AJR AJR-based Continuing Ed for Technologists
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


This Article
Right arrow Abstract Freely available
Right arrow Figures Only
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Holdsworth, C. H.
Right arrow Articles by Van den Abbeele, A. D.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Holdsworth, C. H.
Right arrow Articles by Van den Abbeele, A. D.
Social Bookmarking
 Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?
Hotlight (NEW!)
Right arrow
What's Hotlight?
DOI:10.2214/AJR.07.2496
AJR 2007; 189:W324-W330
© American Roentgen Ray Society


Original Research

CT and PET: Early Prognostic Indicators of Response to Imatinib Mesylate in Patients with Gastrointestinal Stromal Tumor

Clay H. Holdsworth1,2, Ramsey D. Badawi3, Judith B. Manola2, Marie F. Kijewski4, David A. Israel2,4, George D. Demetri2 and Annick D. Van den Abbeele2,4

1 Massachusetts College of Pharmacy and Health Sciences, 4 Brook Rd., Unit 11, Salem, NH 03079.
2 Dana-Farber Cancer Institute, Boston, MA.
3 University of California Davis School of Medicine, Sacramento, CA.
4 Brigham and Women's Hospital, Boston, MA.

Received April 30, 2007; accepted after revision June 19, 2007.

 
Address correspondence to C. H. Holdsworth (clayholdsworth{at}yahoo.com).

The cohort for this study was a subset of the patients enrolled in a wider multicenter trial supported by Novartis Oncology. G. D. Demetri serves as a consultant for and receives honoraria from Novartis, Pfizer, and Johnson & Johnson. He also receives research support from Novartis and Pfizer.

WEB This article is a Web exclusive article.


Abstract
Top
Abstract
Introduction
Subjects and Methods
Results
Discussion
References
 
OBJECTIVE. We report results from a pilot study aimed at optimizing the use of CT bidimensional measurements and 18F-FDG PET maximum standardized uptake values (SUVs-max) for determining response to prolonged imatinib mesylate treatment in patients with advanced gastrointestinal stromal tumors (GISTs).

SUBJECTS AND METHODS. Sixty-three patients enrolled in a multicenter trial evaluating imatinib mesylate therapy for advanced GIST underwent FDG PET at baseline and 1 month after initiation of treatment. Of these 63 patients, 58 underwent concomitant CT. Time-to-treatment failure (TTF) was used as the outcome measure. Patients were followed up over a range of 23.7 to 37 months (median, 31.7 months). The predictive power of change in CT bidimensional measurements, change in PET SUVmax, and PET SUVmax at 1 month after initiation of treatment were determined, optimized, and compared. The effectiveness of combining metrics was also evaluated.

RESULTS. Both a threshold PET SUVmax value of 2.5 at 1 month (p = 0.04) and the European Organization for Research and Treatment of Cancer (EORTC) criteria for partial response on FDG PET (25% reduction in PET SUVmax) at 1 month (p = 0.004) were predictive of prolonged treatment success. The Southwest Oncology Group (SWOG) criteria for partial response (3 50% reduction in CT bidimensional measurements) at 1 month were not predictive (p = 0.55) of TTF. Optimizing metrics improved results performance. An optimized PET SUVmax threshold of 3.4 (p = 0.00002), a reduction in the SUVmax of 40% (p = 0.002), and an optimized CT bidimensional measurement threshold—that is, no growth from baseline to 1 month (p = 0.00005)—outperformed the existing standards (i.e., EORTC and SWOG criteria). Combinations of metrics did not improve performance.

CONCLUSION. The two best metrics were the optimized PET SUVmax threshold of 3.4 at 1 month (p = 0.00002) and the optimized CT bidimensional measurement threshold (no growth from baseline to 1 month, p = 0.00005) in this patient group.

Keywords: CT • gastrointestinal stromal tumor • imatinib mesylate • oncologic imaging • PET


Introduction
Top
Abstract
Introduction
Subjects and Methods
Results
Discussion
References
 
Gastrointestinal stromal tumor (GIST) is unresponsive to conventional chemotherapy and may be unresponsive to radiation therapy as well [1-3]. The receptor tyrosine kinase KIT is strongly expressed in GIST [4, 5], and imatinib mesylate is a competitive inhibitor of a specific ATP-binding site on KIT. Imatinib mesylate therapy can be effective in treating GIST, but there is a subgroup of patients whose tumors exhibit primary resistance to imatinib mesylate and another subgroup who subsequently rapidly fail to respond to therapy [6, 7].

