glioma [10 low-grade gliomas (LGGs), 14 high-grade gliomas (HGGs)] underwent a multi-parametric MRI (MP-MRI) scheme, including conventional MRI (cMRI), perfusion-weighted imaging (PWI), diffusion kurtosis imaging (DKI) and short-TE (1)H MRSI. MP-MRI parameters were derived: T2, T1 + contrast, fluid-attenuated inversion recovery (FLAIR), relative cerebral blood volume (rCBV), mean diffusivity (MD), fractional anisotropy (FA), mean kurtosis (MK) and the principal metabolites lipids (Lip), lactate (Lac), N-acetyl-aspartate (NAA), total choline (Cho), etc. Hierarchical non-negative matrix factorization (hNMF) was applied to the MP-MRI parameters, providing tissue characterization on a patient-by-patient and voxel-by-voxel basis. Tissue-specific patterns were obtained and the spatial distribution of each tissue type was visualized by means of abundance maps. Dice scores were calculated by comparing tissue segmentation derived from hNMF with the manual segmentation by a radiologist. Correlation coefficients were calculated between each pathologic tissue source and the average feature vector within the corresponding tissue region. For the patients with HGG, mean Dice scores of 78%, 85% and 83% were obtained for viable tumor, the tumor core and the complete tumor region. The mean correlation coefficients were 0.91 for tumor, 0.97 for necrosis and 0.96 for edema. For the patients with LGG, a mean Dice score of 85% and mean correlation coefficient of 0.95 were found for the tumor region. hNMF was also applied to reduced MRI datasets, showing the added value of individual MRI modalities.

Dynamics of the connectome in Huntington's disease: A longitudinal diffusion MRI study.

OBJECTIVES: To longitudinally investigate the connectome in different stages of Huntington's disease (HD) by applying graph theoretical analysis to diffusion MRI data. EXPERIMENTAL DESIGN: We constructed weighted structural networks and calculated their topological properties. Twenty-two premanifest (preHD), 10 early manifest HD and 24 healthy controls completed baseline and 2 year follow-up scans. We stratified the preHD group based on their predicted years to disease onset into a far (preHD-A) and near (preHD-B) to disease onset group. We collected clinical and behavioural measures per assessment time point. PRINCIPLE OBSERVATIONS: We found a significant reduction over time in nodal betweenness centrality both in the early manifest HD and preHD-B groups as compared to the preHD-A and control groups, suggesting a decrease of importance of specific nodes to overall network organization in these groups (FDR adjusted ps < 0.05). Additionally, we found a significant longitudinal decrease of the clustering coefficient in preHD when compared to healthy controls (FDR adjusted p < 0.05), which can be interpreted as a reduced capacity for internodal information processing at the local level. Furthermore, we demonstrated dynamic changes to hub-status loss and gain both in preHD and early manifest HD. Finally, we found significant cross-sectional as well as longitudinal relationships between graph metrics and clinical and neurocognitive measures. CONCLUSIONS: This study demonstrates divergent longitudinal changes to the connectome in (pre) HD compared to healthy controls. This provides novel insights into structural correlates associated with clinical and cognitive functions in HD and possible compensatory mechanisms at play in preHD.

Evaluating contextual processing in diffusion MRI: application to optic radiation reconstruction for epilepsy surgery.

Diffusion MRI and tractography allow for investigation of the architectural configuration of white matter in vivo, offering new avenues for applications like presurgical planning. Despite the promising outlook, there are many pitfalls that complicate its use for (clinical) application. Amongst these are inaccuracies in the geometry of the diffusion profiles on which tractography is based, and poor alignment with neighboring profiles. Recently developed contextual processing techniques, including enhancement and well-posed geometric sharpening, have shown to result in sharper and better aligned diffusion profiles. However, the research that has been conducted up to now is mainly of theoretical nature, and so far these techniques have only been evaluated by visual inspection of the diffusion profiles. In this work, the method is evaluated in a clinically relevant application: the reconstruction of the optic radiation for epilepsy surgery. For this evaluation we have developed a framework in which we incorporate a novel scoring procedure for individual pathways. We demonstrate that, using enhancement and sharpening, the extraction of an anatomically plausible reconstruction of the optic radiation from a large amount of probabilistic pathways is greatly improved in three healthy controls, where currently used methods fail to do so. Furthermore, challenging reconstructions of the optic radiation in three epilepsy surgery candidates with extensive brain lesions demonstrate that it is beneficial to integrate these methods in surgical planning.

