Dynamic contrast-enhanced MRI perfusion parameters are imaging biomarkers for angiogenesis in lung cancer

被引:1
|
作者
Du, Yonghao [1 ]
Zhang, Shuo [1 ]
Liang, Ting [1 ]
Shang, Jin [1 ]
Guo, Chenguang [1 ]
Lian, Jie [2 ]
Gong, Huilin [2 ]
Yang, Jian [1 ]
Niu, Gang [1 ]
机构
[1] Xi An Jiao Tong Univ, Affiliated Hosp 1, Dept Radiol, Xian 710061, Peoples R China
[2] Xi An Jiao Tong Univ, Affiliated Hosp 1, Dept Pathol, Xian, Peoples R China
关键词
Magnetic resonance imaging; lung neoplasms; microvessel densities; Ki-67; antigen; SOLITARY PULMONARY NODULES; MICROVESSEL DENSITY; PROGNOSTIC INDICATOR; GROWTH-FACTOR; STATISTICS; CARCINOMA; SURVIVAL; PET/CT; KI67;
D O I
10.1177/02841851221088581
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
Background Quantitative parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) may have the potential to reflect angiogenesis and proliferation of pulmonary neoplasms. Purpose To verify whether DCE-MRI can identify pulmonary neoplasm property and evaluate the correlation of DCE-MRI perfusion parameters with microvessel density (MVD) and Ki-67 in lung cancer. Material and Methods This study enrolled 65 patients with one pulmonary neoplasm who underwent computed tomography-guided percutaneous lung biopsy with pathological diagnosis (43 malignant, 22 benign; mean age = 59.71 +/- 11.72 years). All patients did DCE-MRI before biopsy. Quantitative MRI parameters including endothelial transfer constant (K-trans), flux rate constant (K-ep), and fractional extravascular extracellular space (EES) volume (V-e) were calculated by extended Tofts linear model. MVD was evaluated by CD34-expressing tumor vessels. Proliferation was assessed by Ki-67 staining. The correlations of parameters with MVD and Ki-67 expression were analyzed. Results K-trans and K-ep values were significantly increased in malignant lesions compared to benign lesions (P = 0.001 and 0.022, respectively), whereas no statistical difference in V-e was found. The CD34 expression was positively correlated to K-trans (r = 0.608; P = 0.004) and K-ep (r = 0.556; P = 0.001). Subsequent subtype analyses also showed positive correlations of K-trans and K-ep with MVD in adenocarcinoma group (r = 0.550 and 0.563; P = 0.012 and 0.015, respectively). No significant correlation was found between these parameters and Ki-67. Conclusion K-trans and K-ep may distinguish benign and malignant pulmonary neoplasm. K-trans and K-ep, with their positive correlation to MVD, can be used as non-invasive parameters reflecting lung cancer angiogenesis.
引用
收藏
页码:572 / 580
页数:9
相关论文
共 50 条
  • [1] Dynamic Contrast-Enhanced MRI Perfusion Parameters as Imaging Biomarkers of Angiogenesis
    Kim, Sung Hun
    Lee, Hyeon Sil
    Kang, Bong Joo
    Song, Byung Joo
    Kim, Hyun-Bin
    Lee, Hyunyong
    Jin, Min-Sun
    Lee, Ahwon
    [J]. PLOS ONE, 2016, 11 (12):
  • [2] Parameters of Dynamic Contrast-Enhanced MRI as Imaging Markers for Angiogenesis and Proliferation in Human Breast Cancer
    Li, Lin
    Wang, Kai
    Sun, Xilin
    Wang, Kezheng
    Sun, Yingying
    Zhang, Guangfeng
    Shen, Baozhong
    [J]. MEDICAL SCIENCE MONITOR, 2015, 21 : 376 - 382
  • [3] Pulmonary perfusion imaging in the rodent lung using dynamic contrast-enhanced MRI
    Mistry, Nilesh N.
    Pollaro, James
    Song, Jiayu
    De Lin, Ming
    Johnson, G. Allan
    [J]. MAGNETIC RESONANCE IN MEDICINE, 2008, 59 (02) : 289 - 297
  • [4] Correlation of Dynamic Contrast-Enhanced MRI Perfusion Parameters With Angiogenesis and Biologic Aggressiveness of Rectal Cancer: Preliminary Results
    Yeo, Dong-Myung
    Oh, Soon Nam
    Jung, Chan-Kwon
    Lee, Myung Ah
    Oh, Seong Taek
    Rha, Sung Eun
    Jung, Seung Eun
    Byun, Jae Young
    Gall, Peter
    Son, Yohan
    [J]. JOURNAL OF MAGNETIC RESONANCE IMAGING, 2015, 41 (02) : 474 - 480
  • [5] Comparison of Dynamic Contrast-Enhanced MRI and Dynamic Contrast-Enhanced CT Biomarkers in Bladder Cancer
    Naish, J. H.
    McGrath, D. M.
    Bains, L. J.
    Passera, K.
    Roberts, C.
    Watson, Y.
    Cheung, S.
    Taylor, M. B.
    Logue, J. P.
    Buckley, D. L.
    Tessier, J.
    Young, H.
    Waterton, J. C.
    Parker, G. J. M.
    [J]. MAGNETIC RESONANCE IN MEDICINE, 2011, 66 (01) : 219 - 226
  • [6] Evaluation of lung tumor perfusion by dynamic contrast-enhanced MRI
    Pauls, Sandra
    Mottaghy, Felix M.
    Schmidt, Stefan A.
    Krueger, Stefan
    Moeller, Peter
    Brambs, Hans-Juergen
    Wunderlich, Arthur
    [J]. MAGNETIC RESONANCE IMAGING, 2008, 26 (10) : 1334 - 1341
  • [7] Dynamic contrast-enhanced MRI of gastric cancer: Correlation of the perfusion parameters with pathological prognostic factors
    Joo, Ijin
    Lee, Jeong Min
    Han, Joon Koo
    Yang, Han-Kwang
    Lee, Hyuk-Joon
    Choi, Byung Ihn
    [J]. JOURNAL OF MAGNETIC RESONANCE IMAGING, 2015, 41 (06) : 1608 - 1614
  • [8] Characteristics of quantitative perfusion parameters on dynamic contrast-enhanced MRI in mammographically occult breast cancer
    Ryu, Jung Kyu
    Rhee, Sun Jung
    Song, Jeong Yoon
    Cho, Soo Hyun
    Jahng, Geon-Ho
    [J]. JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS, 2016, 17 (05): : 377 - 390
  • [9] Dynamic contrast-enhanced MRI parameters as biomarkers for the effect of vatalanib in patients with non-small-cell lung cancer
    Nensa, Felix
    Stattaus, Joerg
    Morgan, Bruno
    Horsfield, Mark A.
    Soria, Jean-Charles
    Besse, Benjamin
    Gounant, Valerie
    Khalil, Antoine
    Seng, Katja
    Fischer, Berthold
    Krissel, Heiko
    Laurent, Dirk
    Christoph, Daniel
    Eberhardt, Wilfried E. E.
    Gauler, Thomas C.
    [J]. FUTURE ONCOLOGY, 2014, 10 (05) : 823 - 833
  • [10] Dynamic contrast-enhanced MRI perfusion for differentiating between melanoma and lung cancer brain metastases
    Hatzoglou, Vaios
    Tisnado, Jamie
    Mehta, Alpesh
    Peck, Kyung K.
    Daras, Mariza
    Omuro, Antonio M.
    Beal, Kathryn
    Holodny, Andrei I.
    [J]. CANCER MEDICINE, 2017, 6 (04): : 761 - 767