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Clinical Investigations |
1 Division of Nuclear Medicine, University of Washington, Seattle, Washington
2 Division of Medical Oncology, University of Washington, Seattle, Washington
3 Department of Pathology, University of Washington, Seattle, Washington
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONREFERENCES |
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Key Words: PET • neoadjuvant chemotherapy • breast cancer • 18F-FDG • 15O-water • response
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONREFERENCES |
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In a prior report (8), we showed that pretherapy PET measurements of blood flow and glucose metabolism, obtained using 15O-water and 18F-FDG, provided information on tumor biology that was distinct from standard clinical and pathologic data. High pretherapy tumor glucose metabolism, expressed as the metabolic rate of 18F-FDG (MRFDG), was associated with a poor response to neoadjuvant chemotherapy. Furthermore, a low ratio of glucose metabolism to blood flow predicted a complete response (CR) to chemotherapy and improved disease-free survival (DFS).
We now extend our earlier report to describe changes in tumor blood flow and metabolism over the course of neoadjuvant chemotherapy. The hypothesis underlying our study is that changes in glucose metabolism and blood flow over the course of treatment are predictive of ultimate response and survival in LABC patients treated with neoadjuvant chemotherapy. Several earlier reports have shown that serial 18F-FDG PET over the course of neoadjuvant chemotherapy accurately indicates tumor response compared with both clinical and pathologic measurements (9–13). Our work differs from the prior studies in two ways. The first of these differences is that we performed simultaneous measurements of both tumor blood flow and glucose metabolism over the course of treatment. Tumor blood flow is an indirect measure of angiogenesis, which has been shown to predict breast cancer aggressiveness and patient outcome (14,15). Changes in tumor blood flow in response to therapy may therefore provide insights into tumor behavior. The second difference is that in this study, we accounted for the influence of changes in tumor size over the course of therapy, using partial-volume corrections, to measure changes in tumor biologic properties independent of the influence of changes in tumor size on apparent tracer uptake.
Patients were studied before therapy and after 2 mo of chemotherapy based on clinical considerations. Two months is approximately halfway through the typical course of neoadjuvant chemotherapy and is also the earliest time point at which most clinicians are willing to change treatment if the selected chemotherapy has not elicited a tumor response (16). Previous studies of 18F-FDG PET in patients with LABC receiving neoadjuvant chemotherapy have also used this time point for serial imaging (9,10). If changes in blood flow or metabolism at 2 mo predict ultimate response, then these parameters could be used to help guide treatment and direct a change in therapeutic approach, if necessary. Furthermore, quantitative PET imaging provides unique measurements of in vivo tumor biology over the course of treatment that may provide insights into the factors affecting tumor response and resistance to neoadjuvant chemotherapy.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONREFERENCES |
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Pretherapy Clinical and Pathologic Parameters
Before the start of chemotherapy, patient age, menopausal status, tumor size, and the presence or absence of clinically positive lymph nodes, as assessed by the referring oncologist, were recorded. These factors, shown to have prognostic significance, were used in the survival analysis described below. Pretherapy biopsy samples were obtained by fine-needle aspiration, incisional biopsy, or core-needle biopsy. Measurements and in vitro assays to determine tumor histologic grade, estrogen receptor status, c-erbB-2 (HER2/Neu) expression, p53 overexpression, and Ki-67 (MIB1) index of tumor proliferation were performed as previously described (8).
Tumor Measurements and Assessment of Response
The modality providing the best definition of tumor size in the opinion of the referring medical oncologist was used to assess clinical response and included ultrasound, mammography, or physical examinations, as we have previously reported (8,17). A response was defined as a greater than 50% decline in the product of the 2 greatest perpendicular tumor dimensions (18). Patients not achieving this endpoint were classified as having no response (NR) clinically. Patients were judged to have a clinical CR when no viable tumor could be observed by diagnostic imaging or palpated by physical examination. Patients with a residual mass detected at the end of therapy and a minimum 50% reduction in the size of the mass were considered to have a partial response (PR) clinically.
