Imaging techniques that reflect dynamic bone turnover may aid in characterizing a wide range of bone pathologies. We present detailed methodologies for performing and analyzing dynamic [18F]-NaF-PET-MRI data in a patient with facetogenic low back pain using the lumbar facet joints as a prototypical region of interest.
Imaging techniques that reflect dynamic bone turnover may aid in characterizing a wide range of bone pathologies. Bone is a dynamic tissue undergoing continuous remodeling with the competing activity of osteoblasts, which produce the new bone matrix, and osteoclasts, whose function is to eliminate mineralized bone. [18F]-NaF is a positron emission tomography (PET) radiotracer that enables visualization of bone metabolism. [18F]-NaF is chemically absorbed into hydroxyapatite in the bone matrix by osteoblasts and can thus noninvasively detect osteoblastic activity, which is occult to conventional imaging techniques. Kinetic modeling of dynamic [18F]-NaF-PET data provides detailed quantitative measures of bone metabolism. Conventional semi-quantitative PET data, which utilizes standardized uptake values (SUVs) as a measure of radiotracer activity, is referred to as a static technique due to its snapshot of tracer uptake in time. Kinetic modeling, however, utilizes dynamic image data where tracer levels are continuously acquired providing tracer uptake temporal resolution. From the kinetic modeling of dynamic data, quantitative values like blood flow and metabolic rate (i.e., potentially informative metrics of tracer dynamics) can be extracted, all with respect to the measured activity in the image data. When combined with dual modality PET-MRI, region-specific kinetic data can be correlated with anatomically registered high-resolution structural and pathologic information afforded by MRI. The goal of this methodological manuscript is to outline detailed techniques for performing and analyzing dynamic [18F]-NaF-PET-MRI data. The lumbar facet joint is a common site of degenerative arthritis disease and a common cause for axial low back pain. Recent studies suggest [18F]-NaF-PET may serve as a useful biomarker of painful facetogenic disease. The human lumbar facet joint will, therefore, be used as a prototypical region of interest for dynamic [18F]-NaF-PET-MRI analysis in this manuscript.
Standard clinical imaging techniques of bone pathology are primarily limited to characterizing structural changes, which can be nonspecific. For example, asymptomatic morphologic abnormalities related to the normal aging may be indistinguishable from degenerative alterations which are responsible for severe pain and disability1. Bone is a dynamic tissue undergoing continuous remodeling with the competing activity of osteoblasts, which produce the new bone matrix, and osteoclasts, whose function is to eliminate mineralized bone2. [18F]-NaF is a positron emission tomography (PET) radiotracer that enables visualization of bone tissue metabolism. [18F]-NaF is chemically absorbed into hydroxyapatite in the bone matrix by osteoblasts and can thus noninvasively detect osteoblastic activity, thereby detecting a metabolic process which is occult to conventional imaging techniques. As a result, [18F]-NaF has been used for characterizing bone pathology in an increasing number of bone disorders including neoplasms, inflammatory, and degenerative disease of the bone and joints3,4,5.
PET data is most commonly analyzed in a semi-quantitative fashion, which can be readily performed in routine clinical practice with standardized uptake values (SUVs). As a metric, SUVs are useful to clinicians as they represent tissue uptake relative to the rest of the body6. Values from subsequent scans may be used to observe changes in uptake as a result of treatment or disease progression. The numerical nature of SUVs also aids in comparison between patients and between successive scans in the same patient. The algorithm used to calculate SUVs, Equation 1, makes the assumption that the tracer is equally distributed throughout the body and that the lean body mass accurately represents whole body volume. As such, SUVs are a semi-quantitative measurement. For a given region of interest (ROI), SUVmax (the maximum SUV value within a ROI), and SUVmean (the mean of all sampled SUVs within an ROI) are commonly used SUV metrics in clinical practice6.
Kinetic modeling of dynamic PET data can also be performed for more detailed quantitative analysis. While SUV data acquisition is static, kinetic modeling utilizes dynamic image data where tracer levels are continuously acquired providing a temporal dimension. From the more complex kinetic modeling of dynamic data, quantitative values and informative metrics of tracer dynamics can be extracted with respect to the measured activity in the image data. A sample two-tissue compartment model employed for dynamic kinetic modeling is shown in Figure 17. Cp is the concentration of tracer in the blood plasma while Ce and Ct represent the concentration in the unbound interstitial space and bound tracer in the target bone matrix respectively. K1, k2, k3, k4, are 4 rate parameters that describe the kinetic model for tracer wash in/out and binding. K1 describes the tracer taken up from arterial plasma into interstitial space (Ct), k2 describes the fraction of tracer that diffuses back from the interstitial space to plasma, k3 describes the tracer that moves from interstitial (Ce) space to bone (Ct), and k4 describes the tracer that moves from bone (Ct) back to the interstitial space (Ce).
