Fully automated AI-based quantification of tumour volume on PSMA PET-CT images is associated with overall survival in prostate cancer.
7 affiliations
- 1Department of Translational Medicine, Lund University, Malmö, Sweden.
- 2Department of Clinical Physiology and Nuclear Medicine, Skåne University Hospital, Malmö, Sweden.
- 3Department of Urology, Skåne University Hospital, Malmö, Sweden.
- 4Chalmers University of Technology, Gothenburg, Sweden.
- 5Eigenvision AB, Lund, Sweden.
- 6Department of Radiation Physics, Skåne University Hospital, Malmö, Sweden.
- 7Department of Molecular and Clinical Medicine, Gothenburg University, Gothenburg, Sweden.
Abstract
Introduction
Artificial intelligence (AI)-based models can quantify tumour volume in positron emission tomography (PET) examinations using prostate specific membrane antigen (PSMA). It is, however, unknown whether this measurement of tumour volume contains prognostic information. The purpose of this study was to examine whether tumour volume measured by AI is associated with overall survival in patients with prostate cancer.Methods
Patients who had undergone [¹⁸F]PSMA-1007 PET-CT due to primary staging or biochemical recurrence (BCR) of prostate cancer at our centre were retrospectively included and followed for 5 years. Automatic quantification of tumour volume was performed using a previously developed fully automated AI model from our research group for PSMA PET-CT analysis, without manual corrections. The tumour volume for the prostate, lymph nodes, and bone was calculated and summarized as Total Lesion Volume (TLV) and divided categorically (no detectable tumour, low, and high) as well as aggregated to whole-body TLV and divided into tertiles (low, intermediate, and high). Mortality rates were compared using Cox-regression and adjusted for age.Results
Among 267 patients in the final analysis, 48 (18%) died during follow-up. Whole-body TLV was significantly associated with mortality in the combined cohort (p = 0.001) and in the primary staging cohort (p = 0.014) but did not reach statistical significance in the BCR cohort (p = 0.061).Conclusions
Fully automated AI-derived TLV from PSMA PET-CT was associated with overall survival. These findings support the potential role of AI-based tumour quantification as a potential prognostic biomarker in prostate cancer.
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BibTeX
@article{wittgren2026fully,
title = {{Fully automated AI-based quantification of tumour volume on PSMA PET-CT images is associated with overall survival in prostate cancer.}},
author = {Johan Wittgren and Jacob Ingvar and Olof Enqvist and Måns Larsson and David Minarik and Lars Edenbrandt and Anders Bjartell and Elin Trägårdh},
journal = {Clinical physiology and functional imaging},
year = {2026},
month = nov,
doi = {10.1111/cpf.70104},
url = {https://europepmc.org/article/MED/42973055},
note = {CC BY},
}
RIS
TY - JOUR
TI - Fully automated AI-based quantification of tumour volume on PSMA PET-CT images is associated with overall survival in prostate cancer.
AU - Johan Wittgren
AU - Jacob Ingvar
AU - Olof Enqvist
AU - Måns Larsson
AU - David Minarik
AU - Lars Edenbrandt
AU - Anders Bjartell
AU - Elin Trägårdh
PY - 2026
DA - 2026/11/01
JO - Clinical physiology and functional imaging
DO - 10.1111/cpf.70104
UR - https://europepmc.org/article/MED/42973055
AB - Introduction Artificial intelligence (AI)-based models can quantify tumour volume in positron emission tomography (PET) examinations using prostate specific membrane antigen (PSMA). It is, however, unknown whether this measurement of tumour volume contains prognostic information. The purpose of this study was to examine whether tumour volume measured by AI is associated with overall survival in patients with prostate cancer.Methods Patients who had undergone [¹⁸F]PSMA-1007 PET-CT due to primary staging or biochemical recurrence (BCR) of prostate cancer at our centre were retrospectively included and followed for 5 years. Automatic quantification of tumour volume was performed using a previously developed fully automated AI model from our research group for PSMA PET-CT analysis, without manual corrections. The tumour volume for the prostate, lymph nodes, and bone was calculated and summarized as Total Lesion Volume (TLV) and divided categorically (no detectable tumour, low, and high) as well as aggregated to whole-body TLV and divided into tertiles (low, intermediate, and high). Mortality rates were compared using Cox-regression and adjusted for age.Results Among 267 patients in the final analysis, 48 (18%) died during follow-up. Whole-body TLV was significantly associated with mortality in the combined cohort (p = 0.001) and in the primary staging cohort (p = 0.014) but did not reach statistical significance in the BCR cohort (p = 0.061).Conclusions Fully automated AI-derived TLV from PSMA PET-CT was associated with overall survival. These findings support the potential role of AI-based tumour quantification as a potential prognostic biomarker in prostate cancer.
SN - 1475-0961
SN - 1475-097X
ER -