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Original Research |
1 Minimally Invasive Tumor Therapy Laboratory, Beth Israel Deaconess Medical
Center, Harvard Medical School, Boston, MA.
2 Renal Cancer Program, Dana Farber/Harvard Cancer Center, Boston, MA.
3 Department of Radiology, Beth Israel Deaconess Medical Center, 1 Deaconess
Rd., WCC 308-B, Boston, MA 02215.
4 Division of Hematology/Oncology, Beth Israel Deaconess Medical Center, Harvard
Medical School, Boston, MA.
5 Department of Pathology, Brigham and Women's Hospital, Boston, MA.
Received July 10, 2007;
accepted after revision January 10, 2008.
This study was supported by a grant from the National Cancer Institute
(NCI) Dana Farber/Harvard Cancer Center (DF/HCC) Renal Cancer SPORE grant (no.
1 P50 CA10194-01). Sorafenib (BAY 43-9006) used for this study was provided by
Bayer, Inc., West Haven, CT. R. Schor-Bardach is a recipient of a fellowship
grant from The American Physicians Fellowship for Medicine in Israel.
Abstract
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MATERIALS AND METHODS. Twenty-five rats implanted with R3230 mammary adenocarcinoma (diameter, 1.2–2.0 cm) randomly received 7.5 or 30 mg/kg of an antiangiogenic agent, sorafenib, by daily gavage for 4 (n = 4), 9 (n = 9), or 14 (n = 5) days. Seven untreated animals served as a control group. Perfusion MDCT was performed at days 0, 4, 9, and 14 with 0.4 mL of ioversol (350 mg/mL) and included four 5-mm slices covering the entire tumor volume. Changes in tumor growth were determined by volumetric analysis of CT data. Serial changes in tumor volume and blood flow were assessed and correlated with pathology findings.
RESULTS. All control tumors grew larger (from 2.0 ± 0.7 cm3 at day 0 to 5.9 ± 1.0 cm3 at day 14), whereas all treated tumors shrank (from 2.5 ± 1.1 to 2.1 ± 1.0 cm3), with a statistically significant rate of growth or shrinkage in both groups (p < 0.05). Although perfusion in the control tumors changed little from day 0 to day 14 (day 0, 18.1 ± 9.2 mL/min/100 g; day 4, 15.8 ± 5.6; day 9, 21.7 ± 12.2; day 14, 27.7 ± 34), in the sorafenib group, the mean blood flow was significantly lower at day 4 (5.2 ± 3.2 mL/min/100 g, 77% decrease), day 9 (6.4 ± 4.0 mL/min/100 g, 66% decrease), and day 14 (6.3 ± 5.2 mL/min/100 g, 83% decrease) compared with day 0 (23.8 ± 11.6 mL/min/100 g) (p < 0.05). Poor correlation was seen between changes in blood flow and tumor volume for days 0–9 (r2 = 0.34), 4–9 (r2 = 0.0004), and 9–14 (r2 = 0.16). However, when comparing day 4 images with days 9 and 14 images, seven of 14 (50%) sorafenib-treated tumors had focal areas of new perfusion that correlated with areas of histopathologic viability despite the fact that these tumors were shrinking in size from day 4 onward (day 4, 2.18 ± 0.8 cm3; day 9, 1.98 ± 0.8 cm3).
CONCLUSION. Perfusion MDCT can detect focal blood flow changes even when the tumor is shrinking, possibly indicating early reversal of tumor responsiveness to antiangiogenic therapy. Given that changes in tumor volume after antiangiogenic therapy do not necessarily correlate with true treatment response, physiologic imaging of tumor perfusion may be necessary.
Keywords: antiangiogenic therapy • MDCT • perfusion CT • perfusion imaging • renal cell carcinoma • sorafenib
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Traditionally, therapeutic response has been assessed by serial tumor size measurements, most notably using the Response Evaluation Criteria in Solid Tumors (RECIST) [8, 9]. However, preclinical assessment of new antitumoral therapeutics such as antiangiogenic agents has highlighted the limitations associated with using standard morphologic measurements. Tumor response may be better assessed by alterations in vascular perfusion rather than tumor size, and functional measurements may therefore be more appropriate [10–12]. In addition, resistance to antiangiogenic agents appears inevitable, but the nature of this resistance or the ability to detect it before clinically significant disease progression occurs remains limited. This situation highlights the need to develop alternative methods to assess the effects of treatment on tumors.
