Effect of Tumor Perfusion and Receptor Density on Tumor Control Probability in 177Lu-DOTATATE Therapy: An In Silico Analysis for Standard and Optimized Treatment

Absorbed Dose-Response Relationship in Patients with Gastroenteropancreatic Neuroendocrine Tumors Treated with [177Lu]Lu-DOTATATE: One Step Closer to Personalized Medicine

[177Lu]Lu-DOTATATE has been approved for progressive and inoperable gastroenteropancreatic neuroendocrine tumors (GEP-NETs) that overexpress somatostatin receptors. The absorbed doses by limiting organs and tumors can be quantified by serial postinfusion scintigraphy measurements of the γ-emissions from 177Lu. The objective of this work was to explore how postinfusion [177Lu]Lu-DOTATATE dosimetry could influence clinical management by predicting treatment efficacy (tumor shrinkage and survival) and toxicity. Methods: Patients with GEP-NETs treated with [177Lu]Lu-DOTATATE between 2016 and 2022 and who underwent dosimetry were included. Absorbed doses were calculated for healthy organs (liver, kidneys, bone marrow, and spleen) and tumors using PLANET Dose and the local energy deposition method based on serial posttreatment SPECT/CT. Up to 5 lesions per site were selected and measured on images collected at baseline and 3 mo after treatment end (measurement masked to the somatostatin receptor imaging uptake). For toxicity assessment, laboratory parameters were regularly monitored. Clinical data, including time to death or progression, were collected from the patients' health records. Correlations between absorbed doses by organs and toxicity and between absorbed doses by lesions and tumor volume variation were studied using regression models. Results: In total, 35 dosimetric studies were performed in patients with mostly grade 2 (77%) tumors and metastases in liver (89%), lymph nodes (77%), and bone (34%), and 146 lesions were analyzed: 1-9 lesions per patient, mostly liver metastases (65%) and lymph nodes (25%). The median total absorbed dose by tumors was 94.4 Gy. The absorbed doses by tumors significantly decreased between cycles. The absorbed dose by tumors was significantly associated with tumor volume variation (P < 0.001) 3 mo after treatment end, and it was a significant prognostic factor for survival. Toxicity analysis showed a correlation between the decrease of hematologic parameters such as lymphocytes or platelet concentrations and the absorbed doses by the spleen or bone marrow. The mean absorbed dose by the kidneys was not correlated with nephrotoxicity during the studied period. Conclusion: In patients treated with [177Lu]Lu-DOTATATE for GEP-NETs, tumor and healthy organ dosimetry can predict survival and toxicities, thus influencing clinical management.

Radiopharmaceutical transport in solid tumors via a 3-dimensional image-based spatiotemporal model

Lutetium-177 prostate-specific membrane antigen (177Lu-PSMA)-targeted radiopharmaceutical therapy is a clinically approved treatment for patients with metastatic castration-resistant prostate cancer (mCRPC). Even though common practice reluctantly follows "one size fits all" approach, medical community believes there is significant room for deeper understanding and personalization of radiopharmaceutical therapies. To pursue this aim, we present a 3-dimensional spatiotemporal radiopharmaceutical delivery model based on clinical imaging data to simulate pharmacokinetic of 177Lu-PSMA within the prostate tumors. The model includes interstitial flow, radiopharmaceutical transport in tissues, receptor cycles, association/dissociation with ligands, synthesis of PSMA receptors, receptor recycling, internalization of radiopharmaceuticals, and degradation of receptors and drugs. The model was studied for a range of values for injection amount (100-1000 nmol), receptor density (10-500 nmol•l-1), and recycling rate of receptors (10-4 to 10-1 min-1). Furthermore, injection type, different convection-diffusion-reaction mechanisms, characteristic time scales, and length scales are discussed. The study found that increasing receptor density, ligand amount, and labeled ligands improved radiopharmaceutical uptake in the tumor. A high receptor recycling rate (0.1 min-1) increased radiopharmaceutical concentration by promoting repeated binding to tumor cell receptors. Continuous infusion results in higher radiopharmaceutical concentrations within tumors compared to bolus administration. These insights are crucial for advancing targeted therapy for prostate cancer by understanding the mechanism of radiopharmaceutical distribution in tumors. Furthermore, measures of characteristic length and advection time scale were computed. The presented spatiotemporal tumor transport model can analyze different physiological parameters affecting 177Lu-PSMA delivery.

