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The value of diffusion tensor imaging in differentiating high-grade gliomas from brain metastases: a systematic review and meta-analysis.

ABSTRACT: Differentiation of high-grade gliomas and solitary brain metastases is an important clinical issue because the treatment strategies differ greatly. Our study aimed to investigate the potential value of diffusion tensor imaging (DTI) in differentiating high-grade gliomas from brain metastases using a meta-analytic approach.We searched Pubmed, Embase and the Cochrane Library for relevant articles published in English. Studies that both investigated high-grade gliomas and brain metastases using DTI were included. Random effect model was used to compare fractional anisotropy (FA) and mean diffusivity (MD) values in the two tumor entities.Nine studies were included into the meta-analysis. In the peritumoral region, compared with brain metastases, high-grade gliomas had a significant increase of FA (SMD ?=?0.47; 95% CI, 0.22-0.71; P<0.01) and a significant decrease of MD (SMD ?=?-1.49; 95% CI, -1.91 to -1.06; P<0.01). However, in the intratumoral area, no significant change in FA (SMD ?=?0.16; 95% CI, -0.49 to 0.82; P?=?0.73) or MD (SMD ?=?0.34; 95% CI, -0.91 to 1.60; P?=?0.59) was detected between gliomas and metastases.High-grade gliomas may be distinguished from brain metastases by comparing the peritumoral FA and MD values. DTI appears to be a promising tool in diagnosing solitary intracranial lesions.

SUBMITTER: Jiang R

PROVIDER: S-EPMC4224505 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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The value of diffusion tensor imaging in differentiating high-grade gliomas from brain metastases: a systematic review and meta-analysis.

Jiang Rui R Du Fei-Zhou FZ He Ci C Gu Ming M Ke Zhen-Wu ZW Li Jian-Hao JH

PloS one 20141107 11

<h4>Purpose</h4>Differentiation of high-grade gliomas and solitary brain metastases is an important clinical issue because the treatment strategies differ greatly. Our study aimed to investigate the potential value of diffusion tensor imaging (DTI) in differentiating high-grade gliomas from brain metastases using a meta-analytic approach.<h4>Materials and methods</h4>We searched Pubmed, Embase and the Cochrane Library for relevant articles published in English. Studies that both investigated hig ...[more]

PMID: 25380185

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Project description:Introduction Determining the full extent of gliomas during radiotherapy planning can be challenging with conventional T1 and T2 magnetic resonance imaging (MRI). The purpose of this study was to develop a method to automatically calculate differences in the fractional anisotropy (FA) and mean diffusivity (MD) values in target volumes obtained with diffusion tensor imaging (DTI) by comparing with values from anatomically homologous voxels on the contralateral side of the brain. Methods Seven patients with a histologically confirmed glioma underwent postoperative radiotherapy planning with 1.5 T MRI and computed tomography. DTI was acquired using echo planar imaging for 20 noncolinear directions with b = 1000 s/mm2 and one additional image with b = 0, repeated four times for signal averaging. The distribution of FA and MD was calculated in the gross tumor volume (GTV), shells 0-5 mm, 5-10 mm, 10-15 mm, 15-20 mm, and 20-25 mm outside the GTV, and the GTV mirrored in the left-right direction (mirGTV). All images were aligned to a template image, and FA and MD interhemispheric difference images were calculated. The difference in mean FA and MD between the regions of interest was statistically tested using two-sided paired t-tests with ? = 0.05. Results The mean FA in mirGTV was 0.20 ± 0.04, which was larger than the FA in the GTV (0.12 ± 0.03) and shells 0-5 mm (0.15 ± 0.03) and 5-10 mm (0.17 ± 0.03) outside the GTV. The mean MD (×10-3 mm2/s) in mirGTV was 0.93 ± 0.09, which was smaller than the MD in the GTV (1.48 ± 0.19) and the peritumoral shells. The distribution of FA and MD interhemispheric differences followed the same trends as FA and MD values. Conclusions This study successfully implemented a method for calculation of FA and MD differences by comparison of voxel values with anatomically homologous voxels on the contralateral side of the brain. Further research is warranted to determine if radiotherapy planning using these images can be used to improve target delineation.

Project description:BACKGROUND AND PURPOSE:Imaging-based tumor grading is highly desirable but faces challenges in sensitivity, specificity, and diagnostic accuracy. A recently proposed diffusion imaging method by using a fractional order calculus model offers a set of new parameters to probe not only the diffusion process itself but also intravoxel tissue structures, providing new opportunities for noninvasive tumor grading. This study aimed to demonstrate the feasibility of using the fractional order calculus model to differentiate low- from high-grade gliomas in adult patients and illustrate its improved performance over a conventional diffusion imaging method using ADC (or D). MATERIALS AND METHODS:Fifty-four adult patients (18-70 years of age) with histology-proved gliomas were enrolled and divided into low-grade (n = 24) and high-grade (n = 30) groups. Multi-b-value diffusion MR imaging was performed with 17 b-values (0-4000 s/mm(2)) and was analyzed by using a fractional order calculus model. Mean values and SDs of 3 fractional order calculus parameters (D, ?, and ?) were calculated from the normal contralateral thalamus (as a control) and the tumors, respectively. On the basis of these values, the low- and high-grade glioma groups were compared by using a Mann-Whitney U test. Receiver operating characteristic analysis was performed to assess the performance of individual parameters and the combination of multiple parameters for low- versus high-grade differentiation. RESULTS:Each of the 3 fractional order calculus parameters exhibited a statistically higher value (P ? .011) in the low-grade than in the high-grade gliomas, whereas there was no difference in the normal contralateral thalamus (P ? .706). The receiver operating characteristic analysis showed that ? (area under the curve = 0.853) produced a higher area under the curve than D (0.781) or ? (0.703) and offered a sensitivity of 87.5%, specificity of 76.7%, and diagnostic accuracy of 82.1%. CONCLUSIONS:The study demonstrated the feasibility of using a non-Gaussian fractional order calculus diffusion model to differentiate low- and high-grade gliomas. While all 3 fractional order calculus parameters showed statistically significant differences between the 2 groups, ? exhibited a better performance than the other 2 parameters, including ADC (or D).

Dataset Information

The value of diffusion tensor imaging in differentiating high-grade gliomas from brain metastases: a systematic review and meta-analysis.

Publications

The value of diffusion tensor imaging in differentiating high-grade gliomas from brain metastases: a systematic review and meta-analysis.

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