Current Status of Radiopharmaceutical Therapy

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.

Establishing Updated Safety Standards for Independent 99mTc-MAA SPECT/CT Treatment Planning in Radioembolization

PURPOSE

Significant improvements within radioembolization imaging and dosimetry permit the development of an accurate and personalized pretreatment plan using technetium 99m-labeled macroaggregated albumin (99mTc-MAA) and single-photon emission computed tomography (SPECT) combined with anatomical CT (SPECT/CT). Despite these potential advantages, the clinical transition to pretreatment protocols with SPECT/CT is hindered by their unknown safety constraints. This study aimed to address this issue by establishing novel dose limits for 99mTc-MAA SPECT/CT to enable quantitative pretreatment planning.

METHODS AND MATERIALS

Stratification criteria to determine images most viable for dosimetry analysis were created from a cohort of 85 patients. SPECT/CT, cone beam CT, and activity calculations derived from the local deposition method were used to create an accurate pretreatment protocol. Planar and SPECT/CT images were compared using linear regression and modified Bland-Altman analyses to convert accepted planar dose limits to SPECT/CT. To validate these new dose limits, activity calculations based on SPECT/CT were compared with those calculated with the body surface area and planar methods for three treatment plans.

RESULTS

A total of 38 of 85 patients were deemed viable for dosimetry analysis. SPECT yielded greater lung shunt fractions (LSFs) than planar imaging when LSFs were <4.89%, whereas SPECT yielded lower LSFs than planar imaging when LSFs were >4.89%. Planar to SPECT/CT dose conversions were 0.76×, 0.70×, and 0.55× for the whole liver, normal liver, and lungs, respectively. Patients with SPECT LSFs ≤4.89% were safely treated with the direct application of planar lung dose limits. Activity calculations with the newly established SPECT/CT dose limits were greater than those of the body surface area method by a median range of 33.1% to 61.9% and were lower than planar-based activity calculations by a median range of 12.5% to 13.7% for the whole liver and by 29.4% to 32.2% for the normal liver.

CONCLUSIONS

This study demonstrated a safe method for translating dose limits from 99mTc-MAA planar imaging to SPECT/CT. A robust pretreatment protocol was further developed guided by the current knowledge in the field. Established SPECT/CT dose limits safely treated 97.5% of patients and permitted the application of independent pretreatment planning with 99mTc-MAA SPECT/CT.

Monte Carlo-Based Nanoscale Dosimetry Holds Promise for Radiopharmaceutical Therapy Involving Auger Electron Emitters

Radiopharmaceutical therapy (RPT) is evolving as a promising strategy for treating cancer. As interest grows in short-range particles, like Auger electrons, understanding the dose-response relationship at the deoxyribonucleic acid (DNA) level has become essential. In this study, we used the Geant4-DNA toolkit to evaluate DNA damage caused by the Auger-electron-emitting isotope I-125. We compared the energy deposition and single strand break (SSB) yield at each base pair location in a short B-form DNA (B-DNA) geometry with existing simulation and experimental data, considering both physical direct and chemical indirect hits. Additionally, we evaluated dosimetric differences between our high-resolution B-DNA target and a previously published simple B-DNA geometry. Overall, our benchmarking results for SSB yield from I-125 decay exhibited good agreement with both simulation and experimental data. Using this simulation, we then evaluated the SSB and double strand break (DSB) yields caused by a theranostic Br-77-labeled poly ADP ribose polymerase (PARP) inhibitor radiopharmaceutical. The results indicated a predominant contribution of chemical indirect hits over physical direct hits in generating SSB and DSB. This study lays the foundation for future investigations into the nano-dosimetric properties of RPT.

Feasibility of identifying proliferative active bone marrow with fat fraction MRI and multi-energy CT

Objective.Active bone marrow (ABM) can serve as both an organ at risk and a target in external beam radiotherapy.18F-fluorothymidine (FLT) PET is the current gold standard for identifying proliferative ABM but it is not approved for human use, and PET scanners are not always available to radiotherapy clinics. Identifying ABM through other, more accessible imaging modalities will allow more patients to receive treatment specific to their ABM distribution. Multi-energy CT (MECT) and fat-fraction MRI (FFMRI) show promise in their ability to characterize bone marrow adiposity, but these methods require validation for identifying proliferative ABM.Approach.Six swine subjects were imaged using FFMRI, fast-kVp switching (FKS) MECT and sequential-scanning (SS) MECT to identify ABM volumes relative to FLT PET-derived ABM volumes. ABM was contoured on FLT PET images as the region within the bone marrow with a SUV above the mean. Bone marrow was then contoured on the FFMRI and MECT images, and thresholds were applied within these contours to determine which threshold produced the best agreement with the FLT PET determined ABM contour. Agreement between contours was measured using the Dice similarity coefficient (DSC).Main results.FFMRI produced the best estimate of the PET ABM contour. Compared to FLT PET ABM volumes, the FFMRI, SS MECT and FKS MECT ABM contours produced average peak DSC of 0.722 ± 0.080, 0.619 ± 0.070, and 0.464 ± 0.080, respectively. The ABM volume was overestimated by 40.51%, 97.63%, and 140.13% by FFMRI, SS MECT and FKS MECT, respectively.Significance.This study explored the ability of FFMRI and MECT to identify the proliferative relative to ABM defined by FLT PET. Of the methods investigated, FFMRI emerged as the most accurate approximation to FLT PET-derived active marrow contour, demonstrating superior performance by both DSC and volume comparison metrics. Both FFMRI and SS MECT show promise for providing patient-specific ABM treatments.

