Pre-therapy PET-based voxel-wise dosimetry prediction by characterizing intra-organ heterogeneity in PSMA-directed radiopharmaceutical theranostics.

BACKGROUND AND OBJECTIVE: Treatment planning through the diagnostic dimension of theranostics provides insights into predicting the absorbed dose of RPT, with the potential to individualize radiation doses for enhancing treatment efficacy. However, existing studies focusing on dose prediction from diagnostic data often rely on organ-level estimations, overlooking intra-organ variations. This study aims to characterize the intra-organ theranostic heterogeneity and utilize artificial intelligence techniques to localize them, i.e. to predict voxel-wise absorbed dose map based on pre-therapy PET. METHODS: 23 patients with metastatic castration-resistant prostate cancer treated with [177Lu]Lu-PSMA I&T RPT were retrospectively included. 48 treatment cycles with pre-treatment PET imaging and at least 3 post-therapeutic SPECT/CT imaging were selected. The distribution of PET tracer and RPT dose was compared for kidney, liver and spleen, characterizing intra-organ heterogeneity differences. Pharmacokinetic simulations were performed to enhance the understanding of the correlation. Two strategies were explored for pre-therapy voxel-wise dosimetry prediction: (1) organ-dose guided direct projection; (2) deep learning (DL)-based distribution prediction. Physical metrics, dose volume histogram (DVH) analysis, and identity plots were applied to investigate the predicted absorbed dose map. RESULTS: Inconsistent intra-organ patterns emerged between PET imaging and dose map, with moderate correlations existing in the kidney (r = 0.77), liver (r = 0.5), and spleen (r = 0.58) (P < 0.025). Simulation results indicated the intra-organ pharmacokinetic heterogeneity might explain this inconsistency. The DL-based method achieved a lower average voxel-wise normalized root mean squared error of 0.79 ± 0.27%, regarding to ground-truth dose map, outperforming the organ-dose guided projection (1.11 ± 0.57%) (P < 0.05). DVH analysis demonstrated good prediction accuracy (R2 = 0.92 for kidney). The DL model improved the mean slope of fitting lines in identity plots (199% for liver), when compared to the theoretical optimal results of the organ-dose approach. CONCLUSION: Our results demonstrated the intra-organ heterogeneity of pharmacokinetics may complicate pre-therapy dosimetry prediction. DL has the potential to bridge this gap for pre-therapy prediction of voxel-wise heterogeneous dose map.

Dosimetric Analysis of a Phase I Study of PSMA-Targeting Radiopharmaceutical Therapy With [177Lu]Ludotadipep in Patients With Metastatic Castration-Resistant Prostate Cancer.

OBJECTIVE: 177Lutetium [Lu] Ludotadipep is a novel prostate-specific membrane antigen targeting therapeutic agent with an albumin motif added to increase uptake in the tumors. We assessed the biodistribution and dosimetry of [177Lu]Ludotadipep in patients with metastatic castration-resistant prostate cancer (mCRPC). MATERIALS AND METHODS: Data from 25 patients (median age, 73 years; range, 60-90) with mCRPC from a phase I study with activity escalation design of single administration of [177Lu]Ludotadipep (1.85, 2.78, 3.70, 4.63, and 5.55 GBq) were assessed. Activity in the salivary glands, lungs, liver, kidneys, and spleen was estimated from whole-body scan and abdominal SPECT/CT images acquired at 2, 24, 48, 72, and 168 h after administration of [177Lu]Ludotadipep. Red marrow activity was calculated from blood samples obtained at 3, 10, 30, 60, and 180 min, and at 24, 48, and 72 h after administration. Organ- and tumor-based absorbed dose calculations were performed using IDAC-Dose 2.1. RESULTS: Absorbed dose coefficient (mean ± standard deviation) of normal organs was 1.17 ± 0.81 Gy/GBq for salivary glands, 0.05 ± 0.02 Gy/GBq for lungs, 0.14 ± 0.06 Gy/GBq for liver, 0.77 ± 0.28 Gy/GBq for kidneys, 0.12 ± 0.06 Gy/GBq for spleen, and 0.07 ± 0.02 Gy/GBq for red marrow. The absorbed dose coefficient of the tumors was 10.43 ± 7.77 Gy/GBq. CONCLUSION: [177Lu]Ludotadipep is expected to be safe at the dose of 3.7 GBq times 6 cycles planned for a phase II clinical trial with kidneys and bone marrow being the critical organs, and shows a high tumor absorbed dose.

Chemistry of Antimony in Radiopharmaceutical Development: Unlocking the Theranostic Potential of Sb Isotopes.

