The evidence base for the use of internal dosimetry in the clinical practice of molecular radiotherapy

Rethinking Dosimetry: A European Perspective

Radiopharmaceutical therapy (RPT) is entering a new era of personalization, driven by advances in molecular imaging, radiopharmaceutical development, and a growing body of clinical evidence linking absorbed dose to treatment outcomes. Although external-beam radiotherapy has long integrated dosimetry into standard practice, RPT historically relied on fixed radiopharmaceutical activities and absorbed dose-effect relationships adapted from external-beam radiotherapy, often without accounting for the unique pharmacokinetics, absorbed dose rate dynamics, and biologic responses of systemically administered radiopharmaceuticals. As RPT expands into earlier disease stages, at which patients have longer life expectancies and better performance status, the role of dosimetry in optimizing treatment is becoming increasingly evident. However, despite growing recognition of its benefits, the implementation of dosimetry in clinical practice remains limited, partly because of a self-reinforcing cycle in which the lack of routine dosimetry limits clinical evidence, which in turn hinders its broader adoption. Breaking this cycle is essential to advancing RPT and ensuring that evaluation of dosimetry is based on clinical merit rather than logistic constraints. This article examines the current landscape of RPT dosimetry, highlighting key challenges and opportunities from a European perspective and aiming to foster a more factual and constructive discussion on the topic. We discuss the fundamental differences between dosimetry-driven treatment planning and posttherapy absorbed dose verification, emphasizing the latter as a practical entry point for clinical adoption. We underscore the need for harmonized standards, improved imaging resolution, and tailored absorbed dose-effect relationships that reflect the heterogeneity of RPT delivery and the complexity of tumor and organ responses. The paper also addresses regulatory, infrastructural, and resource barriers to RPT dosimetry implementation and highlights ongoing European initiatives to strengthen frameworks, enhance stakeholder collaboration, and integrate absorbed dose biomarkers into authorization processes and clinical decision-making. By rethinking dosimetry and promoting standardized, evidence-based approaches, the field can advance beyond fixed-activity protocols toward truly individualized RPT. However, achieving clinically feasible integration of dosimetry into routine practice requires structured efforts to generate high-quality clinical evidence and improve accessibility. Ultimately, reliable, patient-centered dosimetry has the potential to enhance therapeutic efficacy, manage toxicity more effectively, and support the long-term evolution of RPT as a cornerstone of precision oncology.

Analysis of dosimetry and clinical variables in treatments of neuroendocrine tumours with [177Lu]Lu-DOTA-TATE

PURPOSE

The main objectives were to study differences between the first and the fourth cycle in dosimetry variables in patients treated for neuroendocrine tumours with four cycles of [177Lu]Lu-DOTA-TATE, as well as to look for absorbed dose-effect correlations aiming to help individualise and optimise this therapy for future patients.

MATERIAL AND METHODS

SPECT/CT based dosimetry of tumour lesions and kidneys was performed in the first and the fourth cycles of the [177Lu]Lu-DOTA-TATE treatments for 17 patients from 2020 to 2023. Clinical variables of interest were collected in order to look for correlations with some dosimetry variables. Statistical analysis was performed using the R software.

RESULTS

Regarding dosimetry variables, for lesions a significant decrease in absorbed dose, mass and initial activity between the first and fourth cycles was observed. For kidneys, a significant increase in absorbed dose was observed. Effective decay constants did not significantly change neither for lesions nor for kidneys. The relative decrease in lesion masses correlated with their total absorbed dose. Total absorbed doses to kidneys were well below the toxicity limits mostly used in this therapy. Relative decrease in lesion absorbed doses was significantly lower for tumour primary sites in ileum and jejunum compared to those in pancreas. Moreover, radiological response correlated with clinical response.

CONCLUSIONS

The results seem to indicate that the current treatment scheme could be optimised in order to obtain better treatment outcomes.

Computational Nuclear Oncology Toward Precision Radiopharmaceutical Therapies: Current Tools, Techniques, and Uncharted Territories

Radiopharmaceutical therapy (RPT), with its targeted delivery of cytotoxic ionizing radiation, demonstrates significant potential for treating a wide spectrum of malignancies, with particularly unique benefits for metastatic disease. There is an opportunity to optimize RPTs and enhance the precision of theranostics by moving beyond a one-size-fits-all approach and using patient-specific image-based dosimetry for personalized treatment planning. Such an approach, however, requires accurate methods and tools for the mathematic modeling and prediction of dose and clinical outcome. To this end, the SNMMI AI-Dosimetry Working Group is promoting the paradigm of computational nuclear oncology: mathematic models and computational tools describing the hierarchy of etiologic mechanisms involved in RPT dose response. This includes radiopharmacokinetics for image-based internal dosimetry and radiobiology for the mapping of dose response to clinical endpoints. The former area originates in pharmacotherapy, whereas the latter originates in radiotherapy. Accordingly, models and methods developed in these predecessor disciplines serve as a foundation on which to develop a repurposed set of tools more appropriate to RPT. Over the long term, this computational nuclear oncology framework also promises to facilitate widespread cross-fertilization of ideas between nuclear medicine and the greater mathematic and computational oncology communities.

On the reduction of imaging time-points for dosimetry in radionuclide therapy

BACKGROUND

The aim was to develop a theoretical framework for how errors in estimated activities propagate to a dispersion in time-integrated activity in radionuclide-therapy dosimetry and how this affects the comparison of radionuclide-therapy dosimetry schemes.

METHODS

Formulae for the variance of relative errors of estimated time-integrated activities and relative differences in time-integrated activities between measurement schemes when one or more time-points are removed were derived using the law of propagation of uncertainty for a population of time-activity-curve parameters. The formulae were derived under the assumptions of fixed coefficients of variation for estimated activities, and underlying mono-exponential curves. Analytical predictions were compared with results from numerical simulations and data for kidneys, liver, and spleen from a data-set of 18 patients treated with 177Lu-DOTA-TATE.

RESULTS

The dispersion in time-integrated activity is minimized if the time-points used for curve fitting have a large dispersion and are centered over the mean of τ = λ eff - 1 over the population, where λ eff is the effective decay constant (i.e., the sum of the biological and physical decay constants). For large dispersions of decay constants in the population, the centering of time-points becomes gradually less important. The analytical expressions replicated the main trends from the numerical simulations. Furthermore, the analytical expressions predicted correctly the optimal reduced imaging schedule in 9 of 12 pairwise comparisons between schedules for patients.

CONCLUSIONS

The dispersion of errors and deviations in estimated time-activity curves can be predicted using simple formulae. These formulae have the potential to be used for optimization of dosimetry measurement schemes for established and new radiopharmaceuticals as long as the mean and dispersion of biological half-lives are known in the patient population.

