Comparison of commercial dosimetric software platforms in patients treated with 177 Lu-DOTATATE for peptide receptor radionuclide therapy

Dosimetry of [177Lu]Lu-PSMA-Targeted Radiopharmaceutical Therapies in Patients with Prostate Cancer: A Comparative Systematic Review and Metaanalysis

Novel theranostic approaches using radiopharmaceuticals targeting prostate-specific membrane antigen (PSMA) have emerged for treating metastatic castration-resistant prostate cancer. The physical properties and commercial availability of 177Lu make it one of the most used radionuclides for radiopharmaceutical therapy (RPT). In this literature review, we aimed at comparing the dosimetry of the most used [177Lu]Lu-PSMA RPT compounds. Methods: This was a systematic review and metaanalysis of [177Lu]Lu-PSMA RPT (617, I&T, and J591) dosimetry in patients with prostate cancer. Absorbed doses in Gy/GBq for each organ at risk (kidney, parotid and submandibular glands, bone marrow, liver, and lacrimal glands) and for tumor lesions (bone and nonbone lesions) were extracted from included articles. These were used to estimate the pooled average absorbed dose of each agent in Gy/GBq and in Gy/cycle, normalized to the injected activity (per cycle) used in the VISION (7.4 GBq), SPLASH (6.8 GBq), and PROSTACT trials (5.8 GBq). Results: Twenty-nine published articles comprising 535 patients were included in the metaanalysis. The pooled doses (weighted average across studies) of [177Lu]Lu-PSMA-617 and [177Lu]Lu-PSMA-I&T were 4.04 Gy/GBq (17 studies, 297 patients) and 4.70 Gy/GBq (10 studies, 153 patients) for the kidney (P = 0.10), 5.85 Gy/GBq (14 studies, 216 patients) and 2.62 Gy/GBq (5 studies, 86 patients) for the parotids (P < 0.01), 5.15 Gy/GBq (5 studies, 81 patients) and 4.35 Gy/GBq (1 study, 18 patients) for the submandibular glands (P = 0.56), 11.03 Gy/GBq (6 studies, 121 patients) and 19.23 Gy/GBq (3 studies, 53 patients) for the lacrimal glands (P = 0.20), 0.24 Gy/GBq (12 studies, 183 patients) and 0.19 Gy/GBq (4 studies, 68 patients) for the bone marrow (P = 0.31), and 1.11 Gy/GBq (9 studies, 154 patients) and 0.56 Gy/GBq (4 studies, 56 patients) for the liver (P = 0.05), respectively. Average tumor doses tended to be higher for [177Lu]Lu-PSMA-617 than for [177Lu]Lu-PSMA-I&T in soft tissue tumor lesions (4.19 vs. 2.94 Gy/GBq; P = 0.26). Dosimetry data of [177Lu]Lu-J591 were limited to one published study of 35 patients with reported absorbed doses of 1.41, 0.32, and 2.10 Gy/GBq to the kidney, bone marrow, and liver, respectively. Conclusion: In this metaanalysis, there was no significant difference in absorbed dose between [177Lu]Lu-PSMA-I&T and [177Lu]Lu-PSMA-617. There was a possible trend toward a higher kidney dose with [177Lu]Lu-PSMA-I&T and a higher tumor lesion dose with [177Lu]Lu-PSMA-617. It remains unknown whether this finding has any clinical impact. The dosimetry methodologies were strikingly heterogeneous among studies, emphasizing the need for standardization.

An International Study of Factors Affecting Variability of Dosimetry Calculations, Part 3: Contribution from Calculating Absorbed Dose from Time-Integrated Activity

Image-based dosimetry-guided radiopharmaceutical therapy has the potential to personalize treatment by limiting toxicity to organs at risk and maximizing the therapeutic effect. The 177Lu dosimetry challenge of the Society of Nuclear Medicine and Molecular Imaging consisted of 5 tasks assessing the variability in the dosimetry workflow. The fifth task investigated the variability associated with the last step, dose conversion, of the dosimetry workflow on which this study is based. Methods: Reference variability was assessed by 2 medical physicists using different software, methods, and all possible combinations of input segmentation formats and time points as provided in the challenge. General descriptive statistics for absorbed dose values from the global submissions from participants were calculated, and variability was measured using the quartile coefficient of dispersion. Results: For the liver, which included lesions with high uptake, variabilities of up to 36% were found. The baseline analysis showed a variability of 29% in absorbed dose results for the liver from datasets where lesions included and excluded were grouped, indicating that variation in how lesions in normal liver were treated was a significant source of variability. For other organs and lesions, variability was within 7%, independently of software used except for the local deposition method. Conclusion: The choice of dosimetry method or software had a small contribution to the overall variability of dose estimates.

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.

