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Automated analysis of PSMA-PET/CT studies using convolutional neural networks

Edenbrandt, L.; Borrelli, P.; Ulen, J.; Enqvist, O.; Tragardh, E.

2021-03-05 radiology and imaging
10.1101/2021.03.03.21252818 medRxiv
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PurposeProstate-specific membrane antigen (PSMA) PET/CT has shown to be more sensitive and accurate than conventional imaging. Visual interpretation of the images causes both intra- and inter-reader disagreement and there is therefore a need for objective methods to analyze the images. The aim of this study was to develop an artificial intelligence (AI) tool for PSMA PET/CT and to evaluate the influence of the tool on inter-reader variability. ApproachWe have recently trained AI tools to automatically segment organs, detect tumors, and quantify volume and tracer uptake of tumors in PET/CT. The primary prostate gland tumor, bone metastases, and lymph nodes were analyzed in patients with prostate cancer. These studies were based on non-PSMA targeting PET tracers. In this study an AI tool for PSMA PET/CT was developed based on our previous AI tools. Letting three physicians analyze ten PSMA PET/CT studies first without support from the AI tool and at a second occasion with the support of the AI tool assessed the influence of the tool. A two-sided sign test was used to analyze the number of cases with increased and decreased variability with support of the AI tool. ResultsThe range between the physicians in prostate tumor total lesion uptake (TLU) decreased for all ten patients with AI support (p=0.002) and decreased in bone metastases TLU for nine patients and increased in one patient (p=0.01). Regarding the number of detected lymph nodes the physicians agreed in on average 72% of the lesions without AI support and this number decreased to 65% with AI support. ConclusionsPhysicians supported by an AI tool for automated analysis of PSMA-PET/CT studies showed significantly less inter-reader variability in the quantification of primary prostate tumors and bone metastases than when performing a completely manual analysis. A similar effect was not found for lymph node lesions. The tool may facilitate comparisons of studies from different centers, pooling data within multicenter trials and performing meta-analysis. We invite researchers to apply and evaluate our AI tool for their PSMA PET/CT studies. The AI tool is therefore available upon reasonable request for research purposes at www.recomia.org.

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