Dosimetry for Radiopharmaceutical Therapy: Practical Implementation, From the AJR Special Series on Quantitative Imaging

Radiopharmaceutical therapy (RPT) is advancing rapidly and achieving wider clinical application. However, RPT is not yet optimized in practice, as tumor and normal-organ dose estimates and, in turn, dose-response relationships remain poorly defined. Internal dosimetry is evolving to address such issues, transitioning from the estimation of population-average organ-level or tumor-level doses to individualized patient-specific sub-organ or sub-tumor doses. Derivation of patient-specific doses allows the further development of reliable dose-response relationships for diseased tissues and dose-toxicity relationships for normal tissues. Resources such as commercially available or publicly downloadable software are being increasingly developed to facilitate the use of these emerging methods. This review addresses the determination of patient-specific radiation doses for target tissue and at-risk normal tissues in the setting of RPT. Topics covered include: quantities, units, and radionuclides relevant to RPT; dose prescription algorithms; the steps in the dosimetry workflow; and bioeffects modeling. Implementation of patient-specific dosimetry will be essential for this therapeutic modality's optimization and further clinical expansion.

Distinct Urinary Metabolite Signatures Mirror In Vivo Oxidative Stress-Related Radiation Responses in Mice

Exposure to ionizing radiation disrupts metabolic pathways and causes oxidative stress, which can lead to organ damage. In this study, urinary metabolites from mice exposed to high-dose and low-dose whole-body irradiation (WBI HDR, WBI LDR) or partial-body irradiation (PBI BM2.5) were analyzed using targeted and untargeted metabolomics approaches. Significant metabolic changes particularly in oxidative stress pathways were observed on Day 2 post-radiation. By Day 30, the WBI HDR group showed persistent metabolic dysregulation, while the WBI LDR and PBI BM2.5 groups were similar to control mice. Machine learning models identified metabolites that were predictive of the type of radiation exposure with high accuracy, highlighting their potential use as biomarkers for radiation damage and oxidative stress.

The role of biomarkers and dosimetry parameters in overall and progression free survival prediction for patients treated with personalized 90Y glass microspheres SIRT: a preliminary machine learning study

BACKGROUND

Overall Survival (OS) and Progression-Free Survival (PFS) analyses are crucial metrics for evaluating the efficacy and impact of treatment. This study evaluated the role of clinical biomarkers and dosimetry parameters on survival outcomes of patients undergoing 90Y selective internal radiation therapy (SIRT).

MATERIALS/METHODS

This preliminary and retrospective analysis included 17 patients with hepatocellular carcinoma (HCC) treated with 90Y SIRT. The patients underwent personalized treatment planning and voxel-wise dosimetry. After the procedure, the OS and PFS were evaluated. Three structures were delineated including tumoral liver (TL), normal perfused liver (NPL), and whole normal liver (WNL). 289 dose-volume constraints (DVCs) were extracted from dose-volume histograms of physical and biological effective dose (BED) maps calculated on 99mTc-MAA and 90Y SPECT/CT images. Subsequently, the DVCs and 16 clinical biomarkers were used as features for univariate and multivariate analysis. Cox proportional hazard ratio (HR) was employed for univariate analysis. HR and the concordance index (C-Index) were calculated for each feature. Using eight different strategies, a cross-combination of various models and feature selection (FS) methods was applied for multivariate analysis. The performance of each model was assessed using an averaged C-Index on a three-fold nested cross-validation framework. The Kaplan-Meier (KM) curve was employed for univariate and machine learning (ML) model performance assessment.

RESULTS

The median OS was 11 months [95% CI: 8.5, 13.09], whereas the PFS was seven months [95% CI: 5.6, 10.98]. Univariate analysis demonstrated the presence of Ascites (HR: 9.2[1.8,47]) and the aim of SIRT (segmentectomy, lobectomy, palliative) (HR: 0.066 [0.0057, 0.78]), Aspartate aminotransferase (AST) level (HR:0.1 [0.012-0.86]), and MAA-Dose-V205(%)-TL (HR:8.5[1,72]) as predictors for OS. 90Y-derived parameters were associated with PFS but not with OS. MAA-Dose-V205(%)-WNL, MAA-BED-V400(%)-WNL with (HR:13 [1.5-120]) and 90Y-Dose-mean-TL, 90Y-D50-TL-Gy, 90Y-Dose-V205(%)-TL, 90Y-Dose- D50-TL-Gy, and 90Y-BED-V400(%)-TL (HR:15 [1.8-120]) were highly associated with PFS among dosimetry parameters. The highest C-index observed in multivariate analysis using ML was 0.94 ± 0.13 obtained from Variable Hunting-variable-importance (VH.VIMP) FS and Cox Proportional Hazard model predicting OS, using clinical features. However, the combination of VH. VIMP FS method with a Generalized Linear Model Network model predicting OS using Therapy strategy features outperformed the other models in terms of both C-index and stratification of KM curves (C-Index: 0.93 ± 0.14 and log-rank p-value of 0.023 for KM curve stratification).

CONCLUSION

This preliminary study confirmed the role played by baseline clinical biomarkers and dosimetry parameters in predicting the treatment outcome, paving the way for the establishment of a dose-effect relationship. In addition, the feasibility of using ML along with these features was demonstrated as a helpful tool in the clinical management of patients, both prior to and following 90Y-SIRT.

Heterogeneity of absorbed dose distribution in kidney tissues and dose-response modelling of nephrotoxicity in radiopharmaceutical therapy with beta-particle emitters: A review

Absorbed dose heterogeneity in kidney tissues is an important issue in radiopharmaceutical therapy. The effect of absorbed dose heterogeneity in nephrotoxicity is, however, not fully understood yet, which hampers the implementation of treatment optimization by obscuring the interpretation of clinical response data and the selection of optimal treatment options. Although some dosimetry methods have been developed for kidney dosimetry to the level of microscopic renal substructures, the clinical assessment of the microscopic distribution of radiopharmaceuticals in kidney tissues currently remains a challenge. This restricts the anatomical resolution of clinical dosimetry, which hinders a thorough clinical investigation of the impact of absorbed dose heterogeneity. The potential of absorbed dose-response modelling to support individual treatment optimization in radiopharmaceutical therapy is recognized and gaining attraction. However, biophysical modelling is currently underexplored for the kidney, where particular modelling challenges arise from the convolution of a complex functional organization of renal tissues with the function-mediated dose distribution of radiopharmaceuticals. This article reviews and discusses the heterogeneity of absorbed dose distribution in kidney tissues and the absorbed dose-response modelling of nephrotoxicity in radiopharmaceutical therapy. The review focuses mainly on the peptide receptor radionuclide therapy with beta-particle emitting somatostatin analogues, for which the scientific literature reflects over two decades of clinical experience. Additionally, detailed research perspectives are proposed to address various identified challenges to progress in this field.

Personalized dosimetry assessment of [177Lu]Lu-PSMA-617 radioligand therapy in the management of metastatic castration-resistant prostate cancer

INTRODUCTION

Prostate-specific membrane antigen (PSMA)-targeted radioligand therapy (RLT) is revolutionizing the treatment landscape for metastatic castration-resistant prostate cancer (mCRPC) patients. This study aimed to establish patient-specific radiation dosimetry for [177Lu]Lu-PSMA-617 RLT in Iranian patients with mCRPC.

METHOD

Twelve biopsy-proven prostate cancer patients (aged 68.73 ± 5.26 yr) underwent 6.62 ± 0.36 GBq [177Lu]Lu-PSMA-617 RLT. Post-therapy whole-body planar scans were acquired approximately at 4, 48, and 72 h post-administration, alongside a single SPECT/CT around 48 h using Siemens Symbia T2 to obtain cumulated activity. An imaging protocol and dosimetry approach were designed to balance between time efficacy and accuracy in post-therapeutic dosimetry. Using accurate activity calibration, S-values were calculated by importing SPECT/CT images as the source/geometry into the Geant4 application for the tomographic emission (GATE) Monte Carlo (MC) toolkit. The Medical Internal Radiation Dose (MIRD) scheme was followed for subsequent absorbed dose (AD) calculations in organs at risk (OAR) and tumoral lesions using the dose actor and accumulated activities for precise dose estimations.

