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. Author manuscript; available in PMC: 2015 Jul 1.
Published in final edited form as: Clin Cancer Res. 2014 Mar 31;20(13):3550–3559. doi: 10.1158/1078-0432.CCR-13-1440

Treatment Response Evaluation using 18F-FDOPA PET in Patients with Recurrent Malignant Glioma on Bevacizumab Therapy

Johannes Schwarzenberg 1,2,6, Johannes Czernin 1,2, Timothy F Cloughesy 3, Benjamin M Ellingson 4, Whitney B Pope 4, Tristan Grogan 5, David Elashoff 5, Cheri Geist 1,2, Daniel H S Silverman 1,2, Michael E Phelps 1, Wei Chen 1,2
PMCID: PMC4079729  NIHMSID: NIHMS581873  PMID: 24687922

Abstract

Purpose

This study compares the value of 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (18F-FDOPA) PET and MRI in assessing outcome during antiangiogenic treatment in patients with recurrent high-grade gliomas.

Experimental Design

Thirty patients were prospectively studied with 18F-FDOPA PET scans immediately before, and two and six weeks after start of bevacizumab therapy. 18F-FDOPA metabolic tumor volumes (MTV) as well as max and mean SUVs within this MTV were obtained. MRI treatment response was assessed at 6 weeks. The predictive ability of 18F-FDOPA PET and MRI response assessment were evaluated with regard to progression-free survival (PFS) and overall survival (OS).

Results

30, 28, and 24 18F-FDOPA PET scans at baseline, 2 weeks, and 6 weeks, were available for analysis, respectively. 18F-FDOPA PET SUVs as well as their changes through therapy were not predictive of outcome. However, metabolic tumor volume (MTV) parameters such as MTV changes were highly prognostic. Interestingly, absolute MTV at the first follow up scan provides the most significant prediction for increased OS (P < 0.0001) as well as PFS (P = 0.001). This surprising result was scrutinized with cross-validation and simulation analysis. Responders based on 18F-FDOPA PET data survived 3.5 times longer (12.1 vs. 3.5 months median OS, P < 0.001) than non-responders (17 vs. 11 patients, respectively). In comparison, responders based on MRI data lived 1.5 times longer (11.4 vs 7.7 mo, P = 0.03) than non-responders (22 vs. 7 patients, respectively).

Conclusions

18F-FDOPA PET identifies treatment responders to antiangiogenic therapy as early as two weeks after treatment initiation.

Introduction

High-grade gliomas carry a very poor prognosis (1). Patients when initially diagnosed are treated typically by the combination of surgery, chemo and radiation therapy. Inevitably, tumors will recur. The disease status in patients with high-grade gliomas is routinely evaluated clinically and radiographically by contrast-enhanced MRI. However, due to the highly heterogeneous nature of these tumors and the complexity of changes induced by the treatment, the structural information derived from these images does not always adequately reflect both the extent of the actual lesion as well as its malignant potential (2, 3). Biomarkers that are surrogates of proliferative and malignant properties of the tumor and thus can predict treatment responses early and reliably, are under active investigation (4, 5),

Amino acid analogues (6–14) have been studied for brain tumor imaging. 18F-labeled amino acid analogues have the advantage of easy clinical application because of the favorable half life (110 min) of the 18F-PET tracer (7). Preliminary studies with 18F-Fluoroethyl-L-Tyrosine PET in twenty-one patients with recurrent high-grade glioma on antiangiogenic treatment have shown promising results (15,16). The amino-acid-analogue L-3,4-dihydroxy-6-18F-fluorophenyl-alanine (18F-FDOPA) has recently also been under investigation in the evaluation of brain tumors (17–24). 18F-FDOPA uptake in brain tumors is increased compared to normal brain tissue due to the up-regulation of amino acid transport across the blood brain barrier (BBB) by the neutral amino acid transporter. It has been shown previously that 18F-FDOPA provides excellent visualization of high-grade as well as low-grade brain tumors (17–20). Furthermore, its uptake in tumor tissue correlates with tumor grade as well as Ki-67 proliferation index in newly diagnosed gliomas, allowing for a quantitative assessment of malignancy (23).