Characterizing the microstructural basis of "unidentified bright objects" in neurofibromatosis type 1: A combined in vivo multicomponent T2 relaxation and multi-shell diffusion MRI analysis.

INTRODUCTION: The histopathological basis of "unidentified bright objects" (UBOs) (hyperintense regions seen on T2-weighted magnetic resonance (MR) brain scans in neurofibromatosis-1 (NF1)) remains unclear. New in vivo MRI-based techniques (multi-exponential T2 relaxation (MET2) and diffusion MR imaging (dMRI)) provide measures relating to microstructural change. We combined these methods and present previously unreported data on in vivo UBO microstructure in NF1. METHODS: 3-Tesla dMRI data were acquired on 17 NF1 patients, covering 30 white matter UBOs. Diffusion tensor, kurtosis and neurite orientation and dispersion density imaging parameters were calculated within UBO sites and in contralateral normal appearing white matter (cNAWM). Analysis of MET2 parameters was performed on 24 UBO-cNAWM pairs. RESULTS: No significant alterations in the myelin water fraction and intra- and extracellular (IE) water fraction were found. Mean T2 time of IE water was significantly higher in UBOs. UBOs furthermore showed increased axial, radial and mean diffusivity, and decreased fractional anisotropy, mean kurtosis and neurite density index compared to cNAWM. Neurite orientation dispersion and isotropic fluid fraction were unaltered. CONCLUSION: Our results suggest that demyelination and axonal degeneration are unlikely to be present in UBOs, which appear to be mainly caused by a shift towards a higher T2-value of the intra- and extracellular water pool. This may arise from altered microstructural compartmentalization, and an increase in 'extracellular-like', intracellular water, possibly due to intramyelinic edema. These findings confirm the added value of combining dMRI and MET2 to characterize the microstructural basis of T2 hyperintensities in vivo.

Integrating diffusion kurtosis imaging, dynamic susceptibility-weighted contrast-enhanced MRI, and short echo time chemical shift imaging for grading gliomas.

BACKGROUND: We assessed the diagnostic accuracy of diffusion kurtosis imaging (DKI), dynamic susceptibility-weighted contrast-enhanced (DSC) MRI, and short echo time chemical shift imaging (CSI) for grading gliomas. METHODS: In this prospective study, 35 patients with cerebral gliomas underwent DKI, DSC, and CSI on a 3 T MR scanner. Diffusion parameters were mean diffusivity (MD), fractional anisotropy, and mean kurtosis (MK). Perfusion parameters were mean relative regional cerebral blood volume (rrCBV), mean relative regional cerebral blood flow (rrCBF), mean transit time, and relative decrease ratio (rDR). The diffusion and perfusion parameters along with 12 CSI metabolite ratios were compared among 22 high-grade gliomas and 14 low-grade gliomas (Mann-Whitney U-test, P < .05). Classification accuracy was determined with a linear discriminant analysis for each MR modality independently. Furthermore, the performance of a multimodal analysis is reported, using a decision-tree rule combining the statistically significant DKI, DSC-MRI, and CSI parameters with the lowest P-value. The proposed classifiers were validated on a set of subsequently acquired data from 19 clinical patients. RESULTS: Statistically significant differences among tumor grades were shown for MK, MD, mean rrCBV, mean rrCBF, rDR, lipids over total choline, lipids over creatine, sum of myo-inositol, and sum of creatine. DSC-MRI proved to be the modality with the best performance when comparing modalities individually, while the multimodal decision tree proved to be most accurate in predicting tumor grade, with a performance of 86%. CONCLUSIONS: Combining information from DKI, DSC-MRI, and CSI increases diagnostic accuracy to differentiate low- from high-grade gliomas, possibly providing diagnosis for the individual patient.

Diffusion tensor MRI of chemotherapy-induced cognitive impairment in non-CNS cancer patients: a review.