The difference in metabolic activity after even a single dose of imatinib mesylate can be shown on 18F-FDG PET scans and is often dramatic [8, 9]. Little or no change can be seen on corresponding CT images initially [10], and over time, lesions may become more noticeable due to lower attenuation [11, 12]. Fewer than 15% of patients exhibit primary resistance to imatinib mesylate or rapidly fail to respond to therapy [6-8]. Patients who initially respond to imatinib mesylate may, over an extended period, develop secondary resistance to imatinib mesylate and the disease subsequently progresses; however, their prognosis remains substantially better than it would have been without imatinib mesylate therapy.

Objective response to therapy in oncology has commonly been defined using Response Evaluation Criteria in Solid Tumors (RECIST) [13] for unidimensional tumor measurements using CT or Southwest Oncology Group (SWOG) criteria [14], which uses CT bidimensional measurements. RECIST requires a 30% reduction in unidimensional measurements to meet the condition for partial response. This definition of partial response corresponds directly to the SWOG criteria that specify a 3 50% reduction in CT bidimensional measurements to satisfy the same condition.

Criteria for therapeutic response assessment have also been developed in the context of functional imaging. The European Organization for Research and Treatment of Cancer (EORTC) has defined guidelines for the use of PET using FDG. These guidelines state that a 25% reduction in the maximum standardized uptake value (SUVmax) should be considered as the threshold for definition of partial response [15, 16].

All of these criteria were originally defined for PET and CT evaluations of prognosis in patients receiving cytotoxic drug therapy or undergoing radiation therapy. Whether the use of such criteria after the initiation of therapy using molecularly targeted kinase inhibitors is generally predictive of outcome is not clear. The EORTC guidelines for partial response have been shown to correlate with outcome in patients with advanced GIST when SUV is measured 2 months after initiation of imatinib mesylate therapy [10]. Similar results were found when PET scans were obtained between 3 and 16 weeks after therapy start [17].

In the literature, a cut point of 2.5 in the SUVmax for FDG PET has also been used to assess response to imatinib mesylate treatment of GIST and has been shown to correlate with outcome when measured 1 month after initiation of imatinib mesylate therapy [9, 18-20]. In contrast, standard CT criteria, such as the RECIST and SWOG criteria, have not been found to be predictive of outcome [21, 22]; however, thresholds showing little or no reduction in CT bidimensional measurements at early time points after initiation of treatment were found to correlate well with outcome [10, 18].

The purpose of study was to evaluate and optimize the use of CT and FDG PET at baseline and 1 month after therapy initiation as predictors of time-to-treatment failure (TTF) in the context of imatinib mesylate treatment of patients with advanced GIST. TTF is defined as the time from the first dose of imatinib mesylate to the earliest occurrence of disease progression, death, or discontinuation from the trial for any medical reason.


Subjects and Methods
Top
Abstract
Introduction
Subjects and Methods
Results
Discussion
References
 
Patient Population
The patient population consisted of 63 patients with advanced GIST enrolled in a phase II trial evaluating imatinib mesylate therapy: 40 men (mean age, 54 years; range, 25-80 years) and 23 women (mean age, 56 years; range, 19-84 years). Patients were enrolled between June 2000 and March 2001. Twenty-seven patients were treated using an initial dose of 400 mg per day of imatinib mesylate, and 36 patients received 600 mg per day.

This study was approved by the institutional review board and performed in an ambulatory setting in two tertiary care oncology academic centers (Dana-Farber Cancer Institute and Brigham and Women's Hospital). Written informed consent was obtained from all patients. The cohort for this study was a subset of the patients enrolled in a wider multicenter trial supported by Novartis Oncology.

Imaging
All 63 patients underwent FDG PET before treatment and 21-40 days after initiation of therapy. Fifty-eight of these patients also underwent CT at baseline and 21-40 days after initiation of therapy. All FDG PET data were acquired on a tomograph (ECAT Exact HR+, Siemens/CTI). The mean dose given to patients was 20 mCi (740 MBq) (range, 7-22 mCi [259-814 MBq]) for the baseline scans and 20 mCi (740 MBq) (range, 16-27 mCi [592-999 MBq]) for the 1-month scans. The mean time between FDG injection and the start of scanning was 51 minutes (range, 27-82 minutes) for baseline scans and 52 minutes (range, 27-87 minutes) for the 1-month scans.