Given the limitations of clinical criteria alone, various authors have evaluated the use of single-detector CT for the assessment of tumor blood flow [13–25]. With the aid of reliable and accurate commercially available software algorithms, they were able to show good correlations and reproducibility of measurements, thus establishing the basis for further experimentation and the use of CT functional measurements. In a more recent study [26], perfusion MDCT achieved a better correlation to the reference standard laser Doppler flowmetry compared with a single-detector technique for detecting acute changes in tumor blood flow induced over 1 hour by the antivascular agent arsenic trioxide in an animal tumor model. In that study, perfusion MDCT also showed potential as an independent predictor of tumor perfusion and improvement in the interobserver agreement compared with perfusion imaging using a single-detector CT technique.
Other authors have also shown that MDCT enables assessment of changes in tumor vascularity and perfusion that result from chemotherapy and radiation therapy [27, 28]. Nevertheless, use of this technique over the long time intervals required for monitoring antiangiogenic therapy requires validation.
The purpose of this study was therefore to determine whether perfusion MDCT can be used to monitor the effects of antiangiogenic therapy to potentially enable earlier prediction of tumor response and resistance to therapy compared with conventionally measured imaging parameters in an animal tumor model.
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Sorafenib Administration
Sorafenib was administered daily by gavage in blinded fashion as 7.5 or 30
mg/kg depending on experimental group. Sorafenib was dissolved in a 50%
polyethoxylated castor oil (Cremophore EL, Sigma)–50% ethanol mixture at
four times (4x) the desired highest concentration; for the dose of 30
mg/kg, the concentration of the dosing solution was 8 mg/mL, with this
4x solution measuring 32 mg/mL. The compounds were heated to 60°C
for 1 minute and sonicated for 20–30 minutes to suspend the sorafenib.
Once in solution, the aqueous component was gradually added and diluted to
generate the 1x dosing solution. The lower dose levels were then made by
dilution of this preparation with 12.5% Cremophor EL, 12.5% ethanol, and 75%
water [1]. Each dose of
sorafenib was weighed and stored in dry form away from light and was dissolved
to liquid form immediately before administration.
Tumor Preparation
A parent tumor (
1 cm in diameter) was initially harvested from a live
carrier. Within 30 minutes of its dissection and removal, the tumor was
homogenized with a tissue homogenizer (PowerGen model 125, Fisher Scientific)
using aseptic technique, and the tumor cells were suspended in 7 mL of a
culture medium (RPMI 1640, INC Biomedicals). In prior control experiments in
our laboratory, this process resulted in a concentration of 1 x
107 cells per milliliter, with more than 95% cellular
viability.
During direct visualization, 0.2–0.3 mL of the tumor cell suspension was injected slowly through an 18-gauge needle into the mammary fat pad. Animals were monitored every 3–4 days to measure tumor growth. Tumors were allowed to grow for 14–24 days until the desired treatment size (1.2–2 cm) was achieved. Tumor size was chosen to optimally match the size with maximum z-axis coverage (4-MDCT acquisition at 5-mm thickness = 20 mm). Tumor induction, monitoring, and randomization were performed by two authors. Tumors were measured with calipers daily until reaching the desired size. Solid tumor architecture was confirmed by sonography before CT. Tumor size and composition were also confirmed by CT during experimentation. On completion of the study, the animals were sacrificed by barbiturate overdose (Somlethal, J. A. Webster) according to IACUC guidelines.
Perfusion CT
Perfusion MDCT was performed on days 0, 4, 9, and 14 as described by Hakime
et al. [26]. Rats were scanned
using a 16-MDCT scanner (Light-Speed Plus, GE Healthcare). Before CT, the tail
vein was catheterized with a 24-gauge cannula for administration of contrast
material. After an intra-peritoneal injection of a mixture of ketamine
(Ketaject, Phoenix Pharmaceutica), at a dose of 50 mg/kg of body weight, and
xylazine (Rompun, Bayer), at a dose of 5 mg/kg, was administered, rats were
placed on the CT table and restrained to limit movement. When necessary,
booster anesthetic in jections at one tenth of those doses were admin istered
intra peritoneally every 30–60 minutes.
