SPECT image segmentation for estimation of tumour volume and activity concentration in 177Lu-DOTATATE radionuclide therapy

Background: Dosimetry in radionuclide therapy has the potential to allow for a treatment tailored to the individual patient. One therapeutic radiopharmaceutical where patient-specific dosimetry is feasible is Lu-177-DOTATATE, used for the treatment of neuroendocrine tumours. The emission of gamma photons by Lu-177 allows for imaging with SPECT (single photon emission computed tomography). One important step for dosimetry using this imaging technique is the SPECT image segmentation, which needs to be robust and accurate for the estimated quantities to be reliable. This work investigates different methods for automatic tumour delineation in Lu-177-DOTATATE SPECT images. Three segmentation methods are considered: a fixed 42% threshold (FT), the Otsu method (OM) and a method based on Fourier surfaces (FS). Effects of including resolution compensation in the iterative SPECT image reconstruction are also studied. Evaluation is performed based on Monte Carlo-simulated SPECT images from 24 h and 336 h post injection (p.i.), for determination of the volume, activity concentration and dice similarity coefficient. In addition, patient data are used to investigate the correspondence of tumour volumes when delineated in SPECT or morphological CT or MR images. Patient data are also used to examine the sensitivity to the operator-dependent initialization. Results: For simulated images from 24 h p.i. reconstructed without resolution compensation, a volume and activity-concentration root-mean-square error below 15% is typically obtained for tumours above approximately 10 cm(3) when using OM or FS, while FT performs considerably worse. When including resolution compensation, the tumour volume becomes underestimated and the activity concentration overestimated. The FS method appears to be robust to noise, as seen for the 336 h images. The differences between the tumour volumes estimated from the SPECT images and the volumes estimated from morphological images are generally larger than the discrepancies seen for the simulated data sets. Conclusions: Segmentation results are encouraging for future dosimetry of tumours with volumes above approximately 10 cm(3). Using resolution compensation in the reconstruction may have a negative effect on volume estimation.