21 March 2014 Wavelets based algorithm for the evaluation of enhanced liver areas
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Abstract
Hepatocellular carcinoma (HCC) is a primary tumor of the liver. After local therapies, the tumor evaluation is based on the mRECIST criteria, which involves the measurement of the maximum diameter of the viable lesion. This paper describes a computed methodology to measure through the contrasted area of the lesions the maximum diameter of the tumor by a computational algorithm. 63 computed tomography (CT) slices from 23 patients were assessed. Noncontrasted liver and HCC typical nodules were evaluated, and a virtual phantom was developed for this purpose. Optimization of the algorithm detection and quantification was made using the virtual phantom. After that, we compared the algorithm findings of maximum diameter of the target lesions against radiologist measures. Computed results of the maximum diameter are in good agreement with the results obtained by radiologist evaluation, indicating that the algorithm was able to detect properly the tumor limits. A comparison of the estimated maximum diameter by radiologist versus the algorithm revealed differences on the order of 0.25 cm for large-sized tumors (diameter > 5 cm), whereas agreement lesser than 1.0cm was found for small-sized tumors. Differences between algorithm and radiologist measures were accurate for small-sized tumors with a trend to a small increase for tumors greater than 5 cm. Therefore, traditional methods for measuring lesion diameter should be complemented with non-subjective measurement methods, which would allow a more correct evaluation of the contrast-enhanced areas of HCC according to the mRECIST criteria.
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Matheus Alvarez, Matheus Alvarez, Diana Rodrigues de Pina, Diana Rodrigues de Pina, Guilherme Giacomini, Guilherme Giacomini, Fernando Gomes Romeiro, Fernando Gomes Romeiro, Sérgio Barbosa Duarte, Sérgio Barbosa Duarte, Seizo Yamashita, Seizo Yamashita, José Ricardo de Arruda Miranda, José Ricardo de Arruda Miranda, } "Wavelets based algorithm for the evaluation of enhanced liver areas", Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 90344H (21 March 2014); doi: 10.1117/12.2043822; https://doi.org/10.1117/12.2043822
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