Correlation between apparent diffusion coefficient value and pathological grading in pT1b clear cell renal cell carcinoma
10.3760/cma.j.issn.1005-1201.2012.08.003
- VernacularTitle:T1b期肾透明细胞癌ADC值与病理分级相关性的研究
- Author:
Jun SUN
;
Wei XING
;
Jie CHEN
;
Shijun XING
;
Lijun ZHANG
;
Yanwen ZHANG
;
Tongbing CHEN
;
Yunjie CAO
- Publication Type:Journal Article
- Keywords:
Magnetic resonance imaging;
Renal neoplasms;
Pathological grading
- From:
Chinese Journal of Radiology
2012;46(8):682-686
- CountryChina
- Language:Chinese
-
Abstract:
Objective To evaluate the correlation of ADC values on 3.0 T MR with the pathological grades in pT1b clear cell renal cell carcinoma(CCRCC).Methods Conventional MR images,ADC values and Fuhrman pathological grading of pT1b CCRCC were performed in 30 patients.Grade Ⅰ and Ⅱ were defined as low-grade group; grade Ⅲ and IV were defined as high-grade group.The differences of ADC values among four different pathologic grades were compared with a one-way analysis of variance. The comparison of ADC values of two different grade groups was performed with t test,and the ROC curve was performed to evaluate the diagnostic efficacy of ADC value. Correlation between pathological gradings and ADC values was assessed with Spearman rank correlation analysis. Results ( 1 ) The mean ADC value of grading Ⅰ ( 10 patients ), Ⅱ ( 8 patients ),Ⅲ ( 7 patients ),IV ( 5 patients ) was ( 0.94 ± 0.11 ) ×10-3 mm2/s,(0.82 ±0.13) × 10-3 mm2/s,(0.68 ±0.09) × 10-3 mm2/s,(0.59 ±0.03) × 10-3 mm2/s,respectively.Significant differences of ADC values among the four grades were present (F =16.422,P =0.000 ).( 2 ) The mean ADC value of the low-grade group was significantly higher than that of the high-grade group(t =5.738,P =0.000).Sensitivity and specificity of diagnosing the low-grade group was 88.9％ and 83.3％ respectively.There was a negative correlation between pathological grading and ADC value ( r =-0.807,P ＜ 0.05). Conclusions The ADC values of pT1b CCRCC have close correlation with pathological gradings.They can be used to predict the degree of tumor malignancy preoperatively and guide surgical planning.
