In this work, we present details and initial results from a 177 Lu dosimetry challenge that has been designed to collect data from the global nuclear medicine community aiming at identifying, understanding, and quantitatively characterizing the consequences of the various sources of variability in dosimetry. Methods: The challenge covers different approaches to performing dosimetry: planar, hybrid, and pure SPECT. It consists of 5 different and independent tasks to measure the variability of each step in the dosimetry workflow. Each task involves the calculation of absorbed doses to organs and tumors and was meant to be performed in sequential order. The order of the tasks is such that results from a previous one would not affect subsequent ones. Different sources of variability are removed as the participants advance through the challenge by giving them the data required to begin the calculations at different steps of the dosimetry workflow. Data from 2 patients after a therapeutic administration of 177 Lu-DOTATATE were used for this study. The data are hosted in Deep Blue Data, a data repository service run by the University of Michigan. Participants submit results in standardized spreadsheets and with a short description summarizing their methods. Results: In total, 178 participants have signed up for the challenge, and 119 submissions have been received. Sixty percent of submissions have used voxelized dose methods, with 47% of those using commercial software. In initial analysis, the volume of organs showed a variability of up to 49.8% whereas for lesions this was up to 176%. Variability in time-integrated activity was up to 192%. Mean absorbed doses varied up to 57.7%. Segmentation is the step that required the longest time to complete, with a median of 43 min. The median total time to perform the full calculation was 89 min. Conclusion: To advance dosimetry and encourage its routine use in radiopharmaceutical therapy applications, it is critical that dosimetry results be reproducible across centers. Our initial results provide insights into the variability associated with performing dose calculations. It is expected that this dataset, including results from future stages, will result in efforts to standardize and harmonize methods and procedures.

Validation of dosimetry software, such as Monte Carlo (MC) radiation transport codes used for patient-specific absorbed dose estimation, is critical prior to their use in clinical decision making. However, direct experimental validation in the clinic is generally not performed for low/medium-energy beta emitters used in radiopharmaceutical therapy (RPT) due to the challenges of measuring energy deposited by short-range particles. Our objective was to design a practical phantom geometry for radiochromic film (RF)-based absorbed dose measurements of beta-emitting radionuclides and perform experiments to directly validate our in-house developed Dose Planning Method (DPM) MC code dedicated to internal dosimetry. Methods: The experimental setup was designed for measuring absorbed dose from beta emitters that have a range sufficiently penetrating to ∼200 µm in water as well as to capture any photon contributions to absorbed dose. Assayed 177 Lu and 90 Y liquid sources, 13-450 MBq estimated to deliver 0.5-10 Gy to the sensitive layer of the RF, were injected into the cavity of two 3D-printed half -cylinders that had been sealed with 12.7 µm or 25.4 µm thick Kapton Tape. A 3.8 × 6 cm strip of GafChromic EBT3 RF was sandwiched between the two taped half -cylinders. After 2-48 h exposures, films were retrieved and wipe tested for contamination. Absorbed dose to the RF was measured using a commercial triple-channel dosimetry optimization method and a calibration generated via 6 MV photon beam. Profiles were analyzed across the central 1 cm 2 area of the RF for validation. Eleven experiments were completed with 177 Lu and nine with 90 Y both in saline and a bone equivalent solution. Depth dose curves were generated for 177 Lu and 90 Y stacking multiple RF strips between a single filled half -cylinder and an acrylic backing. All experiments were modeled in DPM to generate voxelized MC absorbed dose estimates. We extended our study to benchmark general purpose MC codes MCNP6 and EGSnrc against the experimental results as well. Results: A total of 20 experiments showed that both the 3D-printed phantoms and the final absorbed dose values were reproducible. The agreement between the absorbed dose estimates from the RF measurements and DPM was on average −4.0% (range −10.9% to 3.2%) for all single film 177 Lu experiments and was on average −1.0% (range −2.7% to 0.7%) for all single film 90 Y experiments. Absorbed depth dose estimates by DPM agreed with RF on averageThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Portable coded-aperture imaging systems based on scintillators and semiconductors have found use in a variety of radiological applications. For stand-off detection of weakly emitting materials, large volume detectors can facilitate the rapid localization of emitting materials. We describe a scalable coded-aperture imaging system based on 5.02 × 5.02 cm CsI(Tl) scintillator modules, each partitioned into 4 × 4 × 20 mm pixels that are optically coupled to 12 × 12 pixel silicon photo-multiplier (SiPM) arrays. The 144 pixels per module are read-out with a resistor-based charge-division circuit that reduces the readout outputs from 144 to four signals per module, from which the interaction position and total deposited energy can be extracted. All 144 CsI(Tl) pixels are readily distinguishable with an average energy resolution, at 662 keV, of 13.7% FWHM, a peak-to-valley ratio of 8.2, and a peak-to-Compton ratio of 2.9. The detector module is composed of a SiPM array coupled with a 2 cm thick scintillator and modified uniformly redundant array mask. For the image reconstruction, cross correlation and maximum likelihood expectation maximization methods are used. The system shows a field of view of 45° and an angular resolution of 4.7° FWHM.

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Introduction Much progress has been made in implementing selective internal radiation therapy (SIRT) as a viable treatment option for hepatic malignancies. However, there is still much need for improved options for calculating the amount of activity to be administered. To make advances towards this goal, this study examines the relationship between predicted biological outcomes of liver tumors via tumor control probabilities (TCP) and parenchyma via normal tissue complication probabilities (NTCP) given variations in absorbed dose prescription methodologies. Methods Thirty-nine glass microsphere treatments in 35 patients with hepatocellular carcinoma or metastatic liver disease were analyzed using 99mTc-MAA SPECT/CT and 90Y PET/CT scans. Predicted biological outcomes corresponding to the single compartment (standard) model and multi-compartment (partition) dosimetry model were compared using our previously derived TCP dose-response curves over a range of 80–150 Gy prescribed absorbed dose to the perfused volume, recommended in the package insert for glass microspheres. Retrospective planning dosimetry was performed on the MAA SPECT/CT; changes from the planned infused activity due to selection of absorbed dose level and dosimetry model (standard or partition) were used to scale absorbed doses reported from 90Y PET/CT including liver parenchyma and lesions (N = 120) > 2 ml. A parameterized charting system was developed across all potential prescription options to enable a clear relationship between standard prescription vs. the partition model-based prescription. Using a previously proposed NTCP model, the change in prescribed dose from a standard model prescription of 120 Gy to the perfused volume to a 15% NTCP prescription to the normal liver was explored. Results Average TCP predictions for the partition model compared with the standard model varied from a 13% decrease to a 32% increase when the prescribed dose was varied across the range of 80–150 Gy. In the parametrized chart comparing absorbed dose prescription ranges across the standard model and partition models, a line of equivalent absorbed dose to a tumor was identified. TCP predictions on a per lesion basis varied between a 26% decrease and a 81% increase for the most commonly chosen prescription options when comparing the partition model with the standard model. NTCP model was only applicable to a subset of patients because of the small volume fraction of the liver that was targeted in most cases. Conclusion Our retrospective analysis of patient imaging data shows that the choice of prescribed dose and which model to prescribe potentially contribute to a wide variation in average tumor efficacy. Biological response data should be included as one factor when looking to improve patient care in the clinic. The use of parameterized charting, such as presented here, will help direct physicians when transitioning to newer prescription methods.