Computer-assisted image analysis can aid the prognostication of advanced-stage neuroblastomas

J. G. Mogilner; S. Eldar; E. Sabo; M. Hassoun; D. Attias; A. Brodski; M. Ben Harush; A. Kuten; Z. Steiner; I. Misselevich; J. Bejar; D. Ben Yizhak; V. Kerner; R. Laor; J. H. Boss

doi:10.1007/s004320050344

Computer-assisted image analysis can aid the prognostication of advanced-stage neuroblastomas

J. G. Mogilner, S. Eldar, E. Sabo, M. Hassoun, D. Attias, A. Brodski, M. Ben Harush, A. Kuten, Z. Steiner, I. Misselevich, J. Bejar, D. Ben Yizhak, V. Kerner, R. Laor, J. H. Boss^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

Purpose: The aim of this work was to detect nuclear parameters related to the prognosis of patients with stage III, IV or DS neuroblastomas. Methods: Histological sections of 25 operation specimens obtained from children with advanced-stage neuroblastomas were subjected to computer- assisted image analysis. Statistical relationships between nuclear descriptors of the tumor cells and patients' clinical outcome were determined. Results: The coefficient of variability of the mean nuclear area the mean nuclear elongation factor, and the mean nuclear averaged Feret diameter of the neuroblastoma cells were ascertained to be discriminators separating high-grade from low-grade tumors. Conclusions: The histomorphometrically gauged nuclear parameters may help oncologists to assess the prognosis of patients with advanced-stage neuroblastoma.

Original language	English
Pages (from-to)	285-290
Number of pages	6
Journal	Journal of Cancer Research and Clinical Oncology
Volume	126
Issue number	5
DOIs	https://doi.org/10.1007/s004320050344
State	Published - 2000
Externally published	Yes

Keywords

Advanced-stage neuroblastomas
Computer-assisted image analysis
Nuclear descriptors
Prognostication of neuroblastomas

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/s004320050344

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Mogilner, J. G., Eldar, S., Sabo, E., Hassoun, M., Attias, D., Brodski, A., Ben Harush, M., Kuten, A., Steiner, Z., Misselevich, I., Bejar, J., Ben Yizhak, D., Kerner, V., Laor, R., & Boss, J. H. (2000). Computer-assisted image analysis can aid the prognostication of advanced-stage neuroblastomas. Journal of Cancer Research and Clinical Oncology, 126(5), 285-290. https://doi.org/10.1007/s004320050344

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title = "Computer-assisted image analysis can aid the prognostication of advanced-stage neuroblastomas",

abstract = "Purpose: The aim of this work was to detect nuclear parameters related to the prognosis of patients with stage III, IV or DS neuroblastomas. Methods: Histological sections of 25 operation specimens obtained from children with advanced-stage neuroblastomas were subjected to computer- assisted image analysis. Statistical relationships between nuclear descriptors of the tumor cells and patients' clinical outcome were determined. Results: The coefficient of variability of the mean nuclear area the mean nuclear elongation factor, and the mean nuclear averaged Feret diameter of the neuroblastoma cells were ascertained to be discriminators separating high-grade from low-grade tumors. Conclusions: The histomorphometrically gauged nuclear parameters may help oncologists to assess the prognosis of patients with advanced-stage neuroblastoma.",

keywords = "Advanced-stage neuroblastomas, Computer-assisted image analysis, Nuclear descriptors, Prognostication of neuroblastomas",

author = "Mogilner, {J. G.} and S. Eldar and E. Sabo and M. Hassoun and D. Attias and A. Brodski and {Ben Harush}, M. and A. Kuten and Z. Steiner and I. Misselevich and J. Bejar and {Ben Yizhak}, D. and V. Kerner and R. Laor and Boss, {J. H.}",

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doi = "10.1007/s004320050344",

language = "אנגלית",

volume = "126",

pages = "285--290",

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issn = "0171-5216",

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number = "5",

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Mogilner, JG, Eldar, S, Sabo, E, Hassoun, M, Attias, D, Brodski, A, Ben Harush, M, Kuten, A, Steiner, Z, Misselevich, I, Bejar, J, Ben Yizhak, D, Kerner, V, Laor, R & Boss, JH 2000, 'Computer-assisted image analysis can aid the prognostication of advanced-stage neuroblastomas', Journal of Cancer Research and Clinical Oncology, vol. 126, no. 5, pp. 285-290. https://doi.org/10.1007/s004320050344

TY - JOUR

T1 - Computer-assisted image analysis can aid the prognostication of advanced-stage neuroblastomas

AU - Mogilner, J. G.

AU - Eldar, S.

AU - Sabo, E.

AU - Hassoun, M.

AU - Attias, D.

AU - Brodski, A.

AU - Ben Harush, M.

AU - Kuten, A.

AU - Steiner, Z.

AU - Misselevich, I.

AU - Bejar, J.

AU - Ben Yizhak, D.

AU - Kerner, V.

AU - Laor, R.

AU - Boss, J. H.

PY - 2000

Y1 - 2000

N2 - Purpose: The aim of this work was to detect nuclear parameters related to the prognosis of patients with stage III, IV or DS neuroblastomas. Methods: Histological sections of 25 operation specimens obtained from children with advanced-stage neuroblastomas were subjected to computer- assisted image analysis. Statistical relationships between nuclear descriptors of the tumor cells and patients' clinical outcome were determined. Results: The coefficient of variability of the mean nuclear area the mean nuclear elongation factor, and the mean nuclear averaged Feret diameter of the neuroblastoma cells were ascertained to be discriminators separating high-grade from low-grade tumors. Conclusions: The histomorphometrically gauged nuclear parameters may help oncologists to assess the prognosis of patients with advanced-stage neuroblastoma.

AB - Purpose: The aim of this work was to detect nuclear parameters related to the prognosis of patients with stage III, IV or DS neuroblastomas. Methods: Histological sections of 25 operation specimens obtained from children with advanced-stage neuroblastomas were subjected to computer- assisted image analysis. Statistical relationships between nuclear descriptors of the tumor cells and patients' clinical outcome were determined. Results: The coefficient of variability of the mean nuclear area the mean nuclear elongation factor, and the mean nuclear averaged Feret diameter of the neuroblastoma cells were ascertained to be discriminators separating high-grade from low-grade tumors. Conclusions: The histomorphometrically gauged nuclear parameters may help oncologists to assess the prognosis of patients with advanced-stage neuroblastoma.

KW - Advanced-stage neuroblastomas

KW - Computer-assisted image analysis

KW - Nuclear descriptors

KW - Prognostication of neuroblastomas

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AN - SCOPUS:0034014420

SN - 0171-5216

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SP - 285

EP - 290

JO - Journal of Cancer Research and Clinical Oncology

JF - Journal of Cancer Research and Clinical Oncology

IS - 5

ER -

Computer-assisted image analysis can aid the prognostication of advanced-stage neuroblastomas

Abstract

Keywords

UN SDGs

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