Maximum Fractional Anisotropy Research Articles

The Role of Multidirectional Diffusion Weighted Imaging in the diagnosis of breast carcinoma in Magnetic Resonance Imaging.

Background: Magnetic resonance imaging (MRI) is increasingly used in breast imaging. Diffusion imaging (DWI) is used in conjunction with contrast enhanced series. There will be a signal difference between the stationary and moving water molecules in DWI, due to the fact that all molecules will receive a first gradient pulse and then another pulse at the 180 degree-reverse direction of the first one. The stationary molecules will have zero signal after the two of the pulses and show restriction (low signal). Whereas, the moving molecule will not be at the same location and escape from the 180 degree pulse and have an energy in the end of the gradients. Multidirectional Diffusion-Weighted Imaging (MDDWI) gives information signifying water’s capacity to move freely in a direction according to its physiological and pathological boundaries, which is referred to as fractional anisotropy (FA). This study aimed to determine the usefulness of FA maps in in differentiating benign and malignant breast lesions. Methods: The patients had breast MRI including MDDWI series and went through pathological evaluation (Seventy-nine patients with 86 lesions) were included in the study. The FA values were measured in addition to the conventional Diffusion-ADC values. Also, diffusion restriction and pathology results were noted. The lesion FA and ADC values, diffusion assessment, and pathology results were compared using the Student t-test. Results: The patients were between 23 and 76 years and mean age for benign lesions was 43.9 whereas, it was 50.4 for the malignant lesions. Fourty-five patients had benign lesions and 41 had malignant. Mean ADC values were significant between benign and malignant lesions (correspondingly; 1256.5x10–3 mm²/s. and 978.7x10–3 mm²/s.) The FASD value of each lesion was found to be significant for malignant lesions (100x10–3), especially those with restricted diffusion. In addition, for lesions with restricted diffusion, the maximum FA (75x10–3) and mean FA(200x10–3 ) values were found to be significant for malignancy. A cut-off point of 500×10–3 of FA max was found to be a value that could be used to increase the specificity of suspicious lesions with restricted diffusion Conclusion: Restricted diffusion is used as a supporting finding for biopsy indication. But due to its lower specificity DWI cannot be very helpful in the aspect of increasing specificity of conventional breast MRI. In the search of finding a tool to increase the specificity of breast MRI, FA values seem to have the potential in differentiating benign lesions.

Elucidating the structural–functional connectome of language in glioma‐induced aphasia using nTMS and DTI

Glioma‐induced aphasia (GIA) is frequently observed in patients with newly diagnosed gliomas. Previous studies showed an impact of gliomas not only on local brain regions but also on the functionality and structure of brain networks. The current study used navigated transcranial magnetic stimulation (nTMS) to localize language‐related regions and to explore language function at the network level in combination with connectome analysis. Thirty glioma patients without aphasia (NA) and 30 patients with GIA were prospectively enrolled. Tumors were located in the vicinity of arcuate fasciculus‐related cortical and subcortical regions. The visualized ratio (VR) of each tract was calculated based on their respective fractional anisotropy (FA) and maximal FA. Using a thresholding method of each tract at 25% VR and 50% VR, DTI‐based tractography was performed to construct structural brain networks for graph‐based connectome analysis, containing functional data acquired by nTMS. The average degree of left hemispheric networks (M left) was higher in the NA group than in the GIA group for both VR thresholds. Differences of global and local efficiency between 25% and 50% VR thresholds were significantly lower in the NA group than in the GIA group. Aphasia levels correlated with connectome properties in M left and networks based on positive nTMS mapping regions (M pos). A more substantial relation to language performance was found in M pos and M left compared to the network of negative mapping regions (M neg). Gliomas causing deterioration of language are related to various cerebral networks. In NA patients, mainly M neg was impacted, while M pos was impacted in GIA patients.

Pipeline comparisons of convolutional neural networks for structural connectomes: predicting sex across 3,152 participants.

With several initiatives well underway towards amassing large and high-quality population-based neuroimaging datasets, deep learning is set to push the boundaries of what is possible in classification and prediction in neuroimaging studies. This includes those that derive increasingly popular structural connectomes, which map out the connections (and their relative strengths) between brain regions. Here, we test different Convolutional Neural Network (CNN) models in a benchmark sex prediction task in a large sample of N=3,152 structural connectomes acquired from the UK Biobank, and compare results across different connectome processing choices. The best results (76.5% test accuracy) were achieved using Fractional Anisotropy (FA) weighted connectomes, without sparsification, and with a simple weight normalisation through division by the maximum FA value. We also confirm that for structural connectomes, a Graph CNN approach, the recently proposed BrainNetCNN, outperforms an image-based CNN.

