Fractional order calculus model diffusion weighted imaging for evaluating pathological classification and differentiation degree of cervical cancer
10.13929/j.issn.1003-3289.2024.11.020
- VernacularTitle:分数阶微积分模型弥散加权成像判断宫颈癌病理类型及分化程度
- Author:
Jinchao ZHANG
1
;
Yinan SUN
;
Qing YANG
;
Ming CHEN
;
Wangyan XU
;
Mengxiao LIU
;
Juan ZHU
;
Fei WANG
Author Information
1. 安徽医科大学安庆医学中心(安庆市立医院)医学影像科,安徽安庆 246003
- Keywords:
uterine cervical neoplasms;
magnetic resonance imaging;
fractional order calculus
- From:
Chinese Journal of Medical Imaging Technology
2024;40(11):1730-1734
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the value of fractional order calculus(FROC)model diffusion weighted imaging(DWI)for evaluating pathological classification and differentiation degree of cervical cancer(CCA).Methods Totally 74 CCA patients were enrolled and divided into squamous cell carcinoma(SCC)group(n=54)and adenocarcinoma(ACA)group(n=20)based on pathological classification,also low differentiation group(n=33)and medium-high differentiation group(n=41)based on differentiation degree.Conventional MR examination and DWI with 12 b-values were performed,FROC model parameters(D,β,and p value)and the apparent diffusion coefficient(ADC)of mono-exponential model were obtained via software analysis.The parameters were compared between groups,and receiver operating characteristic curve of those being significantly different between groups were drawn,the area under the curves(AUC)were calculated to evaluate the diagnostic efficacy.Results Significant differences of ADC,D,and β values were found between SCC group and ACA group(all P＜0.05),and D value had the highest AUC(0.726)for distinguishing pathological classification CCA.Meanwhile,significant differences of D,β,p values and ADC were observed between low differentiation group and medium-high differentiation group(all P＜0.05),D value also had the highest AUC(0.865).AUC of the combined model constructed based on significant variables β and p values in logistic regression was 0.926,higher than that of each parameter alone(all P＜0.05).Conclusion FROC model DWI could be used to evaluate pathological classification and differentiation degree of CCA.
