Purpose Ra-223 dichloride (223Ra, Xofigo®) is used for treatment of patients suffering from castration-resistant metastatic prostate cancer. The objective of this work was to apply the most recent biokinetic model for radium and its progeny to show their radiopharmacokinetic behaviour. Organ absorbed doses after intravenous injection of 223Ra were estimated and compared to clinical data and data of an earlier modelling study. Methods The most recent systemic biokinetic model of 223Ra and its progeny, developed by the International Commission on Radiological Protection (ICRP), as well as the ICRP human alimentary tract model were applied for the radiopharmacokinetic modelling of Xofigo® biodistribution in patients after bolus administration. Independent kinetics were assumed for the progeny of 223Ra. The time activity curves for 223Ra were modelled and the time integrated activity coefficients, $$ \overset{\sim }{a}\left({r}_S,{T}_D\right), $$ a ~ r S T D , in the source regions for each progeny were determined. For estimating the organ absorbed doses, the Specific Absorbed Fractions (SAF) and dosimetric framework of ICRP were used together with the aforementioned $$ \overset{\sim }{a}\left({r}_S,{T}_D\right) $$ a ~ r S T D values. Results The distribution of 223Ra after injection showed a rapid plasma clearance and a low urinary excretion. Main elimination was via faeces. Bone retention was found to be about 30% at 4 h post-injection. Similar tendencies were observed in clinical trials of other authors. The highest absorbed dose coefficients were found for bone endosteum, liver and red marrow, followed by kidneys and colon. Conclusion The biokinetic modelling of 223Ra and its progeny may help to predict their distributions in patients after administration of Xofigo®. The organ dose coefficients of this work showed some variation to the values reported from clinical studies and an earlier compartmental modelling study. The dose to the bone endosteum was found to be lower by a factor of ca. 3 than previously estimated.
Radiopharmaceutical dosimetry is usually estimated via organ-level MIRD schema-style formalisms, which form the computational basis for commonly used clinical and research dosimetry software. Recently, MIRDcalc internal dosimetry software was developed to provide a freely available organ-level dosimetry solution that incorporates upto-date models of human anatomy, addresses uncertainty in radiopharmaceutical biokinetics and patient organ masses, and offers a 1-screen user interface as well as quality assurance tools. The present work describes the validation of MIRDcalc and, secondarily, provides a compendium of radiopharmaceutical dose coefficients obtained with MIRDcalc. Biokinetic data for about 70 currently and historically used radiopharmaceuticals were obtained from the International Commission on Radiological Protection (ICRP) publication 128 radiopharmaceutical data compendium. Absorbed dose and effective dose coefficients were derived from the biokinetic datasets using MIRDcalc, IDAC-Dose, and OLINDA software. The dose coefficients obtained with MIRDcalc were systematically compared against the other software-derived dose coefficients and those originally presented in ICRP publication 128. Dose coefficients computed with MIRDcalc and IDAC-Dose showed excellent overall agreement. The dose coefficients derived from other software and the dose coefficients promulgated in ICRP publication 128 both were in reasonable agreement with the dose coefficients computed with MIRDcalc. Future work should expand the scope of the validation to include personalized dosimetry calculations.
Medical internal radiation dosimetry constitutes a fundamental aspect of diagnosis, treatment, optimization, and safety in nuclear medicine. The MIRD committee of the Society of Nuclear Medicine and Medical Imaging developed a new computational tool to support organ-level and suborgan tissue dosimetry (MIRDcalc, version 1). Based on a standard Excel spreadsheet platform, MIRDcalc provides enhanced capabilities to facilitate radiopharmaceutical internal dosimetry. This new computational tool implements the well-established MIRD schema for internal dosimetry. The spreadsheet incorporates a significantly enhanced database comprising details for 333 radionuclides, 12 phantom reference models (International Commission on Radiological Protection), 81 source regions, and 48 target regions, along with the ability to interpolate between models for patient-specific dosimetry. The software also includes sphere models of various composition for tumor dosimetry. MIRDcalc offers several noteworthy features for organ-level dosimetry, including modeling of blood source regions and dynamic source regions defined by user input, integration of tumor tissues, error propagation, quality control checks, batch processing, and reportpreparation capabilities. MIRDcalc implements an immediate, easy-touse single-screen interface. The MIRDcalc software is available for free download (www.mirdsoft.org) and has been approved by the Society of Nuclear Medicine and Molecular Imaging.