Characterizing the voxel-based approaches in radioembolization dosimetry with reDoseMC

BACKGROUND

Yttrium-90 (90 Y $^{90}{\rm {Y}}$ ) represents the primary radioisotope used in radioembolization procedures, while holmium-166 (166 Ho $^{166}{\rm {Ho}}$ ) is hypothesized to serve as a viable substitute for90 Y $^{90}{\rm {Y}}$ due to its comparable therapeutic potential and improved quantitative imaging. Voxel-based dosimetry for these radioisotopes relies on activity images obtained through PET or SPECT and dosimetry methods, including the voxel S-value (VSV) and the local deposition method (LDM). However, the evaluation of the accuracy of absorbed dose calculations has been limited by the use of non-ideal reference standards and investigations restricted to the liver. The objective of this study was to expand upon these dosimetry characterizations by investigating the impact of image resolutions, voxel sizes, target volumes, and tissue materials on the accuracy of90 Y $^{90}{\rm {Y}}$ and166 Ho $^{166}{\rm {Ho}}$ dosimetry techniques.

METHODS

A specialized radiopharmaceutical dosimetry software called reDoseMC was developed using the Geant4 Monte Carlo toolkit and validated by benchmarking the generated90 Y $^{90}{\rm {Y}}$ kernels with published data. The decay spectra of both90 Y $^{90}{\rm {Y}}$ and166 Ho $^{166}{\rm {Ho}}$ were also compared. Multiple VSV kernels were generated for the liver, lungs, soft tissue, and bone for isotropic voxel sizes of 1 mm, 2 mm, and 4 mm. Three theoretical phantom setups were created with 20 or 40 mm activity and mass density inserts for the same three voxel sizes. To replicate the limited spatial resolutions present in PET and SPECT images, image resolutions were modeled using a 3D Gaussian kernel with a Full Width at Half Maximum (FWHM) ranging from 0 to 16 mm and with no added noise. The VSV and LDM dosimetry methods were evaluated by characterizing their respective kernels and analyzing their absorbed dose estimates calculated on theoretical phantoms. The ground truth for these estimations was calculated using reDoseMC.

RESULTS

The decay spectra obtained through reDoseMC showed less than a 1% difference when compared to previously published experimental data for energies below 1.9 MeV in the case of90 Y $^{90}{\rm {Y}}$ and less than 1% for energies below 1.5 MeV for166 Ho $^{166}{\rm {Ho}}$ . Additionally, the validation kernels for90 Y $^{90}{\rm {Y}}$ VSV exhibited results similar to those found in published Monte Carlo codes, with source dose depositions having less than a 3% error margin. Resolution thresholds (FWHM thresh s ${\rm {FWHM}}_\mathrm{thresh}{\rm {s}}$ ), defined as resolutions that resulted in similar dose estimates between the LDM and VSV methods, were observed for90 Y $^{90}{\rm {Y}}$ . They were 1.5 mm for bone, 2.5 mm for soft tissue and liver, and 8.5 mm for lungs. For166 Ho $^{166}{\rm {Ho}}$ , the accuracy of absorbed dose deposition was found to be dependent on the contributions of absorbed dose from photons. Volume errors due to variations in voxel size impacted the final dose estimates. Larger target volumes yielded more accurate mean doses than smaller volumes. For both radioisotopes, the radial dose profiles for the VSV and LDM approximated but never matched the reference standard.

CONCLUSIONS

reDoseMC was developed and validated for radiopharmaceutical dosimetry. The accuracy of voxel-based dosimetry was found to vary widely with changes in image resolutions, voxel sizes, chosen target volumes, and tissue material; hence, the standardization of dosimetry protocols was found to be of great importance for comparable dosimetry analysis.

Radiological and Molecular Analysis of Radioiodinated Anastrozole and Epirubicin as Innovative Radiopharmaceuticals Targeting Methylenetetrahydrofolate Dehydrogenase 2 in Solid Tumors

In the dynamic field of radiopharmaceuticals, innovating targeted agents for cancer diagnosis and therapy is crucial. Our study enriches this evolving landscape by evaluating the potential of radioiodinated anastrozole ([125I]anastrozole) and radioiodinated epirubicin ([125I]epirubicin) as targeting agents against MTHFD2-driven tumors. MTHFD2, which is pivotal in one-carbon metabolism, is notably upregulated in various cancers, presenting a novel target for radiopharmaceutical application. Through molecular docking and 200 ns molecular dynamics (MD) simulations, we assess the binding efficiency and stability of [125I]anastrozole and [125I]epirubicin with MTHFD2. Molecular docking illustrates that [125I]epirubicin has a superior binding free energy (∆Gbind) of -41.25 kJ/mol compared to -39.07 kJ/mol for [125I]anastrozole and -38.53 kJ/mol for the control ligand, suggesting that it has a higher affinity for MTHFD2. MD simulations reinforce this, showing stable binding, as evidenced by root mean square deviation (RMSD) values within a narrow range, underscoring the structural integrity of the enzyme-ligand complexes. The root mean square fluctuation (RMSF) analysis indicates consistent dynamic behavior of the MTHFD2 complex upon binding with [125I]anastrozole and [125I]epirubicin akin to the control. The radius of gyration (RG) measurements of 16.90 Å for MTHFD2-[125I]anastrozole and 16.84 Å for MTHFD2-[125I]epirubicin confirm minimal structural disruption upon binding. The hydrogen bond analysis reveals averages of two and three stable hydrogen bonds for [125I]anastrozole and [125I]epirubicin complexes, respectively, highlighting crucial stabilizing interactions. The MM-PBSA calculations further endorse the thermodynamic favorability of these interactions, with binding free energies of -48.49 ± 0.11 kJ/mol for [125I]anastrozole and -43.8 kJ/mol for MTHFD2-. The significant contribution of Van der Waals and electrostatic interactions to the binding affinities of [125I]anastrozole and [125I]epirubicin, respectively, underscores their potential efficacy for targeted tumor imaging and therapy. These computational findings lay the groundwork for the future experimental validation of [125I]anastrozole and [125I]epirubicin as MTHFD2 inhibitors, heralding a notable advancement in precision oncology tools. The data necessitate subsequent in vitro and in vivo assays to corroborate these results.