Initially, an unenhanced study was performed to identify the tumor for planning purposes using the following parameters: helical acquisition; slice thickness, 2.5 x 2.5 mm; speed, 27 mm/s; pitch, 1.3; 120 kV; 240 mA; rotation speed, 0.5 second; scan field of view (FOV), 24 cm; and matrix, 512 x 512. The images were then inspected by two of the authors on the CT console; the target slices were selected to plan subsequent dynamic studies to ensure that the entire tumor was covered by the 20-mm scan volume.
For measurement of perfusion, CT was initiated 2 seconds before the near-instantaneous manual administration of a 0.4-mL bolus of contrast agent (2 mL/kg of ioversol [Optiray 350, Mallinckrodt Imaging] at 0.05 mL/s); contrast injection was performed consistently by the same investigator to minimize variation. Images were obtained at 1-second intervals covering the entire tumor using the axial mode (120 kV; 240 mA; FOV, 50 cm; matrix, 512 x 512) throughout the bolus in ject ion of contrast agent and continued for a total of 65 seconds. The 20-mm scan volume was reconstructed into four contiguous slices collimated to 5 mm each. Immediately after the dynamic study, the tumor was imaged in the high-resolution mode for calculation of tumor volumes (helical acquisition; collimation, 1.0 mm; rotation speed, 0.5 second; 120 kV; 240 mA; FOV, 24 cm; and matrix, 512 x 512).
Image Processing
For each dynamic CT scan acquisition, four single perfusion CT image maps,
each of 5 mm thickness, were obtained from the single scanned 20-mm tumor
volume. The 400 images from the dynamic studies were processed using perfusion
CT software (Perfusion 2.0, GE Healthcare) with a body tumor perfusion
algorithm. This software has been previously validated for the determination
of changes to tumor perfusion by various authors
[21–24].
A processing threshold of 0–120 H was selected to permit appropriate
subsequent analysis of both unenhanced and enhanced soft tissue.
Arterial input was determined by placing a region of interest (ROI) over the best visualized artery in the slice plane (aorta, iliac artery, or superficial femoral artery). Time–attenuation curves were automatically generated for the arterial input along with perfusion maps for all the tissues within the scanning plane over the 65-second perfusion acquisition. To determine tumor perfusion, an ROI was drawn freehand around the peripheral margin of the tumor using an electronic cursor. Care was taken to exclude peritumoral skin and fat and intraluminal gas by viewing the cine loop to gauge the extent of movement during acquisition. A global time–attenuation curve for the selected tumor tissue and the mean blood flow for the tumor tissue within the ROI were derived.
The blood flow maps of all four single slices of a given dynamic CT study were saved in high-resolution gray-scale format. Every picture was then loaded in ImageJ (Image Processing and Analysis in Java, National Institutes of Health Image; available at http://rsb.info.nih.gov/ij/) to calculate the histogram of the perfusion values within the ROIs. The pixel data from the four tumor slices were then combined in Microsoft Excel to calculate the mean CT perfusion for the entire tumor volume blood flow.
Blood flow in each perfusion map was represented in a color-coding scheme in rainbow format such that a flow of 0 mL/min/100 g was shown in black and maximal blood flow (50 mL/min/100 g) was shown in bright red. Flow values between 0 and 50 mL/min/100 g were represented as varying shades of blue, green, yellow, and red in order of increasing perfusion.
For calculation of tumor volumes, high-resolution axial images were loaded as a single volume to the workstation and were reconstructed into multiplanar images that were used separately by two authors to draw outlines around the tumor edges. These outlines were used by the software algorithm to separate the tumor from the main rat body and to calculate its volume.
Histopathologic Correlation
All animals in the control and experiment groups were sacrificed on day 0,
4, 9, or 14 after their last scheduled CT scan. Tumors were sectioned
immediately (within 1 hour) in the axial plane corresponding to the CT slice
orientation, fixed in 10% formalin, and embedded in paraffin. Tissue sections
were stained with H and E. All tissue specimens were examined at their
greatest axial diameter. Nonviable tumor areas were identified using
morphologic criteria by an experienced pathologist. Four of 18 animals in the
experimental group were exclusively followed to day 4 and were then sacrificed
for purposes of histopathologic verification and comparison.
Statistical Analysis
Serial changes in tumor volume as determined by CT were compared with and
correlated to mean tumor blood flow for each of the scan days 0, 4, 9, and 14.
