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. Author manuscript; available in PMC: 2015 Aug 6.
Published in final edited form as: J Nucl Med. 2015 Jun 25;56(8):1223–1228. doi: 10.2967/jnumed.115.158717

[F-18]-Fluoromisonidazole Quantification of Hypoxia in Human Cancer Patients using Image-derived Blood Surrogate Tissue Reference Regions

Mark Muzi 1, Lanell M Peterson 1, Janet N O’Sullivan 2, James R Fink 1, Joseph G Rajendran 1, Lena J McLaughlin 1, John P Muzi 1, David A Mankoff 3, Kenneth A Krohn 1
PMCID: PMC4526410  NIHMSID: NIHMS703370  PMID: 26112020

Abstract

18F-FMISO is the most widely used PET agent for imaging hypoxia, a condition associated with resistance to tumor therapy. 18F-FMISO equilibrates in normoxic tissues, but is retained under hypoxic conditions because of reduction and binding to macromolecules.

A simple tissue-to-blood ratio (TB) is suitable for quantifying hypoxia. A threshold of TB ≥ 1.2 is useful in discriminating the hypoxic volume (HV) of tissue; TBmax is the maximum intensity of the hypoxic region and does not invoke a threshold. Because elimination of blood sampling would simplify clinical use, we tested the validity of using imaging regions as a surrogate for blood sampling.

Methods

Patients underwent 20 min 18F-FMISO scans during the 90–140 min interval post-injection with venous blood sampling. 223 18F-FMISO patient studies had detectable surrogate blood regions in the field-of-view. Quantitative parameters of hypoxia (TBmax, HV) derived from blood samples were compared to values using surrogate blood regions derived from heart, aorta and/or cerebellum. In a subset of brain cancer patients, parameters from blood samples and from cerebellum were compared for their ability to independently predict outcome.

Results

Vascular regions of heart showed the highest correlation to measured blood activity (R2 = 0.84). For brain studies, cerebellar activity was similarly correlated to blood samples. In brain cancer patients, Kaplan-Meier analysis showed that image-derived reference regions had nearly identical predictive power as parameters derived from blood, thus obviating the need for venous sampling in these patients.

Conclusions

Simple static analysis of 18F-FMISO PET captures both the intensity (TBmax) and spatial extent (HV) of tumor hypoxia. An image-derived region to assess blood activity can be used as a surrogate for blood sampling in quantification of hypoxia.

Keywords: hypoxia, PET, 18F-FMISO, quantitation

Introduction

Hypoxia Imaging strategies were developed to identify an important factor that limits response to cancer treatment, because of decreased blood flow and drug delivery, decreased proliferation with fewer cycling cells and the genomic component of HIF (hypoxia inducing factor) signaling (1). Tumors have chronically hypoxic areas due to a mismatch between vascular supply and cellular growth. While ionizing radiation is a strategy for killing cancer cells that does not rely on vascular delivery, the cytotoxicity of ionizing radiation depends on the O2 level. Radiation oncologists have devised numerous strategies to overcome the therapy-limiting consequences of hypoxia, but with little success (2, 3). Hypoxia imaging has two clinically important roles: selecting a cohort of patients who might respond better to treatments designed to overcome the limitations of hypoxia and identifying the location of hypoxia in support of intensifying therapy, for example escalating radiation dose (4–6).

Calibrated O2-sensitive electrodes can directly measure oxygen partial pressure (PO2, mmHg), but the signal becomes small in hypoxia. Furthermore, electrodes are invasive, require image-guidance and can not access many tumors (7). Hypoxia is a phenomenological concept with no specific concentration of tissue PO2 that results in a transition from normoxia to hypoxia. The consequences of hypoxia occur when O2 levels are too low to satisfy metabolic demand. Therefore, the best way to measure hypoxia would be with a biomarker that competes directly with intracellular O2, where the agent was not trapped with sufficient O2, but retained when O2 supply was inadequate to accommodate mitochondrial respiration. The mechanism of [F-18]-fluoromisonidazole (18F-FMISO) distribution and retention meets these characteristics (1). However, any attempt to infer PO2 from hypoxia images is misguided.

