The clinical value of histogram analysis of diffusion kurtosis imaging in prostate cancer and the correlation between histogram parameters and Gleason score
10.3760/cma.j.issn.1005-1201.2019.10.010
- VernacularTitle: 扩散峰度成像直方图分析在前列腺癌诊断及Gleason评分评估中的价值
- Author:
Yuwei JIANG
1
;
Ying LIU
2
;
Lu YU
1
;
Yadong CUI
1
;
Ming LIU
3
;
Wei ZHANG
4
;
Chen ZHANG
1
;
Jintao ZHANG
1
;
Chunmei LI
1
;
Min CHEN
1
Author Information
1. Department of Radiology, Beijing Hospital, National Center of Gerontology, Beijing 100730, China
2. Department of Radiology, Beijing Hospital, National Center of Gerontology, Beijing 100730, China(Now Works in Department of Radiology, Civil Aviation General Hospital, Beijing 100123, China
3. Department of Urological Surgical, Beijing Hospital, National Center of Gerontology, Beijing 100730, China
4. Department of Pathology, Beijing Hospital, National Center of Gerontology, Beijing 100730, China
- Publication Type:Journal Article
- Keywords:
Prostate neoplasms;
Diffusion kurtosis imaging;
Histogram analysis
- From:
Chinese Journal of Radiology
2019;53(10):844-848
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the value of diffusion kurtosis imaging (DKI) histogram analysis for differential diagnosis of prostate cancer and noncancerous foci and the correlation between histogram parameters and Gleason score.
Methods:Twenty-one patients were retrospectively enrolled in Beijing Hospital from May 2017 to May 2018. All subjects underwent Philips 3.0 T MR scanning. The pathologies were confirmed by in-bore MR-guided biopsy. Finally, 31 lesions were collected (two lesions each from 10 patients), including 15 prostate cancer and 16 noncancerous foci (benign prostatic hyperplasia and prostatitis). ROI was drawn manually by two experienced radiologists. All the lesions were measured mean apparent diffusion coefficient (Dapp), mean apparent kurtosis coefficient (Kapp) and their histogram parameters, the averages of two measurements were used to be calculated. The values of these parameters in cancer and noncancerous foci were compared using independent-samples t test. The Spearman test was used to evaluate the correlation of these parameters and Gleason scores of prostate cancer.
Results:Mean Dapp, 10th Dapp, 25th Dapp, 50th Dapp, 75th Dapp, 90th Dapp, minimum Dapp, maximum Dapp, mean Kapp, 50th Kapp, 75th Kapp, 90th Kapp, maximum Kapp between prostate cancer and noncancerous foci were statistically significant (P<0.05). 90th Kapp (r=0.630, P<0.05) and maximum Kapp (r=0.565, P<0.05) increased with the Gleason scores increasing.
Conclusion:Histogram analysis of DKI model is valuable for diagnosing and assessing aggressiveness of prostate cancer.
