MIRD pamphlet No. 23: quantitative SPECT for patient-specific 3-dimensional dosimetry in internal radionuclide therapy

A step toward simplified dosimetry of radiopharmaceutical therapy via SPECT frame duration reduction

Despite being time-consuming, SPECT/CT data is necessary for accurate dosimetry in patient-specific radiopharmaceutical therapy. We investigated how reducing the frame duration (FD) during SPECT acquisition can simplify the dosimetry workflow for [177Lu]Lu-PSMA radioligand therapy (RLT). We aimed to determine the impact of shortened acquisition times on dosimetric precision. Three SPECT scans with FD of 20, 10, and 5 second/frame (sec/fr) were obtained 48 h post-RLT from one metastatic castration-resistant prostate cancer (mCRPC) patient's pelvis. Planar images at 4, 48, and 72 h post-therapy were used to calculate time-integrated activities (TIAs). Using accurate activity calibrations and GATE Monte Carlo (MC) dosimetry, absorbed doses in tumor lesions and kidneys were estimated. Dosimetry precision was assessed by comparing shorter FD results to the 20 sec/fr reference using relative percentage difference (RPD). We observed consistent calibration factors (CFs) across different FDs. Using the same CF, we obtained marginal RPD deviations less than 4% for the right kidney and tumor lesions and less than 7% for the left kidney. By reducing FD, simulation time was slightly decreased. This study shows we can shorten SPECT acquisition time in RLT dosimetry by reducing FD without sacrificing dosimetry accuracy. These findings pave the way for streamlined personalized internal dosimetry workflows.

Linear Boltzmann equation solver for voxel-level dosimetry in radiopharmaceutical therapy: Comparison with Monte Carlo and kernel convolution

BACKGROUND

With recent interest in patient-specific dosimetry for radiopharmaceutical therapy (RPT) and selective internal radiation therapy (SIRT), an increasing number of voxel-based algorithms are being evaluated. Monte Carlo (MC) radiation transport, generally considered to be the most accurate among different methods for voxel-level absorbed dose estimation, can be computationally inefficient for routine clinical use.

PURPOSE

This work demonstrates a recently implemented grid-based linear Boltzmann transport equation (LBTE) solver for fast and accurate voxel-based dosimetry in RPT and SIRT and benchmarks it against MC.

METHODS

A deterministic LBTE solver (Acuros MRT) was implemented within a commercial RPT dosimetry package (Velocity 4.1). The LBTE is directly discretized using an adaptive mesh refined grid and then the coupled photon-electron radiation transport is iteratively solved inside specified volumes to estimate radiation doses from both photons and charged particles in heterogeneous media. To evaluate the performance of the LBTE solver for RPT and SIRT applications, 177Lu SPECT/CT, 90Y PET/CT, and 131I SPECT/CT images of phantoms and patients were used. Multiple lesions (2-1052 mL) and normal organs were delineated for each study. Voxel dosimetry was performed with the LBTE solver, dose voxel kernel (DVK) convolution with density correction, and a validated in-house MC code using the same time-integrated activity and density maps as input to the different dose engines. The resulting dose maps, difference maps, and dose-volume-histogram (DVH) metrics were compared, to assess the voxel-level agreement. Evaluation of mean absorbed dose included comparison with structure-level estimates from OLINDA.

RESULTS

In the phantom inserts/compartments, the LBTE solver versus MC and DVK convolution demonstrated good agreement with mean absorbed dose and DVH metrics agreeing to within 5% except for the D90 and D70 metrics of a very low activity concentration insert of 90Y where the agreement was within 15%. In the patient studies (five patients imaged after 177Lu DOTATATE RPT, five after 90Y SIRT, and two after 131I radioimmunotherapy), in general, there was better agreement between the LBTE solver and MC than between LBTE solver and DVK convolution for mean absorbed dose and voxel-level evaluations. Across all patients for all three radionuclides, for soft tissue structures (kidney, liver, lesions), the mean absorbed dose estimates from the LBTE solver were in good agreement with those from MC (median difference < 1%, maximum 9%) and those from DVK (median difference < 5%, maximum 9%). The LBTE and OLINDA estimates for mean absorbed dose in kidneys and liver agreed to within 10%, but differences for lesions were larger with a maximum 14% for 177Lu, 23% for 90Y, and 26% for 131I. For bone regions, the agreement in mean absorbed doses between LBTE and both MC and DVK were similar (median < 11%, max 11%) while for lung the agreement between LBTE and MC (median < 1%, max 8%) was substantially better than between LBTE and DVK (median < 16%, max 33%). Voxel level estimates for soft tissue structures also showed good agreement between the LBTE solver and both MC and DVK with a median difference < 5% (maximum < 13%) for the DVH metrics with all three radionuclides. The largest difference in DVH metrics was for the D90 and D70 metric in lung and bone where the uptake was low. Here, the difference between LBTE and MC had a median value < 14% (maximum 23%) for bone and < 4% (maximum 37%) for lung, while the corresponding differences between LBTE and DVK were < 23% (maximum 31%) and < 67% (maximum 313%), respectively. For a typical patient with a matrix size of 166 × 166 × 129 (voxel size 3 × 3 × 3 mm3), voxel dosimetry using the LBTE solver was as fast as ∼2 min on a desktop computer.

CONCLUSION

Having established good agreement between the LBTE solver and MC for RPT and SIRT applications, the LBTE solver is a viable option for voxel dosimetry that can be faster than MC. Further analysis is being performed to encompass the broad range of radionuclides and conditions encountered clinically.

Estimation of kidney doses from [177Lu]Lu-DOTA-TATE PRRT using single time point post-treatment SPECT/CT

BACKGROUND

Dosimetry after [177Lu]Lu-DOTA-TATE therapy can be demanding for both patients and the clinical service due to the need for imaging at several time points. In this work we compare three methods of single time point (STP) kidney dosimetry after [177Lu]Lu-DOTA-TATE therapy with a multiple time point (MTP) dosimetry method.

METHOD

Method 1 (MTP): Kidney doses were calculated from 31 patients including 107 therapy cycles. Post-therapy SPECT images were acquired on day 0, 4 and 7 along with a CT scan on day 4. A mono-exponential fit was used to calculate kidney doses using cycle specific data. Method 2 (Consistent effective half-life): The effective half-life [Formula: see text] calculated in cycle 1 was assumed consistent for subsequent cycles of therapy and the activity scaled using a single day 3-5 SPECT/CT. Methods 3 and 4 (Hänscheid and Madsen approximations): The Hänscheid approximation and Madsen approximation were both evaluated using a single SPECT/CT acquired on day 0, 4 and 7. All STP methods were compared to the MTP method for accuracy.

RESULTS

Using the MTP method, mean right and left kidney doses were calculated to be 2.9 ± 1.1 Gy and 2.8 ± 0.9 Gy respectively and the population [Formula: see text] was 56 ± 13 h. For the consistent [Formula: see text], Hänscheid and Madsen methods, the percentage of results within ± 20% of MTP method were 96% (n = 70), 95% (n = 80) and 94% (n = 80) respectively.

CONCLUSION

All three single time point methods had > 94% of results within ± 20% of the MTP method, however the consistent [Formula: see text] method resulted in the highest alignment with the MTP method and is the only method which allows for calculation of the patient-specific [Formula: see text]. If only a single scan can be performed, day 4 is optimal for kidney dosimetry where the Hänscheid or Madsen approximation can be implemented with good accuracy.

A review of 177Lu dosimetry workflows: how to reduce the imaging workloads?

177 Lu radiopharmaceutical therapy is a standardized systemic treatment, with a typical dose of 7.4 GBq per injection, but its response varies from patient to patient. Dosimetry provides the opportunity to personalize treatment, but it requires multiple post-injection images to monitor the radiopharmaceutical's biodistribution over time. This imposes an additional imaging burden on centers with limited resources. This review explores methods to lessen this burden by optimizing acquisition types and minimizing the number and duration of imaging sessions. After summarizing the different steps of dosimetry and providing examples of dosimetric workflows for177 Lu -DOTATATE and177 Lu -PSMA, we examine dosimetric workflows based on a reduced number of acquisitions, or even just one. We provide a non-exhaustive description of simplified methods and their assumptions, as well as their limitations. Next, we detail the specificities of each normal tissue and tumors, before reviewing dose-response relationships in the literature. In conclusion, we will discuss the current limitations of dosimetric workflows and propose avenues for improvement.

Pareto optimization of SPECT acquisition and reconstruction settings for 177Lu activity quantification

BACKGROUND

The aim was to investigate the noise and bias properties of quantitative 177Lu-SPECT with respect to the number of projection angles, and the number of subsets and iterations in the OS-EM reconstruction, for different total acquisition times.

METHODS

Experimental SPECT acquisition of six spheres in a NEMA body phantom filled with 177Lu was performed, using medium-energy collimators and 120 projections with 180 s per projection. Bootstrapping was applied to generate data sets representing acquisitions with 20 to 120 projections for 10 min, 20 min, and 40 min, with 32 noise realizations per setting. Monte Carlo simulations were performed of 177Lu-DOTA-TATE in an anthropomorphic computer phantom with three tumours (2.8 mL to 40.0 mL). Projections representing 24 h and 168 h post administration were simulated, each with 32 noise realizations. Images were reconstructed using OS-EM with compensation for attenuation, scatter, and distance-dependent resolution. The number of subsets and iterations were varied within a constrained range of the product number of iterations × number of projections ≤ 2400 . Volumes-of-interest were defined following the physical size of the spheres and tumours, the mean activity-concentrations estimated, and the absolute mean relative error and coefficient of variation (CV) over noise realizations calculated. Pareto fronts were established by analysis of CV versus mean relative error.

RESULTS

Points at the Pareto fronts with low CV and high mean error resulted from using a low number of subsets, whilst points at the Pareto fronts associated with high CV but low mean error resulted from reconstructions with a high number of subsets. The number of projection angles had limited impact.

CONCLUSIONS

For accurate estimation of the 177Lu activity-concentration from SPECT images, the number of projection angles has limited importance, whilst the total acquisition time and the number of subsets and iterations are parameters of importance.

Lutetium-177-Prostate-Specific Membrane Antigen Radioligand Therapy: What Is the Value of Post-Therapeutic Imaging?