This study examines the tumor staging potential and predictive power of 18F-FDOPA-PET in the assessment of treatment response for patients with recurrent high-grade glioma undergoing bevacizumab therapy. First, tumor uptake of 18F-FDOPA as well as tumor volumes was obtained. Second, the predictive power of 18F-FDOPA for progression-free (PFS) and overall survival (OS) in patients with recurrent high-grade gliomas was assessed. Last, the predictive power of 18F-FDOPA was compared with MRI and other survival predictors.

PATIENTS AND METHODS

Patients

Thirty patients with recurrent high-grade gliomas were enrolled prospectively in this study (Table 1). There were 18 males and 12 females with median age of 57.5 (range: 26–78) years. All patients met the following inclusion criteria: they had a histologically confirmed diagnosis of glioblastoma (GBM) or anaplastic astrocytoma (AA) (GBM: N = 24; AA: N = 6) and had previously undergone surgical resection and chemoradiation therapy. All patients had MRI-confirmed recurrent disease by the time bevacizumab treatment was started. Further criteria included a Karnofsky Performance Score (KPS) ≥70, adequate hematological values, and sufficient hepatic and renal function. Patients were excluded if there was a bleeding disorder, a recent history of intracranial bleeding or thromboembolism.

Table 1.

Patient Characteristics

Characteristic No.
Median age, years 57.5
 Range 26–78
Tumor grade
 Grade III 6
 Grade IV 24
Number of recurrences
 Median 2
 1–2 recurrences 24
 3–4 recurrences 5
 5 recurrences 1
Median prior treatment regimen 3.07
 Range 0–9
 1–2 regimens 18
 3–5 regimens 6
 6–9 regimens 6
Dexamethasone treatment
 Absence 12
 Presence 18
Karnofsky Performance Score (KPS)
 70–80 13
 90–100 17
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All patients gave written consent to participate in this study, which had been approved by the University of California, Los Angeles, Office for Protection of Research Subjects.

Treatment

All Patients were treated with bevacizumab and irinotecan except for 3 patients who were treated with bevacizumab alone (patient no. 23, 26, and 28, Table 2). Co-administration of corticosteroids was closely monitored. While 12 patients did not require corticosteroids, 9 patients were maintained on stable or tapering doses of dexamethasone, and 9 patients needed a dose increase after the baseline MRI and PET studies were obtained.

Table 2.

Patient Characteristics, Tumor 18F- FDOPA uptake, and OS

Pt No Sex/Age Dx 18F-FDOPA baseline MTV 18F-FDOPA MTV 2 wk after treatment start 18F-FDOPA ΔMTV 2 wk after treatment start 18F-FDOPA MTV 6 wk after treatment start 18F-FDOPA ΔMTV 6 wk after treatment start 18F-FDOPA response (MTV 2 wk)b 18F-FDOPA response (ΔMTV 2 wk)b MRI respone (6 wk)c PFS (mon) OS (mon)
1 F/38 AA 30.02 20.56 −32% ND NA No No SD‡ 5.0 8.5
2 M/78 GBM 22.12 ND NA ND NA NA NA PD 0.5 0.8
3 M/64 GBM 3.27 3.38 3% 2.64 −19% Yes No PR 2.2 7.6
4 F/45 GBM 15.00 12.60 −16% 8.16 −46% Yes No SD 1.7 11.3
5 M/37 GBM 32.77 10.84 −67% 11.71 −64% Yes Yes SD 3.8 4.0
6 M/65 AA 272.35 138.63 −49% 115.51 −58% No Yes NA* 3.6 4.6
7 M/65 AMG 34.50 23.08 −33% ND NA No No PD 0.7 2.6
8 F/61 GBM 104.27 ND NA 19.00 −82% NA NA SD 4.5 13.1
9 M/69 GBM 87.42 18.43 −79% 2.62 −97% No Yes PR‡ 2.8 2.8
10 M/26 GBM 17.16 11.47 −33% 12.33 −28% Yes No SD 3.2 11.5
11 F/65 GBM 26.71 30.13 13% 54.05 102% No No SD‡ 2.5 3.5
12 F/35 GBM 54.86 33.82 −38% 24.02 −56% No Yes PD 2.1 10.4
13 F/62 GBM 3.75 0.81 −78% 0.77 −79% Yes Yes PR 8.9 23.2
14 M/28 AA 185.06 181.03 −2% ND NA No No PD 1.5 7.7
15 F/68 GBM 34.12 25.68 −25% ND NA No No PD 1.1 1.6
16 F/47 GBM 16.18 17.22 6% 7.86 −51% Yes No SD 5.6 12.7
17 F/54 GBM 29.67 7.03 −76% 7.60 −74% Yes Yes PR 7.3 12.1
18 M/58 GBM 43.83 40.77 −7% 36.94 −16% No No SD‡ 1.6 3.2
19 M/46 GBM 10.23 5.48 −46% 5.84 −43% Yes Yes SD 2.4 11.2
20 M/50 AA 15.36 10.42 a −32% ND NA No a NA a SD‡ 0.9 1.9
21 M/70 GBM 9.41 4.05 −57% 3.30 −65% Yes Yes PR 6.7 12.9
22 M/66 GBM 17.29 3.71 −79% 3.06 −82% Yes Yes SD 11.1 12.3
23 M/47 GBM 2.76 1.79 −35% 1.65 −40% Yes Yes CR 18.2 34.3
24 F/58 GBM 56.36 30.41 −46% 37.75 −33% No Yes SD‡ 1.3 5.5
25 M/76 GBM 36.00 11.10 −69% 3.56 −90% Yes Yes CR 24.0 32.0
26 M/68 GBM 5.17 3.01 −42% 3.93 −24% Yes Yes PR 6.9 10.1
27 F/37 GBM 34.29 14.66 −57% 12.02 −65% Yes Yes PR 10.6 14.6
28 M/37 AA 18.82 6.28 −67% 1.73 −91% Yes Yes PD‡ 1.9 9.5
29 M/57 GBM 1.64 0.97 −41% 0.83 −49% Yes Yes SD 4.2 19.5
30 F/41 GBM 6.28 4.94 −21% 7.59 21% Yes No PD‡ 1.4 12.0
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Annotations:

