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Purpose <p>Differential diagnoses of primary pancreatic lesions include pancreatic ductal adenocarcinomas (PDAC) and inflammatory lesions of the pancreas (ILP). Post-pancreatic surgery, differentiation of postoperative reactive tissue (PRT) and PDAC-recurrence challenges oncological imaging. Static <sup>68</sup>Ga-FAPI-PET/CT uptake is increased in all of these lesions with marked overlap in signal intensity, hampering their FAPI-PET-based assessment. Here, we evaluated static and parametric imaging parameters for discrimination of pancreatic lesions in primary and post-pancreatic surgery scenarios.</p> Methods <p>55 Patients with pancreatic lesions (36 primary, 19 post-pancreatic surgery) underwent static and dynamic <sup>68</sup>Ga-FAPI-46-PET/CT. Primary lesions were classified either by histology following PET/CT or follow-up (&gt; 6 months). Post-surgery, PRT and PDAC-recurrence were classified by CT- and clinical course (&gt; 18 months). Parametric maps (1 tissue compartment (1TC), 2TC and Logan plot (LP)) from dynamic PET-data were generated via image-based aortic input function using PMOD-software. Pancreatic lesions (PDAC, ILP, PRT, PDAC-recurrence) were then delineated using VOI-technique (30–70% isocontour) and signal intensities were analyzed. SPSS was used to detect outliers, unpaired t-tests was applied for comparison of static and parametric imaging parameters. Receiver-operating-characteristic curves for differentiating PDAC/ILP or recurrent PDAC/PRT were generated.</p> Results <p>42 patients were included in the final analysis: in primary setting, 16 PDAC and 10 ILP; in post-surgery setting 9 PDAC-recurrences and 7 PRT. In the primary setting, although PDAC showed higher SUVmax/mean than ILP, no significant differences in maximum/mean signal values neither in static imaging nor in parametric maps were detected. With regard to the differentiation of PDAC-recurrences versus postoperative tissue, LPmax were significantly higher in PDAC-recurrences compared to PRT (4.74 vs. 2.40, p-value 0.020) with AUC 82.5% (95-CI 0.62-1.0) and a possible diagnostic threshold at &gt; 3,49 (LR + 5.44), while differences in static imaging or other parametric maps were not statistically significant.</p> Conclusion <p>Differentiating pancreatic lesions remains challenging. While LPmax significantly distinguished PDAC-recurrence from PRT, other parametric mapping parameters yielded no significant results. Larger studies and additional dynamic data analysis methods should be explored.</p>

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Parametric mapping of dynamic 68Ga FAPI-46-PET data of 42 patients with pancreatic lesions

  • 期刊论文

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  • 发表日期：

    2026年4月28日

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  • Anna-Maria Spektor,
  • Isabelle von Goetze,
  • Hans-Georg Buchholz,
  • Ulrike Heger,
  • Matthias Lang,
  • Jakob Liermann,
  • Maximilian Knoll,
  • Klaus Herfarth,
  • Mathias Schreckenberger,
  • Jürgen Debus,
  • Uwe Haberkorn,
  • Manuel Röhrich

摘要

Purpose

Differential diagnoses of primary pancreatic lesions include pancreatic ductal adenocarcinomas (PDAC) and inflammatory lesions of the pancreas (ILP). Post-pancreatic surgery, differentiation of postoperative reactive tissue (PRT) and PDAC-recurrence challenges oncological imaging. Static 68Ga-FAPI-PET/CT uptake is increased in all of these lesions with marked overlap in signal intensity, hampering their FAPI-PET-based assessment. Here, we evaluated static and parametric imaging parameters for discrimination of pancreatic lesions in primary and post-pancreatic surgery scenarios.

Methods

55 Patients with pancreatic lesions (36 primary, 19 post-pancreatic surgery) underwent static and dynamic 68Ga-FAPI-46-PET/CT. Primary lesions were classified either by histology following PET/CT or follow-up (> 6 months). Post-surgery, PRT and PDAC-recurrence were classified by CT- and clinical course (> 18 months). Parametric maps (1 tissue compartment (1TC), 2TC and Logan plot (LP)) from dynamic PET-data were generated via image-based aortic input function using PMOD-software. Pancreatic lesions (PDAC, ILP, PRT, PDAC-recurrence) were then delineated using VOI-technique (30–70% isocontour) and signal intensities were analyzed. SPSS was used to detect outliers, unpaired t-tests was applied for comparison of static and parametric imaging parameters. Receiver-operating-characteristic curves for differentiating PDAC/ILP or recurrent PDAC/PRT were generated.

Results

42 patients were included in the final analysis: in primary setting, 16 PDAC and 10 ILP; in post-surgery setting 9 PDAC-recurrences and 7 PRT. In the primary setting, although PDAC showed higher SUVmax/mean than ILP, no significant differences in maximum/mean signal values neither in static imaging nor in parametric maps were detected. With regard to the differentiation of PDAC-recurrences versus postoperative tissue, LPmax were significantly higher in PDAC-recurrences compared to PRT (4.74 vs. 2.40, p-value 0.020) with AUC 82.5% (95-CI 0.62-1.0) and a possible diagnostic threshold at > 3,49 (LR + 5.44), while differences in static imaging or other parametric maps were not statistically significant.

Conclusion

Differentiating pancreatic lesions remains challenging. While LPmax significantly distinguished PDAC-recurrence from PRT, other parametric mapping parameters yielded no significant results. Larger studies and additional dynamic data analysis methods should be explored.