Lutetium-177 (Lu-177)-labelled radioligand therapies (RLT) targeting prostate-specific membrane antigen (PSMA) present a promising treatment for patients with progressive metastasized castration-resistant prostate cancer (mCRPC). Personalized dosimetry, facilitated by post-therapeutic imaging, offers the potential to enhance treatment efficacy by customizing radiation doses to individual patient needs, thereby maximizing therapeutic benefits while minimizing toxicity to healthy tissues. However, implementing personalized dosimetry is resource-intensive, requiring multiple single-photon emission-computed tomography (SPECT)/CT scans and posing significant logistical challenges for both healthcare facilities and patients. Despite these challenges, personalized dosimetry can lead to optimized radiation delivery, improved safety, and better management of complex cases. Nevertheless, the financial and resource burdens complicate its adoption in routine clinical practice. While the European Association of Nuclear Medicine (EANM) supports personalized dosimetry, standardization is lacking due to these practical constraints. Further research and streamlined methodologies are essential to balance the benefits and feasibility of personalized dosimetry, potentially improving treatment outcomes for mCRPC patients.

Assessing Response to PSMA Radiopharmaceutical Therapies with Single SPECT Imaging at 24 Hours After Injection

Understanding the relationship between lesion-absorbed dose and tumor response in 177Lu-PSMA-617 radiopharmaceutical therapies (RPTs) remains complex. We aimed to investigate whether baseline lesion-absorbed dose can predict lesion-based responses and to explore the connection between lesion-absorbed dose and prostate-specific antigen (PSA) response. Methods: In this retrospective study, we evaluated 50 patients with 335 index lesions undergoing 177Lu-PSMA-617 RPT, who had dosimetry analysis performed on SPECT/CT at 24 h after cycles 1 and 2. First, we identified the index lesions for each patient and measured the lesion-based absorbed doses. Lesion-based response was calculated after cycle 2. Additionally, PSA50 response (a decline of 50% from baseline PSA) after cycle 2 was also calculated. The respective responses for mean and maximum absorbed doses and prostate-specific membrane antigen (PSMA) volumetric intensity product (VIP-PSMA) at cycles 1 and 2 were termed SPECTmean, SPECTmaximum, and SPECTVIP-PSMA, respectively. Results: Of the 50 patients reviewed, 46% achieved a PSA50 response after cycle 2. Of the 335 index lesions, 58% were osseous, 32% were lymph nodes, and 10% were soft-tissue metastatic lesions. The SPECT lesion-based responses were higher in PSA responders than in nonresponders (SPECTmean response of 46.8% ± 26.1% vs. 26.2% ± 24.5%, P = 0.007; SPECTmaximum response of 45% ± 25.1% vs. 19% ± 27.0%, P = 0.001; SPECTVIP-PSMA response of 49.2% ± 30.3% vs. 14% ± 34.7%, P = 0.0005). An association was observed between PSA response and SPECTVIP-PSMA response (R 2 = 0.40 and P < 0.0001). A limited relationship was found between baseline absorbed dose measured with a 24-h single time point and SPECT lesion-based response (R 2 = 0.05, P = 0.001, and R 2 = 0.03, P = 0.007, for mean and maximum absorbed doses, respectively). Conclusion: In this retrospective study, quantitative lesion-based response correlated with patient-level PSA response. We observed a limited relationship between baseline absorbed dose and lesion-based responses. Most of the variance in response remains unexplained solely by baseline absorbed dose. Establishment of a dose-response relationship in RPT with a single time point at 24 h presented some limitations.

The MIRD Schema for Radiopharmaceutical Dosimetry: A Review

Internal dosimetry evaluates the amount and spatial and temporal distributions of radiation energy deposited in tissue from radionuclides within the body. Historically, nuclear medicine had been largely a diagnostic specialty, and the implicitly performed risk-benefit analyses have been straightforward, with relatively low administered activities yielding important diagnostic information whose benefit far outweighs any potential risk associated with the attendant normal-tissue radiation doses. Although dose estimates based on anatomic models and population-average kinetics in this setting may deviate rather significantly from the actual normal-organ doses for individual patients, the large benefit-to-risk ratios are very forgiving of any such inaccuracies. It is in this context that the MIRD schema was originally developed and has been largely applied. The MIRD schema, created and maintained by the MIRD committee of the Society of Nuclear Medicine and Molecular Imaging, comprises the notation, terminology, mathematic formulas, and reference data for calculating tissue radiation doses from radiopharmaceuticals administered to patients. However, with the ongoing development of new radiopharmaceuticals and the increasing therapeutic application of such agents, internal dosimetry in nuclear medicine and the MIRD schema continue to evolve-from population-average and organ-level to patient-specific and suborgan to voxel-level to cell-level dose estimation. This article will review the basic MIRD schema, relevant quantities and units, reference anatomic models, and its adaptation to small-scale and patient-specific dosimetry.

Enhancing voxel-based dosimetry accuracy with an unsupervised deep learning approach for hybrid medical image registration

BACKGROUND

Deformable registration is required to generate a time-integrated activity (TIA) map which is essential for voxel-based dosimetry. The conventional iterative registration algorithm using anatomical images (e.g., computed tomography (CT)) could result in registration errors in functional images (e.g., single photon emission computed tomography (SPECT) or positron emission tomography (PET)). Various deep learning-based registration tools have been proposed, but studies specifically focused on the registration of serial hybrid images were not found.

PURPOSE

In this study, we introduce CoRX-NET, a novel unsupervised deep learning network designed for deformable registration of hybrid medical images. The CoRX-NET structure is based on the Swin-transformer (ST), allowing for the representation of complex spatial connections in images. Its self-attention mechanism aids in the effective exchange and integration of information across diverse image regions. To augment the amalgamation of SPECT and CT features, cross-stitch layers have been integrated into the network.

METHODS

Two different 177 Lu DOTATATE SPECT/CT datasets were acquired at different medical centers. 22 sets from Seoul National University and 14 sets from Sunway Medical Centre are used for training/internal validation and external validation respectively. The CoRX-NET architecture builds upon the ST, enabling the modeling of intricate spatial relationships within images. To further enhance the fusion of SPECT and CT features, cross-stitch layers have been incorporated within the network. The network takes a pair of SPECT/CT images (e.g., fixed and moving images) and generates a deformed SPECT/CT image. The performance of the network was compared with Elastix and TransMorph using L1 loss and structural similarity index measure (SSIM) of CT, SSIM of normalized SPECT, and local normalized cross correlation (LNCC) of SPECT as metrics. The voxel-wise root mean square errors (RMSE) of TIA were compared among the different methods.

RESULTS

The ablation study revealed that cross-stitch layers improved SPECT/CT registration performance. The cross-stitch layers notably enhance SSIM (internal validation: 0.9614 vs. 0.9653, external validation: 0.9159 vs. 0.9189) and LNCC of normalized SPECT images (internal validation: 0.7512 vs. 0.7670, external validation: 0.8027 vs. 0.8027). CoRX-NET with the cross-stitch layer achieved superior performance metrics compared to Elastix and TransMorph, except for CT SSIM in the external dataset. When qualitatively analyzed for both internal and external validation cases, CoRX-NET consistently demonstrated superior SPECT registration results. In addition, CoRX-NET accomplished SPECT/CT image registration in less than 6 s, whereas Elastix required approximately 50 s using the same PC's CPU. When employing CoRX-NET, it was observed that the voxel-wise RMSE values for TIA were approximately 27% lower for the kidney and 33% lower for the tumor, compared to when Elastix was used.

CONCLUSION

This study represents a major advancement in achieving precise SPECT/CT registration using an unsupervised deep learning network. It outperforms conventional methods like Elastix and TransMorph, reducing uncertainties in TIA maps for more accurate dose assessments.

Deep transformer-based personalized dosimetry from SPECT/CT images: a hybrid approach for [177Lu]Lu-DOTATATE radiopharmaceutical therapy

PURPOSE

Accurate dosimetry is critical for ensuring the safety and efficacy of radiopharmaceutical therapies. In current clinical dosimetry practice, MIRD formalisms are widely employed. However, with the rapid advancement of deep learning (DL) algorithms, there has been an increasing interest in leveraging the calculation speed and automation capabilities for different tasks. We aimed to develop a hybrid transformer-based deep learning (DL) model that incorporates a multiple voxel S-value (MSV) approach for voxel-level dosimetry in [177Lu]Lu-DOTATATE therapy. The goal was to enhance the performance of the model to achieve accuracy levels closely aligned with Monte Carlo (MC) simulations, considered as the standard of reference. We extended our analysis to include MIRD formalisms (SSV and MSV), thereby conducting a comprehensive dosimetry study.

METHODS

We used a dataset consisting of 22 patients undergoing up to 4 cycles of [177Lu]Lu-DOTATATE therapy. MC simulations were used to generate reference absorbed dose maps. In addition, MIRD formalism approaches, namely, single S-value (SSV) and MSV techniques, were performed. A UNEt TRansformer (UNETR) DL architecture was trained using five-fold cross-validation to generate MC-based dose maps. Co-registered CT images were fed into the network as input, whereas the difference between MC and MSV (MC-MSV) was set as output. DL results are then integrated to MSV to revive the MC dose maps. Finally, the dose maps generated by MSV, SSV, and DL were quantitatively compared to the MC reference at both voxel level and organ level (organs at risk and lesions).

RESULTS

The DL approach showed slightly better performance (voxel relative absolute error (RAE) = 5.28 ± 1.32) compared to MSV (voxel RAE = 5.54 ± 1.4) and outperformed SSV (voxel RAE = 7.8 ± 3.02). Gamma analysis pass rates were 99.0 ± 1.2%, 98.8 ± 1.3%, and 98.7 ± 1.52% for DL, MSV, and SSV approaches, respectively. The computational time for MC was the highest (~2 days for a single-bed SPECT study) compared to MSV, SSV, and DL, whereas the DL-based approach outperformed the other approaches in terms of time efficiency (3 s for a single-bed SPECT). Organ-wise analysis showed absolute percent errors of 1.44 ± 3.05%, 1.18 ± 2.65%, and 1.15 ± 2.5% for SSV, MSV, and DL approaches, respectively, in lesion-absorbed doses.

