Purpose: To evaluate the clinical value of positron emission tomography (PET) for monitoring chemotherapy in metastatic breast cancer.

Experimental Design: Twenty patients with hormonorefractory or hormonoreceptor-negative multimetastatic breast cancer were prospectively included. PET studies were done at baseline, at day 21 after the first cycle and at day 21 after the third cycle of chemotherapy. Metabolic response was defined based on visual and various modes of standardized uptake value (SUV) analysis of sequential PET studies.

Results: After one cycle, PET indicated a partial response in 12 patients, stable disease in 7 patients, and progressive disease in 1 patient, according to the visual analysis. After three cycles, PET showed a complete response in 5 patients, partial response in 11 patients, stable disease in 3 patients, and progressive disease in 1 patient. Seventy-five percent of the patients showing a metabolic response on visual analysis effectively responded to the treatment. The average SUV decreased on both the second and the third PET study, but only changes measured after three cycles of chemotherapy predicted the clinical response to chemotherapy and the overall survival. All methods for calculating the SUV (normalized for body weight, body surface area, or lean body mass) provided similar results.

Conclusion: Semiquantitative analysis of [18F]fluorodeoxyglucose-PET studies done after three cycles of chemotherapy is useful for monitoring the response to chemotherapy in metastatic breast cancer.

Previous studies have shown that positron emission tomography (PET) using the glucose analogue [18F]fluorodeoxyglucose ([18F]FDG) is useful for staging or restaging breast cancer (15). As chemotherapy is the standard treatment for hormonorefractory metastatic breast cancer, accurate monitoring of the response to treatment is a major clinical challenge. The limitations of conventional imaging techniques are well known. In particular, they cannot distinguish viable tumor tissue from fibrotic scar tissue in patients with residual masses during or after treatment. Furthermore, tumor shrinkage is sometimes only apparent after the administration of several doses of toxic and expensive chemotherapy. An earlier identification of responding patients may allow rapid change or discontinuation of ineffective treatment regimens. PET is more accurate than conventional imaging studies for monitoring response to treatment in various tumors (6). Few data are available about metastatic breast cancer, but Schwarz et al. (7) reported that, in a series of 11 patients, visual analysis of PET studies done as early as after one cycle of chemotherapy predicted the response to treatment. On the other hand, there remain several unanswered questions as regard to the optimal methodology for measuring the FDG uptake in this setting (8).

The aim of this study was to evaluate whether PET done after one and three cycles of chemotherapy could predict the short-term response to chemotherapy, as measured at 6 months, and the long-term objective response to chemotherapy [event-free survival (EFS) and overall survival (OS)]. A secondary aim was to verify whether visual analysis and various methods for calculating the standardized uptake value (SUV) done equally as predictive variables.

Patients and chemotherapy. Twenty patients with confirmed metastatic breast cancer were prospectively enrolled in this study. The median number of metastatic sites was 5 (range, 2-8). Fifteen of 20 patients suffered from bone metastases, 12 from lung or pleural metastases, 14 from lymph node infiltration, and 5 from liver metastases. Patients with symptomatic brain metastases were excluded. All patients had to be candidates for chemotherapy. They were either hormonoreceptor negative or refractory to hormonotherapy. The treatment being evaluated was anthracycline based if the patient had not been pretreated by adjuvant chemotherapy, which was the case for four patients. The 16 other patients received taxane-based chemotherapy because they received anthracycline-based chemotherapy in the adjuvant setting. It consisted of docetaxel (100 mg/m2) in 12 patients or paclitaxel (70-80 mg/m2) in four patients, including one who also received Herceptin (2 mg/m2). The anthracycline-based regimen consisted of 5-fluorouracil (500 mg/m2), epirubicine (75 mg/m2), and cyclophosphamide (600 mg/m2). One cycle of chemotherapy was administered every 3 weeks. All patients gave informed consent to undergo PET studies in addition to blood analysis (tumor marker CA15.3) and conventional imaging procedures for monitoring response to chemotherapy. All patients were followed up until death. Conventional imaging procedures were carried out according to the routine clinical practice in our institution and included computed tomography (CT) scanning, ultrasonography, and bone scanning, depending on the metastatic sites. Fifteen patients had target lesions that were evaluated according to the Response Evaluation Criteria in Solid Tumors, including 12 lung involvements followed by chest CT and 3 liver involvements followed by abdominal CT (12). There were only three patients with lung metastases only; all the other patients had at least two metastatic sites. One patient with both nontarget lesions (biopsy-proven skin metastases) and target lesions (enlarged axillary nodes) developed brain metastases visualized on magnetic resonance done after six cycles. One patient had only nontarget lesions, which rapidly progressed (bone metastases on bone scintigraphy). Three patients had bone metastases that were clinically (assessment of pain and functional limitation) and biologically (CA15.3) followed. Following these criteria, patients with progressive disease or stable disease were considered as nonresponders to chemotherapy, and patients with partial or complete response were considered as responders to chemotherapy. This assessment was done after six cycles of chemotherapy and is defined as the clinical response after treatment completion.