Lu-DOTATATE (Lutathera ® ) enables targeted radionuclide therapy of neuroendocrine tumors expressing somatostatin receptor type 2. Though patient-specific dosimetry estimates may be clinically important for predicting absorbed dose-effect relationships, there are multiple relevant dosimetry paradigms which are distinct in terms of clinical effort, numerical output and added-value. This work compares three different approaches for 177 Lu-DOTATATE dosimetry, including 1) an organ-level approach based on reference phantom MIRD S-values scaled to patient-specific organ masses (MIRDcalc), 2) an organ-level approach based on Monte Carlo simulation in a patient-specific mesh phantoms (PARaDIM), and 3) a 3D approach based on Monte Carlo simulation in patientspecific voxel phantoms. Method. Serial quantitative SPECT/CT images for two patients receiving 177 Lu-DOTATATE therapy were obtained from archive in the Deep Blue database. For each patient, the serial CT images were co-registered to the first time point CT using a deformable registration technique aided by virtual landmarks placed in the kidney pelves and the lesion foci. The co-registered SPECT images were integrated voxel-wise to generate time-integrated activity maps. Lesions, kidneys, liver, spleen, lungs, compact bone, spongiosa, and rest of body were segmented at the first imaging time point and overlaid on co-registered integrated activity maps. The resultant segmentation was used for three purposes: 1) to generate patient-specific phantoms, 2) to determine organ-level timeintegrated activities, and 3) to generate dose volume histograms from 3D voxel-based calculations. Results. Mean absorbed doses were computed for lesions and 48 tissues with MIRDcalc software. Mean organ absorbed doses and dose volume histograms were obtained for lesions and 6 tissues with the voxel Monte Carlo approach. Lesion-and organ-level absorbed dose estimates agreed within ±26% for the lesions and ±13% for the critical organs, among the different methods tested. Overall good agreement was observed with the dosimetry estimates from the NETTER-1 trial. Conclusions. For personalized 177 Lu-DOTATATE dosimetry, a combined approach was determined to be valuable, which utilized two dose calculation methods supported by a single image processing workflow. In the absence of quantitative imaging limitations, the voxel Monte Carlo method likely provides valuable information to guide treatment by considering absorbed dose non-uniformity in lesions and organs at risk. The patient-scaled reference phantom method also provides valuable information, including absorbed dose estimates for non-segmented organs, and more accurate dose estimates for complex radiosensitive organs including the active marrow. REVISED
Purpose: Current standard practice for clinical radionuclide dosimetry utilizes reference phantoms, where defined organ dimensions represent population averages for a given sex and age. Greater phantom personalization would support more accurate dose estimations and personalized dosimetry. Tailoring phantoms is traditionally accomplished using operator-intensive organ-level segmentation of anatomic images. Modern mesh phantoms provide enhanced anatomical realism, which has motivated their integration within Monte Carlo codes. Here, we present an automatable strategy for generating patient-specific phantoms/dosimetry using intensity-based deformable image registration between mesh reference phantoms and patient CT images. This work demonstrates a proof-of-concept personalized dosimetry workflow, presented in comparison to the manual segmentation approach. Methods: A linear attenuation coefficient phantom was generated by resampling the PSRK-Man reference phantom onto a voxel grid and defining organ regions with corresponding Hounsfield unit (HU) reference values. The HU phantom was co-registered with a patient CT scan using Plastimatch B-spline deformable registration. In parallel, major organs were manually contoured to generate a "ground truth" patient-specific phantom for comparisons. Monte Carlo derived S-values, which support nuclear medicine dosimetry, were calculated using both approaches and compared. Results: Application of the derived B-spline transform to the polygon vertices comprising the PSRK-Man yielded a deformed variant more closely matching the patient's body contour and most organ volumes as-evaluated by Hausdorff distance and Dice metrics. S-values computed for fluorine-18 for the deformed phantom using the Particle and Heavy Ion Transport code System showed improved agreement with those derived from the patient-specific analog. Conclusions: Deformable registration techniques can be used to create a personalized phantom and better support patient-specific dosimetry. This method is shown to be easier and faster than manual segmentation. Our study is limited to a proof-of-concept scope, but demonstrates that integration of personalized phantoms into clinical dosimetry workflows can reasonably be achieved when anatomical images (CT) are available.
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