The PET SUVmax value was calculated for the lesion with the most intense uptake at baseline and was subsequently calculated for the same lesion on follow-up scans. No corrections for partial volume effects, lean body mass, or blood glucose levels were applied. Because of the substantial changes in uptake, lesions were not always visible on follow-up images, and in these cases, guidance for location of the lesion for PET SUVmax calculations was obtained from the concomitant CT scan. All scans were obtained after the patient had fasted for 6 hours.

CT data were acquired on an MDCT scanner (Somatom Volume Zoom, Siemens Medical Solutions). Patients were asked to fast for 6 hours before scanning. Oral contrast material (diatrizoate meglumine, 5.0 g, and diatrizoate sodium, 0.75 g, in a 500-mL aqueous solution) was administered approximately 150 minutes and then again 90 minutes before scanning. Immediately before scanning, 100 mL of ioxilan (300 mg/mL) iodinated contrast material was administered IV at a rate of 2 mL/s or slower in patients with limited IV access. Scanning was performed from the thoracic inlet through the pelvis, with the patient breath-holding during scanning of the chest and quietly breathing during scanning of the abdomen and pelvis.

The nominal scanning parameters were as follows, with adjustments as necessary for body habitus: beam current, 165 mAs; beam energy, 120 kVp; beam collimation, 2.5 cm; and table speed, 5.4 cm/s. CT images were reconstructed at 7.0-mm intervals. Images were examined using standard clinical window and level settings, and measurable lesions, at least one lesion and up to 12 lesions per patient, were chosen by an experienced radiologist. Axial plane measurements of the maximum diameter of the lesions and their maximal perpendicular dimension were made in the standard fashion.

Outcome Measure
The outcome measure was TTF. It was defined as the time from the first dose of imatinib mesylate to the earliest occurrence of disease progression, death, or discontinuation from the trial for any medical reason. Patients for whom the treatment had not failed according to this definition were censored at the date of their last disease assessment. Four patients had to stop taking imatinib mesylate because of medical complications independent of the effectiveness of this drug on their disease. Because predicting these side effects using imaging is not possible, these patients skew our results, but only very slightly due to the small number of patients involved. Patients were followed for up to 37 months after treatment initiation.

Prognostic Metrics
The following specific metrics about the single largest lesion for each image were examined: first, percent change in CT bidimensional measurements from baseline to 1 month after initiation of treatment; second, PET SUVmax at 1 month after initiation of treatment; and, third, percent change in PET SUVmax from baseline to 1 month after treatment initiation. Thresholds that divided the patient population into separate poor- and good-prognosis groups were used. These thresholds were varied over the entire range of measured values to find the threshold that yielded optimum performance for each metric.

The optimized thresholds were then compared with the following standards: first, ≥50% reduction in CT bidimensional measurements from baseline to 1 month after initiation of treatment (SWOG criteria for partial response); second, PET SUVmax of less than 2.5 at 1 month after initiation of treatment (physiologic FDG uptake in tissue); and, third, 25% reduction in PET SUVmax from baseline to 1 month after initiation of treatment (EORTC guidelines for partial response). The performance of combinations of metrics (i.e., PET SUVmax and CT bidimensional measurements) was also investigated.

Statistical Analysis
The goal of this effort was to find an early prognostic imaging indicator of treatment efficacy (i.e., TTF). To evaluate existing thresholds, including SWOG and EORTC cutoffs for partial response, the p value from the log-rank test was used. To identify thresholds for PET SUVmax and CT bidimensional measurements at 1 month, recursive partitioning was used [23]. In this method, the maximally selected chi-square statistic is used to identify an optimal cut point.


Figure 1
View larger version (77K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 1A —Patient with gastrointestinal stromal tumor who responded to imatinib mesylate treatment. Maximum-intensity-projection images obtained before (A) and 1 month after (B) initiation of imatinib mesylate therapy. Metabolic activity in large tumor masses in patient's liver is reduced to normal levels after treatment initiation.

 


Figure 2
View larger version (73K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 1B —Patient with gastrointestinal stromal tumor who responded to imatinib mesylate treatment. Maximum-intensity-projection images obtained before (A) and 1 month after (B) initiation of imatinib mesylate therapy. Metabolic activity in large tumor masses in patient's liver is reduced to normal levels after treatment initiation.