18F-FMISO is the most widely used radiotracer for assessing tissue hypoxia with positron emission tomography (PET). Its initial tissue distribution following injection is correlated to blood flow (8) because it is freely diffusible. At PO2 < 3 mm Hg, nitroimidazoles such as 18F-FMISO are reduced to a product that is retained in viable hypoxic cells for the duration of the imaging study (9). Normoxic tissues equilibrate with blood after an hour (9, 10). However, longer uptake times are advantageous to minimize unreduced tracer by excretion and improve image contrast. Retention of reduced 18F-FMISO by covalent binding in tissues correlates with the severity of hypoxia (11, 12).

Several methods have been proposed for analyzing 18F-FMISO PET data to quantify oxygenation in human patients (13–15). Our group initially developed a kinetic model with dynamic imaging and arterial sampling, an approach validated using cancer cell spheroids in culture or in animals (16). This approach proved excessively complicated in practice and did not provide useful information because 18F-FMISO has a nearly uniform distribution in almost every tissue after one hour (17). Our first reports quantifying 18F-FMISO hypoxia in animal and human studies examined tissue-to-muscle and tissue-to-blood (TB) ratios to normalize uptake to a reference activity (10, 18). The tissue-to-muscle values produced a variable normalization factor compromised by hypoxic muscle that was compressed during the imaging period. The use of a simple TB ratio adequately and consistently quantified tissue hypoxia. An empiric hypoxic threshold ratio of TB ≥ 1.2, developed over decades of examining thousands of normal and tumor tissues, is useful in discriminating the hypoxic volume (HV) of tissue regions (19).

The maximum TB value in the tumor region, TBmax, reflects the intensity of uptake, while the volume of pixels in a tumor that exceeds the hypoxic threshold is the hypoxic volume (HV), and reflects the extent of hypoxia. Both of these parameters (TBmax and HV) have been shown to be independent predictors of patient outcome in brain cancer (20), head and neck cancer (H&N) (21) and sarcoma (22). However, elimination of blood sampling and analysis requiring a cross-calibrated well counter would be advantageous. The use of SUV, which is common in FDG PET, would not be appropriate because it fails to account for differences in clearance of background activity. The effect on quantification of TB by using reference tissue regions from 18F-FMISO images as surrogates for blood sampling was evaluated. Hypoxic parameters determined from image-derived (ID) blood surrogate regions were also examined for their ability to predict survival and time-to-progression (TTP) in a brain cancer cohort (20).

Methods

Patient Characteristics

223 18F-FMISO imaging studies on 187 cancer patients (64 glioma, 79 H&N, 14 breast, 17 sarcoma, 10 lung, 2 lymphoma, 1 melanoma) who had 269 detectable blood surrogate regions in the imaging field-of-view (FOV) were recruited from the Veterans’ Administration Puget Sound Health Care System, University of Washington Medical Center, and Harborview Medical Center (Table 1). Signed informed consent, as approved by the respective Investigational Review Boards and Radiation Safety Committees, was obtained for all patients prior to imaging. Early studies were done under RDRC, but the majority was performed under IND approval. Many of these patients (73 H&N, 27 GBM, 11 sarcoma and 7 breast) were included in previous reports examining survival prediction or the relationship of 18F-FDG to 18F-FMISO imaging (20–22). A more complete description of the patients appears in supplemental materials.

Table 1.

18F-FMISO Patient Region Summary.

Image-derived blood regions
Cancer Type Cerebellum Aorta Heart
Brain 93
H&N 75 4 3
Sarcoma 2 21 17
Breast 15 15
Lung 10 8
Lymphoma 2 2
Melanoma 1 1
Total Regions 170 53 46
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223 studies on 187 patients were selected based on the presence of a detectable surrogate normoxic tissue.

Radiosynthesis

18F-FMISO was initially prepared using the glycidyl tosylate method (23), then changed to the method developed by Lim (24) and modified by Adamsen (25). In all cases, the same purification by HPLC was used. The product specific activity ranged from 37–74 GBq/μmol at the time of injection with > 98% radiochemical purity. 18F-FMISO was administered by venous injection of a 10 mL solution of isotonic saline containing < 10% (v/v) ethanol USP. The average injected dose for all studies was 267 MBq (range 370 to 148 MBq).

