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. 2025 Jul 1;25(1):81.
doi: 10.1186/s40644-025-00899-5.

Imaging-derived biomarkers from 68Ga-DOTATOC PET/CT scans to predict survival of patients with neuroendocrine tumors after PRRT with 177Lu-DOTATATE

Stephan Raad  1 , Ali Al-Fatlawi  2   3 , C Louise Wise  4 , Christian Fottner  5 , Simin Schadmand-Fischer  6 , Mathias Schreckenberger  4 , Matthias M Weber  5 , Thomas J Musholt  7 , Michael Schroeder  2   8 , Matthias Miederer  9
Affiliations

Imaging-derived biomarkers from 68Ga-DOTATOC PET/CT scans to predict survival of patients with neuroendocrine tumors after PRRT with 177Lu-DOTATATE

Stephan Raad et al. Cancer Imaging. .

Abstract

Background: Neuroendocrine tumors have increased in prevalence and diversity in recent years and are often diagnosed at metastatic stages. Compared with nonradioactive systemic treatment with somatostatin analogs, peptide receptor radionuclide therapy (PRRT) has shown superior overall survival benefits for well-differentiated neuroendocrine tumor patients. This study aimed to identify biomarkers from 68Ga‒DOTATOC PET/CT scans to predict survival in patients treated with PRRT in the clinic.

Methodology: This retrospective study analyzed 68Ga-DOTATOC PET/CT data from 67 NET patients undergoing PRRT. Tumor volumes and SUV metrics were segmented using standardized protocols. Radiomics features from liver metastases were extracted and preprocessed for analysis. Data were analysed via Kaplan-Meier, Cox regression, and PCA to evaluate the prognostic value of volumetric-, radiomics-, and clinicopathological parameters.

Results: This study included scans from 67 patients with an average age of 67 years. The mean survival time was 46.5 months, with 43% of patients alive or lost to follow-up at the conclusion of data collection. Despite comprehensive analyses, neither volumetric parameters, including total tumor volume and organ-specific tumor volume, nor SUV values (SUVmax and SUVmean) were robust predictors of overall survival. K‒M and Cox regression analyses revealed no significant differences in survival between the high- and low-risk groups for these parameters. Furthermore, radiomics features extracted from liver metastases did not demonstrate significant prognostic value.

Conclusion: Quantification of 68Ga-DOTATOC PET/CT-derived parameters offers limited prognostic value for OS in NET patients who are receiving PRRT in clinical practice. These findings might emphasize the current robust integration of imaging in clinical decision-making for NET management.

Keywords: 68Ga-DOTATOC PET/CT; Neuroendocrine tumors; Overall survival; PRRT; Radiomics; SUV; Tumor volume.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: This retrospective analysis was performed in accordance with the requirements of the competent ethics committee (Landesärztekammer Rheinland-Pfalz). Informed consent to obtain and analyze patient data was given within a German registry study approved by the local ethical committee. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
The course of the study
Fig. 2
Fig. 2
Kaplan‒Meier survival analysis showing high TV and low TV curves
Fig. 3
Fig. 3
Kaplan‒Meier survival analysis showing high-LV and low-LV curves
Fig. 4
Fig. 4
KDE plot for LVs according to the three survival groups above
Fig. 5
Fig. 5
KDE plot for AV according to the three survival groups above
Fig. 6
Fig. 6
Kaplan‒Meier survival analysis showing the high-SUVmax and low-SUVmax curves
Fig. 7
Fig. 7
KDE plot for the SUVmax according to the three survival groups above
Fig. 8
Fig. 8
KDE plot for the SUVmean according to the three survival groups above
Fig. 9
Fig. 9
Kaplan‒Meier survival analysis showing high SALGE and low SALGE curves
Fig. 10
Fig. 10
KDE plot for SALGE according to the three survival groups above
Fig. 11
Fig. 11
KDE plot for DNUNs according to the three survival groups above
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Fig. 12
PCA and representation of PC29 and PC43 according to the three survival groups
Fig. 13
Fig. 13
Kaplan‒Meier curves showing the survival differences between patients with different numbers of affected organs
See this image and copyright information in PMC

References

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