Bone Metastases

ABSTRACT

Bone metastases occur frequently in common malignancies such as breast and prostate cancer. They are responsible for considerable morbidity and skeletal-related events. Fortunately, there are now several systemic, focal, and targeted therapies that can improve quality and length of life, including radionuclide therapies. It is therefore important that bone metastases can be detected as early as possible and that treatment can be accurately and sensitively monitored. Several bone-specific and tumor-specific single-photon emission computed tomography and positron emission tomography molecular imaging agents are available, for detection and monitoring response to systemic therapeutics, as well as theranostic agents to confirm target expression and predict response to radionuclide therapies.

The Effects of Particle LET and Fluence on the Complexity and Frequency of Clustered DNA Damage

Motivation

Clustered DNA-lesions are predominantly induced by ionizing radiation, particularly by high-LET particles, and considered as lethal damage. Quantification of this specific type of damage as a function of radiation parameters such as LET, dose rate, dose, and particle type can be informative for the prediction of biological outcome in radiobiological studies. This study investigated the induction and complexity of clustered DNA damage for three different types of particles at an LET range of 0.5-250 keV/μm.

Methods

Nanometric volumes (36.0 nm3) of 15 base-pair DNA with its hydration shell was modeled. Electron, proton, and alpha particles at various energies were simulated to irradiate the nanometric volumes. The number of ionization events, low-energy electron spectra, and chemical yields for the formation of °OH, H°, e aq - , and H2O2 were calculated for each particle as a function of LET. Single- and double-strand breaks (SSB and DSB), base release, and clustered DNA-lesions were computed from the Monte-Carlo based quantification of the reactive species and measured yields of the species responsible for the DNA lesion formation.

Results

The total amount of DNA damage depends on particle type and LET. The number of ionization events underestimates the quantity of DNA damage at LETs higher than 10 keV/μm. Minimum LETs of 9.4 and 11.5 keV/μm are required to induce clustered damage by a single track of proton and alpha particles, respectively. For a given radiation dose, an increase in LET reduces the number of particle tracks, leading to more complex clustered DNA damage, but a smaller number of separated clustered damage sites.

Conclusions

The dependency of the number and the complexity of clustered DNA damage on LET and fluence suggests that the quantification of this damage can be a useful method for the estimation of the biological effectiveness of radiation. These results also suggest that medium-LET particles are more appropriate for the treatment of bulk targets, whereas high-LET particles can be more effective for small targets.

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.

Modification patterns and metabolic characteristics of m6A regulators in digestive tract tumors

M6A is essential for tumor occurrence and progression. The expression patterns of m6A regulators differ in various kinds of tumors. Transcriptomic expression statistics together with clinical data from a database were analyzed to distinguish patients with digestive tract tumors. Based on the expression patterns of diverse m6A regulators, patients were divided into several clusters. Survival analysis suggested significant differences in patient prognosis among the m6A clusters. The results showed overlapping of m6A expression patterns with energy metabolism and nucleotide metabolism. Functional analyses imply that m6A modifications in tumor cells probably drive metabolic reprogramming to sustain rapid proliferation of cancer cells. Our analysis highlights the m6A risk characterizes various kinds of metabolic features and predicts chemotherapy sensitivity in digestive tract tumors, providing evidence for m6A regulators as markers to predict patient outcomes.

Radiomics and Artificial Intelligence in Radiotheranostics: A Review of Applications for Radioligands Targeting Somatostatin Receptors and Prostate-Specific Membrane Antigens

Radiotheranostics refers to the pairing of radioactive imaging biomarkers with radioactive therapeutic compounds that deliver ionizing radiation. Given the introduction of very promising radiopharmaceuticals, the radiotheranostics approach is creating a novel paradigm in personalized, targeted radionuclide therapies (TRTs), also known as radiopharmaceuticals (RPTs). Radiotherapeutic pairs targeting somatostatin receptors (SSTR) and prostate-specific membrane antigens (PSMA) are increasingly being used to diagnose and treat patients with metastatic neuroendocrine tumors (NETs) and prostate cancer. In parallel, radiomics and artificial intelligence (AI), as important areas in quantitative image analysis, are paving the way for significantly enhanced workflows in diagnostic and theranostic fields, from data and image processing to clinical decision support, improving patient selection, personalized treatment strategies, response prediction, and prognostication. Furthermore, AI has the potential for tremendous effectiveness in patient dosimetry which copes with complex and time-consuming tasks in the RPT workflow. The present work provides a comprehensive overview of radiomics and AI application in radiotheranostics, focusing on pairs of SSTR- or PSMA-targeting radioligands, describing the fundamental concepts and specific imaging/treatment features. Our review includes ligands radiolabeled by 68Ga, 18F, 177Lu, 64Cu, 90Y, and 225Ac. Specifically, contributions via radiomics and AI towards improved image acquisition, reconstruction, treatment response, segmentation, restaging, lesion classification, dose prediction, and estimation as well as ongoing developments and future directions are discussed.

Carrier systems of radiopharmaceuticals and the application in cancer therapy

Radiopharmaceuticals play a vital role in cancer therapy. The carrier of radiopharmaceuticals can precisely locate and guide radionuclides to the target, where radionuclides kill surrounding tumor cells. Effective application of radiopharmaceuticals depends on the selection of an appropriate carrier. Herein, different types of carriers of radiopharmaceuticals and the characteristics are briefly described. Subsequently, we review radiolabeled monoclonal antibodies (mAbs) and their derivatives, and novel strategies of radiolabeled mAbs and their derivatives in the treatment of lymphoma and colorectal cancer. Furthermore, this review outlines radiolabeled peptides, and novel strategies of radiolabeled peptides in the treatment of neuroendocrine neoplasms, prostate cancer, and gliomas. The emphasis is given to heterodimers, bicyclic peptides, and peptide-modified nanoparticles. Last, the latest developments and applications of radiolabeled nucleic acids and small molecules in cancer therapy are discussed. Thus, this review will contribute to a better understanding of the carrier of radiopharmaceuticals and the application in cancer therapy.