Figure 1. A sample two-tissue compartment model for dynamic kinetic modeling. Cp is the tracer concentration in the blood plasma compartment, Ce free and non-specifically bound tracer concentration in tissue, and Ct specifically bound tracer concentration in the tissue. Please click here to view a larger version of this figure.
The Patlak kinetic model produces Ki_Patlak as a measure of radiotracer influx rate (mL/ccm/min, cubic cm = ccm) from the blood pool into the bone matrix. The tracer influx rate from the blood pool to the bone matrix can then be calculated using Equation 2 and Equation 3 for Ki_Patlak and Ki_NonLinear respectively. Ki_Patlak and Ki_NonLinear are the rates at which [18F]-NaF leaves the arterial blood pool and irreversibly binds to a subsite bone matrix, using the two models respectively. A difference between the Patlak and non-linear kinetic model is in their utilization of the dynamic data. The Patlak model requires equilibrium to be met and then calculates the influx rate from the established linear slope. The Patlak kinetic model produces Ki_Patlak influx rates, by using a 24-minute time to equilibration of the plasma pool, Cp, to the unbound pool, Cu. The 24-minute time can change depending on the time found for all subsites to reach equilibration with the plasma pool in the sample. The more computationally rigorous non-linear model uses the entirety of the temporal data to fit a curve.
The goal of this methodological manuscript is to outline detailed techniques for performing dynamic [18F]-NaF-PET-MRI. The lumbar facet joint is a common site of degenerative arthritis disease and a common cause for axial low back pain8. Recent studies suggest [18F]-NaF-PET-MRI may serve as a useful biomarker of painful facetogenic disease9. The human lumbar facet joints from a single patient with facetogenic low back pain will thus be analyzed as a prototypical ROI for dynamic [18F]-NaF-PET-MRI analysis.
This prospective feasibility study recruited patients after obtaining Human Study IRB approval and complying with HIPAA regulations.
1. Phantom
2. Patient Preparation
3. Imaging Protocol
4. Image analysis
5. Data analysis
6. SUV Calculations and Kinetic Data
7. PET Partial Volume Correction
NOTE: Due to PVE the tracer activity is underestimated in relation to the size of the target. Therefore, steps are taken to correct for the PVE.
8. SUV Calculations and Kinetic Data
Note: The algorithm used to calculate Standard Uptake Value (SUV), Equation 1, makes the assumption that the tracer is equally distributed throughout the body and that the lean body mass accurately represents whole body volume. Therefore, SUVs are referred to as a semi-quantitative measurement.
Equation 1: Standard Uptake Value
9. Statistical Analysis
18NaF-PET uptake values are measured in the bilateral facet joints at the L1-L2 through L5-S1 vertebral levels for a total of 10 ROIs in a single representative patient with axial low back pain. Representative [18F]-NaF-PET, axial T2 fat suppressed, and axial T1 post-contrast fat-suppressed MR images through the level of the L3-L4 facet joints are shown in Figure 2. The Ki_Patlak, SUVmean, SUVmax, and MRI facet arthropathy grade for each of the 10 sampled facet joints in a representative patient are summarized in Table 1. Ki_Patlak influx rates are plotted again SUVmean and MRI-based facet arthropathy grades in Figure 3. In this representative case, the facet joint with the highest MRI grade of degenerative facet arthropathy (left-sided L3-L4) has the highest Ki_Patlak and SUVmean values.
Figure 2. Representative [18F]-NaF-PET and MR images of lumbar facet joints. A) Axial [18F]-NaF-PET SUV image through the L3-L4 facet joints revealing asymmetric radiotracer uptake on the left. Red-dashed circles outline the approximate ROI for analysis of each facet joint. Axial T2 fat-suppressed (B) and axial T1 post-contrast fat-suppressed (C) images through the L3-L4 level in the same patient showing asymmetric left-sided peri-facet edema and enhancement (white arrows in B and C respectively). Please click here to view a larger version of this figure.
Figure 3. Ki_Patlak plots: Ki_Patlak versus SUVmean (A) and Ki_Patlak versus MRI facet arthropathy grade (B) for all 10 lumbar facet joints in a representative patient. The single isolated data point with relatively elevated Ki_Patlak, SUVmean, and MRI facet grade in the upper right quadrant of each plot corresponds to the patients left L3-L4 facet joint. Please click here to view a larger version of this figure.