Pathologic response was determined from the report of the pathologist performing gross and histopathologic evaluation of the posttherapy surgical breast specimen. By standard definitions, a macroscopic pathologic CR was defined as the absence of macroscopic tumor by gross examination at the time of surgery (3). This response endpoint has been used in several prior studies of neoadjuvant treatment of LABC and has been shown to carry prognostic significance (3,4). Patients with macroscopic abnormalities on gross pathology and minimal evidence of invasive tumor on histologic analysis were considered to have a macroscopic CR. Patients with a macroscopic CR were further classified as having a microscopic CR if no invasive tumor was seen by microscopic examination of the specimen. Patients with residual macroscopic tumor—that is, a pathologic response other than CR—were further classified as having NR or a PR by comparison with pretherapy clinical size measurements. Pathologic lack of response in patients with NR clinically was confirmed by comparing tumor size measurements of the surgical specimen with clinical size measurements that had indicated a lack of response. Similarly, pathologic evidence of PR was confirmed by a comparison of pathologic tumor size with pretherapy clinical size measurements. Any discrepancy between posttherapy clinical size measurements and pathologic size measurements was reflected in the pathologic response category (PR or NR). Tumors with equivocal findings were reviewed and classified by a pathologist specializing in breast pathology, who was unaware of the PET imaging results.
PET Imaging
We have previously described in detail our imaging and data analysis methods (8). We summarize those methods here, highlighting differences from our prior study. All imaging was performed using the Advance tomograph (General Electric Medical Systems). Blood flow imaging was performed using 962–1,998 MBq of 15O-water produced as previously described (8). Tracer was administered by bolus intravenous injection in a 1- to 4-mL volume, and dynamic 15O-water images were collected for 7.75 min after injection. Peak total coincidence count rates did not exceed 700 kcps and were therefore well within the ability of the tomograph to perform accurate dead-time corrections (19). Metabolism imaging was performed using 259–407 MBq of 18F-FDG, prepared using the method of Hamacher et al. (20). 18F-FDG radiochemical purity was in excess of 95%, and specific activity was greater than 47 GBq/µmol in all cases. 18F-FDG was infused over 2 min in a 7- to 10-mL volume. Dynamic imaging was performed for 60 min after the start of the 18F-FDG infusion. For both tracers, dynamic imaging data were corrected for random coincidences, scattered coincidences, and attenuation and were reconstructed into 35 x 128 x 128 matrices using a Hanning filter yielding a reconstructed spatial resolution of 10–12 mm (19). Image count data were converted to kBq/cm3 values obtained weekly by scanning calibration vials of known activity measured in a dose calibrator (Radioisotope Calibrator CRC-7; Capintec, Inc.). PET imaging studies were performed before therapy and were repeated after approximately 2 mo of therapy.
PET Image Analysis
Analysis of dynamic images was performed as previously described (8). Regions of interest (ROI) were drawn over the tumor, contralateral normal breast, and left ventricle to obtain the blood time-activity curves (21). Tumor ROIs were 1.5-cm-diameter circles placed on 3 adjacent imaging planes (total axial distance, 1.3 cm) and surrounded the area of maximal tumor 18F-FDG uptake seen on the 30- to 60-min summed images. This area was chosen to be representative of the most metabolic portion of the tumor and therefore likely represented the area with the most biologically aggressive behavior. The area of highest 18F-FDG uptake was used for both the pretherapy and the 2-mo images, even if the location of those sites was slightly different on the pretherapy and 2-mo images. Because some breast tumors substantially changed in size and shape over the course of treatment, it was difficult to ensure that exactly the same region was used in both analyses. We therefore chose to use the area of maximum 18F-FDG uptake to guide consistent region selection over the course of treatment.
Water studies were analyzed according to the method of Wilson et al. (22) using a 1-compartmental model as previously described (8). In the current analysis, parameters were estimated through an optimized modeling approach using the software package Berkeley Madonna. Model optimization was verified using simulated time-activity curves generated by the modeling program used in previous analyses, and parameter estimates were compared with estimates from our previous analysis (8) obtained using EXCEL (Microsoft). Parameter estimates using the current approach yielded similar results (r = 0.95) to those of our previous approach. Simulations of data with statistical noise added to match that observed in clinical studies revealed an SE of 13% for blood flow. A single repeated study on 1 patient yielded a difference of 11% for blood flow.
18F-FDG studies were analyzed through a standard Patlak-Gjedde graphical analysis approach to estimate the tracer flux constant, Ki (mL/min/g), obtained from the slope of the graphical relationship of normalized tissue uptake versus normalized time (23), using the decay-corrected data obtained from 30 to 60 min after injection. MRFDG values (µmol/min/100 g) were calculated as the product of plasma glucose (µmol/mL) and Ki.
To account for changes in tumor size over the course of treatment, partial-volume correction was performed. Size estimates were obtained from ultrasound, mammography, or physical examinations, depending on which examination best delineated tumor boundaries. Partial-volume correction was not applied to the posttreatment scans of 5 patients whose tumor uptake could not be clearly distinguished from the normal breast. In this case, ROI placement was based on the location of the tumor on the pretherapy scan.