Detection of high GS risk group prostate tumors by diffusion tensor imaging and logistic regression modelling

PurposeTo assess the value of joint evaluation of diffusion tensor imaging (DTI) measures by using logistic regression modelling to detect high GS risk group prostate tumors. Materials and methodsFifty tumors imaged using DTI on a 3 T MRI device were analyzed. Regions of interests focusing on the center of tumor foci and noncancerous tissue on the maps of mean diffusivity (MD) and fractional anisotropy (FA) were used to extract the minimum, the maximum and the mean measures. Measure ratio was computed by dividing tumor measure by noncancerous tissue measure. Logistic regression models were fitted for all possible pair combinations of the measures using 5-fold cross validation. ResultsSystematic differences are present for all MD measures and also for all FA measures in distinguishing the high risk tumors [GS ≥ 7(4 + 3)] from the low risk tumors [GS ≤ 7(3 + 4)] (P < 0.05). Smaller value for MD measures and larger value for FA measures indicate the high risk. The models enrolling the measures achieve good fits and good classification performances (R2adj = 0.55–0.60, AUC = 0.88–0.91), however the models using the measure ratios perform better (R2adj = 0.59–0.75, AUC = 0.88–0.95). The model that employs the ratios of minimum MD and maximum FA accomplishes the highest sensitivity, specificity and accuracy (Se = 77.8%, Sp = 96.9% and Acc = 90.0%). ConclusionJoint evaluation of MD and FA diffusion tensor imaging measures is valuable to detect high GS risk group peripheral zone prostate tumors. However, use of the ratios of the measures improves the accuracy of the detections substantially. Logistic regression modelling provides a favorable solution for the joint evaluations easily adoptable in clinical practice.

Reduced Field-of-View Diffusion Tensor Imaging of the Spinal Cord Shows Motor Dysfunction of the Lower Extremities in Patients With Cervical Compression Myelopathy.

A cross-sectional study. The aim of this study was to quantify spinal cord dysfunction at the tract level in patients with cervical compressive myelopathy (CCM) using reduced field-of-view (rFOV) diffusion tensor imaging (DTI). Although magnetic resonance imaging (MRI) is the standard used for radiological evaluation of CCM, information acquired by MRI does not necessarily reflect the severity of spinal cord disorder. There is a growing interest in developing imaging methods to quantify spinal cord dysfunction. To acquire high-resolution DTI, a new scheme using rFOV has been proposed. We enrolled 10 healthy volunteers and 20 patients with CCM in this study. The participants were studied using a 3.0-T MRI system. For DTI acquisitions, diffusion-weighted spin-echo rFOV single-shot echo-planar imaging was used. Regions-of-interest (ROI) for the lateral column (LC) and posterior column (PC) tracts were determined on the basis of a map of fractional anisotropy (FA) of the spinal cord and FA values were measured. The FA of patients with CCM was compared with that of healthy controls and correlated with Japanese Orthopaedic Association (JOA) score. In LC and PC tracts, FA values in patients with CCM were significantly lower than in healthy volunteers. Total JOA scores correlated moderately with FA in LC and PC tracts. JOA subscores for motor dysfunction of the lower extremities correlated strongly with FA in LC and PC tracts. It is feasible to evaluate the cervical spinal cord at the tract level using rFOV DTI. Although FA values at the maximum compression level were not well correlated with total JOA scores, they were strongly correlated with JOA subscores for motor dysfunction of the lower extremities. Our findings suggest that FA reflects white matter dysfunction below the maximum compression level and FA can be used as an imaging biomarker of spinal cord dysfunction. 4.

Preoperative Prediction of Location and Shape of Facial Nerve in Patients with Large Vestibular Schwannomas Using Diffusion Tensor Imaging-Based Fiber Tracking.