PET studies. All studies were done using the C-PET scanner (UGM-Philips, Milpitas, CA). The system has been fully described elsewhere (9). All patients fasted for at least 4 hours before tracer injection. Blood glucose level was measured in each case and did not exceed 7.77 mmol/L (140 mg/dL). Patients were injected i.v. with 3.9 ± 0.5 MBq/kg FDG (mean ± SD, 0.105 ± 0.014 mCi/kg) through an indwelling catheter. Acquisition was started 69 ± 13 minutes postinjection (mean ± SD; range, 53-94) for the first scan, 71 ± 21 minutes postinjection (range, 47-118) for the second scan, and 71 ± 12 minutes postinjection (range, 49-91) for the third scan. There were no statistically significant differences among these uptake times. The PET acquisition consisted of five or six bed positions. Five-minute emission scans, 1-minute transmission scans using a 137Cs point source, and 8-second emission contamination scans were interleaved. Images were reconstructed using the ordered subset-expectation maximization algorithm and corrected for decay, scatter, random coincidences, and attenuation.

Data analysis. PET studies were done at baseline (PET1), at day 21 after the first cycle (PET2) and at day 21 after the third cycle (PET3) of chemotherapy. The tumor marker CA15.3 was increased at baseline in 12 of 20 patients. We only followed the tumor marker level after one and three cycles of chemotherapy in these patients. The metabolic response based on visual analysis of sequential PET studies was assessed according to European Organization for Research and Treatment of Cancer 1999 recommendations (10): (a) complete response for complete resolution of [18F]FDG uptake within the tumor volume (indistinguishable from surrounding normal tissue); (b) partial response for a significant decrease in tumor uptake and/or a decrease in the total number of hypermetabolic lesions; (c) stable disease for no visible increase of tumor uptake and the absence of new hypermetabolic lesions; and (d) progressive disease for a visible increase in tumor uptake or new hypermetabolic lesion(s). Any focus visualized in the three planes and which did not correspond to physiologic activity was considered as abnormal. Furthermore, semiquantitative analysis of [18F]FDG uptake (SUV) was done using the median value of SUV changes between PET1 and PET2 and between PET1 and PET3: tumors showing changes greater than the median value were considered as responders and those showing changes equal or lower than the median value were considered as nonresponders.

Regions of interest were placed visually in the transversal slice over focal lesions, in which [18F]FDG accumulation was the highest. The regions of interest followed an isocontour at 60% of the maximum pixel value. Average and maximum SUVs normalized for body weight (SUVBW), for body surface area (SUVBSA), and for lean body mass (SUVLBM) were calculated using the following equations (10, 11):

\[\begin{array}{l}\mathrm{SUV_{BW}}=\frac{\mathrm{tissue\ concentration\ (MBq/mL)}}{\mathrm{injected\ dose\ (MBq)/patient\ body\ weight(g)}}\\\\\mathrm{SUV_{BSA}}=\frac{\mathrm{tissue\ concentration(MBq/mL)}}{\mathrm{injected\ dose(MBq)/BSA(m^{2})}}\\\\\mathrm{with\ BSA\ =\ 0.007184\ {\times}\ body\ weight^{0.425}\ {\times}body\ height^{0.725}}\\\\\mathrm{SUV_{LBM}}=\frac{\mathrm{tissue\ concentration\ (MBq/mL)}}{\mathrm{injected\ dose(MBq)/LBM}}\\\\\mathrm{with\ LBM_{women}\ =\ (1.07\ {\times}\ body\ weight)\ {-}\ 148\ (body\ weight/body\ height)^{2}}\\\\\mathrm{and\ LBM_{men}\ =\ (1.1\ {\times}\ body\ weight)\ {-}\ 120\ (body\ weight/body\ height)^{2}}\end{array}\]

