Literature DB >> 7840841

Morphometrically assisted grading of astrocytomas.

M Scarpelli1, P H Bartels, R Montironi, C M Galluzzi, D Thompson.   

Abstract

Alcohol-fixed, toluidine-blue-stained smears from 24 astrocytomas (12 low grade and 12 high grade or anaplastic) were included in the study. In each case 50 nuclei from representative areas of the tumor were selected for analysis; quantitative features pertaining to both the entire nucleus and the nucleoli were computed. Nuclear features were nuclear area and total optical density. Nucleolar features were number of nucleoli per nucleus, nucleolar area, variance of the nucleolar area, and mean and variance of the distance of nucleoli from the nuclear membrane. The results showed distinct changes in a number of nuclear and nucleolar features from low to high grade astrocytomas. Features expressing the most pronounced nuclear changes were area, grey level nonuniformity and run percentage. Changes were also found in the following nucleolar features: number of nucleoli, nucleolar area, variance of nucleolar area, nucleolar location and variance of nucleolar location. Linear discriminant analysis was carried out to determine a direction in feature space along which astrocytomas of low and high grade might be ranked. The nuclear area, number of low gray value pixels and a run length feature provided a useful linear combination. The study showed that one can derive a set of objective criteria from morphometric measurements that allows an ordering of astrocytoma cases along an axis and that might be used for continuous grading.

Entities:  

Mesh:

Year:  1994        PMID: 7840841

Source DB:  PubMed          Journal:  Anal Quant Cytol Histol        ISSN: 0884-6812            Impact factor:   0.302


  3 in total

Review 1.  Signal-Based Methods in Dielectrophoresis for Cell and Particle Separation.

Authors:  Malihe Farasat; Ehsan Aalaei; Saeed Kheirati Ronizi; Atin Bakhshi; Shaghayegh Mirhosseini; Jun Zhang; Nam-Trung Nguyen; Navid Kashaninejad
Journal:  Biosensors (Basel)       Date:  2022-07-11

2.  Brain tumor classification using AFM in combination with data mining techniques.

Authors:  Marlene Huml; René Silye; Gerald Zauner; Stephan Hutterer; Kurt Schilcher
Journal:  Biomed Res Int       Date:  2013-08-25       Impact factor: 3.411

3.  Isolation of circulating tumor cells by dielectrophoresis.

Authors:  Peter R C Gascoyne; Sangjo Shim
Journal:  Cancers (Basel)       Date:  2014-03-12       Impact factor: 6.639

  3 in total

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