Analysis of image data from the EuroNet PHL-C2 trial indicates a potential reduction in injected F-18 FDG activities in children: a proposal to update the EANM Paediatric Dosage Card.

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 [18F]FDG-PET scans performed within the EuroNet-PHL-C2 trial, the administered [18F]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 [18F]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 [18F]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 [18F]FDG-PET/CT scans performed with conventional PET/CT systems.

EANM guidance document: dosimetry for first-in-human studies and early phase clinical trials.

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.

EANM enabling guide: how to improve the accessibility of clinical dosimetry.

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 [131I]-NaI for benign thyroid disorders, [177Lu]-DOTATATE and 131I-mIBG for neuroendocrine tumours and [90Y]-microspheres for unresectable hepatic carcinoma.

68Ga-PSMA I&T PET/CT for primary staging of prostate cancer.

PURPOSE: The present study is based on a retrospective analysis of Gallium-68 (68Ga)-labelled prostate-specific membrane antigen (68Ga-PSMA I&T) PET/CT performed in newly diagnosed, treatment-naïve prostate cancer (PCa) patients prior to definitive treatment. METHODS: A total of 82 men were included in the study and were imaged with 68Ga-PSMA I&T PET/CT to assess the distribution of PSMA-avid disease for staging purposes (11 with low-risk, 32 with intermediate-risk, and 39 with high-risk PCa). Forty patients (20 with intermediate- and 20 with high-risk disease) underwent subsequent radical prostatectomy with extended pelvic lymph node dissection which allowed for correlation of imaging findings with histopathologic data. RESULTS: PSMA-positive disease was detected in 83% of patients with 66/82 (80.5%) primary tumours being visualized. PSMA-avid lymph nodes were recorded in 17/82 patients (20.7%, 3 with intermediate-risk and 14 with high-risk PCa); distant disease was found in 14/82 subjects (17.1%, 2 with intermediate-risk and 12 with high-risk PCa). No extraprostatic disease was found in low-risk PCa. SUVmax of primary tumours showed a weak but significant correlation with serum PSA values (r = 0.51, p < 0.001) and Gleason scores (GSC; r = 0.35, p = 0.001), respectively. In correlation with histopathology, calculated per-region sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for detection of lymph node metastases were 35.0%, 98.4%, 63.6%, 95.0%, and 93.0%, respectively. CONCLUSIONS: In patients with initial diagnosis of intermediate- and high-risk prostate cancer, 68Ga-PSMA I&T PET/CT emerges as a relevant staging procedure by identifying nodal and/or distant metastases. Due to the low prevalence of extraprostatic disease, its value seems to be limited in low-risk disease.

Multifrequency reconstruction for frequency-modulated bSSFP.

PURPOSE: Banding artifacts in images acquired by balanced steady-state free precession (bSSFP) remain a challenge in MRI as they considerably reduce image quality, and diagnostic value deteriorates accordingly. As the steady-state tolerates small shifts in frequency, it is possible to acquire frequency-modulated bSSFP. Unfortunately, standard reconstructions of such measurements suffer from signal loss. Our study proposes a multifrequency reconstruction and demonstrates its capability of suppressing banding artifacts while retaining the high signal level of standard bSSFP. METHODS: Numerical simulations in vitro and in vivo measurements were performed using both standard bSSFP and frequency-modulated bSSFP. The modulated data were reconstructed using a multifrequency approach consisting of three steps: phase correction, multiple reconstructions for different assumed frequencies, and maximum intensity projection. RESULTS: Although standard bSSFP measurements showed banding artifacts that compromised the image quality, standard reconstructions of frequency-modulated acquisitions suffered from signal loss. In contrast, images reconstructed from frequency-modulated data using the proposed multifrequency reconstruction showed no visual bandings and featured a higher signal-to-noise ratio (SNR). The SNR gain for phantom and in vivo measurements ranged from 1.23 to 1.49. CONCLUSIONS: The presented multifrequency reconstruction for frequency-modulated bSSFP provides images showing no bandings and featuring high SNR in short scan times. Magn Reson Med 78:2226-2235, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

A model-based reconstruction technique for quantitative myocardial perfusion imaging.

PURPOSE: To reduce saturation effects in the arterial input function (AIF) estimation of quantitative myocardial first-pass saturation recovery perfusion imaging by employing a model-based reconstruction. THEORY AND METHODS: Imaging was performed with a saturation recovery prepared radial FLASH sequence. A model-based reconstruction was applied for reconstruction. By exploiting prior knowledge about the relaxation process, an image series with different saturation recovery times was reconstructed. By evaluating images with an effective saturation time of approximately 3 ms, saturation effects in the AIF determination were reduced. In a volunteer study, this approach was compared with a standard prebolus technique. RESULTS: In comparison to the low-dose injection of a prebolus acquisition, saturation effects were further reduced in the AIFs determined using the model-based approach. These effects, which were clearly visible for all six volunteers, were reflected in a statistically significant difference of up to 20% in the absolute perfusion values. CONCLUSION: The application of model-based reconstruction algorithms in quantitative myocardial perfusion imaging promises a significant improvement of the AIF determination. In addition to greatly reducing saturation effects that occur even for the prebolus methods, only a single bolus has to be applied. Magn Reson Med 76:880-887, 2016. © 2015 Wiley Periodicals, Inc.

