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(Radiology. 1999;213:265-272.)
© RSNA, 1999

Experimental Studies

Prostate Cancer Tumor Grade Differentiation with Dynamic Contrast-enhanced MR Imaging in the Rat: Comparison of Macromolecular and Small-Molecular Contrast Media-Preliminary Experience1

Axel Gossmann, MD 2, Yoshitaka Okuhata, MD, David M. Shames, MD, Thomas H. Helbich, MD, Timothy P. L. Roberts, PhD, Michael F. Wendland, PhD, Sabine Huber, MD and Robert C. Brasch, MD

1 From the Department of Radiology, Contrast Media Laboratory, University of California, San Francisco, Box 0628, 513 Parnassus Ave, San Francisco, CA 94143-0628. Received October 6, 1998; revision requested December 14; revision received December 28; accepted April 8, 1999. Address reprint requests to R.C.B.


   Abstract
TOP
 Abstract
Introduction
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
PURPOSE: To differentiate prostate cancers of different histopathologic grades with dynamic gadolinium-enhanced magnetic resonance (MR) imaging. Results with a conventional small-molecular contrast medium (CM) were compared to those with a prototypic macromolecular CM.

MATERIALS AND METHODS: High- and low-grade tumors, sublines of the Dunning R3327 rat prostate cancer line, were subcutaneously implanted into the flanks of 12 male Copenhagen rats. Dynamic contrast material–enhanced MR imaging was performed with small-molecular CM and macromolecular CM at an interval of 1 day. Microvascular permeability, as estimated with the endothelial transfer coefficient, and fractional plasma volume were calculated for each tumor and each CM by means of a two-compartmental, bidirectional kinetic model.

RESULTS: Mean endothelial transfer coefficient values for both macromolecular CM and small-molecular CM were significantly different between the two tumor sublines (P = .0004 and P = .01, respectively). For the high- and low-grade tumors, no overlap of values was seen with macromolecular CM, but a broad overlap was seen with small-molecular CM despite a significant difference in mean values.

CONCLUSION: Dynamic contrast-enhanced MR imaging permits differentiation of histopathologic prostatic tumor types. Quantitative microvascular permeability characteristics estimated from macromolecular CM–enhanced data were significantly superior to those derived from small-molecular CM–enhanced data.

Index terms: Gadolinium • Magnetic resonance (MR), contrast media, 844.121412, 844.12143 • Prostate, MR, 844.121412, 844.12143 • Prostate, neoplasms,844.32


   Introduction
TOP
 Abstract
 Introduction
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
In American men, prostate cancer is currently the most common malignancy and the second most lethal cancer (1). Increased screening with more sensitive diagnostic tests is resulting in early detection of a greater number of incidental prostatic carcinomas. It is known that more than 30% of men older than 50 years have microscopic prostatic carcinoma at autopsy (2), yet fewer than 10% of men develop clinical prostate cancer in their lifetime (3). These observations suggest that the majority of prostate cancers do not progress. Furthermore, a dilemma in the management of prostate cancer is that clinically nonaggressive cancers do not require aggressive treatment whereas highly aggressive cancers requiring active intervention cannot be easily identified (4). Thus, reliable methods are needed to define the malignant, aggressive potential of an individual prostatic carcinoma.

Pathologic stage and histopathologic tumor grade are the most accurate predictors of prognosis for prostate cancer (5). Both factors strongly influence patient treatment and outcome (6–9). Magnetic resonance (MR) imaging is considered a useful tool for the staging of prostate cancer (10), but MR imaging has not been shown to provide any direct information about the histopathologic tumor grade. The majority of prostate cancers are diagnosed and graded by means of needle biopsy. However, owing to intratumoral heterogeneity of prostate cancer, findings at needle biopsy frequently result in underestimation of the histopathologic tumor grade (ie, Gleason score) assigned to prostatectomy specimens (4,9,11). Noninvasive techniques for accurate grading of prostatic tumors, therefore, would help assignment of individual patients to appropriate therapeutic regimens and might reduce the need for invasive procedures.

