Development of Techniques for the Automatic Extraction and Grade Detection of Glioma Tumors from Conventional Brain Magnetic Resonant Images

Cerebral glioma is the most prevalent primary brain tumor, which are classified broadly into low and high grades according to the degree of malignancy. High grade gliomas are highly malignant which possess a poor prognosis, and the patients survive less than eighteen months after diagnosis. Low grade gliomas are slow growing, least malignant and has better response to therapy. To date, histological grading is used as the standard technique for diagnosis, treatment planning and survival prediction. The main objective of this thesis is to propose novel methods for automatic extraction of low and high grade glioma and other brain tissues, grade detection techniques for glioma using conventional magnetic resonance imaging (MRI) modalities and 3D modelling of glioma from segmented tumor slices in order to assess the growth rate of tumors. Two new methods are developed for extracting tumor regions, of which the second method, named as Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA) can also extract white matter and grey matter from T1 FLAIR an T2 weighted images. The methods were validated with manual Ground truth images, which showed promising results. The developed methods were compared with widely used Fuzzy c-means clustering technique and the robustness of the algorithm with respect to noise is also checked for different noise levels. Image texture can provide significant information on the (ab)normality of tissue, and this thesis expands this idea to tumour texture grading and detection. Based on the thresholds of discriminant first order and gray level cooccurrence matrix based second order statistical features three feature sets were formulated and a decision system was developed for grade detection of glioma from conventional T2 weighted MRI modality.The quantitative performance analysis using ROC curve showed 99.03% accuracy for distinguishing between advanced (aggressive) and early stage (non-aggressive) malignant glioma. The developed brain texture analysis techniques can improve the physician’s ability to detect and analyse pathologies leading to a more reliable diagnosis and treatment of disease. The segmented tumors were also used for volumetric modelling of tumors which can provide an idea of the growth rate of tumor; this can be used for assessing response to therapy and patient prognosis.

A semi-automatic method for segmentation and 3D modeling of glioma tumors from brain MRI

This work presents an efficient method for volume rendering of glioma tumors from segmented 2D MRI Datasets with user interactive control, by replacing manual segmentation required in the state of art methods. The most common primary brain tumors are gliomas, evolving from the cerebral supportive cells. For clinical follow-up, the evaluation of the pre- operative tumor volume is essential. Tumor portions were automatically segmented from 2D MR images using morphological filtering techniques. These seg- mented tumor slices were propagated and modeled with the software package. The 3D modeled tumor consists of gray level values of the original image with exact tumor boundary. Axial slices of FLAIR and T2 weighted images were used for extracting tumors. Volumetric assessment of tumor volume with manual segmentation of its outlines is a time-consuming proc- ess and is prone to error. These defects are overcome in this method. Authors verified the performance of our method on several sets of MRI scans. The 3D modeling was also done using segmented 2D slices with the help of a medical software package called 3D DOCTOR for verification purposes. The results were validated with the ground truth models by the Radi- ologist.

Texture Description of low grade and high grade Glioma using Statistical features in Brain MRIs

Low grade and High grade Gliomas are tumors that originate in the glial cells. The main challenge in brain tumor diagnosis is whether a tumor is benign or malignant, primary or metastatic and low or high grade. Based on the patient's MRI, a radiologist could not differentiate whether it is a low grade Glioma or a high grade Glioma. Because both of these are almost visually similar, autopsy confirms the diagnosis of low grade with high-grade and infiltrative features. In this paper, textural description of Grade I and grade III Glioma are extracted using First order statistics and Gray Level Co-occurance Matrix Method (GLCM). Textural features are extracted from 16X16 sub image of the segmented Region of Interest(ROI) .In the proposed method, first order statistical features such as contrast, Intensity , Entropy, Kurtosis and spectral energy and GLCM features extracted were showed promising results. The ranges of these first order statistics and GLCM based features extracted are highly discriminant between grade I and Grade III. In this study which gives statistical textural information of grade I and grade III Glioma which is very useful for further classification and analysis and thus assisting Radiologist in greater extent.

