Comparison of conventional, model-based quantitative planar, and quantitative SPECT image processing methods for organ activity estimation using In-111 agents

Few-time-points time-integrated activity coefficients calculation using non-linear mixed-effects modeling: Proof of concept for [111In]In-DOTA-TATE in kidneys

PURPOSE

The purpose of this study is to investigate the accuracy of few-time-points (FTP) time-integrated activity coefficients (TIACs) in peptide-receptor radionuclide therapy (PRRT) using non-linear mixed-effects (NLME) modeling.

METHODS

Biokinetic data of [111In]In-DOTA-TATE in kidneys at T-1 = (2.9 ± 0.6) h, T-2 = (4.6 ± 0.4) h, T-3 = (22.8 ± 1.6) h, T-4 = (46.7 ± 1.7) h, and T-5 = (70.9 ± 1.0) h after injection were obtained from eight patients using planar imaging. The Sum-Of-Exponentials (SOE) function with four parameters was used, which was selected as the best model for the renal biokinetic data of [111In]In-DOTA-TATE. The parameters of the SOE function were fitted to the all-time-point data in the NLME framework to derive reference (rTIACs). FTP fits, which consist of all combinations of time points, are done to calculate the estimated TIACs (eTIACs). The accuracy of the FTP-NLME TIACs calculations was assessed by calculating the relative deviations (RDs) and relative root-mean-square errors (RMSEs) between the eTIACs and rTIACs.

RESULTS

The lowest (mean ± SD) of RDs for the single-, two-, three-, four-time point FTPs were (0 ± 8) % (T-4), (1 ± 6) % (T-3 and T-4), (3 ± 5) % (T-2, T-3 and T-4), and (0 ± 2) % (T-2, T-3, T-4, and T-5), respectively. The lowest RMSEs for the one-, two-, three-, and four-time point FTPs were 8 % (T-4), 6 % (T-3 and T-4), 5 % (T-2, T-3 and T-4), and 2 % (T-2, T-3, T-4, and T-5), respectively.

CONCLUSION

Our results showed that FTP-NLME in an example of [111In]In-DOTA-TATE could lead to a high accuracy of eTIAC across various time points, when incorporating time point T-4 = (46.7 ± 1.7) h.

Population-based model selection for an accurate estimation of time-integrated activity using non-linear mixed-effects modelling

PURPOSE

Personalized treatment planning in Molecular Radiotherapy (MRT) with accurately determining the absorbed dose is highly desirable. The absorbed dose is calculated based on the Time-Integrated Activity (TIA) and the dose conversion factor. A crucial unresolved issue in MRT dosimetry is which fit function to use for the TIA calculation. A data-driven population-based fitting function selection could help solve this problem. Therefore, this project aims to develop and evaluate a method for accurately determining TIAs in MRT, which performs a Population-Based Model Selection within the framework of the Non-Linear Mixed-Effects (NLME-PBMS) model.

METHODS

Biokinetic data of a radioligand for the Prostate-Specific Membrane Antigen (PSMA) for cancer treatment were used. Eleven fit functions were derived from various parameterisations of mono-, bi-, and tri-exponential functions. The functions' fixed and random effects parameters were fitted (in the NLME framework) to the biokinetic data of all patients. The goodness of fit was assumed acceptable based on the visual inspection of the fitted curves and the coefficients of variation of the fitted fixed effects. The Akaike weight, the probability that the model is the best among the whole set of considered models, was used to select the fit function most supported by the data from the set of functions with acceptable goodness of fit. NLME-PBMS Model Averaging (MA) was performed with all functions having acceptable goodness of fit. The Root-Mean-Square Error (RMSE) of the calculated TIAs from individual-based model selection (IBMS), a shared-parameter population-based model selection (SP-PBMS) reported in the literature, and the functions from NLME-PBMS method to the TIAs from MA were calculated and analysed. The NLME-PBMS (MA) model was used as the reference as this model considers all relevant functions with corresponding Akaike weights.

RESULTS

The function [Formula: see text] was selected as the function most supported by the data with an Akaike weight of (54 ± 11) %. Visual inspection of the fitted graphs and the RMSE values show that the NLME model selection method has a relatively better or equivalent performance than the IBMS or SP-PBMS methods. The RMSEs of the IBMS, SP-PBMS, and NLME-PBMS (f3a) methods are 7.4%, 8.8%, and 2.4%, respectively.

CONCLUSION

A procedure including fitting function selection in a population-based method was developed to determine the best fit function for calculating TIAs in MRT for a given radiopharmaceutical, organ and set of biokinetic data. The technique combines standard practice approaches in pharmacokinetics, i.e. an Akaike-weight-based model selection and the NLME model framework.

Technological Advances in SPECT and SPECT/CT Imaging

Single photon emission tomography/computed tomography (SPECT/CT) is a mature imaging technology with a dynamic role in the diagnosis and monitoring of a wide array of diseases. This paper reviews the technological advances, clinical impact, and future directions of SPECT and SPECT/CT imaging. The focus of this review is on signal amplifier devices, detector materials, camera head and collimator designs, image reconstruction techniques, and quantitative methods. Bulky photomultiplier tubes (PMTs) are being replaced by position-sensitive PMTs (PSPMTs), avalanche photodiodes (APDs), and silicon PMs to achieve higher detection efficiency and improved energy resolution and spatial resolution. Most recently, new SPECT cameras have been designed for cardiac imaging. The new design involves using specialised collimators in conjunction with conventional sodium iodide detectors (NaI(Tl)) or an L-shaped camera head, which utilises semiconductor detector materials such as CdZnTe (CZT: cadmium-zinc-telluride). The clinical benefits of the new design include shorter scanning times, improved image quality, enhanced patient comfort, reduced claustrophobic effects, and decreased overall size, particularly in specialised clinical centres. These noticeable improvements are also attributed to the implementation of resolution-recovery iterative reconstructions. Immense efforts have been made to establish SPECT and SPECT/CT imaging as quantitative tools by incorporating camera-specific modelling. Moreover, this review includes clinical examples in oncology, neurology, cardiology, musculoskeletal, and infection, demonstrating the impact of these advancements on clinical practice in radiology and molecular imaging departments.

An International Study of Factors Affecting Variability of Dosimetry Calculations, Part 2: Overall Variabilities in Absorbed Dose

Dosimetry for personalized radiopharmaceutical therapy has gained considerable attention. Many methods, tools, and workflows have been developed to estimate absorbed dose (AD). However, standardization is still required to reduce variability of AD estimates across centers. One effort for standardization is the Society of Nuclear Medicine and Molecular Imaging 177Lu Dosimetry Challenge, which comprised 5 tasks (T1-T5) designed to assess dose estimate variability associated with the imaging protocol (T1 vs. T2 vs. T3), segmentation (T1 vs. T4), time integration (T4 vs. T5), and dose calculation (T5) steps of the dosimetry workflow. The aim of this work was to assess the overall variability in AD calculations for the different tasks. Methods: Anonymized datasets consisting of serial planar and quantitative SPECT/CT scans, organ and lesion contours, and time-integrated activity maps of 2 patients treated with 177Lu-DOTATATE were made available globally for participants to perform dosimetry calculations and submit their results in standardized submission spreadsheets. The data were carefully curated for formal mistakes and methodologic errors. General descriptive statistics for ADs were calculated, and statistical analysis was performed to compare the results of different tasks. Variability in ADs was measured using the quartile coefficient of dispersion. Results: ADs to organs estimated from planar imaging protocols (T2) were lower by about 60% than those from pure SPECT/CT (T1), and the differences were statistically significant. Importantly, the average differences in dose estimates when at least 1 SPECT/CT acquisition was available (T1, T3, T4, T5) were within ±10%, and the differences with respect to T1 were not statistically significant for most organs and lesions. When serial SPECT/CT images were used, the quartile coefficients of dispersion of ADs for organs and lesions were on average less than 20% and 26%, respectively, for T1; 20% and 18%, respectively, for T4 (segmentations provided); and 10% and 5%, respectively, for T5 (segmentation and time-integrated activity images provided). Conclusion: Variability in ADs was reduced as segmentation and time-integration data were provided to participants. Our results suggest that SPECT/CT-based imaging protocols generate more consistent and less variable results than planar imaging methods. Effort at standardizing segmentation and fitting should be made, as this may substantially reduce variability in ADs.