Automated segmentation of lesions and organs at risk on [68Ga]Ga-PSMA-11 PET/CT images using self-supervised learning with Swin UNETR

BACKGROUND

Prostate-specific membrane antigen (PSMA) PET/CT imaging is widely used for quantitative image analysis, especially in radioligand therapy (RLT) for metastatic castration-resistant prostate cancer (mCRPC). Unknown features influencing PSMA biodistribution can be explored by analyzing segmented organs at risk (OAR) and lesions. Manual segmentation is time-consuming and labor-intensive, so automated segmentation methods are desirable. Training deep-learning segmentation models is challenging due to the scarcity of high-quality annotated images. Addressing this, we developed shifted windows UNEt TRansformers (Swin UNETR) for fully automated segmentation. Within a self-supervised framework, the model's encoder was pre-trained on unlabeled data. The entire model was fine-tuned, including its decoder, using labeled data.

METHODS

In this work, 752 whole-body [68Ga]Ga-PSMA-11 PET/CT images were collected from two centers. For self-supervised model pre-training, 652 unlabeled images were employed. The remaining 100 images were manually labeled for supervised training. In the supervised training phase, 5-fold cross-validation was used with 64 images for model training and 16 for validation, from one center. For testing, 20 hold-out images, evenly distributed between two centers, were used. Image segmentation and quantification metrics were evaluated on the test set compared to the ground-truth segmentation conducted by a nuclear medicine physician.

RESULTS

The model generates high-quality OARs and lesion segmentation in lesion-positive cases, including mCRPC. The results show that self-supervised pre-training significantly improved the average dice similarity coefficient (DSC) for all classes by about 3%. Compared to nnU-Net, a well-established model in medical image segmentation, our approach outperformed with a 5% higher DSC. This improvement was attributed to our model's combined use of self-supervised pre-training and supervised fine-tuning, specifically when applied to PET/CT input. Our best model had the lowest DSC for lesions at 0.68 and the highest for liver at 0.95.

CONCLUSIONS

We developed a state-of-the-art neural network using self-supervised pre-training on whole-body [68Ga]Ga-PSMA-11 PET/CT images, followed by fine-tuning on a limited set of annotated images. The model generates high-quality OARs and lesion segmentation for PSMA image analysis. The generalizable model holds potential for various clinical applications, including enhanced RLT and patient-specific internal dosimetry.

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.

Technical note: Impact of dose voxel kernel (DVK) values on dosimetry estimates in 177 Lu and 90 Y radiopharmaceutical therapy (RPT) applications

BACKGROUND

Radiopharmaceutical therapy (RPT) is an increasingly adopted modality for treating cancer. There is evidence that the optimization of the treatment based on dosimetry can improve outcomes. However, standardization of the clinical dosimetry workflow still represents a major effort. Among the many sources of variability, the impact of using different Dose Voxel Kernels (DVKs) to generate absorbed dose (AD) maps by convolution with the time-integrated activity (TIA) distribution has not been systematically investigated.

PURPOSE

This study aims to compare DVKs and assess the differences in the ADs when convolving the same TIA map with different DVKs.

METHODS

DVKs of 3 × 3 × 3 mm3 sampling-nine for 177 Lu, nine for 90 Y-were selected from those most used in commercial/free software or presented in prior publications. For each voxel within a 11 × 11 × 11 matrix, the coefficient of variation (CoV) and the percentage difference between maximum and minimum values (% maximum difference) were calculated. The total absorbed dose per decay (SUM), calculated as the sum of all the voxel values in each kernel, was also compared. Publicly available quantitative SPECT images for two patients treated with 177 Lu-DOTATATE and PET images for two patients treated with 90 Y-microspheres were used, including organs at risk (177 Lu: kidneys; 90 Y: liver and healthy liver) and tumors' segmentations. For each patient, the mean AD to the volumes of interest (VOIs) was calculated using the different DVKs, the same TIA map and the same software tool for dose convolution, thereby focusing on the DVK impact. For each VOI, the % maximum difference of the mean AD between maximum and minimum values was computed.

RESULTS

The CoV (% maximum difference) in voxels of normalized coordinates [0,0,0], [0,1,0], and [0,1,1] were 5%(21%), 9%(35%), and 10%(46%) for the 177 Lu DVKs. For the case of 90 Y, these values were 2%(9%), 4%(14%), and 4%(16%). The CoV (% maximum difference) for SUM was 9%(33%) for 177 Lu, and 4%(15%) for 90 Y. The variability of the mean tumor and organ AD was up to 19% and 15% in 177 Lu-DOTATATE and 90 Y-microspheres patients, respectively.

CONCLUSIONS

This study showed a considerable AD variability due exclusively to the use of different DVKs. A concerted effort by the scientific community would contribute to decrease these discrepancies, strengthening the consistency of AD calculation in RPT.

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.

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.