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

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

Data reconciliation connected to guard bands to set specification limits related to risk assessment for radiopharmaceutical activity

Radiopharmaceuticals have been used to diagnose several diseases, particularly because the procedure is non-invasive. However, it is important that the correct amount of radiopharmaceutical is used to avoid inaccurate diagnostic results and suboptimal therapeutic outcomes. The amount of the radiopharmaceutical is measured when produced (by the supplier) and a second time (by the receiver), before it's use. When measured at the receiver, the result is corrected for its normal radioactivity decay. Even then, it is possible that both measurements should be considered nominal different or even statistically different when compared through various statistical tools. This research combines two innovative techniques in the field of clinical metrology. The first technique is data reconciliation, which not only enhances measurement accuracy but also reduces measurement uncertainty. The second technique involves using uncertainty information to establish specification limits for compliance assessments. In this way, our proposal aimed to minimize the risk of making incorrect decisions regarding the conformity of the concentration of radiopharmaceutical activity, that is, rejecting an item or batch that is within specification or accepting an item or batch that is outside of specification. A spreadsheet, based on these metrology fundamentals, is available to help the user with the calculations, presenting numerical and graphical results for some common radioisotopes. Reliable specification limits can be calculated and used to determine if the radiopharmaceutical is in accordance with its proposed application.

Developments in 177Lu-based radiopharmaceutical therapy and dosimetry

177Lu is a radioisotope that has become increasingly popular as a therapeutic agent for treating various conditions, including neuroendocrine tumors and metastatic prostate cancer. 177Lu-tagged radioligands are molecules precisely designed to target and bind to specific receptors or proteins characteristic of targeted cancer. This review paper will present an overview of the available 177Lu-labelled radioligands currently used to treat patients. Based on recurring, active, and completed clinical trials and other available literature, we evaluate current status, interests, and developments in assessing patient-specific dosimetry, which will define the future of this particular treatment modality. In addition, we will discuss the challenges and opportunities of the existing dosimetry standards to measure and calculate the radiation dose delivered to patients, which is essential for ensuring treatments' safety and efficacy. Finally, this article intends to provide an overview of the current state of 177Lu- tagged radioligand therapy and highlight the areas where further research can improve patient treatment outcomes.

Theranostics and Patient-Specific Dosimetry

Radiopharmaceutical therapy (RPT) is an invigorated form of cancer therapy that systemically delivers targeted radioactive drugs to cancer cells. Theranostics is a type of RPT that utilizes imaging, either of the RPT drug directly or a companion diagnostic, to inform whether a patient will benefit from the treatment. Given the ability to image the drug onboard theranostic treatments also lends itself readily to patient-specific dosimetry, which is a physics-based process that determines the overall absorbed dose burden to healthy organs and tissues and tumors in patients. While companion diagnostics identify who will benefit from RPT treatments, dosimetry determines how much activity these beneficiaries can receive to maximize therapeutic efficacy. Clinical data is starting to accrue suggesting tremendous benefits when dosimetry is performed for RPT patients. RPT dosimetry, which was once performed by florid and often inaccurate workflows, can now be performed more efficiently and accurately with FDA-cleared dosimetry software. Therefore, there is no better time for the field of oncology to adopt this form of personalize medicine to improve outcomes for cancer patients.

Clinical Advances and Perspectives in Targeted Radionuclide Therapy

Targeted radionuclide therapy has become increasingly prominent as a nuclear medicine subspecialty. For many decades, treatment with radionuclides has been mainly restricted to the use of iodine-131 in thyroid disorders. Currently, radiopharmaceuticals, consisting of a radionuclide coupled to a vector that binds to a desired biological target with high specificity, are being developed. The objective is to be as selective as possible at the tumor level, while limiting the dose received at the healthy tissue level. In recent years, a better understanding of molecular mechanisms of cancer, as well as the appearance of innovative targeting agents (antibodies, peptides, and small molecules) and the availability of new radioisotopes, have enabled considerable advances in the field of vectorized internal radiotherapy with a better therapeutic efficacy, radiation safety and personalized treatments. For instance, targeting the tumor microenvironment, instead of the cancer cells, now appears particularly attractive. Several radiopharmaceuticals for therapeutic targeting have shown clinical value in several types of tumors and have been or will soon be approved and authorized for clinical use. Following their clinical and commercial success, research in that domain is particularly growing, with the clinical pipeline appearing as a promising target. This review aims to provide an overview of current research on targeting radionuclide therapy.

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

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

Roadmap for precision preclinical x-ray radiation studies

This Roadmap paper covers the field of precision preclinical x-ray radiation studies in animal models. It is mostly focused on models for cancer and normal tissue response to radiation, but also discusses other disease models. The recent technological evolution in imaging, irradiation, dosimetry and monitoring that have empowered these kinds of studies is discussed, and many developments in the near future are outlined. Finally, clinical translation and reverse translation are discussed.

Synthesis and evaluation of radioiodinated estrogens for diagnosis and therapy of male urogenital tumours

The preparation of 24 estrogens, their estrogen receptor (ER) affinity and studies of radioiodinated estrogen binding to ER-positive male bladder tumor cells (HTB9) are described. The estrogens with the highest affinity were selected using fluorescence anisotropy assays. A 2,2,2-trifluoroethyl group at the 11β-position caused particularly promising affinity. (Radio)iodination was performed on the 17α-vinyl group. Binding studies on HTB9 cells revealed picomolar affinities of radioconjugates 19 and 31, indicating promising ability for targeting of urogenital tumors.

Large-scale in vitro microdosimetry via live cell microscopy imaging: implications for radiosensitivity and RBE evaluations in alpha-emitter radiopharmaceutical therapy

BACKGROUND

Alpha-emitter radiopharmaceutical therapy (αRPT) has shown promising outcomes in metastatic disease. However, the short range of the alpha particles necessitates dosimetry on a near-cellular spatial scale. Current knowledge on cellular dosimetry is primarily based on in vitro experiments using cell monolayers. The goal of such experiments is to establish cell sensitivity to absorbed dose (AD). However, AD cannot be measured directly and needs to be modeled. Current models, often idealize cells as spheroids in a regular grid (geometric model), simplify binding kinetics and ignore the stochastic nature of radioactive decay. It is unclear what the impact of such simplifications is, but oversimplification results in inaccurate and non-generalizable results, which hampers the rigorous study of the underlying radiobiology.