RESULTS

Using the MC approach, the mean ADs to the liver, spleen, right and left kidneys, and tumor lesions were 0.11 ± 0.04 Gy/GBq, 0.08 ± 0.03 Gy/GBq, 0.34 ± 0.09 Gy/GBq, 0.34 ± 0.10 Gy/GBq, and 0.83 ± 0.54 Gy/GBq, respectively. Notably, tumoral lesions demonstrated significantly higher ADs, indicating enhanced uptake of radiopharmaceuticals by malignant cells.

CONCLUSIONS

This study indicates that the ADs of OARs and tumoral lesions from [177Lu]Lu-PSMA-617 RLT in patients with mCRPC are consistent with existing literature. The dosimetry findings suggest that increasing the administered activity of [177Lu]Lu-PSMA-617 RLT is feasible and does not pose a significant risk of adverse effects on OARs, as supported by our data. However, to validate the safety and efficacy of higher doses, further clinical follow-up studies are recommended.

3D small-scale dosimetry and tumor control of 225Ac radiopharmaceuticals for prostate cancer

Radiopharmaceutical therapy using α -emitting225 Ac is an emerging treatment for patients with advanced metastatic cancers. Measurement of the spatial dose distribution in organs and tumors is needed to inform treatment dose prescription and reduce off-target toxicity, at not only organ but also sub-organ scales. Digital autoradiography with α -sensitive detection devices can measure radioactivity distributions at 20-40 μ m resolution, but anatomical characterization is typically limited to 2D. We collected digital autoradiographs across whole tissues to generate 3D dose volumes and used them to evaluate the simultaneous tumor control and regional kidney dosimetry of a novel therapeutic radiopharmaceutical for prostate cancer, [225Ac]Ac-Macropa-PEG4-YS5, in mice. 22Rv1 xenograft-bearing mice treated with 18.5 kBq of [225Ac]Ac-Macropa-PEG4-YS5 were sacrificed at 24 h and 168 h post-injection for quantitative α -particle digital autoradiography and hematoxylin and eosin staining. Gamma-ray spectroscopy of biodistribution data was used to determine temporal dynamics and213 Bi redistribution. Tumor control probability and sub-kidney dosimetry were assessed. Heterogeneous225 Ac spatial distribution was observed in both tumors and kidneys. Tumor control was maintained despite heterogeneity if cold spots coincided with necrotic regions.225 Ac dose-rate was highest in the cortex and renal vasculature. Extrapolation of tumor control suggested that kidney absorbed dose could be reduced by 41% while maintaining 90% TCP. The 3D dosimetry methods described allow for whole tumor and organ dose measurements following225 Ac radiopharmaceutical therapy, which correlate to tumor control and toxicity outcomes.

Impact of the Reference Multiple-Time-Point Dosimetry Protocol on the Validity of Single-Time-Point Dosimetry for [177Lu]Lu-PSMA-I&T Therapy

Internal dosimetry supports safe and effective patient management during radionuclide therapy. Yet, it is associated with high clinical workload, costs, and patient burden, as patient scans at multiple time points (MTPs) must be acquired. Dosimetry based on imaging at a single time point (STP) has continuously gained popularity. However, MTP protocols, used as a reference to judge the validity of STP dosimetry, differ depending on local requirements and deviate from the unknown patient-specific ground truth pharmacokinetics. The aim of this study was to compare the error and optimum time point for different STP approaches using different reference MTP protocols. Methods: Whole-body SPECT/CT scans of 7 patients (7.4-8.9 GBq of [177Lu]Lu-PSMA-I&T) were scheduled at 24, 48, 72, and 168 h after injection. Sixty lesions, 14 kidneys, and 10 submandibular glands were delineated in the SPECT/CT data. Two curve models, that is, a mono- and a biexponential model, were fitted to the MTP data, in accordance with goodness-of-fit analysis (coefficients of variation, sum of squared errors). Three population-based STP approaches were compared: one method published by Hänscheid et al., one by Jackson et al., and one using population-based effective half-lives in the mono- or biexponential curve models. Percentage differences between STP and MTP dosimetry were evaluated. Results: Goodness-of-fit parameters show that a monoexponential function and a biexponential function with shared population-based parameters and physical tail are reasonable reference models. When comparing both reference models, we observed maximum differences of -44%, -19%, and -28% in the estimated absorbed doses for lesions, kidneys, and salivary glands, respectively. STP dosimetry with an average deviation of less than 10% from MTP dosimetry may be feasible; however, this deviation and the optimum imaging time point showed a dependence on the chosen reference protocol. Conclusion: STP dosimetry for [177Lu]Lu-PSMA therapy is promising to boost the integration of dosimetry into clinical routine. According to our patient cohort, 48 h after injection may be regarded as a compromise for STP dosimetry for lesions and at-risk organs. The results from this analysis show that a common gold standard for dosimetry is desirable to allow for reliable and comparable STP dosimetry.

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.

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.

Radioactive Iodine Therapy in Differentiated Thyroid Cancer: An Update on Dose Recommendations and Risk of Secondary Primary Malignancies

Radioactive iodine (RAI) therapy with iodine-131 is performed in select cases of differentiated thyroid cancer (DTC), typically for remnant ablation, adjuvant therapy, or treatment of known persistent disease. Herein, we review updated RAI dose recommendations and associated risks of secondary primary malignancy (SPM). RAI dose is usually chosen empirically based on the risk assessment of tumor recurrence and other factors. Dose recommendations differ slightly among relevant medical societies. As of April 2024, most medical societies, including the American Thyroid Association (ATA), European Thyroid Association (ETA), Society of Nuclear Medicine and Molecular Imaging/European Association of Nuclear Medicine (SNMMI/ EANM), and National Comprehensive Cancer Network (NCCN), recommend a dose of 1.11 GBq (30 mCi) I-131 for remnant ablation. For adjuvant therapy, the recommended RAI dose ranges from 1.11 to 3.7 GBq (30-100) mCi I-131, although doses up to 5.6 GBq (150 mCi) may also be considered. In patients with known or suspected metastatic disease, at least 3.7 GBq (100 mCi) I-131 should be administered, and RAI doses as high as 7.4 GBq (200 mCi) may be justified depending on the suspected tumor burden and extent. Dosimetry has the advantage of tailoring the RAI dose to each patient's pharmacokinetics, resulting in ≥ 7.4 GBq (200 mCi) of I-131 in most cases. There is an ongoing debate about the risk of developing SPM due to RAI therapy, with several multicenter studies and meta-analyses concerning SPM being published in the last 2 years. The incidence of RAI-associated SPM varies according to the study design and detection method. Several studies showed no increased incidence, and there was no specific secondary cancer or cancer group linked to RAI exposures. Some reports indicated that cumulative RAI doses exceeding 5.6-7.4 GBq (150-200 mCi) were found to represent an increased risk for developing SPM. However, a clearly defined dose threshold cannot be provided based on the current literature. Nonetheless, caution should be exercised when considering repeated RAI therapies for persistent metastatic PTC, with a cumulative dose exceeding 37.0 GBq (1,000 mCi), due to the potential risk of developing SPM and other long-term toxicity. Further research is warranted to understand better the relationship between RAI dose and the risk of SPM.