The assessment of left ventricular volume and function in gated small animal 18F-FDG PET/CT imaging: a comparative study of three commercially available software tools

BACKGROUND

Several software tools have been developed for gated PET imaging that use distinct algorithms to analyze tracer uptake, myocardial perfusion, and left ventricle volumes and function. Studies suggest that different software tools cannot be used interchangeably in humans. In this study, we sought to compare the left ventricular parameters in gated 18F-FDG PET/CT imaging in mice by three commercially available software tools: PMOD, MIM, and QGS.

METHODS AND RESULTS

Healthy mice underwent ECG-gated 18F-FDG imaging using a small-animal nanoPET/CT (Mediso) under isoflurane narcosis. Reconstructed gates PET images were subsequently analyzed in three different software tools, and cardiac volume and function (end-diastolic (EDV), end-systolic volumes (ESV), stroke volume (SV), and ejection fraction (EF)) were evaluated. While cardiac volumes correlated well between PMOD, MIM, and QGS, the left ventricular parameters and cardiac function differed in agreement using Bland-Altman analysis. EDV in PMOD vs. QGS: r = 0.85; p < 0.001, MIM vs. QGS: r = 0.92; p < 0.001, and MIM vs. PMOD: r = 0.88; p < 0.001, showed good correlations. Correlation was also found in ESV: PMOD vs. QGS: r = 0.48; p = 0.07, MIM vs QGS: r = 0.79; p < 0.001, and MIM vs. PMOD: r = 0.69; p < 0.01. SV showed good correlations in: PMOD vs. QGS: r = 0.73; p < 0.01, MIM vs. QGS: r = 0.86; p < 0.001, and MIM vs. PMOD: r = 0.92; p < 0.001. However, EF among correlated poorly: PMOD vs. QGS: r = -0.31; p = 0.26, MIM vs. QGS: r = 0.48; p = 0.07, and MIM vs. PMOD: r = 0.23; p = 0.41. Inter-class and intra-class correlation coefficient were > 0.9 underlining repeatability in using PMOD, MIM, and QGS for cardiac volume and function assessment.

CONCLUSIONS

All three commercially available software tools are feasible in small animal cardiac volume assessment in gated 18F-FDG PET/CT imaging. However, due to software-related differences in agreement analysis for cardiac volumes and function, PMOD, MIM, and QGS cannot be used interchangeably in murine research.

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.

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.

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.

Safety and Therapeutic Optimization of Lutetium-177 Based Radiopharmaceuticals

Peptide receptor radionuclide therapy (PRRT) using Lutetium-177 (¹⁷⁷Lu) based radiopharmaceuticals has emerged as a therapeutic area in the field of nuclear medicine and oncology, allowing for personalized medicine. Since the first market authorization in 2018 of [¹⁷⁷Lu]Lu-DOTATATE (Lutathera®) targeting somatostatin receptor type 2 in the treatment of gastroenteropancreatic neuroendocrine tumors, intensive research has led to transfer innovative ¹⁷⁷Lu containing pharmaceuticals to the clinic. Recently, a second market authorization in the field was obtained for [¹⁷⁷Lu]Lu-PSMA-617 (Pluvicto®) in the treatment of prostate cancer. The efficacy of ¹⁷⁷Lu radiopharmaceuticals are now quite well-reported and data on the safety and management of patients are needed. This review will focus on several clinically tested and reported tailored approaches to enhance the risk-benefit trade-off of radioligand therapy. The aim is to help clinicians and nuclear medicine staff set up safe and optimized procedures using the approved ¹⁷⁷Lu based radiopharmaceuticals.

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.

Initial Testing of an Approximated, Fast Calculation Procedure for Personalized Dosimetry in Radionuclide Therapy Based on Planar Whole-Body Scan and Monte-Carlo Specific Dose Rates from the OpenDose Project

Individualized dosimetry in nuclear medicine is currently at least advisable in order to obtain the best risk–benefit balance in terms of the maximal dose to lesions and under-threshold doses to radiosensitive organs. This article aims to propose a procedure for fast dosimetric calculations based on planar whole-body scintigraphy (WBS) images and developed to be employed in everyday clinical practice. Methods: For simplicity and legacy reasons, the method is based on planar imaging dosimetry, complemented with some assumptions on the radiopharmaceutical kinetics empirically derived from single-photon emission tomography/computed tomography (SPECT/CT) image analysis. The idea is to exploit a rough estimate of the time-integrated activity as has been suggested for SPECT/CT dosimetry but using planar images. The resulting further reduction in dose estimation accuracy is moderated by the use of a high-precision Monte-Carlo S-factor, such as those available within the OpenDose project. Results: We moved the problem of individualized dosimetry to a transformed space where comparing doses was imparted to the ICRP Average Male/Female computational phantom, resulting from an activity distribution related to patient’s pharmaceutical uptake. This is a fast method for the personalized dosimetric evaluation of radionuclide therapy, bearing in mind that the resulting doses are meaningful in comparison with thresholds calculated in the same framework. Conclusion: The simplified scheme proposed here can help the community, or even the single physician, establish a quantitative guide-for-the-eye approach to individualized dosimetry.