 


Figure 3
View larger version (74K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 1C —Patient with gastrointestinal stromal tumor who responded to imatinib mesylate treatment. Transaxial 18F-FDG PET images before (C) and 1 month after (D) initiation of imatinib mesylate therapy show that metabolic activity in tumor has decreased to normal levels after treatment.

 


Figure 4
View larger version (66K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 1D —Patient with gastrointestinal stromal tumor who responded to imatinib mesylate treatment. Transaxial 18F-FDG PET images before (C) and 1 month after (D) initiation of imatinib mesylate therapy show that metabolic activity in tumor has decreased to normal levels after treatment.

 


Figure 5
View larger version (118K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 1E —Patient with gastrointestinal stromal tumor who responded to imatinib mesylate treatment. Transaxial CT images obtained before (E) and 1 month after (F) initiation of imatinib mesylate therapy show that tumor is still present and has decreased very little in size.

 


Figure 6
View larger version (117K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 1F —Patient with gastrointestinal stromal tumor who responded to imatinib mesylate treatment. Transaxial CT images obtained before (E) and 1 month after (F) initiation of imatinib mesylate therapy show that tumor is still present and has decreased very little in size.

 
Using this method, we selected the best from among many possible cut points; therefore, evaluation of the p value from the log-rank statistic would not accurately reflect the test's true error probability. Instead, a permutation test in which the group classification variable was randomly assigned to the actual TTF and indicator values for each patient was used. For each permutation with random classification categories, the score statistic from the Cox proportional hazards model was calculated and compared with the score statistic from the correctly labeled patients. After 100,000 permutations, we calculated the proportion of times the permuted score statistic was more extreme than the true score statistic and considered this value to be an estimate of the p value. We illustrated distributions of survival time and TTF using Kaplan-Meier plots. Cox proportional hazards models were also used to explore the efficacy of using multiple metrics in combination.

Imaging data were also analyzed by receiver operating characteristic (ROC) techniques [25]. Two binary classification tasks were defined by specifying survival thresholds of 180 and 365 days. Fifty-four patients with all imaging variables were included. Imaging metrics were used as input to a publicly available continuous ROC analysis program (ROCKIT, University of Chicago) [24, 25]. Classification performance was quantified using the area under the ROC curve.


Results
Top
Abstract
Introduction
Subjects and Methods
Results
Discussion
References
 
Example Images
Figures 1A, 1B, 1C and 1D are example images from our data set that show a reduction of FDG uptake in large intraabdominal GIST masses after 1 month of imatinib mesylate therapy. In contrast, little change in tumor size is seen on the corresponding CT images (Figs. 1E and 1F), even though treatment was successful according to clinical criteria. Figures 2A and 2B show an example of a patient from our study group with GIST who did not respond to imatinib mesylate therapy: In this case, the tumors increased in size, and new lesions formed. These changes can also be seen on the corresponding CT images in Figures 2C and 2D.


Figure 7
View larger version (67K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 2A —Patient with gastrointestinal stromal tumor (GIST) who did not respond to imatinib mesylate treatment. 18F-FDG PET images obtained before (A) and 1 month after (B) initiation of imatinib mesylate show that metabolic activity in tumor has increased and patient's GIST is unresponsive to imatinib mesylate treatment.

 

Figure 8
View larger version (70K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 2B —Patient with gastrointestinal stromal tumor (GIST) who did not respond to imatinib mesylate treatment. 18F-FDG PET images obtained before (A) and 1 month after (B) initiation of imatinib mesylate show that metabolic activity in tumor has increased and patient's GIST is unresponsive to imatinib mesylate treatment.

 

Figure 9
View larger version (100K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 2C —Patient with gastrointestinal stromal tumor (GIST) who did not respond to imatinib mesylate treatment. Transaxial CT images corresponding to A and B before (C) and 1 month after (D) initiation of imatinib mesylate therapy show two tumors (arrows) on far right side of these images that had tripled in size according to CT bidimensional measurements in 1 month.

 

Figure 10
View larger version (106K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 2D —Patient with gastrointestinal stromal tumor (GIST) who did not respond to imatinib mesylate treatment. Transaxial CT images corresponding to A and B before (C) and 1 month after (D) initiation of imatinib mesylate therapy show two tumors (arrows) on far right side of these images that had tripled in size according to CT bidimensional measurements in 1 month.