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.

Improvements of 177Lu SPECT images from sparsely acquired projections by reconstruction with deep-learning-generated synthetic projections

BACKGROUND

For dosimetry, the demand for whole-body SPECT/CT imaging, which require long acquisition durations with dual-head Anger cameras, is increasing. Here we evaluated sparsely acquired projections and assessed whether the addition of deep-learning-generated synthetic intermediate projections (SIPs) could improve the image quality while preserving dosimetric accuracy.

METHODS

This study included 16 patients treated with 177Lu-DOTATATE with SPECT/CT imaging (120 projections, 120P) at four time points. Deep neural networks (CUSIPs) were designed and trained to compile 90 SIPs from 30 acquired projections (30P). The 120P, 30P, and three different CUSIP sets (30P + 90 SIPs) were reconstructed using Monte Carlo-based OSEM reconstruction (yielding 120P_rec, 30P_rec, and CUSIP_recs). The noise levels were visually compared. Quantitative measures of normalised root mean square error, normalised mean absolute error, peak signal-to-noise ratio, and structural similarity were evaluated, and kidney and bone marrow absorbed doses were estimated for each reconstruction set.

RESULTS

The use of SIPs visually improved noise levels. All quantitative measures demonstrated high similarity between CUSIP sets and 120P. Linear regression showed nearly perfect concordance of the kidney and bone marrow absorbed doses for all reconstruction sets, compared to the doses of 120P_rec (R2 ≥ 0.97). Compared to 120P_rec, the mean relative difference in kidney absorbed dose, for all reconstruction sets, was within 3%. For bone marrow absorbed doses, there was a higher dissipation in relative differences, and CUSIP_recs outperformed 30P_rec in mean relative difference (within 4% compared to 9%). Kidney and bone marrow absorbed doses for 30P_rec were statistically significantly different from those of 120_rec, as opposed to the absorbed doses of the best performing CUSIP_rec, where no statistically significant difference was found.

CONCLUSION

When performing SPECT/CT reconstruction, the use of SIPs can substantially reduce acquisition durations in SPECT/CT imaging, enabling acquisition of multiple fields of view of high image quality with satisfactory dosimetric accuracy.

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.

Impact of different models based on blood samples and images for bone marrow dosimetry after 177Lu-labeled somatostatin-receptor therapy

BACKGROUND

Peptide receptor radionuclide therapy with 177Lu-DOTATATE is a recognized option for treating neuroendocrine tumors and has few toxicities, except for the kidneys and bone marrow. The bone marrow dose is generally derived from a SPECT/CT image-based method with four timepoints or from a blood-based method with up to 9 timepoints, but there is still no reference method. This retrospective single-center study on the same cohort of patients compared the calculated bone marrow dose administered with both methods using mono, bi- or tri-exponential models. For the image-based method, the dose was estimated using Planetdose© software. Pearson correlation coefficients were calculated. We also studied the impact of late timepoints for both methods.

RESULTS

The bone marrow dose was calculated for 131 treatments with the blood-based method and for 17 with the image-based method. In the former, the median absorbed dose was 15.3, 20.5 and 28.3 mGy/GBq with the mono-, bi- and tri-exponential model, respectively. With the image-based method, the median absorbed dose was 63.9, 41.9 and 60.8 with the mono-, bi- and tri-exponential model, respectively. Blood samples after 24h post-injection did not evidence any change in the absorbed bone marrow dose with the bi-exponential model. On the contrary, the 6-day post-injection timepoint was more informative with the image-based model.

CONCLUSION

This study confirms that the estimated bone marrow dose is significantly lower with the blood-based method than with the image-based method. The blood-based method with a bi-exponential model proved particularly useful, without the need for blood samples after 24h post-injection. Nevertheless, this blood-based method is based on an assumption that needs to be more validated. The important difference between the two methods does not allow to determine the optimal one to estimate the true absorbed dose and further studies are necessary to compare with biological effects.

Activity quantification and dosimetry in radiopharmaceutical therapy with reference to 177Lutetium

Radiopharmaceutical therapy has been widely adopted owing primarily to the development of novel radiopharmaceuticals. To fully utilize the potential of these RPTs in the era of precision medicine, therapy must be optimized to the patient's tumor characteristics. The vastly disparate dosimetry methodologies need to be harmonized as the first step towards this. Multiple factors play a crucial role in the shift from empirical activity administration to patient-specific dosimetry-based administrations from RPT. Factors such as variable responses seen in patients with presumably similar clinical characteristics underscore the need to standardize and validate dosimetry calculations. These efforts combined with ongoing initiatives to streamline the dosimetry process facilitate the implementation of radiomolecular precision oncology. However, various challenges hinder the widespread adoption of personalized dosimetry-based activity administration, particularly when compared to the more convenient and resource-efficient approach of empiric activity administration. This review outlines the fundamental principles, procedures, and methodologies related to image activity quantification and dosimetry with a specific focus on 177Lutetium-based radiopharmaceuticals.

Towards Effective Targeted Alpha Therapy for Neuroendocrine Tumours: A Review

This review article explores the evolving landscape of Molecular Radiotherapy (MRT), emphasizing Peptide Receptor Radionuclide Therapy (PRRT) for neuroendocrine tumours (NETs). The primary focus is on the transition from β-emitting radiopharmaceuticals to α-emitting agents in PRRT, offering a critical analysis of the radiobiological basis, clinical applications, and ongoing developments in Targeted Alpha Therapy (TAT). Through an extensive literature review, the article delves into the mechanisms and effectiveness of PRRT in targeting somatostatin subtype 2 receptors, highlighting both its successes and limitations. The discussion extends to the emerging paradigm of TAT, underlining its higher potency and specificity with α-particle emissions, which promise enhanced therapeutic efficacy and reduced toxicity. The review critically evaluates preclinical and clinical data, emphasizing the need for standardised dosimetry and a deeper understanding of the dose-response relationship in TAT. The review concludes by underscoring the significant potential of TAT in treating SSTR2-overexpressing cancers, especially in patients refractory to β-PRRT, while also acknowledging the current challenges and the necessity for further research to optimize treatment protocols.

Beyond Average: α-Particle Distribution and Dose Heterogeneity in Bone Metastatic Prostate Cancer

α-particle emitters are emerging as a potent modality for disseminated cancer therapy because of their high linear energy transfer and localized absorbed dose profile. Despite great interest and pharmaceutical development, there is scant information on the distribution of these agents at the scale of the α-particle pathlength. We sought to determine the distribution of clinically approved [223Ra]RaCl2 in bone metastatic castration-resistant prostate cancer at this resolution, for the first time to our knowledge, to inform activity distribution and dose at the near-cell scale. Methods: Biopsy specimens and blood were collected from 7 patients 24 h after administration. 223Ra activity in each sample was recorded, and the microstructure of biopsy specimens was analyzed by micro-CT. Quantitative autoradiography and histopathology were segmented and registered with an automated procedure. Activity distributions by tissue compartment and dosimetry calculations based on the MIRD formalism were performed. Results: We revealed the activity distribution differences across and within patient samples at the macro- and microscopic scales. Microdistribution analysis confirmed localized high-activity regions in a background of low-activity tissue. We evaluated heterogeneous α-particle emission distribution concentrated at bone-tissue interfaces and calculated spatially nonuniform absorbed-dose profiles. Conclusion: Primary patient data of radiopharmaceutical therapy distribution at the small scale revealed that 223Ra uptake is nonuniform. Dose estimates present both opportunities and challenges to enhance patient outcomes and are a first step toward personalized treatment approaches and improved understanding of α-particle radiopharmaceutical therapies.