Antimony-119 (119Sb) holds promise for radiopharmaceutical therapy (RPT), emitting short-range Auger and conversion electrons that can deliver cytotoxic radiation on a cellular level. While it has high promise theoretically, experimental validation is necessary for 119Sb in vivo applications. Current 119Sb production and separation methods face robustness and compatibility challenges in radiopharmaceutical synthesis. Limited progress in chelator development hampers targeted experiments with 119Sb. This review compiles literature on the toxicological, biodistribution and redox properties of Sb, along with existing Sb complexes, evaluating their suitability for radiopharmaceuticals. Sb(III) is suggested as the preferred oxidation state for radiopharmaceutical elaboration due to its stability in vivo and lack of skeletal uptake. While Sb complexes with both hard and soft donor atoms can be achieved, Sb thiol complexes offer enhanced stability and compatibility with the desired Sb(III) oxidation state. For 119Sb to find application in RPT, scientists need to make discoveries and advancements in the areas of isotope production, and radiometal chelation. This review aims to guide future research towards harnessing the therapeutic potential of 119Sb in RPT.

Physiologically based radiopharmacokinetic (PBRPK) modeling to simulate and analyze radiopharmaceutical therapies: studies of non-linearities, multi-bolus injections, and albumin binding.

BACKGROUND: We aimed to develop a publicly shared computational physiologically based pharmacokinetic (PBPK) model to reliably simulate and analyze radiopharmaceutical therapies (RPTs), including probing of hot-cold ligand competitions as well as alternative injection scenarios and drug designs, towards optimal therapies. RESULTS: To handle the complexity of PBPK models (over 150 differential equations), a scalable modeling notation called the "reaction graph" is introduced, enabling easy inclusion of various interactions. We refer to this as physiologically based radiopharmacokinetic (PBRPK) modeling, fine-tuned specifically for radiopharmaceuticals. As three important applications, we used our PBRPK model to (1) study the effect of competition between hot and cold species on delivered doses to tumors and organs at risk. In addition, (2) we evaluated an alternative paradigm of utilizing multi-bolus injections in RPTs instead of prevalent single injections. Finally, (3) we used PBRPK modeling to study the impact of varying albumin-binding affinities by ligands, and the implications for RPTs. We found that competition between labeled and unlabeled ligands can lead to non-linear relations between injected activity and the delivered dose to a particular organ, in the sense that doubling the injected activity does not necessarily result in a doubled dose delivered to a particular organ (a false intuition from external beam radiotherapy). In addition, we observed that fractionating injections can lead to a higher payload of dose delivery to organs, though not a differential dose delivery to the tumor. By contrast, we found out that increased albumin-binding affinities of the injected ligands can lead to such a differential effect in delivering more doses to tumors, and this can be attributed to several factors that PBRPK modeling allows us to probe. CONCLUSIONS: Advanced computational PBRPK modeling enables simulation and analysis of a variety of intervention and drug design scenarios, towards more optimal delivery of RPTs.

The MIRD Schema for Radiopharmaceutical Dosimetry: A Review.

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

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.