Statistical analysis. Paired Wilcoxon's tests were used to compare injected doses and SUV values between the three PET examinations. Mann-Whitney U tests were used to compare changes in SUVs between PET1 and PET2 and between PET1 and PET3. Relationship between metabolic response (patients stratified according to the median value of SUV variations) and clinical response was analyzed by Fisher's exact tests. EFS and OS were determined by standard Kaplan-Meier survival analysis, and comparison between groups was done by the log-rank test. EFS was defined as the time interval from the date of enrollment in the study until progression, relapse, death, or date of last follow-up. OS was calculated from the date of enrollment until death from any cause. Relationships between SUV values on PET1, PET2, or PET3 and survival were also evaluated using a linear regression model. If these relationships were not linear, Spearman's correlation coefficients were calculated. Relationship between changes of tumor markers CA15.3 and changes of SUV were evaluated using a linear regression analysis between CA15.3 slopes and SUV slopes for each patient. Regression models assumed residual normality and homoscedasticity, both of which being graphically verified. In all cases, the level of significance was set at 0.05. All analyses were done using Graphpad prism version 4.0b 2004 (Graphpad Software, San Diego, CA).

Visual assessment of tumor response. The patient characteristics and outcome data are summarized in Table 1. Among the 12 patients who showed a partial metabolic response after one cycle, nine effectively responded to treatment (partial or complete response at 6 months). Eight patients showed either stable or progressive metabolic disease, with only two of them eventually responding to treatment. After three cycles, 16 patients showed either complete or partial metabolic response. Six of these did not respond to treatment. Three of the four patients who were classified as stable metabolic disease did not respond to chemotherapy.

Table 1.

Patient characteristics

PatientAgeER statusMenopauseNo. previous chemotherapyTreatmentMetastases
Changes in SUV (%)
Clinical responseSurvival (mo)
LNBoneVisceralPET1-PET2PET1-PET3
51 − Docetaxel − − −10 −59 677 
59 Docetaxel − −15 −37 NR 252 
55 − Docetaxel − −36 −59 538 
52 − FEC − −19 −40 NR 818 
37 − − Paclitaxel/Herceptin − − −47 −31 NR 340 
66 FEC − − −20 −37 406 
50 − − Paclitaxel − − −51 −59 NR 531 
25 − − Docetaxel − +9 +14 NR 547 
46 − FEC −7 −49 787 
10* 55 − Docetaxel − −26 −63 NR 124 
11 63 Paclitaxel − −31 −75 505 
12 54 FEC − − −57 −36 796 
13 60 − Docetaxel − −55 −70 261 
14 47 − Docetaxel −83 623 
15 53 − Paclitaxel − −46 −71 645 
16 66 Docetaxel − −63 −50 1,005 
17 45 − Docetaxel − −58 −72 1,014 
18 61 Docetaxel − −31 −41 504 
19 51 Docetaxel − −12 −15 NR 103 
20 67 − Docetaxel − − −8 −41 NR 513 
PatientAgeER statusMenopauseNo. previous chemotherapyTreatmentMetastases
Changes in SUV (%)
Clinical responseSurvival (mo)
LNBoneVisceralPET1-PET2PET1-PET3
51 − Docetaxel − − −10 −59 677 
59 Docetaxel − −15 −37 NR 252 
55 − Docetaxel − −36 −59 538 
52 − FEC − −19 −40 NR 818 
37 − − Paclitaxel/Herceptin − − −47 −31 NR 340 
66 FEC − − −20 −37 406 
50 − − Paclitaxel − − −51 −59 NR 531 
25 − − Docetaxel − +9 +14 NR 547 
46 − FEC −7 −49 787 
10* 55 − Docetaxel − −26 −63 NR 124 
11 63 Paclitaxel − −31 −75 505 
12 54 FEC − − −57 −36 796 
13 60 − Docetaxel − −55 −70 261 
14 47 − Docetaxel −83 623 
15 53 − Paclitaxel − −46 −71 645 
16 66 Docetaxel − −63 −50 1,005 
17 45 − Docetaxel − −58 −72 1,014 
18 61 Docetaxel − −31 −41 504 
19 51 Docetaxel − −12 −15 NR 103 
20 67 − Docetaxel − − −8 −41 NR 513 

NOTE: The estrogen receptor status and menopausal status are those at the time of diagnosis. The SUV is the SUVbw maximum. See text for dosages of 5-fluorouracil, epirubicine, and cyclophosphamide.