CONCLUSION

A hybrid transformer-based deep learning model was developed for fast and accurate dose map generation, outperforming the MIRD approaches, specifically in heterogenous regions. The model achieved accuracy close to MC gold standard and has potential for clinical implementation for use on large-scale datasets.

[161Tb]Tb-PSMA-617 radioligand therapy in patients with mCRPC: preliminary dosimetry results and intra-individual head-to-head comparison to [177Lu]Lu-PSMA-617

Rationale: Evaluation of alternative radionuclides for use in prostate-specific membrane antigen (PSMA)-targeted radioligand therapy (RLT) is currently focusing on 161Tb, which may provide advantages by emitting additional Auger and conversion electrons. In this pilot study, we present preliminary dosimetry data for [161Tb]Tb-PSMA-617 RLT in a direct comparison with [177Lu]Lu-PSMA-617. Method: Six patients with metastatic castration-resistant prostate cancer (mCRPC) underwent treatment with [177Lu]Lu-PSMA-617 and subsequently - after inadequate response - with [161Tb]Tb-PSMA-617. Whole-body planar and SPECT imaging-based dosimetry of organs at risk (kidneys and salivary glands) and tumor lesions were calculated using IDAC for 177Lu and OLINDA/EXM for 161Tb. The therapeutic index (TI) of mean tumor-absorbed doses over relevant organs at risk was calculated. Results: Mean absorbed doses to organs at risk of PSMA-RLT were slightly higher for [161Tb]Tb-PSMA-617 compared to [177Lu]Lu-PSMA-617 (kidneys: 0.643 ± 0.247 vs. 0.545 ± 0.231 Gy/GBq, factor 1.18; parotid gland: 0.367 ± 0.198 vs. 0.329 ± 0.180 Gy/GBq, factor 1.10), but markedly higher regarding tumor lesions (6.10 ± 6.59 vs 2.59 ± 3.30 Gy/GBq, factor 2.40, p < 0.001). Consequently, the mean TI was higher for [161Tb]Tb-PSMA-617 compared to [177Lu]Lu-PSMA-617 for both, the kidneys (11.54 ± 9.74 vs. 5.28 ± 5.13, p = 0.002) and the parotid gland (16.77 ± 13.10 vs. 12.51 ± 18.09, p = 0.008). Conclusion: In this intra-individual head-to-head pilot study, [161Tb]Tb-PSMA-617 delivered higher tumor-absorbed doses and resulted in superior TI compared to [177Lu]Lu-PSMA-617. This preliminary data support 161Tb as a promising radionuclide for PSMA-RLT in mCRPC.

Anatomy-based correction of kidney PVE on [Formula: see text] SPECT images

BACKGROUND

In peptide receptor radionuclide therapy (PRRT), accurate quantification of kidney activity on post-treatment SPECT images paves the way for patient-specific treatment. Due to the limited spatial resolution of SPECT images, the partial volume effect (PVE) is a significant source of quantitative bias. In this study, we aimed to evaluate the performance and robustness of anatomy-based partial volume correction (PVC) algorithms to recover the accurate activity concentration of realistic kidney geometries on [Formula: see text]Lu SPECT images recorded under clinical conditions.

METHODS

Based on the CT scan data from patients, three sets of fillable kidneys with surface-to-volume (S:V) ratios ranging from 1.5 to 2.8 cm-1, were 3D printed and attached in a IEC phantom. Quantitative [Formula: see text]Lu SPECT/CT acquisitions were performed on a GE Discovery NM CT 870 DR camera for the three modified IEC phantoms and for 6 different Target-To-Background ratios (TBRs: 2, 4, 6, 8, 10, 12). Two region-based (GTM and Labbé) and five voxel-based (GTM + MTC, Labbé + MTC, GTM + RBV, Labbé + RBV and IY) methods were evaluated with this data set. Additionally, the robustness of PVC methods to Point Spread Function (PSF) discrepancies, registration mismatches and background heterogeneity was evaluated.

RESULTS

Without PVC, the average kidney RCs across all TBRs ranged from 0.66 ± 0.05 (smallest kidney) to 0.80 ± 0.03 (largest kidney). For a TBR of 12, all anatomy-based method were able to recover the kidneys activity concentration with an error < 6%. All methods result in a comparable decline in RC restoration with decreasing TBR. The Labbé method was the most robust against PSF and registration mismatches but was also the most sensitive to background heterogeneity. Among the voxel-based methods, MTC images were less uniform than RBV and IY images at the outer edge of high uptake areas (kidneys and spheres).

CONCLUSION

Anatomy-based PVE correction allows for accurate SPECT quantification of the [Formula: see text]Lu activity concentration with realistic kidney geometries. Combined with recent progress in deep-learning algorithms for automatic anatomic segmentation of whole-body CT, these methods could be of particular interest for a fully automated OAR dosimetry pipeline with PVE correction.

3D printed non-uniform anthropomorphic phantoms for quantitative SPECT

BACKGROUND

A 3D printing grid-based method was developed to construct anthropomorphic phantoms with non-uniform activity distributions, to be used for evaluation of quantitative SPECT images. The aims were to characterize the grid-based method and to evaluate its capability to provide realistically shaped phantoms with non-uniform activity distributions.

METHODS

Characterization of the grid structures was performed by printing grid-filled spheres. Evaluation was performed by micro-CT imaging to investigate the printing accuracy and by studying the modulation contrast ([Formula: see text]) in SPECT images for 177Lu and 99mTc as a function of the grid fillable-volume fraction (FVF) determined from weighing. The grid-based technique was applied for the construction of two kidney phantoms and two thyroid phantoms, designed using templates from the XCAT digital phantoms. The kidneys were constructed with a hollow outer container shaped as cortex, an inner grid-based structure representing medulla and a solid section representing pelvis. The thyroids consisted of two lobes printed as grid-based structures, with void hot spots within the lobes. The phantoms were filled with solutions of 177Lu (kidneys) or 99mTc (thyroids) and imaged with SPECT. For verification, Monte Carlo simulations of SPECT imaging were performed for activity distributions corresponding to those of the printed phantoms. Measured and simulated SPECT images were compared qualitatively and quantitatively.

RESULTS

Micro-CT images showed that printing inaccuracies were mainly uniform across the grid. The relationships between the FVF from weighing and [Formula: see text] were found to be linear (r = 0.9995 and r = 0.9993 for 177Lu and 99mTc, respectively). The FVF-deviations from the design were up to 15% for thyroids and 4% for kidneys, mainly related to possibilities of cleaning after printing. Measured and simulated SPECT images of kidneys and thyroids exhibited similar activity distributions and quantitative comparisons agreed well, thus verifying the grid-based method.

CONCLUSIONS

We find the grid-based technique useful for the provision of 3D printed, realistically shaped, phantoms with non-uniform activity distributions, which can be used for evaluation of different quantitative methods in SPECT imaging.

The Challenge of Single-Photon Emission Computed Tomography Image Segmentation in the Internal Dosimetry of 177Lu Molecular Therapies

The aim of this article is to review the single photon emission computed tomography (SPECT) segmentation methods used in patient-specific dosimetry of 177Lu molecular therapy. Notably, 177Lu-labelled radiopharmaceuticals are currently used in molecular therapy of metastatic neuroendocrine tumours (ligands for somatostatin receptors) and metastatic prostate adenocarcinomas (PSMA ligands). The proper segmentation of the organs at risk and tumours in targeted radionuclide therapy is an important part of the optimisation process of internal patient dosimetry in this kind of therapy. Because this is the first step in dosimetry assessments, on which further dose calculations are based, it is important to know the level of uncertainty that is associated with this part of the analysis. However, the robust quantification of SPECT images, which would ensure accurate dosimetry assessments, is very hard to achieve due to the intrinsic features of this device. In this article, papers on this topic were collected and reviewed to weigh up the advantages and disadvantages of the segmentation methods used in clinical practice. Degrading factors of SPECT images were also studied to assess their impact on the quantification of 177Lu therapy images. Our review of the recent literature gives an insight into this important topic. However, based on the PubMed and IEEE databases, only a few papers investigating segmentation methods in 177Lumolecular therapy were found. Although segmentation is an important step in internal dose calculations, this subject has been relatively lightly investigated for SPECT systems. This is mostly due to the inner features of SPECT. What is more, even when studies are conducted, they usually utilise the diagnostic radionuclide 99mTc and not a therapeutic one like 177Lu, which could be of concern regarding SPECT camera performance and its overall outcome on dosimetry.

Radiomics and Artificial Intelligence in Radiotheranostics: A Review of Applications for Radioligands Targeting Somatostatin Receptors and Prostate-Specific Membrane Antigens

Radiotheranostics refers to the pairing of radioactive imaging biomarkers with radioactive therapeutic compounds that deliver ionizing radiation. Given the introduction of very promising radiopharmaceuticals, the radiotheranostics approach is creating a novel paradigm in personalized, targeted radionuclide therapies (TRTs), also known as radiopharmaceuticals (RPTs). Radiotherapeutic pairs targeting somatostatin receptors (SSTR) and prostate-specific membrane antigens (PSMA) are increasingly being used to diagnose and treat patients with metastatic neuroendocrine tumors (NETs) and prostate cancer. In parallel, radiomics and artificial intelligence (AI), as important areas in quantitative image analysis, are paving the way for significantly enhanced workflows in diagnostic and theranostic fields, from data and image processing to clinical decision support, improving patient selection, personalized treatment strategies, response prediction, and prognostication. Furthermore, AI has the potential for tremendous effectiveness in patient dosimetry which copes with complex and time-consuming tasks in the RPT workflow. The present work provides a comprehensive overview of radiomics and AI application in radiotheranostics, focusing on pairs of SSTR- or PSMA-targeting radioligands, describing the fundamental concepts and specific imaging/treatment features. Our review includes ligands radiolabeled by 68Ga, 18F, 177Lu, 64Cu, 90Y, and 225Ac. Specifically, contributions via radiomics and AI towards improved image acquisition, reconstruction, treatment response, segmentation, restaging, lesion classification, dose prediction, and estimation as well as ongoing developments and future directions are discussed.

