Validation of a SIMIND Monte Carlo modelled gamma camera for Iodine-123 and Iodine-131 imaging

Accuracy of patient-specific I-131 dosimetry using hybrid whole-body planar-SPECT/CT I-123 and I-131 imaging

PURPOSE

This study aimed to assess the accuracy of patient-specific absorbed dose calculations for tumours and organs at risk in radiopharmaceutical therapy planning, utilizing hybrid planar-SPECT/CT imaging.

METHODS

Three Monte Carlo (MC) simulated digital patient phantoms were created, with time-activity data for mIBG labelled to I-123 (LEHR and ME collimators) and I-131 (HE collimator). The study assessed the accuracy of the mean absorbed doses for I-131-mIBG therapy treatment planning. Multiple planar whole-body (WB) images were simulated (between 1 to 72 h post-injection (p.i)). The geometric-mean image of the anterior and posterior WB images was calculated, with scatter and attenuation corrections applied. Time-activity curves were created for regions of interest over the liver and two tumours (diameters: 3.0 cm and 5.0 cm) in the WB images. A corresponding SPECT study was simulated at 24 h p.i and reconstructed using the OS-EM algorithm, incorporating scatter, attenuation, collimator-detector response, septal scatter and penetration corrections. MC voxel-based absorbed dose rate calculations used two image sets, (i) the activity distribution represented by the SPECT images and (ii) the activity distribution from the SPECT images distributed uniformly within the volume of interest. Mean absorbed doses were calculated considering photon and charged particle emissions, and beta emissions only. True absorbed doses were calculated by MC voxel-based dosimetry of the known activity distributions for reference.

RESULTS

Considering photon and charged particle emissions, mean absorbed dose accuracies across all three radionuclide-collimator combinations of 3.8 ± 5.5% and 0.1 ± 0.9% (liver), 5.2 ± 10.0% and 4.3 ± 1.7% (3.0 cm tumour) and 15.0 ± 5.8% and 2.6 ± 0.6% (5.0 cm tumour) were obtained for image set (i) and (ii) respectively. Considering charged particle emissions, accuracies of 2.7 ± 4.1% and 5.7 ± 0.7% (liver), 3.2 ± 10.2% and 9.1 ± 1.7% (3.0 cm tumour) and 13.6 ± 5.7% and 7.0 ± 0.6% (5.0 cm tumour) were obtained for image set (i) and (ii) respectively.

CONCLUSION

The hybrid WB planar-SPECT/CT method proved accurate for I-131-mIBG dosimetry, suggesting its potential for personalized treatment planning.

ISIT-QA: In Silico Imaging Trial to Evaluate a Low-Count Quantitative SPECT Method Across Multiple Scanner-Collimator Configurations for 223Ra-Based Radiopharmaceutical Therapies

Personalized dose-based treatment planning requires accurate and reproducible noninvasive measurements to ensure safety and effectiveness. Dose estimation using SPECT is possible but challenging for alpha (α)-particle-emitting radiopharmaceutical therapy (α-RPT) because of complex γ-emission spectra, extremely low counts, and various image-degrading artifacts across a plethora of scanner-collimator configurations. Through the incorporation of physics-based considerations and skipping of the potentially lossy voxel-based reconstruction step, a recently developed projection-domain low-count quantitative SPECT (LC-QSPECT) method has the potential to provide reproducible, accurate, and precise activity concentration and dose measures across multiple scanners, as is typically the case in multicenter settings. To assess this potential, we conducted an in silico imaging trial to evaluate the LC-QSPECT method for a 223Ra-based α-RPT, with the trial recapitulating patient and imaging system variabilities. Methods: A virtual imaging trial titled In Silico Imaging Trial for Quantitation Accuracy (ISIT-QA) was designed with the objectives of evaluating the performance of the LC-QSPECT method across multiple scanner-collimator configurations and comparing performance with a conventional reconstruction-based quantification method. In this trial, we simulated 280 realistic virtual patients with bone-metastatic castration-resistant prostate cancer treated with 223Ra-based α-RPT. The trial was conducted with 9 simulated SPECT scanner-collimator configurations. The primary objective of this trial was to evaluate the reproducibility of dose estimates across multiple scanner-collimator configurations using LC-QSPECT by calculating the intraclass correlation coefficient. Additionally, we compared the reproducibility and evaluated the accuracy of both considered quantification methods across multiple scanner-collimator configurations. Finally, the repeatability of the methods was evaluated in a test-retest study. Results: In this trial, data from 268 223RaCl2 treated virtual prostate cancer patients, with a total of 2,903 lesions, were used to evaluate LC-QSPECT. LC-QSPECT provided dose estimates with good reproducibility across the 9 scanner-collimator configurations (intraclass correlation coefficient > 0.75) and high accuracy (ensemble average values of recovery coefficients ranged from 1.00 to 1.02). Compared with conventional reconstruction-based quantification, LC-QSPECT yielded significantly improved reproducibility across scanner-collimator configurations, accuracy, and test-retest repeatability ([Formula: see text] Conclusion: LC-QSPECT provides reproducible, accurate, and repeatable dose estimations in 223Ra-based α-RPT as evaluated in ISIT-QA. These findings provide a strong impetus for multicenter clinical evaluations of LC-QSPECT in dose quantification for α-RPTs.

