Differentiating prostate cancer from benign prostatic hyperplasia using whole-lesion histogram and texture analysis of diffusion- and T2-weighted imaging

被引:17
作者
Xing, Pengyi [1 ]
Chen, Luguang [1 ]
Yang, Qingsong [1 ]
Song, Tao [1 ]
Ma, Chao [1 ]
Grimm, Robert [2 ]
Fu, Caixia [3 ]
Wang, Tiegong [1 ]
Peng, Wenjia [1 ]
Lu, Jianping [1 ]
机构
[1] Second Mil Med Univ, Changhai Hosp Shanghai, Dept Radiol, 168 Changhai Rd, Shanghai 200433, Peoples R China
[2] Siemens Healthcare, Applicat Predev, Erlangen, Germany
[3] Siemens Shenzhen Magnet Resonance Ltd, MR Applicat Dev, Shenzhen, Peoples R China
基金
上海市自然科学基金;
关键词
Prostate cancer; Prostatic Hyperplasia; Magnetic resonance imaging; Diffusion; WEIGHTED MRI; TUMOR HETEROGENEITY; COEFFICIENT; REPRODUCIBILITY; REPEATABILITY; UTILITY; TISSUE; TOOL;
D O I
10.1186/s40644-021-00423-5
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background To explore the usefulness of analyzing histograms and textures of apparent diffusion coefficient (ADC) maps and T2-weighted (T2W) images to differentiate prostatic cancer (PCa) from benign prostatic hyperplasia (BPH) using histopathology as the reference. Methods Ninety patients with PCa and 112 patients with BPH were included in this retrospective study. Differences in whole-lesion histograms and texture parameters of ADC maps and T2W images between PCa and BPH patients were evaluated using the independent samples t-test. The diagnostic performance of ADC maps and T2W images in being able to differentiate PCa from BPH was assessed using receiver operating characteristic (ROC) curves. Results The mean, median, 5(th), and 95(th) percentiles of ADC values in images from PCa patients were significantly lower than those from BPH patients (p < 0.05). Significant differences were observed in the means, standard deviations, medians, kurtosis, skewness, and 5(th) percentile values of T2W image between PCa and BPH patients (p < 0.05). The ADC(5th) showed the largest AUC (0.906) with a sensitivity of 83.3 % and specificity of 89.3 %. The diagnostic performance of the T2W image histogram and texture analysis was moderate and had the largest AUC of 0.634 for T2W(Kurtosis) with a sensitivity and specificity of 48.9% and 79.5 %, respectively. The diagnostic performance of the combined ADC(5th) & T2W(Kurtosis) parameters was also similar to that of the ADC(5th) & ADC(Diff-Variance). Conclusions Histogram and texture parameters derived from the ADC maps and T2W images for entire prostatic lesions could be used as imaging biomarkers to differentiate PCa and BPH biologic characteristics, however, histogram parameters outperformed texture parameters in the diagnostic performance.
引用
收藏
页数:11
相关论文
共 50 条
  • [31] Texture features on T2-weighted magnetic resonance imaging: new potential biomarkers for prostate cancer aggressiveness
    Vignati, A.
    Mazzetti, S.
    Giannini, V.
    Russo, F.
    Bollito, E.
    Porpiglia, F.
    Stasi, M.
    Regge, D.
    PHYSICS IN MEDICINE AND BIOLOGY, 2015, 60 (07) : 2685 - 2701
  • [32] Seminal vesicle invasion in prostate cancer: prediction with combined T2-weighted and diffusion-weighted MR imaging
    Ren, Jing
    Huan, Yi
    Wang, He
    Ge, YaLi
    Chang, YingJuan
    Yin, Hong
    Sun, LiJun
    EUROPEAN RADIOLOGY, 2009, 19 (10) : 2481 - 2486
  • [33] Magnetic Resonance Imaging Detection of Glucose-Stimulated Zinc Secretion in the Enlarged Dog Prostate as a Potential Method for Differentiating Prostate Cancer From Benign Prostatic Hyperplasia
    Khalighinejad, Pooyan
    Parrott, Daniel
    Jordan, Veronica Clavijo
    Chirayil, Sara
    Preihs, Christian
    Rofsky, Neil M.
    Xi, Yin
    Sherry, A. Dean
    INVESTIGATIVE RADIOLOGY, 2021, 56 (07) : 450 - 457
  • [34] Automated prostate cancer detection using T2-weighted and high-b-value diffusion-weighted magnetic resonance imaging
    Kwak, Jin Tae
    Xu, Sheng
    Wood, Bradford J.
    Turkbey, Baris
    Choyke, Peter L.
    Pinto, Peter A.
    Wang, Shijun
    Summers, Ronald M.
    MEDICAL PHYSICS, 2015, 42 (05) : 2368 - 2378
  • [35] Whole-tumor radiomics analysis of T2-weighted imaging in differentiating neuroblastoma from ganglioneuroblastoma/ganglioneuroma in children: an exploratory study
    Wang, Haoru
    Chen, Xin
    Yu, Wenqing
    Xie, Mingye
    Zhang, Li
    Ding, Hao
    Li, Ting
    Qin, Jinjie
    He, Ling
    ABDOMINAL RADIOLOGY, 2023, 48 (04) : 1372 - 1382
  • [36] Preoperative T2-weighted MR imaging texture analysis of gastric cancer: prediction of TNM stages
    Xiangmei Qiao
    Zhengliang Li
    Lin Li
    Changfeng Ji
    Hui Li
    Tingting Shi
    Qing Gu
    Song Liu
    Zhengyang Zhou
    Kefeng Zhou
    Abdominal Radiology, 2021, 46 : 1487 - 1497
  • [37] Whole-tumor radiomics analysis of T2-weighted imaging in differentiating neuroblastoma from ganglioneuroblastoma/ganglioneuroma in children: an exploratory study
    Haoru Wang
    Xin Chen
    Wenqing Yu
    Mingye Xie
    Li Zhang
    Hao Ding
    Ting Li
    Jinjie Qin
    Ling He
    Abdominal Radiology, 2023, 48 : 1372 - 1382
  • [38] A study of T2-weighted MR image texture features and diffusion-weighted MR image features for computer-aided diagnosis of prostate cancer
    Peng, Yahui
    Jiang, Yulei
    Antic, Tatjana
    Giger, Maryellen L.
    Eggener, Scott
    Oto, Aytekin
    MEDICAL IMAGING 2013: COMPUTER-AIDED DIAGNOSIS, 2013, 8670
  • [39] Preoperative T2-weighted MR imaging texture analysis of gastric cancer: prediction of TNM stages
    Qiao, Xiangmei
    Li, Zhengliang
    Li, Lin
    Ji, Changfeng
    Li, Hui
    Shi, Tingting
    Gu, Qing
    Liu, Song
    Zhou, Zhengyang
    Zhou, Kefeng
    ABDOMINAL RADIOLOGY, 2021, 46 (04) : 1487 - 1497
  • [40] Prediction of placenta accreta spectrum using texture analysis on coronal and sagittal T2-weighted imaging
    Ren, Hainan
    Mori, Naoko
    Mugikura, Shunji
    Shimizu, Hiroaki
    Kageyama, Sakiko
    Saito, Masatoshi
    Takase, Kei
    ABDOMINAL RADIOLOGY, 2021, 46 (11) : 5344 - 5352