Preserving the facial nerve (FN) during surgery for large vestibular schwannomas (VSs) is challenging because of the unpredictable locations and morphologic changes in the FN. Diffusion tensor imaging-based fiber tracking (DTI-FT) has been proposed to preoperatively visualize the FN. This study was performed to evaluate the efficacy of DTI-FT for predicting FN location and shape in patients with large VSs. In this prospective study, imaging data from 30 consecutive patients with large VSs were obtained using 3-T magnetic resonance imaging. The DTI-FT results included the location of the reconstructed FN relative to the tumor, and maximal fractional anisotropy (MFA) threshold values for FN tracking were determined with iPlan software. Intraoperative findings including the location of FN relative to the tumor and shape were determined by microscopic observations and electrophysiologic monitoring. A correlation analysis was performed between the DTI-FT results and intraoperative findings. Preoperative visualization of the FN using DTI-FT was successful in all 30 patients. The location of the cisternal segment of the FN in relation to the tumors predicted by DTI-FT was consistent with the intraoperative findings in 29 (96.7%) of the 30 patients. The area under the curve of MFA for differentiation between the compact and flat FN was 0.84 (95% confidence interval [CI]: 0.69-0.98) (P= 0.002). DTI-FT with modified tracking settings was useful to preoperatively predict the location of FN in patients with large VSs. The MFA of FN demonstrated moderate diagnostic performance for distinguishing compact from flat FNs.

Potential role of quantitative MRI assessment in differentiating high from low-grade gliomas

BackgroundIt is crucial to accurately differentiate HGGs from LGGs, as treatment strategies vary. Our study aims to assess the sensitivity and specificity of fractional anisotropy (FA) values derived from diffusion tensor imaging (DTI) and dynamic contrast enhanced perfusion-weighted imaging (PWI) in differentiating HGGs from LGGs. Materials15 patients with HGGs and 9 LGGs were examined. Mean, Minimal and Maximal FA fractional anisotropy in tumour, necrotic area and in surrounding oedema, as well as (rCBV) ratio of the lesions were measured and compared between LGG and HGG. The efficacy of the above parameters in grading gliomas was evaluated. In perfusion MRI, we measure rCBV ratio as parameter of neovascularity of tumour. ResultsThe use of MR DTI had an important role in the grading of brain gliomas as it was accurate in grading 24 cases. There was significant correlation between histopathological grade and FA values measured in tumour and necrotic areas. No positive correlation in perifocal areas could be established. Our results show significant difference between HGG and LGG with mean rCBV ratio as 2.62 & 0.79 with best cut-off value (1.2).Combined use of MR DTI and MR perfusion added to the accuracy of grading of glioma.

Combination of diffusion tensor imaging and conventional MRI correlates with isocitrate dehydrogenase 1/2 mutations but not 1p/19q genotyping in oligodendroglial tumours.

To explore the correlations of conventional MRI (cMRI) and diffusion tensor imaging (DTI) values with the 1p/19 codeletion and IDH mutations in oligodendroglial tumours (OTs). Eighty-four patients with OTs who underwent cMRI and DTI were retrospectively reviewed. The maximal fractional anisotropy and minimal apparent diffusion coefficient (ADC) were measured and compared using the Mann-Whitney U test. Receiver operating characteristic curves, logistic regression analysis and four-table statistics analysis were performed to predict genotypings. OTs with 1p/19q codeletion or IDH mutations were prone to locate in frontal (P = 0.106 and 0.005, respectively) and insular lobes and were associated with absent or blurry contrast enhancement (P = 0.040 and 0.013, respectively). DTI values showed significant differences between OTs with and without IDH mutations (P < 0.05) but not in OTs with and without 1p/19q loss. The Ki-67 index significantly correlated with IDH mutations (P = 0.002) but not with 1p/19q codeletion. A combination of DTI and cMRI for the identification of IDH mutations resulted in sensitivity, specificity, positive and negative predictive values of 92.2%, 75.8%, 93.8% and 71.1%, respectively. Combination of DTI and cMRI correlates with isocitrate dehydrogenase 1/2 mutations but not 1p/19q genotyping in OTs. • OTs with 1p/19q codeletion were associated with absent or blurry contrast enhancement • OTs with IDH mutations were also associated with absent or blurry contrast enhancement • OTs with IDH mutations were prone to locate in frontal and insular lobes • DTI values can provide a non-invasive method for assessing the IDH status of OTs • A combination of DTI and cMRI correlates with isocitrate dehydrogenase 1/2 mutations.

Diagnostic and Prognostic Value of 11C-Methionine PET for Nonenhancing Gliomas.