METHODS

We systematically mapped out 3D cell geometries, clustering behavior, agent binding, internalization, and subcellular trafficking kinetics for a large cohort of live cells under representative experimental conditions using confocal microscopy. This allowed for realistic Monte Carlo-based (micro)dosimetry. Experimentally established surviving fractions of the HER2 + breast cancer cell line treated with a ²¹²Pb-labelled anti-HER2 conjugate or external beam radiotherapy, anchored a rigorous statistical approach to cell sensitivity and relative biological effectiveness (RBE) estimation. All outcomes were compared to a reference geometric model, which allowed us to determine which aspects are crucial model components for the proper study of the underlying radiobiology.

RESULTS

In total, 567 cells were measured up to 26 h post-incubation. Realistic cell clustering had a large (2x), and cell geometry a small (16.4% difference) impact on AD, compared to the geometric model. Microdosimetry revealed that more than half of the cells do not receive any dose for most of the tested conditions, greatly impacting cell sensitivity estimates. Including these stochastic effects in the model, resulted in significantly more accurate predictions of surviving fraction and RBE (permutation test; p < .01).

CONCLUSIONS

This comprehensive integration of the biological and physical aspects resulted in a more accurate method of cell survival modelling in αRPT experiments. Specifically, including realistic stochastic radiation effects and cell clustering behavior is crucial to obtaining generalizable radiobiological parameters.

A Primer on Radiopharmaceutical Therapy

The goal of this article is to serve as a primer for the United States-based radiation oncologist who may be interested in learning more about radiopharmaceutical therapy (RPT). Specifically, we define RPT, review the data behind its current and anticipated indications, and discuss important regulatory considerations for incorporating it into clinical practice. RPT represents an opportunity for radiation oncologists to leverage 2 key areas of expertise, namely therapeutic radiation therapy and oncology, and apply them in a distinct context in collaboration with nuclear medicine and medical oncology colleagues. Although not every radiation oncologist will incorporate RPT into their day-to-day practice, it is important to understand the role for this modality and how it can be appropriately used in select patients.

Experimental validation of Monte Carlo dosimetry for therapeutic beta emitters with radiochromic film in a 3D-printed phantom

PURPOSE

Validation of dosimetry software, such as Monte Carlo (MC) radiation transport codes used for patient-specific absorbed dose estimation, is critical prior to their use in clinical decision making. However, direct experimental validation in the clinic is generally not performed for low/medium-energy beta emitters used in radiopharmaceutical therapy (RPT) due to the challenges of measuring energy deposited by short-range particles. Our objective was to design a practical phantom geometry for radiochromic film (RF)-based absorbed dose measurements of beta-emitting radionuclides and perform experiments to directly validate our in-house developed Dose Planning Method (DPM) MC code dedicated to internal dosimetry.

METHODS

The experimental setup was designed for measuring absorbed dose from beta emitters that have a range sufficiently penetrating to ∼200 μm in water as well as to capture any photon contributions to absorbed dose. Assayed ¹⁷⁷ Lu and ⁹⁰ Y liquid sources, 13-450 MBq estimated to deliver 0.5-10 Gy to the sensitive layer of the RF, were injected into the cavity of two 3D-printed half-cylinders that had been sealed with 12.7 μm or 25.4 μm thick Kapton Tape. A 3.8 × 6 cm strip of GafChromic EBT3 RF was sandwiched between the two taped half-cylinders. After 2-48 h exposures, films were retrieved and wipe tested for contamination. Absorbed dose to the RF was measured using a commercial triple-channel dosimetry optimization method and a calibration generated via 6 MV photon beam. Profiles were analyzed across the central 1 cm² area of the RF for validation. Eleven experiments were completed with ¹⁷⁷ Lu and nine with ⁹⁰ Y both in saline and a bone equivalent solution. Depth dose curves were generated for ¹⁷⁷ Lu and ⁹⁰ Y stacking multiple RF strips between a single filled half-cylinder and an acrylic backing. All experiments were modeled in DPM to generate voxelized MC absorbed dose estimates. We extended our study to benchmark general purpose MC codes MCNP6 and EGSnrc against the experimental results as well.

RESULTS

A total of 20 experiments showed that both the 3D-printed phantoms and the final absorbed dose values were reproducible. The agreement between the absorbed dose estimates from the RF measurements and DPM was on average -4.0% (range -10.9% to 3.2%) for all single film ¹⁷⁷ Lu experiments and was on average -1.0% (range -2.7% to 0.7%) for all single film ⁹⁰ Y experiments. Absorbed depth dose estimates by DPM agreed with RF on average 1.2% (range -8.0% to 15.2%) across all depths for ¹⁷⁷ Lu and on average 4.0% (range -5.0% to 9.3%) across all depths for ⁹⁰ Y. DPM absorbed dose estimates agreed with estimates from EGSnrc and MCNP across the board, within 4.7% and within 3.4% for ¹⁷⁷ Lu and ⁹⁰ Y respectively, for all geometries and across all depths. MC showed that absorbed dose to RF from betas was greater than 92% of the total (betas + other radiations) for ¹⁷⁷ Lu, indicating measurement of dominant beta contribution with our design.

CONCLUSIONS

The reproducible results with a RF insert in a simple phantom designed for liquid sources demonstrate that this is a reliable setup for experimentally validating dosimetry algorithms used in therapies with beta-emitting unsealed sources. Absorbed doses estimated with the DPM MC code showed close agreement with RF measurement and with results from two general purpose MC codes, thereby validating the use of this algorithms for clinical RPT dosimetry.

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.

