Use of fractional anisotropy value by diffusion tensor MRI for preoperative diagnosis of astrocytic tumors: case report

A comparison of diffusion tractography techniques in simulating the generalized Ising model to predict the intrinsic activity of the brain

Diffusion tractography is a non-invasive technique that is being used to estimate the location and direction of white matter tracts in the brain. Identifying the characteristics of white matter plays an important role in research as well as in clinical practice that relies on finding the relationship between the structure and function of the brain. An Ising model implemented on a structural connectivity (SC) has proven to explain the spontaneous fluctuations in the brain at criticality using brain's structure depicted by white matter tracts. Since the SC is the only input of the model, identifying the tractography technique which provides a SC that delivers the highest prediction of the brain's intrinsic activity via the generalized Ising model (GIM) is essential. Hence an Ising model is simulated on SCs generated using two different acquisition schemes (single and multi-shell) and two different tractography approaches (deterministic and probabilistic) and analyzed at criticality across 69 healthy subjects. Results showed that by introducing the GIM, predictability of the empirical correlation matrix increases on average from 0.2 to 0.6 compared to the predictability using the empirical connectivity matrix directly. It is also observed that the SC generated using deterministic tractography without fractional anisotropy resulted in the highest correlation coefficient value of 0.65 between the simulated and empirical correlation matrices. Additionally, calculated dimensionalities per simulation illustrated that the dimensionality depends upon the method of tractography that has been used to extract the SC.

The correlation of fractional anisotropy parameters with Ki-67 index, and the clinical implication in grading of non-enhancing gliomas and neuronal-glial tumors

PURPOSE

To investigate the correlation between the FA parameters and Ki-67 labeling index, and their diagnostic performance in grading supratentorial non-enhancing gliomas and neuronal-glial tumors (GNGT).

METHODS

This institutional review board-approved, Health Insurance Portability and Accountability (HIPAA) compliant retrospective study enrolled 35 patients, including 19 with low grade GNGT and 16 with high grade GNGT. The mean FA, maximal FA and mean maximal FA values derived from diffusion tensor imaging were measured. The correlation between the FA parameters and the Ki-67 labeling index was assessed by Spearman rank test. The receiver operating characteristic curve analysis and multivariate logistic regression analysis were performed to detect the optimal imaging parameters in grading GNGT.

RESULTS

The three FA parameters of low grade GNGT were significantly lower than the high grade GNGT (p < 0.001). The mean FA, maximal FA and mean maximal FA had significant positive correlation with Ki-67 labeling index (p = 0.001, p < 0.001, p < 0.001 respectively). The maximal FA showed a higher sensitivity and specificity in grading of non-enhancing GNGT with specificity of 78.9%, sensitivity of 100.0%, respectively.

CONCLUSIONS

The FA parameters correlated with Ki-67 labeling index, and were useful surrogates in preoperative grading supratentorial non-enhancing GNGT.

Quantitative evaluation of diffusion tensor imaging for clinical management of glioma

Diffusion tensor imaging (DTI), assessing physiological motion of water in vivo, provides macroscopic view of microstructures of white matter in the central nervous system, and such imaging technique had been extensively used for the clinical treatment and research of glioma. This review mainly focuses on illuminating the merits of quantitative evaluation of DTI for glioma management. The content of the article includes DTI's application on tissue characterization, white matter tracts mapping, radiotherapy delineation, post-therapy outcome assessment, and multimodal imaging. At last, we elucidate a synoptic presentation of DTI limitation, which is critical for physicians making DTI-based clinical decisions in glioma management.

Diffusion Weighted/Tensor Imaging, Functional MRI and Perfusion Weighted Imaging in Glioblastoma-Foundations and Future

In this article, we review the basics of diffusion tensor imaging and functional MRI, their current utility in preoperative neurosurgical mapping, and their limitations. We also discuss potential future applications, including implementation of resting state functional MRI. We then discuss perfusion and diffusion-weighted imaging and their application in advanced neuro-oncologic practice. We explain how these modalities can be helpful in guiding surgical biopsies and differentiating recurrent tumor from treatment related changes.

Diffusion-tensor Imaging and Tractography Application in Pre-operative Planning of Intra-axial Brain Lesions

Gliomas are the most common brain tumors that diffusely infiltrate the surrounding white matter (WM) tracts. Conventional MRI is commonly used for tumor localization and characterization. However, this does not give precise information about the WM infiltration surrounding the tumor. Diffusion-tensor imaging (DTI) is a non-invasive magnetic resonance (MR) technique that measures WM tissue integrity and tractography (fiber tracking) used to investigate the preferential directionality of diffusion. DTI allows visualization of WM tracts in the immediate vicinity of brain tumors that permit maximum tumor resection while also preserving the eloquent brain areas. The relation of tumors with the white matter tracts (deviation, infiltration, and disruption) has been one the most important initial applications of DTI. The fibers can be infiltrated in normal-appearing areas, and abnormal-appearing areas of the brain can show anatomically intact fibers. In the surgical planning of brain tumors, surgery is aided by knowing the proximity and relative position of the tumor to the adjacent WM tracts. The aim of the present study is to assess the role of DT tractography (DTT) in preoperative mapping of major WM tracts in relation to brain tumors.

A systematic review of functional magnetic resonance imaging and diffusion tensor imaging modalities used in presurgical planning of brain tumour resection

Historically, brain tumour resection has relied upon standardised anatomical atlases and classical mapping techniques for successful resection. While these have provided adequate results in the past, the emergence of new technologies has heralded a wave of less invasive, patient-specific techniques for the mapping of brain function. Functional magnetic resonance imaging (fMRI) and, more recently, diffusion tensor imaging (DTI) are two such techniques. While fMRI is able to highlight localisation of function within the cortex, DTI represents the only technique able to elucidate white matter structures in vivo. Used in conjunction, both of these techniques provide important presurgical information for thorough preoperative planning, as well as intraoperatively via integration into frameless stereotactic neuronavigational systems. Together, these techniques show great promise for improved neurosurgical outcomes. While further research is required for more widespread clinical validity and acceptance, results from the literature provide a clear road map for future research and development to cement these techniques into the clinical setup of neurosurgical departments globally.

