Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging of bone marrow in healthy individuals

2011 ◽  
Vol 52 (3) ◽  
pp. 324-330 ◽  
Author(s):  
Jens Hillengass ◽  
Bram Stieltjes ◽  
Tobias Bäuerle ◽  
Fabienne McClanahan ◽  
Christiane Heiss ◽  
...  
2020 ◽  
pp. 028418512095626
Author(s):  
Lu Yang ◽  
Yuchuan Tan ◽  
Hanli Dan ◽  
Lin Hu ◽  
Jiuquan Zhang

Background The diagnostic performance of diffusion-weighted imaging (DWI) combined with dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) for the detection of prostate cancer (PCa) has not been studied systematically to date. Purpose To investigate the value of DWI combined with DCE-MRI quantitative analysis in the diagnosis of PCa. Material and Methods A systematic search was conducted through PubMed, MEDLINE, the Cochrane Library, and EMBASE databases without any restriction to language up to 10 December 2019. Studies that used a combination of DWI and DCE-MRI for diagnosing PCa were included. Results Nine studies with 778 participants were included. The combination of DWI and DCE-MRI provide accurate performance in diagnosing PCa with pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratios of 0.79 (95% confidence interval [CI] = 0.76–0.81), 0.85 (95% CI = 0.83–0.86), 6.58 (95% CI = 3.93–11.00), 0.24 (95% CI = 0.17–0.34), and 36.43 (95% CI = 14.41–92.12), respectively. The pooled area under the summary receiver operating characteristic curve was 0.9268. Moreover, 1.5-T MR scanners demonstrated a slightly better performance than 3.0-T scanners. Conclusion Combined DCE-MRI and DWI could demonstrate a highly accurate area under the curve, sensitivity, and specificity for detecting PCa. More studies with large sample sizes are warranted to confirm these results.


Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 2704-2704
Author(s):  
Jens Hillengass ◽  
Christian M Zechmann ◽  
Tobias Bäuerle ◽  
Christiane Heiss ◽  
Axel Benner ◽  
...  

Abstract The aim of the present study was to investigate whether dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) allows visualization of a change in microcirculation between healthy controls on the one side and early/advanced stages of plasma cell disease on the other. We examined a group of 222 individuals consisting of 60 patients with monoclonal gammopathy of undetermined significance (MGUS), 65 patients with asymptomatic multiple myeloma (aMM), 75 patients with newly diagnosed symptomatic MM (sMM) and 22 healthy controls with DCE-MRI of the lumbar spine. A continuous increase in the microcirculation parameter amplitude A reflecting vascular volume was detected from normal controls over MGUS and asymptomatic to symptomatic MM. Significant differences were found between controls and aMM (p = 0.03), controls and sMM (p = 0.001) and between asymptomatic and symptomatic MM (p = 0.02) respectively. While diffuse microcirculation patterns were found in healthy controls as well as MGUS and MM, a pattern with focal hot spots was exclusively detected in 42.6 % of sMM and in 3 patients with MGUS and 3 patients with aMM. Patients with MGUS and aMM with increased microcirculation patterns showed a significantly higher bone marrow plasmocytosis compared to patients with a low microcirculation pattern. Our investigations substantiate by means of a non invasive assessment of bone marrow microcirculation the concept of an angiogenic switch from early plasma cell disorders to symptomatic MM. Pathological DCE-MRI findings can be identified and correlate with an adverse prognostic parameter.


Pharmaceutics ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 212
Author(s):  
Krishnashis Chatterjee ◽  
Naciye Atay ◽  
Daniel Abler ◽  
Saloni Bhargava ◽  
Prativa Sahoo ◽  
...  

Background: Glioblastoma (GBM) is the deadliest and most common brain tumor in adults, with poor survival and response to aggressive therapy. Limited access of drugs to tumor cells is one reason for such grim clinical outcomes. A driving force for therapeutic delivery is interstitial fluid flow (IFF), both within the tumor and in the surrounding brain parenchyma. However, convective and diffusive transport mechanisms are understudied. In this study, we examined the application of a novel image analysis method to measure fluid flow and diffusion in GBM patients. Methods: Here, we applied an imaging methodology that had been previously tested and validated in vitro, in silico, and in preclinical models of disease to archival patient data from the Ivy Glioblastoma Atlas Project (GAP) dataset. The analysis required the use of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), which is readily available in the database. The analysis results, which consisted of IFF flow velocity and diffusion coefficients, were then compared to patient outcomes such as survival. Results: We characterized IFF and diffusion patterns in patients. We found strong correlations between flow rates measured within tumors and in the surrounding parenchymal space, where we hypothesized that velocities would be higher. Analyzing overall magnitudes indicated a significant correlation with both age and survival in this patient cohort. Additionally, we found that neither tumor size nor resection significantly altered the velocity magnitude. Lastly, we mapped the flow pathways in patient tumors and found a variability in the degree of directionality that we hypothesize may lead to information concerning treatment, invasive spread, and progression in future studies. Conclusions: An analysis of standard DCE-MRI in patients with GBM offers more information regarding IFF and transport within and around the tumor, shows that IFF is still detected post-resection, and indicates that velocity magnitudes correlate with patient prognosis.


Breast Care ◽  
2016 ◽  
Vol 11 (4) ◽  
pp. 254-258 ◽  
Author(s):  
Qingjun Wang ◽  
Yong Guo ◽  
Jing Zhang ◽  
Zijun Wang ◽  
Minhua Huang ◽  
...  

Background: The aim of this study was to determine whether the indicators obtained from intravoxel incoherent motion (IVIM) imaging can improve the characterization of benign and malignant breast masses compared with conventional dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted magnetic resonance imaging (DW-MRI). Patients and Methods: This study included 23 benign and 31 malignant breast masses of 48 patients. Main indicators were initial enhancement ratio (IER), time-signal intensity curve (TIC), apparent diffusion coefficient (ADC), tissue diffusivity (D), pseudodiffusivity (D*), and perfusion fraction (f). The discriminative abilities of the different models were compared by means of receiver operating characteristic (ROC) curve and area under the ROC curve (AUC) analysis. Results: D had the highest AUC (0.980), sensitivity (93.55%), specificity (100%), and diagnostic accuracy (96.36%). Both D and TIC could provide the independent predicted features for malignant breast masses. The combination of D and TIC had an AUC of up to 0.990. Conclusion: D of IVIM can effectively complement existing conventional DCE-MRI and DW-MRI in differentiating malignant from benign breast masses. IVIM combined with DCE-MRI is a robust means of evaluating breast masses.


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