[18F]-sodium fluoride ([18F]NaF) is a well-established bone-seeking agent that has shown promise as a marker to study bone turnover in a variety of bone and joint disorders, including the knee.1–4 Although most often used in oncological examinations, elevated [18F]NaF SUV has been reported to coincide with early disease changes in osteoarthritis,3–5 rheumatoid arthritis,6,7 and pain.4,5,8,9 However, SUV only provides a semiquantitative measure of tracer uptake and is unable to differentiate underlying physiological mechanisms of clinical importance. Fluoride uptake in bone tissue is dependent on a number of factors including perfusion, capillary permeability, and transit times between blood plasma and extracellular fluid. After reaching the bone matrix, fluoride ions either bind by exchanging with hydroxyl groups in the hydroxyapatite-like mineral of bone to form fluoroapatite10,11 at sites of remodeling and turnover12–15 or reenter the bloodstream. Using the Hawkins16 kinetic model of [18F]NaF uptake (Fig. 1), these underlying processes can be quantified by the rate of transit of the 18F− concentration from plasma to the extravascular bone compartment (K1), the fraction of extravascular 18F− ions binding to the bone matrix (k3/(k2 + k3)), and the total rate of fluoride clearance from plasma to the bone matrix (Ki). The parameter Ki has been found to have higher sensitivity to treatment response17–19 than SUV and similar precision in terms of repeatability.19,20 Further, K1 has been applied by several groups as a marker for bone vasculature,21–24 whereas the parameter describing the tracer extraction fraction (k3/(k2 + k3)) has been used as a marker for bone turnover.23,25
Although [18F]NaF kinetic modeling has been studied for bone turnover in the upper body, there are few data for parametric values in the healthy knee.1,26,27 Further, integrated PET/MRI systems have the potential to improve the clinical feasibility of kinetic modeling. Not only is MRI already widely utilized for imaging of joint disorders, but also high-resolution MR angiograms can also help obtain the necessary input function of PET tracer delivery without invasive arterial blood sampling.28 Furthermore, quantitative MRI metrics such as T1rho and T2 relaxation times are able to assess biochemical and structural properties in cartilage, tendons, and muscle.29–34 PET/MRI systems provide a unique opportunity to leverage the extended MRI scanning time for a simultaneous kinetic PET examination and lower radiation dose, combining the advantages of conventional MRI, quantitative MRI, and molecular information from PET. The purpose of this study was to investigate key parametric and semiparametric values for [18F]NaF uptake in the healthy knee, including Ki, K1, k3/(k2 + k3), SUV, and SUVmax, using PET/MRI. The bone tissues investigated included trabecular bone and subchondral bone of the distal end of the femoral bone and tibial head, as well as the cortical bone of the femoral and tibial shafts.
Twelve healthy subjects with no history of musculoskeletal complications (7 women, aged 22–44 years, body mass index 23 ± 3.3 kg/m2) and having abstained from exercise for 24 hours were hand-injected via an intravenous catheter with 92.5 MBq of [18F]NaF. The study was performed in compliance with the local institutional review board (Stanford University, Administrative Panels for the Protection of Human Subjects) regulations, and all subjects provided written consent prior to the study. One subject repeated the trial on 3 separate days to evaluate reproducibility.
Subjects were scanned on a 3-T whole-body time-of-flight PET-MR hybrid system (GE Healthcare, Milwaukee, Wis). Each subject was positioned feet first with a 16-channel flexible phased-array receive-only coil (NeoCoil, Pewaukee, Wis) around each knee.35 The coils were used because of their lower attenuation effect on PET photons. Both knees were scanned using 1 PET bed (field of view = 25 cm) in list mode starting with the injection of NaF for 50 minutes, and all MRI data were acquired simultaneously with PET imaging.