Single-time-point estimation of absorbed doses in PRRT using a non-linear mixed-effects model

INTRODUCTION

Estimation of accurate time-integrated activity coefficients (TIACs) and radiation absorbed doses (ADs) is desirable for treatment planning in peptide-receptor radionuclide therapy (PRRT). This study aimed to investigate the accuracy of a simplified dosimetry using a physiologically-based pharmacokinetic (PBPK) model, a nonlinear mixed effect (NLME) model, and single-time-point imaging to calculate the TIACs and ADs of ⁹⁰Y-DOTATATE in various organs of dosimetric interest and tumors.

MATERIALS & METHODS

Biokinetic data of ¹¹¹In-DOTATATE in tumors, kidneys, liver, spleen, and whole body were obtained from eight patients using planar scintigraphic imaging at T1 = (2.9 ± 0.6), T2 = (4.6 ± 0.4), T3 = (22.8 ± 1.6), T4 = (46.7 ± 1.7) and T5 = (70.9 ± 1.0) h post injection. Serum activity concentration was measured at 5 and 15 min; 0.5, 1, 2, and 4 h; and 1, 2, and 3 d p.i.. A published PBPK model for PRRT, NLME, and a single-time-point imaging datum at different time points were used to calculate TIACs in tumors, kidneys, liver, spleen, whole body, and serum. Relative deviations (RDs) (median [min, max]) between the calculated TIACs from single-time-point imaging were compared to the TIACs calculated from the all-time-points fit. The root mean square error (RMSE) of the difference between the computed ADs from the single-time-point imaging and reference ADs from the all-time point fittings were analyzed. A joint root mean square error RMSE_joint of the ADs was calculated with the RSME from both the tumor and kidneys to sort the time points concerning accurate results for the kidneys and tumor dosimetry. The calculations of TIACs and ADs from the single-time-point dosimetry were repeated using the sum of exponentials (SOE) approach introduced in the literature. The RDs and the RSME of the PBPK approach in our study were compared to the SOE approach.

RESULTS

Using the PBPK and NLME models and the biokinetic measurements resulted in a good fit based on visual inspection of the fitted curves and the coefficient of variation CV of the fitted parameters (<50%). T4 was identified being the time point with a relatively low median and range of TIACs RDs, i.e., 5 [1, 21]% and 2 [-15, 21]% for kidneys and tumors, respectively. T4 was found to be the time point with the lowest joint root mean square error RMSE_joint of the ADs. Based on the RD and RMSE, our results show a similar performance as the SOE and NLME model approach.

SUMMARY

In this study, we introduced a simplified calculation of TIACs/ADs using a PBPK model, an NLME model, and a single-time-point measurement. Our results suggest a single measurement might be used to calculate TIACs/ADs in the kidneys and tumors during PRRT.

Imaging and dosimetry for alpha-particle emitter radiopharmaceutical therapy: improving radiopharmaceutical therapy by looking into the black box

Radiopharmaceutical therapy using α-particle emitting radionuclides (αRPT) is a novel treatment modality that delivers highly potent alpha-particles to cancer cells or their environment. We review the advantages and challenges of imaging and dosimetry in implementing αRPT for cancer patients.

Impacts of acquisition and reconstruction parameters on the absolute technetium quantification of the cadmium-zinc-telluride-based SPECT/CT system: a phantom study

Background

The digital cadmium–zinc–telluride (CZT)-based SPECT system has many advantages, including better spatial and energy resolution. However, the impacts of different acquisition and reconstruction parameters on CZT SPECT quantification might still need to be validated. This study aimed to evaluate the impacts of acquisition parameters (the main energy window and acquisition time per frame) and reconstruction parameters (the number of iterations, subsets in iterative reconstruction, post-filter, and image correction methods) on the technetium quantification of CZT SPECT/CT.

Methods

A phantom (PET NEMA/IEC image quality, USA) was filled with four target-to-background (T/B) ratios (32:1, 16:1, 8:1, and 4:1) of technetium. Mean uptake values (the calculated mean concentrations for spheres) were measured to evaluate the recovery coefficient (RC) changes under different acquisition and reconstruction parameters. The corresponding standard deviations of mean uptake values were also measured to evaluate the quantification error. Image quality was evaluated using the National Electrical Manufacturers Association (NEMA) NU 2–2012 standard.

Results

For all T/B ratios, significant correlations were found between iterations and RCs (r = 0.62–0.96 for 1–35 iterations, r = 0.94–0.99 for 35–90 iterations) as well as between the full width at half maximum (FWHM) of the Gaussian filter and RCs (r = − 0.86 to − 1.00, all P values < 0.05). The regression coefficients of 1–35 iterations were higher than those of 35–90 iterations (0.51–1.60 vs. 0.02–0.19). RCs calculated with AC (attenuation correction) + SC (scatter correction) + RR (resolution recovery correction) combination were more accurate (53.82–106.70%) than those calculated with other combinations (all P values < 0.05). No significant statistical differences (all P values > 0.05) were found between the 15% and 20% energy windows except for the 32:1 T/B ratio (P value = 0.023) or between the 10 s/frame and 120 s/frame acquisition times except for the 4:1 T/B ratio (P value = 0.015) in terms of RCs.

Conclusions

CZT-SPECT/CT of technetium resulted in good quantification accuracy. The favourable acquisition parameters might be a 15% energy window and 40 s/frame of acquisition time. The favourable reconstruction parameters might be 35 iterations, 20 subsets, the AC + SC + RR correction combination, and no filter.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40658-021-00412-4.

Learning fuzzy clustering for SPECT/CT segmentation via convolutional neural networks

PURPOSE

Quantitative bone single-photon emission computed tomography (QBSPECT) has the potential to provide a better quantitative assessment of bone metastasis than planar bone scintigraphy due to its ability to better quantify activity in overlapping structures. An important element of assessing the response of bone metastasis is accurate image segmentation. However, limited by the properties of QBSPECT images, the segmentation of anatomical regions-of-interests (ROIs) still relies heavily on the manual delineation by experts. This work proposes a fast and robust automated segmentation method for partitioning a QBSPECT image into lesion, bone, and background.

METHODS

We present a new unsupervised segmentation loss function and its semi- and supervised variants for training a convolutional neural network (ConvNet). The loss functions were developed based on the objective function of the classical Fuzzy C-means (FCM) algorithm. The first proposed loss function can be computed within the input image itself without any ground truth labels, and is thus unsupervised; the proposed supervised loss function follows the traditional paradigm of the deep learning-based segmentation methods and leverages ground truth labels during training. The last loss function is a combination of the first and the second and includes a weighting parameter, which enables semi-supervised segmentation using deep learning neural network.

EXPERIMENTS AND RESULTS

We conducted a comprehensive study to compare our proposed methods with ConvNets trained using supervised, cross-entropy and Dice loss functions, and conventional clustering methods. The Dice similarity coefficient (DSC) and several other metrics were used as figures of merit as applied to the task of delineating lesion and bone in both simulated and clinical SPECT/CT images. We experimentally demonstrated that the proposed methods yielded good segmentation results on a clinical dataset even though the training was done using realistic simulated images. On simulated SPECT/CT, the proposed unsupervised model's accuracy was greater than the conventional clustering methods while reducing computation time by 200-fold. For the clinical QBSPECT/CT, the proposed semi-supervised ConvNet model, trained using simulated images, produced DSCs of 0.75 and 0.74 for lesion and bone segmentation in SPECT, and a DSC of 0.79 bone segmentation of CT images. These DSCs were larger than that for standard segmentation loss functions by > 0.4 for SPECT segmentation, and > 0.07 for CT segmentation with P-values < 0.001 from a paired t-test.