Noninvasive radiologic evaluation of glioma can facilitate correct diagnosis and detection of malignant transformation. Although positron-emission tomography is considered valuable in the care of patients with gliomas, (18)F-fluorodeoxyglucose and (11)C-methionine have reportedly shown ambiguous results in terms of grading and prognostication. The present study compared the diagnostic and prognostic capabilities of diffusion tensor imaging, FDG, and (11)C-methionine PET in nonenhancing gliomas. Thirty-five consecutive newly diagnosed, histologically confirmed nonenhancing gliomas that underwent both FDG and (11)C-methionine PET were retrospectively investigated (23 grade II and 12 grade III gliomas). Apparent diffusion coefficient, fractional anisotropy, and tumor-to-normal tissue ratios of both FDG and (11)C-methionine PET were compared between grade II and III gliomas. Prognostic values of these parameters were also tested by using progression-free survival. Grade III gliomas showed significantly higher average tumor-to-normal tissue and maximum tumor2-to-normal tissue than grade II gliomas in (11)C-methionine (P = .013, P = .0017, respectively), but not in FDG-PET imaging. There was no significant difference in average ADC, minimum ADC, average fractional anisotropy, and maximum fractional anisotropy. (11)C-methionine PET maximum tumor-to-normal tissue ratio of 2.0 was most suitable for detecting grade III gliomas among nonenhancing gliomas (sensitivity, 83.3%; specificity, 73.9%). Among patients not receiving any adjuvant therapy, median progression-free survival was 64.2 ± 7.2 months in patients with maximum tumor-to-normal tissue ratio of <2.0 for (11)C-methionine PET and 18.6 ± 6.9 months in patients with maximum tumor-to-normal tissue ratio of >2.0 (P = .0044). (11)C-methionine PET holds promise for World Health Organization grading and could offer a prognostic imaging biomarker for nonenhancing gliomas.

Decomposition of brain diffusion imaging data uncovers latent schizophrenias with distinct patterns of white matter anisotropy

Fractional anisotropy (FA) analysis of diffusion tensor-images (DTI) has yielded inconsistent abnormalities in schizophrenia (SZ). Inconsistencies may arise from averaging heterogeneous groups of patients. Here we investigate whether SZ is a heterogeneous group of disorders distinguished by distinct patterns of FA reductions. We developed a Generalized Factorization Method (GFM) to identify biclusters (i.e., subsets of subjects associated with a subset of particular characteristics, such as low FA in specific regions). GFM appropriately assembles a collection of unsupervised techniques with Non-negative Matrix Factorization to generate biclusters, rather than averaging across all subjects and all their characteristics. DTI tract-based spatial statistics images, which output is the locally maximal FA projected onto the group white matter skeleton, were analyzed in 47 SZ and 36 healthy subjects, identifying 8 biclusters. The mean FA of the voxels of each bicluster was significantly different from those of other SZ subjects or 36 healthy controls. The eight biclusters were organized into four more general patterns of low FA in specific regions: 1) genu of corpus callosum (GCC), 2) fornix (FX)+external capsule (EC), 3) splenium of CC (SCC)+retrolenticular limb (RLIC)+posterior limb (PLIC) of the internal capsule, and 4) anterior limb of the internal capsule. These patterns were significantly associated with particular clinical features: Pattern 1 (GCC) with bizarre behavior, pattern 2 (FX+EC) with prominent delusions, and pattern 3 (SCC+RLIC+PLIC) with negative symptoms including disorganized speech. The uncovered patterns suggest that SZ is a heterogeneous group of disorders that can be distinguished by different patterns of FA reductions associated with distinct clinical features.

Detecting isocitrate dehydrogenase gene mutations in oligodendroglial tumors using diffusion tensor imaging metrics and their correlations with proliferation and microvascular density.

Isocitrate dehydrogenase (IDH) mutations are frequently present in oligodendroglial tumors (OTs) and have prognostic value. We assessed whether diffusion tensor imaging (DTI) metrics could aid the noninvasive detection of IDH mutations and their correlations with tumor proliferation and microvascular density (MVD) in OTs. Ninety patients with OTs who underwent conventional magnetic resonance imaging (MRI) and DTI were retrospectively reviewed (3T). IDH mutations were determined by immunohistochemical staining or direct sequencing. MVD and cell proliferation were evaluated by immunohistochemical staining with anti-CD31 and Ki-67, respectively. The Mann-Whitney U-test was applied to each of the imaging parameters. Spearman correlation analysis and receiver operating characteristic curve analysis were performed. The maximal fractional anisotropy (FA), ratio of maximal FA (rmFA), minimal ADC, and ratio of minimal (rmADC) values were demonstrated to be significantly different between the OTs with IDH1/2 mutations and those without mutations (P < 0.05). The areas under the curve (AUCs) for the maximal FA, rmFA, minimal ADC, and rmADC were 0.79, 0.82, 0.77, and 0.80, respectively. A combination rmFA and rmADC for the diagnosis of IDH1/2 mutations led to sensitivity, specificity, and AUC of 91.5%, 76.5%, and 0.86, respectively. The Ki-67 and MVD levels in the IDH-mutated samples were lower than those in the IDH wildtype cases (P < 0.05). DTI metrics may provide a noninvasive method for assessing the IDH statuses of OTs. Significantly higher minimal ADC and lower maximal FA in OTs with IDH mutations may suggest that IDH mutations lead to proliferation inhibition and an angiogenesis decrease.

