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

• Published in: Journal of cancer research and clinical oncology Vol. 126; no. 5; pp. 285 - 290
• Main Authors: MOGILNER, J. G, ELDAR, S, BEJAR, J, BEN YIZHAK, D, KERNER, V, LAOR, R, BOSS, J. H, SABO, E, HASSOUN, M, ATTIAS, D, BRODSKI, A, BEN HARUSH, M, KUTEN, A, STEINER, Z, MISSELEVICH, I
• Format: Journal Article
• Language: English
• Published: Berlin Springer 01-05-2000; Springer Nature B.V
• Subjects: Adrenal Gland Neoplasms - mortality; Adrenal Gland Neoplasms - pathology; Age Factors; Biological and medical sciences; Child; Child, Preschool; Disease-Free Survival; Female; Head and Neck Neoplasms - mortality; Head and Neck Neoplasms - pathology; Humans; Image Processing, Computer-Assisted - standards; Infant; Infant, Newborn; Investigative techniques, diagnostic techniques (general aspects); Israel - epidemiology; Logistic Models; Male; Mediastinal Neoplasms - mortality; Mediastinal Neoplasms - pathology; Medical sciences; Nervous system; Neuroblastoma - mortality; Neuroblastoma - pathology; Neurology; Pathology. Cytology. Biochemistry. Spectrometry. Miscellaneous investigative techniques; Pelvic Neoplasms - mortality; Pelvic Neoplasms - pathology; Predictive Value of Tests; Prognosis; Retroperitoneal Neoplasms - mortality; Retroperitoneal Neoplasms - pathology; Survival Analysis; Tumors of the nervous system. Phacomatoses; Israel; Human; Nervous system diseases; Histopathology; Prognosis; Cell nucleus; Advanced stage; Malignant tumor; Neuroblastoma; Autonomic neuropathy; Morphometry; Child; Computer aid
• ISSN: 0171-5216; 1432-1335
• DOI: 10.1007/s004320050344

The aim of this work was to detect nuclear parameters related to the prognosis of patients with stage III, IV or DS neuroblastomas.
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.
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.
The histomorphometrically gauged nuclear parameters may help oncologists to assess the prognosis of patients with advanced-stage neuroblastoma.