CONCLUSIONS

A ConvNet-based image segmentation method that uses novel loss functions was developed and evaluated. The method can operate in unsupervised, semi-supervised, or fully-supervised modes depending on the availability of annotated training data. The results demonstrated that the proposed method provides fast and robust lesion and bone segmentation for QBSPECT/CT. The method can potentially be applied to other medical image segmentation applications.

Prospective SPECT-CT Organ Dosimetry-Driven Radiation-Absorbed Dose Escalation Using the In-111 (111In)/Yttrium 90 (90Y) Ibritumomab Tiuxetan (Zevalin®) Theranostic Pair in Patients with Lymphoma at Myeloablative Dose Levels

Simple Summary

We prospectively evaluated the feasibility of SPECT-CT/planar organ dosimetry-based radiation dose escalation radioimmunotherapy in patients with recurrent non-Hodgkin’s lymphoma using the theranostic pair of ¹¹¹In and ⁹⁰Y anti-CD20 ibritumomab tiuxetan (Zevalin^®) at myeloablative radiation-absorbed doses with autologous stem cell support. Unlike most routine dose escalation approaches, our approach used patient-individualized measurements of organ radiation absorbed dose from the tracer study, with patient-specific adjustments of the injected therapy dose to deliver a pre-specified radiation absorbed dose to the liver. Our approach was feasible, stem cell engraftment was swift, resulted in an 89% tumor response rate in treated patients, demonstrated over 3 fold variability in liver dosimetry/injected activity among patients, allowed us to exceed the FDA approved administered activity by over 5 fold and demonstrated the normal liver maximum tolerated dose to exceed 28 Gy. Dose escalation was not continued due to lack of drug availability. With modern dosimetry approaches, patient specific dosimetry-driven radiation dose escalation is feasible, allows adjustment of administered activity for heterogeneous pharmacokinetics and allows marked dose escalation vs. non-dosimetry driven approaches.

Abstract

Purpose: We prospectively evaluated the feasibility of SPECT-CT/planar organ dosimetry-based radiation dose escalation radioimmunotherapy in patients with recurrent non-Hodgkin’s lymphoma using the theranostic pair of ¹¹¹In and ⁹⁰Y anti-CD20 ibritumomab tiuxetan (Zevalin^®) at myeloablative radiation-absorbed doses with autologous stem cell support. We also assessed acute non-hematopoietic toxicity and early tumor response in this two-center outpatient study. Methods: 24 patients with CD20-positive relapsed or refractory rituximab-sensitive, low-grade, mantle cell, or diffuse large-cell NHL, with normal organ function, platelet counts > 75,000/mm³, and <35% tumor involvement in the marrow were treated with Rituximab (375 mg/m²) weekly for 4 consecutive weeks, then one dose of cyclophosphamide 2.5 g/m² with filgrastim 10 mcg/kg/day until stem cell collection. Of these, 18 patients with successful stem cell collection (at least 2 × 10⁶ CD34 cells/kg) proceeded to RIT. A dosimetric administration of ¹¹¹In ibritumomab tiuxetan (185 MBq) followed by five sequential quantitative planar and one SPECT/CT scan was used to determine predicted organ radiation-absorbed dose. Two weeks later, ⁹⁰Y ibritumomab tiuxetan was administered in an outpatient setting at a cohort- and patient-specific predicted organ radiation-absorbed dose guided by a Continuous Response Assessment (CRM) methodology with the following cohorts for dose escalation: 14.8 MBq/kg, and targeted 18, 24, 28, and 30.5 Gy to the liver. Autologous stem cell infusion occurred when the estimated marrow radiation-absorbed dose rate was predicted to be <1 cGy/h. Feasibility, short-term toxicities, and tumor response were assessed. Results: Patient-specific hybrid SPECT/CT + planar organ dosimetry was feasible in all 18 cases and used to determine the patient-specific therapeutic dose and guide dose escalation (26.8 ± 7.3 MBq/kg (mean), 26.3 MBq/kg (median) of ⁹⁰Y (range: 12.1–41.4 MBq/kg)) of ibritumomab tiuxetan that was required to deliver 10 Gy to the liver. Infused stem cells engrafted rapidly. The most common treatment-related toxicities were hematological and were reversible following stem cell infusion. No significant hepatotoxicity was seen. One patient died from probable treatment-related causes—pneumonia at day 27 post-transplant. One patient at dose level 18 Gy developed myelodysplastic syndrome (MDS), 4 patients required admission post-⁹⁰Y RIT for febrile neutropenia, 16/18 patients receiving ⁹⁰Y ibritumomab tiuxetan (89%) responded to the therapy, with 13 CR (72%) and 3/18 PR (17%), at 60 days post-treatment. Two patients had progressive disease at sixty days. One patient was lost to follow-up. Median time to progression was estimated to be at least 13 months. MTD to the liver is greater than 28 Gy, but the MTD was not reached as the study was terminated due to unexpected discontinuation of availability of the therapeutic agent. Conclusions: Patient-specific outpatient ⁹⁰Y ibritumomab tiuxetan RIT with myeloablative doses of RIT up to a targeted 30.5 Gy to the liver is feasible, guided by prospective SPECT/CT + planar imaging with the theranostic pair of ¹¹¹In and ⁹⁰Y anti-CD20, with outpatient autologous stem cell transplant support. Administered activity over 5 times the standard FDA-approved activity was well-tolerated. The non-hematopoietic MTD in this study exceeds 28 Gy to the liver. Initial tumor responses were common at all dose levels. This study supports the feasibility of organ dosimetry-driven patient-specific dose escalation in the treatment of NHL with stem cell transplant and provides additional information on the radiation tolerance of the normal liver to radiopharmaceutical therapy.

Variability in lutetium-177 SPECT quantification between different state-of-the-art SPECT/CT systems

BACKGROUND

Quantitative SPECT imaging in targeted radionuclide therapy with lutetium-177 holds great potential for individualized treatment based on dose assessment. The establishment of dose-effect relations requires a standardized method for SPECT quantification. The purpose of this multi-center study is to evaluate quantitative accuracy and inter-system variations of different SPECT/CT systems with corresponding commercially available quantitative reconstruction algorithms. This is an important step towards a vendor-independent standard for quantitative lutetium-177 SPECT.

METHODS

Four state-of-the-art SPECT/CT systems were included: Discovery™ NM/CT 670Pro (GE Healthcare), Symbia Intevo™, and two Symbia™ T16 (Siemens Healthineers). Quantitative accuracy and inter-system variations were evaluated by repeatedly scanning a cylindrical phantom with 6 spherical inserts (0.5 - 113 ml). A sphere-to-background activity concentration ratio of 10:1 was used. Acquisition settings were standardized: medium energy collimator, body contour trajectory, photon energy window of 208 keV (± 10%), adjacent 20% lower scatter window, 2 × 64 projections, 128 × 128 matrix size, and 40 s projection time. Reconstructions were performed using GE Evolution with Q.Metrix™, Siemens xSPECT Quant™, Siemens Broad Quantification™ or Siemens Flash3D™ algorithms using vendor recommended settings. In addition, projection data were reconstructed using Hermes SUV SPECT™ with standardized reconstruction settings to obtain a vendor-neutral quantitative reconstruction for all systems. Volumes of interest (VOI) for the spheres were obtained by applying a 50% threshold of the sphere maximum voxel value corrected for background activity. For each sphere, the mean and maximum recovery coefficient (RC_mean and RC_max) of three repeated measurements was calculated, defined as the imaged activity concentration divided by the actual activity concentration. Inter-system variations were defined as the range of RC over all systems.

RESULTS

RC decreased with decreasing sphere volume. Inter-system variations with vendor-specific reconstructions were between 0.06 and 0.41 for RC_mean depending on sphere size (maximum 118% quantification difference), and improved to 0.02-0.19 with vendor-neutral reconstructions (maximum 38% quantification difference).

CONCLUSION

This study shows that eliminating sources of possible variation drastically reduces inter-system variation in quantification. This means that absolute SPECT quantification for ¹⁷⁷Lu is feasible in a multi-center and multi-vendor setting; however, close agreement between vendors and sites is key for multi-center dosimetry and quantitative biomarker studies.