a

Patient developed a second lesion after 2 weeks.

b

according to PET criteria derived from ROC statistical analysis.

c

As this was MRI evaluation at 6 weeks, no 4 week sustained response requirement for responders based on RANO (14) was taken into consideration for this evaluation.

‡

Mismatch between MRI and best PET response assessment, SD, PR, and CR are considered treatment responders

Abbreviations: Pt: patient; Dx: diagnosis; AA: anaplastic astrocytoma; GBM: glioblastoma multiforme; AMG: anaplastic mixed glioma; ND: not done; NA: not applicable; PFS: progression-free survival and OS: overall survival from begin of bevacizumab treatment. PD: progressive disease; SD: stable disease; PR: partial response; CR: complete response.

Patient’s disease status was evaluated and monitored using gadolinium enhanced as well as non-enhanced MRI obtained within one week before and at approximately six-week intervals after starting bevacizumab therapy. Patients were followed until death with no subjects lost to follow up. The overall survival (OS) was defined as the interval between treatment initiation and death while progression-free survival (PFS) was defined as the interval between treatment initiation and radiographic and/or clinical progression.

PET Imaging

PET imaging was performed on a dedicated PET system (ECAT HR or HR+) (25, 26). Patients were asked to fast for at least 4 hours before image acquisition. 18F-FDOPA was synthesized according to a previously reported procedure (27, 28) and was injected intravenously at a mean dose of 1.89±0.37 MBq/kg. Data were acquired in the 3-dimensional mode. The emission scan was started 10 minutes after tracer injection. To correct for photon attenuation, 5-min transmission scans were acquired after the emission scans for all patients. Images were acquired for 30 minutes in the 3-dimensional mode. Image data acquired between 10 and 30 minutes were summed to obtain a 20 minute static image. PET images were reconstructed using iterative techniques with ordered-subset expectation maximization consisting of 6 iterations with 8 subsets (29, 30). A Gaussian filter with a full width at half maximum of 4 mm was applied.

Image Analysis

Images were first inspected visually with the axial PET image slice displaying the maximum tumor 18F-FDOPA uptake selected. The radiotracer concentration in the regions of interest (ROIs) was normalized to the injected dose per kilogram of patient’s body weight to derive the standardized uptake values (SUVs).

Tumor ROIs were defined on summed images in two ways. First, a standardized 10 mm circular region was placed over the area with the maximum activity. This was used to derive SUVmax and SUVpeak. Then, metabolic tumor volume (MTV) was obtained by including all voxels that fall within an SUV threshold determined by the mean SUV of the contralateral striatum (19). In cases where the tumor involved the striatum bilaterally, a threshold of 1.5 mean SUV of normal hemispheric background was used (19). Mean 18F-FDOPA uptake within this volume (SUVmean) was determined. Absolute MTVs and SUVs as well as their changes were correlated with clinical outcome.