Abbreviations: ER, estrogen receptor; FEC, 5-fluorouracil, epirubicine, and cyclophosphamide; LN, lymph node; R, responders, NR, nonresponders.

*

This patient did not complete the treatment because of acute toxicity.

Semiquantitative measurements (SUVs). There was no significant difference between injected doses (MBq/kg) or uptake durations on PET1, PET2, and PET3 (P = 0.88 and 0.87, respectively, for injected doses and uptake durations). Whether the SUVs were normalized for body weight (SUVBW), for body surface area (SUVBSA), and for lean body mass (SUVLBM), they decreased gradually between the three examinations (Fig. 1). Both SUVs were the highest on the first PET and the lowest on PET3. In addition, the reduction in SUV was less important between the PET2 and PET3 than between the PET1 and PET2.

Fig. 1.

Evolution of the SUVs after one and three cycles of chemotherapy. *, statistically significant differences. R, clinical response to chemotherapy; NR, absence of clinical response to chemotherapy.

Fig. 1.

Evolution of the SUVs after one and three cycles of chemotherapy. *, statistically significant differences. R, clinical response to chemotherapy; NR, absence of clinical response to chemotherapy.

Close modal

Relationship between metabolic response and clinical response to chemotherapy. The visual assessment of the metabolic response after one or three cycles was not predictive of the clinical response to chemotherapy (Fisher's exact tests, >5%; Fig. 2). Similarly, the SUV changes after one cycle did not predict the clinical response, regardless of the method for calculating the SUVs. After three cycles, however, there was a marked difference between the changes in SUVs in clinical responders (52-56% decrease, depending on SUV calculation methods) and nonresponders (16-26% decrease). These differences were statistically significant for all the methods used for calculating the SUV (data not shown). The Fisher's exact test between metabolic responses measured as changes in SUV after the third cycle and clinical response after six cycles was statistically significant (P = 0.0198), showing that metabolic changes after three cycles were predictive of the clinical response after six cycles.

Fig. 2.

Metabolic responses versus clinical response after six cycles of chemotherapy. Metabolic responders are those patients with SUV changes greater than the median value. Visual response is based on the European Organization for Research and Treatment of Cancer criteria. Fisher's exact tests are not significant, except for the changes in SUVs after three cycles (P = 0.0198).

Fig. 2.

Metabolic responses versus clinical response after six cycles of chemotherapy. Metabolic responders are those patients with SUV changes greater than the median value. Visual response is based on the European Organization for Research and Treatment of Cancer criteria. Fisher's exact tests are not significant, except for the changes in SUVs after three cycles (P = 0.0198).

Close modal

Patients' outcome. All the patients died of their disease. The median survival was 527 days (103-1,014). The metabolic response, when assessed using visual analysis, was not correlated with the patients' survival. Similarly, there was no relationship between the survival and the SUVs on PET1, PET2, or PET3. For all the SUVs, the Spearman's coefficients were relatively low and all Ps were >5 % (data not shown).

The clinical response measured at 6 months using conventional methods predicted the OS but not the EFS (Fig. 3). Similarly, the metabolic response measured as changes in SUV after the third cycle of chemotherapy predicted the OS but not the EFS (Fig. 4). However, early changes in SUVs (after the first cycle of chemotherapy) were not predictive of the long-term outcome (Fig. 5).

Fig. 3.

Kaplan-Meier analysis showing the EFS between nonresponders (NR; stable disease + progressive disease; median, 209 days; range, 47-450) and responders (R; partial response + complete response; median, 248 days; range, 155-557) as evaluated by conventional methods. Statistical difference of OS between nonresponders (median, 452 days; range, 102-613) and responders (median, 667 days; range, 257-998) as evaluated by conventional methods.