BIGDOSE: software for 3D personalized targeted radionuclide therapy dosimetry

Background

Advance 3D quantitative radionuclide imaging techniques boost the accuracy of targeted radionuclide therapy (TRT) dosimetry to voxel level. The goal of this work is to develop a comprehensive 3D dosimetric software, BIGDOSE, with new features of image registration and virtual CT for patient-specific dosimetry.

Methods

BIGDOSE includes a portable graphical user interface written in Python, integrating (I) input of sequential ECT/CT images; (II) segmentation; (III) non-rigid image registration; (IV) curve fitting and voxel-based integration; (V) dose conversion and (VI) 3D dose analysis. The accuracy of the software was evaluated using a simulation study with 9 XCAT phantoms. We simulated SPECT/CT acquisitions at 1, 12, 24, 72 and 144-hrs post In-111 Zevalin injection with inter-scans misalignments using an analytical projector for medium energy general purpose (MEGP) collimator, modeling attenuation, scatter and collimator-detector response. The SPECT data were reconstructed using quantitative OS-EM method. A CT organ-based registration was performed before the dose calculation. Organ absorbed doses for the corresponding Y-90 therapeutic agent were calculated on target organs and compared with those obtained from OLINDA/EXM, using dose measured from GATE as the gold standard. One patient with In-111 DTPAOC injection as well as two patients with Y-90 microsphere embolization were used to demonstrate the clinical effectiveness of our software.

Results

In the simulation, the organ dose errors of BIGDOSE were -9.59%±9.06%, -8.36±5.82%, -23.41%±6.67%, -6.05%±2.06% for liver, spleen, kidneys and lungs, while they were -25.72%±12.52%, -14.93%±10.91%, -28.63%±12.97% and -45.30%±5.84% for OLINDA/EXM. Cumulative dose volume histograms, dose maps and iso-dose contours provided 3D dose distribution information on the simulated and patient data.

Conclusions

BIGDOSE provides a one-stop platform for voxel-based dose estimation with enhanced functions. It is a promising tool to streamline the current clinical TRT dosimetric practice with high accuracy, incorporating 3D personalized imaging information for improved treatment outcome.

Towards standardization of absolute SPECT/CT quantification: a multi-center and multi-vendor phantom study

Abstract

Absolute quantification of radiotracer distribution using SPECT/CT imaging is of great importance for dosimetry aimed at personalized radionuclide precision treatment. However, its accuracy depends on many factors. Using phantom measurements, this multi-vendor and multi-center study evaluates the quantitative accuracy and inter-system variability of various SPECT/CT systems as well as the effect of patient size, processing software and reconstruction algorithms on recovery coefficients (RC).

Methods

Five SPECT/CT systems were included: Discovery™ NM/CT 670 Pro (GE Healthcare), Precedence™ 6 (Philips Healthcare), Symbia Intevo™, and Symbia™ T16 (twice) (Siemens Healthineers). Three phantoms were used based on the NEMA IEC body phantom without lung insert simulating body mass indexes (BMI) of 25, 28, and 47 kg/m². Six spheres (0.5–26.5 mL) and background were filled with 0.1 and 0.01 MBq/mL ^99mTc-pertechnetate, respectively. Volumes of interest (VOI) of spheres were obtained by a region growing technique using a 50% threshold of the maximum voxel value corrected for background activity. RC, defined as imaged activity concentration divided by actual activity concentration, were determined for maximum (RC_max) and mean voxel value (RC_mean) in the VOI for each sphere diameter. Inter-system variability was expressed as median absolute deviation (MAD) of RC. Acquisition settings were standardized. Images were reconstructed using vendor-specific 3D iterative reconstruction algorithms with institute-specific settings used in clinical practice and processed using a standardized, in-house developed processing tool based on the SimpleITK framework. Additionally, all data were reconstructed with a vendor-neutral reconstruction algorithm (Hybrid Recon™; Hermes Medical Solutions).

Results

RC decreased with decreasing sphere diameter for each system. Inter-system variability (MAD) was 16 and 17% for RC_mean and RC_max, respectively. Standardized reconstruction decreased this variability to 4 and 5%. High BMI hampers quantification of small lesions (< 10 ml).

Conclusion

Absolute SPECT quantification in a multi-center and multi-vendor setting is feasible, especially when reconstruction protocols are standardized, paving the way for a standard for absolute quantitative SPECT.

A method for tumor dosimetry based on hybrid planar-SPECT/CT images and semiautomatic segmentation

PURPOSE

A hybrid planar-SPECT/CT method for tumor dosimetry in 177 Lu-DOTATATE therapy, applicable to datasets consisting of multiple conjugate-view images and one SPECT/CT, is developed and evaluated.

METHODS

The imaging protocol includes conjugate-view imaging at 1, 24, 96, and 168 h post infusion (p.i.) and a SPECT/CT acquisition 24 h p.i. The dosimetry method uses the planar images to estimate the shape of the time-activity concentration curve, which is then rescaled to absolute units using the SPECT-derived activity concentration. The resulting time-integrated activity concentration coefficient (TIACC) is used to calculate the tumor-absorbed dose. Semiautomatic segmentation techniques are applied for tumor delineation in both planar and SPECT images, where the planar image segmentation is accomplished using an active-rays-based technique. The selection of tumors is done by visual inspection of planar and SPECT images and applying a set of criteria concerning the tumor visibility and possible interference from superimposed activity uptakes in the planar images. Five different strategies for determining values from planar regions of interest (ROIs), based on entire or partial ROIs, and with and without background correction, are evaluated. Evaluation is performed against a SPECT/CT-based method on data from six patients where sequential conjugate-view and SPECT/CT imaging have been performed in parallel and against ground truths in Monte Carlo simulated images. The patient data are also used to evaluate the interoperator variability and to assess the validity of the developed criteria for tumor selection.

RESULTS

For patient images, the hybrid method produces TIACCs that are on average 6% below those of the SPECT/CT only method, with standard deviations for the relative TIACC differences of 8%-11%. Simulations show that the hybrid and SPECT-based methods estimate the TIACCs to within approximately 10% for tumors larger than around 10 ml, while for smaller tumors, all methods underestimate the TIACCs due to underestimations of the activity concentrations in the SPECT images. The planar image segmentation has a low operator dependence, with a median Dice similarity coefficient of 0.97 between operators. The adopted criteria for tumor selection manage to discriminate the tumors for which the absorbed-dose deviations between the hybrid and SPECT methods are the highest.

CONCLUSIONS

The hybrid method is found suitable for studies of tumor-absorbed doses in radionuclide therapy, provided that selection criteria regarding the visibility and overlapping activities in the planar images are applied.

Quantitative Imaging for Targeted Radionuclide Therapy Dosimetry - Technical Review

Targeted radionuclide therapy (TRT) is a promising technique for cancer therapy. However, in order to deliver the required dose to the tumor, minimize potential toxicity in normal organs, as well as monitor therapeutic effects, it is important to assess the individualized internal dosimetry based on patient-specific data. Advanced imaging techniques, especially radionuclide imaging, can be used to determine the spatial distribution of administered tracers for calculating the organ-absorbed dose. While planar scintigraphy is still the mainstream imaging method, SPECT, PET and bremsstrahlung imaging have promising properties to improve accuracy in quantification. This article reviews the basic principles of TRT and discusses the latest development in radionuclide imaging techniques for different theranostic agents, with emphasis on their potential to improve personalized TRT dosimetry.

Strengths and Weaknesses of a Planar Whole-Body Method of (153)Sm Dosimetry for Patients with Metastatic Osteosarcoma and Comparison with Three-Dimensional Dosimetry

PURPOSE

Dosimetric accuracy depends directly upon the accuracy of the activity measurements in tumors and organs. The authors present the methods and results of a retrospective tumor dosimetry analysis in 14 patients with a total of 28 tumors treated with high activities of (153)Sm-ethylenediaminetetramethylenephosphonate ((153)Sm-EDTMP) for therapy of metastatic osteosarcoma using planar images and compare the results with three-dimensional dosimetry.

