Head and Neck Tumors: Amide Proton Transfer MRI

被引:62
|
作者
Law, Benjamin King Hong [1 ]
King, Ann D. [1 ]
Ai, Qi-Yong [1 ]
Poon, Darren M. C. [2 ]
Chen, Weitian [1 ]
Bhatia, Kunwar S. [3 ]
Ahuja, Anil T. [1 ]
Ma, Brigette B. [2 ]
Yeung, David Ka-Wai [2 ]
Mo, Frankie Kwok Fai [2 ]
Wang, Yi-Xiang [1 ]
Yuan, Jing [4 ]
机构
[1] Chinese Univ Hong Kong, Prince Wales Hosp, State Key Lab Oncol South China, Sir YK Pao Ctr Canc,Fac Med,Dept Imaging & Interv, 30-32 Ngan Shing St, Shatin, Hong Kong, Peoples R China
[2] Chinese Univ Hong Kong, Prince Wales Hosp, State Key Lab Oncol South China, Sir YK Pao Ctr Canc,Fac Med,Dept Clin Oncol, 30-32 Ngan Shing St, Shatin, Hong Kong, Peoples R China
[3] St Marys Hosp, Imperial Coll Healthcare, Dept Imaging, Natl Hlth Serv Trust, London, England
[4] Hong Kong Sanat & Hosp, Med Phys & Res Dept, Happy Valley, Hong Kong, Peoples R China
关键词
APPARENT DIFFUSION-COEFFICIENT; SATURATION-TRANSFER CEST; HIGH-GRADE GLIOMAS; HUMAN BRAIN-TUMORS; TRANSFER APT; CONTRAST ENHANCEMENT; ENDOGENOUS PROTEIN; PROSTATE-CANCER; T; DIFFERENTIATION;
D O I
10.1148/radiol.2018171528
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose: To evaluate the utility of amide proton transfer (APT) imaging in the characterization of head and neck tumors. Materials and Methods: This retrospective study of APT imaging included 117 patients with 70 nasopharyngeal undifferentiated carcinomas (NUCs), 26 squamous cell carcinomas (SCCs), eight non-Hodgkin lymphomas (NHLs), and 13 benign salivary gland tumors (BSGTs). Normal tissues were examined in 25 patients. The APT means of malignant tumors, normal tissues, and benign tumors were calculated and compared with the Student t test and analysis of variance. The added value of the mean APT to the mean apparent diffusion coefficient (ADC) for differentiating malignant and benign tumors was evaluated by using receiver operating characteristic analysis and integrated discrimination index. Results: The mean APT of malignant tumors (2.40% +/- 0.97 [standard deviation]) was significantly higher than that of brain tissue (1.13% +/- 0.43), muscle tissue (0.23% +/- 0.73), and benign tumors (1.32% +/- 1.20) (P <.001). There were no differences between malignant groups (NUC, 2.37% +/- 0.90; SCC, 2.41% +/- 1.16; NHL, 2.65% +/- 0.89; P = .45 to P = .86). The mean ADC of malignant tumors ([0.85 +/- 0.17] x 10(-3) mm(2)/sec) was significantly lower than that of benign tumors ([1.46 +/- 0.47] x 10(-3) mm(2)/sec) (P = .001). Adding APT to ADC increased the area under the curve from 0.87 to 0.96, with an integrated discrimination index of 7.6% ( P = .13). Conclusion: These preliminary data demonstrate differences in amide proton transfer (APT) mean of malignant tumors, normal tissues, and benign tumors, although APT mean could not be used to differentiate between malignant tumor groups. APT imaging has the potential to be of added value to apparent diffusion coefficient in differentiating malignant from benign tumors. (C) RSNA, 2018.