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.

Accuracy of two dosimetry software programs for 177Lu radiopharmaceutical therapy using voxel-based patient-specific phantoms

Purpose

Virtual dosimetry using voxel-based patient-specific phantoms and Monte Carlo (MC) simulations offer the advantage of having a gold standard against which absorbed doses may be benchmarked to establish the dosimetry accuracy. Furthermore, these reference values assist in investigating the accuracy of the absorbed dose methodologies from different software programs. Therefore, this study aimed to compare the accuracy of the absorbed doses computed using LundADose and OLINDA/EXM 1.0.

Methods

The accuracy was based on ¹⁷⁷Lu-DOTATATE distributions of three voxel-based phantoms. SPECT projection images were simulated for 1, 24, 96, and 168 h post-administration and reconstructed with LundADose using 3D OS-EM reconstruction. Mono-exponential curves were fitted to the bio-kinetic data for the kidneys, liver, spleen, and tumours resulting in SPECT time-integrated activity (SPECT-TIA). The SPECT-TIA were used to compute mean absorbed doses using LundADose (LND-D_SPECT) and OLINDA (OLINDA-D_SPECT) for the organs. Pre-defined true activity images, were used to obtain TRUE-TIA and, together with full MC simulations, computed the true doses (MC-D_True). The dosimetry accuracy was assessed by comparing LND-D_SPECT and OLINDA-D_SPECT to MC-D_True.

Results

Overall, the results presented an overestimation of the mean absorbed dose by LND-D_SPECT compared to the MC-D_True with a dosimetry accuracy ≤6.6%. This was attributed to spill-out activity from the reconstructed LND-D_SPECT, resulting in a higher dose contribution than the MC-D_True. There was a general underestimation (<8.1%) of OLINDA-D_SPECT compared to MC-D_True attributed to the geometrical difference in shape between the voxel-based phantoms and the OLINDA models. Furthermore, OLINDA-D_SPECT considers self-doses while MC-D_True reflects self-doses plus cross-doses.

Conclusion

The better than 10% accuracy suggests that the mean dose values obtained with LND-D_SPECT and OLINDA-D_SPECT approximate the true values. The mean absorbed doses of the two software programs, and the gold standard were comparable. This work shall be of use for optimising ¹⁷⁷Lu dosimetry for clinical applications.

Fast beta-emitter Monte Carlo simulations and full patient dose calculations of targeted radionuclide therapy: introducing egs_mird

BACKGROUND

Targeted Radionuclide Therapy (TRT) is a fast-growing field garnering much interest, with several clinical trials currently underway, that has a steady increase in development of treatment techniques. Unfortunately, within the field and many clinical trials, the dosimetry calculation techniques used remain relatively simple, often using a mix of S-value calculations and kernel convolutions.

PURPOSE

The common TRT calculation techniques, although very quick, can often ignore important aspects of patient anatomy and radionuclide distribution, as well as the interplay there-in. This paper introduces egs_mird, a new Monte Carlo (MC) application built in EGSnrc which allows users to model full patient tissue and density (using clinical CT images) and radionuclide distribution (using clinical PET images) for fast and detailed dose TRT calculation.

METHODS

The novel application egs_mird is introduced along with a general outline of the structure of egs_mird simulations. The general structure of the code, and the track-length estimator scoring implementation for variance reduction, is described. A new egs++ source class egs_internal_source, created to allow detailed patient-wide source distribution, and a modified version of egs_radionuclide_source, changed to be able to work with egs_internal_source, are also described. The new code is compared to other MC calculations of S-values kernels of ¹³¹ I, ⁹⁰ Y, and ¹⁷⁷ Lu in the literature, along with further self-validation using a histogram variant of the electron Fano test. Several full patient prostate ¹⁷⁷ Lu TRT prostate cancer treatment simulations are performed using a single set of patient DICOM CT and [¹⁸ F]-DCFPyL PET data.

RESULTS

Good agreement is found between S-value kernels calculated using egs_mird with egs_internal_source and those found in the literature. Calculating 1000 doses (individual voxel uncertainties of ∼0.05%) in a voxel grid Fano test for monoenergetic 500 keV electrons and ¹⁷⁷ Lu electrons results in 94 and 99% of the doses being within 0.1% of the expected dose, respectively. For a hypothetical ¹⁷⁷ Lu treatment, patient prostate, rectum, bone marrow, and bladder dose volume histograms (DVHs) results did not vary significantly when using the track-length estimator and not modelling electron transport, modelling bone marrow explicitly (rather than using generic tissue compositions), and reducing activity to voxels containing partial or full calcifications to half or none, respectively. Dose profiles through different regions demonstrate there are some differences with model choices not seen in the DVH. Simulations using the track-length estimator can be completed in under 15 minutes (∼30 minutes when using standard interaction scoring).

