BackgroundRecently, 177Lu-dotatate therapy for neuroendocrine tumours has received regulatory approval. Dosimetry can be used to optimize treatment on an individual basis, but there is no international consensus as to how it should be done.The aim of this study is to determine a feasible and accurate dosimetry method to guide individualized peptide receptor radionuclide therapy (PRRT) for patients with neuroendocrine tumours.As part of a clinical trial on 177Lu-dotatate therapy, renal dosimetry was performed for all patients in each treatment cycle, using a hybrid planar-SPECT/CT method. In the present study, we use the image data acquired from 22 patients and 119 cycles and define a set of alternative treatment planning strategies, each representing a simplification in terms of image acquisition and dosimetric calculations. The results from the simplified strategies are compared to the results from the protocol-prescribed hybrid planar-SPECT/CT-based method by analysing differences both in per-cycle and total cumulative absorbed dose (AD) analyses.ResultsIn general, the SPECT-based methods gave results that were largely consistent with the protocol-specified hybrid method, both in the per-cycle and cumulative AD analyses. Notably, performing one SPECT/CT per cycle at 96 h yielded ADs that were very similar to the protocol method. The methods using planar dosimetry resulted in larger variations, as expected, while giving 4 cycles to all patients resulted in the largest inter-individual differences in cumulative AD.ConclusionsPerforming one SPECT/CT at 96 h in every treatment cycle gives sufficiently reliable dosimetric results to base individualized treatment planning on, with a reasonable demand on resources.Electronic supplementary materialThe online version of this article (10.1186/s40658-018-0210-2) contains supplementary material, which is available to authorized users.

Patient-specific image-based dosimetry is considered to be a useful tool to limit toxicity associated with peptide receptor radionuclide therapy (PRRT). To facilitate the establishment and reliability of absorbed-dose response relationships, it is essential to assess the accuracy of dosimetry in clinically realistic scenarios. To this end, we developed pharmacokinetic digital phantoms corresponding to patients treated with 177 Lu-DOTATATE. Three individual voxel phantoms from the XCAT population were generated and assigned a dynamic activity distribution based on a compartment model for 177 Lu-DOTATATE, designed specifically for this purpose. The compartment model was fitted to time-activity data from 10 patients, primarily acquired using quantitative scintillation camera imaging. S values for all phantom source-target combinations were calculated based on Monte-Carlo simulations. Combining the S values and time-activity curves, reference values of the absorbed dose to the phantom kidneys, liver, spleen, tumours and whole-body were calculated. The phantoms were used in a virtual dosimetry study, using Monte-Carlo simulated gamma-camera images and conventional methods for absorbed-dose calculations. The characteristics of the SPECT and WB planar images were found to well represent those of real patient images, capturing the difficulties present in image-based dosimetry. The phantoms are expected to be useful for further studies and optimisation of clinical dosimetry in 177 Lu PRRT.

A computer model of a patient-specific clinical (177)Lu-DOTATATE therapy dosimetry system is constructed and used for investigating the variability of renal absorbed dose and biologically effective dose (BED) estimates. As patient models, three anthropomorphic computer phantoms coupled to a pharmacokinetic model of (177)Lu-DOTATATE are used. Aspects included in the dosimetry-process model are the gamma-camera calibration via measurement of the system sensitivity, selection of imaging time points, generation of mass-density maps from CT, SPECT imaging, volume-of-interest delineation, calculation of absorbed-dose rate via a combination of local energy deposition for electrons and Monte Carlo simulations of photons, curve fitting and integration to absorbed dose and BED. By introducing variabilities in these steps the combined uncertainty in the output quantity is determined. The importance of different sources of uncertainty is assessed by observing the decrease in standard deviation when removing a particular source. The obtained absorbed dose and BED standard deviations are approximately 6% and slightly higher if considering the root mean square error. The most important sources of variability are the compensation for partial volume effects via a recovery coefficient and the gamma-camera calibration via the system sensitivity.

Background: Prostate-specific membrane antigen (PSMA) radiotracers such as [ 18 F]PSMA-1007 used with positron emission tomography-computed tomography (PET-CT) is promising for initial staging and detection of recurrent disease in prostate cancer patients. The block-sequential regularization expectation maximization algorithm (BSREM) is a new PET reconstruction algorithm, which provides higher image contrast while also reducing noise. The aim of the present study was to evaluate the influence of different acquisition times and different noise-suppressing factors in BSREM (β values) in [ 18 F]PSMA-1007 PET-CT regarding quantitative data as well as a visual image quality assessment. We included 35 patients referred for clinical [ 18 F]PSMA-1007 PET-CT. Four megabecquerels per kilogramme were administered and imaging was performed after 120 min. Eighty-four image series per patient were created with combinations of acquisition times of 1-4 min/bed position and β values of 300-1400. The noise level in normal tissue and the contrast-to-noise ratio (CNR) of pathological uptakes versus the local background were calculated. Image quality was assessed by experienced nuclear medicine physicians. Results: The noise level in the liver, spleen, and muscle was higher for low β values and low acquisition times (written as activity time products (ATs = administered activity × acquisition time)) and was minimized at maximum AT (16 MBq/kg min) and maximum β (1400). There was only a small decrease above AT 10. The median CNR increased slowly with AT from approximately 6 to 12 and was substantially lower at AT 4 and higher at AT 14-16. At AT 4-6, many images were regarded as being of unacceptable quality. For AT 8, β values of 700-900 were considered of acceptable quality. Conclusions: An AT of 8 (for example as in our study, 4 MB/kg with an acquisition time of 2 min) with a β value of 700 performs well regarding noise level, CNR, and visual image quality assessment.