A PBPK model for PRRT with [177Lu]Lu-DOTA-TATE: Comparison of model implementations in SAAM II and MATLAB/SimBiology

Physiologically based pharmacokinetic (PBPK) models offer the ability to simulate and predict the biodistribution of radiopharmaceuticals and have the potential to enable individualised treatment planning in molecular radiotherapy. The objective of this study was to develop and implement a whole-body compartmental PBPK model for peptide receptor radionuclide therapy (PRRT) with [177Lu]Lu-DOTA-TATE in SimBiology to allow for more complex analyses. The correctness of the model implementation was ensured by comparing its outputs, such as the time-integrated activity (TIA), with those of a PBPK model implemented in SAAM II software.

METHODS

A combined PBPK model for [68Ga]Ga-DOTA-TATE and [177Lu]Lu-DOTA-TATE was developed and implemented in both SAAM II and SimBiology. A retrospective analysis of 12 patients with metastatic neuroendocrine tumours (NETs) was conducted. First, time-activity curves (TACs) and TIAs from the two software were calculated and compared for identical parameter values. Second, pharmacokinetic parameters were fitted to activity concentrations, analysed and compared.

RESULTS

The PBPK model implemented in SimBiology produced TIA results comparable to those generated by the model implemented in SAAM II, with a relative deviation of less than 0.5% when using the same input parameters. The relative deviation of the fitted TIAs was less than 5% when model parameter values were fitted to the measured activity concentrations.

CONCLUSION

The proposed PBPK model implemented in SimBiology can be used for dosimetry in radioligand therapy and TIA prediction. Its outputs are similar to those generated by the PBPK model implemented in SAAM II, confirming the correctness of the model implementation in SimBiology.

Predicting [177Lu]Lu-HA-DOTATATE kidney and tumor accumulation based on [68Ga]Ga-HA-DOTATATE diagnostic imaging using semi-physiological population pharmacokinetic modeling

BACKGROUND

Prediction of [177Lu]Lu-HA-DOTATATE kidney and tumor uptake based on diagnostic [68Ga]Ga-HA-DOTATATE imaging would be a crucial step for precision dosing of [177Lu]Lu-HA-DOTATATE. In this study, the population pharmacokinetic (PK) differences between [177Lu]Lu-HA-DOTATATE and [68Ga]Ga-HA-DOTATATE were assessed and subsequently [177Lu]Lu-HA-DOTATATE was predicted based on [68Ga]Ga-HA-DOTATATE imaging.

METHODS

A semi-physiological nonlinear mixed-effects model was developed for [68Ga]Ga-HA-DOTATATE and [177Lu]Lu-HA-DOTATATE, including six compartments (representing blood, spleen, kidney, tumor lesions, other somatostatin receptor expressing organs and a lumped rest compartment). Model parameters were fixed based on a previously developed physiologically based pharmacokinetic model for [68Ga]Ga-HA-DOTATATE. For [177Lu]Lu-HA-DOTATATE, PK parameters were based on literature values or estimated based on scan data (four time points post-injection) from nine patients. Finally, individual [177Lu]Lu-HA-DOTATATE uptake into tumors and kidneys was predicted based on individual [68Ga]Ga-HA-DOTATATE scan data using Bayesian estimates. Predictions were evaluated compared to observed data using a relative prediction error (RPE) for both area under the curve (AUC) and absorbed dose. Lastly, to assess the predictive value of diagnostic imaging to predict therapeutic exposure, individual prediction RPEs (using Bayesian estimation) were compared to those from population predictions (using the population model).