 
Optimization of Imaging Metrics
Figure 3A shows the predictive power of using an optimized threshold for percent reduction in CT bidimensional measurements (no reduction in bidimensional tumor area) at 1 month. Percent reduction in CT bidimensional measurements with an optimized threshold (i.e., no growth) results in a large and highly significant split between the two populations (p < 0.0001). This measure is a significant improvement over SWOG criteria for partial response, which were not predictive of successful treatment with imatinib mesylate (p = 0.55).


Figure 11
View larger version (8K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 3A —Kaplan-Meier plots of population split (n = 58). Plot shows data obtained using optimized threshold of 0% reduction (or lack of growth) in CT bidimensional measurements from baseline to 1 month after initiation of therapy.

 


Figure 12
View larger version (8K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 3B —Kaplan-Meier plots of population split (n = 58). Plot shows data obtained using previously determined threshold of 5% reduction [10] in CT bidimensional measurements from baseline to 2 months after initiation of therapy. (p < 0.0001, log-rank statistic)

 
Log-rank analysis was also performed using a threshold of a 5% reduction in CT bidimensional measurements determined at 2 months after the start of therapy that was reported in a previous study [10]. The log-rank p value for that threshold was again less than 0.0001; the results are shown in Figure 3B.

Kaplan-Meier plots for percent reduction in PET SUVmax between baseline and 21-40 days are shown in Figure 4A. EORTC guidelines (i.e., 25% reduction in PET SUVmax) were predictive of outcome (p = 0.004). The performance of the percent reduction in PET SUVmax test was improved using the optimal threshold of 40% reduction (p =0.002); however, the improvement in performance was smaller than the improvement for other imaging measures.


Figure 13
View larger version (9K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 4A —Kaplan-Meier plots of population split (n = 58) using different thresholds. Plot shows data obtained using optimized threshold of 40% reduction in maximum standardized uptake value (SUVmax) on 18F-FDG PET from baseline to 1 month after initiation of therapy.

 
Kaplan-Meier plots for using a PET SUVmax threshold of 3.4 at 21-40 days after initiation of treatment are shown in Figure 4B. The standard PET SUVmax threshold of 2.5 generated a significant split in the population (p = 0.04); however, that threshold was not as effective as EORTC guidelines and was not nearly as effective as the optimized metrics. The optimized PET SUVmax threshold of 3.4 generated a split of very high significance (p < 0.0001). This is approximately equivalent to results obtained using no reduction in CT bidimensional measurement at 1 month. Baseline PET SUVmax and baseline CT bidimensional measurement values were not predictive of treatment success.


Figure 14
View larger version (8K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 4B —Kaplan-Meier plots of population split (n = 58) using different thresholds. Plot shows data obtained using optimized FDG PET SUVmax threshold of 3.4 at 1 month after initiation of therapy.

 


Figure 15
View larger version (12K):
[in this window]
[in a new window]
[as a PowerPoint slide]
 
Fig. 5 Time-to-treatment failure (TTF) curves for four populations (n = 58) defined by optimized maximum standardized uptake value (SUVmax) on 18F-FDG PET success and optimized CT bidimensional measurement success, SUVmax failure and CT bidimensional measurement failure, SUVmax success and CT bidimensional measurement failure, and SUVmax failure and CT bidimensional measurement success.

 
Combinations of Metrics
Figure 5 shows a combination of the two best metrics. Only one patient had a low PET SUVmax and an increase in CT bidimensional measurements. In that patient, treatment failed due to drug toxicity, a factor that is not likely to be predicted on the basis of imaging. Six patients had a high PET SUVmax and no growth in CT bidimensional measurements. In all six patients, the treatment failed, within the first year in four patients. This finding suggests that the optimized PET SUVmax at 1 month is a slightly more effective metric, but optimized CT bidimensional measurement has, nevertheless, proved to be a powerful prognostic indicator. Further investigation using a Cox proportional hazards model supports a lack of independent information among all metrics, suggesting that little information is gained by combining them.

A summary of performance of the evaluated metrics is shown in Table 1. Median TTFs for the predicted treatment success groups and predicted treatment failure groups for the various indicators are included.


View this table:
[in this window]
[in a new window]

 
TABLE 1: Performance of Imaging Metrics

 

ROC Analysis
ROC analysis was also performed on the data. Percent change in PET SUVmax at 1 month after initiation of treatment, PET SUVmax at 1 month, and percent change in CT bidimensional measurements at 1 month were used to discriminate patients for whom treatment would fail less than 180 days after the initiation of treatment from those who would survive more than 180 days after the initiation of treatment. Performance was quantified by the area under the ROC curve and found to be 0.850 ± 0.056 (mean ± standard error [SE]) for percent change in PET SUVmax from baseline to 1 month, 0.874 ± 0.047 for PET SUVmax at 1 month, and 0.857 ± 0.080 for percent change in CT bidimensional measurements from baseline to 1 month.