引用
收藏
页码:782 / 790
页数:9
相关论文
共 50 条
  • [1] Amide Proton Transfer-weighted MRI in the Diagnosis of Major Salivary Gland Tumors
    Bae, Yun Jung
    Choi, Byung Se
    Jeong, Woo-Jin
    Jung, Young Ho
    Park, Jung Hyun
    Sunwoo, Leonard
    Jung, Cheolkyu
    Kim, Jae Hyoung
    SCIENTIFIC REPORTS, 2019, 9 (1)
  • [2] Amide proton transfer imaging of tumors: theory, clinical applications, pitfalls, and future directions
    Kamimura, Kiyohisa
    Nakajo, Masanori
    Yoneyama, Tomohide
    Takumi, Koji
    Kumagae, Yuichi
    Fukukura, Yoshihiko
    Yoshiura, Takashi
    JAPANESE JOURNAL OF RADIOLOGY, 2019, 37 (02) : 109 - 116
  • [3] Assessment of Amide proton transfer weighted (APTw) MRI for pre-surgical prediction of final diagnosis in gliomas
    Durmo, Faris
    Rydhog, Anna
    Testud, Frederik
    Latt, Jimmy
    Schmitt, Benjamin
    Rydelius, Anna
    Englund, Elisabet
    Bengzon, Johan
    van Zijl, Peter
    Knutsson, Linda
    Sundgren, Pia C.
    PLOS ONE, 2020, 15 (12):
  • [4] Evaluation of Brain Tumors Using Amide Proton Transfer Imaging: A Comparison of Normal Amide Proton Transfer Signal With Abnormal Amide Proton Transfer Signal Value
    Sugawara, Kazuaki
    Miyati, Tosiaki
    Wakabayashi, Hikaru
    Yoshimaru, Daisuke
    Komatsu, Shuhei
    Hagiwara, Kazuchika
    Saigusa, Kuniyasu
    Ohno, Naoki
    JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY, 2023, 47 (01) : 121 - 128
  • [5] Discriminating MGMT promoter methylation status in patients with glioblastoma employing amide proton transfer-weighted MRI metrics
    Jiang, Shanshan
    Rui, Qihong
    Wang, Yu
    Heo, Hye-Young
    Zou, Tianyu
    Yu, Hao
    Zhang, Yi
    Wang, Xianlong
    Du, Yongxing
    Wen, Xinrui
    Chen, Fangyao
    Wang, Jihong
    Eberhart, Charles G.
    Zhou, Jinyuan
    Wen, Zhibo
    EUROPEAN RADIOLOGY, 2018, 28 (05) : 2115 - 2123
  • [6] Liver MRI with amide proton transfer imaging: feasibility and accuracy for the characterization of focal liver lesions
    Seo, Nieun
    Jeong, Ha-Kyu
    Choi, Jin-Young
    Park, Mi-Suk
    Kim, Myeong-Jin
    Chung, Yong Eun
    EUROPEAN RADIOLOGY, 2021, 31 (01) : 222 - 231
  • [7] Magnetization Transfer and Amide Proton Transfer MRI of Neonatal Brain Development
    Zheng, Yang
    Wang, Xiaoming
    Zhao, Xuna
    BIOMED RESEARCH INTERNATIONAL, 2016, 2016
  • [8] Amide proton transfer-weighted MRI for renal tumors: Comparison with diffusion-weighted imaging
    Xu, Yun
    Wan, Qingxuan
    Ren, Xihui
    Jiang, Yutao
    Wang, Fang
    Yao, Jing
    Wu, Peng
    Shen, Aijun
    Wang, Peijun
    MAGNETIC RESONANCE IMAGING, 2024, 106 : 104 - 109
  • [9] Evolution of Cerebral Ischemia Assessed by Amide Proton Transfer-Weighted MRI
    Song, Guodong
    Li, Chunmei
    Luo, Xiaojie
    Zhao, Xuna
    Zhang, Shuai
    Zhang, Yi
    Jiang, Shanshan
    Wang, Xianlong
    Chen, Yuhui
    Chen, Haibo
    Gong, Tao
    Zhou, Jinyuan
    Chen, Min
    FRONTIERS IN NEUROLOGY, 2017, 8
  • [10] An evidence-based approach to evaluate the accuracy of amide proton transfer-weighted MRI in characterization of gliomas
    Zhao, Jiaying
    Huang, Songtao
    Xie, Huan
    Li, Wenfei
    MEDICINE, 2019, 98 (10)