Using self-consistency for an iterative trajectory adjustment (SCITA).

PURPOSE: To iteratively correct for deviations in radial trajectories with no need of additionally performed calibration scans. THEORY AND METHODS: Radially acquired data sets-even when undersampled to a certain extend-inherently feature an oversampled area in the center of k-space. Thus, for a perfectly measured trajectory and neglecting noise, information is consistent between multiple measurements gridded to the same Cartesian position within this region. In the case of erroneous coordinates, this accordance-and therefore a correction of the trajectory-can be enforced by an algorithm iteratively shifting the projections with respect to each other by applying the GRAPPA operator. The method was validated in numerical simulations, as well as in radial acquisitions of a phantom and in vivo images at 3T. The results of the correction were compared to a previously proposed correction method. RESULTS: The newly introduced technique allowed for a reliable trajectory correction in each of the presented examples. The method was able to remove artifacts as effectively as methods that are based on data from additional calibration scans. CONCLUSION: The iterative technique introduced in this paper allows for a correction of trajectory errors in radial imaging with no need for additional calibration data.

A Deep-Learning-Based Partial-Volume Correction Method for Quantitative 177Lu SPECT/CT Imaging.

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 177Lu 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 177Lu 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 177Lu SPECT/CT. Our analysis validates the functionality of DL-PVC and paves the way for future deployment on clinical image data.

Effect of kilovoltage and quality reference mAs on CT-based attenuation correction in 177Lu SPECT/CT imaging: a phantom study.

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 (CTDIvol) 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 177Lu 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, 177Lu µ-maps were generated for each CT image, and three low-dose CT related aspects were examined. First, the µ-map-based attenuation values (µmeasured) were compared with theoretical values (µtheoretical). Second, changes in 177Lu 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). 177Lu 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 µmeasured and µtheoretical were observed in the lung inhale insert (range: 18%-36%), while it remained below 6% for all other inserts. The resulting changes in 177Lu activity quantification were -3.5% in the lung inhale insert and less than -2.3% in all other inserts. Coefficient of variation and CTDIvol 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 177Lu SPECT/CT imaging, while the selection of low values of kVp and QRM reduce the CTDIvol.

Position dependence of recovery coefficients in 177Lu-SPECT/CT reconstructions - phantom simulations and measurements.

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 177Lu 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.

Time-Activity data fitting in molecular Radiotherapy: Methodology and pitfalls.

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.

Implementation of dosimetry for molecular radiotherapy; results from a European survey.

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 131I-based treatments for thyroid diseases and thyroid cancer, and [223Ra]RaCl2 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 32P sodium-phosphate for myeloproliferative disease and [89Sr]SrCl2 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.

Model-based Acceleration of Parameter mapping (MAP) for saturation prepared radially acquired data.

A reconstruction technique called Model-based Acceleration of Parameter mapping (MAP) is presented allowing for quantification of longitudinal relaxation time and proton density from radial single-shot measurements after saturation recovery magnetization preparation. Using a mono-exponential model in image space, an iterative fitting algorithm is used to reconstruct one well resolved and consistent image for each of the projections acquired during the saturation recovery relaxation process. The functionality of the algorithm is examined in numerical simulations, phantom experiments, and in-vivo studies. MAP reconstructions of single-shot acquisitions feature the same image quality and resolution as fully sampled reference images in phantom and in-vivo studies. The longitudinal relaxation times obtained from the MAP reconstructions are in very good agreement with the reference values in numerical simulations as well as phantom and in-vivo measurements. Compared to available contrast manipulation techniques, no averaging of projections acquired at different time points of the relaxation process is required in MAP imaging. The proposed technique offers new ways of extracting quantitative information from single-shot measurements acquired after magnetization preparation. The reconstruction simultaneously yields images with high spatiotemporal resolution fully consistent with the acquired data as well as maps of the effective longitudinal relaxation parameter and the relative proton density.

On the Use of Artificial Intelligence for Dosimetry of Radiopharmaceutical Therapies.

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.

PSMA-PET improves deep learning-based automated CT kidney segmentation.

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 [68Ga]Ga-PSMA-I&T and 55 [18F]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.

Enhancing Interoperability and Harmonisation of Nuclear Medicine Image Data and Associated Clinical Data.

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.

Development of a validation imaging dataset for Molecular Radiotherapy dosimetry multicenter intercomparison exercises based on anthropomorphic phantoms.

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 177Lu 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.

Quantitative 177Lu SPECT/CT imaging for personalized dosimetry using a ring-shaped CZT-based camera.

BACKGROUND: Dosimetry after radiopharmaceutical therapy with 177Lu (177Lu-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 177Lu-RPT. METHODS: A series of 177Lu-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 [177Lu]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 177Lu 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.

The Medical Informatics Initiative and the Network University Medicine - Perspectives for Nuclear Medicine.

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.