CONCLUSION

This work shows egs_mird to be a reliable MC code for computing TRT doses as realistically as the patient CT and PET data allow. Furthermore, the code can compute doses to sub-1% uncertainty within 15 minutes, with little to no optimization. Thus, this work supports the use of egs_mird for dose calculations in TRT. This article is protected by copyright. All rights reserved.

Proof-of-concept of DosiTest: A virtual multicentric clinical trial for assessing uncertainties in molecular radiotherapy dosimetry

Clinical dosimetry in molecular radiotherapy (MRT) is a multi-step procedure, prone to uncertainties at every stage of the dosimetric workflow. These are difficult to assess, especially as some are complex or even impossible to measure experimentally. The DosiTest project was initiated to assess the variability associated with clinical dosimetry, by setting up a 'virtual' multicentric clinical dosimetry trial based on Monte Carlo (MC) modelling. A reference patient model with a realistic geometry and activity input for a specific tracer is considered. Reference absorbed dose rate distribution maps are generated at various time-points from MC modelling, combining precise information on density and activity distributions (voxel wise). Then, centre-specific calibration and patient SPECT/CT datasets are modelled, on which the clinical centres can perform clinical (i.e. image-based) dosimetry. The results of this dosimetric analysis can be benchmarked against the reference dosimetry to assess the variability induced by implementing different clinical dosimetry approaches. The feasibility of DosiTest is presented here for a clinical situation of therapeutic administration of ¹⁷⁷Lu-DOTATATE (Lutathera®) peptide receptor radionuclide therapy (PRRT). From a real patient dataset composed of 5 SPECT/CT images and associated calibrations, we generated the reference absorbed dose rate images with GATE. Then, simulated SPECT/CT image generation based on GATE was performed, both for a calibration phantom and virtual patient images. Based on this simulated dataset, image-based dosimetry could be performed, and compared with reference dosimetry. The good agreement, between real and simulated images, and between reference and image-based dosimetry established the proof of concept of DosiTest.

Personalized Dosimetry in Targeted Radiation Therapy: A Look to Methods, Tools and Critical Aspects

Targeted radiation therapy (TRT) is a strategy increasingly adopted for the treatment of different types of cancer. The urge for optimization, as stated by the European Council Directive (2013/59/EURATOM), requires the implementation of a personalized dosimetric approach, similar to what already happens in external beam radiation therapy (EBRT). The purpose of this paper is to provide a thorough introduction to the field of personalized dosimetry in TRT, explaining its rationale in the context of optimization and describing the currently available methodologies. After listing the main therapies currently employed, the clinical workflow for the absorbed dose calculation is described, based on works of the most experienced authors in the literature and recent guidelines. Moreover, the widespread software packages for internal dosimetry are presented and critical aspects discussed. Overall, a selection of the most important and recent articles about this topic is provided.

Joint EANM, SNMMI and IAEA enabling guide: how to set up a theranostics centre

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 tumours 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 tumour such as prostate cancer requires the expansion of existing and the establishment of new theranostics centres. 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 theranostics centres. 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.

Quantitative SPECT/CT for dosimetry of peptide receptor radionuclide therapy

Neuroendocrine tumors (NETs) are uncommon malignancies of increasing incidence and prevalence. As these slow growing tumors usually overexpress somatostatin receptors (SSTRs), the use of ⁶⁸Ga-DOTA-peptides (gallium-68 chelated with dodecane tetra-acetic acid to somatostatin), which bind to the SSTRs, allows for PET based imaging and selection of patients for peptide receptor radionuclide therapy (PRRT). PRRT with radiolabeled somatostatin analogues such as ¹⁷⁷Lu-DOTATATE (lutetium-177-[DOTA,Tyr³]-octreotate), is mainly used for the treatment of metastatic or inoperable NETs. However, PRRT is generally administered at a fixed injected activity in order not to exceed dose limits in critical organs, which is suboptimal given the variability in radiopharmaceutical uptake among patients. Advances in SPECT (single photon emission computed tomography) imaging enable the absolute quantitative measure of the true radiopharmaceutical distribution providing for PRRT dosimetry in each patient. Personalized PRRT based on patient-specific dosimetry could improve therapeutic efficacy by optimizing effective tumor absorbed dose while limiting treatment related radiotoxicity.

