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| Home > Publications database > Are liver metastases from uveal melanoma a clinical indication for dynamic PET? A comparison of Patlak parametric imaging with standard and delayed static SUV imaging using long axial field-of-view PET/CT. |
| Home > Publications database > Are liver metastases from uveal melanoma a clinical indication for dynamic PET? A comparison of Patlak parametric imaging with standard and delayed static SUV imaging using long axial field-of-view PET/CT. |
| Journal Article | DKFZ-2026-01506 |
; ; ; ;
2026
Springer-Verl.
Heidelberg [u.a.]
Abstract: Despite decades of technical development, dynamic PET and parametric imaging have not yet achieved widespread clinical implementation in oncology, largely due to technical complexity and the limited number of clinical scenarios in which clear additional value over static imaging has been demonstrated. We hypothesized that liver metastases from uveal melanoma-a tumor entity often characterized by low tumor-to-background contrast on static imaging- may represent a particularly promising application for dynamic PET imaging. Accordingly, we aimed to determine whether dynamic Patlak parametric imaging improves lesion detectability and conspicuity compared with standard (50-60 min) and delayed (70-85 min) static standardized uptake value (SUV) imaging.Twenty-six patients with uveal melanoma and a total of 126 tumor lesions, including 58 liver metastases and 68 other metastases, were prospectively enrolled. All patients underwent a 60 min dynamic data acquisition (skull to upper thigh) followed by whole-body [18F]FDG PET/CT imaging at 70 min post-injection. Three image datasets were generated and compared: (1) Direct Patlak Ki parametric images derived from dynamic acquisition at 30-60 min post-injection, (2) standard static SUV images reconstructed from same dynamic acquisition at 50-60 min post-injection (standardSUV), and (3) delayed static SUV images acquired at 70-85 min post-injection (lateSUV). All three image sets were assessed qualitatively for lesion detectability and quantitative analysis was performed for all 126 lesions using tumor-to-background ratio (TBRmean) measurements.No significant differences were observed among the three imaging approaches with respect to the total number of detected tumor lesions. However, one discordant finding was noted: a true-positive liver metastasis was identified on Patlak Ki imaging and subsequently confirmed by MRI, but was not clearly visualized on static SUV images. Qualitatively, for liver and other metastases, Patlak Ki and lateSUV images showed significantly higher TBRmean values than standardSUV, with mean increases of ~ 2.1-2.3-fold for Ki and ~ 1.3-fold for lateSUV. Furthermore, Patlak Ki yielded significantly higher TBRmean than lateSUV (52/58 and 65/68) and standardSUV (57/58 and 67/68) for liver and other metastases, respectively.Although lesion detection rates were not significantly increased, dynamic acquisition with Patlak parametric imaging provided a robust and less timing-dependent method to enhance tumor-to-background contrast compared with static SUV imaging and may yield discordant findings with additional clinical value in selected cases. Overall, Patlak imaging may therefore represent a complementary contrast-optimization approach for evaluating liver metastases from uveal melanoma.
Keyword(s): Liver Metastases ; Long axial field-of-view PET/CT ; Patlak parametric imaging ; Uveal melanoma ; [18F]FDG PET/CT
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