Evidence map›Paper›PMID 42050595›Full record

ArticleCancer imaging : the official publication of the International Cancer Imaging Society2026

Parametric mapping of dynamic

Anna-Maria Spektor, Isabelle von Goetze, Hans-Georg Buchholz, Ulrike Heger, Matthias Lang, Jakob Liermann, Maximilian Knoll, Klaus Herfarth, Mathias Schreckenberger, Jürgen Debus and 2 more

Abstract read
In one paragraph

Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Anna-Maria Spektor *Department of Nuclear Medicine, University Medical Center Mainz, Langenbeckstraße 1, 55131, Mainz, Germany.ORCID http://orcid.org/0009-0005-1092-5773
Isabelle von GoetzeDepartment of Nuclear Medicine, University Medical Center Mainz, Langenbeckstraße 1, 55131, Mainz, Germany.
Hans-Georg BuchholzDepartment of Nuclear Medicine, University Medical Center Mainz, Langenbeckstraße 1, 55131, Mainz, Germany.
Ulrike HegerDepartment of Surgery, University Hospital Heidelberg, Heidelberg, Germany.
Matthias LangDepartment of Surgery, University Hospital Heidelberg, Heidelberg, Germany.
Jakob LiermannDepartment of Radiation Oncology, University Hospital Heidelberg, Heidelberg, Germany.
Maximilian KnollDepartment of Radiation Oncology, University Hospital Heidelberg, Heidelberg, Germany.
Klaus HerfarthDepartment of Radiation Oncology, University Hospital Heidelberg, Heidelberg, Germany.
Mathias SchreckenbergerDepartment of Nuclear Medicine, University Medical Center Mainz, Langenbeckstraße 1, 55131, Mainz, Germany.
Jürgen DebusDepartment of Radiation Oncology, University Hospital Heidelberg, Heidelberg, Germany.
Uwe HaberkornDepartment of Nuclear Medicine, University Hospital Heidelberg, Heidelberg, Germany.
Manuel RöhrichDepartment of Nuclear Medicine, University Medical Center Mainz, Langenbeckstraße 1, 55131, Mainz, Germany. manuel.roehrich@unimedizin-mainz.de.ORCID http://orcid.org/0000-0001-7609-243X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeDifferential 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.

methods55 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.

results42 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.

conclusionDifferentiating 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.

Indexed as

Carcinoma, Pancreatic DuctalGallium RadioisotopesPancreatic NeoplasmsPositron Emission Tomography Computed TomographyAdultAgedAged, 80 and overDiagnosis, DifferentialFemaleFibroblast Activation Protein AlphaHumansMaleMiddle AgedQuinolinesRadiopharmaceuticals68Ga-FAPIFibroblast Activation Protein AlphaGallium RadioisotopesQuinolinesRadiopharmaceuticalsCancerFAPIFibroblast activation proteinPDACPET

Identifiers

PMID42050595
PMCPMC13127050

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.