• 2018-07
  • 2019-04
  • 2019-05
  • 2019-06
  • Bone marrow DCE MRI performed at diagnosis and


    Bone marrow DCE-MRI performed at diagnosis and complete remission of the acute myeloid leukemia (AML) patients, those multi-parametric data from DCE-MRI correlated significantly with treatment outcome. Three distinct parameters: peak enhancement ratio (Peak) to indicate tissue blood perfusion; amplitude (Amp) to reflect vascularity; and volume transfer constant (Ktrans) to indicate vascular permeability. The Peak and Amp decreased significantly at remission status after induction chemotherapy as compared to their initial status (Figs. 1 and 2). Patients with higher Peak or Amp at initial diagnosis (before any intervention) had shorter overall survival and disease-free survival than others. Cox multivariate analysis identified higher Peak value (hazard ratio, 9.181; 95% confidence interval, 1.740–48.437; p = 0.009) as an independent predictor for overall survival in addition to unfavorable death associated protein kinase and old age. These findings provide evidence that increased BM angiogenesis measured by DCE-MRI can predict adverse clinical outcome in AML patients and may help to select high-risk phenotype AML patients for tailored antiangiogenic therapy and to monitor treatment response. DCE-MRI may be a better alternative method than MVD in bone marrow biopsy specimens because it is non-invasive and can evaluate much bigger bone volumes, thus better representing the overall disease burden. This has prompted novel antiangiogenic approaches in AML. The current study\'s finding that DCE-MRI assessment of patients with AML with increased bone marrow angiogenesis can predict poor clinical outcome also indicates that anti-angiogenesis treatment may be beneficial for these patients. More importantly, DCE-MRI can provide noninvasive, convenient, and reproducible serial evaluations of global bone marrow angiogenesis diagnostics with only 600 s of scanning time and preparation for whole scanning only less than 20 min. This is more practical than repeated bone marrow biopsies and MVD studies. In short, DCE-MRE play an important role to help physicians both identify the most appropriate patients for antiangiogenic therapies for the best treatment results and to monitor the response to treatment. Moreover, the finding that patients receiving bone marrow transplantation survive longer than those without in the group with higher Peak value implies that bone marrow transplantation may be a therapeutic option for those with higher bone marrow angiogenesis. Further studies in more patients are needed to clarify channels point. According to the large-scale prospective study that used DCE-MRI to evaluate the functional bone marrow angiogenesis in patients with AML is a possible and convenient method achievable. The pretreatment Peak, reflecting bone marrow perfusion, and Amp, reflecting vascularity, of functional bone marrow angiogenesis MRI can predict overall survival and disease free survival of patients with newly diagnosed AML. More intriguingly, higher Peak value was an independent predictor for poor overall survival. These findings suggest that functional MRI of BM angiogenesis is a useful biomarker to predict clinical outcome of patients with AML, and tumor angiogenesis may play an important role in the pathogenesis of AML. Another study also showed that a decreasing peak enhancement ratio after induction chemotherapy was associated with a higher chance of achieving complete remission (CR), better overall survival (OS), and also disease-free survival (DFS). On the other way, the research has demonstrated that DCE-MR imaging parameters in AML patients with a CR status may be an indicator of survival and outcome and serve as an imaging biomarker for selecting risk-adapted treatment. All DCE MR imaging parameters (peak, slope, amplitude, Kep, and Kel) had a significant association with OS; however, only Kep was significantly related to RFS in the univariate analysis. Furthermore, Kep was an independent prognostic factor of OS and RFS in the multivariate.