RESULTS

Population uptake rate parameters for spleen, kidney and tumors differed by a 0.29-fold (15% relative standard error (RSE)), 0.49-fold (15% RSE) and 1.43-fold (14% RSE), respectively, for [177Lu]Lu-HA-DOTATATE compared to [68Ga]Ga-HA-DOTATATE. Model predictions adequately described observed data in kidney and tumors for both peptides (based on visual inspection of goodness-of-fit plots). Individual predictions of tumor uptake were better (RPE AUC -40 to 28%) compared to kidney predictions (RPE AUC -53 to 41%). Absorbed dose predictions were less predictive for both tumor and kidneys (RPE tumor and kidney -51 to 44% and -58 to 82%, respectively). For most patients, [177Lu]Lu-HA-DOTATATE tumor accumulation predictions based on individual PK parameters estimated from diagnostic imaging outperformed predictions based on population parameters.

CONCLUSION

Our semi-physiological PK model indicated clear differences in PK parameters for [68Ga]Ga-HA-DOTATATE and [177Lu]Lu-HA-DOTATATE. Diagnostic images provided additional information to individually predict [177Lu]Lu-HA-DOTATATE tumor uptake compared to using a population approach. In addition, individual predictions indicated that many aspects, apart from PK differences, play a part in predicting [177Lu]Lu-HA-DOTATATE distribution.

Clinical Pharmacokinetics of Radiopharmaceuticals from SPECT/CT Image Acquisition by Contouring in Patients with Gastroenteropancreatic Neuroendocrine Tumors: Lu-177 DOTATATE (Lutathera®) Case

BACKGROUND AND OBJECTIVE

Lu-177 DOTATATE (Lutathera^®) is a radiolabeled analog of somatostatin administered intravenously in patients with somatostatin receptor-positive gastroenteropancreatic neuroendocrine tumors. Biodistribution of Lu-177 DOTATATE in tumor and healthy tissues can be monitored by serial post-injection scintigraphy imaging. Patient exposure to the drug is variable with the recommended fixed dosage, and hence there is a variable response to treatment. The aim of this work was to study the pharmacokinetics of Lu-177 DOTATATE by a population modeling approach, based on single-photon emission computed tomography (SPECT)/computed tomography (CT) images used as surrogate of plasma concentrations to study the interindividual variability and finally optimize an individual dosage.

METHODS

From a retrospective study, SPECT/CT images were acquired at 4 h, 24 h, 72 h, and 192 h postadministration. From these images, volumic activities were calculated in blood and bone marrow. An individual non-compartmental pharmacokinetic analysis was performed, and the mean pharmacokinetic parameters of each tissue were compared together and with reference data. Blood volumic activities were then used to perform a population pharmacokinetic analysis (NONMEM).

RESULTS

The pharmacokinetic parameters (non-compartmental analysis) obtained from blood (clearance [CL] = 2.65 L/h, volume of distribution at steady state [Vss] = 309 L, elimination half-life [t_1/2] = 86.3 h) and bone marrow (CL =1.68 L/h, Vss = 233 L, t_1/2 = 98.8 h) were statistically different from each other and from reference values (CL = 4.50 L/h, Vss = 460 L, t_1/2 = 71.0 h) published in the literature. SPECT/CT blood images were used as a surrogate of plasma concentrations to develop a population pharmacokinetic model. Weight was identified as covariate on volume of the central compartment, reducing the interindividual variability of all population pharmacokinetic parameters.

CONCLUSION

This study is a proof of concept that obtaining pharmacokinetic parameters with image-based blood concentration is possible. Obtaining observed concentrations from SPECT/CT images, without the need for blood sampling, is a real advantage for the patient and the drug monitoring. Pharmacokinetic modeling could be combined with a deep learning model for automatic contouring and allow precise patient-specific dose adjustment in a non-invasive manner.

