Dynamic contrast‐enhanced MRI of neuroendocrine hepatic metastases: A feasibility study using a dual‐input two‐compartment model

Abstract

Neuroendocrine hepatic metastases exhibit various contrast uptake enhancement patterns in dynamic contrast-enhanced MRI. Using a dual-input two-compartment distributed parameter model, we analyzed the dynamic contrast-enhanced MRI datasets of seven patient study cases with the aim to relate the tumor contrast uptake patterns to parameters of tumor microvasculature. Simulation studies were also performed to provide further insights into the effects of individual microcirculatory parameter on the tumor concentration-time curves. Although the tumor contrast uptake patterns can be influenced by many parameters, initial results indicate that hepatic blood flow and the ratio of fractional vascular volume to fractional interstitial volume may potentially distinguish between the patterns of neuroendocrine hepatic metastases. Key words: neuroendocrine hepatic metastases; DCE MRI; tracer kinetics modeling Neuroendocrine tumors are a rare and heterogeneous group of hormone-secreting neoplasms that arise from neoplastic proliferation of enterochromaffin or Kulchitsky cells of the neuroendocrine system (1,2). Primary tumors can occur in various organs, predominantly in the gastrointestinal tract, pancreas, and lung. Despite their relatively low incidence, neuroendocrine tumors pose a significant clinical challenge due to their varied presentations and the primary tumor is often revealed through detection of metastases (2).Although neuroendocrine hepatic metastases have been described as predominantly hypervascular (1), in practice various contrast uptake enhancement patterns have been observed in dynamic contrast-enhanced (DCE) MRI, possibly due to their heterogeneous histology from diverse locations of origin. Apart from the usual contrast uptake pattern of rapid increase followed by rapid washout commonly associated with hypervascular hepatic lesions, neuroendocrine hepatic metastases can exhibit a spectrum of other contrast uptake behavior ranging from a progressively increasing pattern (within a few minutes following bolus administration of contrast medium) to patterns with an initial moderate increase followed by either a plateau, gradual increase or decrease.Although there are considerable interests in studying the various shapes of tumor contrast uptake patterns, the physiological basis of these patterns has remained unclear. Tracer kinetics analysis of these tumor contrast uptake patterns may provide insights into the differences in tumor microvasculature that result in these patterns. We aim to study the various contrast uptake patterns of neuroendocrine hepatic metastases and relate these patterns to tumor microcirculatory parameters derived from tracer kinetics modeling. MATERIALS AND METHODS Tracer Kinetics ModelingTracer kinetics modeling of the liver is uniquely challenging in two ways: (i) The liver has a dual blood supply derived from the hepatic artery and portal vein. (ii) Normal liver sinusoids are fenestrated, which allow free access of low-molecular weight compounds (including conventional gadolinium-bas...

Fundamentals of tracer kinetics for dynamic contrast‐enhanced MRI

“…However, the interstitial compartment (EES) may have a larger radial dimension (compared with its axial dimension) without a radial concentration gradient, and can be regarded as largely homogeneous. The impulse residue function for DP2 model can be given by two physiologic phases (63)(64)(65)(66)(67)(68)(69):…”

“…Also, by setting E or PS ¼ 0, the single-(vascular) compartment DP model, R DP1 (t), is simply given by R p (t). The physiological meaning of the two transport phases can be explained as follows (63)(64)(65)(66)(67)(68)(69). During the initial vascular transit phase 0<t<t p , R p (t) is a constant (unity) reflecting the fact that the total amount (100%) of tracer in the injected bolus is residing in the tissue, although a portion of the tracer could diffuse from the IVPS into EES.…”

Prognostication and response assessment in liver and pancreatic tumors: The new imaging

“…DCE-MRI has been tested for PanNETs staging. Koh et al [75] found three different patterns of contrast enhancement for neuroendocrine hepatic metastases, with specific perfusional parameters. DCE-MRI is therefore potentially able to categorize metastases on the basis of their vascular characteristics, with prognostic and therapeutic consequences.…”

Multiple-pathway modeling of tumor blood flow for dynamic contrast-enhanced imaging

“…Immediately after t cap , the tracer that was not extracted and remains in the vascular space exits through plug flow, which results in a sudden decrease in R(t). A more gradual decrease in R(t) follows as the extracted portion diffuses back into the vascular space and is cleared by blood outflow [1,12,[14][15][16]. For a weighted sum of N pathways, the number of discontinuities is repeated N times.…”