Targeted Alpha Therapy of Glioma Using 211At-Labeled Heterodimeric Peptide Targeting Both VEGFR and Integrins

Targeted radionuclide therapy based on α-emitters plays an increasingly important role in cancer treatment. In this study, we proposed to apply a heterodimeric peptide (iRGD-C6-lys-C6-^DA7R) targeting both VEGFR and integrins as a new vector for ²¹¹At radiolabeling to obtain high-performance radiopharmaceuticals with potential in targeted alpha therapy (TAT). An astatinated peptide, iRGD-C6-lys(²¹¹At-ATE)-C6-^DA7R, was prepared with a radiochemical yield of ∼45% and high radiochemical purity of >95% via an electrophilic radioastatodestannylation reaction. iRGD-C6-lys(²¹¹At-ATE)-C6-^DA7R showed good stability in vitro and high binding ability to U87MG (glioma) cells. Systematic in vitro antitumor investigations involving cytotoxicity, apoptosis, distribution of the cell cycle, and reactive oxygen species (ROS) clearly demonstrated that ²¹¹At-labeled heterodimeric peptides could significantly inhibit cell viability, induce cell apoptosis, arrest the cell cycle in G2/M phase, and increase intracellular ROS levels in a dose-dependent manner. Biodistribution revealed that iRGD-C6-lys(²¹¹At-ATE)-C6-^DA7R had rapid tumor accumulation and fast normal tissue/organ clearance, which was mainly excreted through the kidneys. Moreover, in vivo therapeutic evaluation indicated that iRGD-C6-lys(²¹¹At-ATE)-C6-^DA7R was able to obviously inhibit tumor growth and prolong the survival of mice bearing glioma xenografts without notable toxicity to normal organs. All these results suggest that TAT mediated by iRGD-C6-lys(²¹¹At-ATE)-C6-^DA7R can provide an effective and promising strategy for the treatment of glioma and some other tumors.

Melanin and Melanin-Functionalized Nanoparticles as Promising Tools in Cancer Research-A Review

Cancer poses an ongoing global challenge, despite the substantial progress made in the prevention, diagnosis, and treatment of the disease. The existing therapeutic methods remain limited by undesirable outcomes such as systemic toxicity and lack of specificity or long-term efficacy, although innovative alternatives are being continuously investigated. By offering a means for the targeted delivery of therapeutics, nanotechnology (NT) has emerged as a state-of-the-art solution for augmenting the efficiency of currently available cancer therapies while combating their drawbacks. Melanin, a polymeric pigment of natural origin that is widely spread among many living organisms, became a promising candidate for NT-based cancer treatment owing to its unique physicochemical properties (e.g., high biocompatibility, redox behavior, light absorption, chelating ability) and innate antioxidant, photoprotective, anti-inflammatory, and antitumor effects. The latest research on melanin and melanin-like nanoparticles has extended considerably on many fronts, allowing not only efficient cancer treatments via both traditional and modern methods, but also early disease detection and diagnosis. The current paper provides an updated insight into the applicability of melanin in cancer therapy as antitumor agent, molecular target, and delivery nanoplatform.

Dosimetry of nuclear medicine therapies: current controversies and impact on treatment optimization

Nuclear medicine therapeutic procedures have considerably expanded over the last few years, and their number is expected to grow exponentially in the future. Internal dosimetry has significantly developed as well, but has not yet been uniformly accepted as a valuable tool for prediction of therapeutic efficacy and toxicity. In this paper, we briefly summarize some of the arguments about the implementation of internal dosimetry in clinical practice. In addition, we provide a few examples of radionuclide anticancer therapies for which internal dosimetry demonstrated a significant impact on treatment optimization and patient outcome.

Compensating Positron Range Effects of Ga-68 in Preclinical PET Imaging by Using Convolutional Neural Network: A Monte Carlo Simulation Study

This study aimed to investigate the feasibility of positron range correction based on three different convolutional neural network (CNN) models in preclinical PET imaging of Ga-68. The first model (CNN1) was originally designed for super-resolution recovery, while the second model (CNN2) and the third model (CNN3) were originally designed for pseudo CT synthesis from MRI. A preclinical PET scanner and 30 phantom configurations were modeled in Monte Carlo simulations, where each phantom configuration was simulated twice, once for Ga-68 (CNN input images) and once for back-to-back 511-keV gamma rays (CNN output images) with a 20 min emission scan duration. The Euclidean distance was used as the loss function to minimize the difference between CNN input and output images. According to our results, CNN3 outperformed CNN1 and CNN2 qualitatively and quantitatively. With regard to qualitative observation, it was found that boundaries in Ga-68 images became sharper after correction. As for quantitative analysis, the recovery coefficient (RC) and spill-over ratio (SOR) were increased after correction, while no substantial increase in coefficient of variation of RC (CV_RC) or coefficient of variation of SOR (CV_SOR) was observed. Overall, CNN3 should be a good candidate architecture for positron range correction in Ga-68 preclinical PET imaging.

National Cancer Institute support for targeted alpha-emitter therapy

BACKGROUND

Radiopharmaceutical targeted therapy (RPT) has been studied for decades; however, recent clinical trials demonstrating efficacy have helped renewed interest in the modality.

METHODS

This article reviews National Cancer Institute (NCI)'s support of RPT through communication via workshops and interest groups, through funding extramural programs in academia and small business, and through intramural research, including preclinical and clinical studies.

RESULTS

NCI has co-organized workshops and organized interest groups on RPT and RPT dosimetry to encourage the community and facilitate rigorous preclinical and clinical studies. NCI has been supporting RPT research through various mechanisms. Research has been funded through peer-reviewed NCI Research and Program Grants (RPG) and NCI Small Business Innovation Research (SBIR) Development Center, which funds small business-initiated projects, some of which have led to clinical trials. The NCI Cancer Therapy Evaluation Program (CTEP)'s Radiopharmaceutical Development Initiative supports RPT in NCI-funded clinical trials, including Imaging and Radiation Oncology Core (IROC) expertise in imaging QA and dosimetry procedures. Preclinical targeted a-emitter therapy (TAT) research at the NCI's intramural program is ongoing, building on foundational work dating back to the 1980s. Ongoing "bench-to-bedside" efforts leverage the unique infrastructure of the National Institutes of Health's (NIH) Clinical Center.