MATERIALS AND METHODS

Analysis of phantom data provided a complete set of parameters for dosimetric calculations, including buildup factor, attenuation coefficient, and camera dead-time compensation. The latter was obtained using a previously developed methodology that accounts for the relative motion of the camera and patient during whole-body (WB) imaging. Tumor activity values calculated from the anterior and posterior views of WB planar images of patients treated with (153)Sm-EDTMP for pediatric osteosarcoma were compared with the geometric mean value. The mean activities were integrated over time and tumor-absorbed doses were calculated using the software package OLINDA/EXM.

RESULTS

The authors found that it was necessary to employ the dead-time correction algorithm to prevent measured tumor activity half-lives from often exceeding the physical decay half-life of (153)Sm. Measured half-lives so long are unquestionably in error. Tumor-absorbed doses varied between 0.0022 and 0.27 cGy/MBq with an average of 0.065 cGy/MBq; however, a comparison with absorbed dose values derived from a three-dimensional analysis for the same tumors showed no correlation; moreover, the ratio of three-dimensional absorbed dose value to planar absorbed dose value was 2.19. From the anterior and posterior activity comparisons, the order of clinical uncertainty for activity and dose calculations from WB planar images, with the present methodology, is hypothesized to be about 70%.

CONCLUSION

The dosimetric results from clinical patient data indicate that absolute planar dosimetry is unreliable and dosimetry using three-dimensional imaging is preferable, particularly for tumors, except perhaps for the most sophisticated planar methods. The relative activity and patient kinetics derived from planar imaging show a greater level of reliability than the dosimetry.

A study of SPECT/CT camera stability for quantitative imaging

Background

The purpose of this study was twofold: to evaluate the quantitative stability of a SPECT/CT gamma camera over time and to determine if daily flood acquisitions can reliably serve as calibration factors for quantitative SPECT. Using a cylindrical water phantom filled with measured amounts of ^99mTc, factors were calculated to convert counts/cc to activity/cps. Measurements were made over an 18-month period. System sensitivity data calculated from ⁵⁷Co daily quality assurance (DQA) flood acquisitions were then compared to the ^99mTc calibration factors to determine the relationship of the factors.

Results

The coefficient of variation is 2.7 % for the ^99mTc cylinder conversion factors and 2.6 % for the ⁵⁷Co DQA flood data. The greatest difference between the cylinder conversion factors and the flood data is less than 3 %.

Conclusions

Based on the results, the camera was stable within 3 % over an 18-month time period. The daily flood source acquisitions can be a reliable source for tracking camera stability and may provide information on updating the calibration factor for quantitative imaging.

Development and evaluation of convergent and accelerated penalized SPECT image reconstruction methods for improved dose-volume histogram estimation in radiopharmaceutical therapy

PURPOSE

Three-dimensional (3D) dosimetry has the potential to provide better prediction of response of normal tissues and tumors and is based on 3D estimates of the activity distribution in the patient obtained from emission tomography. Dose-volume histograms (DVHs) are an important summary measure of 3D dosimetry and a widely used tool for treatment planning in radiation therapy. Accurate estimates of the radioactivity distribution in space and time are desirable for accurate 3D dosimetry. The purpose of this work was to develop and demonstrate the potential of penalized SPECT image reconstruction methods to improve DVHs estimates obtained from 3D dosimetry methods.

METHODS

The authors developed penalized image reconstruction methods, using maximum a posteriori (MAP) formalism, which intrinsically incorporate regularization in order to control noise and, unlike linear filters, are designed to retain sharp edges. Two priors were studied: one is a 3D hyperbolic prior, termed single-time MAP (STMAP), and the second is a 4D hyperbolic prior, termed cross-time MAP (CTMAP), using both the spatial and temporal information to control noise. The CTMAP method assumed perfect registration between the estimated activity distributions and projection datasets from the different time points. Accelerated and convergent algorithms were derived and implemented. A modified NURBS-based cardiac-torso phantom with a multicompartment kidney model and organ activities and parameters derived from clinical studies were used in a Monte Carlo simulation study to evaluate the methods. Cumulative dose-rate volume histograms (CDRVHs) and cumulative DVHs (CDVHs) obtained from the phantom and from SPECT images reconstructed with both the penalized algorithms and OS-EM were calculated and compared both qualitatively and quantitatively. The STMAP method was applied to patient data and CDRVHs obtained with STMAP and OS-EM were compared qualitatively.

RESULTS

The results showed that the penalized algorithms substantially improved the CDRVH and CDVH estimates for large organs such as the liver compared to optimally postfiltered OS-EM. For example, the mean squared errors (MSEs) of the CDRVHs for the liver at 5 h postinjection obtained with CTMAP and STMAP were about 15% and 17%, respectively, of the MSEs obtained with optimally filtered OS-EM. For the CDVH estimates, the MSEs obtained with CTMAP and STMAP were about 16% and 19%, respectively, of the MSEs from OS-EM. For the kidneys and renal cortices, larger residual errors were observed for all algorithms, likely due to partial volume effects. The STMAP method showed promising qualitative results when applied to patient data.

CONCLUSIONS

Penalized image reconstruction methods were developed and evaluated through a simulation study. The study showed that the MAP algorithms substantially improved CDVH estimates for large organs such as the liver compared to optimally postfiltered OS-EM reconstructions. For small organs with fine structural detail such as the kidneys, a large residual error was observed for both MAP algorithms and OS-EM. While CTMAP provided marginally better MSEs than STMAP, given the extra effort needed to handle misregistration of images at different time points in the algorithm and the potential impact of residual misregistration, 3D regularization methods, such as that used in STMAP, appear to be a more practical choice.

Factors affecting the repeatability of gamma camera calibration for quantitative imaging applications using a sealed source

Several applications in nuclear medicine require absolute activity quantification of single photon emission computed tomography images. Obtaining a repeatable calibration factor that converts voxel values to activity units is essential for these applications. Because source preparation and measurement of the source activity using a radionuclide activity meter are potential sources of variability, this work investigated instrumentation and acquisition factors affecting repeatability using planar acquisition of sealed sources. The calibration factor was calculated for different acquisition and geometry conditions to evaluate the effect of the source size, lateral position of the source in the camera field-of-view (FOV), source-to-camera distance (SCD), and variability over time using sealed Ba-133 sources. A small region of interest (ROI) based on the source dimensions and collimator resolution was investigated to decrease the background effect. A statistical analysis with a mixed-effects model was used to evaluate quantitatively the effect of each variable on the global calibration factor variability. A variation of 1 cm in the measurement of the SCD from the assumed distance of 17 cm led to a variation of 1-2% in the calibration factor measurement using a small disc source (0.4 cm diameter) and less than 1% with a larger rod source (2.9 cm diameter). The lateral position of the source in the FOV and the variability over time had small impacts on calibration factor variability. The residual error component was well estimated by Poisson noise. Repeatability of better than 1% in a calibration factor measurement using a planar acquisition of a sealed source can be reasonably achieved. The best reproducibility was obtained with the largest source with a count rate much higher than the average background in the ROI, and when the SCD was positioned within 5 mm of the desired position. In this case, calibration source variability was limited by the quantum noise.

Factors affecting the stability and repeatability of gamma camera calibration for quantitative imaging applications based on a retrospective review of clinical data

BACKGROUND

Absolute quantitative single-photon emission computed tomography (SPECT) has several important applications including monitoring tumor response after treatment and dose estimation for targeted radionuclide therapy treatment planning. Obtaining quantitative SPECT images in absolute activity units requires the use of a calibration factor, and the repeatability of this directly affects the repeatability of image quantification. This study focused on evaluating the factors affecting the repeatability of a calibration factor measured using a planar image of an in-air calibration source.

METHODS

The calibration factors calculated as part of (131)I-tositumomab patient dosimetry scans used in treatment planning performed over a 4-year period were retrospectively analyzed. Raw data included total counts in whole-body images of a radioactive calibration source, the activity of the source measured in a radionuclide activity meter (often referred to as a dose calibrator), and the background count rate obtained at three time points for each patient. The count rate from extrinsic flood source acquisitions and radionuclide activity meter constancy obtained on the same day as each image were also used. The data were analyzed statistically using a mixed-effects model to determine the factors affecting variations in the measured calibration factors.