Our primary aim in this study was to show the potential for gadolinium-enhanced MR imaging to help differentiate prostate cancers with different histopathologic grades. We hypothesized that estimates of permeability based on dynamic contrast material–enhanced MR imaging data should allow reliable differentiation of low- from high-grade prostate cancers. Furthermore, because reported studies have consistently demonstrated selective hyperpermeability of tumor microvessels to macromolecular solutes (12,13), dynamic MR imaging data obtained with macromolecular contrast medium (CM) should help differentiate tumor grade more accurately than should data obtained with small-molecular CM, which readily diffuse across endothelium of normal and neoplastic microvessels. In this study, results with a prototypic macromolecular CM were compared to those with a conventional small-molecular CM in the same prostate cancer–bearing rodents.


   MATERIALS AND METHODS
TOP
 Abstract
 Introduction
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 References
 
Animal and Tumor Models
This study was conducted with the approval of the institutional committee for animal research and conformed to the guidelines of the National Institutes of Health for the care and use of laboratory animals. The Dunning R3327 rat prostate cancer line is a well-studied model system and offers a broad spectrum of tumor characteristics in its sublines (14). We chose two well-characterized sublines, MAT-LyLu and PAP (Isaacs JT, Johns Hopkins Oncology Center, Baltimore, Md).

The MAT-LyLu subline is anaplastic carcinoma that shows no indication of glandular function. It produces little stromal tissue, and focal necrosis can often be observed. The doubling time of the MAT-LyLu tumor type is 1.5 to 1.8 days, uninfluenced by the androgen status of the host. Lymph node and lung metastases are grossly detectable at autopsy (15). In contrast, the PAP subline is a well-differentiated adenocarcinoma composed of tumor acini containing both glandular and basal tumor cells surrounded by a continuous basement membrane. Between the multiple tumor acini is well-developed stromal tissue that composes 30%–40% of the total tumor volume. This androgen-sensitive tumor grows with a doubling time of 10–14 days and rarely metastasizes. When grown subcutaneously, PAP tumors are well encapsulated, vascular, and moderately soft (16). Thus, the two tumor lines have markedly different characteristics.

Twelve 60-day-old male Copenhagen rats (Harlan, Indianapolis, Ind) were assigned randomly to two groups. Fragments of approximately 10 mm3 of either MAT-LyLu or PAP tumors were subcutaneously implanted bilaterally in the flanks of each animal with a 16-gauge bone marrow aspiration needle (Sherwood, Davis, and Geck, St Louis, Mo). Tumors were allowed to grow to approximately 1.0–1.5 cm in diameter before MR imaging was performed. Typically, MAT-LyLu tumors were imaged 8–9 days after implantation, whereas the less aggressive PAP tumors were imaged after 150–175 days.

Anesthesia
Tumor implantation was performed with light anesthesia by means of inhalation of halothane (Wyeth-Ayerst, Philadelphia, Pa). Before MR imaging, pentobarbital (50 mg per kilogram of body weight) (Abbott Laboratories, North Chicago, Ill) was injected intraperitoneally. For CM injection during MR imaging, a 23-gauge butterfly cannula (Abbott Laboratories) was inserted into a tail vein of each animal.

Small-Molecular CM and Macromolecular CM
Small-molecular CM (gadopentetate dimeglumine, Magnevist; Berlex Laboratories, Wayne, NJ) was administered in a dose of 0.1 mmol per kilogram of body weight. This compound has been used extensively in clinical practice. It is a representative conventional small-molecular CM with a molecular mass of 547 d and a distribution volume of 0.266 L/kg, approximating the extracellular fluid volume (17,18).

A prototypic macromolecular CM for MR imaging, albumin gadolinium diethylenetriaminepentaacetic acid 30, was prepared in our laboratory as described by Ogan et al (19). It was administered in a dose of 0.03 mmol/kg. Because of the increased relaxation potency of gadolinium in the macromolecule compared with that in the small-molecular CM, this lower dose gives approximately equal initial blood enhancement. As a well-characterized blood-pool CM, this macromolecule produces nearly constant enhancement of blood and normal tissues for more than 60 minutes after injection (20). It has a molecular mass of 92,000 d, a volume of distribution of about 0.05 L/kg, which closely approximates the blood volume, and a plasma half-life of approximately 31/2 hours in rats (19,20).

