Diffusion MR Imaging of the Brain in Patients with Cancer

Neuroimaging Biomarkers and Neurocognitive Outcomes in Pediatric Medulloblastoma Patients: a Systematic Review

Medulloblastoma is a malign posterior fossa brain tumor, mostly occurring in childhood. The CNS-directed chemoradiotherapy treatment can be very harmful to the developing brain and functional outcomes of these patients. However, what the underlying neurotoxic mechanisms are remain inconclusive. Hence, this review summarizes the existing literature on the association between advanced neuroimaging and neurocognitive changes in patients that were treated for pediatric medulloblastoma. The PubMed/Medline database was extensively screened for studies investigating the link between cognitive outcomes and multimodal magnetic resonance (MR) imaging in childhood medulloblastoma survivors. A behavioral meta-analysis was performed on the available IQ scores. A total of 649 studies were screened, of which 22 studies were included. Based on this literature review, we conclude medulloblastoma patients to be at risk for white matter volume loss, more frequent white matter lesions, and changes in white matter microstructure. Such microstructural alterations were associated with lower IQ, which reached the clinical cut-off in survivors across studies. Using functional MR scans, changes in activity were observed in cerebellar areas, associated with working memory and processing speed. Finally, cerebral microbleeds were encountered more often, but these were not associated with cognitive outcomes. Regarding intervention studies, computerized cognitive training was associated with changes in prefrontal and cerebellar activation and physical training might result in microstructural and cortical alterations. Hence, to better define the neural targets for interventions in pediatric medulloblastoma patients, this review suggests working towards neuroimaging-based predictions of cognitive outcomes. To reach this goal, large multimodal prospective imaging studies are highly recommended.

MRSI-based molecular imaging of therapy response to temozolomide in preclinical glioblastoma using source analysis

Characterization of glioblastoma (GB) response to treatment is a key factor for improving patients' survival and prognosis. MRI and magnetic resonance spectroscopic imaging (MRSI) provide morphologic and metabolic profiles of GB but usually fail to produce unequivocal biomarkers of response. The purpose of this work is to provide proof of concept of the ability of a semi-supervised signal source extraction methodology to produce images with robust recognition of response to temozolomide (TMZ) in a preclinical GB model. A total of 38 female C57BL/6 mice were used in this study. The semi-supervised methodology extracted the required sources from a training set consisting of MRSI grids from eight GL261 GBs treated with TMZ, and six control untreated GBs. Three different sources (normal brain parenchyma, actively proliferating GB and GB responding to treatment) were extracted and used for calculating nosologic maps representing the spatial response to treatment. These results were validated with an independent test set (7 control and 17 treated cases) and correlated with histopathology. Major differences between the responder and non-responder sources were mainly related to the resonances of mobile lipids (MLs) and polyunsaturated fatty acids in MLs (0.9, 1.3 and 2.8 ppm). Responding tumors showed significantly lower mitotic (3.3 ± 2.9 versus 14.1 ± 4.2 mitoses/field) and proliferation rates (29.8 ± 10.3 versus 57.8 ± 5.4%) than control untreated cases. The methodology described in this work is able to produce nosological images of response to TMZ in GL261 preclinical GBs and suitably correlates with the histopathological analysis of tumors. A similar strategy could be devised for monitoring response to treatment in patients. Copyright © 2016 John Wiley & Sons, Ltd.

Diagnosis and New Treatment Modalities for Glioblastoma: Do They Improve Patient Survival?

Central nervous system (CNS) malignances include tumors of the brain and spinal cord. Taking into account the cell type where they originate from, there are almost 120 different types of CNS tumors. Benign tumors are not aggressive and normally do not invade other organs; however, they require surgical removal before they alter the surrounding brain functions. Primary malignant brain tumors commonly include astrocytomas, oligodendrogliomas, and ependimomas, where astrocytomas represent around 76%. The World Health Organization (WHO) has defined four histological grades of astrocytomas that range from the less aggressive tumors (grade I) to highly malignant tumors (grade IV). These grade IV tumors, also called glioblastoma (GBM), are the most aggressive of the primary malignant brain tumors. Patients with GBM have a median survival of 12 to 15 months. Current treatment for GBM includes surgery, radiotherapy and chemotherapy. Although there have been some advances in diagnosis and treatment, there is still no optimal treatment available for GBMs. In this review, we will discuss the approaches for GBM diagnosis and treatment, with a special emphasis to post-treatment imaging, and whether novel targeted therapies have impacted the survival of GBM patients. In addition, we will discuss clinical trials and the future of GBM diagnosis and treatment.