Essentials of Theranostics: A Guide for Physicians and Medical Physicists

Radiopharmaceutical therapies (RPTs) are gaining increased interest with the recent emergence of novel safe and effective theranostic agents, improving outcomes for thousands of patients. The term theranostics refers to the use of diagnostic and therapeutic agents that share the same molecular target; a major step toward precision medicine, especially for oncologic applications. The authors dissect the fundamentals of theranostics in nuclear medicine. First, they explain the radioactive decay schemes and the characteristics of emitted electromagnetic radiation used for imaging, as well as particles used for therapeutic purposes, followed by the interaction of the different types of radiation with tissue. These concepts directly apply to clinical RPTs and play a major role in the efficacy and toxicity profile of different radiopharmaceutical agents. Personalized dosimetry is a powerful tool that can help estimate patient-specific absorbed doses, in tumors as well as normal organs. Dosimetry in RPT is an area of active investigation, as most of what we know about the relationship between delivered dose and tissue damage is extrapolated from external-beam radiation therapy; more research is needed to understand this relationship as it pertains to RPTs. Tumor heterogeneity is increasingly recognized as an important prognostic factor. Novel molecular imaging agents, often in combination with fluorine 18-fluorodeoxyglucose, are crucial for assessment of target expression in the tumor and potential hypermetabolic disease that may lack the molecular target expression. ©RSNA, 2023 Test Your Knowledge questions are available in the supplemental material.

A novel model-based equation for size dependent mean recovery coefficients for spheres and other shapes

BACKGROUND

In NM-imaging, theoretical curves for the recovery coefficient (RC) of the signal maximum and mean are known for spheres and cubes, if a 3D Gaussian PSF is assumed. The RC of the maximum is also known for cylinders. For these and other shapes empirical equations with one or two fit-parameters have been utilized.

METHODS

An equation for the RC for large objects of arbitrary shape is derived and generalized into an empirical equation for smaller objects, which is verified by numerical simulations. The proposed equation is compared to published results on SPECT kidney phantom measurements and to PET measurements on the NEMA IEC PET body phantom with six spheres.

RESULTS

The signal loss (1-RC) for large spheres is inversely proportional to the radius, where the slope is proportional to the FWHM of the spatial resolution. For non-spherical shapes the generalized instead of the volume equivalent radius should be utilized. For smaller objects, an equation with one added empirical fit-parameter is presented. It is demonstrated that the EANM-guidelines' two-parameter logistic function results in a poor fit if the theoretical slope and inverse proportionality are forced and it gives a suboptimal fit when both parameters are fitted.

CONCLUSIONS

A novel model-based equation for the mean RC-curve is derived. It can be used for arbitrary shapes as long as the sphericity is taken into account and it is accurate down to RC = 10 %. One parameter is directly related to the spatial resolution, while the other is a shape depending fit-parameter.

A radiomic- and dosiomic-based machine learning regression model for pretreatment planning in 177 Lu-DOTATATE therapy

BACKGROUND

Standardized patient-specific pretreatment dosimetry planning is mandatory in the modern era of nuclear molecular radiotherapy, which may eventually lead to improvements in the final therapeutic outcome. Only a comprehensive definition of a dosage therapeutic window encompassing the range of absorbed doses, that is, helpful without being detrimental can lead to therapy individualization and improved outcomes. As a result, setting absorbed dose safety limits for organs at risk (OARs) requires knowledge of the absorbed dose-effect relationship. Data sets of consistent and reliable inter-center dosimetry findings are required to characterize this relationship.

PURPOSE

We developed and standardized a new pretreatment planning model consisting of a predictive dosimetry procedure for OARs in patients with neuroendocrine tumors (NETs) treated with 177 Lu-DOTATATE (Lutathera). In the retrospective study described herein, we used machine learning (ML) regression algorithms to predict absorbed doses in OARs by exploiting a combination of radiomic and dosiomic features extracted from patients' imaging data.

METHODS

Pretreatment and posttreatment data for 20 patients with NETs treated with 177 Lu-DOTATATE were collected from two clinical centers. A total of 3412 radiomic and dosiomic features were extracted from the patients' computed tomography (CT) scans and dose maps, respectively. All dose maps were generated using Monte Carlo simulations. An ML regression model was designed based on ML algorithms for predicting the absorbed dose in every OAR (liver, left kidney, right kidney, and spleen) before and after the therapy and between each therapy session, thus predicting any possible radiotoxic effects.

RESULTS

We evaluated nine ML regression algorithms. Our predictive model achieved a mean absolute dose error (MAE, in Gy) of 0.61 for the liver, 1.58 for the spleen, 1.30 for the left kidney, and 1.35 for the right kidney between pretherapy 68 Ga-DOTATOC positron emission tomography (PET)/CT and posttherapy 177 Lu-DOTATATE single photon emission (SPECT)/CT scans. Τhe best predictive performance observed was based on the gradient boost for the liver, the left kidney and the right kidney, and on the extra tree regressor for the spleen. Evaluation of the model's performance according to its ability to predict the absorbed dose in each OAR in every possible combination of pretherapy 68 Ga-DOTATOC PET/CT and any posttherapy 177 Lu-DOTATATE treatment cycle SPECT/CT scans as well as any 177 Lu-DOTATATE SPECT/CT treatment cycle and the consequent 177 Lu-DOTATATE SPECT/CT treatment cycle revealed mean absorbed dose differences ranges from -0.55 to 0.68 Gy. Incorporating radiodosiomics features from the 68 Ga-DOTATOC PET/CT and first 177 Lu-DOTATATE SPECT/CT treatment cycle scans further improved the precision and minimized the standard deviation of the predictions in nine out of 12 instances. An average improvement of 57.34% was observed (range: 17.53%-96.12%). However, it's important to note that in three instances (i.e., Ga,C.1 → C3 in spleen and left kidney, and Ga,C.1 → C2 in right kidney) we did not observe an improvement (absolute differences of 0.17, 0.08, and 0.05 Gy, respectively). Wavelet-based features proved to have high correlated predictive value, whereas non-linear-based ML regression algorithms proved to be more capable than the linear-based of producing precise prediction in our case.

CONCLUSIONS

The combination of radiomics and dosiomics has potential utility for personalized molecular radiotherapy (PMR) response evaluation and OAR dose prediction. These radiodosiomic features can potentially provide information on any possible disease recurrence and may be highly useful in clinical decision-making, especially regarding dose escalation issues.

Pre-treatment dosimetry in90Y-SIRT: Is it possible to optimise SPECT reconstruction parameters and calculation methods for accurate dosimetry?

PURPOSE

The aim of this study was (a) to optimise the99mTc-SPECT reconstruction parameters for the pre-treatment dosimetry of90Y-selective internal radiation therapy (SIRT) and (b) to compare the accuracy of clinical dosimetry methods with full Monte-Carlo dosimetry (fMCD) performed with Gate.

METHODS

To optimise the reconstruction parameters, two hundred reconstructions with different parameters were performed on a NEMA phantom, varying the number of iterations, subsets, and post-filtering. The accuracy of the dosimetric methods was then investigated using an anthropomorphic phantom. Absorbed dose maps were generated using (1) the Partition Model (PM), (2) the Dose Voxel Kernel (DVK) convolution, and (3) the Local Deposition Method (LDM) with known activity restricted to the whole phantom (WP) or to the liver and lungs (LL). The dose to the lungs was calculated using the "multiple DVK" and "multiple LDM" methods.

RESULTS

Optimal OSEM reconstruction parameters were found to depend on object size and dosimetric criterion chosen (Dmean or DVH-derived metric). The Dmean of all three dosimetric methods was close (≤ 10%) to the Dmean of fMCD simulations when considering large segmented volumes (whole liver, normal liver). In contrast, the Dmean to the small volume (∅=31) was systemically underestimated (12%-25%). For lungs, the "multiple DVK" and "multiple LDM" methods yielded a Dmean within 20% for the WP method and within 10% for the LL method.

CONCLUSIONS

All three methods showed a substantial degradation of the dose-volume histograms (DVHs) compared to fMCD simulations. The DVK and LDM methods performed almost equally well, with the "multiple DVK" method being more accurate in the lungs.

Quantitative 177Lu SPECT/CT imaging for personalized dosimetry using a ring-shaped CZT-based camera

BACKGROUND

Dosimetry after radiopharmaceutical therapy with 177Lu (177Lu-RPT) relies on quantitative SPECT/CT imaging, for which suitable reconstruction protocols are required. In this study, we characterized for the first time the quantitative performance of a ring-shaped CZT-based camera using two different reconstruction algorithms: an ordered subset expectation maximization (OSEM) and a block sequential regularized expectation maximization (BSREM) combined with noise reduction regularization. This study lays the foundations for the definition of a reconstruction protocol enabling accurate dosimetry for patients treated with 177Lu-RPT.

METHODS

A series of 177Lu-filled phantoms were acquired on a StarGuide™ (GE HealthCare), with energy and scatter windows centred at 208 (± 6%) keV and 185 (± 5%) keV, respectively. Images were reconstructed with the manufacturer implementations of OSEM (GE-OSEM) and BSREM (Q.Clear) algorithms, and various combinations of iterations and subsets. Additionally, the manufacturer-recommended Q.Clear-based reconstruction protocol was evaluated. Quantification accuracy, measured as the difference between the SPECT-based and the radionuclide calibrator-based activity, and noise were evaluated in a large cylinder. Recovery coefficients (RCs) and spatial resolution were assessed in a NEMA IEC phantom with sphere inserts. The reconstruction protocols considered suitable for clinical applications were tested on a cohort of patients treated with [177Lu]Lu-PSMA-I&T.

RESULTS

The accuracy of the activity from the cylinder, although affected by septal penetration, was < 10% for all reconstructions. Both algorithms featured improved spatial resolution and higher RCs with increasing updates at the cost of noise build-up, but Q.Clear outperformed GE-OSEM in reducing noise accumulation. When the reconstruction parameters were carefully selected, similar values for noise (~0.15), spatial resolution (~1 cm) and RCs were found, irrespective of the reconstruction algorithm. Analogue results were found in patients.

CONCLUSIONS

Accurate activity quantification is possible when imaging 177Lu with StarGuide™. However, the impact of septal penetration requires further investigations. GE-OSEM is a valid alternative to the recommended Q.Clear reconstruction algorithm, featuring comparable performances assessed on phantoms and patients.

Reducing scan time in 177 Lu planar scintigraphy using convolutional neural network: A Monte Carlo simulation study

PURPOSE

The aim of this study was to reduce scan time in 177 Lu planar scintigraphy through the use of convolutional neural network (CNN) to facilitate personalized dosimetry for 177 Lu-based peptide receptor radionuclide therapy.

