3.1. Outline of Validation Steps
In our view, validating Patlak-P as a surrogate for Patlak Ki in radiotherapy planning required two major comparisons of tumors and other regions of elevated uptake derived from Patlak Ki, SUV∞, and SUV maps, target-to-background (TB) ratios and qualitative assessments of image quality. TB ratios were calculated from manual segmentations of the target region and a nearby background region that presented the largest challenge to target visualization. In this way, TB ratios quantitatively reflected the ability of each technique to delineate the target from all nearby structures. The metrics for qualitative assessment were visual contrast, delineation of target boundary, and presence/absence of well-known structural detail such as tooth “holes” and the cerebellum.
In an effort to maintain analytical cohesion, we decided to combine select quantitative and qualitative findings for each patient and present them in their own subsections. A final subsection was used to summarize general trends.
Tumor volumes derived from the three methods were not directly compared, because (a) there is no general consensus for which segmentation algorithm to use [27
]; (b) dose maps drawn by radiation oncologists or nuclear medicine physicians are considered the gold standard [28
]. Thus, the validation steps of the present work focused on image quality and contrast as it is reasoned that these factors primarily influence which regions are included in tumor volumes by therapy-planning physicians.
3.2. TB Ratios Methodology
As stated previously, the purpose of TB ratios was to compare how each technique is able to delineate tumors or other regions of elevated uptake from the background and adjacent structures. A representative example of how target and background definitions were defined is illustrated in .
Representative example of target (1) and background definition (2) on SUV image from FLT-PET. The typical background (3) is less indicative of the difficulty associated with delineating the target.
3.3. Patient 1 Comparisons
Both FDG and FLT acquisitions of Patient 1 show a region with elevated uptake (REU) near the base of the mouth ().
REU near base of the mouth as calculated by Patlak (left), Patlak-P (center), and SUV (right). Top row is FLT-PET, and the bottom row is FDG-PET.
Inspection of shows that FLT images derived from Patlak-P and Patlak have higher contrast than SUV and in general appear to be of higher quality because their backgrounds are diminished. These findings are quantitatively confirmed through TB ratios: Patlak-P (3.45), Patlak (3.77), and SUV (2.98). In addition, the REU appears to be slightly smaller in Patlak and Patlak-P images. Images generated from the FDG-PET scans are similar to their FLT counterparts, but the contrast differences are slightly less pronounced: Patlak-P (2.736), Patlak (2.481), and SUV (2.270). In this case, however, the Patlak-P parametric map has slightly higher contrast than Patlak.
An overall analysis of image quality showed that parametric maps generated by the three methods follow the prior examples. For both FDG and FLT studies of this patient, Patlak and Patlak-P generated parametric maps with higher contrast and visual quality than SUV. Furthermore, this increased contrast led to sharper boundaries between regions of high uptake and their surrounding areas in Patlak and Patlak-P images, as evidenced in how well each technique resolved the teeth and bony structures (arrows) in FLT-PET (Figures –) and the cerebellum in FDG-PET (Figures –). In particular, Patlak-P predicts more uniform uptake in the cerebellum, when compared with Patlak and SUV. Such a result may have implications for neurometabolism studies (see Discussion Section).
Transaxial slices of FLT-PET (a–c) and FDG-PET (d–f) that show difference in quality of visualizing well-known structures (teeth, cerebellum) for each technique: Patlak (left), Patlak-P (center), and SUV (right).
3.4. Patient 2 Comparisons
An REU was seen in both FDG and FLT images of Patient 2 near the upper row of teeth ().
Region of high uptake near top row of teeth as calculated by Patlak (left), Patlak-P (center), and SUV (right). Top row is FLT-PET, and the bottom row is FDG-PET. Arrows indicate background ROI.
Inspection of shows that Patlak-P FLT images have higher contrast than either Patlak or SUV, which is mirrored by TB ratios of the REU: Patlak-P (5.64), Patlak (4.37), and SUV (3.71). Patlak-P's high TB ratio is explained by increased diffusivity of the REU in Patlak and SUV images and increased background reduction in the Patlak-P image. In this study, however, the increase of image contrast is paired with a slight decrease in image quality.
