Browsing by Author "Smitha, KA"

Now showing 1 - 6 of 6
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    Fractal analysis: fractal dimension and lacunarity from MR images for differentiating the grades of glioma
    (Physics in medicine and biology, 2015-10) Smitha, KA; Gupta, AK; Jayasree, RS
    Glioma, the heterogeneous tumors originating from glial cells, generally exhibit varied grades and are difficult to differentiate using conventional MR imaging techniques. When this differentiation is crucial in the disease prognosis and treatment, even the advanced MR imaging techniques fail to provide a higher discriminative power for the differentiation of malignant tumor from benign ones. A powerful image processing technique applied to the imaging techniques is expected to provide a better differentiation. The present study focuses on the fractal analysis of fluid attenuation inversion recovery (FLAIR) MR images, for the differentiation of glioma. For this, we have considered the most important parameters of fractal analysis, fractal dimension and lacunarity. While fractal analysis assesses the malignancy and complexity of a fractal object, lacunarity gives an indication on the empty space and the degree of inhomogeneity in the fractal objects. Box counting method with the preprocessing steps namely binarization, dilation and outlining was used to obtain the fractal dimension and lacunarity in glioma. Statistical analysis such as one-way analysis of variance (AVOVA) and receiver operating characteristic (ROC) curve analysis helped to compare the mean and to find discriminative sensitivity of the results. It was found that the lacunarity of low and high grade gliomas vary significantly. ROC curve analysis between low and high grade glioma for fractal dimension and lacunarity yielded 70.3% sensitivity and 66.7% specificity and 70.3% sensitivity and 88.9% specificity respectively. The study observes that fractal dimension and lacunarity increases with increase in the grade of glioma and lacunarity is helpful in identifying most malignant grades.
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    Relative percentage signal intensity recovery of perfusion metrics-an efficient tool for differentiating grades of glioma
    (BRITISH JOURNAL OF RADIOLOGY, 2015) Smitha, KA; Gupta, AK; Jayasree, RS
    Objective: Glioma classification and characterization may be facilitated by a multiparametric approach of perfusion metrics, which could not be achieved by conventional MRI alone. Our aim is to explore the potential of relative percentage signal intensity recovery (rPSR) values, in addition to relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF) of first-pass T-2* dynamic susceptibility contrast (DSC) perfusion MRI, in differentiating high-and low-grade glioma. Methods: This prospective study included 39 patients with low-grade and 25 patients with high-grade glioma. rPSR, rCBV and rCBF were calculated from the first-pass T-2* DSC perfusion MRI. rPSR was calculated using standard software and validated with dedicated perfusion metrics analysis software. The statistical analysis was performed using analysis of variance and receiver operating characteristic (ROC) curves. Results: Variation in rPSR, rCBV and rCBF values between low-and high-grade gliomas were statistically significant (p<0.005). The ROC curve analysis for each of them yielded 96% sensitivity and 71.8% specificity; 88% sensitivity and 69.2% specificity; and 72% sensitivity and 66.7% specificity. The area under the curve (AUC) from the ROC curve analysis yielded 0.893, 0.852 and 0.702 for rPSR, rCBV and rCBF, respectively. The rPSR calculation with the validation software yielded 92.3% sensitivity and 72% specificity with an AUC of 0.864. Conclusion: rPSR inversely correlates while rCBV and rCBF values directly correlate with the tumour grade. Furthermore, the overall diagnostic performance of rPSR is better than rCBV and rCBF values. Advances in knowledge: rPSR of T-2* DSC perfusion is an indicator of blood-brain barrier status and lesion leakiness, which has not been explored yet compared with the usual haemodynamic parameters, rCBV and rCBF.