Fig. 3.

Kaplan-Meier analysis showing the EFS between nonresponders (NR; stable disease + progressive disease; median, 209 days; range, 47-450) and responders (R; partial response + complete response; median, 248 days; range, 155-557) as evaluated by conventional methods. Statistical difference of OS between nonresponders (median, 452 days; range, 102-613) and responders (median, 667 days; range, 257-998) as evaluated by conventional methods.

Close modal
Fig. 4.

Kaplan-Meier estimates of the EFS in metabolic nonresponders (median EFS, 208 days; range, 47-450) and metabolic responders after three cycles of chemotherapy (median, 241 days; range, 104-557). There is a statistically significant difference in OS between nonresponders (median, 447; range, 102-613) and responders (median, 721 days; range, 122-998). The median values of SUV variations to discriminate responders from nonresponders were −40% and −45% for SUVavg and SUVmax, respectively.

Fig. 4.

Kaplan-Meier estimates of the EFS in metabolic nonresponders (median EFS, 208 days; range, 47-450) and metabolic responders after three cycles of chemotherapy (median, 241 days; range, 104-557). There is a statistically significant difference in OS between nonresponders (median, 447; range, 102-613) and responders (median, 721 days; range, 122-998). The median values of SUV variations to discriminate responders from nonresponders were −40% and −45% for SUVavg and SUVmax, respectively.

Close modal
Fig. 5.

Kaplan-Meier estimates of the EFS in metabolic nonresponders (median EFS, 226 days; range, 47-450) and metabolic responders after one cycle of chemotherapy (median, 239 days; range, 155-557). The OS was similar among nonresponders (median, 513; range, 102-775) and responders (median, 582 days; range, 257-998). The median values of SUV variations to discriminate responders and nonresponders were −28% for both SUVavg and SUVmax.

Fig. 5.

Kaplan-Meier estimates of the EFS in metabolic nonresponders (median EFS, 226 days; range, 47-450) and metabolic responders after one cycle of chemotherapy (median, 239 days; range, 155-557). The OS was similar among nonresponders (median, 513; range, 102-775) and responders (median, 582 days; range, 257-998). The median values of SUV variations to discriminate responders and nonresponders were −28% for both SUVavg and SUVmax.

Close modal

Correlation between [18F]FDG uptake and CA15.3 tumor markers. Among the 12 patients with increased levels of the tumor marker CA15.3 before starting the chemotherapy, the values were 139 ± 174 units/mL (mean ± SD) at baseline, 192 ± 205 units/mL after one cycle, and 75 ± 43 units/mL after three cycles of chemotherapy. There was no significant correlation between CA15.3 at baseline, after one or three cycles of chemotherapy and SUV values at the corresponding time points. Based on the three measurements of CA15.3, a slope was calculated for each patient. These slopes represented the CA15.3 evolution throughout the first three cycles of chemotherapy. Comparison between CA15.3 slopes and SUV slopes were done using a linear model of regression. The coefficients of regression were all negative but the results did not reach statistical significance (Fig. 6).

Fig. 6.

Relationship between tumor marker levels (CA15.3) and SUVBW. Individual slopes were calculated for each patient, both for changes in CA15.3 and for changes in SUVBW, before the start of chemotherapy, after one cure (•), and after three cures (○). Again, the coefficients of regression were all negative, suggesting a relationship between metabolic and biological responses, but it was not statistically significant. Similar results were found for other calculations of SUV.

Fig. 6.

Relationship between tumor marker levels (CA15.3) and SUVBW. Individual slopes were calculated for each patient, both for changes in CA15.3 and for changes in SUVBW, before the start of chemotherapy, after one cure (•), and after three cures (○). Again, the coefficients of regression were all negative, suggesting a relationship between metabolic and biological responses, but it was not statistically significant. Similar results were found for other calculations of SUV.