A physiologically based pharmacokinetic model for [68Ga]Ga-(HA-)DOTATATE to predict whole-body distribution and tumor sink effects in GEP-NET patients

BACKGROUND

Little is known about parameters that have a relevant impact on (dis)similarities in biodistribution between various ⁶⁸Ga-labeled somatostatin analogues. Additionally, the effect of tumor burden on organ uptake remains unclear. Therefore, the aim of this study was to describe and compare organ and tumor distribution of [⁶⁸Ga]Ga-DOTATATE and [⁶⁸Ga]Ga-HA-DOTATATE using a physiologically based pharmacokinetic (PBPK) model and to identify factors that might cause biodistribution and tumor uptake differences between both peptides. In addition, the effect of tumor burden on peptide biodistribution in gastroenteropancreatic (GEP) neuroendocrine tumor (NET) patients was assessed.

METHODS

A PBPK model was developed for [⁶⁸Ga]Ga-(HA-)DOTATATE in GEP-NET patients. Three tumor compartments were added, representing primary tumor, liver metastases and other metastases. Furthermore, reactions describing receptor binding, internalization and recycling, renal clearance and intracellular degradation were added to the model. Scan data from GEP-NET patients were used for evaluation of model predictions. Simulations with increasing tumor volumes were performed to assess the tumor sink effect.

RESULTS

Data of 39 and 59 patients receiving [⁶⁸Ga]Ga-DOTATATE and [⁶⁸Ga]Ga-HA-DOTATATE, respectively, were included. Evaluations showed that the model adequately described image-based patient data and that different receptor affinities caused organ uptake dissimilarities between both peptides. Sensitivity analysis indicated that tumor blood flow and blood volume impacted tumor distribution most. Tumor sink predictions showed a decrease in spleen uptake with increasing tumor volume, which seemed clinically relevant for patients with total tumor volumes higher than ~ 550 mL.

CONCLUSION

The developed PBPK model adequately predicted tumor and organ uptake for this GEP-NET population. Relevant organ uptake differences between [⁶⁸Ga]Ga-DOTATATE and [⁶⁸Ga]Ga-HA-DOTATATE were caused by different affinity profiles, while tumor uptake was mainly affected by tumor blood flow and blood volume. Furthermore, tumor sink predictions showed that for the majority of patients a tumor sink effect is not expected to be clinically relevant.

Theranostic digital twins for personalized radiopharmaceutical therapies: Reimagining theranostics via computational nuclear oncology

This work emphasizes that patient data, including images, are not operable (clinically), but that digital twins are. Based on the former, the latter can be created. Subsequently, virtual clinical operations can be performed towards selection of optimal therapies. Digital twins are beginning to emerge in the field of medicine. We suggest that theranostic digital twins (TDTs) are amongst the most natural and feasible flavors of digitals twins. We elaborate on the importance of TDTs in a future where 'one-size-fits-all' therapeutic schemes, as prevalent nowadays, are transcended in radiopharmaceutical therapies (RPTs). Personalized RPTs will be deployed, including optimized intervention parameters. Examples include optimization of injected radioactivities, sites of injection, injection intervals and profiles, and combination therapies. Multi-modal multi-scale images, combined with other data and aided by artificial intelligence (AI) techniques, will be utilized towards routine digital twinning of our patients, and will enable improved deliveries of RPTs and overall healthcare.

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

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

Know thy tumour: Biomarkers to improve treatment of molecular radionuclide therapy

Molecular radionuclide therapy (MRT) is an effective treatment for both localised and disseminated tumours. Biomarkers can be used to identify potential subtypes of tumours that are known to respond better to standard MRT protocols. These enrolment-based biomarkers can further be used to develop dose-response relationships using image-based dosimetry within these defined subtypes. However, the biological identity of the cancers treated with MRT are commonly not well-defined, particularly for neuroendocrine neoplasms. The biological heterogeneity of such cancers has hindered the establishment of dose-responses and minimum tumour dose thresholds. Biomarkers could also be used to determine normal tissue MRT dose limits and permit greater injected doses of MRT in patients. An alternative approach is to understand the repair capacity limits of tumours using radiobiology-based biomarkers within and outside patient cohorts currently treated with MRT. It is hoped that by knowing more about tumours and how they respond to MRT, biomarkers can provide needed dimensionality to image-based biodosimetry to improve MRT with optimized protocols and personalised therapies.

