Computer-Aided Diagnosis

Neuromorphometry of primary brain tumors by magnetic resonance imaging

[+] Author Affiliations
Nidiyare Hevia-Montiel

Universidad Nacional Autónoma de México, Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Computer Science Department, Avenue Colon 503-F (x av. Reforma and 62) Centro, Merida-Yucatan 97000, Mexico

Pedro I. Rodriguez-Perez

Universidad Nacional Autónoma de México, Computer Science and Engineery, Circuito Escolar s/n Ciudad Universitaria, Distrito Federal 04510, Mexico

Paul J. Lamothe-Molina, Marco A. Alegria-Loyola

Centro Neurológico—Centro Médico ABC, Avenue Carlos Graef Fernandez 154 Col. Tlaxala, Distrito Federal 05300, Mexico

Alfonso Arellano-Reynoso

Centro Neurológico—Centro Médico ABC, Avenue Carlos Graef Fernandez 154 Col. Tlaxala, Distrito Federal 05300, Mexico

Instituto Nacional de Neurología y Neurocirugia Manuel Velasco Suarez, Avenue Insurgentes Sur 3877 Col. La Fama, Distrito Federal 14269, Mexico

Ernesto Bribiesca

Universidad Nacional Autónoma de México, Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Computer Science Department, Circuito Escolar s/n Ciudad Universitaria, Distrito Federal 04510, Mexico

J. Med. Imag. 2(2), 024503 (May 12, 2015). doi:10.1117/1.JMI.2.2.024503
History: Received October 13, 2014; Accepted April 13, 2015
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Abstract.  Magnetic resonance imaging is a technique for the diagnosis and classification of brain tumors. Discrete compactness is a morphological feature of two-dimensional and three-dimensional objects. This measure determines the compactness of a discretized object depending on the sum of the areas of the connected voxels and has been used for understanding the morphology of nonbrain tumors. We hypothesized that regarding brain tumors, we may improve the malignancy grade classification. We analyzed the values in 20 patients with different subtypes of primary brain tumors: astrocytoma, oligodendroglioma, and glioblastoma multiforme subdivided into the contrast-enhanced and the necrotic tumor regions. The preliminary results show an inverse relationship between the compactness value and the malignancy grade of gliomas. Astrocytomas exhibit a mean of 973±14, whereas oligodendrogliomas exhibit a mean of 942±21. In contrast, the contrast-enhanced region of the glioblastoma presented a mean of 919±43, and the necrotic region presented a mean of 869±66. However, the volume and area of the enclosing surface did not show a relationship with the malignancy grade of the gliomas. Discrete compactness appears to be a stable characteristic between primary brain tumors of different malignancy grades, because similar values were obtained from different patients with the same type of tumor.

Figures in this Article
© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Nidiyare Hevia-Montiel ; Pedro I. Rodriguez-Perez ; Paul J. Lamothe-Molina ; Alfonso Arellano-Reynoso ; Ernesto Bribiesca, et al.
"Neuromorphometry of primary brain tumors by magnetic resonance imaging", J. Med. Imag. 2(2), 024503 (May 12, 2015). ; http://dx.doi.org/10.1117/1.JMI.2.2.024503


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