Facet Joint | Ki_Patlak mL/ccm/min* | SUVmean | SUVmax | MRI Grade |
Right L1-L2 | 0.015 | 3.1 | 5.4 | 1 |
Left L1-L2 | 0.009 | 2.4 | 5.4 | 1 |
Right L2-L3 | 0.014 | 2.9 | 5.9 | 1 |
Left L2-L3 | 0.012 | 2.8 | 5.7 | 1 |
Right L3-L4 | 0.013 | 2.7 | 5.4 | 1 |
Left L3-L4 | 0.028 | 7 | 13.6 | 3 |
Right L4-L5 | 0.011 | 2.9 | 5.5 | 1 |
Left L4-L5 | 0.014 | 3.3 | 5.7 | 1 |
Right L5-S1 | 0.011 | 3.3 | 6.6 | 1 |
Left L5-S1 | 0.013 | 3.3 | 5.9 | 0 |
*mL/ccm/min=millilitres per cubic centimeter per min |
Table 1: Ki_Patlak, SUVmean, SUVmax, and MRI facet arthropathy grade for each of the 10 sampled facet joints in a representative patient.
In this methodological manuscript, we have provided background on the potential utility of dynamic [18F]-NaF-PET-MRI for evaluating a wide range of bone pathologies and have outlined the techniques for dynamic [18F]-NaF-PET-MRI image acquisition and analysis using the human lumbar facet joints as prototypical regions of interest. Dual modality PET-MRI allows for acquisition of dynamic PET data over a time period similar to that required for MR data acquisition alone, thus maximizing the overlap of scan time. While MRI provides high-resolution structural imaging of the spine that can readily identify a broad range of bone pathologies, the addition of quantitative dynamic PET with hybrid PET-MRI may add benefit as a functional biomarker of active bone turnover. Although we describe techniques for dual modality PET-MRI, our methods could be easily adapted for PET only or combined PET-CT datasets.
SUV values make an assumption that radiotracer is evenly distributed throughout the entire body and base the measurement off a lean body mass coefficient. Kinetic indices of radiotracer uptake such as Ki_Patlak on the other hand measure specific concentrations of radiotracer reaching the target via the arterial system over the time length of the scan. This added information may reveal the subtle changes in flow of the tracer to regions of interest that would otherwise be missed. Brenner and colleagues previously reported a linear relationship between SUVmean, SUVmax and Ki_Patlak in a wide range of normal and pathologic bone conditions12. Previous work has further demonstrated a strong positive linear correlation between Ki_Patlak of facet joints and clinical measures of facetogenic low back pain13. Ongoing prospective clinical trials are underway to evaluate the potential for [18F]-NaF-PET-MRI to aid in treatment planning and longitudinal monitoring of degenerative lumbar facet disease. Although in the early stages of clinical translation, dynamic [18F]-NaF-PET-MRI analysis holds great potential for a variety of common bone and joint diseases.
In addition to facetogenic low back pain, there are many potential applications for this technology. For example, the osteoblastic activity leading to hypertrophic osteophytes found in joints with ankylosing spondylitis is controlled by inflammatory cytokines, wingless (wnt) and bone morphogenic proteins. Wnt proteins act to cause an anabolic skeletal response14. A regulatory protein of wnt known as Dickkopf, DKK, competes with wnt and thereby regulates osteoblastic activity. Lower levels of DKK result in increased osteoblastic activity and increased bone formation in ankylosing spondylitis patients. The pathway from inflammatory cytokine to osteoblastic activity is not known yet15. The connection between these pathways in ankylosing spondylitis and pathological osteoblastic activity in osteoarthritis is purely speculative at this time. But, it has been shown by immunohistochemical analysis of facet joints that both ankylosing spondylitis and osteoarthritis may share a repair mechanism of new bone formation through osteoblastic activity15. These changes in osteoblastic activity may be observed quantitatively using the [18F]-NaF-PET-MRI PET techniques described herein.
The authors have nothing to disclose.
Research support was provided by NIH P50AR060752 and GE Healthcare. We would like to acknowledge the support by Vahid Ravanfar.
Gadolinium Contrast agent (Gadovist) | Bayer | na | 1.0mmol/ml solution for IV injection. |
[18F]-NaF Radiotracer | na | na | 2.96 MBq/kg |
GE Signa PET-MRI Scanner | General Electric | na | 3.0Tesla 60cm Bore PET-MRI scanner |
PMOD Kinetic Modeling Software | PMOD Technologies, LLC | na | Version 3.8 |