Magnetic Resonance Imaging

Data were collected on a 1.5T MRI system (General Electric Medical Systems, Waukesha, WI) using pulse sequences supplied by the scanner manufacturer. Standard anatomical MRI sequences included axial proton density, T1, and T2 weighted fast spin-echo images, along with fluid-attenuated inversion recovery (FLAIR) images, all obtained with a 5mm slice thickness with 1mm inter-slice distance, two excitations, matrix size of 256×256, and a field-of-view of 24cm. Additionally, gadopentetate dimeglumine enhanced (Magnevist; Berlex, Wayne, NJ) axial and coronal T1 weighted images were acquired after contrast injection.

Regions of FLAIR abnormality were chosen based on Response Assessment in Neuro-Oncology (RANO) recommendations (31). The regions of post-contrast T1-weighted image (T1+C) hyperintensity were defined on post-contrast T1-weighted images, excluding any T1 shortening from blood products on pre-contrast T1-weighted images as well as cystic and surgical resection cavities. The volumes of FLAIR and T1+C were calculated using a semi-automated procedure as described previously (32).

MRI based response at 6 weeks was defined according to the RANO criteria. However, the 4 week sustained response requirement for complete and partial response was not considered since the goal of the study was to compare the predictive values of MRI and PET at 6 weeks after starting treatment (31). Progressive disease (PD) was defined as more than a 25% increase in the sum of the products of perpendicular diameters, a significant increase in non-enhancing tumor, or neurologic decline. Complete response (CR) was defined as neither enhancing- nor non-enhancing-tumor, without steroid use. Partial response (PR) was defined as more than a 50% decrease in the sum of the products of perpendicular diameters on stable steroids, without new lesions. Non-enhancing tumor was identified by mass effect and/or architectural distortion including blurring of the gray-white boundary. All scans that did not qualify above were considered stable disease (SD). MRI assessment was performed by a board certified neuroradiologist (W.B.P.).

In addition to assessment using the standard MRI response criteria, tumor volumes by MRI at baseline and follow up scans were also evaluated for response predication.

Statistical Analysis

18F-FDOPA PET uptake threshold values for treatment response were established by receiver-operating-characteristic (ROC) curve analysis. Threshold values derived from this method were scrutinized by leave-one-out cross-validation analysis to assess how robust and sensitive these cutpoints were to individual values. The differences between groups of patients were established by the Student t test. Kaplan-Meier (KM) curves were subsequently generated to obtain survival estimates (33).

Univariate and multivariate Cox proportional-hazards models were constructed to test the relationship between 18F-FDOPA metabolic response and other predictors with regard to survival (OS and PFS). The forward stepwise selection technique was utilized to reduce the multivariate models (P < 0.10). Harrell’s c-index was used to compare the strength of predictive performance for each model. Furthermore, a permutation simulation study was performed to evaluate the effect of cut-point selection bias on the strength of the association between FDOPA and survival. Survival outcomes were randomly permuted and we recomputed the optimal cut-point for F-FDOPA for prediction of survival. For each of these cut-points we computed the c-statistic. This was done 10,000 times to form an empirical distribution for the optimal c-statistic. The p-value for the observed c-statistic was computed based on the proportion of the simulated c-statistics that were larger than the observed c-statistic. Statistical analyses were performed in SAS (version 9.2; SAS Institute. Cary, NC) and R (version 2.14.2 www.rproject.org).

RESULTS

18F-FDOPA-PET Uptake Changes

Thirty patients were enrolled for the 18F-FDOPA PET study (Table 1). All 30 patients completed the baseline 18F-FDOPA PET scan while 28 patients completed the second scan two weeks later and 24 patients were able to complete the third 18F-FDOPA PET scan six weeks after starting treatment.

Tumor 18F-FDOPA SUVs for all scans were obtained. Tumor SUVmax on baseline scans varied between 1.32 and 4.14. Following therapy, no significant changes of SUVs were seen (Figure 1; SUVmax 2 weeks: -4.3% ± 15%; 6 weeks: −2.7% ± 19%; 2 – 6 weeks: +3.5% ± 22%).

Figure 1.