MR Imaging
MR imaging was performed with a 2-T system (Omega CSI-II; Bruker Instruments, Fremont, Calif) equipped with self-shielded gradient coils (Acustar S-150) (±20 G/cm, 15-cm inner diameter). Animals were placed supine in a birdcage radio-frequency coil that was 7.6 cm long and had an inner diameter of 5.0 cm. A phantom containing dilute small-molecular CM was included in the field of view, close to each animal.

Tumors were examined at MR imaging with a T1-weighted, three-dimensional, spoiled gradient-refocused acquisition in a steady state (SPGR) sequence. Three-dimensional SPGR images were obtained with the following parameters: repetition time msec/echo time msec of 50/1.4, one signal acquired, 90° flip angle, 128 x 128 x 16 matrix, 3-mm section thickness, 50 x 50 x 48-mm field of view, and acquisition time of 1 minute 42 seconds per volume of 16 sections. Precontrast longitudinal relaxation rates (R1 = 1/T1) were calculated on the basis of a set of seven similar SPGR images obtained with repetition times that varied between 50 and 3,200 msec. To monitor macromolecular CM enhancement, three initial precontrast images and 30 dynamic postcontrast images (obtained with a fixed repetition time of 50 msec) were acquired during 1 hour.

Small-molecular CM has a rapid biodistribution and therefore requires imaging with a higher temporal resolution. With a "keyhole" technique (21,22), the acquisition rate was increased fourfold during the first 10 minutes after injection of CM. First, a baseline high-spatial-resolution, three-dimensional SPGR image was acquired with the parameters described previously. Subsequently, dynamic images were acquired with a reduced matrix (128 x 64 x 8) before, during, and for 10 minutes after rapid injection of a bolus of small-molecular CM. Acquisition of each three-dimensional data set required approximately 30 seconds. Six precontrast images were substituted into a precontrast reference full-matrix data set, and 20 postcontrast images were substituted into a postcontrast reference full-matrix data set (22). After the 10-minute keyhole data acquisition, 15 additional postcontrast three-dimensional SPGR images were acquired with a matrix of 128 x 128 x 16 at 2-minute intervals for a total study duration of 40 minutes.

Animals were imaged on consecutive days. Small-molecular CM was administered on day 1, and macromolecular CM was administered on day 2. Signal intensity values in blood and tumor were noted to return to baseline values in each animal prior to administration of the second CM.

Image and Data Analysis
All MR image data were transferred to a workstation (SunSparc 10; Sun Microsystems, Mountain View, Calif). Signal intensity values for each time point were obtained in regions of interest defined by one of our group (A.G.) in the areas that were most enhanced within the individual tumor masses. Three to five regions of interest (a minimum of 30 pixels per region) over several different anatomic image sections were evaluated with an image analysis program (MRVision, Menlo Park, Calif). Additionally, signal intensity was measured in the inferior vena cava (in the central sections of the volume and in the middle of the vessel to minimize inflow and partial volume effects) and in a gadolinium phantom in the field of view.

The mean signal intensity value in the tumor and the inferior vena cava blood were corrected for spectrometer variation over time by dividing their signal intensities at each time point by the signal intensities of the phantom. Precontrast estimates of R1 for tumors were obtained by means of curve fitting on the basis of seven nonenhanced SPGR images obtained with repetition times from 50 to 3,200 msec. The precontrast R1 value for inferior vena cava blood was assumed to be 0.752 (1/1.33) according to previous measurements (23). Postcontrast R1 values can be calculated on the basis of signal intensity and knowledge of precontrast R1 values (23,24). The change in R1 ({Delta}R1) between the postcontrast R1 value at each time point and the precontrast R1, {Delta}R1(t), is taken to be directly proportional to the local gadolinium concentration in tissue at time t (25,26).

Our techniques for determining the fractional plasma volume of the tumor tissue (in milliliters per cubic centimeter of tissue) and the permeability of the tumor tissue to a particular CM, as estimated with the endothelial transfer coefficient (in milliliters per minute per 100 cubic centimeters of tissue), have been reported in detail elsewhere (27). Briefly, a compartmental model of capillary permeability was fitted to the {Delta}R1(t) data from the inferior vena cava and tumor after the former was corrected for hematocrit, assuming a value of 0.42 (28). The {Delta}R1(t) from the inferior vena cava, fitted by means of a monoexponential function for macromolecular CM and a triexponential function for small-molecular CM, served as forcing functions for the tumor tissue model, which had a two-compartmental structure corresponding to plasma and interstitial water spaces. Reflux of CM from the interstitial water compartment back to the plasma compartment of the tumor tissue was resolvable with the small-molecular CM but not with the macromolecular CM. The model was fitted to the data by means of software (SAAM II; SAAM Institute, Seattle, Wash), and the precision of the parameter estimates was determined from the covariance matrix at the least squares fit.