METHODS

The CNN model used in this work was based on DenseNet, and the training and testing datasets were generated from Monte Carlo simulation. The CNN input images (IMGinput ) consisted of 177 Lu planar scintigraphy that contained 10-90% of the total photon counts, while the corresponding full-count images (IMG100% ) were used as the CNN label images. Two-sample t-test was conducted to compare the difference in pixel intensities within region of interest between IMG100% and CNN output images (IMGoutput ).

RESULTS

No difference was found in IMGoutput for rods with diameters ranging from 13 to 33 mm in the Derenzo phantom with a target-to-background ratio of 20:1, while statistically significant differences were found in IMGoutput for the 10-mm diameter rods when IMGinput containing 10% to 60% of the total photon counts were denoised. Statistically significant differences were found in IMGoutput for both right and left kidneys in the NCAT phantom when IMGinput containing 10% of the total photon counts were denoised. No statistically significant differences were found in IMGoutput for any other source organs in the NCAT phantom.

CONCLUSION

Our results showed that the proposed method can reduce scan time by up to 70% for objects larger than 13 mm, making it a useful tool for personalized dosimetry in 177 Lu-based peptide receptor radionuclide therapy in clinical practice.

Physics-Guided Deep Scatter Estimation by Weak Supervision for Quantitative SPECT

Accurate scatter estimation is important in quantitative SPECT for improving image contrast and accuracy. With a large number of photon histories, Monte-Carlo (MC) simulation can yield accurate scatter estimation, but is computationally expensive. Recent deep learning-based approaches can yield accurate scatter estimates quickly, yet full MC simulation is still required to generate scatter estimates as ground truth labels for all training data. Here we propose a physics-guided weakly supervised training framework for fast and accurate scatter estimation in quantitative SPECT by using a 100× shorter MC simulation as weak labels and enhancing them with deep neural networks. Our weakly supervised approach also allows quick fine-tuning of the trained network to any new test data for further improved performance with an additional short MC simulation (weak label) for patient-specific scatter modelling. Our method was trained with 18 XCAT phantoms with diverse anatomies / activities and then was evaluated on 6 XCAT phantoms, 4 realistic virtual patient phantoms, 1 torso phantom and 3 clinical scans from 2 patients for 177Lu SPECT with single / dual photopeaks (113, 208 keV). Our proposed weakly supervised method yielded comparable performance to the supervised counterpart in phantom experiments, but with significantly reduced computation in labeling. Our proposed method with patient-specific fine-tuning achieved more accurate scatter estimates than the supervised method in clinical scans. Our method with physics-guided weak supervision enables accurate deep scatter estimation in quantitative SPECT, while requiring much lower computation in labeling, enabling patient-specific fine-tuning capability in testing.

Performance study of a 360° CZT camera for monitoring 177Lu-PSMA treatment

BACKGROUND

The aim of this study was to investigate the quantification performance of a 360° CZT camera for 177Lu-based treatment monitoring.

METHODS

Three phantoms with known 177Lu activity concentrations were acquired: (1) a uniform cylindrical phantom for calibration, (2) a NEMA IEC body phantom for analysis of different-sized spheres to optimise quantification parameters and (3) a phantom containing two large vials simulating organs at risk for tests. Four sets of reconstruction parameters were tested: (1) Scatter, (2) Scatter and Point Spread Function Recovery (PSFR), (3) PSFR only and (4) Penalised likelihood option and Scatter, varying the number of updates (iterations × subsets) with CT-based attenuation correction only. For each, activity concentration (ARC) and contrast recovery coefficients (CRC) were estimated as well as root mean square. Visualisation and quantification parameters were applied to reconstructed patient image data.

RESULTS

Optimised quantification parameters were determined to be: CT-based attenuation correction, scatter correction, 12 iterations, 8 subsets and no filter. ARC, CRC and RMS results were dependant on the methodology used for calculations. Two different reconstruction parameters were recommended for visualisation and for quantification. 3D whole-body SPECT images were acquired and reconstructed for 177Lu-PSMA patients in 2-3 times faster than the time taken for a conventional gamma camera.

CONCLUSION

Quantification of whole-body 3D images of patients treated with 177Lu-PSMA is feasible and an optimised set of parameters has been determined. This camera greatly reduces procedure time for whole-body SPECT.

Real-time in vivo dose measurement using ruby-based fibre optic dosimetry during internal radiation therapy

In vivo dosimetry (IVD) in a commonly used liver cancer treatment of selective internal radiation therapy (SIRT) has been done based on the post-treatment image-based dosimetry approach. Real-time IVD is necessary to verify the dose delivery and detect errors during the treatment for better patient outcomes. This study aims to develop a fibre optic dosimeter (FOD) for in vivo real-time dose rate measurement during internal beta radiation therapy, e.g., SIRT. A ruby fibre optic probe was prepared and studied the radioluminescence (RL) characteristics, including its major challenge of stem effect arising from Cherenkov radiation and luminescence from the irradiated fibre. The stem signal was suppressed adequately using the stem removal technique of optical filtering, and only 2.3 ± 1.1% stem signal was contributed to the measured RL signal. A linear dose rate response was observed during the exposure of the ruby probe to varying dose rates using a 6 MeV electron beam and a positron-emitting radionuclide fluorine-18. The ruby exhibited a temporally non-constant RL signal, which increased the RL signal by 0.84 ± 0.29 counts/sec2 during the irradiation of the maximum dose rate used in this study of 9 Gy/min for 2 min. The ability of ruby FOD to measure the absolute dose rate with sufficient stem effect suppression and the linear RL dose rate response indicates its suitability for real-time IVD during internal beta radiation therapy. Future work will investigate the time-dependent RL characteristic of ruby and validate post-treatment image-based dosimetry using ruby-based FOD.

Patient-specific biokinetics and hybrid 2D/3D approach integration in OEDIPE software: Application to radioiodine therapy

BACKGROUND

The progression of targeted radionuclide therapy requires the development of dosimetry software accounting for patient-specific biokinetics. New functionalities were thus developed in the OEDIPE software, to deal with multiple 3D images or multiple planar images and a SPECT image.

MATERIEL & METHOD

Methods were implemented to recover patient biokinetics in volumes of interest. If several 3D SPECT images are available, they are registered to a reference CT scan. When several planar images and a single SPECT are available, the planar images are registered to the SPECT and counts of the planar images converted to activity. To validate these developments, six SPECT/CT and planar images of a Jaszczak phantom containing I-131 were acquired at different dates. Cumulated activity was estimated in each sphere using the SPECT/CT images only or the planar series associated to one SPECT/CT. Biokinetics and doses in lesions and in the lungs of a patient treated with I-131 for differentiated thyroid cancer were then estimated using four planar images and a SPECT/CT scan. Whole-body retention data were used to compare the biokinetics obtained from the planar and SPECT data.

RESULTS

Activities and cumulated activities estimated using OEDIPE in the phantom spheres agreed well with the reference values for both approaches. Results obtained for the patient compared well with those derived from whole-body retention data.

CONCLUSION

The implemented features allow automatic evaluation of patient-specific biokinetics from different series of patient images, enabling patient-specific dosimetry without the need for external software to estimate the cumulated activities in different VOIs.

Updating 90Y Voxel S-Values including internal Bremsstrahlung: Monte Carlo study and development of an analytical model

PURPOSE

Internal Bremsstrahlung (IB) is a process accompanying β-decay but neglected in Voxel S-Values (VSVs) calculation. Aims of this work were to calculate, through Monte Carlo (MC) simulation, updated 90Y-VSVs including IB, and to develop an analytical model to evaluate 90Y-VSVs for any voxel size of practical interest.

METHODS

GATE (Geant4 Application for Tomographic Emission) was employed for simulating voxelized geometries of soft tissue, with voxels sides l ranging from 2 to 6 mm, in steps of 0.5 mm. The central voxel was set as a homogeneous source of 90Y when IB photons are not modelled. For each l, the VSVs were computed for 90Y decays alone and for 90Y + IB. The analytical model was then built through fitting procedures of the VSVs including IB contribution.

RESULTS

Comparing GATE-VSVs with and without IB, differences between + 25% and + 30% were found for distances from the central voxel larger than the maximum β-range. The analytical model showed an agreement with MC simulations within ± 5% in the central voxel and in the Bremsstrahlung tails, for any l value examined, and relative differences lower than ± 40%, for other distances from the source.

CONCLUSIONS

The presented 90Y-VSVs include for the first time the contribution due to IB, thus providing a more accurate set of dosimetric factors for three-dimensional internal dosimetry of 90Y-labelled radiopharmaceuticals and medical devices. Furthermore, the analytical model constitutes an easy and fast alternative approach for 90Y-VSVs estimation for non-standard voxel dimensions.

An International Study of Factors Affecting Variability of Dosimetry Calculations, Part 2: Overall Variabilities in Absorbed Dose

Dosimetry for personalized radiopharmaceutical therapy has gained considerable attention. Many methods, tools, and workflows have been developed to estimate absorbed dose (AD). However, standardization is still required to reduce variability of AD estimates across centers. One effort for standardization is the Society of Nuclear Medicine and Molecular Imaging 177Lu Dosimetry Challenge, which comprised 5 tasks (T1-T5) designed to assess dose estimate variability associated with the imaging protocol (T1 vs. T2 vs. T3), segmentation (T1 vs. T4), time integration (T4 vs. T5), and dose calculation (T5) steps of the dosimetry workflow. The aim of this work was to assess the overall variability in AD calculations for the different tasks. Methods: Anonymized datasets consisting of serial planar and quantitative SPECT/CT scans, organ and lesion contours, and time-integrated activity maps of 2 patients treated with 177Lu-DOTATATE were made available globally for participants to perform dosimetry calculations and submit their results in standardized submission spreadsheets. The data were carefully curated for formal mistakes and methodologic errors. General descriptive statistics for ADs were calculated, and statistical analysis was performed to compare the results of different tasks. Variability in ADs was measured using the quartile coefficient of dispersion. Results: ADs to organs estimated from planar imaging protocols (T2) were lower by about 60% than those from pure SPECT/CT (T1), and the differences were statistically significant. Importantly, the average differences in dose estimates when at least 1 SPECT/CT acquisition was available (T1, T3, T4, T5) were within ±10%, and the differences with respect to T1 were not statistically significant for most organs and lesions. When serial SPECT/CT images were used, the quartile coefficients of dispersion of ADs for organs and lesions were on average less than 20% and 26%, respectively, for T1; 20% and 18%, respectively, for T4 (segmentations provided); and 10% and 5%, respectively, for T5 (segmentation and time-integrated activity images provided). Conclusion: Variability in ADs was reduced as segmentation and time-integration data were provided to participants. Our results suggest that SPECT/CT-based imaging protocols generate more consistent and less variable results than planar imaging methods. Effort at standardizing segmentation and fitting should be made, as this may substantially reduce variability in ADs.

