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Background: The aim was to investigate the noise and bias properties of quantitative 177 Lu-SPECT with respect to the number of projection angles, and the number of subsets and iterations in the OS-EM reconstruction, for different total acquisition times., Methods: Experimental SPECT acquisition of six spheres in a NEMA body phantom filled with 177 Lu was performed, using medium-energy collimators and 120 projections with 180 s per projection. Bootstrapping was applied to generate data sets representing acquisitions with 20 to 120 projections for 10 min, 20 min, and 40 min, with 32 noise realizations per setting. Monte Carlo simulations were performed of 177 Lu-DOTA-TATE in an anthropomorphic computer phantom with three tumours (2.8 mL to 40.0 mL). Projections representing 24 h and 168 h post administration were simulated, each with 32 noise realizations. Images were reconstructed using OS-EM with compensation for attenuation, scatter, and distance-dependent resolution. The number of subsets and iterations were varied within a constrained range of the product number of iterations × number of projections ≤ 2400 . Volumes-of-interest were defined following the physical size of the spheres and tumours, the mean activity-concentrations estimated, and the absolute mean relative error and coefficient of variation (CV) over noise realizations calculated. Pareto fronts were established by analysis of CV versus mean relative error., Results: Points at the Pareto fronts with low CV and high mean error resulted from using a low number of subsets, whilst points at the Pareto fronts associated with high CV but low mean error resulted from reconstructions with a high number of subsets. The number of projection angles had limited impact., Conclusions: For accurate estimation of the 177 Lu activity-concentration from SPECT images, the number of projection angles has limited importance, whilst the total acquisition time and the number of subsets and iterations are parameters of importance., (© 2024. The Author(s).)

Peptide receptor radionuclide therapy presents the possibility of tracing and quantifying the uptake of the drug in the body and performing dosimetry, potentially allowing individualization of treatment schemes. However, the details of how neuroendocrine tumors (NETs) respond to different absorbed doses are insufficiently known. Here, we investigated the relationship between tumor-absorbed dose and tumor response in a cohort of patients with NETs treated with [ 177 Lu]Lu-DOTATATE. Methods: This was a retrospective study based on 69 tumors in 32 patients treated within a clinical trial. Dosimetry was performed at each cycle of [ 177 Lu]Lu-DOTATATE, rendering 366 individual absorbed dose assessments. Hybrid planar-SPECT/CT imaging using [ 177 Lu]Lu-DOTATATE was used, including quantitative SPECT reconstruction, voxel-based absorbed dose rate calculation, semiautomatic image segmentation, and partial-volume correction. Changes in tumor volume were used to determine tumor response. The volume for each tumor was manually delineated on consecutive CT scans, giving a total of 712 individual tumor volume assessments. Tumors were stratified according to grade. The relationship between absorbed dose and response was investigated using mixed-effects models and logistic regression. Tumors smaller than 4 cm 3 were excluded. Results: In grade 2 NETs, a clear relationship between absorbed dose and volume reduction was observed. Our observations suggest a 90% probability of partial tumor response for an accumulated tumor-absorbed dose of at least 135 Gy. Conclusion: Our findings are in accordance with previous observations regarding the relationship between tumor shrinkage and absorbed dose. Moreover, our data suggest an absorbed dose threshold for partial response in grade 2 NETs. These observations provide valuable insights for the design of dosimetry-guided peptide receptor radionuclide therapy schemes., (© 2024 by the Society of Nuclear Medicine and Molecular Imaging.)

Background: Although the importance of quantitative SPECT has increased tremendously due to newly developed therapeutic radiopharmaceuticals, there are still no accreditation programs to harmonize SPECT imaging. Work is currently underway to develop an accreditation for quantitative 177 Lu SPECT/CT. The aim of this study is to verify whether the positioning of the spheres within the phantom has an influence on the recovery and thus needs to be considered in SPECT harmonization. In addition, the effects of these recovery coefficients on a potential partial volume correction as well as absorbed-dose estimates are investigated., Methods: Using a low-dose CT of a SPECT/CT acquisition, a computerized version of the NEMA body phantom was created using a semi-automatic threshold-based method. Based on the mass-density map, the detector orbit, and the sphere centers, realistic SPECT acquisitions of all possible 720 sphere configurations of both the PET and the SPECT versions of the NEMA Body Phantom were generated using Monte Carlo simulations. SPECT reconstructions with different numbers of updates were performed without (CASToR) and with resolution modeling (STIR). Recovery coefficients were calculated for all permutations, reconstruction methods, and phantoms, and their dependence on the sphere positioning was investigated. Finally, the simulation-based findings were validated using SPECT/CT acquisitions of six different sphere configurations., Results: Our analysis shows that sphere positioning has a significant impact on the recovery for both of the reconstruction methods and the phantom type. Although resolution modeling resulted in significantly higher recovery, the relative variation in recovery within the 720 permutations was even larger. When examining the extreme values of the recovery, reconstructions without resolution modeling were influenced primarily by the sphere position, while with resolution modeling the volume of the two adjacent spheres had a larger influence. The SPECT measurements confirmed these observations, and the recovery curves showed good overall agreement with the simulated data., Conclusion: Our study shows that sphere positioning has a significant impact on the recovery obtained in NEMA sphere phantom measurements and should therefore be considered in a future SPECT accreditation. Furthermore, the single-measurement method normally performed for PVC should be reconsidered to account for the position dependency., (© 2024. The Author(s).)