Figure 1

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Changes in 18F-FDOPA SUVmean, SUVmax, and MTV from baseline to 2-weeks and baseline to 6 weeks as measured from bevacizumab treatment initiation.

Metabolic tumor volumes, as delineated by 18F-FDOPA uptake, were determined and are listed in Table 2. Patients’ median MTVs were 24.4 (range 1.6 to 272.3 ml) at baseline, 11.3 (range 1.0 to 181.0 ml) at 2 weeks, and 7.6 (range 0.83 to 115.5) at 6 weeks (Table 2). Significant changes of 18F-FDOPA-PET MTV were found (mean values: −40% ± 27% at 2 weeks and −47% ± 42% at 6 weeks (Figure 1).

Optimal 18F-FDOPA-PET Criteria for Survival Prediction

18F-FDOPA uptake values (at baseline, two weeks or six weeks) both as SUVmax as well as SUVpeak were initially analyzed but were found not to be predictive of survival. Changes of SUV over the course of therapy were not indicative of treatment success, either.

However, 18F-FDOPA MTV changes were predictive of treatment response. Using receiver-operating-characteristic curve (ROC) analysis, threshold values for MTV changes between baseline and 2 weeks, and baseline and 6 weeks, were obtained. Subsequently, Kaplan-Meier analysis was performed to assess their predictive power for PFS and OS.

When comparing 18F-FDOPA MTV changes from baseline to 2 weeks using the ROC derived threshold value of ≥ 35% reduction, 16 responders and 12 non-responders were identified with 18F-FDOPA MTV changes of −58% ± 16% for responders and −15% ± 17% for non-responders, respectively (P < 0.001). The mean OS was 13.7 months for responders versus 7.0 months for non-responders (P = 0.02). At 6 weeks, 17 responders and 7 non-responders were identified with 18F-FDOPA MTV changes of −67% ± 18% for responders and +0.4% ± 48% non-responders, respectively (P = 0.01). Mean OS was 14.1 months for responders and 7.6 months for non-responders (P = 0.02). 18F-FDOPA MTV change at 6 weeks is a stronger predictor of overall survival (P < 0.001) than MTV change at 2 weeks (P = 0.001), whereas 18F-FDOPA MTV change at 2 weeks (P < 0.001) is a stronger predictor for progression free survival than 18F-FDOPA MTV change at 6 weeks (P = 0.003).

Next, absolute MTVs at baseline and follow up scans were assessed for their predictive performance. As expected, baseline MTVs do not correlate with survival (PFS and OS). Interestingly, MTVs at follow up scans do correlate with survival and ROC analysis identifies an optimal threshold tumor volume of 18 ml. This surprising result was scrutinized by performing a leave-one-out cross-validation analysis to assess how robust and sensitive this cut point was to individual values. 28 of 30 cut point result thus derived generate a value of 18 ml, with the remaining two being 16.55 ml and 18.89 ml. When applying the optimal threshold value 18F-FDOPA MTV ≤ 18 ml at 2 weeks, 17 responders and 11 non-responders are indentified. Examples of individual responses are shown in Figure 2. The median survival for the responders was 12.1 versus 3.5 months for non-responders, a 3.5 fold survival advantage (P < 0.001). 18F-FDOPA MTV at two weeks is the most significant predictor of overall survival as well as progression free survival by Kaplan Meier analysis (P < 0.001 and P = 0.001 respectively; Figure 3). 18F-FDOPA MTV at 6 weeks is also predictive of overall survival and progression free survival (P = 0.03 and P = 0.02 respectively).

Figure 2.

Figure 2

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18F-FDOPA PET at baseline, 2 weeks, and 6 weeks of a responding patient (A, patient 25, Table 2) and a non-responding patient (B, patient 18, Table 2).

Figure 3.

Figure 3

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Kaplan-Meier OS curve separated by 18F-FDOPA PET MTV at 2 weeks after treatment initiation.

