Literature DB >> 26171918

MIB-1 Index as a Surrogate for Mitosis-Karyorrhexis Index in Neuroblastoma.

Taywin Atikankul1, Yupapin Atikankul, Sakun Santisukwongchote, Paula Marrano, Shanop Shuangshoti, Paul S Thorner.   

Abstract

Neuroblastoma, the most common extracranial solid tumor in infancy, shows marked biological heterogeneity. Multiple prognostic markers are combined to risk-stratify neuroblastoma patients for treatment. One marker assesses histology, dividing patients into favorable and unfavorable categories based, in part, on the mitosis-karyorrhexis index (MKI). The recommended scoring of 5000 cells is, however, time-consuming and observer-dependent, and accurate counts may not always be performed. In the present study, we investigated using MIB-1 as a surrogate marker for the MKI. Twenty-five cases of neuroblastoma, ranging from low to high MKI, were immunostained for MIB-1. A total of 375 microscopic fields were digitally captured with > 100,000 cells scored. The MIB-1 index was determined by image analysis and MKI, by manual counting of the same immunostained fields. There was a significant correlation between the MIB-1 index and MKI comparing all fields (r = 0.7869, P < 0.01) and an even better correlation comparing individual cases (r = 0.9147, P < 0.01). Using a linear regression model, a formula was generated to calculate MKI from the MIB-1 index as follows: MKI = (MIB-1 index × 0.124) + 1.412. With this formula, a low MKI corresponds to an MIB-1 index < 4.74, intermediate MKI to an MIB-1 index of 4.74 to 20.87, and high MKI to an MIB-1 index > 20.87. For comparison, the calculations were repeated using a manual MIB-1 count on the same images. Similar significant correlations were obtained, with nearly identical cutoff values for MKI categories. This approach can facilitate determination of the MKI by assessing the MIB-1 index, either by image analysis or manual counting.

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Year:  2015        PMID: 26171918     DOI: 10.1097/PAS.0000000000000478

Source DB:  PubMed          Journal:  Am J Surg Pathol        ISSN: 0147-5185            Impact factor:   6.394


  2 in total

1.  Prediction for Mitosis-Karyorrhexis Index Status of Pediatric Neuroblastoma via Machine Learning Based 18F-FDG PET/CT Radiomics.

Authors:  Lijuan Feng; Luodan Qian; Shen Yang; Qinghua Ren; Shuxin Zhang; Hong Qin; Wei Wang; Chao Wang; Hui Zhang; Jigang Yang
Journal:  Diagnostics (Basel)       Date:  2022-01-20

2.  A three-dimensional bioprinted model to evaluate the effect of stiffness on neuroblastoma cell cluster dynamics and behavior.

Authors:  Ezequiel Monferrer; Susana Martín-Vañó; Aitor Carretero; Andrea García-Lizarribar; Rebeca Burgos-Panadero; Samuel Navarro; Josep Samitier; Rosa Noguera
Journal:  Sci Rep       Date:  2020-04-14       Impact factor: 4.379

  2 in total

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