Journal of Computer Assisted Tomography · 2016 · 39 citations · 25 references
MedicineOncologyRadiologyDiagnostic ImagingDiagnostic RadiologyHistopathologyDiffusion ImagingMagnetic Resonance ImagingMedical ImagingPancreatic CancerPerfusion ImagingTumor CharacterizationApparent Diffusion Coefficient AnalysisCancer ImagingDiffusion-weighted ContrastFibroblast Activation Protein ImagingHistopathologic ExaminationHistopathologic InterpretationPancreatic Cancer ImagingTumor Diffusion Imaging
OBJECTIVE: To clarify diffusion and perfusion abnormalities and evaluate correlation between apparent diffusion coefficient (ADC), MR perfusion and histopathologic parameters of pancreatic cancer (PC). METHODS: Eighteen patients with PC underwent diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Parameters of DCE-MRI and ADC of cancer and non-cancerous tissue were compared. Correlation between the rate constant that represents transfer of contrast agent from the arterial blood into the extravascular extracellular space (K, volume of the extravascular extracellular space per unit volume of tissue (Ve), and ADC of PC and histopathologic parameters were analyzed. RESULTS: The rate constant that represents transfer of contrast agent from the extravascular extracellular space into blood plasma, K, tissue volume fraction occupied by vascular space, and ADC of PC were significantly lower than nontumoral pancreases. Ve of PC was significantly higher than that of nontumoral pancreas. Apparent diffusion coefficient and K values of PC were negatively correlated to fibrosis content and fibroblast activation protein staining score. Fibrosis content was positively correlated to Ve. CONCLUSION: Apparent diffusion coefficient values and parameters of DCE-MRI can differentiate PC from nontumoral pancreases. There are correlations between ADC, K, Ve, and fibrosis content of PC. Fibroblast activation protein staining score of PC is negatively correlated to ADC and K. Apparent diffusion coefficient, K, and Ve may be feasible to predict prognosis of PC.
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Matthew Kraman, Paul Bambrough, James N. Arnold et al. · Science · 2010 · 1.1K citations
Medicine, Immunology, Oncology +17
Ahmedin Jemal, Michael J. Thun, Lynn A. G. Ries et al. · JNCI Journal of the National Cancer Institute · 2008 · 955 citations · Full text