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(Radiology. 2001;218:556-561.)
© RSNA, 2001

Experimental Studies

Early Changes in Liver Perfusion Caused by Occult Metastases in Rats: Detection with Quantitative CT1

Charles A. Cuenod, MD, PhD, Isabelle Leconte, MD, Nathalie Siauve, MD, PhD, Arnaud Resten, MD, Clarisse Dromain, MD, Bruno Poulet, MD, Frédérique Frouin, PhD, Olivier Clément, MD, PhD and Guy Frija, MD

1 From the Institut National de la Santé et de la Recherche Médicale (INSERM) U494, Paris, France (C.A.C., N.S., F.F., O.C., G.F.); and the Departments of Radiology (C.A.C., I.L., N.S., A.R., C.D., O.C., G.F.) and Pathology (B.P.), Hôpital European Georges Pompidou (HEGP), 20 rue Leblanc, 75015 Paris, France. From the 1998 RSNA scientific assembly. Received August 23, 1999; revision requested October 14; final revision received April 10, 2000; accepted April 21. Address correspondence to C.A.C. (e-mail: ca@cuenod.net).


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
RESULTS
DISCUSSION
 APPENDIX
REFERENCES
 
PURPOSE: To determine whether computed tomography (CT) can depict liver hemodynamic changes caused by occult hepatic micrometastases in rat.

MATERIALS AND METHODS: Liver micrometastases (mean diameter, 500 µm ± 300) were produced in seven BD IX rats by injecting 107 DHDK12 PROb colorectal carcinoma cells into the spleen. Macrometastases (mean diameter, 7 mm ± 3) were produced in four other rats. Five normal rats were studied as controls. CT images were obtained every 300 msec for 30 seconds during the injection of 1 mL per kilogram of body weight of contrast medium. The time-attenuation curves of the aorta, portal vein, and liver were used to calculate liver perfusion with a deconvolution model designed for the dual blood supply.

RESULTS: Micrometastases in an apparently normal liver caused a 34% decrease in portal blood flow and a 25% increase in the mean transit time for the blood to pass through the liver. These findings suggest increased resistance in the sinusoidal capillaries. Similar but greater changes were found in the macrometastases.

CONCLUSION: Occult liver micrometastases in rats generate changes in liver perfusion that can be detected with CT.

Index terms: Animals • Liver, blood supply • Liver, CT, 761.12111, 761.12113, 761.12115 • Liver neoplasms, metastases, 761.33


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
 APPENDIX
REFERENCES
 
The liver is the most common site of visceral metastasis for colorectal carcinoma (1), and hepatic metastases are a frequent clinical problem (2). Despite the availability of many possible treatments, hepatic metastases are difficult to eradicate (3,4) because of their late discovery. Many metastases smaller than 10 mm remain occult (5), even with the best imaging systems (6). Thus, tools are needed that provide earlier detection. Hopes were raised by the suggestion that occult metastases give rise to detectable changes in liver blood flow similar to those caused by overt metastases (7–12). The hepatic perfusion index, or relative contribution of the hepatic artery to liver blood flow, is measured with Doppler ultrasonography (US) and is increased in humans with liver metastases. It is not clear, however, whether this increase results from an increase in the hepatic arterial contribution or from a decrease in the portal venous contribution (8,13,14).

Fast computed tomographic (CT) techniques allow quantification of perfusion parameters of tissues. After injection of a bolus of contrast medium, the linear relationship between CT attenuation and the concentration of contrast medium can be determined (15–18). The high spatial resolution of CT makes it well suited for in vivo measurement of tissue perfusion. CT has also been used to analyze complex liver perfusion by taking into account the blood input from both the hepatic artery and portal vein (19–21).

The purpose of this study was to determine if liver micrometastases cause changes in liver hemodynamics in rats and whether those changes can be depicted with CT. We compared the liver hemodynamic parameters measured at CT in normal rats and in rats bearing micrometastases.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
DISCUSSION
 APPENDIX
REFERENCES
 
Production of Liver Metastases in Rats
This study was performed in accordance with the French law governing animal research and followed the guidelines for animal care of the U.S. National Institutes of Health. Sixteen male BD IX rats (weight range, 300–450 g) with normal livers were included in the study.