Magnetic resonance angiography data were acquired using a 3-dimensional gradient echo sequence with imaging parameters: repetition time/echo time (TE) = 21/2.1 milliseconds, slices = 18, slice thickness = 1.2 mm, and flip angle = 15°. A 2-point Dixon fat-water T1-weighted spoiled gradient echo MR sequence was acquired for MR-based attenuation correction of PET data36 with acquisition parameters: repetition time/TE1/TE2 = 4.1/1.1/2.2 milliseconds, field of view = 50 × 37.5 cm, matrix = 256 × 128, slice thickness/overlap = 5.2/2.6 mm, 120 images/slab, scan time = 18 seconds.
For calculation of the image-derived input function (IDIF), dynamic PET frame times of 40 × 1 seconds, 13 × 10 seconds, and 23 × 2 minutes were reconstructed using time of flight–ordered subset expectation maximization with 3 iterations and 21 subsets with corrections for decay, attenuation, scatter, random, and dead time. Time activity curves of bone PET uptake were determined using dynamic PET time frames of 8 × 2 seconds and 24 × 2 minutes with the same corrections. A 3-mL venous blood sample was taken 50 minutes after injection when arterial and venous blood concentrations have equilibrated and measured in a well counter.37
The IDIF was determined from [18F]NaF activity (kBq/mL) within the popliteal artery of each knee. The artery was segmented automatically from MR angiography images and a short time-frame PET angiogram during the arterial phase (0–16 seconds after injection) when the tracer is predominantly in the arteries.28 In order to minimize spillover artifacts,38 the voxels centered in the middle of the artery were determined for each dynamic PET frame and used for the IDIF. Central voxels were defined by including the voxels in each axial slice within the highest 10% of arterial NaF activity.
Bone Segmentations and Regions of Interest
Using the in-phase, out-of-phase, and water images from the Dixon scans, masks covering the femur, patella, and tibia were first created by manually drawing regions of interest (ROIs) (Fig. 2). The bone tissue was then segmented further to create subchondral/cortical bone masks using k-means clustering (4 cluster groups minimized to squared Euclidean distance repeated 4 times with different initial centroids). The long bone of the femur and tibia was identified as the cortical bone 6 to 8 cm from the center of the joint space. Trabecular bone ROIs in the tibia and distal end of the femoral bone were drawn for both legs maintaining a minimum of 3-mm distance from the edge of the bone to avoid partial voluming. Thereafter, the subchondral bone of the femur was manually subdivided into 5 regions: trochlea and central and posterior regions of the medial and lateral compartments. Similarly, tibial subchondral bone was further separated into lateral and medial regions. Lastly, cortical bone at the site of a patellar tendon insertion (tibial tuberosity) was identified and excluded from the analysis of cortical bone.
SUV and Kinetic Modeling
The time activity curves and IDIF data were fitted to the 2-tissue compartment model using the Patlak method and again using the nonlinear regression (NLR) method. Patlak analysis27,39 is a graphical technique for estimating Ki, the total rate of plasma clearance of NaF to the bone matrix, which assumes that 18F− is irreversibly bound to bone mineral (k4 = 0). Data from 10 to 50 minutes were fit to allow for equilibration between tracer in plasma and the bone extracellular fluid. Nonlinear regression fitting included estimation of 3 rate parameters (K1, k2, and k3) along with a partial volume fraction, a blood fraction, and an input dispersion estimate and was computed using COMKAT software.40 The rate constant k4 was predefined as 0. For both blood fraction and K1, a parameter range from 0 to 1 was applied, whereas a range of 0.015 to 0.8 was used for k2 and k3 and 0 to 2 seconds for the dispersion constant tau. To avoid local minimums, fits were repeated with 3 starting conditions, and results with the lowest residuals were used. The rate of total plasma clearance using the NLR method (KiNLR) was calculated from the K1, k2, and k3 values obtained by using the following formula:
KiNLR, like K1, has units of mL·min−1·mL−1, whereas k2 − k3 have units of min−1.
The KiNLR parameter can be separated into 2 parameters of physiological interest. One parameter is K1, the rate of transit of the 18F− plasma concentration into the extravascular compartment, and reflects flow delivery of the tracer. Perfusion (F) estimates for each ROI were derived from K1 values using least squares regression to the Renkin-Crone formula41:
where the product of permeability and surface area (PS) was assumed to be 0.24, as reported by Piert et al.21 The second physiological parameter is the extraction fraction, k3/(k2 + k3), which represents the fraction of 18F− entering the tissue that binds to the bone matrix as opposed to reentering the bloodstream.
