3D Monte Carlo bone marrow dosimetry for Lu-177-PSMA therapy with guidance of non-invasive 3D localization of active bone marrow via Tc-99m-anti-granulocyte antibody SPECT/CT

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.

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.

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.

Joint EANM/SNMMI procedure guideline for the use of 177Lu-labeled PSMA-targeted radioligand-therapy (177Lu-PSMA-RLT)

Prostate-specific membrane antigen (PSMA) is expressed by the majority of clinically significant prostate adenocarcinomas, and patients with target-positive disease can easily be identified by PSMA PET imaging. Promising results with PSMA-targeted radiopharmaceutical therapy have already been obtained in early-phase studies using various combinations of targeting molecules and radiolabels. Definitive evidence of the safety and efficacy of [177Lu]Lu-PSMA-617 in combination with standard-of-care has been demonstrated in patients with metastatic castration-resistant prostate cancer, whose disease had progressed after or during at least one taxane regimen and at least one novel androgen-axis drug. Preliminary data suggest that 177Lu-PSMA-radioligand therapy (RLT) also has high potential in additional clinical situations. Hence, the radiopharmaceuticals [177Lu]Lu-PSMA-617 and [177Lu]Lu-PSMA-I&T are currently being evaluated in ongoing phase 3 trials. The purpose of this guideline is to assist nuclear medicine personnel, to select patients with highest potential to benefit from 177Lu-PSMA-RLT, to perform the procedure in accordance with current best practice, and to prepare for possible side effects and their clinical management. We also provide expert advice, to identify those clinical situations which may justify the off-label use of [177Lu]Lu-PSMA-617 or other emerging ligands on an individual patient basis.

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.

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

Purpose

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

Methods

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

Results

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

Conclusion

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

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Advances in Bone Marrow Imaging: Strengths and Limitations from a Clinical Perspective

Conventional magnetic resonance imaging (MRI) remains the modality of choice to image bone marrow. However, the last few decades have witnessed the emergence and development of novel MRI techniques, such as chemical shift imaging, diffusion-weighted imaging, dynamic contrast-enhanced MRI, and whole-body MRI, as well as spectral computed tomography and nuclear medicine techniques. We summarize the technical bases behind these methods, in relation to the common physiologic and pathologic processes involving the bone marrow. We present the strengths and limitations of these imaging methods and consider their added value compared with conventional imaging in assessing non-neoplastic disorders like septic, rheumatologic, traumatic, and metabolic conditions. The potential usefulness of these methods to differentiate between benign and malignant bone marrow lesions is discussed. Finally, we consider the limitations hampering a more widespread use of these techniques in clinical practice.

Optimization of the radiation dosimetry protocol in Lutetium-177-PSMA therapy: toward clinical implementation

BACKGROUND

Dosimetry in [¹⁷⁷Lu]Lu-PSMA therapy is a valuable tool to assess treatment efficacy and toxicity. This study aims to develop a clinically implementable protocol to determine the absorbed dose in organs and tumor lesions after [¹⁷⁷Lu]Lu-PSMA-617 therapy, by reducing the imaging time points and utilizing population-based kinetics with a single scan, with evaluation of its influence on the uncertainty in absorbed dose.

METHODS

Ten patients with metastatic hormone-sensitive prostate cancer received two cycles of [¹⁷⁷Lu]Lu-PSMA-617. Post-treatment imaging was performed at 1 h, 24 h, 48 h, 72 h and 168 h, consisting of three-bed positions SPECT/CT and a whole-body planar scan. Five-time point SPECT dosimetry was performed for lesions and organs with physiological uptake (kidneys, liver and salivary glands) and used as the reference standard. Absorbed dose values for various simplified protocols were compared to the reference standard.

RESULTS

Accurate lesion dosimetry is possible using one-time point SPECT imaging at 168 h, with an increase in uncertainty (20% vs. 14% for the reference standard). By including a second time point, uncertainty was comparable to the reference standard (13%). Organ dosimetry can be performed using a single SPECT at 24 h or 48 h. Dosimetry based on planar scans did not provide accurate dose estimations.

CONCLUSION

Accurate lesion dosimetry in [¹⁷⁷Lu]Lu-PSMA therapy can be performed using a one- or two-time point protocol, making dosimetry assessments more suitable for routine clinical implementation, although dosimetry based om multiple time points is more accurate. Clinical trial registration This study was approved by the Medical Review Ethics Committee Region Arnhem-Nijmegen on January 23, 2018 and was registered on clinicaltrials.gov (NCT03828838).

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.