Histopathologic Analysis
Immediately after MR imaging, animals were sacrificed by means of an intravenous overdose of pentobarbital and bilateral thoracotomy. Tumors were resected, fixed in 10% formalin, and sectioned in the same plane as the MR images for histopathologic analyses. Conventional hematoxylin-eosin staining was performed in all tumors for assessment of histopathologic grade.

Statistical Analysis
The mean values of fractional plasma volume and endothelial transfer coefficient for the PAP and MAT-LyLu tumors were compared for each CM by means of a two-tailed t test. A P value less than .05 for the null hypothesis was assigned statistical significance.


   RESULTS
TOP
 Abstract
 Introduction
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 References
 
Eleven highly aggressive, rapidly growing MAT-LyLu tumors and six minimally aggressive, slowly growing PAP tumors were developed in each group of six rats. Consistent with the histopathologic findings, highly aggressive tumors typically enhanced heterogenously with either CM, with the highly vascular rim enhancing more than the partly vascular, partly necrotic tumor core (Fig 1a, 1b), as seen at histopathologic examination. In contrast, minimally aggressive tumors showed a more homogeneous enhancement with either CM (Fig 1c, 1d), consistent with a more homogeneous vascularization and absence of necrotic areas at histopathologic examination.



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  		Figure 1. Representative T1-weighted SPGR images of subcutaneous prostatic tumors. (a-d) Clusters of four images depict each combination of tumor type and CM; in each cluster the images are arranged temporally, precontrast (top left), followed by 1-minute (top right), 30- or 10-minute (lower left), and 60- or 30-minute (lower right) postcontrast images. CM performance can be compared between horizontal clusters, while tumor enhancement patterns with a given agent can be compared vertically between clusters. (a, b) Images were obtained on successive days in the same high-grade MAT-LyLu tumor enhanced with the macromolecular CM (0.03 mmol/kg)(left) and with the small-molecular CM (0.1 mmol/kg) (right). (c, d) Images were obtained on successive days in the same low-grade PAP tumor enhanced with the macromolecular CM (left) and with the small-molecular CM (right) with the same doses as in a and b. Note that enhancement of the subcutaneously implanted tumors (arrows) tends to increase gradually with the macromolecular CM, reflecting diffusion of the agent from blood into the interstitial space, whereas enhancement with the small-molecular CM tends to decline after the 1-minute image owing to rapid transendothelial diffusion and rapid renal elimination of these relatively small molecules. Also, note that with both macromolecular CM and small-molecular CM, the more aggressive and rapidly growing MAT-LyLu tumor enhances more strongly than does the low-grade PAP tumor.

 
Figure 2 shows representative {Delta}R1 data for macromolecular CM enhancement of venous blood and MAT-LyLu and PAP tumors with the respective fits of the model to these data. All {Delta}R1 values from MAT-LyLu tumors increased substantially over time, whereas those from venous blood declined (Fig 2, A); this is indicative of a substantial microvascular leak with progressive accumulation of CM in the interstitial space of the tumor. In contrast, {Delta}R1 values for PAP tumors were noted either to increase slightly, to not change, or to decrease slightly over time whereas, again, venous blood {Delta}R1 response declined (Fig 2, B), which indicates a less pronounced microvascular leak than was seen in the MAT-LyLu tumors.



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  		Figure 2. A, B, Graphs depict typical least squares fit (solid lines) of the model to {Delta}R1 measures from dynamic MR imaging data obtained in blood in the inferior vena cava ({bigtriangleup}) and tumor ({bigcirc}) after intravenous bolus administration of macromolecular CM into rats bearing MAT-LyLu (A) and PAP (B) tumors. On both plots, note the relative convergence of the blood and tumor responses, which suggests that CM is moving gradually from the blood into the tumor interstitial space. The absence of convergence in these plots indicates the absence of a microvascular leak. Note also the converging response is more rapid, indicating more leakiness, in the more aggressive MAT-LyLu tumor.