Radiosynthesis, Stability, Lipophilicity, and Cellular Uptake Evaluations of [131I]Iodine-α-Mangostin for Breast Cancer Diagnosis and Therapy

The high rate of incidence and mortality caused by breast cancer encourage urgent research to immediately develop new diagnostic and therapeutic agents for breast cancer. Alpha mangostin (AM) is a natural compound reported to have anti-breast cancer properties. Its electron-donating groups structure allows it to be labeled with an iodine-131 radioisotope to develop a candidate of a diagnostic and therapeutic agent for breast cancer. This study aims to prepare the [^131I]Iodine-α-mangostin ([¹³¹I]I-AM) and evaluate its stability, lipophilicity, and cellular uptake in breast cancer cell lines. The [¹³¹I]I-AM was prepared by direct radiosynthesis with Chloramine-T method in two conditions (A: AM dissolved in NaOH, B: AM dissolved in ethanol). Reaction time, pH, and mass of the oxidizing agent were optimized as crucial parameters that affected the radiosynthesis reaction. Further analysis was conducted using the radiosynthesis conditions with the highest radiochemical purity (RCP). Stability tests were carried out at three storage conditions, including -20, 2, and 25 °C. A cellular uptake study was performed in T47D (breast cancer cell line) and Vero cells (noncancerous cell line) at various incubation times. The results show that the RCP values of [¹³¹I]I-AM under conditions A and B were 90.63 ± 0.44 and 95.17 ± 0.80% (n = 3), respectively. In the stability test, [¹³¹I]I-AM has an RCP above 90% after three days of storage at -20 °C. A significant difference was obtained between [¹³¹I]I-AM uptake in T47D and Vero cells. Based on these results, [¹³¹I]I-AM has been prepared with high RCP, stable at -20 °C, and specifically uptaken by breast cancer cell lines. Biodistribution evaluations in animals are recommended as further research in developing [¹³¹I]I-AM as a diagnostic and therapeutic agent for breast cancer.

Validation of [Formula: see text]Tc and [Formula: see text]Lu quantification parameters for a Monte Carlo modelled gamma camera

PURPOSE

Monte Carlo (MC) simulation in Nuclear Medicine is a powerful tool for modeling many physical phenomena which are difficult to track or measure directly. MC simulation in SPECT/CT imaging is particularly suitable for optimizing the quantification of activity in a patient, and, consequently, the absorbed dose to each organ. To do so, validating MC results with real data acquired with gamma camera is mandatory. The aim of this study was the validation of the calibration factor (CF) and the recovery coefficient (RC) obtained with SIMIND Monte Carlo code for modeling a Siemens Symbia Intevo Excel SPECT-CT gamma camera to ensure optimal [Formula: see text]Tc and [Formula: see text]Lu SPECT quantification.

METHODS

Phantom experiments using [Formula: see text]Tc and [Formula: see text]Lu have been performed to measure spatial resolution and sensitivity, as well as to evaluate the CF and RC from acquired data. The geometries used for 2D planar imaging were (1) Petri dish and (2) capillary source while for 3D volumetric imaging were (3) a uniform filled cylinder phantom and (4) a Jaszczack phantom with spheres of different volumes. The experimental results have been compared with the results obtained from Monte Carlo simulations performed in the same geometries.

RESULTS

Comparison shows good accordance between simulated and experimental data. The measured planar spatial resolution was 8.3[Formula: see text] mm for [Formula: see text]Tc and 11.8±0.6 mm for [Formula: see text]Lu. The corresponding data obtained by SIMIND for [Formula: see text]Tc was 7.8±0.1 mm, while for [Formula: see text]Lu was 12.4±0.4 mm. The CF was 110.1±5.5 cps/MBq for Technetium and 18.3±1.0 cps/MBq for Lutetium. The corresponding CF obtained by SIMIND for [Formula: see text]Tc was 107.3±0.3 cps/MBq, while for [Formula: see text]Lu 20.4±0.7 cps/MBq. Moreover, a complete curve RCs vs Volume (ml) both for Technetium and Lutetium was determined to correct the PVE for all volumes of clinical interest. In none of the cases, a RC coefficient equal to 100 was found.