Images for mean SUV and SUVmax were calculated from images obtained by averaging the last 2 frames of the dynamic study (46–50 minutes).
Values across the entire patient cohort are reported as median with interquartile range, and P values are from paired Student 2-tailed t tests using a threshold for significance of P < 0.05 after Bonferroni correction for multiple comparisons. Correlations between obtained parameters were analyzed using least products linear regression where goodness of fit was evaluated with a Pearson adjusted R2 value. Reproducibility between IDIF blood activity and venous blood samples was analyzed by calculating the coefficient of variation, reported in percent. Image coregistration, ROI analysis, calculations, and statistical analysis were performed with software created in MATLAB 2013b (MathWorks, Natick, Mass).
Median parametric values along with interquartile range across all subjects are presented in Table 1. Variations in global [18F]NaF uptake were observed between subjects (Fig. 3) with consequently higher or lower SUV values across all 3 types of bone tissue. Comparisons between the 3 bone tissue types are shown in Figure 4. Cortical bone had highest [18F]NaF uptake for all measured parameters compared with trabecular bone (P < 0.01), which had the lowest uptake. SUV and Ki values for subchondral bone were lower than that of cortical bone, but these differences were not significant after correction for multiple comparisons. Subjects had significantly higher SUVmax and K1 values and a significantly lower extraction fraction in cortical bone compared with subchondral bone. Subchondral bone had significantly higher [18F]NaF uptake (SUV, SUVmax, and KiNLR; P < 0.01) than trabecular bone tissue.
There was a regional variance in distribution of K1 and extraction fraction values. The distribution ranged from cortical bone of the shaft, which had the highest vascularization where K1 > Ki and k3/(k3 + k2) < 1, to the trochlea and patella region of subchondral bone, where k3/(k3 + k2) ≃ 1 and K1 ≃ Ki (Fig. 5). By visual analysis of K1 and k3/(k3 + k2) maps, a negative gradient of K1 values can be seen from the femoral and tibial shafts decreasing toward the joint space. A second gradient can be seen as K1 is higher in subchondral bone and declines toward the center of the trabecular bone of the femur and tibial head (Fig. 6). In the subchondral bone of the femur, K1 and blood volume values were higher in the posterior section, decreasing to the lowest in the trochlea (P < 0.01). The opposite gradient was observed in the extraction fraction maps, resulting in total metabolism KiNLR and SUV images that were more spatially uniform.
There were no other significant differences in [18F]NaF uptake parameters between the 3 bone tissue types or between subregions of subchondral bone. The sites of tendon insertion had elevated SUV values and significantly higher KiNLR (P < 0.05) than remaining cortical bone tissue. The vascularization was lower (K1 33% less, blood volume 84% lower [both P > 0.01]), and the extraction fraction higher (k3/(k3 + k2) 88% higher, P < 0.01).
KiNLR values correlated highly with SUV values (R2 = 0.90). Kipat values from the Patlak method had a slightly poorer correlation to SUV (R2 = 0.87) and were 17% lower than those obtained by NLR (Fig. 7). The correlation of Kipat values to KiNLR values was high (R2 = 0.97) despite the 17% bias (Fig. 7). Using K1 values from the NLR fit, flow values were obtained and found to be within a few percentage points of K1 values (Table 1). The K1 values were in the range where K1 < < PS, and thereby the condition F≈K1 applies.
Group average IDIF values at 1, 5, 10, and 50 minutes were 10.2, 6.0, 4.2, and 2 kBq/mL when normalized to a 100-MBq injection. At 50 minutes, mean IDIF values were 6% higher than mean venous blood sample values. Coefficient of variation values between venous blood samples and IDIF values measured at 50 minutes were 8.3%. Repeated injections in 1 subject had mean coefficient of variation values of 9% across time points observed between 1 and 50 minutes (Fig. 8).