 
Figure 3 shows representative {Delta}R1 data sets with their respective model fits after injection of small-molecular CM. Both MAT-LyLu (Fig 3, A) and PAP (Fig 3, B) tumor {Delta}R1 responses increased significantly during the initial 2–3 minutes. The {Delta}R1 values of MAT-LyLu tumors were characterized by a slightly steeper initial slope than was seen in PAP tumors. After about 5–10 minutes, however, tumor response profiles of both tumor sublines paralleled the response of the blood in the inferior vena cava, indicating a rapid transendothelial equilibration of this agent.



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  		Figure 3. A, B, Graphs depict the typical least squares fit (solid lines) of the model to {Delta}R1 measures from dynamic MR imaging data obtained in blood in the inferior vena cava ({bigtriangleup}) and tumors ({bigcirc}) after intravenous bolus administration of small-molecular CM into rats bearing MAT-LyLu (A) and PAP (B) tumors. The general shapes of these responses in blood and tumor are similar for the two tumor types with the small-molecular CM.

 
The bidirectional two-compartmental model (reflux equals 0 for macromolecular CM and greater than 0 for small-molecular CM) fit the data well for each study. The parameter values of our model were well determined with small uncertainty estimates (coefficient of variation, <=35%). The Table shows values for the fractional plasma volume and endothelial transfer coefficient of each CM in each tumor with their respective uncertainty estimates. Mean endothelial transfer coefficient values for macromolecular CM (0.065 mL/min/100 cm3 ± 0.015 [mean ± SD] in MAT-LyLu tumors vs 0.025 mL/min/100 cm3 ± 0.015 in PAP tumors) and small-molecular CM (9.28 mL/min/100 cm3 ± 3.65 in MAT-LyLu tumors vs 5.56 mL/min/100 cm3 ± 1.33 in PAP tumors) were significantly different between the two tumor sublines. However, mean endothelial transfer coefficient values for macromolecular CM between the PAP and MAT-LyLu tumors yielded a more significant difference (P = .0004) than those for small-molecular CM (P = .01). Furthermore, as seen in Figure 4a, no overlap was found between the endothelial transfer coefficient values of the two tumor sublines with macromolecular CM (0.0–0.039 mL/min/100 cm3 for PAP tumors vs 0.040–0.088 mL/min/100 cm3 for MAT-LyLu tumors), which potentially allows a threshold to be defined. With small-molecular CM, however, a substantial overlap was noted between the endothelial transfer coefficient values of slowly growing and highly aggressive tumors (4.25–8.05 mL/min/100 cm3 for PAP tumors vs 5.72–17.75 mL/min/100 cm3 for MAT-LyLu tumors) (Fig 4b). Differences in differentiation of the histopathologic grade of prostate cancers for either CM were not significant on the basis of fractional plasma volume (P > .35).


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  		Fractional Plasma Volumes and Endothelial Transfer Coefficients in Prostate Carcinoma Sublines
 


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  		Figure 4a. Scattergrams of endothelial transfer coefficient (KPS) values (in milliliters per minute per cubic centimeter of tissue) for low-grade (PAP) and high-grade (MAT-LyLu) prostatic tumors obtained from (a) macromolecular CM and (b) small-molecular CM data with a simple two-compartmental tissue model. Suggested thresholds are drawn (straight line) between the values for the different tumor types. No overlap of permeability estimates between the tumors of different grades is observed in a, whereas a considerable overlap of values is observed in b. As might be anticipated, the values are much higher with the small-molecular CM.

 


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  		Figure 4b. Scattergrams of endothelial transfer coefficient (KPS) values (in milliliters per minute per cubic centimeter of tissue) for low-grade (PAP) and high-grade (MAT-LyLu) prostatic tumors obtained from (a) macromolecular CM and (b) small-molecular CM data with a simple two-compartmental tissue model. Suggested thresholds are drawn (straight line) between the values for the different tumor types. No overlap of permeability estimates between the tumors of different grades is observed in a, whereas a considerable overlap of values is observed in b. As might be anticipated, the values are much higher with the small-molecular CM.