After an overnight fast, the rats were anesthetized with an intraperitoneal injection of ketamine (Imalgene; Bayer, Leverkusen, Germany) and xylazine (Rompun; Bayer). Liver metastases were induced via the portal vein by injecting a suspension of DHDK12 colorectal carcinoma cells (22) into the spleen. The DHDK12 cells were previously grown to confluent monolayers in Dulbecco modified Eagle medium (Sigma-Aldrich, St Quentin Fallavier, France) supplemented with 5% fetal calf serum and 20% gentamicin. These cultured cells were freed by means of trypsination, and a suspension of 107 cells in 0.4 mL of phosphate-buffered saline solution (PBS; Life Technologies, Cergy Pontaise, France) was injected manually into the spleen of 11 rats with a 26-gauge needle during 2 minutes. The five control rats were injected with saline solution.

The livers of seven of the 11 rats with tumor cell injections were sliced and stained with hematoxylin-eosin 22–29 days after injection. Micrometastases (mean number, 12 ± 10 [SD]; mean diameter, 500 µm ± 300) were seen in each slice. The livers of the remaining four rats were sliced and stained with hematoxylin-eosin 30 days after injection. Macrometastases (mean diameter, 7 mm ± 3) were seen in each slice.

CT Examination
After an overnight fast, the 16 rats were anesthetized. Sequential images were acquired through the abdomen with a helical CT scanner (Prospeed; GE Medical Systems, Milwaukee, Wis). A series of 100 consecutive CT images (80 kV, 200 mAs, section thickness of 2.5 mm) were obtained during 30 seconds at a single abdominal location that included the portal vein, the aorta, and the liver (Fig 1). The images were acquired every 300 msec with partial angle reconstruction. The acquisition planes in all rats were made as similar as possible by using the visual patterns of the vessels as landmarks. The acquisition field of view was 15 cm, and the reconstruction field of view was 6 cm.



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  		Figure 1a. Dynamic transverse CT images acquired sequentially through the abdomen of a control rat were obtained every 300 msec for 30 seconds. All images depict the portal vein (curved arrow in c), the aorta (straight arrow in c), and the liver. (a) Baseline precontrast image. Iobitridol (1 mL/kg) was injected intravenously as a bolus 3 seconds after the start of the acquisition. (b-d) Postcontrast images were acquired (b) at 5 seconds, during the peak of aortic attenuation; (c) at 10 seconds, during the peak of portal attenuation; and (d) at 15 seconds, during the steady state phase. In d, the liver parenchyma is enhanced.

 


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  		Figure 1b. Dynamic transverse CT images acquired sequentially through the abdomen of a control rat were obtained every 300 msec for 30 seconds. All images depict the portal vein (curved arrow in c), the aorta (straight arrow in c), and the liver. (a) Baseline precontrast image. Iobitridol (1 mL/kg) was injected intravenously as a bolus 3 seconds after the start of the acquisition. (b-d) Postcontrast images were acquired (b) at 5 seconds, during the peak of aortic attenuation; (c) at 10 seconds, during the peak of portal attenuation; and (d) at 15 seconds, during the steady state phase. In d, the liver parenchyma is enhanced.

 


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  		Figure 1c. Dynamic transverse CT images acquired sequentially through the abdomen of a control rat were obtained every 300 msec for 30 seconds. All images depict the portal vein (curved arrow in c), the aorta (straight arrow in c), and the liver. (a) Baseline precontrast image. Iobitridol (1 mL/kg) was injected intravenously as a bolus 3 seconds after the start of the acquisition. (b-d) Postcontrast images were acquired (b) at 5 seconds, during the peak of aortic attenuation; (c) at 10 seconds, during the peak of portal attenuation; and (d) at 15 seconds, during the steady state phase. In d, the liver parenchyma is enhanced.

 


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  		Figure 1d. Dynamic transverse CT images acquired sequentially through the abdomen of a control rat were obtained every 300 msec for 30 seconds. All images depict the portal vein (curved arrow in c), the aorta (straight arrow in c), and the liver. (a) Baseline precontrast image. Iobitridol (1 mL/kg) was injected intravenously as a bolus 3 seconds after the start of the acquisition. (b-d) Postcontrast images were acquired (b) at 5 seconds, during the peak of aortic attenuation; (c) at 10 seconds, during the peak of portal attenuation; and (d) at 15 seconds, during the steady state phase. In d, the liver parenchyma is enhanced.

 
An intravenous dose of 1 mL per kilogram of body weight of iodinated contrast medium (iobitridol, Xenetix [350 mg of iodine per milliliter]; Guerbet, Aulnay, France) was injected manually as a bolus 3 seconds after the start of acquisition and followed by a 0.2-mL saline solution flush. The images acquired before injection of the contrast material provided the baseline data.