Decreased 5-HT2C receptor binding in the cerebral cortex and brain stem during pancreatic regeneration in rats

The purpose of this study was to investigate the role of central 5-HT2C receptor binding in rat model of pancreatic regeneration using 60-70% pancreatectomy. The 5-HT and 5-HT2c receptor kinetics were studied in cerebral cortex and brain stem of sham operated, 72 h pancreatectomised and 7 days pancreatectomised rats. Scatchard analysis with [3H] mesulergine in cerebral cortex showed a significant decrease (p < 0.05) in maximal binding (B^,ax) without any change in Kd in 72 h pancreatectomised rats compared with sham. The decreased Bmax reversed to sham level by 7 days after pancreatectomy. In brain stem , Scatchard analysis showed a significant decrease (p < 0.01) in Bax with a significant increase (p < 0.01) in Kd. Competition analysis in brain stem showed a shift in affinity towards a low affinity. These parameters were reversed to sham level by 7 days after pancreatectomy. Thus the results suggest that 5-HT through the 5-HT2C receptor in the brain has a functional regulatory role in the pancreatic regeneration. (Mol Cell Biochem 272: 165-170, 2005)

Decreased (x1-Adrenergic Receptor Binding in the Cerebral Cortex and Brain Stem during Pancreatic Regeneration in Rats

purpose of this study was to investigate the role of brain al-adrenergic receptor binding in the rat model of pancreatic regeneration using 60-70% pancre:dectorny. The a, -adrenergic receptors kinetics was studied in the cerebral cor:cx and brain stem of sham operated . 72 It pan- crea(ectoinised and 7 days pancreatectomised rats. Scar chard analysis with I `I I lprazocin in cerebral cartes and brain stein showed a significant decrease (/' < 0.01). (P < 0.05) in maximal binding ( 1),,,,,) with it significant decrease (P < 0.001 ), ( P < 0.01) in the K,,in 72 It pancreatecto- raised rats compared with sham , respectively . Competition analysis in cerebral cortex and brain stem showed it shift in affinity during pancreatic regeneration . The sympathetic activity was decreased as indicated by the significantly de- increased norepinephrine level in the plasma (P < 0.001), cerebral cortex (P < 0.01) and brain stem (P < 0.001) of 72 h pancreatectomised rats compared to sham . Thus, from our results it is suggested that the central a, -adrenergic receptors have a functional role in the pancreatic regenera- Lion mediated through the sympathetic pathway.

Increased 5-HT2C Receptor Binding in the Brain Stem And Cerebral Cortex During Liver Regeneration And Hepatic Neoplasia In Rats

In the present study, serotonin 2C (5-HT2c) receptor binding parameters in the brainstem and cerebral cortex were investigated during liver generation after partial hepatectomy (PH) and N-nitrosodiethylamine (NDEA) induced hepatic neoplasia in male Wistar rats. The serotonin content increased significantly (p<0.01) in the cerebral cortex after PH and in NDEA induced hepatic neoplasia. Brain stem serotonin content increased significantly (p<0.05) after PH and (p<0.001) in NDEA induced hepatic neoplasia. The number and affinity of the 5-HT2c receptors in the crude synaptic membrane preparations of the brain stem showed a significant (p<0.001) increase after PH and in NDEA induced hepatic neoplasia. The number and affinity of 5-HT2c receptors increased significantly (p<0.001) in NDEA induced hepatic neoplasia in the crude synaptic membrane preparations of the cerebral cortex. There was a significant (p<0.01) increase in plasma norepinephrine in PH and (p<0.001) in NDEA induced hepatic neoplasia, indicating sympathetic stimulation. Thus, our results suggest that during active hepatocyte proliferation 5-HT2c receptor in the brain stem and cerebral cortex are up-regulated which in turn induce hepatocyte proliferation mediated through sympathetic stimulation.

Enhancement of [m-methoxy 3H]MDL100907 binding to 5HT 2A receptors in cerebral cortex and brain stem of streptozotocin induced diabetic rats