Patients with non-central nervous system cancers often experience subtle cognitive deficits after treatment with cytotoxic agents. Therapy-induced structural changes to the brain could be one of the possible causes underlying these reported cognitive deficits. In this review, we evaluate the use of diffusion tensor imaging (DTI) for assessing possible therapy-induced changes in the microstructure of the cerebral white matter (WM) and provide a critical overview of the published DTI research on therapy-induced cognitive impairment. Both cross-sectional and longitudinal DTI studies have demonstrated abnormal microstructural properties in WM regions involved in cognition. These findings correlated with cognitive performance, suggesting that there is a link between reduced "WM integrity" and chemotherapy-induced impaired cognition. In this paper, we will also introduce the basics of diffusion tensor imaging and how it can be applied to evaluate effects of therapy on structural changes in cerebral WM. The review concludes with considerations and discussion regarding DTI data interpretation and possible future directions for investigating therapy-induced WM changes in cancer patients. This review article is part of a Special Issue entitled: Neuroimaging Studies of Cancer and Cancer Treatment.

Longitudinal assessment of chemotherapy-induced structural changes in cerebral white matter and its correlation with impaired cognitive functioning.

PURPOSE: To uncover the neural substrate of cognitive impairment related to adjuvant chemotherapy, we studied cerebral white matter (WM) integrity before and after chemotherapy by using magnetic resonance diffusion tensor imaging (DTI) in combination with detailed cognitive assessment. PATIENTS AND METHODS: Thirty-four young premenopausal women with early-stage breast cancer who were exposed to chemotherapy underwent neuropsychologic testing and DTI before the start of chemotherapy (t1) and 3 to 4 months after treatment (t2). Sixteen patients not exposed to chemotherapy and 19 age-matched healthy controls underwent the same assessment at matched intervals. In all groups, we used paired t tests to study changes in neuropsychologic test scores and whole-brain voxel-based paired t tests to study changes in WM fractional anisotropy (FA; a DTI measure that reflects WM tissue organization), with depression scores and intelligence quotient as included covariates. We correlated changes of neuropsychologic test scores with the mean change of FA for regions that survived the paired t tests in patients treated with chemotherapy. RESULTS: In contrast to controls, the chemotherapy-treated group performed significantly worse on attention tests, psychomotor speed, and memory at t2 compared with t1 (P < .05). In the chemotherapy-treated group, we found significant decreases of FA in frontal, parietal, and occipital WM tracts after treatment (familywise error P < .05), whereas for both control groups, FA values were the same between t1 and t2. Furthermore, performance changes in attention and verbal memory correlated with mean regional FA changes in chemotherapy-treated patients (P < .05). CONCLUSION: We report evidence of longitudinal changes in cognitive functioning and cerebral WM integrity after chemotherapy as well as an association between both.

Chemotherapy-induced structural changes in cerebral white matter and its correlation with impaired cognitive functioning in breast cancer patients.

A subgroup of patients with breast cancer suffers from mild cognitive impairment after chemotherapy. To uncover the neural substrate of these mental complaints, we examined cerebral white matter (WM) integrity after chemotherapy using magnetic resonance diffusion tensor imaging (DTI) in combination with detailed cognitive assessment. Postchemotherapy breast cancer patients (n = 17) and matched healthy controls (n = 18) were recruited for DTI and neuropsychological testing, including the self-report cognitive failure questionnaire (CFQ). Differences in DTI WM integrity parameters [fractional anisotropy (FA) and mean diffusivity (MD)] between patients and healthy controls were assessed using a voxel-based two-sample-t-test. In comparison with healthy controls, the patient group demonstrated decreased FA in frontal and temporal WM tracts and increased MD in frontal WM. These differences were also confirmed when comparing this patient group with an additional control group of nonchemotherapy-treated breast cancer patients (n = 10). To address the heterogeneity observed in cognitive function after chemotherapy, we performed a voxel-based correlation analysis between FA values and individual neuropsychological test scores. Significant correlations of FA with neuropsychological tests covering the domain of attention and processing/psychomotor speed were found in temporal and parietal WM tracts. Furthermore, CFQ scores correlated negatively in frontal and parietal WM. These studies show that chemotherapy seems to affect WM integrity and that parameters derived from DTI have the required sensitivity to quantify neural changes related to chemotherapy-induced mild cognitive impairment.