PET Imaging

Most of the PET scans (n = 195) used in this analysis were performed on a GE Advance tomograph (GE Medical Systems, Waukesha, WI) operating in either 3D high sensitivity mode at 30cm FOV for brain studies, or 2D high-resolution mode at 55cm FOV for non-brain studies. Twenty-eight studies were performed on a GE Discovery in 3D mode at either 30cm FOV for brain studies (n = 21) or 55cm for body studies (n = 7). Emission images from both scanners were reconstructed and decay corrected using previously described methods (26). Tomograph sensitivity was calibrated every 3 months using a 20 cm cylindrical phantom containing known 18F Bq/mL, and processed using the same protocol as the patient studies. The well counter for determining blood activity (Cobra, Packard Instruments Inc., Meriden CT) was cross-calibrated at the time of scanner calibration using aliquots from the calibration phantom.

After patient immobilization, venous lines were established in each arm, one for injection and the other for blood sampling. This was followed by a 25 min transmission scan for the GE Advance or a 6 sec low-dose CT scan (120KVP, 60A) for the GE Discovery. A 20 min single FOV emission scan of the tumor region was acquired during the interval of 90 to 140 minutes after injection. In seven studies where an adequate blood pool was not in the FOV, additional emission and transmission scans over the heart immediately preceded or followed tumor imaging. Blood samples were acquired during both scans. Typical 18F-FMISO patient images of tumor uptake appear in supplemental materials.

Blood Sampling

During emission tomography 3 or more venous blood samples were obtained, and the activity of 1 mL aliquots was assayed in a calibrated well counter described above. Averaged blood activity was decay corrected to the injection time and converted to the same units as the scanner (Bq/mL).

Image Analysis

For brain studies, MR images acquired within 2 weeks of the PET scan were registered with the 18F-FMISO images to aid in delineating a tissue volume-of-interest (VOI). Conventional anatomic images (CT, MR) and PET emission scans were used with side-by side visualization to guide VOI construction for body images. Tumor VOIs encompassing the entire tumor volume were constructed using either Alice (Parexcel, Waltham MA) or PMOD (V3.4, PMOD Tech., Zurich CH), after which they were applied to the 18F-FMISO images. Tumor VOIs were 4 cc to 750 cc and did not require partial volume correction. The 18F-FMISO image data were normalized by the average blood activity to produce pixel level TB values. HV was determined as the volume of pixels in the tumor VOI with a TB ratio ≥ 1.2, indicating significant hypoxia (21). For each tumor, the pixel with the maximum TB value (TBmax), and HV were determined.

Quantification of 18F-FMISO in image-derived (ID) tissue regions used as surrogates for blood activity were performed as follows: for heart, 3 cm circular regions were placed on ~2 cm of axial distance over the left ventricular cavity; for aorta, 1 cm circular regions were placed on ~3 cm axial distance and for cerebellum two 2 cm diameter regions were placed on the left and right cerebellar cortex over ~1 cm axial distance (Figure 1). Although brain regions are generally normoxic, cerebellum was selected because brain tumors in adults are typically supratentorial, and may undergo severe morphologic deformation during disease progression (27) preventing the selection of consistent areas of normoxic brain without infiltrative glioma cells. Additionally, H&N cancer patients often have cerebellum in the FOV, so this region is adequate for both cancers. Several imaging studies had multiple surrogate blood regions, such as cardiac and aorta regions in lung and breast cancer studies. The total number of regions assessed was 269 (170 cerebellum, 46 cardiac, 53 aorta) from 223 studies on 187 patients.

Figure 1. 18F-FMISO Image Analysis.

Figure 1

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(A) MR FLAIR image registered to (B) a PET 18F-FMISO image showing placement of 2cm diameter cerebellar ROIs to determine surrogate blood activity. (C) An example of a cardiac (3 cm diameter) and an aortic ROI (1cm diameter) on the low-dose CT scan used for attenuation correction and (D) a PET 18F-FMISO scan. Patient examples of 18F-FMISO tumor uptake appear in supplemental materials.

Statistical Analysis

Correlation and regression statistics for comparison of ID tissue and sampled blood activity, with their associated hypoxia parameters were performed using JMP (SAS Institute; Cary, NC). Comparison of the hypoxia parameters TBmax and HV determined from ID and blood sampling was assessed using regression and Bland-Altman plots to investigate statistical agreement.

