Semi-automated segmentation methods of SSTR PET for dosimetry prediction in refractory meningioma patients treated by SSTR-targeted peptide receptor radionuclide therapy

Objectives Tumor dosimetry with somatostatin receptor–targeted peptide receptor radionuclide therapy (SSTR-targeted PRRT) by 177 Lu-DOTATATE may contribute to improved treatment monitoring of refractory meningioma. Accurate dosimetry requires reliable and reproducible pretherapeutic PET tumor segmentation which is not currently available. This study aims to propose semi-automated segmentation methods to determine metabolic tumor volume with pretherapeutic 68 Ga-DOTATOC PET and evaluate SUV mean -derived values as predictive factors for tumor-absorbed dose. Methods Thirty-nine meningioma lesions from twenty patients were analyzed. The ground truth PET and SPECT volumes (Vol GT-PET and Vol GT-SPECT ) were computed from manual segmentations by five experienced nuclear physicians. SUV-related indexes were extracted from Vol GT-PET and the semi-automated PET volumes providing the best Dice index with Vol GT-PET (Vol opt ) across several methods: SUV absolute-value (2.3)-threshold, adaptative methods (Jentzen, Otsu, Contrast-based method), advanced gradient-based technique, and multiple relative thresholds (% of tumor SUV max , hypophysis SUV mean , and meninges SUV peak ) with optimal threshold optimized. Tumor-absorbed doses were obtained from the Vol GT-SPECT , corrected for partial volume effect, performed on a 360° whole-body CZT-camera at 24, 96, and 168 h after administration of 177 Lu-DOTATATE. Results Vol opt was obtained from 1.7-fold meninges SUV peak (Dice index 0.85 ± 0.07). SUV mean and total lesion uptake (SUV mean xlesion volume) showed better correlations with tumor-absorbed doses than SUV max when determined with the Vol GT (respective Pearson correlation coefficients of 0.78, 0.67, and 0.56) or Vol opt (0.64, 0.66, and 0.56). Conclusion Accurate definition of pretherapeutic PET volumes is justified since SUV mean -derived values provide the best tumor-absorbed dose predictions in refractory meningioma patients treated by 177 Lu-DOTATATE. This study provides a semi-automated segmentation method of pretherapeutic 68 Ga-DOTATOC PET volumes to achieve good reproducibility between physicians. Clinical relevance statement SUV mean -derived values from pretherapeutic 68 Ga-DOTATOC PET are predictive of tumor-absorbed doses in refractory meningiomas treated by 177 Lu-DOTATATE, justifying to accurately define pretherapeutic PET volumes. This study provides a semi-automated segmentation of 68 Ga-DOTATOC PET images easily applicable in routine. Key points • SUV mean -derived values from pretherapeutic 68 Ga-DOTATOC PET images provide the best predictive factors of tumor-absorbed doses related to 177 Lu-DOTATATE PRRT in refractory meningioma. • A 1.7-fold meninges SUV peak segmentation method used to determine metabolic tumor volume on pretherapeutic 68 Ga-DOTATOC PET images of refractory meningioma treated by 177 Lu-DOTATATE is as efficient as the currently routine manual segmentation method and limits inter- and intra-observer variabilities. • This semi-automated method for segmentation of refractory meningioma is easily applicable to routine practice and transferrable across PET centers.