Can Diffusion Tensor Imaging Noninvasively Detect IDH1 Gene Mutations in Astrogliomas? A Retrospective Study of 112 Cases

IDH1 mutational status probably plays an important role in the predictive response for patients with astroglioma. This study explores whether DTI metrics are able to noninvasively detect IDH1 status in astrogliomas. The DTI data of 112 patients with pathologically proven astroglioma (including 25, 12, and 10 cases with IDH1 mutation and 11, 11, and 43 cases without mutation in grades II, III, and IV, respectively) were retrospectively reviewed. The maximal fractional anisotropy, minimal ADC, ratio of maximal fractional anisotropy, and ratio of minimal ADC in the tumor body were measured. In the same World Health Organization grading, the imaging parameters of patients with and without IDH1 R132H mutation were compared by means of optimal metrics for detecting mutations. Receiver operating characteristic curve analysis was performed. The maximal fractional anisotropy and ratio of maximal fractional anisotropy values had statistical significance between patients with IDH1 R132H mutation and those without mutation in astrogliomas of grades II and III. The areas under the curve for maximal fractional anisotropy and ratio of maximal fractional anisotropy were both 0.92 in grade II and 0.80 and 0.82 in grade III. The minimal ADC value and ratio of minimal ADC value also demonstrated statistical significance between patients with mutation and those without mutation in all astroglioma grades. The areas under the curve for minimal ADC were 0.94 (II), 0.76 (III), and 0.66 (IV), and the areas under the curve for ratio of minimal ADC were 0.93 (II), 0.83 (III), and 0.70 (IV). Fractional anisotropy and ADC from DTI can noninvasively detect IDH1 R132H mutation in astrogliomas.

The importance of group-wise registration in tract based spatial statistics study of neurodegeneration: a simulation study in Alzheimer's disease.

Tract-based spatial statistics (TBSS) is a popular method for the analysis of diffusion tensor imaging data. TBSS focuses on differences in white matter voxels with high fractional anisotropy (FA), representing the major fibre tracts, through registering all subjects to a common reference and the creation of a FA skeleton. This work considers the effect of choice of reference in the TBSS pipeline, which can be a standard template, an individual subject from the study, a study-specific template or a group-wise average. While TBSS attempts to overcome registration error by searching the neighbourhood perpendicular to the FA skeleton for the voxel with maximum FA, this projection step may not compensate for large registration errors that might occur in the presence of pathology such as atrophy in neurodegenerative diseases. This makes registration performance and choice of reference an important issue. Substantial work in the field of computational anatomy has shown the use of group-wise averages to reduce biases while avoiding the arbitrary selection of a single individual. Here, we demonstrate the impact of the choice of reference on: (a) specificity (b) sensitivity in a simulation study and (c) a real-world comparison of Alzheimer's disease patients to controls. In (a) and (b), simulated deformations and decreases in FA were applied to control subjects to simulate changes of shape and WM integrity similar to what would be seen in AD patients, in order to provide a “ground truth” for evaluating the various methods of TBSS reference. Using a group-wise average atlas as the reference outperformed other references in the TBSS pipeline in all evaluations.

A Diffusion Tensor Imaging Analysis of White Matter Disease in Corticobasal Syndrome (P05.041)