Visual comparison of a histologic tissue section with the corresponding
animal's perfusion CT images was also performed. All values were expressed as
means with SDs. The Student's t test was used to correlate changes in
tumor volume to changes in mean tumor blood flow. A p value of 0.05
was considered to denote statistical significance.
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Tumor Blood Flow
Variable, but not statistically significant, changes in mean tumor blood
flow (mL/min/100 g) were noted for the control group through day 14
(Table 2). However, in the
sorafenib-treated groups, the mean blood flow was significantly lower at day 4
(78% decrease from day 0, p < 0.05) and progressed to an average
decrease of 75% for days 9 and 14 compared with day 0 (p < 0.05).
However, no statistically significant difference in the overall mean tumor
blood flow was observed between days 4 and 9 and day 14 (p >
0.10). Furthermore, there was no significant difference (p > 0.10)
be tween the two different sorafenib doses (7.5 and 30 mg/kg) in terms of mean
tumor blood flow and the percentage changes from baseline.
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Although there was no significant change in either tumor volume or mean overall blood flow when comparing sorafenib-treated day 9 or day 14 values with day 4 values, seven of 14 sorafenib-treated tumors had focal areas of new blood flow that correlated to areas of increased histopathologic viability despite the fact that these tumors had shrunk or were stable in size (day 4, 2.18 ± 0.8 cm3; day 9, 1.98 ± 0.8 cm3). These foci were seen in four of nine (44%) tumors from day 4 to day 9 and in three of five (60%) tumors from day 9 to day 14 (Fig. 2A, 2B, 2C, 2D, 2E, 2F). Thus, 50% of the sorafenib-treated tumors exhibited new foci of increased perfusion from day 4 onward as seen from spatial analysis of the individual perfusion CT slices. These new foci of increased perfusion were seen on the middle two slices of the four slices covering each tumor in five of seven (71%) tumors and on one of four and three of four slices in the other two tumors (2/7, 29%).
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Hakime et al. [26] previously showed the superiority of MDCT to single-detector CT for measuring tumor blood flow, as evidenced by its higher interobserver agreement and greater tumor volume coverage. Our study results further point to the fact that the currently available systems of tumor monitoring, such as RECIST, alone cannot be entirely relied on when using agents that reduce tumor blood flow because changes in blood flow may precede changes in tumor size. Our findings also reveal that a set of tumors receiving the antiangiogenic agent sorafenib can exhibit differences in response to that agent over time, which can range from changes in mean tumor blood flow to development of new zones of perfusion in areas that initially showed minimal or no blood flow. We found that these foci of new perfusion can develop and be detected by perfusion CT even when mean tumor blood flow is unchanged or while tumor size or volume is actively decreasing, greatly emphasizing the importance of perfusion MDCT in such a scenario. Such zones of blood flow correspond to focal areas of viable tumor and may well represent the development of new vessels that occur despite the administration of the antiangiogenic agent, indicating the emergence of cells that have developed a means of resistance to the therapeutic agent. Furthermore, the fact that the zones of new perfusion were not seen in every image further emphasizes the importance of covering large volumes of the tumor with MDCT techniques to maximize diagnostic sensitivity. An alternative approach could be to scan and calculate the blood flow in the middle two slices (center part) of the tumor only in cases in which full tumor volume coverage is not possible. In addition, perfusion CT will ultimately need to be compared with other imaging strategies for mapping perfusion such as arterial spin-labeling MRI [29] and dynamic contrast-enhanced Doppler sonography [30].
Perfusion MDCT was able to successfully identify focal areas of new tumor perfusion 9–14 days into antiangiogenic therapy before clinically measurable changes in tumor mass were seen, perhaps indicating early angiogenic escape in this specific animal tumor model. However, not all tumors may behave in an equal manner with antiangiogenic therapy, and thus further experimentation in other animal, and more importantly human, tumor models is needed to validate the effectiveness of perfusion MDCT for this specific purpose. Thus, specific clinical testing in RCC, a disease that is known to be sensitive to sorafenib, would be of interest and may or may not reproduce these findings.