Response assessment by MRI

Response by MRI was evaluated at approximately 6 weeks (5.9 ± 2.7) after starting treatment based on RANO criteria and was available for twenty-nine patients. By MRI criteria, 22 patients were classified as responders (76%), these include two complete response (CR), seven partial response (PR), and thirteen patients with stable disease (SD). The remaining 7 patients (24%) had progressive disease (PD) and were considered non-responders. MRI response was predictive of overall survival as well as progression-free survival (P = 0.01 and P < 0.001 respectively). Median overall survival for responders based on MRI criteria was 1.5 times longer than for non-responders (11.4 vs 7.7 mo, P = 0.03). Comparing responders by PET and MRI criteria, eight discrepant cases were identified. Of these, six patients showed a response by MRI (5 SDs, 1 PR), but no treatment response by 18F-FDOPA. As these patients had a median survival of only 3.4 months, 18F-FDOPA predicted treatment failure earlier than MRI. A median time benefit of 7.2 weeks (range 2 – 20 weeks) for earlier detection of treatment failure with 18F-FDOPA was demonstrated. The remaining two discrepant cases were classified as non-responders (PD) by MRI but showed response with 18F-FDOPA. These two patients lived for 9.5 and 12 mo.

Contrary to the PET study, MRI derived absolute tumor volumes did not show survival correlation.

18F-FDOPA-PET Changes Compared with other Predictors

Multiple clinical variables were tested by univariate and multivariate analyses (Table 3, 4). Measurements of MTV at baseline, two weeks, and six weeks in addition to changes between these time points were modeled. Baseline characteristics such as age, number of prior recurrences, and RANO response at 6 weeks were considered in the multivariate models. Modeling all MTV measurement combinations at each time point would induce a survival bias because those who died after two weeks would not have had 6 week measurements (and thus be excluded from the model). Therefore models were run with baseline data, data up through 2 weeks, and data up through 6 weeks separately (Table 4). By univariate analysis, OS was better if patients had fewer recurrences. Patients’ age, baseline KPS, dexamethasone treatment, did not predict survival (Table 3). 18F-FDOPA MTVs at 2 weeks and 6 weeks, as well as their changes from baseline to 2 weeks and baseline to 6 weeks were all predictive of OS (P < 0.001, P = 0.04, P = 0.01, P = 0.01, Table 3). However, 18F-FDOPA absolute MTV at 2 weeks and 18F-FDOPA MTV changes at 2 or at 6 weeks provided the highest hazard ratios (HR = 9.05, 2.94 and 4.02 respectively). Response by MRI was also predictive of survival (P = 0.016).

Table 3.

Univariate Cox Regression Analysis of OS and PFS

OS PFS
Predictive factor HR (95% CI) P C HR (95% CI) P C
Age 1.00 (0.97, 1.03) 0.97 0.50 0.99 (0.96, 1.01) 0.33 0.56
No. of recurrences 2.24 (1.44, 3.51) 0.001 0.67 2.04 (1.35, 3.10) 0.001 0.66
Dexamethasone treatment 1.79 (0.77, 4.17) 0.18 0.56 1.16 (0.51, 2.67) 0.73 0.52
Tumor size change by MRI 3.22 (1.25, 8.32) 0.02 0.62 4.15 (1.65, 10.45) 0.003 0.64
18F-FDOPA baseline MTV 1.93 (0.90, 4.13) 0.09 0.58 1.27 (0.60, 2.68) 0.53 0.53
18F-FDOPA MTV at 2 wk 9.05 (2.90, 28.28) <0.001 0.71 3.91 (1.54, 9.94) 0.004 0.66
18F-FDOPA MTV at 6 wk 2.84 (1.06, 7.62) 0.04 0.59 3.39 (1.19, 9.68) 0.02 0.61
18F-FDOPA MTV reduction 0–2 wk 2.94 (1.24, 6.97) 0.01 0.63 4.34 (1.73, 10.88) 0.002 0.66
18F-FDOPA MTV reduction 0–6 wk 4.02 (1.38, 11.72) 0.01 0.63 3.37 (1.28, 8.89) 0.01 0.62
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HR: Hazard ratio. P: Significance. C: Harrell’s C statistic.

Table 4.