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

BACKGROUND: With recent interest in patient-specific dosimetry for radiopharmaceutical therapy (RPT) and selective internal radiation therapy (SIRT), an increasing number of voxel-based algorithms are being evaluated. Monte Carlo (MC) radiation transport, generally considered to be the most accurate among different methods for voxel-level absorbed dose estimation, can be computationally inefficient for routine clinical use. PURPOSE: This work demonstrates a recently implemented grid-based linear Boltzmann transport equation (LBTE) solver for fast and accurate voxel-based dosimetry in RPT and SIRT and benchmarks it against MC. METHODS: A deterministic LBTE solver (Acuros MRT) was implemented within a commercial RPT dosimetry package (Velocity 4.1). The LBTE is directly discretized using an adaptive mesh refined grid and then the coupled photon-electron radiation transport is iteratively solved inside specified volumes to estimate radiation doses from both photons and charged particles in heterogeneous media. To evaluate the performance of the LBTE solver for RPT and SIRT applications, 177Lu SPECT/CT, 90Y PET/CT, and 131I SPECT/CT images of phantoms and patients were used. Multiple lesions (2-1052 mL) and normal organs were delineated for each study. Voxel dosimetry was performed with the LBTE solver, dose voxel kernel (DVK) convolution with density correction, and a validated in-house MC code using the same time-integrated activity and density maps as input to the different dose engines. The resulting dose maps, difference maps, and dose-volume-histogram (DVH) metrics were compared, to assess the voxel-level agreement. Evaluation of mean absorbed dose included comparison with structure-level estimates from OLINDA. RESULTS: In the phantom inserts/compartments, the LBTE solver versus MC and DVK convolution demonstrated good agreement with mean absorbed dose and DVH metrics agreeing to within 5% except for the D90 and D70 metrics of a very low activity concentration insert of 90Y where the agreement was within 15%. In the patient studies (five patients imaged after 177Lu DOTATATE RPT, five after 90Y SIRT, and two after 131I radioimmunotherapy), in general, there was better agreement between the LBTE solver and MC than between LBTE solver and DVK convolution for mean absorbed dose and voxel-level evaluations. Across all patients for all three radionuclides, for soft tissue structures (kidney, liver, lesions), the mean absorbed dose estimates from the LBTE solver were in good agreement with those from MC (median difference < 1%, maximum 9%) and those from DVK (median difference < 5%, maximum 9%). The LBTE and OLINDA estimates for mean absorbed dose in kidneys and liver agreed to within 10%, but differences for lesions were larger with a maximum 14% for 177Lu, 23% for 90Y, and 26% for 131I. For bone regions, the agreement in mean absorbed doses between LBTE and both MC and DVK were similar (median < 11%, max 11%) while for lung the agreement between LBTE and MC (median < 1%, max 8%) was substantially better than between LBTE and DVK (median < 16%, max 33%). Voxel level estimates for soft tissue structures also showed good agreement between the LBTE solver and both MC and DVK with a median difference < 5% (maximum < 13%) for the DVH metrics with all three radionuclides. The largest difference in DVH metrics was for the D90 and D70 metric in lung and bone where the uptake was low. Here, the difference between LBTE and MC had a median value < 14% (maximum 23%) for bone and < 4% (maximum 37%) for lung, while the corresponding differences between LBTE and DVK were < 23% (maximum 31%) and < 67% (maximum 313%), respectively. For a typical patient with a matrix size of 166 × 166 × 129 (voxel size 3 × 3 × 3 mm3), voxel dosimetry using the LBTE solver was as fast as ∼2 min on a desktop computer. CONCLUSION: Having established good agreement between the LBTE solver and MC for RPT and SIRT applications, the LBTE solver is a viable option for voxel dosimetry that can be faster than MC. Further analysis is being performed to encompass the broad range of radionuclides and conditions encountered clinically.

Low cost, high temporal resolution optical fiber-based γ-photon sensor for real-time pre-clinical evaluation of cancer-targeting radiopharmaceuticals.

Cancer radiopharmaceutical therapies (RPTs) have demonstrated great promise in the treatment of neuroendocrine and prostate cancer, giving hope to late-stage metastatic cancer patients with currently very few treatment options. These therapies have sparked a large amount of interest in pre-clinical research due to their ability to target metastatic disease, with many research efforts focused towards developing and evaluating targeted RPTs for different cancer types in in vivo models. Here we describe a method for monitoring real-time in vivo binding kinetics for the pre-clinical evaluation of cancer RPTs. Recognizing the significant heterogeneity in biodistribution of RPTs among even genetically identical animal models, this approach offers long-term monitoring of the same in vivo organism without euthanasia in contrast to ex vivo tissue dosimetry, while providing high temporal resolution with a low-cost, easily assembled platform, that is not present in small-animal SPECT/CTs. The method utilizes the developed optical fiber-based γ-photon biosensor, characterized to have a wide linear dynamic range with Lutetium-177 (177Lu) activity (0.5-500 µCi/mL), a common radioisotope used in cancer RPT. The probe's ability to track in vivo uptake relative to SPECT/CT and ex vivo dosimetry techniques was verified by administering 177Lu-PSMA-617 to mouse models bearing human prostate cancer tumors (PC3-PIP, PC3-flu). With this method for monitoring RPT uptake, it is possible to evaluate changes in tissue uptake at temporal resolutions <1 min to determine RPT biodistribution in pre-clinical models and better understand dose relationships with tumor ablation, toxicity, and recurrence when attempting to move therapies towards clinical trial validation.

Exploration of commercial cyclen-based chelators for mercury-197 m/g incorporation into theranostic radiopharmaceuticals.