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

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

Dosimetry in Lu-177-PSMA-617 prostate-specific membrane antigen targeted radioligand therapy: a systematic review

BACKGROUND

177Lu-prostate-specific membrane antigen (PSMA) gained popularity as a choice of agent in the treatment of patients with advanced prostate cancer or metastatic castration-resistant stage of prostate carcinoma (mCRPC) diseases. However, this treatment may cause fatal effects, probably due to unintended irradiation of normal organs. We performed an extensive systematic review to assess the organs at risk and the absorbed dose received by tumor lesions in 177Lu-PSMA therapy.

DESIGN

In this review, published peer-reviewed articles that cover clinical dosimetry in patients following peptide radionuclide ligand therapy using 177Lu-PSMA have been included. Two senior researchers independently checked the articles for inclusion. A systematic search in the database was made using PubMed, Publons and DOAJ. All selected articles were categorized into three groups: (1) clinical studies with the technical description of dosimetry in 177Lu-PSMA therapy (2) organ dosimetry in 177Lu-PSMA therapy or (3) tumor dosimetry in 177Lu-PSMA therapy.

RESULT

In total, 182 citations were identified on PSMA therapy and 17 original articles on 177Lu-PSMA dosimetry were recognized as eligible for review. The median absorbed dose per unit of administered activity for kidneys, salivary, liver, spleen, lacrimal and bone marrow was 0.55, 0.81, 0.1, 0.1, 2.26 and 0.03 Gy/GBq, respectively. The median absorbed dose per unit of activity for tumor lesions was found in a range of 2.71-10.94 Gy/GBq.

CONCLUSION

177Lu-PSMA systemic radiation therapy (SRT) is a well-tolerated and reliable treatment option against the management of the mCRPC stage of prostate carcinoma. Lacrimal glands and salivary glands are the major critical organs in 177Lu-PSMA SRT. Besides, tumors receive 3-6 times higher absorbed doses compared to organs at risk.

EANM dosimetry committee recommendations for dosimetry of 177Lu-labelled somatostatin-receptor- and PSMA-targeting ligands

The purpose of the EANM Dosimetry Committee is to provide recommendations and guidance to scientists and clinicians on patient-specific dosimetry. Radiopharmaceuticals labelled with lutetium-177 (177Lu) are increasingly used for therapeutic applications, in particular for the treatment of metastatic neuroendocrine tumours using ligands for somatostatin receptors and prostate adenocarcinoma with small-molecule PSMA-targeting ligands. This paper provides an overview of reported dosimetry data for these therapies and summarises current knowledge about radiation-induced side effects on normal tissues and dose-effect relationships for tumours. Dosimetry methods and data are summarised for kidneys, bone marrow, salivary glands, lacrimal glands, pituitary glands, tumours, and the skin in case of radiopharmaceutical extravasation. Where applicable, taking into account the present status of the field and recent evidence in the literature, guidance is provided. The purpose of these recommendations is to encourage the practice of patient-specific dosimetry in therapy with 177Lu-labelled compounds. The proposed methods should be within the scope of centres offering therapy with 177Lu-labelled ligands for somatostatin receptors or small-molecule PSMA.

Radiation Dosimetry in 177Lu-PSMA-617 Therapy

Radionuclide therapy using the small molecule PSMA bound to the beta-emitting radionuclide, Lutetium-177 (¹⁷⁷Lu-PSMA) has demonstrated efficacy and survival benefit castrate resistant metastatic disease and represents a novel new line of therapy. Whilst dosimetry was critical for early development, it was not incorporated into either the TheraP or VISION randomized studies, highlighting the difficulty of adopting dosimetry in routine clinical practice. Accumulated clinical experience has also shown that the common (and generally low grade) toxicities such as nausea, xerostomia, and cytopenias are not readily predicted on the basis of dosimetry estimates. The majority of dosimetry and clinical literature deals with the radiopharmaceutical ¹⁷⁷Lu-PSMA-617 which displays relatively consistent patterns of retention among normal tissues and high specificity for metastatic prostate cancer phenotypes. Population dosimetry incorporating estimates to the kidneys, salivary glands, and bone marrow have been widely reported the typical range of doses is becoming well established. There is growing interest on tumor dosimetry in ¹⁷⁷Lu-PSMA-617 therapy as an overall modest side-effect profile from primary organ retention has been observed. A focus away from normal organ dosimetry to whole body tumor dosimetry may enable early prediction of treatment failure. Given the safety of ¹⁷⁷Lu-PSMA there is also potential to escalate administered radioactivity to further improve outcomes. Importantly, the variability of uptake between individuals, both to tumor and normal organs, has also been highlighted which provides some rationale for the utility of personalized radiation analysis to optimize treatment based on potential toxicity thresholds or tumor control. Methods to perform dosimetry using serial post treatment imaging may incorporate planar, 3D SPECT, or hybrid datasets. Reliable measurements may be obtained through either method, however, continued developments in computational analysis are better suited to fully 3D imaging; particularly in conjunction with volumetric CT to assist with alignment and contouring. Dose analysis over sequential treatment cycles is vital to understand the radiobiology of these treatments which is unique compared to external beam therapy due to dose rate, fractionation scheme, and potential for intratumoral nonuniformity.