A Physiologically Based Pharmacokinetic Model for In Vivo Alpha Particle Generators Targeting Neuroendocrine Tumors in Mice

In vivo alpha particle generators have great potential for the treatment of neuroendocrine tumors in alpha-emitter-based peptide receptor radionuclide therapy (α-PRRT). Quantitative pharmacokinetic analyses of the in vivo alpha particle generator and its radioactive decay products are required to address concerns about the efficacy and safety of α-PRRT. A murine whole-body physiologically based pharmacokinetic (PBPK) model was developed for 212Pb-labeled somatostatin analogs (212Pb-SSTA). The model describes pharmacokinetics of 212Pb-SSTA and its decay products, including specific and non-specific glomerular and tubular uptake. Absorbed dose coefficients (ADC) were calculated for bound and unbound radiolabeled SSTA and its decay products. Kidneys received the highest ADC (134 Gy/MBq) among non-target tissues. The alpha-emitting 212Po contributes more than 50% to absorbed doses in most tissues. Using this model, it is demonstrated that α-PRRT based on 212Pb-SSTA results in lower absorbed doses in non-target tissue than α-PRRT based on 212Bi-SSTA for a given kidneys absorbed dose. In both approaches, the energies released in the glomeruli and proximal tubules account for 54% and 46%, respectively, of the total energy absorbed in kidneys. The 212Pb-SSTA-PBPK model accelerates the translation from bench to bedside by enabling better experimental design and by improving the understanding of the underlying mechanisms.

Nephrotoxicity after radionuclide therapies

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Nuclear medicine theranostics have demonstrated success with a favourable safety and efficacy profile in several malignancies.

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Kidneys being the primary excretory organ for most therapeutic radiopharmaceuticals are at risk of increased radiation exposure.

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Recognition of the mechanisms of radiation induced nephropathy and associated risk factors can help in the development of appropriate interventions to prevent and limit renal toxicity.

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Developments in reducing chronic radiation nephropathy following radionuclide therapies will help in avoiding the related morbidities, preserving the overall quality of life.

Radioligand therapies have opened new treatment avenues for cancer patients. They offer precise tumor targeting with a favorable efficacy-to-toxicity profile. Specifically, the kidneys, once regarded as the critical organ for radiation toxicity, also show excellent tolerance to radiation doses as high as 50–60 Gy in selected cases. However, the number of nephrons that form the structural and functional units of the kidney is determined before birth and is fixed. Thus, loss of nephrons secondary to any injury may lead to an irreversible decline in renal function over time. Our primary understanding of radiation-induced nephropathy is derived from the effects of external beam radiation on the renal tissue. With the growing adoption of radionuclide therapies, considerable evidence has been gained with regard to the occurrence of renal toxicity and its associated risk factors. In this review, we discuss the radionuclide therapies associated with the risk of nephrotoxicity, the present understanding of the factors and mechanisms that contribute to renal injury, and the current and potential methods for preventing, identifying, and managing nephrotoxicity, specifically acute onset nephropathies.

Highlight selection of radiochemistry and radiopharmacy developments by editorial board

BACKGROUND

The Editorial Board of EJNMMI Radiopharmacy and Chemistry releases a biyearly highlight commentary to update the readership on trends in the field of radiopharmaceutical development.

RESULTS

This commentary of highlights has resulted in 21 different topics selected by each member of the Editorial Board addressing a variety of aspects ranging from novel radiochemistry to first in man application of novel radiopharmaceuticals. Also the first contribution in relation to MRI-agents is included.