An International Study of Factors Affecting Variability of Dosimetry Calculations, Part 1: Design and Early Results of the SNMMI Dosimetry Challenge

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

Overview of commercial treatment planning systems for targeted radionuclide therapy

INTRODUCTION

Targeted Radionuclide Therapy (TRT) is a branch of cancer medicine dealing with the therapeutic use of radioisotopes associated with biological vectors accumulating in the tumors/targets, indicated as Molecular Radiotherapy (MRT), or directly injected into the arteries that supply blood to liver tumour vasculature, indicated as Selective RT (SRT). The aim of this work is to offer a panoramic view on the increasing number of commercially-available TRT treatment planning systems (TPSs).

MATERIALS AND METHODS

A questionnaire was sent to manufacturers' representatives. Academic software were not considered. Questions were grouped as follows: general information, clinical workflow, calibration procedure, image processing/reconstruction, image registration and segmentation tools, time-activity curve (TAC) fitting and absorbed dose calculation.

RESULTS

All software reported have CE-marking. TPSs were divided between SRT-dedicated software [4] and MRT [5] dosimetry software. In SRT, since no kinetic process is involved, absorbed dose calculation does not require TAC fitting, and image registration is not fully developed in all TPS. All software requires a radionuclide-specific calibration. In SRT, a relative image calibration can be obtained by scaling the counts to a known activity. Automated VOI contouring and rigid/deformable propagation between different acquisitions time-points is implemented in most TPSs, although DICOM export is rare. Different TAC fits are available depending on the number of time-points. Voxel S-value and Local deposition methods are the most frequent dosimetric approaches; dose-voxel kernel convolution and semi-Monte Carlo method are also available.

CONCLUSIONS

Available TPSs allows performing personalized dosimetry in clinical practice. Individual variations in methodology/algorithms must be considered in the standardisation/harmonization processes.

Role of Artificial Intelligence in Theranostics:: Toward Routine Personalized Radiopharmaceutical Therapies

We highlight emerging uses of artificial intelligence (AI) in the field of theranostics, focusing on its significant potential to enable routine and reliable personalization of radiopharmaceutical therapies (RPTs). Personalized RPTs require patient-specific dosimetry calculations accompanying therapy. Additionally we discuss the potential to exploit biological information from diagnostic and therapeutic molecular images to derive biomarkers for absorbed dose and outcome prediction; toward personalization of therapies. We try to motivate the nuclear medicine community to expand and align efforts into making routine and reliable personalization of RPTs a reality.

Personalized dosimetry of177Lu-DOTATATE: a comparison of organ- and voxel-level approaches using open-access images

¹⁷⁷Lu-DOTATATE (Lutathera^®) enables targeted radionuclide therapy of neuroendocrine tumors expressing somatostatin receptor type 2. Though patient-specific dosimetry estimates may be clinically important for predicting absorbed dose-effect relationships, there are multiple relevant dosimetry paradigms which are distinct in terms of clinical effort, numerical output and added-value. This work compares three different approaches for¹⁷⁷Lu-DOTATATE dosimetry, including 1) an organ-level approach based on reference phantom MIRD S-values scaled to patient-specific organ masses (MIRDcalc), 2) an organ-level approach based on Monte Carlo simulation in a patient-specific mesh phantoms (PARaDIM), and 3) a 3D approach based on Monte Carlo simulation in patient-specific voxel phantoms.Method. Serial quantitative SPECT/CT images for two patients receiving¹⁷⁷Lu-DOTATATE therapy were obtained from archive in theDeep Bluedatabase. For each patient, the serial CT images were co-registered to the first time point CT using a deformable registration technique aided by virtual landmarks placed in the kidney pelves and the lesion foci. The co-registered SPECT images were integrated voxel-wise to generate time-integrated activity maps. Lesions, kidneys, liver, spleen, lungs, compact bone, spongiosa, and rest of body were segmented at the first imaging time point and overlaid on co-registered integrated activity maps. The resultant segmentation was used for three purposes: 1) to generate patient-specific phantoms, 2) to determine organ-level time-integrated activities, and 3) to generate dose volume histograms from 3D voxel-based calculations.Results. Mean absorbed doses were computed for lesions and 48 tissues with MIRDcalc software. Mean organ absorbed doses and dose volume histograms were obtained for lesions and 6 tissues with the voxel Monte Carlo approach. Lesion- and organ-level absorbed dose estimates agreed within ±26% for the lesions and ±13% for the critical organs, among the different methods tested. Overall good agreement was observed with the dosimetry estimates from the NETTER-1 trial.Conclusions. For personalized¹⁷⁷Lu-DOTATATE dosimetry, a combined approach was determined to be valuable, which utilized two dose calculation methods supported by a single image processing workflow. In the absence of quantitative imaging limitations, the voxel Monte Carlo method likely provides valuable information to guide treatment by considering absorbed dose non-uniformity in lesions and organs at risk. The patient-scaled reference phantom method also provides valuable information, including absorbed dose estimates for non-segmented organs, and more accurate dose estimates for complex radiosensitive organs including the active marrow.

