Diffusion kurtosis imaging in assessment of gastric cancer aggressiveness

被引:2
|
作者
Ji, Changfeng [1 ]
Zhang, Yujuan [1 ]
Zheng, Huanghuang [1 ]
Chen, Ling [2 ]
Guan, Wenxian [3 ]
Guo, Tingting [4 ]
Zhang, Qinglei [1 ]
Liu, Song [1 ]
He, Jian [1 ]
Zhou, Zhengyang [1 ]
机构
[1] Nanjing Univ, Med Sch, Affiliated Hosp, Nanjing Drum Tower Hosp,Dept Radiol, Nanjing 210008, Jiangsu, Peoples R China
[2] Nanjing Univ, Med Sch, Affiliated Hosp, Nanjing Drum Tower Hosp,Dept Pathol, Nanjing 210008, Jiangsu, Peoples R China
[3] Nanjing Univ, Med Sch, Affiliated Hosp, Nanjing Drum Tower Hosp,Dept Gastrointestinal Surg, Nanjing 210008, Jiangsu, Peoples R China
[4] Nanjing Univ Chinese Med, Clin Coll Tradit Chinese & Western Med, Nanjing Drum Tower Hosp, Dept Radiol, Nanjing 210008, Jiangsu, Peoples R China
关键词
Aggressiveness; diffusion kurtosis imaging (DKI); magnetic resonance imaging (MRI); stomach neoplasm; INTRAVOXEL INCOHERENT MOTION; GAUSSIAN WATER DIFFUSION; PROGNOSTIC-SIGNIFICANCE; LAUREN CLASSIFICATION; COEFFICIENT VALUE; DIFFERENTIATION; SPECIMEN; INVASION; BIOPSY; MRI;
D O I
10.21037/tcr.2017.07.02
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background: Diffusion kurtosis imaging (DKI) has been utilized in various tumors. The potential associations between parameters derived from DKI and the aggressiveness of gastric cancers are still unclear. Methods: Forty-nine patients with gastric cancers were enrolled in this prospective study. All patients underwent magnetic resonance (MR) examination before surgery. All MR images were reviewed by two radiologists using software IDL 6.3 and an oval region of interest (ROI) was manually drawn on the specific slice showing the largest area of tumor. Three parameters were calculated automatically: apparent diffusion coefficient (ADC), corrected diffusion coefficient (diffusivity) and excess diffusion kurtosis coefficient (kurtosis). Results: Poorly/moderate-poorly differentiated gastric cancers showed significantly lower ADC and higher kurtosis compared with moderately/well differentiated tumors (P = 0.039, 0.002, respectively). Kurtosis was also significantly different in different Lauren classifications (P = 0.010). ADC and diffusivity were significantly lower while kurtosis was significantly higher in gastric cancers with T3-T4 stages than in those with T1-T2 stages (P = 0.004, 0.021, 0.009, respectively). Lower ADC and diffusivity were also observed in gastric cancers with N1-N3 stages (P = 0.010, 0.023, respectively). No significant differences were found for ADC, diffusivity and kurtosis among different status of vascular invasion and perineural invasion. Conclusions: DKI derived parameters might be helpful in preoperative assessment of gastric cancer's aggressiveness, especially in identifying poorly/moderate-poorly differentiated or diffuse type gastric cancers, and in predicting the status of lymph nodes metastasis.
引用
收藏
页码:1032 / +
页数:12
相关论文
共 50 条
  • [1] Diffusion Kurtosis Imaging Combined With DWI at 3-T MRI for Detection and Assessment of Aggressiveness of Prostate Cancer
    Wang, Xiangyu
    Tu, Ning
    Qin, Tao
    Xing, Fen
    Wang, Panying
    Wu, Guangyao
    AMERICAN JOURNAL OF ROENTGENOLOGY, 2018, 211 (04) : 797 - 804
  • [2] Diffusion kurtosis imaging and standard diffusion imaging in the magnetic resonance imaging assessment of prostate cancer
    Palumbo, Pierpaolo
    Martinese, Andrea
    Antenucci, Maria Rosaria
    Granata, Vincenza
    Fusco, Roberta
    De Muzio, Federica
    Brunese, Maria Chiara
    Bicci, Eleonora
    Bruno, Alessandra
    Bruno, Federico
    Giovagnoni, Andrea
    Gandolfo, Nicoletta
    Miele, Vittorio
    Di Cesare, Ernesto
    Manetta, Rosa
    GLAND SURGERY, 2023, 12 (12) : 1806 - 1822
  • [3] Prostate Cancer: Diffusion-weighted MR Imaging for Detection and Assessment of Aggressiveness-Comparison between Conventional and Kurtosis Models
    Tamada, Tsutomu
    Prabhu, Vinay
    Li, Jianhong
    Babb, James S.
    Taneja, Samir S.
    Rosenkrantz, Andrew B.
    RADIOLOGY, 2017, 284 (01) : 100 - 108
  • [4] ZOOMit diffusion kurtosis imaging combined with diffusion weighted imaging for the assessment of microsatellite instability in endometrial cancer
    Wang, Fang
    Wang, Yafei
    Ran, Chenjiao
    Liang, Jing
    Qi, Lisha
    Zhang, Chen
    Ye, Zhaoxiang
    ABDOMINAL RADIOLOGY, 2024,
  • [5] Diffusion Kurtosis Imaging in the Assessment of Cervical Carcinoma
    Wang, Mandi
    Perucho, Jose A. U.
    Chan, Queenie
    Sun, Jianqing
    Ip, Philip
    Tse, Ka Yu
    Lee, Elaine Y. P.
    ACADEMIC RADIOLOGY, 2020, 27 (05) : E94 - E101
  • [6] Diffusion Kurtosis Imaging for Oropharyngeal Cancer Detection
    Ding, Y.
    Mohamed, A.
    Ma, J.
    Frank, S.
    Wang, J.
    Fuller, C.
    MEDICAL PHYSICS, 2016, 43 (06) : 3645 - 3645
  • [7] Diffusion kurtosis imaging as a biomarker of breast cancer
    Honda, Maya
    Le Bihan, Denis
    Kataoka, Masako
    Iima, Mami
    BJR OPEN, 2023, 5 (01):
  • [8] Diffusion kurtosis imaging in the prediction of poor responses of locally advanced gastric cancer to neoadjuvant chemotherapy
    Fu, Jia
    Tang, Lei
    Li, Zi-Yu
    Li, Xiao-Ting
    Zhu, Hai-Feng
    Sun, Ying-Shi
    Ji, Jia-Fu
    EUROPEAN JOURNAL OF RADIOLOGY, 2020, 128
  • [9] Comparison of Diffusion Kurtosis Imaging and Amide Proton Transfer Imaging in the Diagnosis and Risk Assessment of Prostate Cancer
    Yin, Huijia
    Wang, Dongdong
    Yan, Ruifang
    Jin, Xingxing
    Hu, Ying
    Zhai, Zhansheng
    Duan, Jinhui
    Zhang, Jian
    Wang, Kaiyu
    Han, Dongming
    FRONTIERS IN ONCOLOGY, 2021, 11
  • [10] Assessment of Microvascular Invasion of Hepatocellular Carcinoma with Diffusion Kurtosis Imaging
    Wang, Wen-Tao
    Yang, Li
    Yang, Zhao-Xia
    Hu, Xin-Xing
    Ding, Ying
    Yan, Xu
    Fu, Cai-Xia
    Grimm, Robert
    Zeng, Meng-Su
    Rao, Sheng-Xiang
    RADIOLOGY, 2018, 286 (02) : 571 - 580