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    Relative percentage signal intensity recovery of perfusion metrics? An efficient tool for differentiating grades of glioma
    (BJR 2015;88., 2015-07) Smitha, KA; Gupta, AK; Jayasree, RS
    Objective: Glioma classification and characterization may be facilitated by a multiparametric approach of perfusion metrics, which could not be achieved by conventional MRI alone. Our aim is to explore the potential of relative percentage signal intensity recovery (rPSR) values, in addition to relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF) of first-pass T2* dynamic susceptibility contrast (DSC) perfusion MRI, in differentiating high- and low-grade glioma. Methods: This prospective study included 39 patients with low-grade and 25 patients with high-grade glioma. rPSR, rCBV and rCBF were calculated from the first-pass T2* DSC perfusion MRI. rPSR was calculated using standard software and validated with dedicated perfusion metrics analysis software. The statistical analysis was performed using analysis of variance and receiver operating characteristic (ROC) curves. Results: Variation in rPSR, rCBV and rCBF values between low- and high-grade gliomas were statistically significant (p , 0.005). The ROC curve analysis for each of them yielded 96% sensitivity and 71.8% specificity; 88% sensitivity and 69.2% specificity; and 72% sensitivity and 66.7% specificity. The area under the curve (AUC) from the ROC curve analysis yielded 0.893, 0.852 and 0.702 for rPSR, rCBV and rCBF, respectively. The rPSR calculation with the validation software yielded 92.3% sensitivity and 72% specificity with an AUC of 0.864. Conclusion: rPSR inversely correlates while rCBV and rCBF values directly correlate with the tumour grade. Furthermore, the overall diagnostic performance of rPSR is better than rCBV and rCBF values. Advances in knowledge: rPSR of T2* DSC perfusion is an indicator of blood–brain barrier status and lesion leakiness, which has not been explored yet compared with the usual haemodynamic parameters, rCBV and rCBF.
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    Segmentation and volumetric analysis of the caudate nucleus in Alzheimer's disease
    (EUROPEAN JOURNAL OF RADIOLOGY, 2013) Jiji, S; Smitha, KA; Gupta, AK; Pillai, VPM; Jayasree, RS
    Objectives: A quantitative volumetric analysis of caudate nucleus can provide valuable information in early diagnosis and prognosis of patients with Alzheimer's diseases (AD). Purpose of the study is to estimate the volume of segmented caudate nucleus from MR images and to correlate the variation in the segmented volume with respect to the total brain volume. We have also tried to evaluate the caudate nucleus atrophy with the age related atrophy of white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF) in a group of Alzheimer's disease patients. Methods: 3D fast low angle shot (3D FLASH) brain MR images of 15 AD patients, 15 normal volunteers and 15 patients who had normally diagnosed MR images were included in the study. Brain tissue and caudate nuclei were segmented using the statistical parametric mapping package and a semi-automatic tool, respectively and the volumes were estimated. Volume of segmented caudate nucleus is correlated with respect to the total brain volume. Further, the caudate nucleus atrophy is estimated with the age related atrophy of WM, GM and CSF in a group of AD patients. Results: Significant reduction in the caudate volume of AD patients was observed compared to that of the normal volunteers. Statistical analysis also showed significant variation in the volume of GM and CSF of AD patients. Among the patients who had normal appearing brain, 33% showed significant changes in the caudate volume. We hypothesize that these changes can be considered as an indication of early AD. Conclusion: The method of volumetric analysis of brain structures is simple and effective way of early diagnosis of neurological disorders like Alzheimer's disease. We have illustrated this with the observed changes in the volume of caudate nucleus in a group of patients. A detailed study with more subjects will be useful in correlating these results for early diagnosis of AD. (C) 2013 Elsevier Ireland Ltd. All rights reserved.
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    Segmentation and volumetric analysis of the caudate nucleus inAlzheimer’s disease
    (European J Radiol., 2013-08) Jiji, S; Smitha, KA; Gupta, AK; Pillai, VPM; Jayasree, RS
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    Total magnitude of diffusion tensor imaging as an effective tool for the differentiation of glioma
    (European J Radiol., 2013-04) Smitha, KA; Gupta, AK; Jayasree, RS