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

Abstract

Tumor dosimetry with somatostatin receptor-targeted peptide receptor radionuclide therapy (SSTR-targeted PRRT) by ¹⁷⁷Lu-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 ⁶⁸Ga-DOTATOC PET and evaluate SUV_mean-derived values as predictive factors for tumor-absorbed dose. 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 ¹⁷⁷Lu-DOTATATE. Vol_opt was obtained from 1.7-fold meninges SUV_peak (Dice index 0.85 ± 0.07). SUV_mean and total lesion uptake (SUV_meanxlesion 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). 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 ¹⁷⁷Lu-DOTATATE. This study provides a semi-automated segmentation method of pretherapeutic ⁶⁸Ga-DOTATOC PET volumes to achieve good reproducibility between physicians. SUV_mean-derived values from pretherapeutic ⁶⁸Ga-DOTATOC PET are predictive of tumor-absorbed doses in refractory meningiomas treated by ¹⁷⁷Lu-DOTATATE, justifying to accurately define pretherapeutic PET volumes. This study provides a semi-automated segmentation of ⁶⁸Ga-DOTATOC PET images easily applicable in routine. • SUV_mean-derived values from pretherapeutic ⁶⁸Ga-DOTATOC PET images provide the best predictive factors of tumor-absorbed doses related to ¹⁷⁷Lu-DOTATATE PRRT in refractory meningioma. • A 1.7-fold meninges SUV_peak segmentation method used to determine metabolic tumor volume on pretherapeutic ⁶⁸Ga-DOTATOC PET images of refractory meningioma treated by ¹⁷⁷Lu-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.