Differences among [18F]FDG PET-derived parameters in lung cancer produced by three software packages

Investigation of differences in derived [18F]FDG PET metabolic and volumetric parameters among three different software programs in lung cancer. A retrospective analysis was performed on a group of 98 lung cancer patients who underwent a baseline [18F]FDG PET/CT study. To assess appropriate delineation methods, the NEMA phantom study was first performed using the following software: Philips EBW (Extended Brilliance Workstation), MIM Software and Rover. Based on this study, the best cut-off methods (dependent on tumour size) were selected, extracted and applied for lung cancer delineation. Several semiquantitative [18F]FDG parameters (SUVmax, SUVmean, TLG and MTV) were assessed and compared among the three software programs. The parameters were assessed based on body weight (BW), lean body mass (LBM) and Bq/mL. Statistically significant differences were found in SUVmean (LBM) between MIM Software and Rover (4.62 ± 2.15 vs 4.84 ± 1.20; p < 0.005), in SUVmean (Bq/mL) between Rover and Philips EBW (21,852.30 ± 21,821.23 vs 19,274.81 ± 13,340.28; p < 0.005) and Rover and MIM Software (21,852.30 ± 21,821.23 vs 19,399.40 ± 10,051.30; p < 0.005), and in MTV between MIM Software and Philips EBW (19.87 ± 25.83 vs 78.82 ± 228.00; p = 0.0489). This study showed statistically significant differences in the estimation of semiquantitative parameters using three independent image analysis tools. These findings are important for performing further diagnostic and treatment procedures in lung cancer patients.

Generation of clinical 177Lu SPECT/CT images based on Monte Carlo simulation with GATE

PURPOSE

Patient-specific dosimetry in MRT relies on quantitative imaging, pharmacokinetic assessment and absorbed dose calculation. The DosiTest project was initiated to evaluate the uncertainties associated with each step of the clinical dosimetry workflow through a virtual multicentric clinical trial. This work presents the generation of simulated clinical SPECT datasets based on GATE Monte Carlo modelling with its corresponding experimental CT image, which can subsequently be processed by commercial image workstations.

METHODS

This study considers a therapy cycle of 6.85 GBq ¹⁷⁷Lu-labelled DOTATATE derived from an IAEA-Coordinated Research Project (E23005) on "Dosimetry in Radiopharmaceutical therapy for personalised patient treatment". Patient images were acquired on a GE Infinia-Hawkeye 4 gamma camera using a medium energy (ME) collimator. Simulated SPECT projections were generated based on experimental time points and validated against experimental SPECT projections using flattened profiles and gamma index. The simulated projections were then incorporated into the patient SPECT/CT DICOM envelopes for processing and their reconstruction within a commercial image workstation.

RESULTS

Gamma index passing rate (2% - 1 pixel criteria) between 95 and 98% and average gamma between 0.28 and 0.35 among different time points revealed high similarity between simulated and experimental images. Image reconstruction of the simulated projections was successful on HERMES and Xeleris workstations, a major step forward for the initiation of a multicentric virtual clinical dosimetry trial based on simulated SPECT/CT images.

CONCLUSIONS

Realistic ¹⁷⁷Lu patient SPECT projections were generated in GATE. These modelled datasets will be circulated to different clinical departments to perform dosimetry in order to assess the uncertainties in the entire dosimetric chain.

Influence of dosimetry method on bone lesion absorbed dose estimates in PSMA therapy: application to mCRPC patients receiving Lu-177-PSMA-I&T

BACKGROUND

Patients with metastatic, castration-resistant prostate cancer (mCRPC) present with an increased tumor burden in the skeleton. For these patients, Lutetium-177 (Lu-177) radioligand therapy targeting the prostate-specific membrane antigen (PSMA) has gained increasing interest with promising outcome data. Patient-individualized dosimetry enables improvement of therapy success with the aim of minimizing absorbed dose to organs at risk while maximizing absorbed dose to tumors. Different dosimetric approaches with varying complexity and accuracy exist for this purpose. The Medical Internal Radiation Dose (MIRD) formalism applied to tumors assumes a homogeneous activity distribution in a sphere with unit density for derivation of tumor S values (TSV). Voxel S value (VSV) approaches can account for heterogeneous activities but are simulated for a specific tissue. Full patient-individual Monte Carlo (MC) absorbed dose simulation addresses both, heterogeneous activity and density distributions. Subsequent CT-based density weighting has the potential to overcome the assumption of homogeneous density in the MIRD formalism with TSV and VSV methods, which could be a major limitation for the application in bone metastases with heterogeneous density. The aim of this investigation is a comparison of these methods for bone lesion dosimetry in mCRPC patients receiving Lu-177-PSMA therapy.

