A physiologic model of capillary-tissue exchange for dynamic contrast-enhanced imaging of tumor microcirculation

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Abstract

We present a multiple compartment, mammillary distributed-parameter model for capillary-tissue exchange, which can be implemented with dynamic contrast-enhanced imaging to study kinetic heterogeneity in tumors. The proposed n-compartment model consists of a vascular distributed-parameter compartment in direct exchange with a number (n - 1) of interstitial compartments. It is applied to a prostate tumor case study to illustrate the possible co-existence of two kinetically distinct compartments in the tumor, and the estimation of useful physiological parameters (such as perfusion, mean transit time, fractional volumes, and transfer and rate constants) associated with tissue microcirculation. The present model exhibits the convenient property of a separable impulse residue response function in time domain, which can be used to provide further insights and understanding on the physiological basis of tissue enhancement parameters commonly used for correlation studies with tumor histological diagnosis.

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Dynamic breast MR imaging: are signal intensity time course data useful for differential diagnosis of enhancing lesions?

J Gieseke, C Leutner, E Wardelmann … (1999)

To assess the relevance of the signal intensity time course for the differential diagnosis of enhancing lesions in dynamic magnetic resonance (MR) imaging of the breast. Two hundred sixty-six breast lesions were examined with a two-dimensional dynamic MR imaging series and subtraction postprocessing. Time-signal intensity curves of the lesions were obtained and classified according to their shapes as type I, which was steady enhancement; type II, plateau of signal intensity; or type III, washout of signal intensity. Enhancement rates and curve types of benign and malignant lesions were compared. There were 101 malignant and 165 benign lesions. The distribution of curve types for breast cancers was type I, 8.9%; type II, 33.6%; and type III, 57.4%. The distribution of curve types for benign lesions was type I, 83.0%; type II, 11.5%; and type III, 5.5%. The distributions proved significantly different (chi 2 = 139.6; P < .001). The diagnostic indices for signal intensity time course were sensitivity, 91%; specificity, 83%; and diagnostic accuracy, 86%. The diagnostic indices for the enhancement rate were sensitivity, 91%; specificity, 37%; and diagnostic accuracy, 58%. The shape of the time-signal intensity curve is an important criterion in differentiating benign and malignant enhancing lesions in dynamic breast MR imaging. A type III time course is a strong indicator of malignancy and is independent of other criteria.

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Modeling tracer kinetics in dynamic Gd-DTPA MR imaging

Paul Tofts (1997)

Three major models (from Tofts, Larsson, and Brix) for collecting and analyzing dynamic MRI gadolinium-diethylene-triamine penta-acetic acid (Gd-DTPA) data are examined. All models use compartments representing the blood plasma and the abnormal extravascular extracellular space (EES), and they are intercompatible. All measure combinations of three parameters; (1) kPSp is the influx volume transfer constant (min-1), or permeability surface area product per unit volume of tissue, between plasma and EES; (2) ve is the volume of EES space per unit volume of tissue (0 < ve < 1); and (3) K(ep), the efflux rate constant (min-1), is the ratio of the first two parameters (k(ep) = kPSp/ve). The ratio K(ep) is the simplest to measure, requiring only signal linearity with Gd tracer concentration or, alternatively, a measurement of T1 before injection of Gd (T10). To measure the physiologic parameters kPSp and ve separately requires knowledge of T10 and of the tissue relaxivity R1 (approximately in vitro value).