CONCLUSIONS

Trends in (radio)chemistry and radiopharmacy are highlighted demonstrating the progress in the research field being the scope of EJNMMI Radiopharmacy and Chemistry.

A physiologically based pharmacokinetic (PBPK) model to describe organ distribution of 68Ga-DOTATATE in patients without neuroendocrine tumors

Background

Physiologically based pharmacokinetic (PBPK) models combine drug-specific information with prior knowledge on the physiology and biology at the organism level. Whole-body PBPK models contain an explicit representation of the organs and tissue and are a tool to predict pharmacokinetic behavior of drugs. The aim of this study was to develop a PBPK model to describe organ distribution of ⁶⁸Ga-DOTATATE in a population of patients without detectable neuroendocrine tumors (NETs).

Methods

Clinical ⁶⁸Ga-DOTATATE PET/CT data from 41 patients without any detectable somatostatin receptor (SSTR) overexpressing tumors were included. Scans were performed at 45 min (range 30–60 min) after intravenous bolus injection of ⁶⁸Ga-DOTATATE. Organ (spleen, liver, thyroid) and blood activity levels were derived from PET scans, and corresponding DOTATATE concentrations were calculated. A whole-body PBPK model was developed, including an internalization reaction, receptor recycling, enzymatic reaction for intracellular degradation and renal clearance. SSTR2 expression was added for several organs. Input parameters were fixed or estimated using a built-in Monte Carlo algorithm for parameter identification.

Results

⁶⁸Ga-DOTATATE was administered with a median peptide amount of 12.3 µg (range 8.05–16.9 µg) labeled with 92.7 MBq (range 43.4–129.9 MBq). SSTR2 amounts for spleen, liver and thyroid were estimated at 4.40, 7.80 and 0.0108 nmol, respectively. Variability in observed organ concentrations was best described by variability in SSTR2 expression and differences in administered peptide amounts.

Conclusions

To conclude, biodistribution of ⁶⁸Ga-DOTATATE was described with a whole-body PBPK model, where tissue distribution was mainly determined by variability in SSTR2 organ expression and differences in administered peptide amounts.

A Whole-Body Physiologically Based Pharmacokinetic Model for Alpha Particle Emitting Bismuth in Rats

Introduction/Aim: α particle emitting bismuth (²¹²Bi) as decay product of ²¹²Pb-labeled pharmaceuticals has been effective in targeted α particle therapy (TAT). Estimating the contribution of ²¹²Bi released from its chelator to the absorbed doses in nontarget tissues is challenging in TAT. Physiologically based pharmacokinetic (PBPK) modeling can help overcome this limitation. Therefore, a whole-body ²¹²Bi-PBPK model was developed to describe the pharmacokinetics (PKs) of ²¹²Bi in rats. Materials and Methods: The rat ²¹²Bi-PBPK model was implemented using the modeling software SAAM II with data and parameter values from the literature. Besides other mechanisms, ²¹²Bi interactions with red blood cells, high molecular weight plasma protein, and intracellular biological thiols are described. Important PK parameters were fitted to time-activity data. Absorbed dose coefficients (ADCs) were calculated for injecting 0.774 fmol of ²¹²Bi. Results: ²¹²Bi uptake rates of liver, bone, small intestine, bone marrow, skin, and muscle were (0.86 ± 0.13), (3.85 ± 0.63), (0.27 ± 0.05), (1.44 ± 0.29), (0.04 ± 0.01), and (0.007 ± 0.007) per min with corresponding ADCs of 0.09, 0.03, 0.03, 0.07, 0.01, and 0.003 mGy/kBq, respectively. An ADC of 0.70 mGy/kBq was determined for kidneys. Conclusion: Kidneys are the dose-limiting organs in ²¹²Bi-based TAT. The ²¹²Bi-PBPK model is an effective tool to investigate the ²¹²Bi biodistribution in murine models. Integrating the ²¹²Bi-PBPK model into other murine and human PBPK models of α particle generators can help study the efficacy and safety of TAT.