Literature DB >> 26158107

Neuromorphometry of primary brain tumors by magnetic resonance imaging.

Nidiyare Hevia-Montiel1, Pedro I Rodriguez-Perez2, Paul J Lamothe-Molina3, Alfonso Arellano-Reynoso4, Ernesto Bribiesca5, Marco A Alegria-Loyola3.   

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 [Formula: see text], whereas oligodendrogliomas exhibit a mean of [Formula: see text]. In contrast, the contrast-enhanced region of the glioblastoma presented a mean of [Formula: see text], and the necrotic region presented a mean of [Formula: see text]. 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.

Entities:  

Keywords:  brain tumors; discrete compactness; gliobastoma multiforme; magnetic resonance imaging; neuromorphometry

Year:  2015        PMID: 26158107      PMCID: PMC4478878          DOI: 10.1117/1.JMI.2.2.024503

Source DB:  PubMed          Journal:  J Med Imaging (Bellingham)        ISSN: 2329-4302


  16 in total

1.  Computer-aided diagnosis of mass-like lesion in breast MRI: differential analysis of the 3-D morphology between benign and malignant tumors.

Authors:  Yan-Hao Huang; Yeun-Chung Chang; Chiun-Sheng Huang; Tsung-Ju Wu; Jeon-Hor Chen; Ruey-Feng Chang
Journal:  Comput Methods Programs Biomed       Date:  2013-09-07       Impact factor: 5.428

2.  Computer-aided diagnosis for the classification of breast masses in automated whole breast ultrasound images.

Authors:  Woo Kyung Moon; Yi-Wei Shen; Chiun-Sheng Huang; Li-Ren Chiang; Ruey-Feng Chang
Journal:  Ultrasound Med Biol       Date:  2011-04       Impact factor: 2.998

Review 3.  Neuroimaging: diagnosis and response assessment in glioblastoma.

Authors:  Jennifer L Clarke; Susan M Chang
Journal:  Cancer J       Date:  2012 Jan-Feb       Impact factor: 3.360

Review 4.  Imaging of brain tumors: functional magnetic resonance imaging and diffusion tensor imaging.

Authors:  Ajay Gupta; Akash Shah; Robert J Young; Andrei I Holodny
Journal:  Neuroimaging Clin N Am       Date:  2010-08       Impact factor: 2.264

5.  Three-dimensional reconstruction and quantification of cervical carcinoma invasion fronts from histological serial sections.

Authors:  Ulf-Dietrich Braumann; Jens-Peer Kuska; Jens Einenkel; Lars-Christian Horn; Markus Löffler; Michael Höckel
Journal:  IEEE Trans Med Imaging       Date:  2005-10       Impact factor: 10.048

6.  Correlation of myo-inositol levels and grading of cerebral astrocytomas.

Authors:  M Castillo; J K Smith; L Kwock
Journal:  AJNR Am J Neuroradiol       Date:  2000-10       Impact factor: 3.825

7.  Quantitative apparent diffusion coefficients in the characterization of brain tumors and associated peritumoral edema.

Authors:  A Server; B Kulle; J Maehlen; R Josefsen; T Schellhorn; T Kumar; C W Langberg; P H Nakstad
Journal:  Acta Radiol       Date:  2009-07       Impact factor: 1.990

8.  Cystic glioblastoma multiforme: survival outcomes in 22 cases.

Authors:  Marcos V C Maldaun; Dima Suki; Frederick F Lang; Sujit Prabhu; Weiming Shi; Gregory N Fuller; David M Wildrick; Raymond Sawaya
Journal:  J Neurosurg       Date:  2004-01       Impact factor: 5.115

9.  Evaluation of the invasion front pattern of squamous cell cervical carcinoma by measuring classical and discrete compactness.

Authors:  Jens Einenkel; Ulf-Dietrich Braumann; Lars-Christian Horn; Nadine Pannicke; Jens-Peer Kuska; Alexander Schütz; Bettina Hentschel; Michael Höckel
Journal:  Comput Med Imaging Graph       Date:  2007-05-23       Impact factor: 4.790

Review 10.  The 2007 WHO classification of tumours of the central nervous system.

Authors:  David N Louis; Hiroko Ohgaki; Otmar D Wiestler; Webster K Cavenee; Peter C Burger; Anne Jouvet; Bernd W Scheithauer; Paul Kleihues
Journal:  Acta Neuropathol       Date:  2007-07-06       Impact factor: 17.088

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  1 in total

1.  Assessing Variability in Brain Tumor Segmentation to Improve Volumetric Accuracy and Characterization of Change.

Authors:  Edgar A Rios Piedra; Ricky K Taira; Suzie El-Saden; Benjamin M Ellingson; Alex A T Bui; William Hsu
Journal:  IEEE EMBS Int Conf Biomed Health Inform       Date:  2016-04-21
  1 in total

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