The same behavior is observed in the FDG images, except in this case, the Patlak image has higher contrast and lesser quality than the Patlak-P image, though both are superior to SUV in both respects. The TB ratios do not mirror the relative performance of SUV: 1.92 (Patlak-P), 2.661 (Patlak), and 1.95 (SUV). It is more than likely that the TB ratio for SUV is improperly elevated, because the background ROI (indicated by arrows in ) appears to be improperly diffuse in the SUV image. In fact, it is much more difficult to visually separate the REU from the background region in the SUV image. Furthermore, from an overall visual perspective, the Patlak-P image appears to be higher quality than the Patlak and SUV images. This perspective is particularly in the soft tissue surrounding the REU and the cerebellum.
3.5. Patient 3 Comparisons
A tumor was found on the tongue of Patient 3 and could be visualized in Patient 3's FLT and FDG images. illustrates the caudal-most two slices in which the tumor is present in the FLT image, and illustrates the caudal-most two slices in which the tumor is present in the FDG image.
Figure 5 Caudal-most two slices of tumor as calculated by Patlak (left), Patlak-P (center), and SUV (right) from FLT-PET study of Patient 3. In the top row, dashed arrows indicate the tumor nodule, and solid arrows indicate the small REU. In the bottom row, arrows (more ...)
Figure 6 Caudal-most two slices of tumor (a–f) and cerebellar slice (g–i) as calculated by Patlak (left), Patlak-P (center), and SUV (right) from FDG-PET of Patient 3. Solid arrows indicate background ROI (d–f) and cerebellar region of (more ...)
The results shown in are similar to those seen in the FLT-PET study of Patient 2; Patlak-P's contrast is higher than Patlak or SUV and appears slightly noisier. This heightened contrast results in better distinction of the tumor's caudal-most extent from the adjacent soft tissue. In addition, the enhanced contrast provided by Patlak-P improves the visualization of a small REU that is clearly present in both the Patlak and Patlak-P images but only subtly so in the SUV image.
The examination of both slices shows that tumor boundaries are made sharper but also appear slightly noisier (due to background reduction) by applying Patlak-P, as evidenced by TB ratios: 2.04 (Patlak-P), 1.43 (Patlak), and 1.36 (SUV) for the tumor nodule and 4.639 (Patlak-P), 2.912 (Patlak), and 2.77 (SUV) for the tumor cross-section (second row of ). This observation also holds for anatomic structures in the vicinity of the tumor cross-section. However, this effect was less obvious for the prominent bony structures in the second row of (arrows), where Patlak-P provided better resolution without a similar increase in apparent noise.
Visual analysis of indicates that Patlak and Patlak-P possess higher contrast and image quality than SUV for the tumor and the cerebellum. These visual findings do not reflect calculated TB ratios, which do not vary significantly between techniques: 1.71 (Patlak-P), 1.59 (Patlak), and 1.69 (SUV). TBSUV, however, is artificially inflated because, as before, the background region in the SUV image (arrow in ) is not well resolved. Similarly, SUV depicts the tumor with blurrier boundaries and does not delineate the teeth structure as well. Furthermore, cerebellar details (arrow in ) seen in Patlak and Patlak-P images are missing and/or blurred in the SUV image, adding further evidence that Patlak-P could have an impact in neurometabolism studies.
3.6. Overall Comparison
In the previous subsections, we performed qualitative and quantitative analyses of the most interesting features in each patient's FDG and FLT images. However, it is also important to provide an overall picture of how well each technique performs in terms of contrast and image quality.
was compiled from TB ratios calculated from the REUs using each technique. Paired, two-tailed Student t-tests showed that (a) TB ratios calculated by Patlak-P and Patlak were statistically similar (P = 0.125); (b) TB ratios calculated by Patlak and SUV were not statistically similar (P = 0.004); (c) TB ratios calculated by Patlak-P and SUV were not statistically similar (P = 0.002).
TB ratios for all REUs analyzed. Headings under the study column reflect the patient's number and tracer type.
In general, visual contrast observed in Patlak-P and Patlak images were higher than SUV images. There was one instance where the Patlak image possessed significantly higher contrast than the Patlak-P image (2-FDG), and two instances where the Patlak-P image possessed significantly higher contrast than the Patlak image (2-FLT and 3-FLT). In all of these cases, images with significantly enhanced contrast appeared slightly noisier.
Across all studies, SUV images possessed blurrier boundaries than their Patlak and Patlak-P counterparts, which impacted delineation of teeth, bony structures, the cerebellum, and REU/tumor boundaries. This effect was often emphasized around small structures (Figures – and ), which appeared to be more resolved in Patlak and Patlak-P images.