Kidney Protection with the Radical Scavenger α1-Microglobulin (A1M) during Peptide Receptor Radionuclide and Radioligand Therapy

α₁-Microglobulin (A1M) is an antioxidant found in all vertebrates, including humans. It has enzymatic reductase activity and can scavenge radicals and bind free heme groups. Infused recombinant A1M accumulates in the kidneys and has therefore been successful in protecting kidney injuries in different animal models. In this review, we focus on A1M as a radioprotector of the kidneys during peptide receptor radionuclide/radioligand therapy (PRRT/RLT). Patients with, e.g., neuroendocrine tumors or castration resistant prostate cancer can be treated by administration of radiolabeled small molecules which target and therefore enable the irradiation and killing of cancer cells through specific receptor interaction. The treatment is not curative, and kidney toxicity has been reported as a side effect since the small, radiolabeled substances are retained and excreted through the kidneys. In recent studies, A1M was shown to have radioprotective effects on cell cultures as well as having a similar biodistribution as the somatostatin analogue peptide ¹⁷⁷Lu-DOTATATE after intravenous infusion in mice. Therefore, several animal studies were conducted to investigate the in vivo radioprotective potential of A1M towards kidneys. The results of these studies demonstrated that A1M co-infusion yielded protection against kidney toxicity and improved overall survival in mouse models. Moreover, two different mouse studies reported that A1M did not interfere with tumor treatment itself. Here, we give an overview of radionuclide therapy, the A1M physiology and the results from the radioprotector studies of the protein.

Streamlined Schemes for Dosimetry of 177Lu-Labeled PSMA Targeting Radioligands in Therapy of Prostate Cancer

Simple Summary

In patients with progressive metastasized castration-resistance prostate cancer PSMA radioligand therapies have shown promising results regarding clinical safety and efficacy. Dosimetry is mandatory due to legal regulations and also required for the estimation of doses to organs at risk allowing for individual tailoring of treatment in PSMA-RLT. Due to those factors and the often poor health status of patients which restricts intense dosimetric imaging protocols, there is a clear need for simplified dosimetric approaches in mCRPC patients treated with [¹⁷⁷Lu]Lu-PSMA-617. In this study, we evaluated different dosimetric methodologies and found that a streamlined dosimetric approach is feasible and valid. This approach is based on single time-point imaging at 48 h p.i. in cycle 2 to 6 taking into account kinetic results of a full dosimetric scheme performed only in cycle1. These results might have a relevant impact on patients handling regarding dosimetry during [¹⁷⁷Lu]Lu-PSMA-617 radioligand therapy.

Abstract

(Background) Aim of this retrospective analysis was to investigate in mCRPC patients treated with [¹⁷⁷Lu]Lu-PSMA-617 whether the absorbed dose (AD) in organs at risk (OAR, i.e., kidneys and parotid glands) can be calculated using simplified methodologies with sufficient accuracy. For this calculation, results and kinetics of the first therapy cycle were used. (Methods) 46 patients treated with 2 to 6 cycles of [¹⁷⁷Lu]Lu-PSMA-617 were included. As reference (current clinical standard) full dosimetry of the OAR based on quantitative imaging (whole body scintigraphy and quantitative SPECT/CT at 2, 24, 48 and 72 h p.i.) for every cycle was used. Alternatively, two dosimetry schemes, simplified in terms of image acquisition and dose calculation, were established, both assuming nearly unchanged kinetics of the radiopharmaceutical for subsequent cycles. (Results) In general, for both OAR the simplified methods provided results that were consistent with the dosimetric reference method, both per cycle and in terms of cumulative AD. Best results were obtained when imaging was performed at 48 h p.i. in each of the subsequent cycles. However, both simplified methods tended to underestimate the cumulative AD. (Conclusion) Simplified dosimetry schemes are feasible to tailor multi-cycle [¹⁷⁷Lu]Lu-PSMA-targeted therapies.

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.