RESULTS

The global variability in the calibration factor was equal to 2.3% and was decreased by 20% to 1.8%, when the decay-corrected measurements of calibration source activity were averaged over the three time points for each patient. Camera sensitivity variation measured using a (57)Co sheet source was small and had a weak relationship to calibration factor variations. When the averaged source activity was used, the main source of variance was related to preparation and measurement of the source (77%). Radionuclide activity meter constancy had a smaller but statistically significant impact on the calibration factor.

CONCLUSIONS

This study indicates that calibration factors based on planar measurements have good reproducibility. The findings of this study indicate (1) the importance of accurate and precise preparation and measurement of the calibration source activity, (2) the need to carefully control background activity during calibration factor assessment and patient data acquisition, and (3) that the calibration factor and camera sensitivity were stable over time, indicating that careful but less frequent calibration is needed.

Three-dimensional personalized dosimetry for 188Re liver selective internal radiation therapy based on quantitative post-treatment SPECT studies

We demonstrate that accurate patient-specific distributions of microspheres labeled with ¹⁸⁸Re and resulting absorbed doses can be obtained from single-photon emission computed tomography (SPECT) studies performed after ¹⁸⁸Re selective internal radiation therapy when accurate correction methods are employed in image reconstruction. Our quantitative image reconstruction algorithm includes corrections for attenuation, resolution degradations and scatter as well as a window-based compensation for contamination. The procedure has been validated using four phantom experiments containing an 18 ml cylindrical source (82-93 MBq of ¹⁸⁸Re activity) simulating a liver tumor. In addition, we applied our approach to post-therapy SPECT studies of ten patients with progressive primary or metastatic liver carcinomas. Our quantitative algorithm accurately (within 9%) recovered ¹⁸⁸Re activity from four phantom experiments. In addition, for two patients that received three scans, deviations remained consistent between the measured and the reconstructed activities that were determined from studies with differing severity of the dead-time effect. The analysis of absorbed doses for patient studies allowed us to hypothesize that D90 (the minimum dose received by 90% of the tumor volume) may be a reliable metric relating therapy outcomes to the calculated doses. Among several considered metrics, only D90 showed statistically significant correlation with the overall survival.

Improved dose-volume histogram estimates for radiopharmaceutical therapy by optimizing quantitative SPECT reconstruction parameters

In radiopharmaceutical therapy, an understanding of the dose distribution in normal and target tissues is important for optimizing treatment. Three-dimensional (3D) dosimetry takes into account patient anatomy and the nonuniform uptake of radiopharmaceuticals in tissues. Dose-volume histograms (DVHs) provide a useful summary representation of the 3D dose distribution and have been widely used for external beam treatment planning. Reliable 3D dosimetry requires an accurate 3D radioactivity distribution as the input. However, activity distribution estimates from SPECT are corrupted by noise and partial volume effects (PVEs). In this work, we systematically investigated OS-EM based quantitative SPECT (QSPECT) image reconstruction in terms of its effect on DVHs estimates. A modified 3D NURBS-based Cardiac-Torso (NCAT) phantom that incorporated a non-uniform kidney model and clinically realistic organ activities and biokinetics was used. Projections were generated using a Monte Carlo (MC) simulation; noise effects were studied using 50 noise realizations with clinical count levels. Activity images were reconstructed using QSPECT with compensation for attenuation, scatter and collimator-detector response (CDR). Dose rate distributions were estimated by convolution of the activity image with a voxel S kernel. Cumulative DVHs were calculated from the phantom and QSPECT images and compared both qualitatively and quantitatively. We found that noise, PVEs, and ringing artifacts due to CDR compensation all degraded histogram estimates. Low-pass filtering and early termination of the iterative process were needed to reduce the effects of noise and ringing artifacts on DVHs, but resulted in increased degradations due to PVEs. Large objects with few features, such as the liver, had more accurate histogram estimates and required fewer iterations and more smoothing for optimal results. Smaller objects with fine details, such as the kidneys, required more iterations and less smoothing at early time points post-radiopharmaceutical administration but more smoothing and fewer iterations at later time points when the total organ activity was lower. The results of this study demonstrate the importance of using optimal reconstruction and regularization parameters. Optimal results were obtained with different parameters at each time point, but using a single set of parameters for all time points produced near-optimal dose-volume histograms.

An evidence-based review of quantitative SPECT imaging and potential clinical applications

SPECT has traditionally been regarded as nonquantitative. Advances in multimodality γ-cameras (SPECT/CT), algorithms for image reconstruction, and sophisticated compensation techniques to correct for photon attenuation and scattering have, however, now made quantitative SPECT viable in a manner similar to quantitative PET (i.e., kBq cm(-3), standardized uptake value). This review examines the evidence for quantitative SPECT and demonstrates clinical studies in which the accuracy of the reconstructed SPECT data has been assessed in vivo. SPECT reconstructions using CT-based compensation corrections readily achieve accuracy for (99m)Tc to within ± 10% of the known concentration of the radiotracer in vivo. Quantification with other radionuclides is also being introduced. SPECT continues to suffer from poorer photon detection efficiency (sensitivity) and spatial resolution than PET; however, it has the benefit in some situations of longer radionuclide half-lives, which may better suit the biologic process under examination, as well as the ability to perform multitracer studies using pulse height spectroscopy to separate different radiolabels.

Two methods to generate templates for template-based partial volume effect correction: SPECT phantom experiments

In this paper, we explore the applicability of template-based compensation for the partial volume effect (PVE) for situations where (i) the image has multiple uptake sites (tumors and organs) but only one of them is treated as a region of interest (ROI) with the boundaries available from a high-resolution modality and (ii) no information regarding activities inside or outside this ROI is a priori available. We modeled this situation by performing SPECT acquisitions of phantoms containing 21 containers, which had different shapes and sizes and were filled with different levels of activity. In our analysis, each of these containers was treated as an individual ROI. We compared the performance of two methods of template construction. In method 1, the ROI template value was obtained from a conventionally reconstructed (without PVEC) image. In method 2, the ROI template value was directly (bypassing the PVE-affected conventional image) calculated from projections using region-based reconstruction. Our processing shows that method 1 resulted in consistent (activities for all 21 ROIs were improved) but relatively weak PVE compensation (errors of recovered total activities were equal to or lower than 10% for 5 ROIs only). Application of method 2 resulted in a selective (activities for 19 ROIs were improved) but considerably better compensation when compared to method 1 (errors of recovered total activities were equal to or lower than 10% for 10 ROIs).

Development of (99m)Tc-EC-tyrosine for early detection of breast cancer tumor response to the anticancer drug melphalan

RATIONALE AND OBJECTIVES

Radiolabeled tyrosine analogues that have been successfully used in tumor imaging accumulate in tumor cells via an upregulated L-type amino acid transporter system. The anticancer drug melphalan is an L-type amino acid transporter substrate. Therefore, radiolabeled tyrosine analogues may have great potential in evaluating treatment responses to melphalan. In this study, a (99m)Tc-labeled tyrosine analogue, (99m)Tc tyrosine using N,N'-ethylene-di-L-cysteine (EC) as a chelator, was developed and its potential for noninvasively assessing tumors' early response to melphalan determined.

MATERIALS AND METHODS

EC-tyrosine was synthesized in a three-step procedure and labeled with (99m)Tc. To assess cellular uptake kinetics, the percentage uptake of (99m)Tc-EC-tyrosine in the rat breast cancer cell line 13762 was measured. Planar imaging was performed in rats with 13762 cell-derived tumors. To determine the transport mechanisms of (99m)Tc-EC-tyrosine, a competitive inhibition study using L-tyrosine as an inhibitor was performed in vitro and in vivo. To assess tumors' response to melphalan, tumor-bearing rats were treated with different doses of melphalan, and planar imaging was performed 0 and 3 days after treatment. Immunohistochemical analyses were conducted to determine expressions of L-type amino acid transporter 1 and cellular proliferation marker Ki-67.