CONCLUSIONS

The validation of quantification parameters shows that SIMIND can be used for simulating both gamma camera planar and SPECT images of Siemens Symbia Intevo using [Formula: see text]Tc and [Formula: see text]Lu radionuclides for different medical purposes and treatments.

A Projection-Domain Low-Count Quantitative SPECT Method for α-Particle-Emitting Radiopharmaceutical Therapy

Single-photon emission-computed tomography (SPECT) provides a mechanism to estimate regional isotope uptake in lesions and at-risk organs after administration of α-particle-emitting radiopharmaceutical therapies (α-RPTs). However, this estimation task is challenging due to the complex emission spectra, the very low number of detected counts (~20 times lower than in conventional SPECT), the impact of stray-radiation-related noise at these low counts, and the multiple image-degrading processes in SPECT. The conventional reconstruction-based quantification methods are observed to be erroneous for α-RPT SPECT. To address these challenges, we developed a low-count quantitative SPECT (LC-QSPECT) method that directly estimates the regional activity uptake from the projection data (obviating the reconstruction step), compensates for stray-radiation-related noise, and accounts for the radioisotope and SPECT physics, including the isotope spectra, scatter, attenuation, and collimator-detector response, using a Monte Carlo-based approach. The method was validated in the context of 3-D SPECT with 223Ra, a commonly used radionuclide for α-RPT. Validation was performed using both realistic simulation studies, including a virtual clinical trial, and synthetic and 3-D-printed anthropomorphic physical-phantom studies. Across all studies, the LC-QSPECT method yielded reliable regional-uptake estimates and outperformed the conventional ordered subset expectation-maximization (OSEM)-based reconstruction and geometric transfer matrix (GTM)-based post-reconstruction partial-volume compensation methods. Furthermore, the method yielded reliable uptake across different lesion sizes, contrasts, and different levels of intralesion heterogeneity. Additionally, the variance of the estimated uptake approached the Cramér-Rao bound-defined theoretical limit. In conclusion, the proposed LC-QSPECT method demonstrated the ability to perform reliable quantification for α-RPT SPECT.

Future Prospective of Radiopharmaceuticals from Natural Compounds Using Iodine Radioisotopes as Theranostic Agents

Natural compounds provide precursors with various pharmacological activities and play an important role in discovering new chemical entities, including radiopharmaceuticals. In the development of new radiopharmaceuticals, iodine radioisotopes are widely used and interact with complex compounds including natural products. However, the development of radiopharmaceuticals from natural compounds with iodine radioisotopes has not been widely explored. This review summarizes the development of radiopharmaceuticals from natural compounds using iodine radioisotopes in the last 10 years, as well as discusses the challenges and strategies to improve future discovery of radiopharmaceuticals from natural resources. Literature research was conducted via PubMed, from which 32 research articles related to the development of natural compounds labeled with iodine radioisotopes were reported. From the literature, the challenges in developing radiopharmaceuticals from natural compounds were the purity and biodistribution. Despite the challenges, the development of radiopharmaceuticals from natural compounds is a golden opportunity for nuclear medicine advancement.

A tissue-fraction estimation-based segmentation method for quantitative dopamine transporter SPECT

BACKGROUND

Quantitative measures of dopamine transporter (DaT) uptake in caudate, putamen, and globus pallidus (GP) derived from dopamine transporter-single-photon emission computed tomography (DaT-SPECT) images have potential as biomarkers for measuring the severity of Parkinson's disease. Reliable quantification of this uptake requires accurate segmentation of the considered regions. However, segmentation of these regions from DaT-SPECT images is challenging, a major reason being partial-volume effects (PVEs) in SPECT. The PVEs arise from two sources, namely the limited system resolution and reconstruction of images over finite-sized voxel grids. The limited system resolution results in blurred boundaries of the different regions. The finite voxel size leads to TFEs, that is, voxels contain a mixture of regions. Thus, there is an important need for methods that can account for the PVEs, including the TFEs, and accurately segment the caudate, putamen, and GP, from DaT-SPECT images.

PURPOSE

Design and objectively evaluate a fully automated tissue-fraction estimation-based segmentation method that segments the caudate, putamen, and GP from DaT-SPECT images.