RESULTS

In total, 289 bone lesions in 15 mCRPC patients were analyzed. Percentage difference (PD) of average absorbed dose per lesion compared to MC, averaged over all lesions, was + 14 ± 10% (min: - 21%; max: + 56%) for TSVs. With lesion-individual density weighting using Hounsfield Unit (HU)-to-density conversion on the patient's CT image, PD was reduced to - 8 ± 1% (min: - 10%; max: - 3%). PD on a voxel level for three-dimensional (3D) voxel-wise dosimetry methods, averaged per lesion, revealed large PDs of + 18 ± 11% (min: - 27%; max: + 58%) for a soft tissue VSV approach compared to MC; after voxel-wise density correction, this was reduced to - 5 ± 1% (min: - 12%; max: - 2%).

CONCLUSION

Patient-individual MC absorbed dose simulation is capable to account for heterogeneous densities in bone lesions. Since the computational effort prevents its routine clinical application, TSV or VSV dosimetry approaches are used. This study showed the necessity of lesion-individual density weighting for TSV or VSV in Lu-177-PSMA therapy bone lesion dosimetry.

Clinical implementation of PLANET® Dose for dosimetric assessment after [177Lu]Lu-DOTA-TATE: comparison with Dosimetry Toolkit® and OLINDA/EXM® V1.0

Background

The aim of this study was to compare a commercial dosimetry workstation (PLANET® Dose) and the dosimetry approach (GE Dosimetry Toolkit® and OLINDA/EXM® V1.0) currently used in our department for quantification of the absorbed dose (AD) to organs at risk after peptide receptor radionuclide therapy with [¹⁷⁷Lu]Lu-DOTA-TATE.

Methods

An evaluation on phantom was performed to determine the SPECT calibration factor variations over time and to compare the Time Integrated Activity Coefficients (TIACs) obtained with the two approaches. Then, dosimetry was carried out with the two tools in 21 patients with neuroendocrine tumours after the first and second injection of 7.2 ± 0.2 GBq of [¹⁷⁷Lu]Lu-DOTA-TATE (40 dosimetry analyses with each software). SPECT/CT images were acquired at 4 h, 24 h, 72 h and 192 h post-injection and were reconstructed using the Xeleris software (General Electric). The liver, spleen and kidneys masses and TIACs were determined using Dosimetry Toolkit® (DTK) and PLANET® Dose. The ADs were calculated using OLINDA/EXM® V1.0 and the Local Deposition Method (LDM) or Dose voxel-Kernel convolution (DK) on PLANET® Dose.

Results

With the phantom, the 3D calibration factors showed a slight variation (0.8% and 3.3%) over time, and TIACs of 225.19 h and 217.52 h were obtained with DTK and PLANET® Dose, respectively. In patients, the root mean square deviation value was 8.9% for the organ masses, 8.1% for the TIACs, and 9.1% and 7.8% for the ADs calculated with LDM and DK, respectively. The Lin’s concordance correlation coefficient was 0.99 and the Bland–Altman plot analysis estimated that the AD value difference between methods ranged from − 0.75 to 0.49 Gy, from − 0.20 to 0.64 Gy, and from − 0.43 to 1.03 Gy for 95% of the 40 liver, kidneys and spleen dosimetry analyses. The dosimetry method had a minor influence on AD differences compared with the image registration and organ segmentation steps.

Conclusions

The ADs to organs at risk obtained with the new workstation PLANET® Dose are concordant with those calculated with the currently used software and in agreement with the literature. These results validate the use of PLANET® Dose in clinical routine for patient dosimetry after targeted radiotherapy with [¹⁷⁷Lu]Lu-DOTA-TATE.

Scientific Developments in Imaging and Dosimetry for Molecular Radiotherapy

Molecular radiotherapy is a rapidly developing field with new vector and isotope combinations continually added to market. As with any radiotherapy treatment, it is vital that the absorbed dose and toxicity profile are adequately characterised. Methodologies for absorbed dose calculations for radiopharmaceuticals were generally developed to characterise stochastic effects and not suited to calculations on a patient-specific basis. There has been substantial scientific and technological development within the field of molecular radiotherapy dosimetry to answer this challenge. The development of imaging systems and advanced processing techniques enable the acquisition of accurate measurements of radioactivity within the body. Activity assessment combined with dosimetric models and radiation transport algorithms make individualised absorbed dose calculations not only feasible, but commonplace in a variety of commercially available software packages. The development of dosimetric parameters beyond the absorbed dose has also allowed the possibility to characterise the effect of irradiation by including biological parameters that account for radiation absorbed dose rates, gradients and spatial and temporal energy distribution heterogeneities. Molecular radiotherapy is in an exciting time of its development and the application of dosimetry in this field can only have a positive influence on its continued progression.