A comprehensive investigation of the Hg2+ coordination chemistry and 197m/gHg radiolabeling capabilities of cyclen-based commercial chelators, namely, DOTA and DOTAM (aka TCMC), along with their bifunctional counterparts, p-SCN-Bn-DOTA and p-SCN-Bn-TCMC, was conducted to assess the suitability of these frameworks as bifunctional chelators for the 197m/gHg2+ theranostic pair. Radiolabeling studies revealed that TCMC and DOTA exhibited low radiochemical yields (0%-6%), even when subjected to harsh conditions (80°C) and high ligand concentrations (10-4 M). In contrast, p-SCN-Bn-TCMC and p-SCN-Bn-DOTA demonstrated significantly higher 197m/gHg radiochemical yields (100% ± 0.0% and 70.9% ± 1.1%, respectively) under the same conditions. The [197 m/gHg]Hg-p-SCN-Bn-TCMC complex was kinetically inert when challenged against human serum and glutathione. To understand the differences in labeling between the commercial chelators and their bifunctional counterparts, non-radioactive natHg2+ complexes were assessed using NMR spectroscopy and DFT calculations. The NMR spectra of Hg-TCMC and Hg-p-SCN-Bn-TCMC suggested binding of the Hg2+ ion through the cyclen backbone framework. DFT studies indicated that binding of the Hg2+ ion within the backbone forms a thermodynamically stable product. However, competition can form between isothiocyanate binding and binding through the macrocycle, which was experimentally observed. The isothiocyanate bound coordination product was dominant at the radiochemical scale as, in comparison, the macrocycle bound product was seen at the NMR scale, agreeing with the DFT result. Furthermore, a bioconjugate of TCMC (TCMC-PSMA) targeting prostate-specific membrane antigen was synthesized and radiolabeled, resulting in an apparent molar activity of 0.089 MBq/nmol. However, the complex demonstrated significant degradation over 24 h when exposed to human serum and glutathione. Subsequently, cell binding assays were conducted, revealing a Ki value ranging from 19.0 to 19.6 nM. This research provides crucial insight into the effectiveness of current commercial chelators in the context of 197m/gHg2+ radiolabeling. It underscores the necessity for the development of specific and customized chelators to these unique "soft" radiometals to advance 197m/gHg2+ radiopharmaceuticals.

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

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

Localized radiotherapy of solid tumors using radiopharmaceutical loaded implantable system: insights from a mathematical model.

Introduction: Computational models yield valuable insights into biological interactions not fully elucidated by experimental approaches. This study investigates an innovative spatiotemporal model for simulating the controlled release and dispersion of radiopharmaceutical therapy (RPT) using 177Lu-PSMA, a prostate-specific membrane antigen (PSMA) targeted radiopharmaceutical, within solid tumors via a dual-release implantable delivery system. Local delivery of anticancer agents presents a strategic approach to mitigate adverse effects while optimizing therapeutic outcomes. Methods: This study evaluates various factors impacting RPT efficacy, including hypoxia region extension, binding affinity, and initial drug dosage, employing a novel 3-dimensional computational model. Analysis gauges the influence of these factors on radiopharmaceutical agent concentration within the tumor microenvironment. Furthermore, spatial and temporal radiopharmaceutical distribution within both the tumor and surrounding tissue is explored. Results: Analysis indicates a significantly higher total concentration area under the curve within the tumor region compared to surrounding normal tissue. Moreover, drug distribution exhibits notably superior efficacy compared to the radiation source. Additionally, low microvascular density in extended hypoxia regions enhances drug availability, facilitating improved binding to PSMA receptors and enhancing therapeutic effectiveness. Reductions in the dissociation constant (KD) lead to heightened binding affinity and increased internalized drug concentration. Evaluation of initial radioactivities (7.1×107, 7.1×108, and 7.1×109 [Bq]) indicates that an activity of 7.1×108 [Bq] offers a favorable balance between tumor cell elimination and minimal impact on normal tissues. Discussion: These findings underscore the potential of localized radiopharmaceutical delivery strategies and emphasize the crucial role of released drugs relative to the radiation source (implant) in effective tumor treatment. Decreasing the proximity of the drug to the microvascular network and enhancing its distribution within the tumor promote a more effective therapeutic outcome. The study furnishes valuable insights for future experimental investigations and clinical trials, aiming to refine medication protocols and minimize reliance on in vivo testing.

SPECT/CT Image-Derived Absorbed Dose to Red Marrow Correlates with Hematologic Toxicity in Patients Treated with [177Lu]Lu-DOTATATE.