This analysis was repeated for 1-year survival. The area under the ROC curve was 0.676 ± 0.084 for percent change in PET SUVmax from baseline to 1 month, 0.711 ± 0.075 for PET SUVmax at 1 month, and 0.770 ± 0.080 for percent change in CT bidimensional measurements from baseline to 1 month.


Discussion
Top
Abstract
Introduction
Subjects and Methods
Results
Discussion
References
 
The data presented here indicate that conventional objective response criteria defined by SWOG for percent change in CT bidimensional measurements after 1 month of treatment were not useful early indicators of outcome in the patient population examined. EORTC criteria for FDG PET were predictive of outcome, but substantial improvements can be obtained by optimizing the choice of threshold and metric for both CT and FDG PET.

No growth or reduction in CT bidimensional measurement determined at 1 month after therapy initiation was an effective indicator of prolonged treatment success in this patient group, with no significant difference in predictive power compared with the best PET metric (PET SUVmax ≤ 3.4 at 1 month). No combination of metrics could outperform the threshold of 3.4 in PET SUVmax at 1 month.

These conclusions would be strengthened by validation in an independent data set; however, the plausibility of the zero growth threshold for CT bidimensional measurements is improved by the broadly similar findings from other groups [10, 26]—namely, the use of a 5% reduction threshold in CT bidimensional measurements at 2 months in a similar patient group [10] was also predictive of outcome. The difference between the thresholds found may be due to statistical sampling error or to the difference in imaging time points. However, we note that a 5% threshold at 1 month was also predictive of outcome in our data set.

Of note, the median reduction in CT bidimensional measurements of 34% at 1 month is large, suggesting that it may be possible to use CT as a prognostic metric at even earlier time points after therapy initiation. Care would be needed because there is anecdotal evidence that GIST lesions may swell as they begin to respond to imatinib mesylate, but the use of measurements of cystic changes in combination with size criteria may possibly ameliorate the risk of misclassification [12]. It is, of course, highly unlikely that CT could be used as early as FDG PET, which has shown strong responses as early as 24 hours after therapy initiation [18].

With the advent of targeted therapies, there is a need to develop prognostic metrics that can stratify a population into groups who may benefit from therapy and those who may not. Significant efforts have been undertaken to apply molecular or genomic markers in this context: The use of epidermal growth factor receptor (EGFR) overexpression, mutations, and polysomy as outcome predictors for therapy with the EGFR tyrosine kinase inhibitor erlotinib is a prime example [27, 28]. However, the specificity and practicality of such prognostic tests are not perfect, and it is reasonable to look for additional imaging biomarkers that can also be used either prospectively or shortly after therapy initiation. The results presented here are applicable only to the use of imatinib mesylate therapy in GIST, but they are encouraging and strongly suggest the need for further work on imaging biomarkers for use with other targeted therapies.

Our results show that conventional objective response criteria are not generally applicable to prognosis in therapies involving the new generation of molecularly targeted agents such as imatinib mesylate. This finding suggests that similar studies should be performed for each new therapeutic agent, at least until it can be determined whether the results found here are generally applicable to this class of therapeutic agents.


References
Top
Abstract
Introduction
Subjects and Methods
Results
Discussion
References
 