Multivariate COX Regression Analysis of OS

Inclusion of F-FDOPA measure (# cases in model) Predictors HR (95% CI) P-Value C-Statistic
Baseline factors only without 18F-FDOPA PET Recurrences* (30) 2.24 (1.44, 3.51) 0.001 0.67
with 18F-FDOPA PET Baseline 18F-FDOPA MTV (30) 1.01(1.00, 1.01) 0.21 0.70
Recurrences (30) 2.32(1.44, 3.74) 0.001
Baseline and 2 week factors without 18F-FDOPA PET Recurrences* (30) 2.24 (1.44, 3.51) 0.001 0.67
with 18F-FDOPA PET 2 week 18F-FDOPA MTV 7.79 (2.18, 27.77) 0.002 0.76
Recurrences (28) 1.74(1.04, 2.91) 0.036
Baseline, 2 and 6 week factors without 18F-FDOPA PET Recurrences* (29) 2.33 (1.44, 3.67) 0.01 0.68
with 18F-FDOPA PET 2 week 18F-FDOPA MTV 10.71(2.44, 47.09) 0.002 0.73
6 week 18F-FDOPA MTV reduction 4.09(1.23, 13.59) 0.02
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By multivariate analysis, 18F-FDOPA MTV at 2 weeks (P < 0.05; HR = 7.79) and MTV changes at 6 weeks (P < 0.05; HR = 4.09) were the most significant predictors of OS. Interestingly, no apparent added value of 6-week 18F-FDOPA MTV for survival prediction was seen with HR of 10.71 (P < 0.01) for 2 week 18F-FDOPA MTV response and HR of 4.09 (P <0.05) for 6-week 18F-FDOPA MTV response (Table 4).

Similarly, longer PFS was predicted if patients had fewer prior recurrences. 18F-FDOPA MTV at 2 weeks, 6 weeks, and their changes from baseline to 2 weeks and 6 weeks, as well as MRI response were all predictive of PFS (P = 0.004, P = 0.02, P < 0.001, P = 0.002, P = 0.01). By multivariate analysis, 18F-FDOPA MTV change at 2 weeks (P < 0.01; HR, 4.38) is the most significant predictor of PFS.

DISCUSSION

This study examines the value of 18F-FDOPA PET in assessing treatment response in patients with recurrent high-grade gliomas on bevacizumab therapy. First, this study demonstrates that MTV measured by 18F-FDOPA uptake is predictive of OS in patients with recurrent high-grade glioma. Absolute MTV as measured by 18F-FDOPA uptake as early as 2 weeks after starting treatment is the best predictor of OS (P < 0.001). Evaluation of 18F-FDOPA MTV at 2 weeks stratifies patients into 2 subgroups, 18F-FDOPA responders (17/28, 61%) and non-responders (11/28, 39%). 18F-FDOPA responders survived for 12.1 mo, which is 3.5 times longer than the 3.5 mo survival for non-responders (P < 0.001). Second, this study shows that change of 18F-FDOPA MTV at 2 weeks and at 6 weeks (P = 0.002 and P = 0.02) is also predictive of OS, albeit being not as strong a predictor as the absolute MTV at 2 weeks. Third, 18F-FDOPA MTV as well as MTV change at two weeks after treatment initiation are predictive of PFS (P < 0.001 and P = 0.001 respectively). Fourth, 18F-FDOPA SUV values as well as their changes at any time point are not predictive of survival. Finally, this study compared metabolic responses by 18F-FDOPA with MRI response based on RANO criteria. MRI identifies 22 responders (76%; 2 CR, 7 PR, and 13 SD), and 7 patients with PD (24%) and is predictive of OS. Median OS is 1.5 times longer for MRI responders than for MRI non-responders (11.4 vs. 7.7 mo, P = 0.03).

MRI contrast enhancement primarily reflects a disrupted blood–brain barrier (BBB), which can be influenced by changes in corticosteroid dose as well as other treatment effects such as inflammation, radiation necrosis, and postsurgical change (3). In addition, non-enhancing T2-weighted and fluid-attenuated inversion recovery sequence changes can reflect tumor recurrence as well, especially in patients on antiangiogenic therapy (31, 32). Thus, it has been proposed by the recently published Response Assessment in Neurooncology (RANO) that changes in both enhancing and non-enhancing areas should be considered in evaluating treatment response by MRI (31, 32).

All patients in this study had also undergone 18F-fluoro-thymidine (FLT) PET scans as previously reported (5). Current result showed while resonse criteria is different with 18F-FLT PET (maximum tumor SUV changes rather than tumor volume), both 18F-FDOPA PET and 18F-FLT PET have similar predictive value in treatment response in this group of patients. OS for responders and non-responders by 18 F-FLT PET is 12.5 vs 3.8 months (P < 0.001) and OS by 18 F-FDOPA PET is 12.1 vs 3.5 months (P < 0.001).