Hematologic toxicity, although often transient, is the most common limiting adverse effect during somatostatin peptide receptor radionuclide therapy. This study investigated the association between Monte Carlo-derived absorbed dose to the red marrow (RM) and hematologic toxicity in patients being treated for their neuroendocrine tumors. Methods: Twenty patients each receiving 4 treatment cycles of [177Lu]Lu-DOTATATE were included. Multiple-time-point 177Lu SPECT/CT imaging-based RM dosimetry was performed using an artificial intelligence-driven workflow to segment vertebral spongiosa within the field of view (FOV). This workflow was coupled with an in-house macroscale/microscale Monte Carlo code that incorporates a spongiosa microstructure model. Absorbed dose estimates to RM in lumbar and thoracic vertebrae within the FOV, considered as representations of the whole-body RM absorbed dose, were correlated with hematologic toxicity markers at about 8 wk after each cycle and at 3- and 6-mo follow-up after completion of all cycles. Results: The median of absorbed dose to RM in lumbar and thoracic vertebrae within the FOV (D median,vertebrae) ranged from 0.019 to 0.11 Gy/GBq. The median of cumulative absorbed dose across all 4 cycles was 1.3 Gy (range, 0.6-2.5 Gy). Hematologic toxicity was generally mild, with no grade 2 or higher toxicity for platelets, neutrophils, or hemoglobin. However, there was a decline in blood counts over time, with a fractional value relative to baseline at 6 mo of 74%, 97%, 57%, and 97%, for platelets, neutrophils, lymphocytes, and hemoglobin, respectively. Statistically significant correlations were found between a subset of hematologic toxicity markers and RM absorbed doses, both during treatment and at 3- and 6-mo follow-up. This included a correlation between the platelet count relative to baseline at 6-mo follow up: D median,vertebrae (r = -0.64, P = 0.015), D median,lumbar (r = -0.72, P = 0.0038), D median,thoracic (r = -0.58, P = 0.029), and D average,vertebrae (r = -0.66, P = 0.010), where D median,lumbar and D median,thoracic are median absorbed dose to the RM in the lumbar and thoracic vertebrae, respectively, within the FOV and D average,vertebrae is the mass-weighted average absorbed dose of all vertebrae. Conclusion: This study found a significant correlation between image-derived absorbed dose to the RM and hematologic toxicity, including a relative reduction of platelets at 6-mo follow up. These findings indicate that absorbed dose to the RM can potentially be used to understand and manage hematologic toxicity in peptide receptor radionuclide therapy.

Active and passive dosimetry for beta-emitting radiopharmaceutical therapy agents in a custom SPECT/CT compatible phantom.

Objective. This work introduces a novel approach to performing active and passive dosimetry for beta-emitting radionuclides in solution using common dosimeters. The measurements are compared to absorbed dose to water (Dw) estimates from Monte Carlo (MC) simulations. We present a method for obtaining absorbed dose to water, measured with dosimeters, from beta-emitting radiopharmaceutical agents using a custom SPECT/CT compatible phantom for validation of Monte Carlo based absorbed dose to water estimates.Approach. A cylindrical, acrylic SPECT/CT compatible phantom capable of housing an IBA EFD diode, Exradin A20-375 parallel plate ion chamber, unlaminated EBT3 film, and thin TLD100 microcubes was constructed for the purpose of measuring absorbed dose to water from solutions of common beta-emitting radiopharmaceutical therapy agents. The phantom is equipped with removable detector inserts that allow for multiple configurations and is designed to be used for validation of image-based absorbed dose estimates with detector measurements. Two experiments with131I and one experiment with177Lu were conducted over extended measurement intervals with starting activities of approximately 150-350 MBq. Measurement data was compared to Monte Carlo simulations using the egs_chamber user code in EGSnrc 2019.Main results. Agreement withink= 1 uncertainty between measured and MC predictedDwwas observed for all dosimeters, except the A20-375 ion chamber during the second131I experiment. Despite the agreement, the measured values were generally lower than predicted values by 5%-15%. The uncertainties atk = 1 remain large (5%-30% depending on the dosimeter) relative to other forms of radiation therapy.Significance. Despite high uncertainties, the overall agreement between measured and simulated absorbed doses is promising for the use of dosimeter-based RPT measurements in the validation of MC predictedDw.

ISIT-QA: In Silico Imaging Trial to Evaluate a Low-Count Quantitative SPECT Method Across Multiple Scanner-Collimator Configurations for 223Ra-Based Radiopharmaceutical Therapies.