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.

Quality Assurance Considerations in Radiopharmaceutical Therapy Dosimetry Using PLANETDose: An International Atomic Energy Agency Study

Implementation of radiopharmaceutical therapy dosimetry varies depending on the clinical application, dosimetry protocol, software, and ultimately the operator. Assessing clinical dosimetry accuracy and precision is therefore a challenging task. This work emphasizes some pitfalls encountered during a structured analysis, performed on a single-patient dataset consisting of SPECT/CT images by various participants using a standard protocol and clinically approved commercial software. Methods: The clinical dataset consisted of the dosimetric study of a patient administered with [177Lu]Lu-DOTATATE at Tygerberg Hospital, South Africa, as a part of International Atomic Energy Agency-coordinated research project E23005. SPECT/CT images were acquired at 5 time points postinjection. Patient and calibration images were reconstructed on a workstation, and a calibration factor of 122.6 Bq/count was derived independently and provided to the participants. A standard dosimetric protocol was defined, and PLANETDose (version 3.1.1) software was installed at 9 centers to perform the dosimetry of 3 treatment cycles. The protocol included rigid image registration, segmentation (semimanual for organs, activity threshold for tumors), and dose voxel kernel convolution of activity followed by absorbed dose (AD) rate integration to obtain the ADs. Iterations of the protocol were performed by participants individually and within collective training, the results of which were analyzed for dosimetric variability, as well as for quality assurance and error analysis. Intermediary checkpoints were developed to understand possible sources of variation and to differentiate user error from legitimate user variability. Results: Initial dosimetric results for organs (liver and kidneys) and lesions showed considerable interoperator variability. Not only was the generation of intermediate checkpoints such as total counts, volumes, and activity required, but also activity-to-count ratio, activity concentration, and AD rate-to-activity concentration ratio to determine the source of variability. Conclusion: When the same patient dataset was analyzed using the same dosimetry procedure and software, significant disparities were observed in the results despite multiple sessions of training and feedback. Variations due to human error could be minimized or avoided by performing intensive training sessions, establishing intermediate checkpoints, conducting sanity checks, and cross-validating results across physicists or with standardized datasets. This finding promotes the development of quality assurance in clinical dosimetry.

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.

The contest between internal and external-beam dosimetry: The Zeno's paradox of Achilles and the tortoise

Radionuclide therapy, also called molecular radiotherapy (MRT), has come of age, with several novel radiopharmaceuticals being approved for clinical use or under development in the last decade. External beam radiotherapy (EBRT) is a well-established treatment modality, with about half of all oncologic patients expected to receive at least one external radiation treatment over their disease course. The efficacy and the toxicity of both types of treatment rely on the interaction of radiation with biological tissues. Dosimetry played a fundamental role in the scientific and technological evolution of EBRT, and absorbed doses to the target and to the organs at risk are calculated on a routine basis. In contrast, in MRT the usefulness of internal dosimetry has long been questioned, and a structured path to include absorbed dose calculation is missing. However, following a similar route of development as EBRT, MRT treatments could probably be optimized in a significant proportion of patients, likely based on dosimetry and radiobiology. In the present paper we describe the differences and the similarities between internal and external-beam dosimetry in the context of radiation treatments, and we retrace the main stages of their development over the last decades.

Development and Utility of an Imaging System for Internal Dosimetry of Astatine-211 in Mice

In targeted radionuclide therapy, determining the absorbed dose of the ligand distributed to the whole body is vital due to its direct influence on therapeutic and adverse effects. However, many targeted alpha therapy drugs present challenges for in vivo quantitative imaging. To address this issue, we developed a planar imaging system equipped with a cadmium telluride semiconductor detector that offers high energy resolution. This system also comprised a 3D-printed tungsten collimator optimized for high sensitivity to astatine-211, an alpha-emitting radionuclide, and adequate spatial resolution for mouse imaging. The imager revealed a spectrum with a distinct peak for X-rays from astatine-211 owing to the high energy resolution, clearly distinguishing these X-rays from the fluorescent X-rays of tungsten. High collimator efficiency (4.5 × 10-4) was achieved, with the maintenance of the spatial resolution required for discerning mouse tissues. Using this system, the activity of astatine-211 in thyroid cancer tumors with and without the expression of the sodium iodide symporter (K1-NIS/K1, respectively) was evaluated through in vivo imaging. The K1-NIS tumors had significantly higher astatine-211 activity (sign test, p = 0.031, n = 6) and significantly decreased post-treatment tumor volume (Student's t-test, p = 0.005, n = 6). The concurrent examination of intratumor drug distribution and treatment outcome could be performed with the same mice.

Quantitative imaging for 177Lu-PSMA treatment response monitoring and dosimetry

PSMA-targeted radiopharmaceutical therapy is an established treatment option for metastatic castration-resistant prostate cancer (mCRPC). However, response rates and duration using 177Lu-PSMA-617 vary considerably between patients. Quantitative 177Lu SPECT imaging is one approach that may be leveraged to more closely monitor inter-cycle response, as well as patient-specific absorbed doses. In this work, we describe our experience implementing quantitative imaging throughout the course of 177Lu-PSMA treatment, including serial SPECT imaging to monitor response and for individualized dosimetry. We also describe our imaging protocols and dose calculation workflows for 3D voxelized patient-specific organ and tumor dosimetry, including a review of the current landscape and efforts towards harmonized dosimetry.

EFOMP policy statement NO. 19: Dosimetry in nuclear medicine therapy - Molecular radiotherapy

The European Council Directive 2013/59/Euratom (BSS Directive) includes optimisation of treatment with radiotherapeutic procedures based on patient dosimetry and verification of the absorbed doses delivered. The present policy statement summarises aspects of three directives relating to the therapeutic use of radiopharmaceuticals and medical devices, and outlines the steps needed for implementation of patient dosimetry for radioactive drugs. To support the transition from administrations of fixed activities to personalised treatments based on patient-specific dosimetry, EFOMP presents a number of recommendations including: increased networking between centres and disciplines to support data collection and development of codes-of-practice; resourcing to support an infrastructure that permits routine patient dosimetry; research funding to support investigation into individualised treatments; inter-disciplinary training and education programmes; and support for investigator led clinical trials. Close collaborations between the medical physicist and responsible practitioner are encouraged to develop a similar pathway as is routine for external beam radiotherapy and brachytherapy. EFOMP's policy is to promote the roles and responsibilities of medical physics throughout Europe in the development of molecular radiotherapy to ensure patient benefit. As the BSS directive is adopted throughout Europe, unprecedented opportunities arise to develop informed treatments that will mitigate the risks of under- or over-treatments.