Objective: To determine the regions of white matter (WM) atrophy in corticobasal syndrome (CBS) using different methods of diffusion tensor imaging (DTI) analysis. Background CBS is a clinical syndrome mostly associated with frontotemporal lobar degeneration (FTLD), where gray matter atrophy predominantly encompasses frontal and parietal lobes. Although little is known about the pattern of WM disease in CBS, it is known that tau, the histopathological basis of corticobasal degeneration (CBD), has substantial WM burden. For neurodegenerative diseases, there is no gold standard for MRI-based WM analysis. Here, we compared two user-independent approaches in analyzing WM: tract-specific analysis (TSA) and whole-brain analysis. Both used fractional anisotropy (FA), which is sensitive to the integrity of white matter fiber tracts. Design/Methods: In 11 CBS patients and 35 demographically-matched healthy seniors, we analyzed 30-direction diffusion-weighted images. We extracted FA for each individual subject, and registered the image to a common stereotactic space. For TSA, 11 tracts were segmented from a DTI template, converted to 3D binary structures, and modeled as medial meshes to reflect maximum FA locally. For the whole-brain analysis, images were analyzed in local space, localized to a publicly available probabilistic template (ICDM-DTI-81), and then compared statistically with seniors in SPM8. Results: TSA revealed reduced FA in CBS relative to seniors in right uncinate, arcuate fasciculus, and inferior frontal-occipital fasiculus; and bilateral corpus callosum, corticospinal tract and superior longitudinal fasiculus. Whole-brain analysis also revealed reduced FA relative to seniors in the corpus callosum, corticospinal tract, fornix, inferior longitudinal fasiculus, superior longitudinal fasciculus, inferior frontal-occipital fasiculus, and external capsule. Conclusions: In addition to grey matter atrophy, CBS patients have considerable WM disease. TSA and whole-brain analyses display largely overlapping findings, validating user-independent approaches to DTI analyses of WM disease. Supported by: HD060406, NS44266, NS53488, AG15116, AG17586, AG32953, the Wyncote Foundation, NS065347, DA022807, EB006266, NS045839, EB009321, K25 AG027785. Disclosure: Dr. Chandrasekaren has nothing to disclose. Dr. McMillan has nothing to disclose. Dr. Brun has nothing to disclose. Dr. Cook has nothing to disclose. Dr. Yushkevich has nothing to disclose. Dr. Gee has received research support from Pfizer Inc. Dr. Grossman has nothing to disclose.

Effect of age on the fractional anisotropy (FA) value of peripheral nerves and clinical significance of the age-corrected FA value for evaluating polyneuropathies

We investigated the correlation between age and the fractional anisotropy (FA) values of peripheral nerves in healthy adults and compared the age-corrected FA values of peripheral nerves in healthy subjects and patients with polyneuropathy. The institutional review board approved this study and informed consent was obtained from all participants before entry into the study. We optimized diffusion tensor imaging using a 3-T magnetic resonance scanner and an extremity coil for scanning tibial nerves. The effect of age and sex on the FA values of tibial nerves in healthy volunteers was investigated and the age-corrected FA values of tibial nerves in healthy volunteers and patients with polyneuropathy were compared. The maximum FA values of the tibial nerves remained constant until age 45 (approximately 0.516); they subsequently decreased by 0.004/year in healthy volunteers. After removing the effect of age with an age-adjusted equation, the median maximum FA values in the volunteers and patients were 0.518 (range, 0.406-0.616) and 0.442 (range, 0.376-0.530), respectively. The age-corrected FA values were significantly lower in the patients than the healthy volunteers (p < 0.001). There was no significant gender-related difference in the maximum FA values of the tibial nerves (p = 0.416). The age-corrected FA value of the peripheral nerves helps to differentiate between age-related peripheral nerve degeneration and polyneuropathies.

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.

Can diffusion tensor metrics help in preoperative grading of diffusely infiltrating astrocytomas? A retrospective study of 36 cases

Diffusion weighted imaging and diffusion tensor imaging (DTI) give information about the amount and directionality of water diffusion occurring in a given tissue. Here we study the role of diffusion tensor metrics including fractional anisotropy (FA) and spherical anisotropy (CS) in preoperative grading of diffusely infiltrating astrocytomas. We performed DTI in 38 patients with pathologically proven diffusely infiltrating astrocytomas, who were classified into two groups, i.e., 15 patients with high-grade astrocytoma (HGAs, WHO grade III and IV) and 23 patients with low-grade astrocytoma (LGAs, WHO grade II). We measured maximum FA and minimum CS values in all cases from tumor. Histopathological diagnosis was established in all cases. The mean maximum FA values were higher in HGA (0.583 ± 0.104) than LGA (0.295 ± 0.058), while mean minimum CS values were lower in HGA (0.42 ± 0.121) than LGA (0.722 ± 0.061). The difference in the diffusion tensor indices between HGA and LGA was found to be statistically significant with P value of <0.001. Keeping cutoff FA value of 0.4, all HGAs showed higher maximum FA values, and all LGAs showed lower maximum FA values. Also, all HGAs showed minimum CS values less than a cutoff value of 0.6, and all LGAs showed minimum CS values higher than 0.6. Diffusion tensor metrics such as maximum FA and minimum CS can help to differentiate HGA from LGA.