Personalized dose-based treatment planning requires accurate and reproducible noninvasive measurements to ensure safety and effectiveness. Dose estimation using SPECT is possible but challenging for alpha (α)-particle-emitting radiopharmaceutical therapy (α-RPT) because of complex γ-emission spectra, extremely low counts, and various image-degrading artifacts across a plethora of scanner-collimator configurations. Through the incorporation of physics-based considerations and skipping of the potentially lossy voxel-based reconstruction step, a recently developed projection-domain low-count quantitative SPECT (LC-QSPECT) method has the potential to provide reproducible, accurate, and precise activity concentration and dose measures across multiple scanners, as is typically the case in multicenter settings. To assess this potential, we conducted an in silico imaging trial to evaluate the LC-QSPECT method for a 223Ra-based α-RPT, with the trial recapitulating patient and imaging system variabilities. Methods: A virtual imaging trial titled In Silico Imaging Trial for Quantitation Accuracy (ISIT-QA) was designed with the objectives of evaluating the performance of the LC-QSPECT method across multiple scanner-collimator configurations and comparing performance with a conventional reconstruction-based quantification method. In this trial, we simulated 280 realistic virtual patients with bone-metastatic castration-resistant prostate cancer treated with 223Ra-based α-RPT. The trial was conducted with 9 simulated SPECT scanner-collimator configurations. The primary objective of this trial was to evaluate the reproducibility of dose estimates across multiple scanner-collimator configurations using LC-QSPECT by calculating the intraclass correlation coefficient. Additionally, we compared the reproducibility and evaluated the accuracy of both considered quantification methods across multiple scanner-collimator configurations. Finally, the repeatability of the methods was evaluated in a test-retest study. Results: In this trial, data from 268 223RaCl2 treated virtual prostate cancer patients, with a total of 2,903 lesions, were used to evaluate LC-QSPECT. LC-QSPECT provided dose estimates with good reproducibility across the 9 scanner-collimator configurations (intraclass correlation coefficient > 0.75) and high accuracy (ensemble average values of recovery coefficients ranged from 1.00 to 1.02). Compared with conventional reconstruction-based quantification, LC-QSPECT yielded significantly improved reproducibility across scanner-collimator configurations, accuracy, and test-retest repeatability ([Formula: see text] Conclusion: LC-QSPECT provides reproducible, accurate, and repeatable dose estimations in 223Ra-based α-RPT as evaluated in ISIT-QA. These findings provide a strong impetus for multicenter clinical evaluations of LC-QSPECT in dose quantification for α-RPTs.

Alpha-emitter Peptide Receptor Radionuclide Therapy in Neuroendocrine Tumors.

Peptide receptor radionuclide therapy (PRRT) has become mainstream therapy of metastatic neuroendocrine tumors not controlled by somatostatin analog therapy. Currently, beta particle-emitting radiopharmaceuticals are the mainstay of PRRT. Alpha particle-emitting radiopharmaceuticals have a theoretic advantage over beta emitters in terms of improved therapeutic efficacy due to higher cancer cell death and lower nontarget tissue radiation-induced adverse events due to shorter path length of alpha particles. We discuss the available evidence for and the role of alpha particle PRRT.

Evaluation of a bimodal, matched pair theranostic agent targeting prostate-specific membrane antigen.

BACKGROUND: Prostate cancer affects 1 in 6 men, and it is the second­leading cause of cancer-related death in American men. Surgery is one of the main treatment modalities for prostate cancer, but it often results in incomplete resection margins or complete resection that leads to nerve damage and undesirable side effects. In the present work, we have developed a new bimodal tracer, NODAGA-sCy7.5 PSMAi (prostate-specific membrane antigen inhibitor), labeled with the true matched theranostic pair 64Cu/67Cu and a near-infrared fluorescent dye. This agent could potentially be used for concomitant PET imaging, optical surgical navigation, and targeted radiopharmaceutical therapy. METHODS: A prostate-specific membrane antigen (PSMA)-targeting urea derivative was conjugated to NODAGA for copper radiolabeling and to the near-infrared fluorophore sulfo-Cy7.5 (sCy7.5). Binding studies were performed in PSMA-positive PC-3 PIP cells, as well as uptake and internalization assays in PC-3 PIP cells and PSMA-negative PC-3 wild type cells. Biodistribution studies of the 64Cu-labeled compound were performed in PC-3 PIP- and PC-3 tumor-bearing mice, and 67Cu biodistributions of the agent were obtained in PC-3 PIP tumor-carrying mice. PET imaging and fluorescence imaging were also performed, using the same molar doses, in the two mouse models. RESULTS: The PSMA conjugate bound with high affinity to PSMA-positive prostate cancer cells, as opposed to cells that were PSMA-negative. Uptake and internalization were rapid and PSMA-mediated in PC-3 PIP cells, while only minimal non-specific uptake was observed in PC-3 cells. Biodistribution studies showed specific uptake in PC-3 PIP tumors, while accumulation in PC-3 tumor-bearing mice was low. Furthermore, tumor uptake of the 67Cu-labeled agent in the PC-3 PIP model was statistically equivalent to that of 64Cu. PET and fluorescence imaging at 0.5 nmol per mouse also demonstrated that PC-3 PIP tumors could be clearly detected, while PC-3 tumors showed no tumor accumulation. CONCLUSIONS: NODAGA-sCy7.5-PSMAi was specific and selective in detecting PSMA-positive, as opposed to PSMA-negative, tumors in mouse models of prostate cancer. This bioconjugate could potentially be used for PET staging with 64Cu, targeted radiopharmaceutical therapy with 67Cu, and/or image-guided surgery with sCy7.5.