To assess image-derived hypoxia parameters as independent predictors of outcome we used a cohort of glioma patients imaged prior to conventional therapy. Our previous report (20) included 22 glioma patients that relied on blood samples for the determination TBmax and HV, and showed predictive value for outcomes. For the current study, the original cohort of patients was expanded to 38 patients.

Univariate and multivariate Cox proportional-hazards regression analysis (28) were used to compare the capability of hypoxic parameters determined from both measured and ID-blood to predict TTP and survival. Progression was defined by RANO criteria for glioma patients (29). Analyses were considered for overall survival and survival at two years, the median survival for patients diagnosed with primary brain cancer (30). Cox multivariate analysis used the hypoxia parameters along with conventional predictors; extent of resection, age, gender and Karnofsky performance score. Grade was not included as 34 of the 38 glioma patients were WHO grade 4. All continuous variables were standardized, so that the hazard ratio represents an increase in risk associated with a one standard deviation increase for the variable. Survival analyses were performed in R (R Development Core 2014; Vienna, Austria).

Results

Average parameters for blood reference tissue regions, along with the blood surrogate hypoxia parameters are presented in Table 2. Overall, surrogate blood regions showed a high correlation (R2 = 0.84, n = 269) to measured blood (Table 3). For studies with cerebellum in the FOV, ID-blood activity was highly correlated to sampled blood (R2 = 0.84, n = 170). Other surrogate regions showed a similar relationship to measured blood (heart R2 = 0.84, n = 46; aorta R2 = 0.83, n = 53).

Table 2.

Blood and Hypoxia Parameter Mean Values

Cerebellum (170*) Aorta (53) Heart (46)
Blood† 1.51±0.22 1.46±0.24 1.45±0.25
ID-blood* 1.50±0.21 1.42±0.23 1.45±0.25
TBmax 1.77±0.55 1.72±0.68 1.74±0.70
ID-TBmax 1.77±0.56 1.78±0.72 1.77±0.78
HV (cc) 20.6±38.5 35.1±57.0 34.5±53.5
ID-HV (cc) 20.9±42.2 35.4±56.0 35.7±55.3
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*

Number of regions analyzed for each blood surrogate.

†

Values for Blood and ID-blood are SUV.

Values presented are the mean ± SD. Blood, TBmax and HV values were derived from blood sampling. ID-blood, ID-TBmax and ID-HV were determined from blood reference tissue regions.

Table 3.

Correlation of Blood to Image-derived Blood Surrogates

n R2 Slope rho SEE/mean
Cerebellum 170 0.84 0.89 0.92 0.06
Cardiac 46 0.84 0.92 0.92 0.07
Aortic 53 0.83 0.87 0.91 0.07
Overall 269 0.84 0.89 0.91 0.06
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Correlation results of ID to sampled blood activity. Correlation parameters are R2(coefficient of determination), slope from linear regression, Pearson’s rho and SEE/mean as a measure of coefficient of variation of the regression.

The injected dose had a low correlation (R2 = 0.42) to blood activity (Figure 2A). Bland-Altman plots (Figure 2B) for blood activity (MBq/mL) and normalized dose (MBq/kg) showed a severe bias and structure. The regression of ID-TBmax vs TBmax showed values clustered around the line of identity (slope = 0.98, intercept = 0.04, SEE/mean = 7% error), and was similar for HV. Bland-Altman plots of TBmax and HV with their coordinate ID parameters all showed little bias with clustering within the standard error limits of ±2SD (Figure 3). Examination of sampled blood and ID-blood data using Bland-Altman plots for individual ID regions showed agreement between measures. The data were clustered around the mean and showed little bias or structure. The average percent difference between blood and ID-values also showed minimal bias (TBmax 1.3% and HV 6.9%). Overall, the relationship between measured blood and ID-blood were consistent (tables and figures in supplemental material).

Figure 2. Correlation of Blood and ID-blood.

Figure 2

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(A) The normalized injected dose (MBq/kg) showed poor correlation (R2 = 0.42, n = 223) to measured blood activity (kBq/mL). (B) The Bland-Altman plot of the data shows unusual structure with points generally lying obliquely to the mean, indicating a poor linear relationship. The regression (C) and Bland-Altman (D) plots between measured blood and surrogate blood regions (ID-blood) showed a high correlation at R2 = 0.84.

Figure 3. Correlation of Hypoxia Parameters.