MR diffusion tensor and perfusion-weighted imaging in preoperative grading of supratentorial nonenhancing gliomas

We evaluate the value of MR diffusion tensor imaging (DTI) and dynamic susceptibility-weighted contrast material-enhanced perfusion-weighted imaging (PWI) in preoperative grading of supratentorial nonenhancing gliomas. This institutional review board-approved, Health Insurance Portability and Accountability Act-compliant retrospective study involved 52 patients: 37 with low-grade gliomas (LGGs) and 15 with high-grade gliomas (HGGs). The mean trace apparent diffusion coefficient (ADC), minimal ADC, mean fractional anisotropy (FA), maximal FA, and maximal relative cerebral blood volume (rCBV) ratio of the lesions were measured and compared between LGG and HGG. The efficacy of the above parameters in grading supratentorial nonenhancing gliomas was evaluated. There was no significant difference in rCBV ratio, minimal ADC, and mean ADC between LGG and HGG (p > 0.05). The mean and maximal FA values of LGG were significantly lower than the values of HGG (p < 0.001). The receiver operating characteristic analysis showed that the mean FA with a cutoff value of 0.129 and the maximal FA with a cutoff value of 0.219 could differentiate between LGG and HGG with specificity of 69.2% and 76.9%, respectively, and sensitivity of 93.3% and 100.0%, respectively. The combination of mean FA and maximal FA based on the linear discriminant analysis improved the diagnostic accuracy with specificity of 92.3% and sensitivity of 86.7%. These findings were better than maximal rCBV ratio, mean ADC, and minimum ADC. The mean FA and maximal FA, used individually or combined, may be useful in preoperative grading of supratentorial nonenhancing gliomas.

Computer-aided detection of brain tumor invasion using multiparametric MRI

PURPOSE

To determine the potential of using a computer-aided detection method to intelligently distinguish peritumoral edema alone from peritumor edema consisting of tumor using a combination of high-resolution morphological and physiological magnetic resonance imaging (MRI) techniques available on most clinical MRI scanners.

MATERIALS AND METHODS

This retrospective study consisted of patients with two types of primary brain tumors: meningiomas (n = 7) and glioblastomas (n = 11). Meningiomas are typically benign and have a clear delineation of tumor and edema. Glioblastomas are known to invade outside the contrast-enhancing area. Four classifiers of differing designs were trained using morphological, diffusion-weighted, and perfusion-weighted features derived from MRI to discriminate tumor and edema, tested on edematous regions surrounding tumors, and assessed for their ability to detect nonenhancing tumor invasion.

RESULTS

The four classifiers provided similar measures of accuracy when applied to the training and testing data. Each classifier was able to identify areas of nonenhancing tumor invasion supported with adjunct images or follow-up studies.

CONCLUSION

The combination of features derived from morphological and physiological imaging techniques contains the information necessary for computer-aided detection of tumor invasion and allows for the identification of tumor invasion not previously visualized on morphological, diffusion-weighted, and perfusion-weighted images and maps. Further validation of this approach requires obtaining spatially coregistered tissue samples in a study with a larger sample size.

Primary granulomatous angiitis of the central nervous system: findings of magnetic resonance spectroscopy and fractional anisotropy in diffusion tensor imaging prior to surgery. Case report

Primary granulomatous angiitis of the central nervous system (CNS) is extremely rare. Its preoperative diagnosis is difficult as the condition displays nonspecific features on routine neuroimaging investigations. In this paper, the authors report findings of magnetic resonance (MR) spectroscopy and fractional anisotropy (FA) with diffusion tensor MR imaging in a case of granulomatous angiitis of the CNS. A 30-year-old man presented with morning headaches and grand mal seizures. An MR image revealed a mass resembling glioblastoma in the right temporal lobe. Magnetic resonance spectroscopy showed a high choline/creatine (Cho/Cr) ratio indicative of a malignant neoplasm, accompanied by a slight elevation of glutamate and glutamine. The FA value was very low, which is inconsistent with malignant glioma. The mass was totally removed surgically. Histologically, the peripheral lesion of the mass consisted of a rough accumulation of fat granule cells, infiltration of inflammatory cells, and distribution of capillary vessels. Some vessels within the lesion were replaced by granulomas. The histological diagnosis was granulomatous angiitis of the CNS. The MIB-1-positive rate of the granuloma was approximately 5%. Both MR spectroscopy and FA were unable to accurately diagnose granulomatous angiitis of the CNS prior to surgery; however, elevated Cho/Cr and glutamate and glutamine shown by MR spectroscopy may indicate the moderate proliferation potential of the granuloma and the inflammatory process, respectively, in this condition. Although the low FA value in the present case enabled the authors to rule out a diagnosis of glioblastoma, FA values in inflammatory lesions require careful interpretation.

Diffusion tensor imaging for differentiation of recurrent brain tumor and radiation necrosis after radiotherapy--three case reports

Fractional anisotropy (FA) is influenced by histological data such as cellularity, vascularity and/or fiber structure in astrocytic tumors. We describe two patients with tumor recurrence and one patient with radiation necrosis who were diagnosed using assessment of FA value. The assessment of FA value in enhanced lesions after radiotherapy may be able to differentiate radiation necrosis from tumor recurrence.

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.