[Combination of internal and external beam radiotherapy]

External beam radiation therapy and internal vectorized radiation therapy are two types of radiotherapy that can be used to treat cancer. They differ in the way they are administered, and the type of radiation used. Although they can be effective in treating cancer, they each have their own advantages and disadvantages, and their combination could be synergistic. Preclinical studies on combined internal and external beam radiation therapy have mainly used radiolabelled antibodies, whose bone marrow toxicity remains the limiting factor in increasing the administered activities. The use of small radioligands in clinical trials has shown to be better tolerated and more effective, which explains their rapid development. The results of preclinical studies on combined internal and external beam radiation therapy appear heterogeneous, making it impossible to determine an ideal therapeutic sequencing scheme, and complicating the transposition to clinical studies. The few clinical studies on combined internal and external beam radiation therapy available to date have demonstrated feasibility and tolerability. More work remains to be done in the fields of dosimetry and radiobiology, as well as in the sequencing of these two irradiation modalities to optimize their combination.

On the Use of Artificial Intelligence for Dosimetry of Radiopharmaceutical Therapies

Routine clinical dosimetry along with radiopharmaceutical therapies is key for future treatment personalization. However, dosimetry is considered complex and time-consuming with various challenges amongst the required steps within the dosimetry workflow. The general workflow for image-based dosimetry consists of quantitative imaging, the segmentation of organs and tumors, fitting of the time-activity-curves, and the conversion to absorbed dose. This work reviews the potential and advantages of the use of artificial intelligence to improve speed and accuracy of every single step of the dosimetry workflow.

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.

Averaging of absorbed doses: How matter matters

BACKGROUND

Dosimetry in radionuclide therapy often requires the calculation of average absorbed doses within and between spatial regions, for example, for voxel-based dosimetry methods, for paired organs, or across multiple tumors. Formation of such averages can be made in different ways, starting from different definitions.

PURPOSE

The aim of this study is to formally specify different averaging strategies for absorbed doses, and to compare their results when applied to absorbed dose distributions that are non-uniform within and between regions.

METHODS

For averaging within regions, two definitions of the average absorbed dose are considered: the simple average over the region (the region average) and the average when weighting by the mass density (density-weighted region average). The latter is shown to follow from the definition of mean absorbed dose according to the ICRU, and to be consistent with the MIRD formalism. For averaging between different spatial regions, three definitions follow: the volume-weighted, the mass-weighted, and the unweighted average. With respect to characterizing non-uniformity, the different average definitions lead to the use of dose-volume histograms (DVHs) (region average), dose-mass histograms (DMHs) (density-weighted region average), and unweighted histograms (unweighted average). Average absorbed doses are calculated for three worked examples, starting from the different definitions. The first, schematic, example concerns the calculation of the average absorbed dose between two regions with different volumes or mass densities. The second, stylized, example concerns voxel-based dosimetry, for which the average absorbed-dose rate within a region is calculated. The geometries studied include three 177 Lu-filled voxelized spheres, where the sphere masses are held constant while the material compositions, densities, and volumes are varied. For comparison, the mean absorbed-dose rates obtained using unit-density sphere S-values are also included. The third example concerns SPECT/CT-based tumor dosimetry for five patients undergoing therapy with 177 Lu-PSMA and six patients undergoing therapy with 177 Lu-DOTA-TATE, for which the average absorbed-dose rates across multiple tumors are calculated. For the second and third examples, analyses also include representations by histograms.

RESULTS

Example 1 shows that the average absorbed doses, calculated using different definitions, can differ considerably if the masses and absorbed doses for two regions are markedly different. From example 2 it is seen that the density-weighted region average is stable under different activity and density distributions and is also in line with results using S-values. In contrast, the region average varies as function of the activity distribution. In example 3, the absorbed dose rates for individual tumors differ by (1.1 ± 4.3)% and (-0.1 ± 0.4)% with maximum deviations of +34.4% and -1.4% for 177 Lu-PSMA and 177 Lu-DOTA-TATE, respectively, when calculated as region averages or density-weighted region averages, with largest deviations obtained when the density is non-uniform. The average absorbed doses calculated across all tumors are similar when comparing mass-weighted and volume-weighted averages but these differ substantially from unweighted averages.

CONCLUSION

Different strategies for averaging of absorbed doses within and between regions can lead to substantially different absorbed-dose estimates. At reporting of radionuclide therapy dosimetry, it is important to specify the averaging strategy applied.

New horizon of radiopharmaceuticals in management of neuroendocrine tumors

Neuroendocrine neoplasms are rare and heterogenous group of tumors with varying degrees of clinical presentations and involvement of multiple organ systems in the body. In the modern clinical practice somatostatin receptor molecular imaging and targeted radioligand therapy plays a vital role in the diagnosis and management of the disease. Several new and promising radiotracers for NET imaging and theranostics, belonging to various groups and classes are being studied and investigated. This exponential growth of radiotracers poses concerns about the indication, clinical benefit, and safety profile of the agents. We discuss the basis behind these radiotracers clinical use, receptor targeting and intra and inter tumor heterogeneity. Furthermore, role of dual tracer imaging, combination therapy and potential applications of dosimetry in predicting treatment outcome and safety profile is reviewed. Individualized precision medicine with better tumor characterization, maximum therapeutic benefit and minimum toxicity is the way forward for future medicine.

Biodosimetry, can it find its way to the nuclear medicine clinic?

Personalised dosimetry based on molecular imaging is a field that has grown exponentially in the last decade due to the increasing success of Radioligand Therapy (RLT). Despite advances in imaging-based 3D dose estimation, the administered dose of a therapeutic radiopharmaceutical for RLT is often non-personalised, with standardised dose regimens administered every 4-6 weeks. Biodosimetry markers, such as chromosomal aberrations, could be used alongside image-based dosimetry as a tool for individualised dose estimation to further understand normal tissue toxicity and refine the administered dose. In this review we give an overview of biodosimetry markers that are used for blood dose estimation, followed by an overview of their current results when applied in RLT patients. Finally, an in-depth discussion will provide a perspective on the potential for the use of biodosimetry in the nuclear medicine clinic.

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.

A machine learning-based model for a dose point kernel calculation

PURPOSE

Absorbed dose calculation by kernel convolution requires the prior determination of dose point kernels (DPK). This study reports on the design, implementation, and test of a multi-target regressor approach to generate the DPKs for monoenergetic sources and a model to obtain DPKs for beta emitters.

METHODS

DPK for monoenergetic electron sources were calculated using the FLUKA Monte Carlo (MC) code for many materials of clinical interest and initial energies ranging from 10 to 3000 keV. Regressor Chains (RC) with three different coefficients regularization/shrinkage models were used as base regressors. Electron monoenergetic scaled DPKs (sDPKs) were used to assess the corresponding sDPKs for beta emitters typically used in nuclear medicine, which were compared against reference published data. Finally, the beta emitters sDPK were applied to a patient-specific case calculating the Voxel Dose Kernel (VDK) for a hepatic radioembolization treatment with [Formula: see text]Y.

RESULTS

The three trained machine learning models demonstrated a promising capacity to predict the sDPK for both monoenergetic emissions and beta emitters of clinical interest attaining differences lower than [Formula: see text] in the mean average percentage error (MAPE) as compared with previous studies. Furthermore, differences lower than [Formula: see text] were obtained for the absorbed dose in patient-specific dosimetry comparing against full stochastic MC calculations.