 

   DISCUSSION
TOP
 Abstract
 Introduction
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
References
 
In clinical practice, the greatest merit of MR imaging for prostate cancer has been in local staging (29,30). For this purpose, small-molecular CM enhancement does not add substantial diagnostic information and is not routinely used (29,31–33). The tumor grade, however, is another important prognostic variable that can be addressed in the imaging evaluation of prostate cancer (5) and can strongly influence patient treatment and outcome (5–8,34). With use of dynamic contrast-enhanced MR imaging, we developed a technique for quantitative assessment of capillary permeability and fractional plasma volume of various solid tissues (35). This technique has already shown potential for determining the histopathologic tumor grade in mammary carcinomas (27). The results of the current study indicate that dynamic contrast-enhanced MR imaging can also significantly and noninvasively help differentiate different grades of prostate cancer. Permeability measures (as estimated with the endothelial transfer coefficient) generated with the prototypic macromolecular CM were shown to be superior to those generated with a clinically available, widely employed small-molecular CM. Estimates of tumor fractional plasma volume derived with either CM failed to significantly help differentiate tumor grade.

Prostatic carcinomas are usually diagnosed and histopathologically graded on the basis of tissue obtained at needle biopsy or transurethral resection of the prostate (11). There are conflicting data, however, concerning the reliability of biopsy specimens as indicators of the tumor grade for the entire primary tumor. Studies have shown that a difference of at least two units between the Gleason scores from a prostatic biopsy specimen and from the subsequent radical prostatectomy specimen occurs in 28%–48% of cases (36,37). Differences are inevitable between the histopathologic appearance of small portions of prostatic neoplasms obtained at biopsy and large volumes of tumor available from prostatectomy specimens owing to the histopathologic heterogeneity of individual prostatic carcinomas (11). A noninvasive MR imaging method for grading prostate cancer may prove superior to the biopsy method in that tumor sampling with MR imaging is more complete. In our technique, a three-dimensional SPGR data acquisition permits broad anatomic multisection coverage of the entire tumor. Analysis of MR imaging data obtained in several different anatomic image sections provides information about the whole tumor and is therefore less subject to sampling errors.

Several studies have addressed the use of gadolinium chelates in the staging of prostate cancer (31–33,38–41). In a recent study, Jager et al (38) evaluated dynamic small-molecular CM–enhanced MR imaging with a turbo fast low-angle shot, or FLASH, subtraction technique. Their findings indicate that prostate cancer shows an early enhancement, but, unlike our results, the authors were not able to find any quantitative measure from their data that allowed differentiation of benign from malignant prostatic tissue. In contrast, our study was especially designed to grade prostatic tumors with a kinetic model of CM permeability across tumor microvessels. To our knowledge, this the first demonstration of a significant correlation between dynamic contrast-enhanced MR imaging data and prostatic tumor grades.

Vigneron et al (42) recently described another promising approach to the noninvasive grading of prostate cancer with MR spectroscopy. The authors found a significant correlation between elevated choline resonances and histopathologic grade in 26 human prostate cancers. Their method of tumor grade differentiation is based on chemical characteristics, whereas our contrast-enhanced method relies on a physiologic variable, tumor vessel permeability. The two methods may be complementary.

Findings in the present study support our hypothesis that estimates of permeability obtained with the macromolecular CM are superior to those obtained with the small-molecular CM for determining tumor grade. The hyperpermeability to macromolecules of malignant tumor vessels has been shown repeatedly (12,13). In contrast, a selective hyperpermeability in neoplastic tissues has not been demonstrated for molecules smaller than 1,000 d, with the exception of some tumors in the central nervous system. For this study, we chose a macromolecular blood-pool CM with previously demonstrated low permeability through normal vascular endothelium and usefulness for the estimation of tissue blood volume and tumor microvascular permeability (23,27,35). We compared results with this prototypic macromolecular CM to those with a clinically available small-molecular CM, gadopentetate dimeglumine. The latter is poorly suited to provide information on the hyperpermeability of neoplastic microvessels owing to its quick equilibration between the intravascular and interstitial spaces in normal tissues.