Data Analysis
The CT images were transferred to a workstation (SPARC; Sun Microsystems, Mountain View, Calif) and analyzed with a dedicated program written in IDL computer language (Interactive Data Language, Boulder, Colo) to calculate the liver hemodynamic parameters. On the image that depicted the most contrast enhancement of each vessel, one radiologist (I.L.) drew regions of interest on the aorta, the liver, and the portal vein. The region of interest in the liver was drawn as large as possible, with care taken to avoid the large vessels. Then, the three regions of interest were replicated by the computer on each image of the series to extract the CT attenuation numbers (expressed as Hounsfield units) over time.

For the four rats with macrometastases, an additional region of interest was drawn over the tumor nodules on the CT image where the metastatic nodules were most conspicuous. This region was replicated by the computer on each image of the series.

Time-attenuation curves.—The time-attenuation curves for the regions of interest (Fig 2) were analyzed by means of a mathematical deconvolution method (Appendix) (15,23–25) that takes advantage of the linear relationship between the iodine concentration and the CT attenuation numbers. The deconvolution method allows the tissue response to be standardized for any contrast material injection and, hence, calculation of the perfusion parameters.



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  		Figure 2. Time-attenuation curves in the aorta, the portal vein, and the liver in a control rat. The high sharp aortic peak (full-width at half-maximum, 2.7 seconds) appeared early after contrast medium injection. This peak was followed at 6 seconds by a broader lower portal peak and gradual liver enhancement. A slowly decreasing plateau was obtained after 25 seconds. These data were used to calculate the hepatic perfusion parameters. The curves obtained in rats with metastases (not shown) looked similar, and differences were found only after mathematical processing.

 
For the four rats with macrometastases, the time-attenuation curves were used to calculate the perfusion parameters of the metastatic nodules by using the same mathematical model.

Hemodynamic perfusion parameters.—There are two input routes for blood to the liver—the hepatic artery and portal vein—and the deconvolution method takes them both into account (Fig 3). The analytical method used in this study was dedicated to liver perfusion and yielded six major perfusion parameters: (a) hepatic perfusion index, or ratio of arterial liver perfusion to total liver perfusion, reported as a percentage; (b) mean transit time, or mean time taken by the tracer to cross the tissue (from the input to the venous output), reported in seconds; (c) distribution volume, or the ratio of the space in which the contrast media is distributed to the tissue volume, reported as a percentage; (d) total hepatic blood flow, or perfusion for a gram of liver, reported in milliliters per minute per gram; (e) arterial hepatic blood flow, or liver tissue perfusion of arterial origin, reported in milliliters per minute per gram; and (f) portal hepatic blood flow, or liver tissue perfusion of portal venous origin, reported in milliliters per minute per gram.



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  		Figure 3. Diagram of the deconvolution method with two inputs. The liver has two inputs (Ca(t)) and (Cp(t)) affected by coefficients {alpha} and (1 - {alpha}) and one output (Cv(t)) (Appendix). The total input is E(t) = [{alpha}CA(t) + (1 - {alpha})CP(t)]. Because the hepatic artery is too small to obtain a reliable time-attenuation course, the attenuation in the abdominal aorta is taken to represent the arterial input. For any input function [E(t)], the pattern of the contrast medium concentration in the liver [CT(t)] can be predicted as the convolution of the input function by the transfer function RT(t) of the liver: CT(t) = E(t) x RT(t). The ratio of arterial to total liver perfusion, or the hepatic perfusion index, is given by {alpha}.

 
The parameters b–d are similar to those for other organs. The parameters a, e, and f are specific to the liver. Parameter c is the tissue blood volume when the contrast medium remains purely intravascular (as in the brain, owing to the blood-brain barrier) or the tissue blood volume plus the interstitial space (as in the liver when the contrast medium can diffuse across the capillary wall into the interstitial space).

Statistical Analysis
Data were expressed as the median and the range. Data for the rats with micro- and macrometastases were compared with data for the control rats by means of the unpaired Mann-Whitney nonparametric test. Differences with a P value of less than .05 were considered statistically significant.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
DISCUSSION
 APPENDIX
REFERENCES
 
Time-Attenuation Curves
Figure 2 shows a typical time-attenuation curve. The first aortic peak was sharp (full-width at half-maximum, 2.7 sec ± 0.5). The aortic peak was followed by a lower broader portal peak and gradual liver enhancement. A stationary level was reached about 25 seconds after the first pass and a mixing period in the vessels and was followed by a slowly decreasing plateau. There were no obvious visual differences between the enhancement behaviors in the three groups of rats; therefore, we determined any differences in the hepatic perfusion parameters on the basis of these curves.