As amino acid uptake in tumors is not limited to the disruption of BBB, amino acid PET imaging is particularly advantageous in evaluating non-contrast enhancing infiltrating tumors. Amino acid imaging with 18F-FET PET in monitoring treatment in 11 and 10 glioma patients were reported previously (15,16). In was shown 18F-FET PET generally demonstrated treatment failure earlier than MRI. However, follow up 18F-FET-PET was done at 6 – 8 weeks after starting treatment in that study, much later than our study (15,16). Similar to our study, it was shown that 18F-FET PET tumor volume change, but not the SUV change, was predictive of progression free survival. Interestingly, it was noted in our study that not only 18F-FDOPA tumor volume changes but also the 18F-FDOPA tumor volumes at follow up study are predictive of treatment response. As this finding has not been previously reported, rigorous statistical analyses were performed using a leave one out cross-validation analysis to assess how robust and sensitive the cut point to individual values. In addition, a simulation to assess whether this finding was likely a function of selection bias was performed. The process involves breaking up the relationship between 18F-FDOPA MTV and survival variable by randomly permuting the observations and then optimizing a cut point to create an empirical distribution of c-statistics to compare our result to.

In our study, baseline 18F-FDOPA MTV is not predictive of OS (P = 0.08) or PFS (P = 0.31) but the MTVs in the follow up studies are. This is probably due to the fact that while tumor amino acid uptake is not dependent on a permeable BBB, it is enhanced by a broken BBB (34–37). High grade gliomas have pronounced tumor neovascularization through the VEGF pathway and anti-VEGF therapy results in an apparent normalization of the highly permeable BBB (38, 39). It is likely that baseline 18F-FDOPA uptake is in part due to this disturbance of the BBB, thus reflecting a larger than actual tumor volume and therefore is not prognostic of survival. After “normalization” of the disturbed BBB with bevacizumab, 18F-FDOPA uptake in the follow-up studies becomes more reflective of tumor metabolism and outlines an effective tumor volume. Both the decrease of the tumor volume after treatment initiation as well as the resultant tumor size are prognosticators of survival. The fact that only the follow-up 18F-FDOPA MTVs but not the baseline 18F-FDOPA MTV are prognostic, must to some extent reflect the effects of anti-VEGF therapy irrespective of the therapy’s actual mechanism.

The current study has several limitations: First, the study population was small, thus these result need to be validated in a larger prospective study. Second, the patient population is relatively heterogeneous. There was a mix of grade III (N = 6) and grade IV (N = 24) patients. Patients also had a various number of recurrences (median 1.77, range 1 – 5). One could argue that with a patient population at different stages of disease, one would see different prognosis at baseline. Indeed, the number of recurrences before starting treatment is predictive of OS and PFS. However, it is not as strong a predictor as 18F-FDOPA metabolic response, so a significant added predictive value of 18F-FDOPA metabolic response is seen (Table 4).

CONCLUSION

The current study demonstrates that metabolic imaging with 18F-FDOPA PET provides a powerful prognostic tool in assessing treatment response in recurrent high-grade glioma patients on bevacizumab therapy. This response already becomes apparent two weeks after starting treatment. As absolute MTV can be used for assessment, one 18F-FDOPA PET at two weeks suffices to assess treatment response, thus potentially making treatment response assessment with 18F-FDOPA PET both early and cost effective. A further and larger validation study is needed to test the potential of 18F-FDOPA PET in guiding treatment decisions.

Translational Relevance.

Recurrent malignant gliomas carry a very poor prognosis and targeted therapy is an area of active investigation. A non-invasive biomarker that accurately evaluates the disease status and assesses the treatment response with prognostic value (outcome) is critically needed. This study examines the application of 18F-FDOPA PET, a metabolic imaging modality, for monitoring treatment response and for providing prognostic information in patients with recurrent high-grade malignant gliomas on antiangiogenic treatment with bevacizumab. The results of the study can guide the selection of treatment for these patients by identifying responders from non-responders at an early time point after starting therapy. Responders identified by this method live an average of 3.5 times longer than non-responders. Use of this approach would facilitate accrual to clinical trials of targeted therapy in patients with recurrent malignant gliomas.

Acknowledgments

Financial support: This study was supported by grants P50 CA086306 from the National Institutes of Health – National Cancer Institute, and U.S Department of Energy contract DE-FC03-87-ER60615, NIH/National Center for Advancing Translational Science (NCATS) UCLA CTSI Grant Number UL1TR000124

Footnotes

None of the authors report any conflicts of interest.

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