CONCLUSION

Given the great potential of RPT, our goal is to continue to encourage its development that will generate the high-quality evidence needed to bring this multidisciplinary treatment to patients.

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

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

Why bother with alpha particles?

The approval of 223RaCl2 for cancer therapy in 2013 has heralded a resurgence of interest in the development of α-particle emitting radiopharmaceuticals. In the last decade, over a dozen α-emitting radiopharmaceuticals have entered clinical trials, spawned by strong preclinical studies. In this article, we explore the potential role of α-particle therapy in cancer treatment. We begin by providing a background for the basic principles of therapy with α-emitters, and we explore recent breakthroughs in therapy with α-emitting radionuclides, including conjugates with small molecules and antibodies. Finally, we discuss some outstanding challenges to the clinical adoption of α-therapies and potential strategies to address them.

A Mathematical Modeling Approach for Targeted Radionuclide and Chimeric Antigen Receptor T Cell Combination Therapy

Simple Summary

Targeted radionuclide therapy (TRT) and immunotherapy, an example being chimeric antigen receptor T cells (CAR-Ts), represent two potent means of eradicating systemic cancers. Although each one as a monotherapy might have a limited effect, the potency can be increased with a combination of the two therapies. The complications involved in the dosing and scheduling of these therapies make the mathematical modeling of these therapies a suitable solution for designing combination treatment approaches. Here, we investigate a mathematical model for TRT and CAR-T cell combination therapies. Through an analysis of the mathematical model, we find that the tumor proliferation rate is the most important factor affecting the scheduling of TRT and CAR-T cell treatments with faster proliferating tumors requiring a shorter interval between the two therapies.

Abstract

Targeted radionuclide therapy (TRT) has recently seen a surge in popularity with the use of radionuclides conjugated to small molecules and antibodies. Similarly, immunotherapy also has shown promising results, an example being chimeric antigen receptor T cell (CAR-T) therapy in hematologic malignancies. Moreover, TRT and CAR-T therapies possess unique features that require special consideration when determining how to dose as well as the timing and sequence of combination treatments including the distribution of the TRT dose in the body, the decay rate of the radionuclide, and the proliferation and persistence of the CAR-T cells. These characteristics complicate the additive or synergistic effects of combination therapies and warrant a mathematical treatment that includes these dynamics in relation to the proliferation and clearance rates of the target tumor cells. Here, we combine two previously published mathematical models to explore the effects of dose, timing, and sequencing of TRT and CAR-T cell-based therapies in a multiple myeloma setting. We find that, for a fixed TRT and CAR-T cell dose, the tumor proliferation rate is the most important parameter in determining the best timing of TRT and CAR-T therapies.

A deep-learning-based prediction model for the biodistribution of 90 Y microspheres in liver radioembolization

BACKGROUND

Radioembolization with ⁹⁰ Y microspheres is a treatment approach for liver cancer. Currently, employed dosimetric calculations exhibit low accuracy, lacking consideration of individual patient, and tissue characteristics.

PURPOSE

The purpose of the present study was to employ deep learning (DL) algorithms to differentiate patterns of pretreatment distribution of ^99m Tc-macroaggregated albumin on SPECT/CT and post-treatment distribution of ⁹⁰ Y microspheres on PET/CT and to accurately predict how the ⁹⁰ Y-microspheres will be distributed in the liver tissue by radioembolization therapy.

METHODS

Data for 19 patients with liver cancer (10 with hepatocellular carcinoma, 5 with intrahepatic cholangiocarcinoma, 4 with liver metastases) who underwent radioembolization with ⁹⁰ Y microspheres were used for the DL training. We developed a 3D voxel-based variation of the Pix2Pix model, which is a special type of conditional GANs designed to perform image-to-image translation. SPECT and CT scans along with the clinical target volume for each patient were used as inputs, as were their corresponding post-treatment PET scans. The real and predicted absorbed PET doses for the tumor and the whole liver area were compared. Our model was evaluated using the leave-one-out method, and the dose calculations were measured using a tissue-specific dose voxel kernel.

RESULTS

The comparison of the real and predicted PET/CT scans showed an average absorbed dose difference of 5.42% ± 19.31% and 0.44% ± 1.64% for the tumor and the liver area, respectively. The average absorbed dose differences were 7.98 ± 31.39 Gy and 0.03 ± 0.25 Gy for the tumor and the non-tumor liver parenchyma, respectively. Our model had a general tendency to underpredict the dosimetric results; the largest differences were noticed in one case, where the model underestimated the dose to the tumor area by 56.75% or 72.82 Gy.

CONCLUSIONS

The proposed deep-learning-based pretreatment planning method for liver radioembolization accurately predicted ⁹⁰ Y microsphere biodistribution. Its combination with a rapid and accurate 3D dosimetry method will render it clinically suitable and could improve patient-specific pretreatment planning.

Overview of the First NRG Oncology-National Cancer Institute Workshop on Dosimetry of Systemic Radiopharmaceutical Therapy

In 2018, the National Cancer Institute and NRG Oncology partnered for the first time to host a joint workshop on systemic radiopharmaceutical therapy (RPT) to specifically address dosimetry issues and strategies for future clinical trials. The workshop focused on current dosimetric approaches for clinical trials, strategies under development that would optimize dose reporting, and future desired or optimized approaches for novel emerging radionuclides and carriers in development. In this article, we review the main approaches that are applied clinically to calculate the absorbed dose. These include absorbed doses calculated over a variety of spatial scales, including whole body, organ, suborgan, and voxel, the last 3 of which are achievable within the MIRD schema (S value) and can be calculated with analytic methods or Monte Carlo methods, the latter in most circumstances. This article will also contrast currently available methods and tools with those used in the past, to propose a pathway whereby dosimetry helps the field by optimizing the biologic effect of the treatment and trial design in the drug approval process to reduce financial and logistical costs. We also briefly discuss the dosimetric equivalent of biomarkers to help bring a precision medicine approach to RPT implementation when merited by evidence collected during early-phase trial investigations. Advances in the methodology and related tools have made dosimetry the optimum biomarker for RPT.