Semiquantitative and quantitative values for [18F]NaF uptake in the knee were obtained from healthy subjects using PET/MRI. A large intersubject variation in NaF uptake was observed as there were significant differences in uptake parameters between cortical bone and the subchondral/trabecular bone tissues. Trabecular bone was found to have significantly lower SUV, Ki, K1, and blood volume values yet a significantly higher extraction fraction than the cortical bone tissue in the shaft of the femur and tibia. Blood volume was the parameter with the largest discrepancy between bone tissues being significantly higher in the shaft compared with subchondral or trabecular bone of the knee. Subjects had higher vascularization (larger blood volume and higher K1 values) in the shaft of the femur and tibia declining with a negative gradient toward the joint space reaching the lowest values at the center of the trabecular bone near the distal end. This K1 gradient was partially offset by a gradient of increasing extraction efficiency that was significantly lower in the shaft. A similar regional discrepancy was also evident in SUV, SUVmax, and KiNLR, although to a lesser degree. These parameters, like K1, were significantly higher in the shaft decreasing in the subchondral bone and trabecular bone of the knee joint in these healthy individuals. Likewise, the sites of tendon insertion of the cortical bone had much lower vascularization (K1 and blood volume), yet a net uptake than regular cortical bone due to a high extraction fraction. A similar observation has been made between the spine and humeral bone tissues where low K1 values in the humeral bone were partially compensated by a higher k3/(k3 + k2) to give a more comparable, yet still significantly lower, Ki value.23,25 Aside from the K1 and k3/(k3 + k2) gradients, all other parametric values within the subchondral bone tissue ROIs of subjects were quite homogenous with no significant differences when comparing subchondral subregions across the patella, femur, and tibia.
Kipat values from the Patlak method were 17% lower than those obtained by NLR, which is a larger bias than previously reported by Siddique et al,17 where Kipat was 10% lower than KiNLR in the lumbar vertebrae. Still, KiNLR values correlated highly with both Kipat values (R2 = 0.97) and SUV (R2 = 0.90) with no regional variations in their correlation. Ultimately, this study gives no evidence of meaningful differences in using Patlak or NLR methods to determine Ki as they could be interchanged with a conversion factor. Studies including mean SUV, Kipat, and KiNLR have found these parameters to have similar reproducibility with coefficients of variation ranging between 9% and 15%17–20 although KiNLR had lower reproducibility when k4 is not limited to 0 when fitting. In this study, SUV, Kipat, and KiNLR have comparable variance where intersubject SDs are between 43% and 46% of mean values. Despite similar reproducibility, Ki values have been reported to be a more sensitive measure of regional bone metabolism than SUV.17,18,27,42 In the limbs, where F− uptake is low, Brenner et al18 and Apostolova and Brenner42 and concluded the minimal change of SUV in a patient must be greater than 50% to reliably detect disease or treatment-related changes, whereas the same diagnosis could be made from a change in Ki of 25%. Ki values have also shown to be more sensitive when analyzing alterations in subchondral bone of the femur adjacent to cartilage defects.4 SUVmax values in this study are similar to previously reported mean SUVmax values of 2.44 for the tibia43 and 2.22 in the femur shaft.44 SUVmax has been found to correlate well with adjacent cartilage alterations,2,4 and although it had the largest intrasubject variation in this study, it had a relatively lower variance between subjects and greater differentiation between bone tissues (Fig. 4). In this study, using NLR was advantageous as obtaining K1 and extraction fraction parameters provided useful information that could not be extracted from Ki alone.