Close modal

Accurate assessment of tumor extent and response to treatment is an important issue. PET is now increasingly used in the field of breast cancer, as metabolic imaging alone may provide results very similar to those obtained with the combination of several conventional imaging methods (5, 13). In particular, PET may be useful when a tumor recurrence is suspected but conventional staging methods are negative or inconclusive, especially in case of increased tumor marker levels (14). [18F]FDG-PET is also more sensitive than serum tumor markers in detecting recurrence in patients with clinical findings suggestive of relapsed breast cancer (14). In our study, only 12 of 20 multimetastatic breast cancer patients had an abnormal CA15.3 tumor maker level.

[18F]FDG-PET was also proposed for monitoring the response of breast cancer to chemotherapy and thus guide therapeutic regimen. The assessment of the response to therapy by PET is based on the reduction or the complete abolition of the tumor [18F]FDG uptake, depending on the reduction of the tumor glucose metabolism or cellular death, respectively. Such approach was applied for assessing the response to chemotherapy given before surgery (neoadjuvant chemotherapy). [18F]FDG-PET may provide an earlier and noninvasive evaluation, which offers the possibility to modify early on therapeutic regimen to improve the likelihood of obtaining a complete response. Preliminary studies with small cohorts of patients showed a correlation between the early reduction of the tumor [18F]FDG uptake and the clinical response at the end of neoadjuvant chemotherapy (15, 16). No such decline was observed in patients who did not achieve a partial or a complete response. In contrast, conventional imaging studies failed to determine the treatment response as early on as PET did. Further studies with larger series showed that the early reduction of tumor [18F]FDG uptake was correlated with the macroscopic response at the end of neoadjuvant chemotherapy (1719). However, the SUV cutoff values for discriminating responders from nonresponders varied among the studies. For instance, in the study of Schelling et al. (18), the nonresponding patients presented on average a reduction of [18F]FDG tumoral uptake of 15%, whereas Smith et al. (17) reported an average increase of 43% for the nonresponders. Likewise, by using a receiver operator characteristic analysis in the study of Schelling et al., a decrease in SUV after the first cycle of chemotherapy to <55% of baseline discriminated between responders and nonresponders (sensitivity of 100% and specificity of 85%), whereas, in the study of Smith et al., a 20% reduction in [18F]FDG uptake after the first cycle of chemotherapy predicted the response to therapy with a sensitivity of 90% and a specificity of 74%. Differences in the cutoff values for the SUVs may be explained not only by the high variability of breast tumor biology but also by the methodology used to assess the metabolic activity, including the type of region of interest and method for calculating the SUV.

In contrast to the previous studies in the neoadjuvant setting, we assessed early on the response to chemotherapy by PET in multimetastatic breast cancer. There are very few data in the literature in this field. In a small study of 12 metastatic breast cancer patients, Gennari et al. (20) observed a significant decrease in tumor glucose metabolism after the first cycle of chemotherapy in patients who responded to treatment. In contrast, no significant decrease was reported in case of treatment failure. Schwartz et al. (7) evaluated 11 patients with 26 metastatic lesions after one and two cycles of chemotherapy. The decrease in FDG uptake was higher in responding lesions than in the nonresponding locations. In addition, visual analysis of the PET images was able to predict the overall response to treatment. There was also a trend toward longer survival in metabolic responders, although it did not reach statistical significance.

Our results somewhat contradict those previously published in the literature. Indeed, our primary hypothesis is only partly verified: In our series, PET was able to predict the short-term response to chemotherapy and the OS, but only when it was done after three cycles of chemotherapy. In fact, PET done after three cycles of chemotherapy provided results that were very similar to those obtained with conventional methods after completing the treatment. When the metabolic response was evaluated after one cycle of chemotherapy, neither the visual analysis nor the changes in SUVs were able to reliably predict the short-term outcome (clinical response at 6 months) or the long-term outcome (EFS and OS). It seems clearly that PET is more predictive at midcourse than early on during treatment, but statistically, our population is not large enough to rule out a potential role for the early PET. An obvious question arises considering these results: if PET predicts the outcome at midcourse of treatment; would it provide any additional and clinically relevant information compared with conventional methods done at the same time? Our study was not designed to answer this question, as all lesions were not systematically evaluated using conventional technique after three cycles. It is well known however that these techniques are unable to correctly evaluate response after only one cycle (21). The difficulty to assess both the early and the late responses in bone metastases, which are highly prevalent in this population, is also well known. Tumor markers are not very useful either, as up to 25% of patients show an initial increase while responding positively to treatment. Our study confirmed this observation, as the median tumor marker level was higher after one cycle that at baseline, and it became lower after three cycles. Changes in CA15.3 level and in SUV measured during chemotherapy were not similar in trend, as none of our patients presented an initial increase in [18F]FDG uptake before responding to treatment.