Such high transendothelial diffusion rates limit the potential of small molecules for quantitative estimation of fractional blood volume and abnormal capillary permeability, exclusive of central nervous system tissues (18,20,43). Despite this limitation, the mean value of endothelial transfer coefficient for small-molecular CM was significantly smaller in the relatively less aggressive PAP tumors than that in the highly aggressive MAT-LyLu tumors. However, considerable overlap in endothelial transfer coefficient values for the two tumor types was found with small-molecular CM. Such overlap in endothelial transfer coefficient values was not found with the macromolecular CM, which exhibits a considerably smaller leak from the intravascular to the interstitial space (about 100–200 times smaller than that for small-molecular CM).

Currently, large water-soluble, highly paramagnetic molecules such as the macromolecular CM are not available for clinical use; however, macromolecular CM development is being pursued broadly in the pharmaceutical industry, and at least two compounds in this class, cascade polymers (Schering, Berlin, Germany) and MS-325 (Epix Medical, Cambridge, Mass), have recently entered clinical trials (44,45). It is too early to predict which agent or agents will emerge from clinical development with desired properties of high tolerance and easily demonstrable hyperpermeability across tumor endothelium. Recognition of the potential for substantial clinical benefit, as indicated by the present data, may hasten macromolecular CM development.

Because of its rapid 30-second acquisition rate, the keyhole three-dimensional SPGR technique used to acquire our imaging data might have introduced errors that would not appear in full-matrix three-dimensional SPGR data sets (21,22). To examine for this possibility, two small-molecular CM data sets were processed as both conventional SPGR data and again as keyhole data. The maximum difference in signal intensity was only 1% (unpublished data), which was not considered important to data interpretation.

Conclusions from our data are limited in several ways. Results from a subcutaneous prostate cancer model may not apply directly to human neoplasms. Only two different tumor types, high- and low-grade carcinomas, were evaluated. An overlap of permeability estimates with the macromolecular CM might have been found if a greater number of different tumor types, with a broader range of aggressiveness, had been investigated. Tumors were examined at only a single point in their growth, at approximately 1.5 cm in diameter, and microvascular characteristics may differ as a function of time and tumor size.

Finally, it is possible that some of the larger estimates of endothelial transfer coefficient in the MAT-LyLu tumors with small-molecular CM may be underestimated owing to the limited temporal resolution of our data (30 seconds). If so, the degree of significance of differences in the mean values of endothelial transfer coefficient for small-molecular CM in the PAP and MAT-LyLu tumors would be underestimated. Nevertheless, the overlap at lower values of endothelial transfer coefficient between the two tumor types with small-molecular CM would still be present (Table). Consequently, our conclusion would be unaltered that the macromolecular CM affords better separation of the relatively benign PAP and more aggressive MAT-LyLu prostatic tumors than does small-molecular CM.

Practical application: These limitations notwithstanding, the data in this study support the hypothesis that dynamic contrast-enhanced MR imaging with the macromolecular CM can significantly and noninvasively help differentiate histopathologic prostatic tumor grades. Quantitative characteristics of microvascular permeability estimated from the macromolecular CM data by means of a simple two-compartmental tumor tissue model were shown to be superior to estimates similarly derived with small-molecular CM. The grading of tumors at MR imaging on the basis of their microvascular hyperpermeability to macromolecular CM may provide a new and clinically useful method to determine the malignant potential of prostatic tumors. Such noninvasive tumor characterization could help define individual patient prognosis and better assign patients to alternative treatment programs. Tumors defined as "aggressive" could be treated aggressively, and vice versa.


   Footnotes
 
2 Current address: Department of Radiology, University of Cologne, Germany. Back

Abbreviations: CM = contrast medium {Delta}R1 = change in R1 SPGR = spoiled gradient-refocused acquisition in a steady state

Author contributions: Guarantor of integrity of entire study, R.C.B.; study concepts, R.C.B., Y.O., A.G.; study design, R.C.B., A.G., Y.O., M.F.W.; definition of intellectual content, R.C.B., A.G., Y.O., T.P.L.R., M.F.W.; literature research, S.H.; experimental studies, A.G., Y.O., T.H.H.; data acquisition, A.G., Y.O., T.H.H., M.F.W.; data analysis, D.M.S., A.G., T.P.L.R.; statistical analysis, D.M.S., A.G.; manuscript preparation, A.G.; manuscript editing, D.M.S., T.P.L.R.; manuscript review, R.C.B.


   References
TOP
 Abstract
 Introduction
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 

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