Technical note: Errors introduced when using Dose Voxel Kernels for estimating absorbed dose from radiopharmaceutical therapies involving alpha emitters.

BACKGROUND: In radiopharmaceutical therapies (RPT) involving beta emitters, absorbed dose (Dabs) calculations often employ the use of dose voxel kernels (DVK). Such methods are faster and easier to implement than Monte Carlo (MC) simulations. Using DVK methods implies a non-stochastic distribution of particles. This is a valid assumption for betas where thousands to tens of thousands of particles traversing the cell nucleus are required to achieve cell kill. However, alpha particles have linear energy transfers (LET) that are ∼500 times higher than LETs of betas. This results in a significant probability of killing a cell from even a single traversal through its nucleus. Consequently, the activity used for therapy involving alphas is very low, and the use of DVKs for estimating Dabs will generate results that may be erroneous. PURPOSE: This work aims at illustrating how use of DVKs affect the resulting Dabs in small tumors when irradiated with clinically relevant amounts of beta- and alpha-emitters. The results are compared with those from using a Monte Carlo method where the energy deposition from individual tracks is simulated. METHODS: To illustrate the issues associated with DVK for alpha radiopharmaceutical therapies at the microscale, a tumor cluster model was used to compare beta (177Lu) and alphas (211At, 225Ac, and 227Th) irradiations. We used 103 beta particles and 20 alpha particles per cell, which is within the range of the required number of particle traversals through its nucleus to sterilize a cell. Results from using both methods were presented with Dabs histograms, dose volume histograms, and Dabs error maps. RESULTS: For beta-emitter (177Lu) irradiating the modeled tumor cluster, resulting Dabs was similar for both DVK and MC methods. For all alpha emitters, the use of DVK led to an overestimation of Dabs when compared to results generated using a MC approach. CONCLUSIONS: Our results demonstrate that the use of DVK methods for alpha emitters can lead to an overestimation in the calculated Dabs. The use of DVKs for therapies involving alpha emitters may therefore not be appropriate when only referring to the mean Dabs metric.

Spatiotemporal modeling of radiopharmaceutical transport in solid tumors: Application to 177Lu-PSMA therapy of prostate cancer.

BACKGROUND AND OBJECTIVE: 177Lu-labeled prostate-specific membrane antigen (PSMA) radiopharmaceutical therapy (RPT) represents a pivotal advancement in addressing prostate cancer. However, existing therapies, while promising, remain incompletely understood and optimized. Computational models offer potential insights into RPTs, aiding in clinical drug delivery enhancement. In this study, we investigate the impact of various physiological parameters on the delivery of 177Lu-PSMA-617 RPT using the convection-diffusion-reaction (CDR) model. METHODS: Our investigation encompasses tumor geometry and surrounding tissue, characterized by well-defined boundaries and initial conditions. Utilizing the finite element method, we solve governing equations across a range of parameters: dissociation constant KD (1, 0.1, 0.01 [nM]), internalization rate (0.01-0.0001 [min-1]), diverse tumor shapes, and variable necrotic zone sizes. This model can provide an accurate analysis of radiopharmaceutical delivery from the injection site to the tumor cell, including drug transport in the vascular, interstitial, and intracellular spaces, and considering important parameters (e.g., drug extravasation from microvessels or to lymphatic vessels, the extracellular matrix, receptors, and intracellular space). RESULTS: Our findings reveal significant enhancements in tumor-absorbed doses as KD decreases. This outcome can be attributed to the higher affinity of radiopharmaceuticals for PSMA receptors as KD diminishes, facilitating a more efficient binding and retention of the therapeutic agent within the tumor microenvironment. Additionally, tumor-absorbed doses for KD ∼ 1 [nM] show an upward trend with higher internalization rates. This observation can be rationalized by considering that a greater internalization rate would result in a higher proportion of radiopharmaceuticals being taken up by tumor cells after binding to receptors on the cell surface. Notably, tumor shape and necrotic zone size exhibit limited influence on tumor absorbed dose. CONCLUSIONS: The present study employs the CDR model to explore the role of physiological parameters in shaping 177Lu-PSMA-617 RPT delivery. These findings provide insights for improving prostate cancer therapy by understanding radiopharmaceutical transport dynamics. This computational approach contributes to advancing our understanding of radiopharmaceutical delivery mechanisms and has implications for enhancing treatment efficacy.