Figure 3

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(A) Regression plot of TBmax vs ID-TBmax for 269 surrogate blood regions shows a strong relationship with a small COV (SEE/mean). (B) The Bland-Altman plot shows clustering around the mean with little bias. Plots of HV vs ID-HV values in (C) and (D) shows a similar profile.

Kaplan-Meier survival curves are given for both survival and TTP for TBmax and ID-TBmax variables for two-years (Figure 4). Patients were classified as low or high risk by considering whether they were below or above the median TBmax. When overlaid on those plots, the ID-TBmax variable shows a high degree of similarity to blood-derived TBmax. Overall, the image-derived parameters were as predictive and showed similar plot characteristics as parameters determined using sampled blood.

Figure 4. Kaplan-Meier Survival Analysis.

Figure 4

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Hypoxia parameters were used to stratify 38 pretreatment glioma patients with respect to 2-year survival and TTP. Kaplan-Meier plots for TBmax demonstrated significantly shorter survival (A) and TTP (B) in high risk patients (red line) whose tumors possessed TBmax ratios greater than the median (TBmax > 1.83) relative to low risk patients (black line). Using cerebellum as a blood surrogate, produced the hypoxia parameter ID-TBmax (dotted lines, median ID-TBmax = 1.77) that had nearly identical predictive power as TBmax. Kaplan-Meier plots and results for HV appear in supplemental materials.

Univariate analysis (Table 4) showed that ID hypoxia parameters were as predictive as parameters determined using blood samples. Age and Karnofsky score were significantly associated with survival and TTP. Clinical information (age, gender, Karnofsky score and resection status) was considered in multivariate models with each of the hypoxia variables (Table 4). Multivariate Cox proportional hazards analysis showed that all measures of hypoxia (HV, ID-HV, TBmax, ID-TBmax) were highly significant predictors of outcomes, when the model was adjusted for clinical parameters. Hazard ratios and p-values for the 18F-FMISO variables and the clinical covariates all remained similar when the ID variables replaced the ones using sampled blood. R2 values for the models were also similar, with the greatest absolute change being 2% for the comparison of TTP using TBmax or ID-TBmax (R2 = 0.47 for the TBmax model vs R2 = 0.49 for the ID-TBmax model). Using a backwards elimination approach (not shown) age was the only variable that added prognostic utility when included with hypoxia information. Karnofsky score and gender did not add information to the model. HV survival results appear in supplemental materials.

Table 4.

Results of Univariate and Multivariate Cox Regression Analysis for Predictors of Survival in Pretreatment Glioma Patients (n = 38)

Univatiate
Survival
TTP
Hazard P Hazard P
Age 1.73   0.005 1.73   0.004
Gender 1.77   0.144 1.80   0.131
KPS 0.63   0.019 0.67   0.028
HV 2.30 <0.001 2.07 <0.001
ID-HV 2.69 <0.001 2.45 <0.001
TBmax 2.51 <0.001 2.34 <0.001
ID-TBmax 2.41 <0.001 2.31 <0.001
Resection* 1.21   0.604 1.16   0.664
Multivariate
Survival (0.390) †
TTP (0.466)
Hazard P Hazard P
Age 1.26 0.421 1.44   0.158
Gender 1.77   0.525 1.43   0.440
KPS 0.78   0.324 0.88   0.554
TBmax 2.37 <0.001 2.31 <0.001
Resection 0.76   0.516 0.75   0.463
Survival (0.394) TTP (0.485)
Hazard P Hazard P
Age 1.22   0.483 1.38   0.210
Gender 1.23   0.676 1.31   0.559
KPS 0.75   0.244 0.82   0.378
ID-TBmax 2.30 <0.001 2.30 <0.001
Resection 0.81   0.616 0.77   0.519
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*

Resection is dichotomized as biopsy or other (gross/sub-total resection).

†

The coefficient of determination (R2) is given for each table.

Univariate analysis of hypoxia and clinical variables shows the hazard ratio with P values associated with survival and TTP at 2 years. After adjusting for clinical variables using a multivariate model, greater tumor TBmax was still associated with shorter survival and TTP. Multivariate results for HV and ID-HV appear in supplemental materials.

