基于表观扩散系数的细胞计算数学模型的验证

Proving of a Mathematical Model of Cell Calculation Based on Apparent Diffusion Coefficient.

作者信息

Surov Alexey, Garnov Nikita

机构信息

Department of Diagnostic and Interventional radiology, University of Leipzig, Liebigstr. 20, 04103 Leipzig.

出版信息

Transl Oncol. 2017 Oct;10(5):828-830. doi: 10.1016/j.tranon.2017.08.001. Epub 2017 Aug 29.

DOI:10.1016/j.tranon.2017.08.001

PMID:28863287

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5577394/

Abstract

OBJECTIVES

Recently, Atuegwu et al. proposed a mathematical model based on ADC and ADC to calculation of cellularity. Our purpose was to compare the calculated cellularity according to the formula with the estimated cell count by histopathology in different tumors.

METHODS

For this study, we re-analyzed our previous data regarding associations between ADC parameters and histopathological findings. Overall, 134 patients with different tumors were acquired for the analysis. For all tumors, the number of tumor cells was calculated according to Atuegwu et al. 2013. We performed a correlation analysis between the calculated and estimated cellularity. Thereby, Pearson's correlation coefficient was used and P < .05 was taken to indicate statistical significance in all instances.

RESULTS

The estimated and calculated cellularity correlated well together in HNSCC (r=0.701, P=.016) and lymphomas (r=0.661, P=.001), and moderately in rectal cancer (r=0.510, P=.036). There were no statistically significant correlations between the estimated and calculated cellularity in uterine cervical cancer, meningiomas, and in thyroid cancer.

CONCLUSION

The proposed formula for cellularity calculation does not apply for all tumors. It may be used for HNSCC, cerebral lymphomas and rectal cancer, but not for uterine cervical cancer, meningioma, and thyroid cancer. Furthermore, its usefulness should be proved for other tumors.

摘要

目的

最近，阿图埃古等人提出了一种基于表观扩散系数（ADC）和ADC来计算细胞密度的数学模型。我们的目的是比较根据该公式计算出的细胞密度与不同肿瘤中通过组织病理学估计的细胞计数。

方法

在本研究中，我们重新分析了之前关于ADC参数与组织病理学结果之间关联的数据。总共纳入了134例患有不同肿瘤的患者进行分析。对于所有肿瘤，根据阿图埃古等人2013年的方法计算肿瘤细胞数量。我们对计算出的细胞密度和估计的细胞密度进行了相关性分析。因此，使用了Pearson相关系数，在所有情况下，P <.05被视为具有统计学意义。

结果

在头颈部鳞状细胞癌（HNSCC）中，估计的和计算出的细胞密度相关性良好（r = 0.701，P = 0.016），在淋巴瘤中相关性良好（r = 0.661，P = 0.001），在直肠癌中相关性中等（r = 0.510，P = 0.036）。在子宫颈癌、脑膜瘤和甲状腺癌中，估计的和计算出的细胞密度之间没有统计学上的显著相关性。