Predicting [177Lu]Lu‐DOTA‐TATE dosimetry by using pre‐therapy [68Ga]Ga‐DOTA‐TATE PET/CT and biomarkers in patient with neuroendocrine tumors

DOI: 10.1002/mp.17852 Publication Date: 2025-04-24T02:05:28Z
ABSTRACT
AbstractBackgroundLutetium‐177 DOTA‐TATE peptide receptor radionuclide therapy (PRRT) is an established and effective treatment modality for patients with metastatic neuroendocrine tumors (NETs).PurposeThis study aims to predict patient‐absorbed doses from [177Lu]Lu‐DOTA‐TATE PRRT in the liver, kidney and lesion by utilizing patient‐specific absorbed doses from pre‐therapeutic [68Ga]Ga‐DOTA‐TATE PET/CT.MethodsBefore the treatment of cycle 1, 11 patients with NETs underwent PET/CT scans at 0.5, 1.0, 2.0 and 4.0 h after the injection of [68Ga]Ga‐DOTA‐TATE. Patients then received [177Lu]Lu‐DOTA‐TATE PRRT and underwent SPECT/CT scans at 4, 24, 96, and 168 h post‐administration. The segmentations and dosimetry were performed by using a professional software. The linear regression model used the absorbed doses from [68Ga]Ga‐DOTA‐TATE alone as the predictor variable. The multiple linear regression model used the absorbed doses from [68Ga]Ga‐DOTA‐TATE and the relevant clinical biomarkers as the predictor variables.ResultsThe mean absorbed doses from [177Lu]Lu‐DOTA‐TATE PRRT in kidney and liver were 4.1 and 2.1 Gy, respectively. In comparison, the mean absorbed doses from [68Ga]Ga‐DOTA‐TATE were significantly lower: 18.0 mGy and 11.0 mGy, respectively. For lesions, the maximum absorbed dose from [68Ga]Ga‐DOTA‐TATE ranged from 24.1 to 170.4 mGy, while the maximum absorbed dose from [177Lu]Lu‐DOTA‐TATE PRRT was significantly higher, ranging from 9.6 to 77.9 Gy. The linear regression model yielded moderate R‐squared values of 0.50, 0.59, and 0.36 for kidney, liver and lesion, respectively. The performance of multiple linear regression model was better, with R‐squared values increasing to 0.81, 0.77, and 0.84.ConclusionAbsorbed doses from [177Lu]Lu‐DOTA‐TATE PRRT can be accurately predicted. Moreover, our models are formalized into simple equations.
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