Influence on voxel-based dosimetry: noise effect on absorbed dose dosimetry at single time-point versus sequential single-photon emission computed tomography

OBJECTIVE

The purpose of this study was to evaluate how statistical fluctuation in single-photon emission computed tomography (SPECT) images propagate to absorbed dose maps.

METHODS

SPECT/computed tomography (CT) images of iodine-131 filled phantoms, using different acquisition and processing protocols, were evaluated using STRATOS software to assess the absorbed dose distribution at the voxel level. Absorbed dose values and coefficient of variation (COV) were analyzed for dosimetry based on single time-point SPECT images and time-integrated activities of SPECT sequences with low and high counts.

RESULTS

Considering dosimetry based on a single time-point, the mean absorbed dose was not significantly affected by total counts or reconstruction parameters, but the uniformity of the absorbed dose maps had an almost linear correlation with SPECT noise. When high- and low-count SPECT sequences were used to generate an absorbed dose map, the absorbed dose COV for each of the temporal sequences was slightly lower than the absorbed dose COV based on the single SPECT image with the highest count included in the sequence.

CONCLUSION

The impact of changes in SPECT counts and reconstruction parameters is almost linear when dosimetry is based on isolated SPECT images, but less pronounced when dosimetry is based on sequential SPECTs.

Dosimetric assessment of Gadolinium-159 for hepatic radioembolization: Tomographic images and Monte Carlo simulation

A common therapeutic radionuclide used in hepatic radioembolization is yttrium-90 (⁹⁰Y). However, the absence of gamma emissions makes it difficult to verify the post-treatment distribution of ⁹⁰Y microspheres. Gadolinium-159 (¹⁵⁹Gd) has physical properties that are suitable for therapy and post-treatment imaging in hepatic radioembolization procedures. The current study is innovative for conducting a dosimetric investigation of the use of ¹⁵⁹Gd in hepatic radioembolization by simulating tomographic images using the Geant4 application for tomographic emission (GATE) Monte Carlo (MC) simulation. For registration and segmentation, tomographic images of five patients with hepatocellular carcinoma (HCC) who had undergone transarterial radioembolization (TARE) therapy were processed using a 3D slicer. The tomographic images with ¹⁵⁹Gd and ⁹⁰Y separately were simulated using the GATE MC Package. The output of simulation (dose image) was uploaded to 3D slicer to compute the absorbed dose for each organ of interests. ¹⁵⁹Gd were able to provide a recommended dose of 120 Gy to the tumour, with normal liver and lungs absorbed doses close to that of ⁹⁰Y and less than the respective maximum permitted doses of 70 Gy and 30 Gy, respectively. Compared to ⁹⁰Y, ¹⁵⁹Gd requires higher administered activity approximately 4.92 times to achieve a tumour dose of 120 Gy. Thus; this research gives new insights into the use of ¹⁵⁹Gd as a theranostic radioisotope, with the potential to be used as a⁹⁰Y alternative for liver radioembolization.

Activity recovery for differently shaped objects in quantitative SPECT

Objective.The aim was to theoretically and experimentally investigate recovery in SPECT images with objects of different shapes. Furthermore, the accuracy of volume estimation by thresholding was studied for those shapes.Approach.Nine spheres, nine oblate spheroids, and nine prolate spheroids phantom inserts were used, of which the six smaller spheres were part of the NEMA IEC body phantom and the rest of the inserts were 3D-printed. The inserts were filled with99mTc and177Lu. When filled with99mTc, SPECT images were acquired in a Siemens Symbia Intevo Bold gamma camera and when filled with177Lu in a General Electric NM/CT 870 DR gamma camera. The signal rate per activity (SRPA) was determined for all inserts and represented as a function of the volume-to-surface ratio and of the volume-equivalent radius using VOIs defined according to the sphere dimensions and VOIs defined using thresholding. Experimental values were compared with theoretical curves obtained analytically (spheres) or numerically (spheroids), starting from the convolution of a source distribution with a point-spread function. Validation of the activity estimation strategy was performed using four 3D-printed ellipsoids. Lastly, the threshold values necessary to determine the volume of each insert were obtained.Main results.Results showed that SRPA values for the oblate spheroids diverted from the other inserts, when SRPA were represented as a function of the volume-equivalent radius. However, SRPA values for all inserts followed a similar behaviour when represented as a function of the volume-to-surface ratio. Results for ellipsoids were in agreement with those results. For the three types of inserts the volume could be accurately estimated using a threshold method for volumes larger than 25 ml.Significance.Determination of SRPA independently of lesion or organ shape should decrease uncertainties in estimated activities and thereby, in the long term, be beneficial to patient care.

Validation of automated image co-registration integrated into in-house software for voxel-based internal dosimetry on single-photon emission computed tomography images

Objective

To develop an automated co-registration system and test its performance, with and without a fiducial marker, on single-photon emission computed tomography (SPECT) images.

Materials and Methods

Three SPECT/CT scans were acquired for each rotation of a Jaszczak phantom (to 0°, 5°, and 10° in relation to the bed axis), with and without a fiducial marker. Two rigid co-registration software packages-SPM12 and NMDose-coreg-were employed, and the percent root mean square error (%RMSE) was calculated in order to assess the quality of the co-registrations. Uniformity, contrast, and resolution were measured before and after co-registration. The NMDose-coreg software was employed to calculate the renal doses in 12 patients treated with 177Lu-DOTATATE, and we compared those with the values obtained with the Organ Level INternal Dose Assessment for EXponential Modeling (OLINDA/EXM) software.

Results

The use of a fiducial marker had no significant effect on the quality of co-registration on SPECT images, as measured by %RMSE (p = 0.40). After co-registration, uniformity, contrast, and resolution did not differ between the images acquired with fiducial markers and those acquired without. Preliminary clinical application showed mean total processing times of 9 ± 3 min/patient for NMDose-coreg and 64 ± 10 min/patient for OLINDA/EXM, with a strong correlation between the two, despite the lower renal doses obtained with NMDose-coreg.

Conclusion

The use of NMDose-coreg allows fast co-registration of SPECT images, with no loss of uniformity, contrast, or resolution. The use of a fiducial marker does not appear to increase the accuracy of co-registration on phantoms.

Voxel-Based Internal Dosimetry for 177Lu-Labeled Radiopharmaceutical Therapy Using Deep Residual Learning

Purpose

In this study, we propose a deep learning (DL)-based voxel-based dosimetry method in which dose maps acquired using the multiple voxel S-value (VSV) approach were used for residual learning.

Methods

Twenty-two SPECT/CT datasets from seven patients who underwent 177Lu-DOTATATE treatment were used in this study. The dose maps generated from Monte Carlo (MC) simulations were used as the reference approach and target images for network training. The multiple VSV approach was used for residual learning and compared with dose maps generated from deep learning. The conventional 3D U-Net network was modified for residual learning. The absorbed doses in the organs were calculated as the mass-weighted average of the volume of interest (VOI).

Results

The DL approach provided a slightly more accurate estimation than the multiple-VSV approach, but the results were not statistically significant. The single-VSV approach yielded a relatively inaccurate estimation. No significant difference was noted between the multiple VSV and DL approach on the dose maps. However, this difference was prominent in the error maps. The multiple VSV and DL approach showed a similar correlation. In contrast, the multiple VSV approach underestimated doses in the low-dose range, but it accounted for the underestimation when the DL approach was applied.

Conclusion

Dose estimation using the deep learning-based approach was approximately equal to that in the MC simulation. Accordingly, the proposed deep learning network is useful for accurate and fast dosimetry after radiation therapy using 177Lu-labeled radiopharmaceuticals.

Biodistribution and dosimetry for combined [177Lu]Lu-PSMA-I&T/[225Ac]Ac-PSMA-I&T therapy using multi-isotope quantitative SPECT imaging

PURPOSE

Quantitative SPECT for patient-specific dosimetry is a valuable tool in the scope of radionuclide therapy, although its clinical application for ²²⁵Ac-based treatments may be limited due to low therapeutic activities. Therefore, the aim of this study was to demonstrate the feasibility of clinical quantitative low-count SPECT imaging during [¹⁷⁷Lu]Lu-PSMA-I&T/[²²⁵Ac]Ac-PSMA-I&T treatment.

METHODS

Eight prostate cancer patients (1000 MBq/8 MBq [¹⁷⁷Lu]Lu-PSMA-I&T/[²²⁵Ac]Ac-PSMA-I&T) received a single-bed quantitative ¹⁷⁷Lu/²²⁵Ac SPECT/CT acquisition (1 h) at 24 h post treatment (high-energy collimator, 16 projections p. head à 3.5 min, 128 × 128 pixel). The gamma peak at 440 keV (width: 10%) of the progeny ²¹³Bi was imaged along with the peak at 208 keV (width: 15%) of ¹⁷⁷Lu. Quantification included CT-based attenuation and window-based scatter correction plus resolution modelling. Gaussian post-filtering with a full-width-half-maximum of 30 mm and 40-45 mm was employed to match the signal-to-noise ratio of ²²⁵Ac and ¹⁷⁷Lu, respectively.

RESULTS

Kidney (r = 0.96, p < 0.01) and lesion (r = 0.94, p < 0.01) SUV for [¹⁷⁷Lu]Lu-PSMA-I&T and [²²⁵Ac]Ac-PSMA-I&T showed a strong and significant correlation. Kidney SUV were significantly higher (p < 0.01) for [²²⁵Ac]Ac-PSMA-I&T (2.5 ± 0.8 vs. 2.1 ± 0.9), while for [¹⁷⁷Lu]Lu-PSMA-I&T lesion SUV were significantly higher (p = 0.03; 1.8 ± 1.1 vs. 2.1 ± 1.5). For absorbed dose estimates, significant differences regarding the kidneys remained, while no significant differences for lesion dosimetry were found.