RECIP 1.0 Predicts Progression-Free Survival After [177Lu]Lu-PSMA Radiopharmaceutical Therapy in Patients with Metastatic Castration-Resistant Prostate Cancer.

Response Evaluation Criteria in Prostate-Specific Membrane Antigen Imaging (RECIP) 1.0 is an evidence-based framework to evaluate therapeutic efficacy in metastatic prostate cancer using prostate-specific membrane antigen (PSMA) PET/CT. This study aimed to evaluate the associations of interim PSMA PET/CT by RECIP 1.0 with short-term outcome after radiopharmaceutical treatment. Methods: This multicenter retrospective study included patients with metastatic castration-resistant prostate cancer who underwent [177Lu]Lu-PSMA radiopharmaceutical therapy at 3 academic centers and received PSMA PET/CT at baseline and at 12 wk. Pairs of PSMA PET/CT images were assessed by 5 readers for visual RECIP 1.0. The primary outcome was the association of RECIP with prostate-specific antigen progression-free survival (PSA-PFS) by Kaplan-Meier analysis. Results: In total, 124 of 287 screened patients met the inclusion criteria, with 0 (0%), 29 (23%), 54 (44%), and 41 (33%) of those 124 patients having complete response, partial response, stable disease, or progressive disease (PD) by visual RECIP 1.0, respectively. Patients with visual RECIP PD had a significantly shorter PSA-PFS than those with RECIP stable disease or with RECIP partial response (2.6 vs. 6.4 vs. 8.4 mo; P < 0.001). The median PSA-PFS among patients with RECIP PD versus those with non-RECIP PD was 2.6 versus 7.2 mo (hazard ratio, 13.0; 95% CI, 7.0-24.1; P < 0.001). Conclusion: PSMA PET/CT by RECIP 1.0 after 2 cycles of [177Lu]Lu-PSMA is prognostic for PSA-PFS. PSMA PET/CT by RECIP 1.0 may be used in earlier stages of prostate cancer to evaluate drug efficacy and to predict progression-free survival.

Glypican-3 deficiency in liver cancer upregulates MAPK/ERK pathway but decreases cell proliferation.

Glypican-3 (GPC3) is overexpressed in hepatocellular carcinomas and hepatoblastomas and represents an important therapeutic target but the biologic importance of GPC3 in liver cancer is unclear. To date, there are limited data characterizing the biological implications of GPC3 knockout (KO) in liver cancers that intrinsically express this target. Here, we report on the development and characterization of GPC3-KO liver cancer cell lines and compare to them to parental lines. GPC3-KO variants were established in HepG2 and Hep3B liver cancer cell lines using a lentivirus-mediated CRISPR/Cas9 system. We assessed the effects of GPC3 deficiency on oncogenic properties in vitro and in murine xenograft models. Downstream cellular signaling pathway changes induced by GPC3 deficiency were examined by RNAseq and western blot. To confirm the usefulness of the models for GPC3-targeted drug development, we evaluated the target engagement of a GPC3-selective antibody, GC33, conjugated to the positron-emitting zirconium-89 (89Zr) in subcutaneous murine xenografts of wild type (WT) and KO liver cancer cell lines. Deletion of GPC3 significantly reduced liver cancer cell proliferation, migration, and invasion compared to the parental cell lines. Additionally, the tumor growth of GPC3-KO liver cancer xenografts was significantly slower compared with control xenografts. RNA sequencing analysis also showed GPC3-KO resulted in a reduction in the expression of genes associated with cell cycle regulation, invasion, and migration. Specifically, we observed the downregulation of components in the AKT/NFκB/WNT signaling pathways and of molecules related to cell cycle regulation with GPC3-KO. In contrast, pMAPK/ERK1/2 was upregulated, suggesting an adaptive compensatory response. KO lines demonstrated increased sensitivity to ERK (GDC09994), while AKT (MK2206) inhibition was more effective in WT lines. Using antibody-based positron emission tomography (immunoPET) imaging, we confirmed that 89Zr-GC33 accumulated exclusively in GPC3-expression xenografts but not in GPC3-KO xenografts with high tumor uptake and tumor-to-liver signal ratio. We show that GPC3-KO liver cancer cell lines exhibit decreased tumorigenicity and altered signaling pathways, including upregulated pMAPK/ERK1/2, compared to parental lines. Furthermore, we successfully distinguished between GPC3+ and GPC3- tumors using the GPC3-targeted immunoPET imaging agent, demonstrating the potential utility of these cell lines in facilitating GPC3-selective drug development.