With the development of new radiopharmaceutical therapies, quantitative SPECT/CT has progressively emerged as a crucial tool for dosimetry. One major obstacle of SPECT is its poor resolution, which results in blurring of the activity distribution. Especially for small objects, this so-called partial-volume effect limits the accuracy of activity quantification. Numerous methods for partial-volume correction (PVC) have been proposed, but most methods have the disadvantage of assuming a spatially invariant resolution of the imaging system, which does not hold for SPECT. Furthermore, most methods require a segmentation based on anatomic information. Methods: We introduce DL-PVC, a methodology for PVC of 177 Lu SPECT/CT imaging using deep learning (DL). Training was based on a dataset of 10,000 random activity distributions placed in extended cardiac-torso body phantoms. Realistic SPECT acquisitions were created using the SIMIND Monte Carlo simulation program. SPECT reconstructions without and with resolution modeling were performed using the CASToR and STIR reconstruction software, respectively. The pairs of ground-truth activity distributions and simulated SPECT images were used for training various U-Nets. Quantitative analysis of the performance of these U-Nets was based on metrics such as the structural similarity index measure or normalized root-mean-square error, but also on volume activity accuracy, a new metric that describes the fraction of voxels in which the determined activity concentration deviates from the true activity concentration by less than a certain margin. On the basis of this analysis, the optimal parameters for normalization, input size, and network architecture were identified. Results: Our simulation-based analysis revealed that DL-PVC (0.95/7.8%/35.8% for structural similarity index measure/normalized root-mean-square error/volume activity accuracy) outperforms SPECT without PVC (0.89/10.4%/12.1%) and after iterative Yang PVC (0.94/8.6%/15.1%). Additionally, we validated DL-PVC on 177 Lu SPECT/CT measurements of 3-dimensionally printed phantoms of different geometries. Although DL-PVC showed activity recovery similar to that of the iterative Yang method, no segmentation was required. In addition, DL-PVC was able to correct other image artifacts such as Gibbs ringing, making it clearly superior at the voxel level. Conclusion: In this work, we demonstrate the added value of DL-PVC for quantitative 177 Lu SPECT/CT. Our analysis validates the functionality of DL-PVC and paves the way for future deployment on clinical image data., (© 2024 by the Society of Nuclear Medicine and Molecular Imaging.)

Purpose: The aim was to investigate the use of multiple small VOIs for kidney dosimetry in [ 177 Lu]Lu-DOTA-TATE therapy., Method: The study was based on patient and simulated SPECT images in anthropomorphic geometries. Images were reconstructed using two reconstruction programs (local LundaDose and commercial Hermia) using OS-EM with and without resolution recovery (RR). Five small VOIs were placed to determine the average activity concentration (AC) in each kidney. The study consisted of three steps: (i) determination of the number of iterations for AC convergence based on simulated images; (ii) determination of recovery-coefficients (RCs) for 2 mL VOIs using a separate set of simulated images; (iii) assessment of operator variability in AC estimates for simulated and patient images. Five operators placed the VOIs, using for guidance: a) SPECT/CT with RR, b) SPECT/CT without RR, and c) CT only. For simulated images, time-integrated ACs (TIACs) were evaluated. For patient images, estimated ACs were compared with results of a previous method based on whole-kidney VOIs., Results: Eight iterations and ten subsets were sufficient for both programs and reconstruction settings. Mean RCs (mean ± SD) with RR were 1.03 ± 0.02 (LundaDose) and 1.10 ± 0.03 (Hermia), and without RR 0.91 ± 0.03 (LundaDose) and 0.94 ± 0.03 (Hermia). Most stable and accurate estimates of the AC were obtained using five 2-mL VOIs guided by SPECT/CT with RR, applying them to images without RR, and including an explicit RC for recovery correction., Conclusion: The small VOI method based on five 2-mL VOIs was found efficient and sufficiently accurate for kidney dosimetry in [ 177 Lu]Lu-DOTA-TATE therapy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Single-cell technologies have been widely used in biological studies and generated a plethora of single-cell data to be interpreted. Due to the inclusion of the priori metabolic network knowledge as well as gene-protein-reaction associations, genome-scale metabolic models (GEMs) have been a powerful tool to integrate and thereby interpret various omics data mostly from bulk samples. Here, we first review two common ways to leverage bulk omics data with GEMs and then discuss advances on integrative analysis of single-cell omics data with GEMs. We end by presenting our views on current challenges and perspectives in this field., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Genome-scale metabolic models (GEMs) are computational representations that enable mathematical exploration of metabolic behaviors within cellular and environmental constraints. Despite their wide usage in biotechnology, biomedicine and fundamental studies, there are many phenotypes that GEMs are unable to correctly predict. GECKO is a method to improve the predictive power of a GEM by incorporating enzymatic constraints using kinetic and omics data. GECKO has enabled reconstruction of enzyme-constrained metabolic models (ecModels) for diverse organisms, which show better predictive performance than conventional GEMs. In this protocol, we describe how to use the latest version GECKO 3.0; the procedure has five stages: (1) expansion from a starting metabolic model to an ecModel structure, (2) integration of enzyme turnover numbers into the ecModel structure, (3) model tuning, (4) integration of proteomics data into the ecModel and (5) simulation and analysis of ecModels. GECKO 3.0 incorporates deep learning-predicted enzyme kinetics, paving the way for improved metabolic models for virtually any organism and cell line in the absence of experimental data. The time of running the whole protocol is organism dependent, e.g., ~5 h for yeast., (© 2024. Springer Nature Limited.)

Physiologically based pharmacokinetic (PBPK) models offer the ability to simulate and predict the biodistribution of radiopharmaceuticals and have the potential to enable individualised treatment planning in molecular radiotherapy. The objective of this study was to develop and implement a whole-body compartmental PBPK model for peptide receptor radionuclide therapy (PRRT) with [ 177 Lu]Lu-DOTA-TATE in SimBiology to allow for more complex analyses. The correctness of the model implementation was ensured by comparing its outputs, such as the time-integrated activity (TIA), with those of a PBPK model implemented in SAAM II software., Methods: A combined PBPK model for [ 68 Ga]Ga-DOTA-TATE and [ 177 Lu]Lu-DOTA-TATE was developed and implemented in both SAAM II and SimBiology. A retrospective analysis of 12 patients with metastatic neuroendocrine tumours (NETs) was conducted. First, time-activity curves (TACs) and TIAs from the two software were calculated and compared for identical parameter values. Second, pharmacokinetic parameters were fitted to activity concentrations, analysed and compared., Results: The PBPK model implemented in SimBiology produced TIA results comparable to those generated by the model implemented in SAAM II, with a relative deviation of less than 0.5% when using the same input parameters. The relative deviation of the fitted TIAs was less than 5% when model parameter values were fitted to the measured activity concentrations., Conclusion: The proposed PBPK model implemented in SimBiology can be used for dosimetry in radioligand therapy and TIA prediction. Its outputs are similar to those generated by the PBPK model implemented in SAAM II, confirming the correctness of the model implementation in SimBiology., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Associazione Italiana di Fisica Medica e Sanitaria. Published by Elsevier Ltd. All rights reserved.)

