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 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 Ga-DOTATOC PET and evaluate SUV-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 and Vol) were computed from manual segmentations by five experienced nuclear physicians. SUV-related indexes were extracted from Vol and the semi-automated PET volumes providing the best Dice index with Vol (Vol) 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, hypophysis SUV, and meninges SUV) with optimal threshold optimized. Tumor-absorbed doses were obtained from the Vol, corrected for partial volume effect, performed on a 360° whole-body CZT-camera at 24, 96, and 168 h after administration of Lu-DOTATATE.

RESULTS

Vol was obtained from 1.7-fold meninges SUV (Dice index 0.85 ± 0.07). SUV and total lesion uptake (SUVxlesion volume) showed better correlations with tumor-absorbed doses than SUV when determined with the Vol (respective Pearson correlation coefficients of 0.78, 0.67, and 0.56) or Vol (0.64, 0.66, and 0.56).

CONCLUSION

Accurate definition of pretherapeutic PET volumes is justified since SUV-derived values provide the best tumor-absorbed dose predictions in refractory meningioma patients treated by Lu-DOTATATE. This study provides a semi-automated segmentation method of pretherapeutic Ga-DOTATOC PET volumes to achieve good reproducibility between physicians.

CLINICAL RELEVANCE STATEMENT

SUV-derived values from pretherapeutic Ga-DOTATOC PET are predictive of tumor-absorbed doses in refractory meningiomas treated by Lu-DOTATATE, justifying to accurately define pretherapeutic PET volumes. This study provides a semi-automated segmentation of Ga-DOTATOC PET images easily applicable in routine.

KEY POINTS

• SUV-derived values from pretherapeutic Ga-DOTATOC PET images provide the best predictive factors of tumor-absorbed doses related to Lu-DOTATATE PRRT in refractory meningioma. • A 1.7-fold meninges SUV segmentation method used to determine metabolic tumor volume on pretherapeutic Ga-DOTATOC PET images of refractory meningioma treated by 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.