Perfusion is a fundamental biological function that refers to the delivery of oxygen and nutrients to tissue by means of blood flow. Perfusion MRI is sensitive to microvasculature and has been applied in a wide variety of clinical applications, including the classification of tumors, identification of stroke regions, and characterization of other diseases. Perfusion MRI techniques are classified with or without using an exogenous contrast agent. Bolus methods, with injections of a contrast agent, provide better sensitivity with higher spatial resolution, and are therefore more widely used in clinical applications. However, arterial spin-labeling methods provide a unique opportunity to measure cerebral blood flow without requiring an exogenous contrast agent and have better accuracy for quantification. Importantly, MRI-based perfusion measurements are minimally invasive overall, and do not use any radiation and radioisotopes. In this review, we describe the principles and techniques of perfusion MRI. This review summarizes comprehensive updated knowledge on the physical principles and techniques of perfusion MRI.

We describe a new method to allow simultaneous mapping of endothelial permeability and blood volume in intracranial lesions. The technique is based on a tumor leakage profile during the first pass (fp) of contrast bolus calculated from the time‐dependent plasma‐contrast concentration function (PCCF) in three‐dimensional (3D) T1‐weighted dynamic studies. The performance of the method has been evaluated by comparing results with those obtained from more conventional methods in patients with primary brain neoplasms. The new permeability maps (kfp) are visually compatible with those calculated using a conventional multicompartment model (ktran). Quantitatively, the new maps are free from overestimation of ktran due to first‐pass effects. The new blood volume maps, which segment out the contamination of contrast leakage, agree closely with maps derived from susceptibility studies. The new method is fast, robust, and easy to perform. The method is suitable for use in clinical environments and is likely to be of benefit where longitudinal assessment of treatment response is required. J. Magn. Reson. Imaging 2000;12:347–357. © 2000 Wiley‐Liss, Inc.

BackgroundInflammation is hypothesized to be a key event in the growth of sporadic vestibular schwannoma (VS). In this study we sought to investigate the relationship between inflammation and tumor growth in vivo using the PET tracer 11C-(R)-PK11195 and dynamic contrast enhanced (DCE) MRI derived vascular biomarkers.MethodsNineteen patients with sporadic VS (8 static, 7 growing, and 4 shrinking tumors) underwent prospective imaging with dynamic 11C-(R)-PK11195 PET and a comprehensive MR protocol, including high temporal resolution DCE-MRI in 15 patients. An intertumor comparison of 11C-(R)-PK11195 binding potential (BPND) and DCE-MRI derived vascular biomarkers (Ktrans, vp, ve) across the 3 different tumor growth cohorts was undertaken. Tissue of 8 tumors was examined with immunohistochemistry markers for inflammation (Iba1), neoplastic cells (S-100 protein), vessels (CD31), the PK11195 target translocator protein (TSPO), fibrinogen for vascular permeability, and proliferation (Ki-67). Results were correlated with PET and DCE-MRI data.ResultsCompared with static tumors, growing VS displayed significantly higher mean 11C-(R)-PK11195 BPND (−0.07 vs 0.47, P = 0.020), and higher mean tumor Ktrans (0.06 vs 0.14, P = 0.004). Immunohistochemistry confirmed the imaging findings and demonstrated that TSPO is predominantly expressed in macrophages. Within growing VS, macrophages rather than tumor cells accounted for the majority of proliferating cells.ConclusionWe present the first in vivo imaging evidence of increased inflammation within growing sporadic VS. Our results demonstrate that 11C-(R)-PK11195 specific binding and DCE-MRI derived parameters can be used as imaging biomarkers of inflammation and vascular permeability in this tumor group.

We describe a new method to allow simultaneous mapping of endothelial permeability and blood volume in intracranial lesions. The technique is based on a tumor leakage profile during the first pass (fp) of contrast bolus calculated from the time-dependent plasma-contrast concentration function (PCCF) in three-dimensional (3D) T1-weighted dynamic studies. The performance of the method has been evaluated by comparing results with those obtained from more conventional methods in patients with primary brain neoplasms. The new permeability maps (k fp ) are visually compatible with those calculated using a conventional multicompartment model (k tran ). Quantitatively, the new maps are free from overestimation of k tran due to first-pass effects. The new blood volume maps, which segment out the contamination of contrast leakage, agree closely with maps derived from susceptibility studies. The new method is fast, robust, and easy to perform. The method is suitable for use in clinical environments and is likely to be of benefit where longitudinal assessment of treatment response is required.