The role of diffusion and perfusion weighted imaging in the differential diagnosis of cerebral tumors: a review and future perspectives

The role of conventional Magnetic Resonance Imaging (MRI) in the detection of cerebral tumors has been well established. However its excellent soft tissue visualization and variety of imaging sequences are in many cases non-specific for the assessment of brain tumor grading. Hence, advanced MRI techniques, like Diffusion-Weighted Imaging (DWI), Diffusion Tensor Imaging (DTI) and Dynamic-Susceptibility Contrast Imaging (DSCI), which are based on different contrast principles, have been used in the clinical routine to improve diagnostic accuracy. The variety of quantitative information derived from these techniques provides significant structural and functional information in a cellular level, highlighting aspects of the underlying brain pathophysiology. The present work, reviews physical principles and recent results obtained using DWI/DTI and DSCI, in tumor characterization and grading of the most common cerebral neoplasms, and discusses how the available MR quantitative data can be utilized through advanced methods of analysis, in order to optimize clinical decision making.

Differences in supratentorial white matter diffusion after radiotherapy--new biomarker of normal brain tissue damage?

INTRODUCTION

Therapy-induced injury to normal brain tissue is a concern in the treatment of all types of brain tumours. The purpose of this study was to investigate if magnetic resonance diffusion tensor imaging (DTI) could serve as a potential biomarker for the assessment of radiation-induced long-term white matter injury.

MATERIAL AND METHODS

DTI- and T1-weighted images of the brain were obtained in 19 former radiotherapy patients [nine men and 10 women diagnosed with astrocytoma (4), pituitary adenoma (6), meningioma (8) and craniopharyngioma (1), average age 57.8 (range 35-71) years]. Average time from radiotherapy to DTI scan was 4.6 (range 2.0-7.1) years. NordicICE software (NIC) was used to calculate apparent diffusion coefficient maps (ADC-maps). The co-registration between T1 images and ADC-maps were done using the auto function in NIC. The co-registration between the T1 images and the patient dose plans were done using the auto function in the treatment planning system Eclipse from Varian. Regions of interest were drawn on the T1-weighted images in NIC based on isocurves from Eclipse. Data was analysed by t-test. Estimates are given with 95% CI.

RESULTS

A mean ADC difference of 4.6(0.3;8.9)× 10(-5) mm(2)/s, p = 0.03 was found between paired white matter structures with a mean dose difference of 31.4 Gy. Comparing the ADC-values of the areas with highest dose from the paired data (dose > 33 Gy) with normal white matter (dose < 5 Gy) resulted in a mean dose difference of 44.1 Gy and a mean ADC difference of 7.87(3.15;12.60)× 10(-5) mm(2)/s, p = 0.003. Following results were obtained when looking at differences between white matter mean ADC in average dose levels from 5 to 55 Gy in steps of 10 Gy with normal white matter mean ADC: 5 Gy; 1.91(-1.76;5.58)× 10(-5) mm(2)/s, p = 0.29; 15 Gy; 5.81(1.53;10.11)× 10(-5) mm(2)/s, p = 0.01; 25 Gy; 5.80(2.43;9.18)× 10(-5) mm(2)/s, p = 0.002; 35 Gy; 5.93(2.89;8.97)× 10(-5) mm(2)/s, p = 0.0007; 45 Gy; 4.32(-0.24;8.89)× 10(-5) mm(2)/s, p = 0.06; 55 Gy; -4.04(-14.96;6.89)× 10(-5) mm(2)/s, p = 0.39.

CONCLUSION

The results indicate that the structural integrity of white matter, assessed by ADC-values based on DTI, undergoes changes after radiation therapy starting as early as total dose levels between 5 and 15 Gy.