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.
摘要
神经母细胞瘤是婴儿最常见的颅外实体性肿瘤,存在显著的生物学异质性。多个预后标记联合用于神经母细胞瘤病人治疗的风险分级。有一项标记是评估组织学,一定程度上要根据核分裂-核破裂指数(MKI)把病人分为预后好和预后不好两个类型。按照推荐意见要对5000个细胞进行评分,这既费时又会因观察者而异,不能精确计数。
本研究中我们探讨用MIB-1指数替代MKI的可行性。25例神经母细胞瘤,MKI范围从低、中到高,均行MIB-1染色。数码拍摄了375个视野,评分的细胞数大于100,000个。通过图像分析获得MIB-1指数,MKI则由人工计数相同视野得出结果。将所有的视野对比, MIB-1 指数和MKI显著相关(r=0.7869, P<0.01);单个视野对比,两者的相关性更强(r=0.9147, P<0.01)。用线性回归模型分析,得出用MIB-1指数计算MKI的公式: MKI=(MIB-1指数×0.124)+1.412。运用该公式,低MKI对应的MIB-1指数 <4.74,中mki对应的mib-1指数范围4.74—20.87,高mki对应的mib-1指数>20.87。作为对照,用人工计数方法重复计算同一图像的MIB-1指数。MIB-1指数和MKI同样存在显著相关性,MKI对应的MIB-1指数分界值几乎相同。
不管是用图像分析还是人工计数,该方法通过评估MIB-1指数来确定MKI均方便可行。
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