The K1 values obtained in this study were within a flow-dominant regimen where it has, theoretically, a linear correlation to blood flow (K1 < < PS). The flow values obtained in this study compare well with measured blood flow in the femoral shaft,45 but lack a criterion-standard measure to investigate K1 as a surrogate flow measure. To date, the most convincing studies to confirm the relationship between blood flow in bone tissue and K1 for [18F]NaF kinetics have been performed in swine vertebrae.15,21 Since then, authors have reported a poor correlation between K1 and bone perfusion in studies of the hip of human surgery patients22 and the forelimbs of healthy rats.46 Obtaining an estimate of flow would be of great clinical value. Bone perfusion is usually linked to metabolic activity and varies greatly between different bones and bone regions in the skeleton where the extremities are among the lowest.23,25,47 Perfusion studies using microspheres have shown a reduction of blood flow in bones related to age,47 osteoporosis,48 and reduced endothelium-dependent vasodilation.49
With regard to this study's aim to report key parametric values for [18F]NaF uptake in the healthy knee, there are several limitations to be considered when interpreting the results. First, the number of subjects is small where results can be skewed by relatively few abnormalities. The range of ages (22–44 years) is a period of rather stable bone density in human adults, but factors such as body mass index, varus/valgus alignment, disease, or activity level could alter the kinetics in bone tissue. Second, despite the numerous advantages from combining PET imaging with MRI in knee examinations, there are disadvantages in foregoing the superior information on bone density, which CT provides. This information is valuable in both the attenuation correction of PET data and the segmentation of bone tissue. Dixon-based methods, as used by the scanner in this study, have been shown to underestimate bone [18F]NaF mean SUV by 10%,50 ranging between 0% and 20% depending on location. The subchondral bone would be least affected being close to the bone surface, whereas the trabecular bone could have a more pronounced underestimation of SUV due to improper attenuation correction. Likewise, a similar underestimation of K1 and Ki would be expected, although it would be partially offset by a similar underestimation of activity in input function obtained from the popliteal artery. Lastly, the use of an IDIF would best be confirmed by using arterial sampling as a criterion standard. In this study, venous samples confirmed the activity of the later phase of the IDIF but not the earlier phase of high activity.
PET/MRI is an optimal dual-imaging combination offering the advantages of the high soft tissue contrast and resolution of MRI and the sensitivity of PET. In this study, MR angiography added the advantage of segmenting the popliteal artery, making an automated process to obtain the IDIF possible. The input functions obtained correspond well with literature values for [18F]NaF from arterial sampling,37 and visual inspection of generated ROIs confirmed successful automated segmentation of the popliteal artery. Mean IDIF values 50 minutes after injection were 6% higher than venous blood samples taken on an equilibrium time point, whereas Cook et al25 found arterial blood samples to be 2% higher than venous blood samples after 24 minutes. With the increased use of NaF in nononcological studies of the skeleton, it has become even more relevant as moderate differences in NaF uptake may be an early indication of bone degradation in diseases such as osteoarthritis.5 The combination of PET/MRI reduces the radiation dose significantly in 2 ways. First by eliminating CT and, second, because the PET data are acquired for the duration of the MRI protocol (which can be up to an hour), the injected dose of 18F-fluoride can be decreased from a standard clinical dose of 200 MBq to 90 MBq (used in this study) and still retain the same signal-to-noise ratio in PET SUV maps. The effective dose of this study is estimated to be 2.16 mSv.26 Quantitative MRI techniques have been widely studied to develop robust biomarkers for the early detection and monitoring of osteoarthritis5,51 and monitoring of patients having had an anterior cruciate ligament injury.32
This study showed significant variations in regional bone perfusion and metabolism between skeletal tissue types in the knee joint. We have shown the feasibility of using PET/MR to create an accurate IDIF from the popliteal artery and to conduct a quantitative and semiquantitative evaluation of bone metabolism in the knee at a low radiation dosage. [18F]NaF PET/MRI is a noninvasive technique that offers an attractive tool to simultaneously estimate bone perfusion and metabolism at clinically relevant sites of the knee.
The authors thank Dr Mehdi Khalighi and Jorge Guzman for help with development of techniques for hybrid PET/MRI. They also thank Dawn Holley and Harsh Gandhi for help running PET/MRI scans.
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Keywords:Copyright © 2019 Wolters Kluwer Health, Inc. All rights reserved.
bone; fluoride; hybrid imaging; kinetics; knee; MRI; NaF; PET; PET/MRI