Perfusion of Livers with Occult Micrometastases
Portal hepatic blood flow was 34% lower in the rats with micrometastases than in the control rats (P = .03) (Table); therefore, total hepatic blood flow decreased. The mean transit time of blood through the capillaries was 25% longer than in control rats (P = .04). The other perfusion parameters were not altered significantly. The fractional distribution volume of contrast medium diffusion, the arterial hepatic blood flow, and the hepatic perfusion index remained the same as in control rats.


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  		Perfusion Parameter Values in Rats
 
Perfusion Parameters of Macrometastases
For macrometastases, all perfusion parameters but arterial hepatic blood flow were abnormal (Table). Changes in mean transit time, total hepatic blood flow, and portal hepatic blood flow were larger in rats with macrometastases than in those with micrometastases. The hepatic perfusion index increased with macrometastases because of the large decrease in portal hepatic blood flow. The distribution volume of the contrast medium was much lower in rats with macrometastases than in control rats (P = .014). Thus, the attenuation of macrometastases was lower than that of the surrounding liver.

In the liver outside macrometastases compared with the normal liver in control rats, mean transit time was longer (P = .05) and portal hepatic blood flow (P = .05) and total hepatic blood flow (P = .014) were lower.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
DISCUSSION
APPENDIX
REFERENCES
 
The ability to detect a high risk of metastatic liver involvement in a common disease like colorectal cancer may help clarify the decision to use adjuvant chemotherapy (26) and avoid unnecessary treatment of patients who are at low risk of liver metastases (27).

Findings in our study in rats indicate that a decrease in the portal blood flow and an increase in the mean transit time in livers with micrometastases can be detected with CT, although the livers themselves appear normal, with no visible lesions. The hemodynamic changes with micrometastases were similar but smaller than those with macrometastases.

A decrease in the portal blood flow was reported for livers with overt metastases (14,28), but to our knowledge no such decrease has been demonstrated previously in livers with occult metastases. The simultaneous increase in the mean transit time suggests that this low portal blood flow value is caused by a rise in intrahepatic resistance owing to obstruction, stenosis, and compression of the hepatic sinusoidal capillaries. Metastatic cells introduced via the portal vein are arrested at the inflow side of the microvascular bed owing to size restriction (29). Multiple microthrombi in the portal vessels (29–31) increase resistance in the low-pressure vascular bed. The portal venules and sinusoidal capillaries are obliterated abruptly at the borders of the growing metastatic foci (31).

It has been suggested that an agent secreted by the metastatic cells or the surrounding cells could be responsible for constriction of the abdominal arterial vasculature, which leads to a reduction in portal venous blood flow (32). The longer transit time, however, is not in favor of a lower portal pressure. The congestive portal vein index (ratio of the cross-sectional area of the vein to the velocity of blood flow), measured with Doppler US, was also similar in patients with metastases and in control subjects (33); this finding suggests that the portal pressure is not lowered by metastases. Other effects of a circulating agent that increases the splanchnic resistance may explain the absence of the portal hyperemia usually caused by increased portal resistance. The existence and nature of such a circulating agent remain to be determined.

The arterial contribution to liver perfusion (hepatic perfusion index) is increased in humans with liver metastases. We found no such increase in rats bearing micrometastases, however, because their arterial flow was not increased. Metastases smaller than 200 µm receive their blood supply via the sinusoidal capillaries without hepatic arterial neovascularization (30). The increase in hepatic perfusion index in humans may be due to the hepatic arterial buffer response (34,35)—an increase in arterial flow to compensate for a decrease in portal venous blood flow—which tends to maintain a constant total hepatic flow (36,37). The arterial contribution in rats, however, is lower (hepatic perfusion index, 2%–10%) than that in humans (hepatic perfusion index, 20%–30%) (19), and therefore the arterial buffer response may be smaller.

The small arterial contribution to hepatic perfusion in rats helps dissociate the portal and arterial responses to a disease and helps understanding of the pathologic disturbances due to metastases. Indeed, this small arterial contribution allowed us to demonstrate that the portal flow decreases in the presence of liver micrometastases prior to any change in arterial flow. This finding suggests that the increase in arterial liver perfusion found in humans may be due to the buffer response to the reduced portal flow. The buffer response in humans could increase the detection power of quantitative CT in patients. The increase in arterial flow in addition to the decrease in portal flow may result in a larger increase in the hepatic perfusion index.

The hemodynamic changes we found in rats with macrometastases are in agreement with those published for patients with liver metastases (38,39) and correlate well with in vivo changes seen at videomicroscopy (31). Tumor nodules contain irregularly dilated tortuous neoangiogenic vascular networks, whereas the normal liver has regular vasculature (13). Blood flow velocity and direction vary in the tumor capillary network, which accounts for the increase in the mean transit time. Tumor nodules are surrounded by compressed sinusoidal capillaries that resist portal flow. Most flow is stopped at the tumor borders, which accounts for the decrease in portal flow in the tumor. As the nodules enlarge, the pressure in them (40) and in the surrounding vasculature increases. These changes account for the portal hypertension in tumor-bearing livers (31).