Although we were able to correlate the microscopy findings with the perfusion CT maps to within reasonable limits, our study is limited by the resolution and slice thickness used for calculating tumor blood flow. This can be overcome in future studies by the availability of software that allows higher-resolution scanning and use of thinner slices, thus enabling tighter correlation with histopathology results. As an additional limitation, we relied on conventional histologic criteria of cellular viability rather than microvascular density. Nevertheless, tumor growth and viability, not angiogenesis, are the primary end points or concerns. Furthermore, Kan et al. [13] have shown that "functional CT can help quantify the perfusion function of mature vessels but not changes in microvessel density in antiangiogenic therapy." Perfusion CT of thoracic and abdominal tumors may be limited by breathing motion; nonetheless, previous studies [26] using similar techniques and an animal model have shown the accuracy of perfusion CT compared with an established reference standard. Future advances in imaging software and technology will help to further optimize image acquisition and processing with lower radiation doses.
Several potential limitations in our animal model and experimental design warrant discussion. Like most other scientific measurement systems, perfusion CT has room for variation, particularly for heterogeneous biologic systems such as orthotopic tumors. For example, we note that there was a 13% drop in blood flow in the control rats on day 4 compared with their baseline values, but this decrease is well below the reported coefficient of variability in perfusion CT measurements [18, 20, 29]. Furthermore, we did not sacrifice control rats on days 0 and 4 for this study. However, prior experiments in our laboratory [26] using the exact same animal tumor model have shown that untreated R3230 tumors of similar sizes have excellent solidity and vascularity as indicated by radiologic–pathologic correlation. Moreover, our end point was to determine the vascularity of the tumors at days 9 and 14, not at day 4. This, combined with the limited number of rats available, led to an experimental design that did not sacrifice control animals on days 0 and 4.
Inevitably, although rodent studies allow minimization of variability of tumor parameters, the size of the model may introduce untoward errors in the imaging technique. For example, perfusion CT is likely to work best with a tight injection bolus. Nevertheless, by necessity, we used a near-instantaneous manual bolus of 0.4 mL of contrast material, as done in previous published studies [26]. Even though a constant injection rate using a power injector is perhaps the ideal method, to the best of our knowledge, there is no power injector commercially available for use in the tail vein of a 150-g rat. Furthermore, although rats were positioned almost identically every time they were scanned, this position change might have led to variability in tumor volume measurements for such small tumors. However, unpublished data from our laboratory show that repeated volume CT scans of the same rat tumor with the rat in varying positions (prone, supine, lateral, and prone again) have average variability in calculated tumor volumes of 1.0% ± 0.5% (range, –1.9% to 1.2%). Accordingly, this degree of error is way below the changes in tumor volume observed in this study.
Lastly, some authors have used additional perfusion CT calculation parameters such as blood volume, mean transit time, and permeability surface area for determination of a tumor's vascularity in varying tumor models [31, 32]. However, studies from our laboratory [26] have clearly shown tight correlation between blood flow as measured by perfusion MDCT and laser Doppler flowmetry as the reference standard in the same animal model. Thus, we preferentially used this parameter over those with which poorer correlations (unpublished data) were found. Moreover, various authors have clearly shown that of all the commonly calculated perfusion CT parameters (i.e., blood flow, blood volume, mean transit time, and permeability surface area product), blood flow shows the closest correlation to histopathology findings and clinical outcomes [13, 31, 32].
If successfully validated, perfusion MDCT could be used to further characterize the phenomenon of "early breakthrough" in large-scale trials in patients with highly vascular tumors such as RCC, thus enabling us to gain more insight into the physiology and pathogenesis of resistant tumor cells. Earlier identification of resistance through measurement of blood flow would enable clinicians to consider an alteration in therapy, including dose or schedule modifications or switching to another agent before tumor growth is documented, possibly preventing or delaying clinical sequelae of disease progression. Moreover, tumors exhibiting this phenomenon could then be easily singled out for targeted biopsy and extraction of the resistant cells, which can be biochemically and genetically studied to understand and identify the exact resistance mechanism or mechanisms, thus enabling future development of targeted therapies.
In conclusion, in this murine xenograft tumor model receiving antiangiogenic therapy, perfusion MDCT was able to identify changes in tumor blood flow before changes in tumor volume occurred, possibly indicating early reversal of tumor responsiveness to therapy. Given that changes in tumor volume after antiangiogenic therapy do not necessarily correlate with true treatment response, noninvasive physiologic imaging of tumor perfusion may be necessary for evaluating the effectiveness of antiangiogenic agents.
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