Although PET was not predictive after one cycle and its added clinical value was not fully established after three cycles, we believe that our results are clinically relevant. It is important to point out that such prediction of outcome was obtained using a very simple method (i.e., the evolution of SUV in the most active lesion identified throughout the entire body). The capability of PET, as a single procedure, to reach such conclusion provides several advantages over alternative methods, whose diagnostic performances vary highly according to the site of the lesions. PET, on the other hand, is both sensitive and specific for detecting malignant involvement of the liver, lung, skeleton, and lymph nodes (1). Further studies are needed to compare conventional techniques, either targeted for evaluating selected lesions or as a battery of tests (systematic combination of chest CT, abdominal CT, bone scintigraphy, or MRI) with a single one, PET or, given a technological developments that is increasingly available, PET/CT.

About the methodologic aspects, we found that semiquantitative analysis provided better results than the simpler visual analysis and that there were no significant differences according to the various methods for calculating the SUVs. In our series, the variation in body weight during chemotherapy was not sufficient to introduce a bias in the measurements of the metabolic activity when the SUV is normalized for the body weight. In addition, we did not normalize the SUVs for blood glucose levels, as previous studies in healthy subjects showed greater within-patient variability in SUV measurements when such correction was applied (22). The question of which approach of region of interest methods gives the best results for tumor response assessment has yet to be answered. In our study, we used one of the commonly used methods (i.e., a 60% threshold-based region of interest method), which is simple and user independent and which gives results relatively independent of lesion size and geometry (23).

The capability of PET to separate responders from nonresponders after three cycles of chemotherapy may be of value for the development of new drugs. Indeed, only those patients with an early response are candidates to continue the treatment. An early change to standard treatment is indicated for the other patients. Furthermore, many new drugs are more cytostatic than cytotoxic and conventional imaging techniques are largely inappropriate for evaluating the response in these circumstances. Assessment of metabolic changes may well be better suited for monitoring the response to these treatments. Finally, early response evaluation may be particularly important when a second-line treatment with curative intent is available. This is the case for example in non-Hodgkin's lymphomas (24).