CONCLUSION

Quantitative low-count SPECT imaging of the peak at 440 keV during [²²⁵Ac]Ac-PSMA-I&T therapy is feasible. Multi-isotope imaging for [¹⁷⁷Lu]Lu-PSMA-I&T/[²²⁵Ac]Ac-PSMA-I&T therapy indicates accumulation of free ²¹³Bi in the kidneys.

Technical note: The contribution of internal bremsstrahlung to the 90 Y dose point kernel

BACKGROUND

Internal dosimetry has an increasing role in the planning and verification of nuclear medicine therapies with radiopharmaceuticals. Dose Point Kernels (DPKs), quantifying the energy deposition all around a point source, in a homogenous medium, are extensively used for 3D dosimetry and nowadays are mostly evaluated by Monte Carlo (MC) simulation. To our knowledge, DPK for beta emitters is estimated neglecting the continuous photon emission due to the Internal Bremsstrahlung (IB), whose contribution to the absorbed dose can be relevant beyond the maximum range of betas, as evidenced in recent works.

PURPOSE

Aim of this study was to investigate and quantify, by means of MC simulations, the contribution of IB photons to DPK calculated for ⁹⁰ Y and provide the updated ⁹⁰ Y DPK.

METHODS

The overall radiation due to the decay of a ⁹⁰ Y point source, placed at the centre of concentric water shells of increasing radii from 0.02 cm to 20 cm, was simulated with GAMOS, including the IB source term whose spectral distribution was described by an analytical model. Energy deposition was scored in the shells as a function of the distance from the source, R, and DPK was estimated in terms of the scaled absorbed dose fraction, F(R/X₉₀ ), where X₉₀ is the range within which the beta particles deposit 90% of their energy.

RESULTS

A comparison between the two simulated absorbed dose distributions, calculated with or without IB, clearly shows that the latter (incomplete) choice is consistent with the findings of other Authors and systematically underestimates the absorbed dose imparted to the tissue. ⁹⁰ Y DPK values currently used are underestimated by 20%-34% for R>2X₉₀ .

CONCLUSIONS

The revised values provided in this work suggest that the inclusion of IB emission in DPK evaluations is advisable for pure beta emitters.

SPECT/CT-based dosimetry of salivary glands and iodine-avid lesions following 131I therapy

Objective

The purpose was to provide uptake and radiation dose estimates to salivary glands (SG) and pathologic lesions following radioiodine therapy (RIT) of differentiated thyroid cancer patients (DTC).

Methods

A group of DTC patients (n = 25) undergoing ¹³¹I therapy joined this study with varying amounts of therapeutic activity. Sequential SPECT/CT scans were acquired at 4 ± 2, 24 ± 2, and 168 ± 3 h following administration of 3497-9250 MBq 131I. An earlier experiment with Acrylic glass body phantom (PET Phantom NEMA 2012 / IEC 2008) was conducted for system calibration including scatter, partial volume effect and count loss correction. Dose calculation was made via IDAC-Dose 2.1 code.

Results

The absorbed dose to parotid glands was 0.04-0.97 Gy/GBq (median: 0.26 Gy/GBq). The median absorbed dose to submandibular glands was 0.14 Gy/GBq (0.05 to 0.56 Gy/GBq). The absorbed dose to thyroid residues was from 0.55 to 399.5 Gy/GBq (median: 21.8 Gy/GBq), and that to distal lesions ranged from 0.78 to 28.0 Gy/GBq (median: 3.12 Gy/GBq). 41% of the thyroid residues received dose > 80 Gy, 18% between 70-80 Gy, 18% between 40-70 Gy, and 23% has dose < 40 Gy. In contrast, 18% of the metastases exhibited a dose > 80 Gy, 9% between 40-60 Gy, and the dose to the vast majority of lesions (64%) was < 40 Gy.

Conclusion

It was inferred that dose estimation after RIT with SPECT/CT is feasible to apply, together with good agreement with published ¹²⁴I PET/CT dose estimates. A broad and sub-effective dose range was estimated for thyroid residues and distal lesions. Moreover, the current methodology might be useful for establishing a dose-effect relationship and radiation-induced salivary glands damage after RIT.

EANM practice guideline for quantitative SPECT-CT

PURPOSE

Quantitative SPECT-CT is a modality of growing importance with initial developments in post radionuclide therapy dosimetry, and more recent expansion into bone, cardiac and brain imaging together with the concept of theranostics more generally. The aim of this document is to provide guidelines for nuclear medicine departments setting up and developing their quantitative SPECT-CT service with guidance on protocols, harmonisation and clinical use cases.

METHODS

These practice guidelines were written by members of the European Association of Nuclear Medicine Physics, Dosimetry, Oncology and Bone committees representing the current major stakeholders in Quantitative SPECT-CT. The guidelines have also been reviewed and approved by all EANM committees and have been endorsed by the European Association of Nuclear Medicine.

CONCLUSION

The present practice guidelines will help practitioners, scientists and researchers perform high-quality quantitative SPECT-CT and will provide a framework for the continuing development of quantitative SPECT-CT as an established modality.

Treatment-naïve idiopathic inflammatory myopathy: disease evaluation by fluorodeoxyglucose versus pyrophosphate

Background

Imaging of idiopathic inflammatory myopathies (IIMs) is challenging, and no pathognomonic signs exist. Different tracers have been tested for this purpose, mainly inflammation markers including technetium-99m-pyrophosphate (PYP). We aimed to examine the utility of fluorine-18-fluorodeoxyglucose (FDG) relative to PYP in idiopathic inflammatory myopathy (IIM).

Methods

Using visual grading and CT-guided muscular segmentation and standardized uptake values (SUVs), we assessed muscular tracer uptake qualitatively and quantitatively, comparing FDG uptake in eight patients with recent-onset IIM and 24 healthy control persons and FDG and PYP uptake in seven patients.

Results

Muscular FDG and PYP uptake was increased in all patients. However, uptake distribution and signal intensity differed considerably. FDG scans revealed clear involvement of certain muscle groups including core and swallowing muscles and, in addition, abnormality in diseased extra-muscular organs. PYP was mainly visible in bones, whereas muscular PYP uptake was generally discrete and primarily located in the extremities. Quantitatively, FDG uptake was significantly higher in patients than in controls; the volume-weighted SUVmean for all right-side muscles was 0.84 versus 0.60 g/ml (95% confidence interval (CI) for mean difference 0.14–0.34, p = 0.0001). FDG SUVmean values were up to four times higher than PYP mean values in upper limb muscles (95% CI for the mean ratio 2.37–3.77, p = 0.0004) and two–three times higher in lower limb muscles (95% CI for the mean ratio 2.28–2.71, p < 0.0001).

Conclusions

Muscular FDG uptake was higher in treatment-naïve IIM patients than in healthy controls and more distinct than PYP uptake in patients with a potential to reveal extra-muscular IIM involvement and malignancy. Thus, FDG appears to be superior to PYP in the diagnostic evaluation of IIM.

Joint EANM, SNMMI, and IAEA Enabling Guide: How to Set up a Theranostics Center

The theranostics concept using the same target for both imaging and therapy dates back to the middle of the last century, when radioactive iodine was first used to treat thyroid diseases. Since then, radioiodine has become broadly established clinically for diagnostic imaging and therapy of benign and malignant thyroid disease, worldwide. However, only since the approval of SSTR2-targeting theranostics following the NETTER-1 trial in neuroendocrine tumors, and the positive outcome of the VISION trial has theranostics gained substantial attention beyond nuclear medicine. The roll-out of radioligand therapy for treating a high-incidence tumor such as prostate cancer requires the expansion of existing and the establishment of new theranostics centers. Despite wide global variation in the regulatory, financial and medical landscapes, this guide attempts to provide valuable information to enable interested stakeholders to safely initiate and operate theranostic centers. This enabling guide does not intend to answer all possible questions, but rather to serve as an overarching framework for multiple, more detailed future initiatives. It recognizes that there are regional differences in the specifics of regulation of radiation safety, but common elements of best practice valid globally.

Heterogeneity of dose distribution in normal tissues in case of radiopharmaceutical therapy with alpha-emitting radionuclides

Heterogeneity of dose distribution has been shown at different spatial scales in diagnostic nuclear medicine. In cancer treatment using new radiopharmaceuticals with alpha-particle emitters, it has shown an extensive degree of dose heterogeneity affecting both tumour control and toxicity of organs at risk. This review aims to provide an overview of generalized internal dosimetry in nuclear medicine and highlight the need of consideration of the dose heterogeneity within organs at risk. The current methods used for patient dosimetry in radiopharmaceutical therapy are summarized. Bio-distribution and dose heterogeneities of alpha-particle emitting pharmaceutical ²²³Ra (Xofigo) within bone tissues are presented as an example. In line with the strategical research agendas of the Multidisciplinary European Low Dose Initiative (MELODI) and the European Radiation Dosimetry Group (EURADOS), future research direction of pharmacokinetic modelling and dosimetry in patient radiopharmaceutical therapy are recommended.

Dosimetry in Radiopharmaceutical Therapy

The application of radiopharmaceutical therapy for the treatment of certain diseases is well established, and the field is expanding. New therapeutic radiopharmaceuticals have been developed in recent years, and more are in the research pipeline. Concurrently, there is growing interest in the use of internal dosimetry as a means of personalizing, and potentially optimizing, such therapy for patients. Internal dosimetry is multifaceted, and the current state of the art is discussed in this continuing education article. Topics include the context of dosimetry, internal dosimetry methods, the advantages and disadvantages of incorporating dosimetry calculations in radiopharmaceutical therapy, a description of the workflow for implementing patient-specific dosimetry, and future prospects in the field.