Tumor time-activity curves for 15O-water and 18F-FDG were corrected for partial-volume effects as follows (24):
 | (Eq. 1) |
Because the statistical noise in individual time points on the tumor and background time-activity curves can be high, we also performed a simplified analysis assuming that blood flow and MRFDG behave like simple tracer uptake measures according to the following equation:
 | (Eq. 2) |
For each imaging study, tumor parameter estimates were recorded without partial-volume correction, with full partial-volume correction (Eq. 1), and with approximate partial-volume correction (Eq. 2).
Statistical Analysis
Differences in the change in quantitative PET measurements for responders versus nonresponders and the association between the change in PET measures and the pathologic degree of response (NR, PR, or CR) versus PET measures were tested using the Kruskal-Wallis test. Analysis of DFS and overall survival (OS) was performed using Kaplan-Meier curves. Univariate analysis testing of the association of clinical, pathologic, and PET parameters with DFS and OS was performed using the Wilcoxon test. All statistical analyses were performed using the JMP software package (SAS Institute).
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONREFERENCES |
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Treatment
Thirty-two of 35 patients receiving neoadjuvant chemotherapy underwent weekly dose-intensive doxorubicin with granulocyte colony-stimulating factor support. Twenty-eight of 32 had doxorubicin plus cyclophosphamide; 2 of 32 had doxorubicin, cyclophosphamide, and fluorouracil; and 2 of 32 had doxorubicin only. Of the remaining 3 patients, 1 received 3-wk cycles of docetaxel and vinorelbine, 1 underwent cyclophosphamide/methotrexate/fluorouracil chemotherapy with concurrent radiation, and 1 was treated with weekly paclitaxel and trastuzumab. PET imaging results were not used to select chemotherapy regimens. The mean duration of chemotherapy was 14.4 wk (range, 8–24 wk). A mean of 0.9 (range, 0–5) treatment was withheld because of toxicity or patient illness over the course of therapy. After the completion of therapy, 27 patients underwent mastectomy and 8 patients underwent lumpectomy. Surgery was performed a mean of 3.2 wk after the completion of therapy (range, 0.7–1.9 wk). Pretherapy PET imaging was performed a mean of 4.1 d (range, 0–12 d) before the first chemotherapy dose. The second PET examination, performed during therapy, occurred a mean of 9.3 wk (range, 6–15 wk) after the first chemotherapy dose.
Response
Clinical response to neoadjuvant chemotherapy was determined by serial measurements of tumor dimensions. Clinical measurement of tumor size was made by ultrasound in 23 patients, mammography in 1 patient, and physical examinations in 9 patients. Tumor size measurements from MRI were used in 2 patients not routinely followed by the other imaging modalities and whose tumors were difficult to follow by physical examinations. Pathologic response was based on examination of the surgical specimen. Comparison of clinical and pathologic response is summarized in Table 1. In general, there was agreement between resistant and responsive tumors (NR vs. CR or PR), with discrepancies in the extent of response (CR vs. PR). Of 14 patients with a pathologic macroscopic CR, 3 had no evidence of invasive disease by microscopy (microscopic CR) and 11 had residual microscopic invasive carcinoma (microscopic PR). Chemotherapy regimen type was not significantly associated with response. Twenty-six of 35 patients had one or more positive nodes at surgery after chemotherapy (median number of positive nodes, 2.5). Twenty-two of 26 (85%) patients with positive nodes at the time of surgery had abnormal axillary 18F-FDG uptake on the pretherapy PET scan.
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Figure 2 and Table 2 describe the changes in MRFDG and blood flow over the course of therapy for clinical responders versus nonresponders, and Figure 3 and Table 3 describe MRFDG and blood flow changes for the different categories of pathologic response (NR, PR, and CR). Measures are reported without partial-volume correction and with approximate partial-volume correction (Eq. 2) and full partial-volume correction (Eq. 1). Without partial-volume correction, MRFDG declined more for clinical responders than for nonresponders (P = 0.01). With simple partial-volume correction, the difference was of borderline significance (P = 0.05). There was not a significant association between the percentage decline in MRFDG and pathologic response, especially after correction for partial-volume effects. Blood flow, on the other hand, showed a striking average difference between clinical responders and nonresponders, with responders showing an average decline in blood flow and nonresponders showing an average increase in blood flow (P < 0.005 for the difference). There was also an association between the change in blood flow and pathologic response (P = 0.001). Both associations remained highly statistically significant after partial-volume correction by both full and simplified methods. Other factors, including chemotherapy regimen, were not significantly associated with response or changes in PET estimates.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONREFERENCES |
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Several other studies have shown that serial 18F-FDG PET accurately monitors response, in that patients with a favorable response to therapy had a greater decline in 18F-FDG uptake than did patients with a poorer response (9–13). We found similar results in data that were not partial-volume corrected but found smaller, less significant differences after partial-volume correction. A limitation of our approach is that the precise assessment of tumor size in treated breast cancer is difficult (3), and this difficulty could conceivably decrease the reliability of the partial-volume-corrected data. We would expect a similar partial-volume effect for both blood flow and MRFDG; however, changes in blood flow were significantly associated with response, even after partial-volume correction. These results suggest that a decrease in tumor size contributes to the apparent decline in 18F-FDG uptake in LABC patients responding to neoadjuvant chemotherapy. This does not necessarily diminish the utility of 18F-FDG PET for measuring breast cancer response to therapy but should be considered in interpreting the clinical and biologic significance of a decline in apparent 18F-FDG PET uptake in a shrinking tumor.