The energy metabolism of the brain is poorly understood partly due to the complex morphology of neurons and fluctuations in ATP demand over time. To investigate this, we used metabolic models that estimate enzyme usage per pathway, enzyme utilization over time, and enzyme transportation to evaluate how these parameters and processes affect ATP costs for enzyme synthesis and transportation. Our models show that the total enzyme maintenance energy expenditure of the human body depends on how glycolysis and mitochondrial respiration are distributed both across and within cell types in the brain. We suggest that brain metabolism is optimized to minimize the ATP maintenance cost by distributing the different ATP generation pathways in an advantageous way across cell types and potentially also across synapses within the same cell. Our models support this hypothesis by predicting export of lactate from both neurons and astrocytes during peak ATP demand, reproducing results from experimental measurements reported in the literature. Furthermore, our models provide potential explanation for parts of the astrocyte-neuron lactate shuttle theory, which is recapitulated under some conditions in the brain, while contradicting other aspects of the theory. We conclude that enzyme usage per pathway, enzyme utilization over time, and enzyme transportation are important factors for defining the optimal distribution of ATP production pathways, opening a broad avenue to explore in brain metabolism., Competing Interests: Competing interests statement:The authors declare no competing interest.

The tumor microenvironment is composed of a complex mixture of different cell types interacting under conditions of nutrient deprivation, but the metabolism therein is not fully understood due to difficulties in measuring metabolic fluxes and exchange of metabolites between different cell types in vivo . Genome-scale metabolic modeling enables estimation of such exchange fluxes as well as an opportunity to gain insight into the metabolic behavior of individual cell types. Here, we estimated the availability of nutrients and oxygen within the tumor microenvironment using concentration measurements from blood together with a metabolite diffusion model. In addition, we developed an approach to efficiently apply enzyme usage constraints in a comprehensive metabolic model of human cells. The combined modeling reproduced severe hypoxic conditions and the Warburg effect, and we found that limitations in enzymatic capacity contribute to cancer cells' preferential use of glutamine as a substrate to the citric acid cycle. Furthermore, we investigated the common hypothesis that some stromal cells are exploited by cancer cells to produce metabolites useful for the cancer cells. We identified over 200 potential metabolites that could support collaboration between cancer cells and cancer-associated fibroblasts, but when limiting to metabolites previously identified to participate in such collaboration, no growth advantage was observed. Our work highlights the importance of enzymatic capacity limitations for cell behaviors and exemplifies the utility of enzyme-constrained models for accurate prediction of metabolism in cells and tumor microenvironments., Competing Interests: The authors declare no competing interests., (© 2024 The Authors.)

Background: A 3D printing grid-based method was developed to construct anthropomorphic phantoms with non-uniform activity distributions, to be used for evaluation of quantitative SPECT images. The aims were to characterize the grid-based method and to evaluate its capability to provide realistically shaped phantoms with non-uniform activity distributions., Methods: Characterization of the grid structures was performed by printing grid-filled spheres. Evaluation was performed by micro-CT imaging to investigate the printing accuracy and by studying the modulation contrast ([Formula: see text]) in SPECT images for 177 Lu and 99m Tc as a function of the grid fillable-volume fraction (FVF) determined from weighing. The grid-based technique was applied for the construction of two kidney phantoms and two thyroid phantoms, designed using templates from the XCAT digital phantoms. The kidneys were constructed with a hollow outer container shaped as cortex, an inner grid-based structure representing medulla and a solid section representing pelvis. The thyroids consisted of two lobes printed as grid-based structures, with void hot spots within the lobes. The phantoms were filled with solutions of 177 Lu (kidneys) or 99m Tc (thyroids) and imaged with SPECT. For verification, Monte Carlo simulations of SPECT imaging were performed for activity distributions corresponding to those of the printed phantoms. Measured and simulated SPECT images were compared qualitatively and quantitatively., Results: Micro-CT images showed that printing inaccuracies were mainly uniform across the grid. The relationships between the FVF from weighing and [Formula: see text] were found to be linear (r = 0.9995 and r = 0.9993 for 177 Lu and 99m Tc, respectively). The FVF-deviations from the design were up to 15% for thyroids and 4% for kidneys, mainly related to possibilities of cleaning after printing. Measured and simulated SPECT images of kidneys and thyroids exhibited similar activity distributions and quantitative comparisons agreed well, thus verifying the grid-based method., Conclusions: We find the grid-based technique useful for the provision of 3D printed, realistically shaped, phantoms with non-uniform activity distributions, which can be used for evaluation of different quantitative methods in SPECT imaging., (© 2024. The Author(s).)

Introduction: The activity meter is used to determine the activity of delivered radiopharmaceuticals, administered activity to patients and reference activity when gamma-cameras are calibrated prior to imaged-based dosimetry. The aim is to describe a procedure for cross-calibration of activity meters at different clinical sites, and report on 177 Lu activity results when using factory-set calibration factors compared to when calibration is performed with traceability to a primary standard., Methods: Thirty activity meters placed at seven hospitals in Norway and Sweden from four manufacturers: Capintec, Commecer, NuviaTech and Veenstra were included. A stock solution with 177 Lu was prepared at the local sites and measured in each activity meter with factory settings. The solution was shipped to the reference site at Lund University for measurements in a secondary standard activity meter. Deviations between local and reference activity measurements were determined for three geometries: 25-mL vial, 10-mL syringe and 1-mL syringe., Results: The median of the deviations was 6.4 % for the 25 mL vial, 5.9 % for the 10 mL syringe and 6.8 % for the 1 mL syringe. The median of the deviations for the 25 mL vial, was 1.5 % for activity meters from Capintec, 7.0 % for Comecer, 11.0 % for NuviaTech and 2.4 % for Veenstra. The majority of the deviations were positive and the maximum deviation was 14.5 %., Conclusion: The activity of 177 Lu measured in an activity meter with factory-set dial settings may yield deviations up to 14.5%, compared to activities measured with traceability to a primary standard. This would imply an undertreatment of patients., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

Molecular radiotherapy is rapidly expanding, and new radiotherapeutics are emerging. The majority of treatments is still performed using empirical fixed activities and not tailored for individual patients. Molecular radiotherapy dosimetry is often seen as a promising candidate that would allow personalisation of treatments as outcome should ultimately depend on the absorbed doses delivered and not the activities administered. The field of molecular radiotherapy dosimetry has made considerable progress towards the feasibility of routine clinical dosimetry with reasonably accurate absorbed-dose estimates for a range of molecular radiotherapy dosimetry applications. A range of challenges remain with respect to the accurate quantification, assessment of time-integrated activity and absorbed dose estimation. In this review, we summarise a range of technological and methodological advancements, mainly focussed on beta-emitting molecular radiotherapeutics, that aim to improve molecular radiotherapy dosimetry to achieve accurate, reproducible, and streamlined dosimetry. We describe how these new technologies can potentially improve the often time-consuming considered process of dosimetry and provide suggestions as to what further developments might be required., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Associazione Italiana di Fisica Medica e Sanitaria. Published by Elsevier Ltd. All rights reserved.)

Background: Dosimetry in radionuclide therapy often requires the calculation of average absorbed doses within and between spatial regions, for example, for voxel-based dosimetry methods, for paired organs, or across multiple tumors. Formation of such averages can be made in different ways, starting from different definitions., Purpose: The aim of this study is to formally specify different averaging strategies for absorbed doses, and to compare their results when applied to absorbed dose distributions that are non-uniform within and between regions., Methods: For averaging within regions, two definitions of the average absorbed dose are considered: the simple average over the region (the region average) and the average when weighting by the mass density (density-weighted region average). The latter is shown to follow from the definition of mean absorbed dose according to the ICRU, and to be consistent with the MIRD formalism. For averaging between different spatial regions, three definitions follow: the volume-weighted, the mass-weighted, and the unweighted average. With respect to characterizing non-uniformity, the different average definitions lead to the use of dose-volume histograms (DVHs) (region average), dose-mass histograms (DMHs) (density-weighted region average), and unweighted histograms (unweighted average). Average absorbed doses are calculated for three worked examples, starting from the different definitions. The first, schematic, example concerns the calculation of the average absorbed dose between two regions with different volumes or mass densities. The second, stylized, example concerns voxel-based dosimetry, for which the average absorbed-dose rate within a region is calculated. The geometries studied include three 177 Lu-filled voxelized spheres, where the sphere masses are held constant while the material compositions, densities, and volumes are varied. For comparison, the mean absorbed-dose rates obtained using unit-density sphere S-values are also included. The third example concerns SPECT/CT-based tumor dosimetry for five patients undergoing therapy with 177 Lu-PSMA and six patients undergoing therapy with 177 Lu-DOTA-TATE, for which the average absorbed-dose rates across multiple tumors are calculated. For the second and third examples, analyses also include representations by histograms., Results: Example 1 shows that the average absorbed doses, calculated using different definitions, can differ considerably if the masses and absorbed doses for two regions are markedly different. From example 2 it is seen that the density-weighted region average is stable under different activity and density distributions and is also in line with results using S-values. In contrast, the region average varies as function of the activity distribution. In example 3, the absorbed dose rates for individual tumors differ by (1.1 ± 4.3)% and (-0.1 ± 0.4)% with maximum deviations of +34.4% and -1.4% for 177 Lu-PSMA and 177 Lu-DOTA-TATE, respectively, when calculated as region averages or density-weighted region averages, with largest deviations obtained when the density is non-uniform. The average absorbed doses calculated across all tumors are similar when comparing mass-weighted and volume-weighted averages but these differ substantially from unweighted averages., Conclusion: Different strategies for averaging of absorbed doses within and between regions can lead to substantially different absorbed-dose estimates. At reporting of radionuclide therapy dosimetry, it is important to specify the averaging strategy applied., (© 2023 The Authors. Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.)

One example of a PET exam that suffers from noise problems is [ 68 Ga]Ga-DOTA-TOC, where patients are generally administered between 100 and 200 MBq [ 68 Ga]Ga-DOTA-TOC, irrespective of size. However, a fixed activity can result in low signal-to-noise ratios (SNRs) in larger patients. This study aimed to evaluate the impact on image quality with respect to injected activity and patient habitus through Monte Carlo (MC) simulation. Eight anthropomorphic computer phantoms with body mass indices (BMIs) between 19 kg/m 2 and 38 kg/m 2 and tumours distributed in the liver were simulated using the MC software Gate v8.2 with an activity distribution defined according to [ 68 Ga]Ga-DOTA-TOC standardised uptake values. Three activity-administration protocols were simulated: (i) with a fixed activity of 100 MBq, (ii) with the activity scaled by 2 MBq/kg, and (iii) with the activity scaled by a body size-dependent power-function based on the SNR obtained with (ii). BMI, weight, body surface area, and abdominal circumference were evaluated body size parameters. Images were reconstructed with the CASToR software and evaluated for background SNR and lesion contrast-to-noise ratio (CNR). Large SNR variabilities were obtained with protocols (i) and (ii), while (iii) generated good consistency. Several tumours failed to reach a CNR of 5 for large phantoms with protocol (i), but the CNR was generally improved by (ii) and (iii). An activity scaled by patient habitus generate better image quality consistency, which increases the likelihood that patients receive a similar standard of care., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

Objective. The aim was to theoretically and experimentally investigate recovery in SPECT images with objects of different shapes. Furthermore, the accuracy of volume estimation by thresholding was studied for those shapes. Approach. Nine spheres, nine oblate spheroids, and nine prolate spheroids phantom inserts were used, of which the six smaller spheres were part of the NEMA IEC body phantom and the rest of the inserts were 3D-printed. The inserts were filled with 99m Tc and 177 Lu. When filled with 99m Tc, SPECT images were acquired in a Siemens Symbia Intevo Bold gamma camera and when filled with 177 Lu in a General Electric NM/CT 870 DR gamma camera. The signal rate per activity (SRPA) was determined for all inserts and represented as a function of the volume-to-surface ratio and of the volume-equivalent radius using VOIs defined according to the sphere dimensions and VOIs defined using thresholding. Experimental values were compared with theoretical curves obtained analytically (spheres) or numerically (spheroids), starting from the convolution of a source distribution with a point-spread function. Validation of the activity estimation strategy was performed using four 3D-printed ellipsoids. Lastly, the threshold values necessary to determine the volume of each insert were obtained. Main results. Results showed that SRPA values for the oblate spheroids diverted from the other inserts, when SRPA were represented as a function of the volume-equivalent radius. However, SRPA values for all inserts followed a similar behaviour when represented as a function of the volume-to-surface ratio. Results for ellipsoids were in agreement with those results. For the three types of inserts the volume could be accurately estimated using a threshold method for volumes larger than 25 ml. Significance. Determination of SRPA independently of lesion or organ shape should decrease uncertainties in estimated activities and thereby, in the long term, be beneficial to patient care., (© 2023 Institute of Physics and Engineering in Medicine.)

Single-cell RNA sequencing combined with genome-scale metabolic models (GEMs) has the potential to unravel the differences in metabolism across both cell types and cell states but requires new computational methods. Here, we present a method for generating cell-type-specific genome-scale models from clusters of single-cell RNA-Seq profiles. Specifically, we developed a method to estimate the minimum number of cells required to pool to obtain stable models, a bootstrapping strategy for estimating statistical inference, and a faster version of the task-driven integrative network inference for tissues algorithm for generating context-specific GEMs. In addition, we evaluated the effect of different RNA-Seq normalization methods on model topology and differences in models generated from single-cell and bulk RNA-Seq data. We applied our methods on data from mouse cortex neurons and cells from the tumor microenvironment of lung cancer and in both cases found that almost every cell subtype had a unique metabolic profile. In addition, our approach was able to detect cancer-associated metabolic differences between cancer cells and healthy cells, showcasing its utility. We also contextualized models from 202 single-cell clusters across 19 human organs using data from Human Protein Atlas and made these available in the web portal Metabolic Atlas, thereby providing a valuable resource to the scientific community. With the ever-increasing availability of single-cell RNA-Seq datasets and continuously improved GEMs, their combination holds promise to become an important approach in the study of human metabolism.

Hydroxylated polybrominated diphenyl ethers (OH-PBDEs) are formed by metabolism from the flame retardants polybrominated diphenyl ethers (PBDEs). In the aquatic environment, they are also produced naturally. OH-PBDEs are known for their potential to disrupt energy metabolism, the endocrine system, and the nervous system. This is the first study focusing on the effects of OH-PBDEs at the metabolite level in vivo. The aim of the current study was to investigate the metabolic effects of exposure to OH-PBDEs using metabolomics, and to identify potential biomarker(s) for energy disruption of OH-PBDEs. Zebrafish (Danio rerio) embryos were exposed to two different concentrations of 6-OH-BDE47 and 6-OH-BDE85 and a mixture of these two compounds. In total, 342 metabolites were annotated and 79 metabolites were affected in at least one exposure. Several affected metabolites, e.g. succinic acid, glutamic acid, glutamine, tyrosine, tryptophan, adenine, and several fatty acids, could be connected to known toxic mechanisms of OH-PBDEs. Several phospholipids were strongly up-regulated with up to a six-fold increase after exposure to 6-OH-BDE47, a scarcely described effect of OH-PBDEs. Based on the observed metabolic effects, a possible connection between disruption of the energy metabolism, neurotoxicity and potential immunotoxicity of OH-PBDEs was suggested. Single compound exposures to 6-OH-BDE47 and 6-OH-BDE85 showed little overlap in the affected metabolites. This shows that compounds of similar chemical structure can induce different metabolic effects, possibly relating to their different toxic mechanisms. There were inter-concentration differences in the metabolic profiles, indicating that the metabolic effects were concentration dependent. After exposure to the mixture of 6-OH-BDE47 and 6-OH-BDE85, a new metabolic profile distinct from the profiles obtained from the single compounds was observed. Succinic acid was up-regulated at the highest, but still environmentally relevant, concentration of 6-OH-BDE47, 6-OH-BDE85, and the mixture. Therefore, succinic acid is suggested as a potential biomarker for energy disruption of OH-PBDEs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Somatostatin receptor 68 Ga PET imaging is standard for evaluation of a patient's suitability for 177 Lu peptide receptor radionuclide therapy of neuroendocrine tumours (NETs). The 68 Ga PET serves to ensure sufficient somatostatin receptor expression, commonly evaluated qualitatively. The aim of this study is to investigate the quantitative relationships between uptake in 68 Ga PET and absorbed doses in 177 Lu therapy., Method: Eighteen patients underwent [ 68 Ga]Ga-DOTA-TATE PET imaging within 20 weeks prior to their first cycle of [ 177 Lu]Lu-DOTA-TATE. Absorbed doses for therapy were estimated for tumours, kidney, spleen, and normal liver parenchyma using a hybrid SPECT/CT-planar method. Gallium-68 activity concentrations were retrieved from PET images and also used to calculate SUVs and normalized SUVs, using blood and tissue for normalization. The 68 Ga activity concentrations per injected activity, SUVs, and normalized SUVs were compared with 177 Lu activity concentrations 1 d post-injection and 177 Lu absorbed doses. For tumours, for which there was a variable number per patient, both inter- and intra-patient correlations were analysed. Furthermore, the prediction of 177 Lu tumour absorbed doses based on a combination of tumour-specific 68 Ga activity concentrations and group-based estimates of the effective half-lives for grade 1 and 2 NETs was explored., Results: For normal organs, only spleen showed a significant correlation between the 68 Ga activity concentration and 177 Lu absorbed dose (r = 0.6). For tumours, significant, but moderate, correlations were obtained, with respect to both inter-patient (r = 0.7) and intra-patient (r = 0.45) analyses. The correlations to absorbed doses did not improve when using 68 Ga SUVs or normalized SUVs. The relationship between activity uptakes for 68 Ga PET and 177 Lu SPECT was stronger, with correlation coefficients r = 0.8 for both inter- and intra-patient analyses. The 177 Lu absorbed dose to tumour could be predicted from the 68 Ga activity concentrations with a 95% coverage interval of - 65% to 248%., Conclusions: On a group level, a high uptake of [ 68 Ga]Ga-DOTA-TATE is associated with high absorbed doses at 177 Lu-DOTA-TATE therapy, but the relationship has a limited potential with respect to individual absorbed dose planning. Using SUV or SUV normalized to reference tissues do not improve correlations compared with using activity concentration per injected activity., (© 2022. The Author(s).)

Background: In recent years, a lot of effort has been put in the enhancement of medical imaging using artificial intelligence. However, limited patient data in combination with the unavailability of a ground truth often pose a challenge to a systematic validation of such methodologies. The goal of this work was to investigate a recently proposed method for an artificial intelligence-based generation of synthetic SPECT projections, for acceleration of the image acquisition process based on a large dataset of realistic SPECT simulations., Methods: A database of 10,000 SPECT projection datasets of heterogeneous activity distributions of randomly placed random shapes was simulated for a clinical SPECT/CT system using the SIMIND Monte Carlo program. Synthetic projections at fixed angular increments from a set of input projections at evenly distributed angles were generated by different u-shaped convolutional neural networks (u-nets). These u-nets differed in noise realization used for the training data, number of input projections, projection angle increment, and number of training/validation datasets. Synthetic projections were generated for 500 test projection datasets for each u-net, and a quantitative analysis was performed using statistical hypothesis tests based on structural similarity index measure and normalized root-mean-squared error. Additional simulations with varying detector orbits were performed on a subset of the dataset to study the effect of the detector orbit on the performance of the methodology. For verification of the results, the u-nets were applied to Jaszczak and NEMA physical phantom data obtained on a clinical SPECT/CT system., Results: No statistically significant differences were observed between u-nets trained with different noise realizations. In contrast, a statistically significant deterioration was found for training with a small subset (400 datasets) of the 10,000 simulated projection datasets in comparison with using a large subset (9500 datasets) for training. A good agreement between synthetic (i.e., u-net generated) and simulated projections before adding noise demonstrates a denoising effect. Finally, the physical phantom measurements show that our findings also apply for projections measured on a clinical SPECT/CT system., Conclusion: Our study shows the large potential of u-nets for accelerating SPECT/CT imaging. In addition, our analysis numerically reveals a denoising effect when generating synthetic projections with a u-net. Clinically interesting, the methodology has proven robust against camera orbit deviations in a clinically realistic range. Lastly, we found that a small number of training samples (e.g., ~ 400 datasets) may not be sufficient for reliable generalization of the u-net., (© 2022. The Author(s).)

The study aimed to create a pipeline from Monte Carlo simulated projections of a Gate PET system to reconstructed images. The PET system was modelled after the GE Discovery MI (DMI) PET/CT, and the simulated projections were reconstructed with the stand-alone reconstruction software CASToR. Attenuation correction, normalisation calibration, random estimation, and scatter estimation for the simulations were computed with in-house programs. The pipeline was compared in both projection and image space with data acquired on a clinical DMI and reconstructed with GE's off-line PET reconstruction software (PET Toolbox) and CASToR. The simulated and measured data were compared for the number of prompt coincidences, scatter fraction, contrast recovery coefficient (CRC), signal-to-noise ratio (SNR), background variability, residual lung error, and image profiles. A slight discrepancy was noted in the projection space, but good agreements were generally achieved in image space between simulated and measured data. The CRC was found to be 81 % for Gate - CASToR, 84 % for GE - CASToR, and 84 % for GE - PET Toolbox for the largest sphere of the NEMA image quality (IQ) phantom, and the SNR was found to be 98 for Gate - CASToR, 91 for GE - CASToR, and 93 for GE - PET Toolbox. Profiles drawn over the spheres for the NEMA IQ phantom and the Data Spectrum (DS) phantom show a good match between measurement and simulation. The results indicate feasibility to utilise the pipeline as a tool for off-line simulation-based studies. A complete pipeline introduces possibilities to study the impact of single parameters in the whole chain from simulation to reconstructed images., Competing Interests: The authors declare no conflict of interest., (© 2022 The Authors.)

Tumor dosimetry was performed for 177 Lu-DOTATATE with the aims of better understanding the range and variation of the tumor-absorbed doses (ADs), how different dosimetric quantities evolve over the treatment cycles, and whether this evolution differs depending on the tumor grade. Such information is important for radiobiologic interpretation and may inform the design of alternative administration schemes. Methods: The data came from 41 patients with neuroendocrine tumors (NETs) of grade 1 ( n = 23) or 2 ( n = 18) who had received between 2 and 9 treatment cycles. Dosimetry was performed for 182 individual lesions, giving a total of 880 individual AD assessments across all cycles. Hybrid planar-SPECT/CT imaging was used, including quantitative SPECT reconstruction, voxel-based absorbed-dose-rate calculation, semiautomatic image segmentation, and partial-volume correction. Linear mixed-effect models were used to analyze changes in tumor ADs over cycles, absorbed-dose rates and activity concentrations on day 1, effective half-times, and tumor volumes. Tumors smaller than 8 cm 3 were excluded from analyses. Results: Tumor ADs ranged between 2 and 77 Gy per cycle. On average, the AD decreased over the cycles, with significantly different rates ( P < 0.05) of 6% and 14% per cycle for grade 1 and 2 NETs, respectively. The absorbed-dose rates and activity concentrations on day 1 decreased by similar amounts. The effective half-times were less variable but shorter for grade 2 than for grade 1 ( P < 0.001). For grade 2 NETs, the tumor volumes decreased, with a similar tendency in grade 1. Conclusion: The tumor AD, absorbed-dose rate, and activity uptake decrease, in parallel with tumor volumes, between 177 Lu-DOTATATE treatment cycles, particularly for grade 2 NETs. The effective half-times vary less but are lower for grade 2 than grade 1 NETs. These results may indicate the development of radiation-induced fibrosis and could have implications for the design of future treatment and dosimetry protocols., (© 2022 by the Society of Nuclear Medicine and Molecular Imaging.)

Objective . This study considers the error distributions for time-integrated activity (TIA) of single-time-point (STP) methods for patient-specific dosimetry in radionuclide therapy. Approach . The general case with the same pharmaceutical labelled with different radionuclides for imaging and therapy are considered for a mono-exponential time-activity curve. Two methods for STP dosimetry, both based on the combination of one activity estimate with the population-mean effective decay constant, are investigated. The cumulative distribution functions (CDFs) and the probability density functions for the two methods are analytically derived for arbitrary distributions of the biological decay constant. The CDFs are used for determining 95% coverage intervals of the relative errors for different combinations of imaging time points, physical decay constants, and relative standard deviations of the biological decay constant. Two examples, in the form of kidney dosimetry in [ 177 Lu]Lu-DOTA-TATE therapy and tumour dosimetry for Na[ 131 I]I therapy for thyroid cancer with dosimetry based on imaging of Na[ 124 I]I, are also studied in more detail with analysis of the sensitivity with respect to errors in the mean biological decay constant and to higher moments of the distribution. Main results . The distributions of the relative errors are negatively skewed, potentially leading to the situation that some TIA estimates are highly underestimated even if the majority of estimates are close to the true value. Significance . The main limitation of the studied STP dosimetry methods is the risk of large underestimations of the TIA., (Creative Commons Attribution license.)

Standardisation of genetic parts has become a topic of increasing interest over the last decades. The promise of simplifying molecular cloning procedures, while at the same time making them more predictable and reproducible has led to the design of several biological standards, one of which is modular cloning (MoClo). The Yeast MoClo toolkit provides a large library of characterised genetic parts combined with a comprehensive and flexible assembly strategy. Here we aimed to (1) simplify the adoption of the standard by providing a simple design tool for including new parts in the MoClo library, (2) characterise the toolkit further by demonstrating the impact of a BglII site in promoter parts on protein expression, and (3) expand the toolkit to enable efficient construction of gRNA arrays, marker-less integration cassettes and combinatorial libraries. These additions make the toolkit more applicable for common engineering tasks and will further promote its adoption in the yeast biological engineering community.

Genome-scale metabolic models (GEMs) are used extensively for analysis of mechanisms underlying human diseases and metabolic malfunctions. However, the lack of comprehensive and high-quality GEMs for model organisms restricts translational utilization of omics data accumulating from the use of various disease models. Here we present a unified platform of GEMs that covers five major model animals, including Mouse1 ( Mus musculus ), Rat1 ( Rattus norvegicus ), Zebrafish1 ( Danio rerio ), Fruitfly1 ( Drosophila melanogaster ), and Worm1 ( Caenorhabditis elegans ). These GEMs represent the most comprehensive coverage of the metabolic network by considering both orthology-based pathways and species-specific reactions. All GEMs can be interactively queried via the accompanying web portal Metabolic Atlas. Specifically, through integrative analysis of Mouse1 with RNA-sequencing data from brain tissues of transgenic mice we identified a coordinated up-regulation of lysosomal GM2 ganglioside and peptide degradation pathways which appears to be a signature metabolic alteration in Alzheimer's disease (AD) mouse models with a phenotype of amyloid precursor protein overexpression. This metabolic shift was further validated with proteomics data from transgenic mice and cerebrospinal fluid samples from human patients. The elevated lysosomal enzymes thus hold potential to be used as a biomarker for early diagnosis of AD. Taken together, we foresee that this evolving open-source platform will serve as an important resource to facilitate the development of systems medicines and translational biomedical applications., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)

Over the last two decades, the occurrence of hydroxylated polybrominated diphenyl ethers (OH-PBDEs) has been observed to be nearly ubiquitous among Baltic Sea filamentous macroalgae. High concentrations are continuously recorded among red, green, and brown filamentous algae. Several of these algae species are ephemeral, and when large parts of the colonies decay at the end of their lifecycles, the OH-PBDEs are expected to largely partition to the sediment. In this study, the fate of OH-PBDEs in Baltic Sea sediment was investigated, with focus on the effect of reductive debromination. During chemical debromination, it was observed that the half-life could differ with as much as two orders of magnitude between a pentabrominated and a tetrabrominated congener. Using collected Baltic Sea sediment, it was further observed that the half-life of spiked pentabrominated OH-PBDEs spanned from a few days up to a few weeks in room temperature. At 4 °C, it took 6 months to achieve a 50% decrease in concentration of the fasted degrading congener. Clear differences in selectivity between chemical debromination and debromination in sediment were also observed when studying the major reaction products. Baltic Sea sediment seems to have a good capacity for reducing naturally produced OH-PBDEs.

Background: Recently, 177 Lu-dotatate therapy for neuroendocrine tumours has received regulatory approval. Dosimetry can be used to optimize treatment on an individual basis, but there is no international consensus as to how it should be done. The aim of this study is to determine a feasible and accurate dosimetry method to guide individualized peptide receptor radionuclide therapy (PRRT) for patients with neuroendocrine tumours. As part of a clinical trial on 177 Lu-dotatate therapy, renal dosimetry was performed for all patients in each treatment cycle, using a hybrid planar-SPECT/CT method. In the present study, we use the image data acquired from 22 patients and 119 cycles and define a set of alternative treatment planning strategies, each representing a simplification in terms of image acquisition and dosimetric calculations. The results from the simplified strategies are compared to the results from the protocol-prescribed hybrid planar-SPECT/CT-based method by analysing differences both in per-cycle and total cumulative absorbed dose (AD) analyses., Results: In general, the SPECT-based methods gave results that were largely consistent with the protocol-specified hybrid method, both in the per-cycle and cumulative AD analyses. Notably, performing one SPECT/CT per cycle at 96 h yielded ADs that were very similar to the protocol method. The methods using planar dosimetry resulted in larger variations, as expected, while giving 4 cycles to all patients resulted in the largest inter-individual differences in cumulative AD., Conclusions: Performing one SPECT/CT at 96 h in every treatment cycle gives sufficiently reliable dosimetric results to base individualized treatment planning on, with a reasonable demand on resources.

Background: Dosimetry in radionuclide therapy has the potential to allow for a treatment tailored to the individual patient. One therapeutic radiopharmaceutical where patient-specific dosimetry is feasible is 177 Lu-DOTATATE, used for the treatment of neuroendocrine tumours. The emission of gamma photons by 177 Lu allows for imaging with SPECT (single photon emission computed tomography). One important step for dosimetry using this imaging technique is the SPECT image segmentation, which needs to be robust and accurate for the estimated quantities to be reliable. This work investigates different methods for automatic tumour delineation in 177 Lu-DOTATATE SPECT images. Three segmentation methods are considered: a fixed 42% threshold (FT), the Otsu method (OM) and a method based on Fourier surfaces (FS). Effects of including resolution compensation in the iterative SPECT image reconstruction are also studied. Evaluation is performed based on Monte Carlo-simulated SPECT images from 24 h and 336 h post injection (p.i.), for determination of the volume, activity concentration and dice similarity coefficient. In addition, patient data are used to investigate the correspondence of tumour volumes when delineated in SPECT or morphological CT or MR images. Patient data are also used to examine the sensitivity to the operator-dependent initialization., Results: For simulated images from 24 h p.i. reconstructed without resolution compensation, a volume and activity-concentration root-mean-square error below 15% is typically obtained for tumours above approximately 10 cm 3 when using OM or FS, while FT performs considerably worse. When including resolution compensation, the tumour volume becomes underestimated and the activity concentration overestimated. The FS method appears to be robust to noise, as seen for the 336 h images. The differences between the tumour volumes estimated from the SPECT images and the volumes estimated from morphological images are generally larger than the discrepancies seen for the simulated data sets., Conclusions: Segmentation results are encouraging for future dosimetry of tumours with volumes above approximately 10 cm 3 . Using resolution compensation in the reconstruction may have a negative effect on volume estimation.

In this work, the biologically effective dose (BED) is investigated for fractionated molecular radiotherapy (MRT). A formula for the Lea-Catcheside G-factor is derived which takes the possibility of combinations of sub-lethal damage due to radiation from different administrations of activity into account. In contrast to the previous formula, the new G-factor has an explicit dependence on the time interval between administrations. The BED of tumour and liver is analysed in MRT of neuroblastoma with (131)I-mIBG, following a common two-administration protocol with a mass-based activity prescription. A BED analysis is also made for modified schedules, when due to local regulations there is a maximum permitted activity for each administration. Modifications include both the simplistic approach of delivering this maximum permitted activity in each of the two administrations, and also the introduction of additional administrations while maintaining the protocol-prescribed total activity. For the cases studied with additional (i.e. more than two) administrations, BED of tumour and liver decreases at most 12% and 29%, respectively. The decrease in BED of the tumour is however modest compared to the two-administration schedule using the maximum permitted activity, where the decrease compared to the original schedule is 47%.

A computer model of a patient-specific clinical (177)Lu-DOTATATE therapy dosimetry system is constructed and used for investigating the variability of renal absorbed dose and biologically effective dose (BED) estimates. As patient models, three anthropomorphic computer phantoms coupled to a pharmacokinetic model of (177)Lu-DOTATATE are used. Aspects included in the dosimetry-process model are the gamma-camera calibration via measurement of the system sensitivity, selection of imaging time points, generation of mass-density maps from CT, SPECT imaging, volume-of-interest delineation, calculation of absorbed-dose rate via a combination of local energy deposition for electrons and Monte Carlo simulations of photons, curve fitting and integration to absorbed dose and BED. By introducing variabilities in these steps the combined uncertainty in the output quantity is determined. The importance of different sources of uncertainty is assessed by observing the decrease in standard deviation when removing a particular source. The obtained absorbed dose and BED standard deviations are approximately 6% and slightly higher if considering the root mean square error. The most important sources of variability are the compensation for partial volume effects via a recovery coefficient and the gamma-camera calibration via the system sensitivity.

Patient-specific image-based dosimetry is considered to be a useful tool to limit toxicity associated with peptide receptor radionuclide therapy (PRRT). To facilitate the establishment and reliability of absorbed-dose response relationships, it is essential to assess the accuracy of dosimetry in clinically realistic scenarios. To this end, we developed pharmacokinetic digital phantoms corresponding to patients treated with (177)Lu-DOTATATE. Three individual voxel phantoms from the XCAT population were generated and assigned a dynamic activity distribution based on a compartment model for (177)Lu-DOTATATE, designed specifically for this purpose. The compartment model was fitted to time-activity data from 10 patients, primarily acquired using quantitative scintillation camera imaging. S values for all phantom source-target combinations were calculated based on Monte-Carlo simulations. Combining the S values and time-activity curves, reference values of the absorbed dose to the phantom kidneys, liver, spleen, tumours and whole-body were calculated. The phantoms were used in a virtual dosimetry study, using Monte-Carlo simulated gamma-camera images and conventional methods for absorbed-dose calculations. The characteristics of the SPECT and WB planar images were found to well represent those of real patient images, capturing the difficulties present in image-based dosimetry. The phantoms are expected to be useful for further studies and optimisation of clinical dosimetry in (177)Lu PRRT.