OBJECTIVEInflammation and angiogenesis may play a role in the growth of sporadic and neurofibromatosis type 2 (NF2)–related vestibular schwannoma (VS). The similarities in microvascular and inflammatory microenvironment have not been investigated. The authors sought to compare the tumor microenvironment (TME) in sporadic and NF2-related VSs using a combined imaging and tissue analysis approach.METHODSDiffusion MRI and high-temporal-resolution dynamic contrast-enhanced (DCE) MRI data sets were prospectively acquired in 20 NF2-related and 24 size-matched sporadic VSs. Diffusion metrics (mean diffusivity, fractional anisotropy) and DCE-MRI–derived microvascular biomarkers (transfer constant [Ktrans], fractional plasma volume, tissue extravascular-extracellular space [ve], longitudinal relaxation rate, tumoral blood flow) were compared across both VS groups, and regression analysis was used to evaluate the effect of tumor size, pretreatment tumor growth rate, and tumor NF2 status (sporadic vs NF2-related) on each imaging parameter. Tissues from 17 imaged sporadic VSs and a separate cohort of 12 NF2-related VSs were examined with immunohistochemistry markers for vessels (CD31), vessel permeability (fibrinogen), and macrophage density (Iba1). The expression of vascular endothelial growth factor (VEGF) and VEGF receptor 1 was evaluated using immunohistochemistry, Western blotting, and double immunofluorescence.RESULTSImaging data demonstrated that DCE-MRI–derived microvascular characteristics were similar in sporadic and NF2-related VSs. Ktrans (p < 0.001), ve (p ≤ 0.004), and tumoral free water content (p ≤ 0.003) increased with increasing tumor size and pretreatment tumor growth rate. Regression analysis demonstrated that with the exception of mean diffusivity (p < 0.001), NF2 status had no statistically significant effect on any of the imaging parameters or the observed relationship between the imaging parameters and tumor size (p > 0.05). Tissue analysis confirmed the imaging metrics among resected sporadic VSs and demonstrated that across all VSs studied, there was a close association between vascularity and Iba1+ macrophage density (r = 0.55, p = 0.002). VEGF was expressed by Iba1+ macrophages.CONCLUSIONSThe authors present the first in vivo comparative study of microvascular and inflammatory characteristics in sporadic and NF2-related VSs. The imaging and tissue analysis results indicate that inflammation is a key contributor to TME and should be viewed as a therapeutic target in both VS groups.

BackgroundAntiangiogenic therapy of vestibular schwannoma (VS) in type 2 neurofibromatosis can produce tumor shrinkage with response rates of 40%–60%. This study examines the predictive value of parameter-derived MRI in this setting.MethodsTwelve patients with 20 VSs were recruited. Each had at least one rapidly growing tumor. Patients were treated with bevacizumab, 5 mg/kg every 2 weeks. Patients with stable or reduced VS volume were maintained at 2.5–5 mg every 4 weeks after 6 months. Those who failed treatment had their bevacizumab discontinued. Dynamic contrast-enhanced (DCE) MRI performed prior to treatment using a high temporal resolution technique, and data were analyzed to allow measurement of contrast transfer coefficient (Ktrans), vascular fraction (vp), extravascular-extracellular fraction (ve). Relaxation rate (R1N) was measured using a variable flip angle technique. Apparent diffusional coefficient (ADC) was calculated from diffusion-weighted imaging. The predictive power of microvascular parameters and ADC were examined using logistic regression modeling.ResultsResponding tumors were larger (P < .001), had lower R1N (P < .001), and higher Ktrans (P < .05) and ADC (P < .01). They showed increases in R1N (P < .01) and reduction of Ktrans (P < .01) and ADC (P < .01). Modeling to predict response demonstrated significant independent predictive power for R1N (Β = − 0.327, P < .001), and Ktrans (Β = 0.156, P < .05). Modeling to predict percentage change in tumor volume at 90 days identified baseline tumor volume (Β = 5.503, P < .05), R1N (Β = − 5.844, P < .05), and Ktrans (Β = 5.622, P < .05) as independent significant predictors.ConclusionsIn patients with type 2 neurofibromatosis, biomarkers from DCE-MRI are predictive of VS volume response to inhibition of vascular endothelial growth factor inhibition.

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The goal of this study was to investigate the relationship between an empirical contrast kinetic parameter, the signal enhancement ratio (SER), for three-timepoint, high spatial resolution contrast-enhanced (CE) MRI, and a commonly analyzed pharmacokinetic parameter, k ep , using dynamic high temporal resolution CE-MRI. Computer simulation was performed to investigate: 1) the relationship between the SER and the contrast agent concentration ratio (CACR) of two postcontrast timepoints (t p1 and t p2 ); 2) the relationship between the CACR and the redistribution rate constant (k ep ) based on a two-compartment pharmacokinetic model; and 3) the sensitivity of the relationship between the SER and k ep to native tissue T 1 relaxation time, T 10 , and to errors in an assumed vascular input function. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has become a method increasingly used for evaluating breast tumors. Signal enhancement on T 1 -weighted DCE-MRI can be assessed in two ways by using either a semiquantitative method to estimate signal intensity changes or a pharmacokinetic model to quantify changes of tissue contrast agent (CA) concentration (1). Pharmacokinetic model-based analysis of breast DCE-MRI data (2-9) has the advantages of providing parameters related to the changes in perfusion and vessel permeability of the microcirculation and allowing cross-comparison between different sites. However, compromises have to be made trading imaging spatial resolution, which is critical for detecting small features of breast lesions, for high temporal resolution, which is necessary for performing pharmacokinetic analysis. In addition, the native tissue T 1 relaxation time (T 10 ) and vascular input function (VIF) are required for the calculation of perfusion and vessel permeability (10). Establishing robust methods to rapidly measure T 10 and incorporating local VIF into kinetic modeling remain as challenges in model-based breast DCE-MRI.High spatial resolution imaging is advantageous for depicting the heterogeneous microvascular network in breast cancers using parametric methods (11-15). As the importance of tumor morphology for making a correct diagnosis is increasingly being recognized, images with high spatial resolution and high signal-to-noise ratio (SNR) are much more desired over those with high temporal resolution, but low spatial resolution and low SNR in breast MRI. Previous studies have utilized high spatial resolution threedimensional (3D) DCE-MRI with relatively low temporal resolution, e.g., 60 -90 sec/frame (12). Methods based on three-timepoint examination consisting of one pre-and two postcontrast scans are commonly used in clinical studies (11,16,17) to evaluate morphological changes of breast lesion, using high spatial resolution 3D imaging with a typical isotropic pixel size of 1 ϫ 1 ϫ 1 mm covering the entire symptomatic breast or both breasts. Furthermore, our group has utilized such a three-timepoint acquisition strategy to calculate high spatial resolution maps of a semiquantit...