5-Hydroxytryptamine2A (5-HT2A) receptor kinetics was studied in cerebral cortex and brain stem of streptozotocin (STZ) induced diabetic rats. Scatchard analysis with [3H] (±) 2,3dimethoxyphenyl-l-[2-(4-piperidine)-methanol] ([3H]MDL100907) in cerebral cortex showed no significant change in maximal binding (Bmax) in diabetic rats compared to controls. Dissociation constant (K) of diabetic rats showed a significant decrease (p < 0.05) in cerebral cortex, which was reversed to normal by insulin treatment. Competition studies of [3H]MDL100907 binding in cerebral cortex with ketanserin showed the appearance of an additional low affinity site for 5-HT2A receptors in diabetic state, which was reversed to control pattern by insulin treatment. In brain stem, scatchard analysis showed a significant increase (p < 0.05) in Bmax accompanied by a significant increase (p < 0.05) in Kd. Competition analysis in brain stem also showed a shift in affinity towards a low affinity State for 5-HT2A receptors. All these parameters were reversed to control level by insulin treatment. These results show that in cerebral cortex there is an increase in affinity of 5-HT2A receptors without any change in its number and in the case of brain stem there is an increase in number of 5HT2A receptors accompanied by a decrease in its affinity during diabetes. Thus, from the results we suggest that the increase in affinity of 5-HT2A receptors in cerebral cortex and upregulation of 5-HT2A receptors in brain stem may lead to altered neuronal function in diabetes.

Decreased GABAA Receptors Functional Regulation 3 in the Cerebral Cortex and Brainstem of Hypoxic Neonatal Rats: 4 Effect of Glucose and Oxygen Supplementation

Hypoxia in neonates can lead to biochemical and molecular alterations mediated through changes in neurotransmitters resulting in permanent damage to brain. In this study, we evaluated the changes in the receptor status of GABAA in the cerebral cortex and brainstem of hypoxic neonatal rats and hypoxic rats supplemented with glucose and oxygen using binding assays and gene expression of GABAAa1 and GABAAc5. In the cerebral cortex and brainstem of hypoxic neonatal rats, a significant decrease in GABAA receptors was observed, which accounts for the respiratory inhibition. Hypoxic rats sup- plemented with glucose alone and with glucose and oxygen showed, respectively, a reversal of the GABAA receptors, andGABAAa1 and GABAAc5 gene expression to control. Glucose acts as an immediate energy source thereby reducing the ATP-depletion-induced increase in GABA and oxygenation, which helps in encountering anoxia. Resuscitation with oxygen alone was less effective in reversing the receptor alterations. Thus, the results of this study suggest that reduction in the GABAA receptors functional regulation during hypoxia plays an important role in mediating the brain damage. Glucose alone and glucose and oxygen supplementation to hypoxic neonatal rats helps in protecting the brain from severe hypoxic damage.

Adrenergic and Glutamergic Receptor Gene Expression and Their Functional regulation in the Cerebral Cortex of Hypoxia Induced Neonatal Rats:Role of Oxygen,Epinephrine and Glucose Supplementation

In the present work, the role of oxygen, epinephrine and glucose supplementation in regulating neurotransmitter contents, adrenergic and glutamate receptor binding parameters in the cerebral cortex of experimental groups of neonatal rats were investigated. The study of neurotransmitters and their receptors in the cerebral cortex and the EEG pattern in the brain regions of neonatal rats were taken as index for brain damage due to hypoxia, oxygen and epinephrine. Real-Time PCR work was done to confirm the binding parameters. Second messenger, cyclic Adenosine Monophosphate (cAMP) was assayed to find the functional correlation of the receptors. Behavioural studies were carried out to confirm the biochemical and molecular studies. The efficient and timely supplementation of glucose plays a crucial role in correcting the molecular changes due to hypoxia, oxygen and epinephrine. The addictive neuronal damage effect due to oxygen and epinephrine treatment is another important observation. The corrective measures from the molecular study brought to practice will lead to maintain healthy intellectual capacity during the later developmental stages, which has immense clinical significance in neonatal care.

Automatic Detection and Classification of Glioma Tumors using Statistical Features

The characterization and grading of glioma tumors, via image derived features, for diagnosis, prognosis, and treatment response has been an active research area in medical image computing. This paper presents a novel method for automatic detection and classification of glioma from conventional T2 weighted MR images. Automatic detection of the tumor was established using newly developed method called Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA).Statistical Features were extracted from the detected tumor texture using first order statistics and gray level co-occurrence matrix (GLCM) based second order statistical methods. Statistical significance of the features was determined by t-test and its corresponding p-value. A decision system was developed for the grade detection of glioma using these selected features and its p-value. The detection performance of the decision system was validated using the receiver operating characteristic (ROC) curve. The diagnosis and grading of glioma using this non-invasive method can contribute promising results in medical image computing