CONCLUSION

An ML model was developed to assess dosimetry calculations in nuclear medicine. The implemented approach has shown the capacity to accurately predict the sDPK for monoenergetic beta sources in a wide range of energy in different materials. The ML model to calculate the sDPK for beta-emitting radionuclides allowed to obtain VDK useful to achieve reliable patient-specific absorbed dose distributions required short computation times.

EANM enabling guide: how to improve the accessibility of clinical dosimetry

Dosimetry can be a useful tool for personalization of molecular radiotherapy (MRT) procedures, enabling the continuous development of theranostic concepts. However, the additional resource requirements are often seen as a barrier to implementation. This guide discusses the requirements for dosimetry and demonstrates how a dosimetry regimen can be tailored to the available facilities of a centre. The aim is to help centres wishing to initiate a dosimetry service but may not have the experience or resources of some of the more established therapy and dosimetry centres. The multidisciplinary approach and different personnel requirements are discussed and key equipment reviewed example protocols demonstrating these factors are given in the supplementary material for the main therapies carried out in nuclear medicine, including [131I]-NaI for benign thyroid disorders, [177Lu]-DOTATATE and 131I-mIBG for neuroendocrine tumours and [90Y]-microspheres for unresectable hepatic carcinoma.

Evolution of Portable Sensors for In-Vivo Dose and Time-Activity Curve Monitoring as Tools for Personalized Dosimetry in Molecular Radiotherapy

Treatment personalization in Molecular Radiotherapy (MRT) relies on pre- and post-treatment SPECT/ PET-based images and measurements to obtain a patient-specific absorbed dose-rate distribution map and its evolution over time. Unfortunately, the number of time points that are available per patient to investigate individual pharmacokinetics is often reduced by limited patient compliance or SPECT or PET/CT scanner availability for dosimetry in busy departments. The adoption of portable sensors for in-vivo dose monitoring during the entire treatment could improve the assessment of individual biokinetics in MRT and, thus, the treatment personalization. The evolution of portable devices, non-SPECT/PET-based options, already used for monitoring radionuclide activity transit and accumulation during therapy with radionuclides (i.e., MRT or brachytherapy), is presented to identify valuable ones, which combined with conventional nuclear medicine imaging systems could be effective in MRT. External probes, integration dosimeters and active detecting systems were included in the study. The devices and their technology, the range of applications, the features and limitations are discussed. Our overview of the available technologies encourages research and development of portable devices and dedicated algorithms for MRT patient-specific biokinetics study. This would represent a crucial advancement towards personalized treatment in MRT.

Determinants of target absorbed dose in radionuclide therapy

In radionuclide therapy, activity kinetics in tissues determine the absorbed doses administered and thus efficacy and side effects of treatment. The objective of this work was to derive expressions for the parameters affecting the absorbed dose to a target tissue for first-order activity kinetics. The activity uptake results from contributions from the first-pass activity flow through the target tissue preceding systemic equilibration and uptake after distribution of the administered compound in the body. The absorbed dose from uptake after equilibration is the product of the mean energy deposited per decay in the target tissue, the time integral of the plasma activity concentration, the plasma volume flow per unit target tissue mass, the probability of activity removal during passage, and the mean lifetime of activity in the target tissue. Quantitative analysis of the determinants of absorbed dose exemplarily for radioiodine therapy indicates that the high uptake often observed in Graves' disease must be associated with high tissue perfusion and removal probability and that administration of stable iodine increases mean lifetime. For therapies with long residence times of the active compound in the blood, such as radioiodine therapy, the contribution of the first-pass is small compared with uptake after equilibration. The relative first-pass contribution is higher for agents that are rapidly eliminated from the blood pool, such as radiolabelled somatostatin analogues, and may dominate after arterial application. Understanding the determining parameters in radionuclide therapy reveals dose-limiting factors and opens up opportunities to optimise and individualize therapy, potentially improving treatment success rates.

A Machine Learning based model for a Dose Point Kernel calculation

PURPOSE

Absorbed dose calculation by kernel convolution requires the prior determination of dose point kernels (DPK). This study shows applications of machine learning to generate the DPKs for monoenergetic sources and a model to obtain DPKs for beta emitters.

METHODS

DPK for monoenergetic electron sources were calculated using the FLUKA Monte Carlo (MC) code for many materials of clinical interest and initial energies ranging from 10 to 3000 keV. Three machine learning (ML) algorithms were trained using the MC DPKs. Electron monoenergetic scaled DPKs (sDPKs) were used to assess the corresponding sDPKs for beta emitters typically used in nuclear medicine, which were compared against reference published data. Finally, the ML sDPK approach was applied to a patient-specific case calculating the dose voxel kernels (DVK) for a hepatic radioembolization treatment with \(^{90}\)Y.

RESULTS

The three trained machine learning models demonstrated a promising capacity to predict the sDPK for both monoenergetic emissions and beta emitters of clinical interest attaining differences lower than \(10%\) in the mean average percentage error (MAPE) as compared with previous studies. Furthermore, differences lower than \(7 %\) were obtained for the absorbed dose in patient-specific dosimetry comparing against full stochastic MC calculations.

CONCLUSION

An ML model was developed to assess dosimetry calculations in nuclear medicine. The implemented approach has shown the capacity to accurately predict the sDPK for monoenergetic beta sources in a wide range of energy in different materials. The ML model to calculate the sDPK for beta-emitting radionuclides allowed to obtain VDK useful to achieve reliable patient-specific absorbed dose distributions required remarkable short computation times.

Quantification and dosimetry of small volumes including associated uncertainty estimation

BACKGROUND

Accurate quantification of radioactivity in a source of interest relies on accurate registration between SPECT and anatomical images, and appropriate correction of partial volume effects (PVEs). For small volumes, exact registration between the two imaging modalities and recovery factors used to correct for PVE are unreliable. There is currently no guidance relating to quantification or the associated uncertainty estimation for small volumes.

MATERIAL AND METHODS

A method for quantification of small sources of interest is proposed, which uses multiple oversized volumes of interest. The method was applied to three Na[131I]I activity distributions where a Na[131I]I capsule was situated within a cylindrical phantom containing either zero background, uniform background or non-uniform background and to a scenario with small lesions placed in an anthropomorphic phantom. The Na[131I]I capsule and lesions were quantified using the proposed method and compared with measurements made using two alternative quantification methods. The proposed method was also applied to assess the absorbed dose delivered to a bone metastasis following [131I]mIBG therapy for neuroblastoma including the associated uncertainty estimation.

RESULTS

The method is accurate across a range of activities and in varied radioactivity distributions. Median percentage errors using the proposed method in no background, uniform backgrounds and non-uniform backgrounds were - 0.4%, - 0.3% and 1.7% with median associated uncertainties of 1.4%, 1.4% and 1.6%, respectively. The technique is more accurate and robust when compared to currently available alternative methods.

CONCLUSIONS

The proposed method provides a reliable and accurate method for quantification of sources of interest, which are less than three times the spatial resolution of the imaging system. The method may be of use in absorbed dose calculation in cases of bone metastasis, lung metastasis or thyroid remnants.