RESULTS

L-tyrosine significantly inhibited (99m)Tc-EC-tyrosine uptake in vitro and in vivo. Tumor volume decreased in a dose-dependent manner with melphalan, and tumor/muscle ratios of (99m)Tc-EC-tyrosine were significantly reduced in treated groups. Immunohistochemical data indicated that about 70% of tumor cells in the melphalan-treated groups underwent apoptosis, and the changes in tumor/muscle ratios reflected the decreased percentage of viable cells in treated tumors.

CONCLUSIONS

These findings suggest that (99m)Tc-EC-tyrosine has great potential for monitoring tumor response to melphalan in breast tumor-bearing rats.

Study of the impact of tissue density heterogeneities on 3-dimensional abdominal dosimetry: comparison between dose kernel convolution and direct Monte Carlo methods

Dose kernel convolution (DK) methods have been proposed to speed up absorbed dose calculations in molecular radionuclide therapy. Our aim was to evaluate the impact of tissue density heterogeneities (TDH) on dosimetry when using a DK method and to propose a simple density-correction method.

METHODS

This study has been conducted on 3 clinical cases: case 1, non-Hodgkin lymphoma treated with (131)I-tositumomab; case 2, a neuroendocrine tumor treatment simulated with (177)Lu-peptides; and case 3, hepatocellular carcinoma treated with (90)Y-microspheres. Absorbed dose calculations were performed using a direct Monte Carlo approach accounting for TDH (3D-RD), and a DK approach (VoxelDose, or VD). For each individual voxel, the VD absorbed dose, D(VD), calculated assuming uniform density, was corrected for density, giving D(VDd). The average 3D-RD absorbed dose values, D(3DRD), were compared with D(VD) and D(VDd), using the relative difference Δ(VD/3DRD). At the voxel level, density-binned Δ(VD/3DRD) and Δ(VDd/3DRD) were plotted against ρ and fitted with a linear regression.

RESULTS

The D(VD) calculations showed a good agreement with D(3DRD). Δ(VD/3DRD) was less than 3.5%, except for the tumor of case 1 (5.9%) and the renal cortex of case 2 (5.6%). At the voxel level, the Δ(VD/3DRD) range was 0%-14% for cases 1 and 2, and -3% to 7% for case 3. All 3 cases showed a linear relationship between voxel bin-averaged Δ(VD/3DRD) and density, ρ: case 1 (Δ = -0.56ρ + 0.62, R(2) = 0.93), case 2 (Δ = -0.91ρ + 0.96, R(2) = 0.99), and case 3 (Δ = -0.69ρ + 0.72, R(2) = 0.91). The density correction improved the agreement of the DK method with the Monte Carlo approach (Δ(VDd/3DRD) < 1.1%), but with a lesser extent for the tumor of case 1 (3.1%). At the voxel level, the Δ(VDd/3DRD) range decreased for the 3 clinical cases (case 1, -1% to 4%; case 2, -0.5% to 1.5%, and -1.5% to 2%). No more linear regression existed for cases 2 and 3, contrary to case 1 (Δ = 0.41ρ - 0.38, R(2) = 0.88) although the slope in case 1 was less pronounced.

CONCLUSION

This study shows a small influence of TDH in the abdominal region for 3 representative clinical cases. A simple density-correction method was proposed and improved the comparison in the absorbed dose calculations when using our voxel S value implementation.

Accuracy and precision of radioactivity quantification in nuclear medicine images

The ability to reliably quantify activity in nuclear medicine has a number of increasingly important applications. Dosimetry for targeted therapy treatment planning or for approval of new imaging agents requires accurate estimation of the activity in organs, tumors, or voxels at several imaging time points. Another important application is the use of quantitative metrics derived from images, such as the standard uptake value commonly used in positron emission tomography (PET), to diagnose and follow treatment of tumors. These measures require quantification of organ or tumor activities in nuclear medicine images. However, there are a number of physical, patient, and technical factors that limit the quantitative reliability of nuclear medicine images. There have been a large number of improvements in instrumentation, including the development of hybrid single-photon emission computed tomography/computed tomography and PET/computed tomography systems, and reconstruction methods, including the use of statistical iterative reconstruction methods, which have substantially improved the ability to obtain reliable quantitative information from planar, single-photon emission computed tomography, and PET images.

Performance evaluation of PETbox: a low cost bench top preclinical PET scanner

Purpose

PETbox is a low cost bench top preclinical PET scanner dedicated to pharmacokinetic and pharmacodynamic mouse studies. A prototype system was developed at our institute, and this manuscript characterizes the performance of the prototype system.

Procedures

The PETbox detector consists of a 20 × 44 bismuth germanate crystal array with a thickness of 5 mm and cross-section size of 2.05 × 2.05 mm. Two such detectors are placed facing each other at a spacing of 5 cm, forming a dual-head geometry optimized for imaging mice. The detectors are kept stationary during the scan, making PETbox a limited angle tomography system. 3D images are reconstructed using a maximum likelihood and expectation maximization (ML–EM) method. The performance of the prototype system was characterized based on a modified set of the NEMA NU 4-2008 standards.

Results

In-plane image spatial resolution was measured to be an average of 1.53 mm full width at half maximum for coronal images and 2.65 mm for the anterior–posterior direction. The volumetric reconstructed resolution was below 8 mm³ at most locations in the field of view (FOV). The sensitivity, scatter fraction, and noise equivalent count rate (NECR) were measured for different energy windows. With an energy window of 150 - 650 keV and a timing window of 20 ns optimized for mouse imaging, the peak absolute sensitivity was 3.99% at the center of FOV and a peak NECR of 20 kcps was achieved for a total activity of 3.2 MBq (86.8 μCi). Phantom and in vivo imaging studies were performed and demonstrated the utility of the system at low activity levels. The quantitation capabilities of the system were also characterized showing that despite the limited angle tomography, reasonably good quantification accuracy was achieved over a large dynamic range of activity levels.

Conclusions

The presented results demonstrate the potential of this new tomograph for small animal imaging.

EQPlanar: a maximum-likelihood method for accurate organ activity estimation from whole body planar projections

Optimizing targeted radionuclide therapy requires patient-specific estimation of organ doses. The organ doses are estimated from quantitative nuclear medicine imaging studies, many of which involve planar whole body scans. We have previously developed the quantitative planar (QPlanar) processing method and demonstrated its ability to provide more accurate activity estimates than conventional geometric-mean-based planar (CPlanar) processing methods using physical phantom and simulation studies. The QPlanar method uses the maximum likelihood-expectation maximization algorithm, 3D organ volume of interests (VOIs), and rigorous models of physical image degrading factors to estimate organ activities. However, the QPlanar method requires alignment between the 3D organ VOIs and the 2D planar projections and assumes uniform activity distribution in each VOI. This makes application to patients challenging. As a result, in this paper we propose an extended QPlanar (EQPlanar) method that provides independent-organ rigid registration and includes multiple background regions. We have validated this method using both Monte Carlo simulation and patient data. In the simulation study, we evaluated the precision and accuracy of the method in comparison to the original QPlanar method. For the patient studies, we compared organ activity estimates at 24 h after injection with those from conventional geometric mean-based planar quantification using a 24 h post-injection quantitative SPECT reconstruction as the gold standard. We also compared the goodness of fit of the measured and estimated projections obtained from the EQPlanar method to those from the original method at four other time points where gold standard data were not available. In the simulation study, more accurate activity estimates were provided by the EQPlanar method for all the organs at all the time points compared with the QPlanar method. Based on the patient data, we concluded that the EQPlanar method provided a substantial increase in accuracy of organ activity estimates from 24 h planar images compared to the CPlanar using 24 h SPECT as the golden standard. For other time points, where no golden standard is available, better agreement between estimated and measured projections was observed by using the EQPlanar method compared to the QPlanar method. This phenomenon is consistent with the improvement in goodness of fit seen in both simulation data and 24 h patient data. Therefore, this indicates the improved reliability of organ activity estimates obtained though the EQPlanar method.