It is likely that the timing of follow-up 18F-FDG PET relative to the start of chemotherapy affects the difference in 18F-FDG uptake for responders versus nonresponders. For example, Smith et al. (12) found a more significant difference in 18F-FDG uptake for patients with CR versus patients with other than CR after the first dose of chemotherapy and a less significant difference for scans taken after the fourth dose of chemotherapy. Although only patients with CR had an average decline in 18F-FDG uptake after the first dose in the Smith study, both categories of patients had an average decline in 18F-FDG uptake after the fourth dose, similar to our findings. The timing of our 2-mo scan was similar to the timing of the fourth-dose scan in the Smith study. It is possible that by 2 mo, effects such as neovascularization and inflammatory cell infiltration may confound estimation of response using tumor glucose metabolism.
In our study, tumor response and percentage change in blood flow were significantly correlated, even with correction for partial-volume effects. The residual blood flow after 2 mo of therapy predicted DFS. Tumor blood flow is influenced by a variety of factors, including tumor vascularity (26). The association of residual blood flow with DFS parallels other studies showing predictive capability, in untreated tumors, for histologically based measures of breast tumor vascularity (14,15,27). The strong association of blood flow change and response may also explain why imaging studies influenced by tumor blood flow and vascularity, such as contrast-enhanced MRI, 99mTc-sestamibi imaging, and Doppler ultrasound, have been shown to accurately measure the response of LABC to neoadjuvant chemotherapy (17,28–32). These modalities may, in fact, provide more clinically feasible methods of assessing tumor blood flow over the course of therapy.
Although there are significant associations between the changes in blood flow and response to treatment, there is considerable overlap in blood flow change over therapy between response categories. Thus, it would be difficult to make clinical decisions after 2 mo of treatment based solely on the PET findings. The importance of our findings is that they elucidate some of the phenotypic factors of resistant LABC that would be difficult to measure without quantitative in vivo imaging. Our findings also indicate that the incorporation of information on tumor biology after treatment may enhance the current practice of making postchemotherapy decisions based solely on tumor size. In particular, together with our previous analysis of pretherapy blood flow and metabolism (8), we found LABC resistance to neoadjuvant chemotherapy to be associated with high pretherapy glucose metabolism, a high pretherapy ratio of glucose metabolism to blood flow, and failure to diminish tumor blood flow with therapy. One possible explanation for these findings is tumor hypoxia, as illustrated in Figure 6. Hypoxia has been established as a factor in radiotherapy resistance but has more recently also been implicated in resistance to chemotherapy (33–35). Recent work has shown that tumor hypoxia, through a variety of mediators including the transcription factor, hypoxia-inducible factor 1 (HIF-1), leads to several downstream effects that may explain some of our findings (33,36). HIF-1 leads to increased glycolysis and expression of glycolytic enzymes, possibly explaining our finding of increased glucose metabolism in many resistant tumors (36). Hypoxia and HIF-1 lead to strong angiogenic signals (37), which would explain persistent or even increased blood flow with treatment. Finally, recent work has suggested that hypoxia reduces cell cycling (35) and that alterations in metabolism accompanying hypoxia may confer resistance to apoptosis (38–40), both of which would diminish response to cytotoxic chemotherapy. These concepts form a hypothesis for our ongoing work to investigate the tumor biology underlying our findings, including PET imaging measurements of tumor hypoxia and in vitro assay of tumor biopsy material for the downstream effects of hypoxia.
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CONCLUSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONREFERENCES |
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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For correspondence or reprints contact: David A. Mankoff, MD, PhD, Division of Nuclear Medicine, Box 356113, UWMC, 1959 NE Pacific St., Seattle, WA 98195.
E-mail: dam{at}u.washington.edu
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REFERENCES |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONREFERENCES |
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