  1. DeMatteo RP, Lewis JJ, Leung D, et al. Two hundred gastrointestinal stromal tumors: recurrence patterns and prognostic factors for survival. Ann Surg 2000;231 : 51-58[CrossRef][Medline]
  2. Goss GA, Merriam P, Manola J, et al. Clinical and pathological characteristics of gastrointestinal stromal tumors (GIST). (abstr) Prog Proc Am Soc Clin Oncol 2000;19 : 599a
  3. Joensuu H, Fletcher C, Dimitrijevic S, et al. Management of malignant gastrointestinal stromal tumours. Lancet Oncol 2002; 3:655 -664[CrossRef][Medline]
  4. Lux ML, Rubin BP, Biase TL, et al. KIT extracellular and kinase domain mutations in gastrointestinal stromal tumors. Am J Pathol 2000; 156:791 -795[Abstract/Free Full Text]
  5. Rubin BP, Singer S, Tsao C, et al. KIT activation is a ubiquitous feature of gastrointestinal stromal tumors. Cancer Res2001; 61:8118 -8121[Abstract/Free Full Text]
  6. Demetri GD, von Mehren M, Blanke CD, et al. Efficacy and safety of imatinib mesylate in advanced gastrointestinal stromal tumors. N Engl J Med 2002; 347:472 -480[Abstract/Free Full Text]
  7. Joensuu H, Roberts PJ, Sarlomo-Rikala M, et al. Effect of the tyrosine kinase inhibitor STI571 in a patient with a metastatic gastrointestinal stromal tumor. N Engl J Med2001; 344:1052 -1056[Free Full Text]
  8. Van den Abbeele AD, Badawi RD. Use of positron emission tomography in oncology and its potential role to assess response to imatinib mesylate therapy in gastrointestinal stromal tumors (GISTs). Eur J Cancer 2002; 38[suppl 5]: S60-S65
  9. Holdsworth CH, Badawi RD, Manola J, et al. Use of CT, PET, and mutational analysis as early prognostic indicators of response to imatinib mesylate (Gleevec) in patients with gastrointestinal stromal tumors (GIST). J Clin Oncol (abstr) 2004;22 [suppl]:3011
  10. Gayed I, Vu T, Iyer R, et al. The role of 18F-FDG PET in staging and early prediction of response to therapy of recurrent gastrointestinal stromal tumors. J Nucl Med 2004;45 : 17-21[Abstract/Free Full Text][Erratum in J Nucl Med 2004;45 : 1803][Free Full Text]
  11. Antoch A, Kanja J, Bauer S, et al. Comparison of PET, CT, and dual-modality PET/CT imaging for monitoring of imatinib (STI571) therapy in patients with gastrointestinal stromal tumors. J Nucl Med 2004; 45:357 -365[Abstract/Free Full Text]
  12. Bechtold R, Chen M, Stanton TA, Savage PD, Levine EA. Cystic changes in hepatic and peritoneal metastases from gastrointestinal stromal tumors treated with Gleevec. Abdom Imaging2003; 28:808 -814[Medline]
  13. Therasse P, Arbuck S, Eisenhauer EA, et al. New guidelines to evaluate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada. J Natl Cancer Inst 2000; 92:205 -216[Abstract/Free Full Text]
  14. Green S, Weiss GR. Southwest Oncology Group standard response criteria, endpoint definitions and toxicity criteria. Invest New Drugs 1992; 10:239 -253[CrossRef][Medline]
  15. Young H, Baum R, Cremerius U, et al. Measurement of clinical and subclinical tumour response using [18F]-fluorodeoxyglucose and positron emission tomography: review and 1999 EORTC recommendations. European Organization for Research and Treatment of Cancer (EORTC) PET Study Group. Eur J Cancer 1999;35 : 1773-1782[CrossRef][Medline]
  16. Straus LG, Conti PS. The application of PET in clinical oncology. J Nucl Med 1991;37 : 783-788
  17. Goerres GW, Stupp R, Barghouth G, et al. The value of PET, CT and in-line PET/CT in patients with gastrointestinal stromal tumours: long-term outcome of treatment with imatinib mesylate. Eur J Nucl Med Mol Imaging 2005; 32:153 -162[CrossRef][Medline]
  18. Van den Abbeele AD, Badawi RD, Tetrault RJ, et al. FDG-PET as a surrogate marker for response to Gleevec (imatinib mesylate) in patients with advanced gastrointestinal stromal tumors (GIST). J Nucl Med 2003;44 [suppl]:24P
  19. Van den Abbeele AD for the GIST Collaborative PET Study Group (Dana-Farber Cancer Institute, OHSU, Helsinki University Central Hospital, Turku University Central Hospital, Novartis Oncology). F18-FDG-PET provides early evidence of biological response to STI571 in patients with malignant gastrointestinal stromal tumors (GIST). Proc Am Soc Clin Oncol (abstr) 2001; 20:362
  20. Van den Abbeele AD, Badawi RD, Cliche JP, et al. F-FDG-PET predicts response to imatinib mesylate (Gleevec) in patients with advanced gastrointestinal stromal tumors (GIST). (abstr) Proc Am Soc Clin Oncol 2002; 21:403a
  21. Benjamin RS, Choi H, Macapinlac HA, et al. We should desist using RECIST, at least in GIST. J Clin Oncol2007; 25:1760 -1764[Abstract/Free Full Text]
  22. Choi H, Charnsangavej C, Faria SC, at al. Correlation of computed tomography and positron emission tomography in patients with metastatic gastrointestinal stromal tumor treated at a single institution with imatinib mesylate: proposal of new computed tomography response criteria. J Clin Oncol 2007; 25:1753 -1759[Abstract/Free Full Text]
  23. Breiman L, Friedman JH, Olshen RA, Stone CJ. Classification and regression trees. New York, NY: Chapman and Hall, 1984
  24. Metz CE. ROC methodology in radiologic imaging. Invest Radiol 1986; 21:720 -733[Medline]
  25. Metz CE, Herman BA, Shen JH. Maximum likelihood estimation of receiver operating characteristic curves from continuously-distributed data. Stat Med 1998; 17:1033 -1053[CrossRef][Medline]
  26. Choi H, Charnsangavej C, de Castro Faria S, et al. CT evaluation of the response of gastrointestinal stromal tumors after imatinib mesylate treatment: a quantitative analysis correlated with FDG PET findings. AJR 2004; 183:1619 -1628[Abstract/Free Full Text]
  27. Tsao MS, Sakurada A, Cutz JC, et al. Erlotinib in lung cancer: molecular and clinical predictors of outcome. N Engl J Med 2005; 353:133 -144[Abstract/Free Full Text][Erratum in N Engl J Med 2006;355 : 1746][Free Full Text]
  28. Pérez-Soler R, Chachoua A, Hammond LA, et al. Determinants of tumor response and survival with erlotinib in patients with non-small-cell lung cancer. J Clin Oncol 2004;22 : 3238-3247[Abstract/Free Full Text]

Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?


This article has been cited by other articles:


Home page
JNMHome page
K. B. Contractor and E. O. Aboagye
Monitoring Predominantly Cytostatic Treatment Response with 18F-FDG PET
J. Nucl. Med., May 1, 2009; 50(Suppl_1): 97S - 105S.
[Abstract] [Full Text] [PDF]


Home page
RadiologyHome page
S. Stacchiotti, P. Collini, A. Messina, C. Morosi, M. Barisella, R. Bertulli, C. Piovesan, P. Dileo, V. Torri, A. Gronchi, et al.
High-Grade Soft-Tissue Sarcomas: Tumor Response Assessment--Pilot Study to Assess the Correlation between Radiologic and Pathologic Response by Using RECIST and Choi Criteria
Radiology, May 1, 2009; 251(2): 447 - 456.
[Abstract] [Full Text] [PDF]


Home page
Clin. Cancer Res.Home page
L. K. Shankar, A. Van den Abbeele, J. Yap, R. Benjamin, S. Scheutze, and T.J. FitzGerald
Considerations for the Use of Imaging Tools for Phase II Treatment Trials in Oncology
Clin. Cancer Res., March 15, 2009; 15(6): 1891 - 1897.
[Abstract] [Full Text] [PDF]


Home page
Clin. Cancer Res.Home page
A. A. Adjei, M. Christian, and P. Ivy
Novel Designs and End Points for Phase II Clinical Trials
Clin. Cancer Res., March 15, 2009; 15(6): 1866 - 1872.
[Abstract] [Full Text] [PDF]


Home page
JCOHome page
J. O. Prior, M. Montemurro, M.-V. Orcurto, O. Michielin, F. Luthi, J. Benhattar, L. Guillou, V. Elsig, R. Stupp, A. B. Delaloye, et al.
Early Prediction of Response to Sunitinib After Imatinib Failure by 18F-Fluorodeoxyglucose Positron Emission Tomography in Patients With Gastrointestinal Stromal Tumor
J. Clin. Oncol., January 20, 2009; 27(3): 439 - 445.
[Abstract] [Full Text] [PDF]


Home page
Clin. Cancer Res.Home page
J. L. Spratlin, N. J. Serkova, and S. G. Eckhardt
Clinical Applications of Metabolomics in Oncology: A Review
Clin. Cancer Res., January 15, 2009; 15(2): 431 - 440.
[Abstract] [Full Text] [PDF]


This Article
Right arrow Abstract Freely available
Right arrow Figures Only
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Holdsworth, C. H.
Right arrow Articles by Van den Abbeele, A. D.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Holdsworth, C. H.
Right arrow Articles by Van den Abbeele, A. D.
Social Bookmarking
 Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?
Hotlight (NEW!)
Right arrow
What's Hotlight?


HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS