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The female population has a lifetime overall risk of 43% for developing cancer, which is approximately I 2084 i times higher than the excess risk for our female patients [[3]]. Bladder voiding influenced the risk, in comparison to the patient group without bladder voiding during the examination, the mean excess lifetime risk values of the patient group with voiding was 58% lower." In Germany, the male population showed a lifetime overall risk of 50% for developing cancer [[3]], which is about I 3440 i times higher than the mean excess risk for our male patients. [Extracted from the article]

Background: Renal scans are among the most frequent exams performed on infants and toddlers. Due to the young age, this patient group can be classified as a high-risk group with a higher probability for developing stochastic radiation effects compared to adults. As there are only limited data on biokinetics and dosimetry in this patient group, the aim of this study was to reassess the dosimetry and the associated radiation risk for infants undergoing 99mTc-MAG3 renal scans based on a retrospective analysis of existing patient data.Consecutive data were collected from 20 patients younger than 20 months (14 males; 6 females) with normal renal function undergoing 99mTc-MAG3 scans. To estimate the patient-specific organ activity, a retrospective calibration was performed based on a set of two 3D-printed infant kidneys filled with known activities. Both phantoms were scanned at different positions along the anteroposterior axis inside a water phantom, providing depth- and size-dependent attenuation correction factors for planar imaging. Time-activity curves were determined by drawing kidney, bladder, and whole-body regions-of-interest for each patient, and subsequently applying the calibration factor for conversion of counts to activity. Patient-specific time-integrated activity coefficients were obtained by integrating the organ-specific time-activity curves. Absorbed and effective dose coefficients for each patient were assessed with OLINDA/EXM for the provided newborn and 1-year-old model. The risk estimation was performed individually for each of the 20 patients with the NCI Radiation Risk Assessment Tool.Results: The mean age of the patients was 7.0 ± 4.5 months, with a weight between 5 and 12 kg and a body size between 60 and 89 cm. The injected activities ranged from 12 to 24 MBq of 99mTc-MAG3. The patients’ organ-specific mean absorbed dose coefficients were 0.04 ± 0.03 mGy/MBq for the kidneys and 0.27 ± 0.24 mGy/MBq for the bladder. The mean effective dose coefficient was 0.02 ± 0.02 mSv/MBq. Based on the dosimetry results, an evaluation of the excess lifetime risk for the development of radiation-induced cancer showed that the group of newborns has a risk of 16.8 per 100,000 persons, which is about 12% higher in comparison with the 1-year-old group with 14.7 per 100,000 persons (all values are given as mean plus/minus one standard deviation except otherwise specified).Conclusion: In this study, we retrospectively derived new data on biokinetics and dosimetry for infants with normal kidney function after undergoing renal scans with 99mTc-MAG3. In addition, we analyzed the associated age- and gender-specific excess lifetime risk due to ionizing radiation. The radiation-associated stochastic risk increases with the organ doses, taking age- and gender-specific influences into account. Overall, the lifetime radiation risk associated with the 99mTc-MAG3 scans is very low in comparison to the general population risk for developing cancer. [ABSTRACT FROM AUTHOR]

Radioligand therapy is an emerging and effective treatment option for various types of malignancies, but may be intricately linked to hematological side effects such as anemia, lymphopenia or thrombocytopenia. The safety and efficacy of novel theranostic agents, targeting increasingly complex targets, can be well served by comprehensive dosimetry. However, optimization in patient management and patient selection based on risk-factors predicting adverse events and built upon reliable dose-response relations is still an open demand. In this context, artificial intelligence methods, especially machine learning and deep learning algorithms, may play a crucial role. This review provides an overview of upcoming opportunities for integrating artificial intelligence methods into the field of dosimetry in nuclear medicine by improving bone marrow and blood dosimetry accuracy, enabling early identification of potential hematological risk-factors, and allowing for adaptive treatment planning. It will further exemplify inspirational success stories from neighboring disciplines that may be translated to nuclear medicine practices, and will provide conceptual suggestions for future directions. In the future, we expect artificial intelligence-assisted (predictive) dosimetry combined with clinical parameters to pave the way towards truly personalized theranostics in radioligand therapy., Competing Interests: Declaration of competing interest R.S. received research support from Boehringer Ingelheim Fonds and Else Kröner-Fresenius-Stiftung. K.H. reports personal fees from Bayer, personal fees and other from Sofie Biosciences, personal fees from SIRTEX, non-financial support from ABX, personal fees from Adacap, personal fees from Curium, personal fees from Endocyte, grants and personal fees from BTG, personal fees from IPSEN, personal fees from Siemens Healthineers, personal fees from GE Healthcare, personal fees from Amgen, personal fees from Novartis, personal fees from ymabs, personal fees from Aktis Oncology, personal fees from Theragnostics, personal fees from Pharma15, personal fees from Debiopharm, personal fees from AstraZeneca, and personal fees from Janssen outside of the submitted work. D.K. reports funding from the German Research Association (DFG), research funding from Pfizer and speaker honoraria from Novartis and Pfizer outside of the submitted work. The other authors have nothing to declare., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

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.)

For dosimetry of radiopharmaceutical therapies, it is essential to determine the volume of relevant structures exposed to therapeutic radiation. For many radiopharmaceuticals, the kidneys represent an important organ-at-risk. To reduce the time required for kidney segmentation, which is often still performed manually, numerous approaches have been presented in recent years to apply deep learning-based methods for CT-based automated segmentation. While the automatic segmentation methods presented so far have been based solely on CT information, the aim of this work is to examine the added value of incorporating PSMA-PET data in the automatic kidney segmentation., Methods: A total of 108 PET/CT examinations (53 [ 68 Ga]Ga-PSMA-I&T and 55 [ 18 F]F-PSMA-1007 examinations) were grouped to create a reference data set of manual segmentations of the kidney. These segmentations were performed by a human examiner. For each subject, two segmentations were carried out: one CT-based (detailed) segmentation and one PET-based (coarser) segmentation. Five different u-net based approaches were applied to the data set to perform an automated segmentation of the kidney: CT images only, PET images only (coarse segmentation), a combination of CT and PET images, a combination of CT images and a PET-based coarse mask, and a CT image, which had been pre-segmented using a PET-based coarse mask. A quantitative assessment of these approaches was performed based on a test data set of 20 patients, including Dice score, volume deviation and average Hausdorff distance between automated and manual segmentations. Additionally, a visual evaluation of automated segmentations for 100 additional (i.e., exclusively automatically segmented) patients was performed by a nuclear physician., Results: Out of all approaches, the best results were achieved by using CT images which had been pre-segmented using a PET-based coarse mask as input. In addition, this method performed significantly better than the segmentation based solely on CT, which was supported by the visual examination of the additional segmentations. In 80% of the cases, the segmentations created by exploiting the PET-based pre-segmentation were preferred by the nuclear physician., Conclusion: This study shows that deep-learning based kidney segmentation can be significantly improved through the addition of a PET-based pre-segmentation. The presented method was shown to be especially beneficial for kidneys with cysts or kidneys that are closely adjacent to other organs such as the spleen, liver or pancreas. In the future, this could lead to a considerable reduction in the time required for dosimetry calculations as well as an improvement in the results., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Michael Lassmann has received institutional grants by IPSEN Pharma, Nordic Nanovector, and Novartis. No other potential conflicts of interest relevant to this article exist., (Copyright © 2023 The Author(s). Published by Elsevier GmbH.. All rights reserved.)

The numbers of diagnostic and therapeutic nuclear medicine agents under investigation are rapidly increasing. Both novel emitters and novel carrier molecules require careful selection of measurement procedures. This document provides guidance relevant to dosimetry for first-in human and early phase clinical trials of such novel agents. The guideline includes a short introduction to different emitters and carrier molecules, followed by recommendations on the methods for activity measurement, pharmacokinetic analyses, as well as absorbed dose calculations and uncertainty analyses. The optimal use of preclinical information and studies involving diagnostic analogues is discussed. Good practice reporting is emphasised, and relevant dosimetry parameters and method descriptions to be included are listed. Three examples of first-in-human dosimetry studies, both for diagnostic tracers and radionuclide therapies, are given., (© 2024. The Author(s).)

Introduction: CT-based attenuation correction (CT-AC) plays a major role in accurate activity quantification by SPECT/CT imaging. However, the effect of kilovoltage peak (kVp) and quality-reference mAs (QRM) on the attenuation coefficient image (μ-map) and volume CT dose index (CTDI vol ) have not yet been systematically evaluated. Therefore, the aim of this study was to fill this gap and investigate the influence of kVp and QRM on CT-AC in 177 Lu SPECT/CT imaging., Methods: Seventy low-dose CT acquisitions of an Electron Density Phantom (seventeen inserts of nine tissue-equivalent materials) were acquired using various kVp and QRM combinations on a Siemens Symbia Intevo Bold SPECT/CT system. Using manufacturer reconstruction software, 177 Lu μ-maps were generated for each CT image, and three low-dose CT related aspects were examined. First, the μ-map-based attenuation values (μ measured ) were compared with theoretical values (μ theoretical ). Second, changes in 177 Lu activity expected due to changes in the μ-map were calculated using a modified Chang method. Third, the noise in the μ-map was assessed by measuring the coefficient of variation in a volume of interest in the homogeneous section of the Electron Density Phantom. Lastly, two phantoms were designed to simulate attenuation in four tissue-equivalent materials for two different source geometries (1-mL and 10-mL syringes). 177 Lu SPECT/CT imaging was performed using three different reconstruction algorithms (xSPECT Quant, Flash3D, STIR), and the SPECT-based activities were compared against the nominal activities in the sources., Results: The largest relative errors between μ measured and μ theoretical were observed in the lung inhale insert (range: 18%-36%), while it remained below 6% for all other inserts. The resulting changes in 177 Lu activity quantification were -3.5% in the lung inhale insert and less than -2.3% in all other inserts. Coefficient of variation and CTDI vol ranged from 0.3% and 3.6 mGy (130 kVp, 35 mAs) to 0.4% and 0.9 mGy (80 kVp, 20 mAs), respectively. The SPECT-based activity quantification using xSPECT Quant reconstructions outperformed all other reconstruction algorithms., Conclusion: This study shows that kVp and QRM values in low-dose CT imaging have a minimum effect on quantitative 177 Lu SPECT/CT imaging, while the selection of low values of kVp and QRM reduce the CTDI vol ., (© 2024. The Author(s).)

Absorbed radiation doses are essential in assessing the effects, e.g. safety and efficacy, of radiopharmaceutical therapy (RPT). Patient-specific absorbed dose calculations in the target or the organ at risk require multiple inputs. These include the number of disintegrations in the organ, i.e. the time-integrated activities (TIAs) of the organs, as well as other parameters describing the process of radiation energy deposition in the target tissue (i.e. mean energy per disintegration, radiation dose constants, etc). TIAs are then estimated by incorporating the area under the radiopharmaceutical's time-activity curve (TAC), which can be obtained by quantitative measurements of the biokinetics in the patient (typically based on imaging data such as planar scintigraphy, SPECT/CT, PET/CT, or blood and urine samples). The process of TAC determination/calculation for RPT generally depends on the user, e.g., the chosen number and schedule of measured time points, the selection of the fit function, the error model for the data and the fit algorithm. These decisions can strongly affect the final TIA values and thus the accuracy of calculated absorbed doses. Despite the high clinical importance of the TIA values, there is currently no consensus on processing time-activity data or even a clear understanding of the influence of uncertainties and variations in personalised RPT dosimetry related to user-dependent TAC calculation. As a first step towards minimising site-dependent variability in RPT dosimetry, this work provides an overview of quality assurance and uncertainty management considerations of the TIA estimation., 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: The aim of this work is to provide the currently missing evidence that may allow an update of the Paediatric Dosage Card provided by the European Association of Nuclear Medicine (EANM) for conventional PET/CT systems., Methods: In a total of 2082 consecutive [ 18 F]FDG-PET scans performed within the EuroNet-PHL-C2 trial, the administered [ 18 F]FDG activity was compared to the activity recommended by the EANM Paediatric Dosage Card. None of these scans had been rejected beforehand by the reference nuclear medicine panel of the trial because of poor image quality. For detailed quality assessment, a subset of 91 [ 18 F]FDG-PET scans, all performed in different patients at staging, was selected according to pre-defined criteria, which (a) included only patients who had received substantially lower activities than those recommended by the EANM Paediatric Dosage Card, and (b) included as wide a range of different PET systems and imaging parameters as possible to ensure that the conclusions drawn in this work are as generally valid as possible. The image quality of the subset was evaluated visually by two independent readers using a quality scoring system as well as analytically based on a volume-of-interest analysis in 244 lesions and the healthy liver. Finally, recommendations for an update of the EANM Paediatric Dosage Card were derived based on the available data., Results: The activity recommended by the EANM Paediatric Dosage Card was undercut by a median of 99.4 MBq in 1960 [ 18 F]FDG-PET scans and exceeded by a median of 15.1 MBq in 119 scans. In the subset analysis (n = 91), all image data were visually classified as clinically useful. In addition, only a very weak correlation (r = 0.06) between activity reduction and tumour-to-background ratio was found. Due to the intended heterogeneity of the dataset, the noise could not be analysed statistically sound as the high range of different imaging variables resulted in very small subsets. Finally, a suggestion for an update of the EANM Paediatric Dosage Card was developed, based on the analysis presented, resulting in a mean activity reduction by 39%., Conclusion: The results of this work allow for a conservative update of the EANM Paediatric Dosage Card for [ 18 F]FDG-PET/CT scans performed with conventional PET/CT systems., (© 2023. The Author(s).)

Purpose: The use of molecular radiotherapy (MRT) has been rapidly evolving over the last years. The aim of this study was to assess the current implementation of dosimetry for MRTs in Europe., Methods: A web-based questionnaire was open for treating centres between April and June 2022, and focused on 2020-2022. Questions addressed the application of 16 different MRTs, the availability and involvement of medical physicists, software used, quality assurance, as well as the target regions for dosimetry, whether treatment planning and/or verification were performed, and the dosimetric methods used., Results: A total of 173 responses suitable for analysis was received from centres performing MRT, geographically distributed over 27 European countries. Of these, 146 centres (84 %) indicated to perform some form of dosimetry, and 97 % of these centres had a medical physicist available and almost always involved in dosimetry. The most common MRTs were 131 I-based treatments for thyroid diseases and thyroid cancer, and [ 223 Ra]RaCl 2 for bone metastases. The implementation of dosimetry varied widely between therapies, from almost all centres performing dosimetry-based planning for microsphere treatments to none for some of the less common treatments (like 32 P sodium-phosphate for myeloproliferative disease and [ 89 Sr]SrCl 2 for bone metastases)., Conclusions: Over the last years, implementation of dosimetry, both for pre-therapeutic treatment planning and post-therapy absorbed dose verification, increased for several treatments, especially for microsphere treatments. For other treatments that have moved from research to clinical routine, the use of dosimetry decreased in recent years. However, there are still large differences both across and within countries., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Jens Kurth receives an institutional grant by Novartis, and research grants by Novartis and Oncobeta. Manuel Bardiès is supervising a PhD student (J Fragoso Negrin) sponsored by DOSIsoft. All other authors state no conflict of interest., (Copyright © 2023 Associazione Italiana di Fisica Medica e Sanitaria. All rights reserved.)

Nuclear imaging techniques such as positron emission tomography (PET) and single photon emission computed tomography (SPECT) in combination with computed tomography (CT) are established imaging modalities in clinical practice, particularly for oncological problems. Due to a multitude of manufacturers, different measurement protocols, local demographic or clinical workflow variations as well as various available reconstruction and analysis software, very heterogeneous datasets are generated. This review article examines the current state of interoperability and harmonisation of image data and related clinical data in the field of nuclear medicine. Various approaches and standards to improve data compatibility and integration are discussed. These include, for example, structured clinical history, standardisation of image acquisition and reconstruction as well as standardised preparation of image data for evaluation. Approaches to improve data acquisition, storage and analysis will be presented. Furthermore, approaches are presented to prepare the datasets in such a way that they become usable for projects applying artificial intelligence (AI) (machine learning, deep learning, etc.). This review article concludes with an outlook on future developments and trends related to AI in nuclear medicine, including a brief research of commercial solutions., Competing Interests: L. Papp is co-founder of Dedicaid GmbH, Austria (wholly-owned by Telix Pharmaceuticals Ltd), (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)

Routine clinical dosimetry along with radiopharmaceutical therapies is key for future treatment personalization. However, dosimetry is considered complex and time-consuming with various challenges amongst the required steps within the dosimetry workflow. The general workflow for image-based dosimetry consists of quantitative imaging, the segmentation of organs and tumors, fitting of the time-activity-curves, and the conversion to absorbed dose. This work reviews the potential and advantages of the use of artificial intelligence to improve speed and accuracy of every single step of the dosimetry workflow., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

The European Council Directive 2013/59/Euratom (BSS Directive) includes optimisation of treatment with radiotherapeutic procedures based on patient dosimetry and verification of the absorbed doses delivered. The present policy statement summarises aspects of three directives relating to the therapeutic use of radiopharmaceuticals and medical devices, and outlines the steps needed for implementation of patient dosimetry for radioactive drugs. To support the transition from administrations of fixed activities to personalised treatments based on patient-specific dosimetry, EFOMP presents a number of recommendations including: increased networking between centres and disciplines to support data collection and development of codes-of-practice; resourcing to support an infrastructure that permits routine patient dosimetry; research funding to support investigation into individualised treatments; inter-disciplinary training and education programmes; and support for investigator led clinical trials. Close collaborations between the medical physicist and responsible practitioner are encouraged to develop a similar pathway as is routine for external beam radiotherapy and brachytherapy. EFOMP's policy is to promote the roles and responsibilities of medical physics throughout Europe in the development of molecular radiotherapy to ensure patient benefit. As the BSS directive is adopted throughout Europe, unprecedented opportunities arise to develop informed treatments that will mitigate the risks of under- or over-treatments., 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.)

Introduction: Commissioning, calibration, and quality control procedures for nuclear medicine imaging systems are typically performed using hollow containers filled with radionuclide solutions. This leads to multiple sources of uncertainty, many of which can be overcome by using traceable, sealed, long-lived surrogate sources containing a radionuclide of comparable energies and emission probabilities. This study presents the results of a quantitative SPECT/CT imaging comparison exercise performed within the MRTDosimetry consortium to assess the feasibility of using 133 Ba as a surrogate for 131 I imaging., Materials and Methods: Two sets of four traceable 133 Ba sources were produced at two National Metrology Institutes and encapsulated in 3D-printed cylinders (volume range 1.68-107.4 mL). Corresponding hollow cylinders to be filled with liquid 131 I and a mounting baseplate for repeatable positioning within a Jaszczak phantom were also produced. A quantitative SPECT/CT imaging comparison exercise was conducted between seven members of the consortium (eight SPECT/CT systems from two major vendors) based on a standardised protocol. Each site had to perform three measurements with the two sets of 133 Ba sources and liquid 131 I., Results: As anticipated, the 131 I pseudo-image calibration factors (cps/MBq) were higher than those for 133 Ba for all reconstructions and systems. A site-specific cross-calibration reduced the performance differences between both radionuclides with respect to a cross-calibration based on the ratio of emission probabilities from a median of 12-1.5%. The site-specific cross-calibration method also showed agreement between 133 Ba and 131 I for all cylinder volumes, which highlights the potential use of 133 Ba sources to calculate recovery coefficients for partial volume correction., Conclusion: This comparison exercise demonstrated that traceable solid 133 Ba sources can be used as surrogate for liquid 131 I imaging. The use of solid surrogate sources could solve the radiation protection problem inherent in the preparation of phantoms with 131 I liquid activity solutions as well as reduce the measurement uncertainties in the activity. This is particularly relevant for stability measurements, which have to be carried out at regular intervals., (© 2023. The Author(s).)

Background: Dosimetry after radiopharmaceutical therapy with 177 Lu ( 177 Lu-RPT) relies on quantitative SPECT/CT imaging, for which suitable reconstruction protocols are required. In this study, we characterized for the first time the quantitative performance of a ring-shaped CZT-based camera using two different reconstruction algorithms: an ordered subset expectation maximization (OSEM) and a block sequential regularized expectation maximization (BSREM) combined with noise reduction regularization. This study lays the foundations for the definition of a reconstruction protocol enabling accurate dosimetry for patients treated with 177 Lu-RPT., Methods: A series of 177 Lu-filled phantoms were acquired on a StarGuide™ (GE HealthCare), with energy and scatter windows centred at 208 (± 6%) keV and 185 (± 5%) keV, respectively. Images were reconstructed with the manufacturer implementations of OSEM (GE-OSEM) and BSREM (Q.Clear) algorithms, and various combinations of iterations and subsets. Additionally, the manufacturer-recommended Q.Clear-based reconstruction protocol was evaluated. Quantification accuracy, measured as the difference between the SPECT-based and the radionuclide calibrator-based activity, and noise were evaluated in a large cylinder. Recovery coefficients (RCs) and spatial resolution were assessed in a NEMA IEC phantom with sphere inserts. The reconstruction protocols considered suitable for clinical applications were tested on a cohort of patients treated with [ 177 Lu]Lu-PSMA-I&T., Results: The accuracy of the activity from the cylinder, although affected by septal penetration, was < 10% for all reconstructions. Both algorithms featured improved spatial resolution and higher RCs with increasing updates at the cost of noise build-up, but Q.Clear outperformed GE-OSEM in reducing noise accumulation. When the reconstruction parameters were carefully selected, similar values for noise (~0.15), spatial resolution (~1 cm) and RCs were found, irrespective of the reconstruction algorithm. Analogue results were found in patients., Conclusions: Accurate activity quantification is possible when imaging 177 Lu with StarGuide™. However, the impact of septal penetration requires further investigations. GE-OSEM is a valid alternative to the recommended Q.Clear reconstruction algorithm, featuring comparable performances assessed on phantoms and patients., (© 2023. Springer Nature Switzerland AG.)

Digitization in the healthcare sector and the support of clinical workflows with artificial intelligence (AI), including AI-supported image analysis, represent a great challenge and equally a promising perspective for preclinical and clinical nuclear medicine. In Germany, the Medical Informatics Initiative (MII) and the Network University Medicine (NUM) are of central importance for this transformation. This review article outlines these structures and highlights their future role in enabling privacy-preserving federated multi-center analyses with interoperable data structures harmonized between site-specific IT infrastructures. The newly founded working group "Digitization and AI" in the German Society of Nuclear Medicine (DGN) as well as the Fach- und Organspezifische Arbeitsgruppe (FOSA, specialty- and organ-specific working group) founded for the field of nuclear medicine (FOSA Nuklearmedizin) within the NUM aim to initiate and coordinate measures in the context of digital medicine and (image-)data-driven analyses for the DGN., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

Dosimetry can be a useful tool for personalization of molecular radiotherapy (MRT) procedures, enabling the continuous development of theranostic concepts. However, the additional resource requirements are often seen as a barrier to implementation. This guide discusses the requirements for dosimetry and demonstrates how a dosimetry regimen can be tailored to the available facilities of a centre. The aim is to help centres wishing to initiate a dosimetry service but may not have the experience or resources of some of the more established therapy and dosimetry centres. The multidisciplinary approach and different personnel requirements are discussed and key equipment reviewed example protocols demonstrating these factors are given in the supplementary material for the main therapies carried out in nuclear medicine, including [ 131 I]-NaI for benign thyroid disorders, [ 177 Lu]-DOTATATE and 131 I-mIBG for neuroendocrine tumours and [ 90 Y]-microspheres for unresectable hepatic carcinoma., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Validation of a Molecular Radiotherapy (MRT) dosimetry system requires imaging data for which an accompanying "ground truth" pharmacokinetic model and absorbed dose calculation are known., Methods: We present a methodology for production of a validation dataset for image based 177 Lu dotatate dosimetry calculations. A pharmacokinetic model is presented with activity concentrations corresponding to common imaging timepoints. Anthropomorphic 3D printed phantoms, corresponding to the organs at risk, have been developed to provide SPECT/CT and Whole Body imaging with known organ activities corresponding to common clinical timepoints., Results: Results for the accuracy of phantom filling reproduce the activity concentrations from the pharmacokinetic model for all timepoints and organs within measurement uncertainties, with a mean deviation of 0.6(8)%. The imaging dataset, ancillary data and phantoms designs are provided as a source of well characterized input data for the validation of clinical MRT dosimetry systems., Conclusions: The combination of pharmacokinetic modelling with the use of anthropomorphic 3D printed phantoms are a promising procedure to provide data for the validation of Molecular Radiotherapy Dosimetry systems, allowing multicentre comparisons., 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.)

A patient-specific absorbed dose calculation for red marrow dosimetry requires quantifying patient-specific volume fractions of the red marrow, yellow marrow, and trabecular bone in the spongiosa of several skeletal sites. This quantification allows selecting appropriate S values calculated from the parameterized radiation transport models for bone and bone marrow dosimetry. Currently, no comprehensive, individualized, and non-invasive procedure is available for quantifying the volume fractions of red marrow, yellow marrow, and trabecular bone in the spongiosa. This study aims to provide a new quantitative method based on dual-energy computed tomography to fill this gap in red marrow dosimetry using a (SPECT/)CT system., Methods: First, a method for parametrizing the photon attenuation coefficients relative to water was implemented. Next, a method to calculate the effective atomic number (Z eff ) and effective mass density (ρ eff ) using dual-energy CT (DECT) was employed. Lastly, two- and three-material decomposition using a dual-energy quantitative CT method (DEQCT) was performed in an anthropomorphic spine phantom and two bone samples of a boar, respectively. The measurements of Z eff and ρ eff were compared with the syngo.CT DE Rho/Z tool (Siemens Healthineers). Furthermore, the DEQCT method implemented in this study (DEQCT-I) was compared with a second DEQCT method based on the use of external material standards (DEQCT-II). DEQCT-II was used as reference method for calculating relative errors., Results: The two-material decomposition in the anthropomorphic spine phantom presented a maximum relative error of -10% for the bone mineral density quantification. Furthermore, Z eff and ρ eff calculated by DEQCT-I differed from syngo.CT DE Rho/Z tool by less than 4.4% and 1.9%, respectively. The three-material decomposition in the two bone samples showed a maximum relative error of 21%, -17%, and 15% for the quantification of the volume fractions of fat, water, and bone mineral equivalent materials. Lastly, Z eff and ρ eff calculated by DEQCT-I differed from syngo.CT DE Rho/Z tool by less than 8.2% and 7.0%, respectively., Conclusion: This study shows that quantifying the volume fraction of fat, water, and bone mineral using a phantom-independent and post-reconstruction DEQCT method is feasible. DEQCT-I has the advantage of not requiring prior information about the X-ray spectra or the detector sensitivity function, as is the case with spectral-based DEQCT methods. Instead, DEQCT-I, similar to other DEQCT methods depends on the chemical description of reference materials and a beam hardening correction function. DEQCT-I method provides an individualized and non-invasive procedure using a (SPECT/)CT system to apply S values based on the patient-specific volume fractions of yellow marrow, red marrow, and bone mineral in red marrow dosimetry., (Copyright © 2022. Published by Elsevier GmbH.)

Purpose: The aim is to assess the impact of different imaging-protocols on image-based kidney dosimetry in 177 Lu labelled peptide receptor radiotherapies., Methods: Kidney data of five [ 177 Lu]Lu-OPS201 injected pigs and a 3D printed phantom were used for comparing the absorbed doses and time-integrated activity coefficients calculated based on the following imaging-protocols: A-) multiple time-point SPECT/CTs, B-) multiple time-point planar scans in combination with one SPECT/CT, C-) single time-point SPECT/CT. In addition, the influence of late scan time-points on kidney dosimetry was investigated by sequentially eliminating scan data at > 100 h from the pig/phantom datasets for imaging-protocols A and B., Results: Compared to imaging-protocol A, absorbed doses based on imaging-protocols B and C (scans at > 24 h post-injection) were always lower (differences > 34%). The best agreement in absorbed dose was achieved by imaging-protocol C at ∼ 100 h post-injection (difference: 4%). Regarding the phantom/pig experiments, eliminating scan data at > 100 h post-injection increased the time-integrated activity coefficients calculated based on imaging-protocols A and B by up to 83%., Conclusion: While imaging-protocol A is accurate if scans at >∼100 h are included, it is time-consuming. In addition to being time-consuming, imaging-protocol B shows high differences associated with organ-count overlay, a lack of accuracy concerning the geometric mean based 2D attenuation correction, and 2D background subtraction due to the inhomogeneous and time-varying background contributions. Our findings indicate that dosimetry based on imaging-protocol C, if appropriately performed, provides similar kidney absorbed doses compared to imaging-protocol A, while only a single scan time-point is necessary., (Copyright © 2022 Associazione Italiana di Fisica Medica e Sanitaria. Published by Elsevier Ltd. All rights reserved.)

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).)