Our findings suggest that both the short-term survival and the OS are predicted by the metabolic response when assessed after three cycles of chemotherapy and that PET is a better predictor when done at midcourse than after the first cycle. Semiquantitative measurements are superior to the visual analysis of the PET images, regardless of the method for obtaining the SUV. Overall, sequential PET studies are useful for monitoring response to chemotherapy in metastatic breast cancer.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1
Schirrmeister H, Kuhn T, Guhlmann A, et al. Fluorine-18 2-deoxy-2-fluoro-d-glucose PET in the preoperative staging of breast cancer: comparison with the standard staging procedures.
Eur J Nucl Med
2001
;
28
:
351
–8.
2
Smith IC, Ogston KN, Whitford P, et al. Staging of the axilla in breast cancer: accurate in vivo assessment using positron emission tomography with 2-(fluorine-18)-fluoro-2-deoxy-d-glucose.
Ann Surg
1998
;
228
:
220
–7.
3
Wahl RL, Cody RL, Hutchins GD, et al. Primary and metastatic breast carcinoma: initial clinical evaluation with PET with the radiolabeled glucose analogue 2-[F-18]-fluoro-2-deoxy-d-glucose.
Radiology
1991
;
179
:
765
–70.
4
Scheidhauer K, Scharl A, Pietrzyk U, et al. Qualitative [18F]FDG positron emission tomography in primary breast cancer: clinical relevance and practicability.
Eur J Nucl Med
1996
;
23
:
618
–23.
5
Moon DH, Maddahi J, Silverman DH, et al. Accuracy of whole-body fluorine-18-FDG PET for the detection of recurrent or metastatic breast carcinoma.
J Nucl Med
1998
;
39
:
431
–5.
6
Jerusalem G, Hustinx R, Beguin Y, Fillet G. PET scan imaging in oncology.
Eur J Cancer
2003
;
39
:
1525
–34.
7
Schwarz J, Bader M, Jenicke L, Hemminger G, Janicke F, Avril N. Early prediction of response to chemotherapy in metastatic breast cancer using sequential 18F-FDG PET.
J Nucl Med
2005
;
46
:
1144
–50.
8
Hoekstra C, Hoekstra O, Stroobants S, et al. Methods to monitor response to chemotherapy in non-small cell lung cancer with 18F-FDG PET.
J Nucl Med
2002
;
43
:
1304
–9.
9
Adam LE, Karp JS, Daube-Witherspoon ME, et al. Performance of a whole-body PET scanner using curve-plate NaI(Tl) detectors.
J Nucl Med
2001
;
42
:
1821
–30.
10
Young H, Baum R, Cremerius U, et al.; European Organization for Research and Treatment of Cancer (EORTC) PET Study Group. Measurement of clinical and subclinical tumour response using [18F]-fluorodeoxyglucose and positron emission tomography: review and 1999 EORTC recommendations.
Eur J Cancer
1999
;
35
:
1773
–82.
11
DuBois D, DuBois E. A formula to estimate the approximate surface area if height and weight be known.
Arch Intern Med
1916
;
17
:
863
–71.
12
Therasse P, Arbuck SG, Eisenhauer EA, et al.; European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada. New guidelines to evaluate the response to treatment in solid tumors.
J Natl Cancer Inst
2000
;
92
:
205
–16.
13
Rostom AY, Powe J, Kandil A, et al. Positron emission tomography in breast cancer: a clinicopathological correlation of results.
Br J Radiol
1999
;
72
:
1064
–8.
14
Siggelkow W, Rath W, Buell U, Zimny M. FDG PET and tumour markers in the diagnosis of recurrent and metastatic breast cancer.
Eur J Nucl Med Mol Imaging
2004
;
31
Suppl 1:
S118
–24.
15
Jansson T, Westlin JE, Ahlstrom H, et al. Positron emission tomography studies in patients with locally advanced and/or metastatic breast cancer: a method for early therapy evaluation?
J Clin Oncol
1995
;
13
:
1470
–7.
16
Wahl RL, Zasadny K, Helvie M, et al. Metabolic monitoring of breast cancer chemohormonotherapy using positron emission tomography: initial evaluation.
J Clin Oncol
1993
;
11
:
2101
–11.
17
Smith IC, Welch AE, Hutcheon AW, et al. Positron emission tomography using [(18)F]-fluorodeoxy-d-glucose to predict the pathologic response of breast cancer to primary chemotherapy.
J Clin Oncol
2000
;
18
:
1676
–88.
18
Schelling M, Avril N, Nahrig J, et al. Positron emission tomography using [(18)F]Fluorodeoxyglucose for monitoring primary chemotherapy in breast cancer.
J Clin Oncol
2000
;
18
:
1689
–95.
19
Bassa P, Kim EE, Inoue T, et al. Evaluation of preoperative chemotherapy using PET with fluorine-18-fluorodeoxyglucose in breast cancer.
J Nucl Med
1996
;
37
:
931
–8.
20
Gennari A, Donati S, Salvadori B, et al. Role of 2-[18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) in the early assessment of response to chemotherapy in metastatic breast cancer patients.
Clin Breast Cancer
2000
;
1
:
156
–61; discussion 162–3.
21
Choi H. Critical issues in response evaluation on computed tomography: lessons from the gastrointestinal stromal tumor model.
Curr Oncol Rep
2005
;
7
:
307
–11.
22
Paquet N, Albert A, Foidart J, Hustinx R. Within-patient variability of (18)F-FDG: standardized uptake values in normal tissues.
J Nucl Med
2004
;
45
:
784
–8.
23
Krak NC, Boellaard R, Hoekstra OS, et al. Effects of ROI definition and reconstruction method on quantitative outcome and applicability in a response monitoring trial.
Eur J Nucl Med Mol Imaging
2005
;
32
:
294
–301.
24
Jerusalem G, Beguin Y, Fassotte MF, et al. Persistent tumor 18F-FDG uptake after a few cycles of polychemotherapy is predictive of treatment failure in non-Hodgkin's lymphoma.
Haematologica
2000
;
85
:
613
–8.