A Clinically Useful Watershed-based Method of Auto-segmenting Apparent Diffusion Coefficient (ADC) Maps of Cervical Cancer

2012 ◽  
Vol 84 (3) ◽  
pp. S433
Author(s):  
Y. Rao ◽  
D. Ma ◽  
H. Li ◽  
J. Esthappan ◽  
A. Chang ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Apparent Diffusion

Influence of menstrual status and pathological type on the apparent diffusion coefficient in cervical cancer: a primary study

2020 ◽  
pp. 028418512092689
Author(s):  
Yue Dong ◽  
Rui Tong Dong ◽  
Xiao Miao Zhang ◽  
Qing Ling Song ◽  
Tao Yu ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Primary Study ◽  
Adc Value ◽  
Cervical Cancers ◽  
Menstrual Status ◽  
Pathological Type ◽  
Apparent Diffusion ◽  
Adc Values

Background Apparent diffusion coefficient (ADC) value is an important quantitative parameter in the research of cervical cancer, affected by some factors. Purpose To investigate the effect of pathological type and menstrual status on the ADC value of cervical cancer. Material and Methods A total of 352 individuals with pathologically confirmed cervical cancer between January 2015 to December 2017 were retrospectively enrolled in this study, including 317 cases with squamous cell carcinomas (SCC) and 35 cases with adenocarcinomas (AC); 177 patients were non-menopausal and 175 were menopausal. All patients underwent a routine 3.0-T magnetic resonance imaging (MRI) scan and diffusion-weighted imaging (DWI) examination using b-values of 0, 800, and 1000 s/mm2. Three parameters including mean ADC (ADCmean), maximum ADC (ADCmax), and minimum ADC (ADCmin) of cervical cancer lesions were measured and retrospectively analyzed. Independent samples t-test was used to compare the difference of ADC values in different menstrual status and pathological types. Results In all menopausal and non-menopausal patients, the ADCmean and ADCmin values of SCC were lower than those of AC ( P<0.05), the ADCmax of two pathological types showed no statistical difference ( P > 0.05). In menopausal patients, the ADCmean, ADCmax, and ADCmin values of SCC were not statistically different compared with those of AC ( P > 0.05). The ADCmean, ADCmax, and ADCmin values of different pathological types cervical cancers in non-menopausal patients were all higher than those in menopausal patients ( P<0.05). Conclusion The ADC values of the cervical cancers were different in different pathological types and were also affected by menstrual status.

Whole-tumor histogram analysis of apparent diffusion coefficient for differentiating adenosquamous carcinoma and adenocarcinoma from squamous cell carcinoma in patients with cervical cancer

2021 ◽  
pp. 028418512110359
Author(s):  
Meiling Xiao ◽  
Xiaoliang Ma ◽  
Fenghua Ma ◽  
Yongai Li ◽  
Guofu Zhang ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Squamous Cell Carcinoma ◽  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Adenosquamous Carcinoma ◽  
Histogram Analysis ◽  
Characteristic Analysis ◽  
Apparent Diffusion

Background Differentiating adenosquamous carcinoma (ASC) and adenocarcinoma (AC) from squamous cell carcinoma (SCC) precisely is crucial for treatment strategy and prognosis prediction in patients with cervical cancer (CC). Purpose To differentiate ASC and AC from SCC in patients with CC using the apparent diffusion coefficient (ADC) histogram analysis. Material and Methods A total of 118 patients with histologically diagnosed ASC, AC, and SCC were included. The ADC histogram parameters were extracted from ADC maps. Receiver operating characteristic analysis was performed to evaluate the diagnostic performance of each ADC histogram parameter in differentiating the subtypes of CC. The predictors for histologic subtypes were further selected using univariate and multivariate logistic regression analyses. Results The ADCmean, ADCmax, ADCP10, ADCP25, ADCP75, ADCP90, ADCmedian, and ADCmode of the ASC were significantly lower than those of the AC; and ADCkurtosis and ADCskewness of the ASC were lower than those of the SCC. The ADCmean, ADCmax, ADCP10, ADCP25, ADCP75, ADCP90, ADCmedian, and ADCmode of AC were significantly higher than those of the SCC. The ADCP10 and ADCP10 + diameter yielded the AUCs of 0.753 and 0.778 in differentiating ASC from AC. The ADCmedian and ADCmedian + diameter yielded the AUCs of 0.807 and 0.838 in differentiating AC from SCC. The ADCskewness yielded the AUC of 0.713 in differentiating ASC from SCC. Conclusion The ADCP10 and ADCP10 + diameter, ADCmedian, and ADCmedian + diameter performed well in differentiating ASC from AC and AC from SCC, respectively. However, ADCskewness exhibited a limited ability in differentiating ASC from SCC.

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