Impact of radiopharmaceutical therapy (177Lu, 225Ac) microdistribution in a cancer-associated fibroblasts model

Background

The aim of this study is to elucidate the difference in absorbed dose (D_abs) patterns in radiopharmaceutical therapies between alpha emitters (²²⁵Ac) and beta emitters (¹⁷⁷Lu) when targeting cancer-associated fibroblasts (CAF) or tumor cells. Five spherical models with 3 mm diameter were created, representing spherical tumor masses that contain tumor clusters, interspersed with CAFs. The mean distance from a tumor cell to the nearest CAF (L_mean) varied throughout these models from 92 to 1030 µm. D_abs calculations were performed while selecting either CAFs or tumor cells as sources, with Convolution/Superposition with ¹⁷⁷Lu and Monte Carlo simulations (GATE) with ²²⁵Ac. Analyses were conducted with Dose Volume Histograms and efficacy ratios (ER), which represents the ratio of mean D_abs that is deposited in the target volume.

Results

²²⁵Ac is the most optimal radionuclide when CAFs are both targeted and irradiating themselves, as ERs increase from 1.5 to 3.7 when L_mean increases from 92 to 1030 µm. With ¹⁷⁷Lu, these numbers vary from 1.2 to 2.7. Conversely, when CAFs are sources and tumors are targets with ²²⁵Ac, ERs decreased from 0.8 to 0.1 when L_mean increases from 92 to 1030 µm. With ¹⁷⁷Lu, these numbers vary from 0.9 to 0.3

Conclusion

When targeting CAFs to irradiate tumors, the efficacy of using ²²⁵Ac decreases as the average size of the tumor clusters (or L_mean) increases. In such situations, ¹⁷⁷Lu will be more effective than ²²⁵Ac when targeting CAFs due to the longer beta particle range.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40658-022-00497-5.

A Review on Tumor Control Probability (TCP) and Preclinical Dosimetry in Targeted Radionuclide Therapy (TRT)

Targeted radionuclide therapy (TRT) uses radiopharmaceuticals to specifically irradiate tumor cells while sparing healthy tissue. Response to this treatment highly depends on the absorbed dose. Tumor control probability (TCP) models aim to predict the tumor response based on the absorbed dose by taking into account the different characteristics of TRT. For instance, TRT employs radiation with a high linear energy transfer (LET), which results in an increased effectiveness. Furthermore, a heterogeneous radiopharmaceutical distribution could result in a heterogeneous dose distribution at a tissue, cellular as well as subcellular level, which will generally reduce the tumor response. Finally, the dose rate in TRT is protracted, relatively low, and variable over time. This allows cells to repair more DNA damage, which may reduce the effectiveness of TRT. Within this review, an overview is given on how these characteristics can be included in TCP models, while some experimental findings are also discussed. Many parameters in TCP models are preclinically determined and TCP models also play a role in the preclinical stage of radiopharmaceutical development; however, this all depends critically on the calculated absorbed dose. Accordingly, an overview of the existing preclinical dosimetry methods is given, together with their limitation and applications. It can be concluded that although the theoretical extension of TCP models from external beam radiotherapy towards TRT has been established quite well, the experimental confirmation is lacking. Thus, requiring additional comprehensive studies at the sub-cellular, cellular, and organ level, which should be provided with accurate preclinical dosimetry.

Personalized Dosimetry in the Context of Radioiodine Therapy for Differentiated Thyroid Cancer

The most frequent thyroid cancer is Differentiated Thyroid Cancer (DTC) representing more than 95% of cases. A suitable choice for the treatment of DTC is the systemic administration of 131-sodium or potassium iodide. It is an effective tool used for the irradiation of thyroid remnants, microscopic DTC, other nonresectable or incompletely resectable DTC, or all the cited purposes. Dosimetry represents a valid tool that permits a tailored therapy to be obtained, sparing healthy tissue and so minimizing potential damages to at-risk organs. Absorbed dose represents a reliable indicator of biological response due to its correlation to tissue irradiation effects. The present paper aims to focus attention on iodine therapy for DTC treatment and has developed due to the urgent need for standardization in procedures, since no unique approaches are available. This review aims to summarize new proposals for a dosimetry-based therapy and so explore new alternatives that could provide the possibility to achieve more tailored therapies, minimizing the possible side effects of radioiodine therapy for Differentiated Thyroid Cancer.

ASTRO's Framework for Radiopharmaceutical Therapy Curriculum Development for Trainees

In 2017, the American Society for Radiation Oncology (ASTRO) board of directors prioritized radiopharmaceutical therapy (RPT) as a leading area for new therapeutic development, and the ASTRO RPT workgroup was created. Herein, the workgroup has developed a framework for RPT curriculum development upon which education leaders can build to integrate this modality into radiation oncology resident education. Through this effort, the workgroup aims to provide a guide to ensure robust training in an emerging therapeutic area within the context of existing radiation oncology training in radiation biology, medical physics, and clinical radiation oncology. The framework first determines the core RPT knowledge required to select patients, prescribe, safely administer, and manage related adverse events. Then, it defines the most important topics for preparing residents for clinical RPT planning and delivery. This framework is designed as a tool to supplement the current training that exists for radiation oncology residents. The final document was approved by the ASTRO board of directors in the fall of 2021.

Reconstructed SPECT images of 177Lu homogeneous cylindrical phantom used for calibration and texture analysis

In a clinical contest, it is common to use dedicated phantoms to perform quality assurance test to check the performance of a SPECT system. Some of these phantoms are also used to calibrate the system for dosimetric evaluation of patients undergoing radiometabolic cancer therapy. In this work, a 3D-OSEM reconstructed ¹⁷⁷Lu SPECT dataset of a homogeneous cylindrical phantom is described. This dataset was acquired to investigate the variation of the SPECT calibration factor, counts convergence, noise and uniformity by varying the number of subsets and iterations. In particular, the dataset is composed of images reconstructed using five different numbers of subsets and sixteen different numbers of iterations, for a total of 80 different configurations. The dataset is suitable for comparison with other reconstruction algorithms (e.g. FBP, MLEM, etc.) and radionuclides (e.g. technetium, yttrium). In regards to the uniformity issue, the same dataset allows the user to perform radiomic investigations on the influence of the border effect on the reconstructed images.

Measurement(s)	Calibration Factor • coefficient of variation • Texture Descriptor
Technology Type(s)	Single Photon Emission Computed Tomography • Image Feature

Milestones in dosimetry for nuclear medicine therapy

Nuclear Medicine therapy has reached a critical juncture with an unprecedented number of patients being treated and an extensive list of new radiopharmaceuticals under development. Since the early applications of these treatments dosimetry has played a vital role in their development, in both aiding optimisation and enhancing safety and efficacy. To inform the future direction of this field, it is useful to reflect on the scientific and technological advances that have occurred since those early uses. In this review, we explore how dosimetry has evolved over the years and discuss why such initiatives were conceived and the importance of maintaining standards within our practise. Specific milestones and landmark publications are highlighted and a thematic review and significant outcomes during each decade are presented.

Application of machine learning to pretherapeutically estimate dosimetry in men with advanced prostate cancer treated with 177Lu-PSMA I&T therapy

Purpose

Although treatment planning and individualized dose application for emerging prostate-specific membrane antigen (PSMA)-targeted radioligand therapy (RLT) are generally recommended, it is still difficult to implement in practice at the moment. In this study, we aimed to prove the concept of pretherapeutic prediction of dosimetry based on imaging and laboratory measurements before the RLT treatment.

Methods

Twenty-three patients with metastatic castration-resistant prostate cancer (mCRPC) treated with ¹⁷⁷Lu-PSMA I&T RLT were included retrospectively. They had available pre-therapy ⁶⁸ Ga-PSMA-HEBD-CC PET/CT and at least 3 planar and 1 SPECT/CT imaging for dosimetry. Overall, 43 cycles of ¹⁷⁷Lu-PSMA I&T RLT were applied. Organ-based standard uptake values (SUVs) were obtained from pre-therapy PET/CT scans. Patient dosimetry was calculated for the kidney, liver, spleen, and salivary glands using Hermes Hybrid Dosimetry 4.0 from the planar and SPECT/CT images. Machine learning methods were explored for dose prediction from organ SUVs and laboratory measurements. The uncertainty of these dose predictions was compared with the population-based dosimetry estimates. Mean absolute percentage error (MAPE) was used to assess the prediction uncertainty of estimated dosimetry.

Results

An optimal machine learning method achieved a dosimetry prediction MAPE of 15.8 ± 13.2% for the kidney, 29.6% ± 13.7% for the liver, 23.8% ± 13.1% for the salivary glands, and 32.1 ± 31.4% for the spleen. In contrast, the prediction based on literature population mean has significantly larger MAPE (p < 0.01), 25.5 ± 17.3% for the kidney, 139.1% ± 111.5% for the liver, 67.0 ± 58.3% for the salivary glands, and 54.1 ± 215.3% for the spleen.

Conclusion

The preliminary results confirmed the feasibility of pretherapeutic estimation of treatment dosimetry and its added value to empirical population-based estimation. The exploration of dose prediction may support the implementation of treatment planning for RLT.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-022-05883-w.

Relevance of artefacts in 99mTc-MAA SPECT scans on pre-therapy patient-specific 90Y TARE internal dosimetry: a GATE Monte Carlo study

Objective. The direct Monte Carlo (MC) simulation of radiation transport exploiting morphological and functional tomographic imaging as input data is considered the gold standard for internal dosimetry in nuclear medicine, and it is increasingly used in studies regarding trans-arterial radio-embolization (TARE). However, artefacts affecting the functional scans, such as reconstruction artefacts and motion blurring, decrease the accuracy in defining the radionuclide distribution in the simulations and consequently lead to errors in absorbed dose estimations. In this study, the relevance of such artefacts in patient-specific three-dimensional MC dosimetry was investigated in three cases of 90Y TARE. Approach. The pre-therapy 99mTc MacroAggregate Albumin (Tc-MAA) SPECTs and CTs of patients were used as input for simulations performed with the GEANT4-based toolkit GATE. Several pre-simulation SPECT-masking techniques were implemented, with the aim of zeroing the decay probability in air, in lungs, or in the whole volume outside the liver. Main results. Increments in absorbed dose up to about +40% with respect to the native-SPECT simulations were found in liver-related volumes of interest (VOIs), depending on the masking procedure adopted. Regarding lungs-related VOIs, decrements in absorbed doses in right lung as high as −90% were retrieved. Significance. These results highlight the relevant influence of SPECT artefacts, if not properly treated, on dosimetric outcomes for 90Y TARE cases. Well-designed SPECT-masking techniques appear to be a promising way to correct for such misestimations.