Journal of Clinical and Diagnostic Research, ISSN - 0973 - 709X

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Original article / research
Table of Contents - Year : 2018 | Month : July | Volume : 12 | Issue : 7 | Page : TC05 - TC09

Assessment of Primary Solid Renal Mass using Texture Analysis of CT Images of Kidney by Active Contour Method: A Novel Methody TC05-TC09

Gomalavalli Ramesh, Sriram Krishnamoorthy, Muttan Sourirajan, Venkata Sai

Correspondence
Dr. Gomalavalli Ramesh,
PhD Scholar, Department of Electronics and Communication Enginering, College of Enginering, Anna University, Chennai, Tamil Nadu, India.
E-mail: gomalavalli@gmail.com

Introduction: The overall incidence of the renal masses is on the rise. With better imaging modalities more of these masses are picked up earlier. Most of the times, the diagnosis is confirmed after radical nephrectomy. More often there is an inherent tendency to offer overtreatment in cases of benign renal masses. Renal biopsy to discriminate benign from malignant masses can be very useful in such instances but are more invasive. Grey Level Co-Occurence Matrix (GLCM) is recognized as the most representative radiological parameter to define the heterogeneity of solid renal masses.

Aim: To identify certain radiological parameters that might help us to differentiate the benign from malignant renal masses, obviating the need for a biopsy.

Materials and Methods: This was a prospective study done over three years from June 2014 to May 2017. A total of 188 patients were included. These patients were equally divided into two broad groups of 94 patients each: Group 1 was patients with renal mass, of which 67 were malignant and 27 were benign. The group 2 was the control group. We used the active contour method to delineate the renal mass and study the features in them. Data analysis for each feature was individually calculated with the help of Sigma Stats 4.0 software and one-way ANOVA analysis.

Results: Six CT parameters showed significant data that helped the clinician to differentiate the benign from the malignant renal masses. From the study it was evident that the parameters namely, entropy, energy, sum average, sum variance, inertia and low gray level emphasis were found to be statistically significant which helps the clinician to differentiate the benign from the malignant renal masses.

Conclusion: Our data shows that GLCM parameters are crucial tool for the determination of the solid mass composition of tumour. This obviates the need for an invasive procedure like Ultrasound or a CT guided biopsy of the mass.