Discussion

Since the introduction of the kinetic model of 18F-FMISO metabolism to estimate hypoxia in tumor spheroids (16), work on alternative, simpler methods to assess 18F-FMISO retention and reduce blood sampling and imaging time have been reported (5, 14, 15, 31). These techniques have shortcomings associated with the measurement and interpretation. The complexity of dynamic imaging with arterial sampling is unwarranted for a tracer that distributes in tissue by a partition coefficient mechanism. Agents with partition coefficients far from unity may warrant a more complicated dynamic analysis to separate delivery from retention (32, 33). A stable reference such as blood is preferred in order to normalize 18F-FMISO uptake to tracer delivery by computing a tissue-to-blood partition coefficient (34). The TB ratio provides a reliable and consistent measure of HV, which is based on the retention of reduced 18F-FMISO under conditions of low PO2.

The impact of using an image-derived tissue surrogate for blood in determining ID-HV in glioma patients produced an average bias of approximately 6%, and was considered minimal. The average bias for cardiac and aorta surrogates for ID-HV in non-neural tumors was 4% and 8%, respectively. This is tolerable as a trade off to eliminate blood sampling from the protocol.

Imaging 18F-FMISO in several cancer types, with identification of vasculature through coordinate CT or MR mapping, provides an image-derived surrogate that is directly correlated to sampled blood activity. Studies that imaged the heart separately from tumor illustrate that a region without a blood pool can be used to quantify 18F-FMISO, provided that a secondary scan over the heart can be acquired. Results from 18F-FMISO brain studies show a high correlation between cerebellum and venous blood activity. These correlative results suggest that quantifying 18F-FMISO hypoxia parameters can be based on image-derived surrogate activity that has been shown to correlate to sampled blood.

An alternative analysis without blood sampling could be considered based on the relationship between the weight-normalized injected dose and sampled blood activity. The normalized injected dose (MBq/kg) showed poor correlation (R2 = 0.42, n=223) to blood activity concentration (Bq/mL), and the Bland-Altman plot of the data shows structure with points generally lying obliquely to the mean indicating a poor linear relationship. We conclude that normalizing to injected dose is not valid.

Previously, we reported on the predictive value of TBmax and HV determined from blood samples for outcome in glioma patients (20). Survival analysis using 18F-FMISO imaging results from 38 brain tumor patients support the hypothesis that a greater hypoxic tumor burden prior to therapy predicts shorter survival and TTP. However, these results imply that more hypoxic volume means more tumor is at risk for the genomic consequences of hypoxia. This interpretation may apply to HV, but the tumor TBmax or ID-TBmax as indicators of hypoxia are less dependent on tumor volume. TBmax has the advantage of not requiring an empirical threshold for hypoxia assessment and ID-TBmax has a further advantage of not requiring blood sampling. Survival analyses of hypoxic parameters determined without blood sampling were nearly identical to those determined with blood samples. This suggests that the most parsimonious method for quantifying hypoxia with 18F-FMISO is an imaging session after partition equilibrium with no blood sampling to yield hypoxic parameters useful for assessing response and predicting outcome.

Conclusion

Image-derived tissue regions that are highly correlated to blood levels can be used as surrogates in the quantification of hypoxia parameters for 18F-FMISO imaging (TBmax and HV). This association supports the elimination of serial blood sampling during 18F-FMISO imaging. Reducing the complexity of 18F-FMISO imaging through a short static imaging session without blood sampling is a parsimonious method to delineate tumor hypoxia without compromising the efficacy of the hypoxic assessment, that makes it it suitable as a routine clinical procedure and for large clinical trials.

Supplementary Material

Supplemental Material

Acknowledgments

Our initial studies of hypoxia were motivated by Drs Janet Rasey, Wui-Jin Koh, Janet Eary and Alexander Spence, who we gratefully acknowledge for their contribution toward our perspective on hypoxia imaging. We also acknowledge the effort of Dr. Jeanne Link and the UW radiochemistry group for the many productions of 18F-FMISO.

Support: NCI (P01-CA042045), NIH (RR-017229), ACRIN (U01CA079778 and U01CA080098) and the Science Foundation of Ireland (11/PI/1027).

Disclosures: Our research is supported by the National Cancer Institute (P01-CA042045, R01-CA72064), a NIH major equipment grant (RR-017229), ACRIN (U01CA079778 and U01CA080098) and the Science Foundation of Ireland (11/PI/1027).

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