METHODS

The proposed method estimates the posterior mean of the fractional volumes occupied by the caudate, putamen, and GP within each voxel of a three-dimensional DaT-SPECT image. The estimate is obtained by minimizing a cost function based on the binary cross-entropy loss between the true and estimated fractional volumes over a population of SPECT images, where the distribution of true fractional volumes is obtained from existing populations of clinical magnetic resonance images. The method is implemented using a supervised deep-learning-based approach.

RESULTS

Evaluations using clinically guided highly realistic simulation studies show that the proposed method accurately segmented the caudate, putamen, and GP with high mean Dice similarity coefficients of ∼ 0.80 and significantly outperformed (p < 0.01 $p < 0.01$ ) all other considered segmentation methods. Further, an objective evaluation of the proposed method on the task of quantifying regional uptake shows that the method yielded reliable quantification with low ensemble normalized root mean square error (NRMSE) < 20% for all the considered regions. In particular, the method yielded an even lower ensemble NRMSE of ∼ 10% for the caudate and putamen.

CONCLUSIONS

The proposed tissue-fraction estimation-based segmentation method for DaT-SPECT images demonstrated the ability to accurately segment the caudate, putamen, and GP, and reliably quantify the uptake within these regions. The results motivate further evaluation of the method with physical-phantom and patient studies.

Development of a scatter correction technique for planar 99mTc-MAA imaging to improve accuracy in lung shunt fraction estimation

PURPOSE

Prior to ⁹⁰Y selective internal radiation therapy (SIRT) treatment, ^99mTc-MAA scintigraphy imaging is used in the estimation of the lung shunt fraction (LSF). Planar imaging is recommended for determining a LSF ratio. However, the estimate may be affected by scatter contributions, attenuation and respiratory motion. The objective of this study was to correct for the effects of scatter in the LSF, towards the determination of a more accurate estimation method of LSF derived from planar scintigraphy imaging, which is recommended by international guidelines.

METHODS

The open access SIMIND Monte Carlo modelling software was used to estimate an optimum scatter window (SW) for scatter correction. The uncertainties associated with scatter and scatter contributions from the liver on the LSF were evaluated using an anthropomorphic thorax phantom and a virtual Vox-Man phantom. A brief retrospective examination of patient scans and tumour location investigated the impact that the inclusion of the simulated scatter corrections had on the LSF estimation.

RESULTS

The percentage overestimation of the manufacturer recommended method of LSF estimation was 192%. SW corrections improved the uncertainty to within 19% for the range of known LSFs. Similar findings were observed for our patient and tumour location studies.

CONCLUSION

The incorporated scatter corrections can significantly improve the accuracy of the LSF estimation, thereby providing a robust gamma camera, patient and tumour depth specific correction which is easily implementable. This is supported by Monte Carlo, phantom and preliminary patient studies.

Evaluation of Iodine-123 and Iodine-131 SPECT activity quantification: a Monte Carlo study

Purpose

The quantitative accuracy of Nuclear Medicine images, acquired for both planar and SPECT studies, is influenced by the isotope-collimator combination as well as image corrections incorporated in the iterative reconstruction process. These factors can be investigated and optimised using Monte Carlo simulations. This study aimed to evaluate SPECT quantification accuracy for ¹²³I with both the low-energy high resolution (LEHR) and medium-energy (ME) collimators and ¹³¹I with the high-energy (HE) collimator.

Methods

Simulated SPECT projection images were reconstructed using the OS-EM iterative algorithm, which was optimised for the number of updates, with appropriate corrections for scatter, attenuation and collimator detector response (CDR), including septal scatter and penetration compensation. An appropriate calibration factor (CF) was determined from four different source geometries (activity-filled: water-filled cylindrical phantom, sphere in water-filled (cold) cylindrical phantom, sphere in air and point-like source), investigated with different volume of interest (VOI) diameters. Recovery curves were constructed from recovery coefficients to correct for partial volume effects (PVEs). The quantitative method was evaluated for spheres in voxel-based digital cylindrical and patient phantoms.

Results

The optimal number of OS-EM updates was 60 for all isotope-collimator combinations. The CF_point with a VOI diameter equal to the physical size plus a 3.0-cm margin was selected, for all isotope-collimator geometries. The spheres’ quantification errors in the voxel-based digital cylindrical and patient phantoms were less than 3.2% and 5.4%, respectively, for all isotope-collimator combinations.

Conclusion

The study showed that quantification errors of less than 6.0% could be attained, for all isotope-collimator combinations, if corrections for; scatter, attenuation, CDR (including septal scatter and penetration) and PVEs are performed. ¹²³I LEHR and ¹²³I ME quantification accuracies compared well when appropriate corrections for septal scatter and penetration were applied. This can be useful in departments that perform ¹²³I studies and may not have access to ME collimators.