Novel Receptor Tyrosine Kinase Pathway Inhibitors for Targeted Radionuclide Therapy of Glioblastoma

Glioblastoma (GB) remains the most fatal brain tumor characterized by a high infiltration rate and treatment resistance. Overexpression and/or mutation of receptor tyrosine kinases is common in GB, which subsequently leads to the activation of many downstream pathways that have a critical impact on tumor progression and therapy resistance. Therefore, receptor tyrosine kinase inhibitors (RTKIs) have been investigated to improve the dismal prognosis of GB in an effort to evolve into a personalized targeted therapy strategy with a better treatment outcome. Numerous RTKIs have been approved in the clinic and several radiopharmaceuticals are part of (pre)clinical trials as a non-invasive method to identify patients who could benefit from RTKI. The latter opens up the scope for theranostic applications. In this review, the present status of RTKIs for the treatment, nuclear imaging and targeted radionuclide therapy of GB is presented. The focus will be on seven tyrosine kinase receptors, based on their central role in GB: EGFR, VEGFR, MET, PDGFR, FGFR, Eph receptor and IGF1R. Finally, by way of analyzing structural and physiological characteristics of the TKIs with promising clinical trial results, four small molecule RTKIs were selected based on their potential to become new therapeutic GB radiopharmaceuticals.

Moving Forward in the Next Decade: Radiation Oncology Sciences for Patient-Centered Cancer Care

In a time of rapid advances in science and technology, the opportunities for radiation oncology are undergoing transformational change. The linkage between and understanding of the physical dose and induced biological perturbations are opening entirely new areas of application. The ability to define anatomic extent of disease and the elucidation of the biology of metastases has brought a key role for radiation oncology for treating metastatic disease. That radiation can stimulate and suppress subpopulations of the immune response makes radiation a key participant in cancer immunotherapy. Targeted radiopharmaceutical therapy delivers radiation systemically with radionuclides and carrier molecules selected for their physical, chemical, and biochemical properties. Radiation oncology usage of “big data” and machine learning and artificial intelligence adds the opportunity to markedly change the workflow for clinical practice while physically targeting and adapting radiation fields in real time. Future precision targeting requires multidimensional understanding of the imaging, underlying biology, and anatomical relationship among tissues for radiation as spatial and temporal “focused biology.” Other means of energy delivery are available as are agents that can be activated by radiation with increasing ability to target treatments. With broad applicability of radiation in cancer treatment, radiation therapy is a necessity for effective cancer care, opening a career path for global health serving the medically underserved in geographically isolated populations as a substantial societal contribution addressing health disparities. Understanding risk and mitigation of radiation injury make it an important discipline for and beyond cancer care including energy policy, space exploration, national security, and global partnerships.

Ablative radiation therapy to restrain everything safely treatable (ARREST): study protocol for a phase I trial treating polymetastatic cancer with stereotactic radiotherapy

BACKGROUND

Patients with polymetastatic cancer are most often treated with systemic therapy to improve overall survival and/or delay progression, with palliative radiotherapy reserved for sites of symptomatic disease. Stereotactic ablative radiotherapy (SABR) has shown promise in the treatment of oligometastatic disease, but the utility of SABR in treating all sites of polymetastatic disease has yet to be evaluated. This study aims to evaluate the maximally tolerated dose (MTD) of SABR in patients with polymetastatic disease.

METHODS

Up to 48 patients with polymetastatic cancer (> 10 sites) will be enrolled on this phase I, modified 3 + 3 design trial. Eligible patients will have exhausted (or refused) standard systemic therapy options. SABR will be delivered as an escalating number of weekly fractions of 6 Gy, starting at 6 Gy × 2 weekly fractions (dose level 1). The highest dose level (dose level 4) will be 6 Gy × 5 weekly fractions. Feasibility and safety of SABR will be evaluated 6 weeks following treatment using a composite endpoint of successfully completing treatment as well as toxicity outcomes.

DISCUSSION

This study will be the first to explore delivering SABR in patients with polymetastatic disease. SABR will be planned using the guiding principles of: strict adherence to dose constraints, minimization of treatment burden, and minimization of toxicity. As this represents a novel use of radiotherapy, our phase I study will allow for careful selection of the MTD for exploration in future studies.

TRIAL REGISTRATION

This trial was prospectively registered in ClinicalTrials.gov as NCT04530513 on August 28, 2020.

Re-Clustering and Profiling of Digestive System Tumors According to Microenvironment Components

Background

Immunotherapy has become the most promising therapy in digestive system tumors besides conventional chemotherapy and radiotherapy. But only a few patients can benefit from different types of immunotherapies, such as immune checkpoint blockade (ICB). To identify these ICB-susceptible patients, methods are urgently needed to screen and profile subgroups of patients with different responsiveness to ICB.

Methods

This study carried out analysis on patients with digestive system tumors that were obtained from Cancer Genome Atlas (TCGA) cohorts. The analyses were mainly performed using GraphPad Prism 7 and R language.

Results

We have quantified the microenvironmental components of eight digestive system tumor patients in TCGA cohorts and evaluated their clinical value. We re-clustered patients based on their microenvironment composition and divided these patients into six clusters. The differences between these six clusters were profiled, including survival conditions, enriched biological processes, genomic mutations, and microenvironment traits. Cluster 3 was the most immune-related cluster, exhibiting a high infiltration of non-tumor components and poor survival status, along with an inhibitory immune status, and we found that patients with high stromal score indicated a poor response in ICB cohort.

Conclusions

Our research provides a new strategy based on the microenvironment components for the reclassification of digestive system tumors, which could provide guidance for prognosis judgment and treatment response prediction like ICB.