The small distribution volume of the contrast medium in the tumor suggests that the capillary density is lower than that in the normal liver. This finding accounts for the fact that metastases from colon and breast cancers usually appear to be less enhanced than the normal liver after contrast medium injection (31).

The increased perfusion index in macrometastases suggests that the tumor vascularization is predominantly arterial. In fact, the arterial blood flow did not change markedly, whereas the portal flow decreased greatly. The absence of an increase in arterial flow is in accordance with the fact that most metastases do not enhance during the arterial phase at CT. The vascular network surrounding the metastases is formed by dilated portal veins and not by arteries (31). Therefore, the reduction in the hepatic arterial resistive index found with Doppler US in humans with overt liver metastases (33) may again be due to the arterial buffer response caused by the reduction in portal flow.

The major clinical limitation of this technique is the exposure to radiation during the CT acquisitions. A lower sampling rate could be used in humans, because the hemodynamic events are slower than those in rats, which would lead to less irradiation. Moreover, the cost-benefit ratio of the diagnostic and therapeutic techniques must be evaluated in patients treated for cancerous diseases. Nonirradiating techniques such as magnetic resonance imaging or Doppler US, however, could be used to measure perfusion in the future.

Practical application.—These experimental results, obtained with CT in rats, suggest that occult liver metastases lower the portal perfusion by increasing resistance in the sinusoidal capillaries. If similar changes can be documented in human subjects, our technique could be a good screening method. Quantitative detection of a disturbed blood flow in the liver with CT could lead to the early identification of occult metastases in patients at risk and improve their therapeutic treatment.


   APPENDIX
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
DISCUSSION
 APPENDIX
REFERENCES
 
Deconvolution Analysis
Because of the two vascular inputs to the liver, the classic mathematical models used to calculate the tissue perfusion parameters must be modified to take into account this dual blood supply.

Deconvolution with a Single Blood Supply
When there is a single blood supply to a tissue, the changes in tissue attenuation, expressed in Hounsfield units, ({Delta}HUT[t] = HUT[t] - HUT[0]) after an injection of contrast medium can be described by a theoretical impulse response [RT(t)], which is the response to an instantaneous (or impulse) input (15,24).

Since the changes in CT numbers ({Delta}HU) are proportional to the concentration of contrast medium ({Delta}HU = k · C), the true experimental tissue concentration pattern CT(t) in response to an experimental arterial input function CA(t) can be predicted as the convolution of this experimental arterial input function by the theoretical impulse response:

One way of defining RT(t) is to convolve the observed arterial input time-attenuation curve with assumed impulse responses of different widths. The curve yielding the best fit to the observed tissue values can then be used to give the theoretical impulse response (23).

Dual Input Deconvolution
A deconvolution can provide RT(t) because the arterial and venous portal blood inputs are mixed at the entry of the sinusoidal capillaries in the liver (41). We need to know the change in contrast of the liver, CT(t); the two arterial and portal entries, CA(t) and CV(t); and coefficients {alpha} and (1 - {alpha}) that affect each entry (Fig 3):

Calculation of the Perfusion Parameters
The theoretical venous output response (S[t]) to an impulse input is obtained as the negative derivative of RT(t) (24):

Finally, the calculated theoretical venous output response can be used to calculate the mean transit time of the contrast medium through the vascular bed, which is the first moment of (S[t]). The fractional distribution volume is the area under the curve (S[t]).

The total hepatic flow (HBF) is given by HBF = DV/MTT, where DV is distribution volume and MTT is mean transit time, according to the Steward-Hamilton theorem (42). The ratio of arterial perfusion to total liver perfusion, or the hepatic perfusion index, is given by {alpha}. Finally, the arterial hepatic blood flow (FA) is calculated as FA = {alpha} x HBF and the portal hepatic blood flow (FP) as FP = (1 - {alpha}) x HBF.


   ACKNOWLEDGMENTS
 
We thank François Martin, MD, of the Cancer Biology and Therapy Department, INSERM, Dijon, France, for supplying the DHDK12 PROb colorectal carcinoma cells; Philippe Marteau, MD, HEGP, Paris, France, for reviewing the manuscript; and Owen Parkes for editing the English text.


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


   REFERENCES
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 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
DISCUSSION
 APPENDIX
REFERENCES
 

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