Administration Routes for SSTR-/PSMA- and FAP-Directed Theranostic Radioligands in Mice

The NETTER-1, VISION, and TheraP trials proved the efficacy of repeat intravenous application of small radioligands. Application by subcutaneous, intraperitoneal, or oral routes is an important alternative and may yield comparable or favorable organ and tumor radioligand uptake. Here, we assessed organ and tumor biodistribution for various radioligand application routes in healthy mice and models of cancer expressing somatostatin receptor (SSTR), prostate-specific membrane antigen (PSMA), and fibroblast activation protein (FAP). Methods: Healthy and tumor-bearing male C57BL/6 or NOD SCID γ-mice, respectively, were administered a mean of 6.0 ± 0.5 MBq of ⁶⁸Ga-DOTATOC (RM1-SSTR allograft), 5.3 ± 0.3 MBq of ⁶⁸Ga-PSMA11 (RM1-PSMA allograft), or 4.8 ± 0.2 MBq of ⁶⁸Ga-FAPI46 (HT1080-FAP xenograft) by intravenous, intraperitoneal, subcutaneous, or oral routes. In vivo PET images and ex vivo biodistribution in tumor, organs, and the injection site were assessed up to 5 h after injection. Healthy mice were monitored for up to 7 d after the last scan for signs of stress or adverse reactions. Results: After intravenous, intraperitoneal, and subcutaneous radioligand administration, average residual activity at the injection site was less than 17 percentage injected activity per gram (%IA/g) at 1 h after injection, less than 10 %IA/g at 2 h after injection, and no more than 4 %IA/g at 4 h after injection for all radioligands. After oral administration, at least 50 %IA/g remained within the intestines until 4 h after injection. Biodistribution in organs of healthy mice was nearly equivalent after intravenous, intraperitoneal, and subcutaneous application at 1 h after injection and all subsequent time points (≤1 %IA/g for liver, blood, and bone marrow; 11.2 ± 1.4 %IA/g for kidneys). In models for SSTR-, PSMA- and FAP-expressing cancer, tumor uptake was increased or equivalent for intraperitoneal/subcutaneous versus intravenous injection at 5 h after injection (ex vivo): SSTR, 7.2 ± 1.0 %IA/g (P = 0.0197)/6.5 ± 1.3 %IA/g (P = 0.0827) versus 2.9 ± 0.3 %IA/g, respectively; PSMA, 3.4 ± 0.8 %IA/g (P = 0.9954)/3.9 ± 0.8 %IA/g (P = 0.8343) versus 3.3 ± 0.7% IA/g, respectively; FAP, 1.1 ± 0.1 %IA/g (P = 0.9805)/1.1 ± 0.1 %IA/g (P = 0.7446) versus 1.0 ± 0.2 %IA/g, respectively. Conclusion: In healthy mice, biodistribution of small theranostic ligands after intraperitoneal/subcutaneous application is nearly equivalent to that after intravenous injection. Subcutaneous administration resulted in the highest absolute SSTR tumor and tumor-to-organ uptake as compared with the intravenous route, warranting further clinical assessment.

Analysis of a deep learning-based method for generation of SPECT projections based on a large Monte Carlo simulated dataset

Background

In recent years, a lot of effort has been put in the enhancement of medical imaging using artificial intelligence. However, limited patient data in combination with the unavailability of a ground truth often pose a challenge to a systematic validation of such methodologies. The goal of this work was to investigate a recently proposed method for an artificial intelligence-based generation of synthetic SPECT projections, for acceleration of the image acquisition process based on a large dataset of realistic SPECT simulations.

Methods

A database of 10,000 SPECT projection datasets of heterogeneous activity distributions of randomly placed random shapes was simulated for a clinical SPECT/CT system using the SIMIND Monte Carlo program. Synthetic projections at fixed angular increments from a set of input projections at evenly distributed angles were generated by different u-shaped convolutional neural networks (u-nets). These u-nets differed in noise realization used for the training data, number of input projections, projection angle increment, and number of training/validation datasets. Synthetic projections were generated for 500 test projection datasets for each u-net, and a quantitative analysis was performed using statistical hypothesis tests based on structural similarity index measure and normalized root-mean-squared error. Additional simulations with varying detector orbits were performed on a subset of the dataset to study the effect of the detector orbit on the performance of the methodology. For verification of the results, the u-nets were applied to Jaszczak and NEMA physical phantom data obtained on a clinical SPECT/CT system.

Results

No statistically significant differences were observed between u-nets trained with different noise realizations. In contrast, a statistically significant deterioration was found for training with a small subset (400 datasets) of the 10,000 simulated projection datasets in comparison with using a large subset (9500 datasets) for training. A good agreement between synthetic (i.e., u-net generated) and simulated projections before adding noise demonstrates a denoising effect. Finally, the physical phantom measurements show that our findings also apply for projections measured on a clinical SPECT/CT system.

Conclusion

Our study shows the large potential of u-nets for accelerating SPECT/CT imaging. In addition, our analysis numerically reveals a denoising effect when generating synthetic projections with a u-net. Clinically interesting, the methodology has proven robust against camera orbit deviations in a clinically realistic range. Lastly, we found that a small number of training samples (e.g., ~ 400 datasets) may not be sufficient for reliable generalization of the u-net.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40658-022-00476-w.

Individualization of Radionuclide Therapies: Challenges and Prospects

Simple Summary

Currently, patient-specific treatment plans and dosimetry calculations are not routinely performed for radionuclide therapies. In external beam radiotherapy, it is quite the opposite. As a result, a small fraction of patients receives optimal radioactivity. This conservative approach provides “radiation safety” to healthy tissues but delivers a lower than indicated absorbed dose to the tumors, resulting in a lower response rate and a higher disease relapse rate. Evidence shows that better and more predictable outcomes can be achieved with patient-individualized dose assessment. Therefore, the incorporation of individual planning into radionuclide therapies is a high priority for nuclear medicine physicians and medical physicists alike. Internal dosimetry is used in tumor therapy to optimize the absorbed dose to the target tissue. The main reasons for the difficulties in incorporating patients’ internal dosimetry into routine clinical practice are discussed. The article presents the prospects for the routine implementation of personalized radionuclide therapies.

Abstract

The article presents the problems of clinical implementation of personalized radioisotope therapy. The use of radioactive drugs in the treatment of malignant and benign diseases is rapidly expanding. Currently, in the majority of nuclear medicine departments worldwide, patients receive standard activities of therapeutic radiopharmaceuticals. Intensively conducted clinical trials constantly provide more evidence of a close relationship between the dose of radiopharmaceutical absorbed in pathological tissues and the therapeutic effect of radioisotope therapy. Due to the lack of individual internal dosimetry (based on the quantitative analysis of a series of diagnostic images) before or during the treatment, only a small fraction of patients receives optimal radioactivity. The vast majority of patients receive too-low doses of ionizing radiation to the target tissues. This conservative approach provides “radiation safety” to healthy tissues, but also delivers lower radiopharmaceutical activity to the neoplastic tissue, resulting in a low level of response and a higher relapse rate. The article presents information on the currently used radionuclides in individual radioisotope therapies and on radionuclides newly introduced to the therapeutic market. It discusses the causes of difficulties with the implementation of individualized radioisotope therapies as well as possible changes in the current clinical situation.

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.

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.