Quantitative (177)Lu SPECT (QSPECT) imaging using a commercially available SPECT/CT system

Purpose: The combination of single photon emission computed tomography (SPECT) and computer tomography (CT) that incorporates iterative reconstruction algorithms with attenuation and scatter correction should facilitate accurate non-invasive quantitative imaging. Quantitative SPECT (QSPECT) may improve diagnostic ability and could be useful for many applications including dosimetry assessment. Using ¹⁷⁷Lu, we developed a QSPECT method using a commercially available SPECT/CT system. Methods: Serial SPECT of ¹⁷⁷Lu sources (89–12,400 MBq) were acquired with multiple contiguous energy windows along with a co-registered CT, and were reconstructed using an iterative algorithm with attenuation and scatter correction. Camera sensitivity (based on reconstructed SPECT count rate) and dead-time (based on wide-energy spectrum count rate) were resolved by non-linear curve fit. Utilizing these parameters, a SPECT dataset can be converted to a QSPECT dataset allowing quantitation in Becquerels per cubic centimetre or standardized uptake value (SUV). Validation QSPECT/CT studies were performed on a ¹⁷⁷Lu cylindrical phantom (7 studies) and on 5 patients (6 studies) who were administered a therapeutic dose of [¹⁷⁷Lu]octreotate. Results: The QSPECT sensitivity was 1.08 × 10⁻⁵± 0.02 × 10⁻⁵ s⁻¹ Bq⁻¹. The paralyzing dead-time constant was 0.78 ± 0.03 µs. The measured total activity with QSPECT deviated from the calibrated activity by 5.6 ± 1.9% and 2.6 ± 1.8%, respectively, in phantom and patients. Dead-time count loss up to 11.7% was observed in patient studies. Conclusion: QSPECT has high accuracy both in our phantom model and in clinical practice following [¹⁷⁷Lu]octreotate therapy. This has the potential to yield more accurate dosimetry estimates than planar imaging and facilitate therapeutic response assessment. Validating this method with other radionuclides could open the way for many other research and clinical applications.

Development and evaluation of a model-based downscatter compensation method for quantitative I-131 SPECT

PURPOSE

The radionuclide 131I has found widespread use in targeted radionuclide therapy (TRT), partly due to the fact that it emits photons that can be imaged to perform treatment planning or posttherapy dose verification as well as beta rays that are suitable for therapy. In both the treatment planning and dose verification applications, it is necessary to estimate the activity distribution in organs or tumors at several time points. In vivo estimates of the 131I activity distribution at each time point can be obtained from quantitative single-photon emission computed tomography (QSPECT) images and organ activity estimates can be obtained either from QSPECT images or quantification of planar projection data. However, in addition to the photon used for imaging, 131I decay results in emission of a number of other higher-energy photons with significant abundances. These higher-energy photons can scatter in the body, collimator, or detector and be counted in the 364 keV photopeak energy window, resulting in reduced image contrast and degraded quantitative accuracy; these photons are referred to as downscatter. The goal of this study was to develop and evaluate a model-based downscatter compensation method specifically designed for the compensation of high-energy photons emitted by 131I and detected in the imaging energy window.

METHODS

In the evaluation study, we used a Monte Carlo simulation (MCS) code that had previously been validated for other radionuclides. Thus, in preparation for the evaluation study, we first validated the code for 131I imaging simulation by comparison with experimental data. Next, we assessed the accuracy of the downscatter model by comparing downscatter estimates with MCS results. Finally, we combined the downscatter model with iterative reconstruction-based compensation for attenuation (A) and scatter (S) and the full (D) collimator-detector response of the 364 keV photons to form a comprehensive compensation method. We evaluated this combined method in terms of quantitative accuracy using the realistic 3D NCAT phantom and an activity distribution obtained from patient studies. We compared the accuracy of organ activity estimates in images reconstructed with and without addition of downscatter compensation from projections with and without downscatter contamination.

RESULTS

We observed that the proposed method provided substantial improvements in accuracy compared to no downscatter compensation and had accuracies comparable to reconstructions from projections without downscatter contamination.

CONCLUSIONS

The results demonstrate that the proposed model-based downscatter compensation method is effective and may have a role in quantitative 131I imaging.

Image quantification for radiation dose calculations--limitations and uncertainties

Radiation dose calculations in nuclear medicine depend on quantification of activity via planar and/or tomographic imaging methods. However, both methods have inherent limitations, and the accuracy of activity estimates varies with object size, background levels, and other variables. The goal of this study was to evaluate the limitations of quantitative imaging with planar and single photon emission computed tomography (SPECT) approaches, with a focus on activity quantification for use in calculating absorbed dose estimates for normal organs and tumors. To do this we studied a series of phantoms of varying complexity of geometry, with three radionuclides whose decay schemes varied from simple to complex. Four aqueous concentrations of ⁹⁹mTc, ¹³¹I, and ¹¹¹In (74, 185, 370, and 740 kBq mL⁻¹) were placed in spheres of four different sizes in a water-filled phantom, with three different levels of activity in the surrounding water. Planar and SPECT images of the phantoms were obtained on a modern SPECT/computed tomography (CT) system. These radionuclides and concentration/background studies were repeated using a cardiac phantom and a modified torso phantom with liver and "tumor" regions containing the radionuclide concentrations and with the same varying background levels. Planar quantification was performed using the geometric mean approach, with attenuation correction (AC), and with and without scatter corrections (SC and NSC). SPECT images were reconstructed using attenuation maps (AM) for AC; scatter windows were used to perform SC during image reconstruction. For spherical sources with corrected data, good accuracy was observed (generally within ±10% of known values) for the largest sphere (11.5 mL) and for both planar and SPECT methods with ⁹⁹mTc and ¹³¹I, but were poorest and deviated from known values for smaller objects, most notably for ¹¹¹In. SPECT quantification was affected by the partial volume effect in smaller objects and generally showed larger errors than the planar results in these cases for all radionuclides. For the cardiac phantom, results were the most accurate of all of the experiments for all radionuclides. Background subtraction was an important factor influencing these results. The contribution of scattered photons was important in quantification with ¹³¹I; if scatter was not accounted for, activity tended to be overestimated using planar quantification methods. For the torso phantom experiments, results show a clear underestimation of activity when compared to previous experiment with spherical sources for all radionuclides. Despite some variations that were observed as the level of background increased, the SPECT results were more consistent across different activity concentrations. Planar or SPECT quantification on state-of-the-art gamma cameras with appropriate quantitative processing can provide accuracies of better than 10% for large objects and modest target-to-background concentrations; however when smaller objects are used, in the presence of higher background, and for nuclides with more complex decay schemes, SPECT quantification methods generally produce better results.

The effect of volume-of-interest misregistration on quantitative planar activity and dose estimation

In targeted radionuclide therapy (TRT), dose estimation is essential for treatment planning and tumor dose response studies. Dose estimates are typically based on a time series of whole-body conjugate view planar or SPECT scans of the patient acquired after administration of a planning dose. Quantifying the activity in the organs from these studies is an essential part of dose estimation. The quantitative planar (QPlanar) processing method involves accurate compensation for image degrading factors and correction for organ and background overlap via the combination of computational models of the image formation process and 3D volumes of interest defining the organs to be quantified. When the organ VOIs are accurately defined, the method intrinsically compensates for attenuation, scatter and partial volume effects, as well as overlap with other organs and the background. However, alignment between the 3D organ volume of interest (VOIs) used in QPlanar processing and the true organ projections in the planar images is required. The aim of this research was to study the effects of VOI misregistration on the accuracy and precision of organ activity estimates obtained using the QPlanar method. In this work, we modeled the degree of residual misregistration that would be expected after an automated registration procedure by randomly misaligning 3D SPECT/CT images, from which the VOI information was derived, and planar images. Mutual information-based image registration was used to align the realistic simulated 3D SPECT images with the 2D planar images. The residual image misregistration was used to simulate realistic levels of misregistration and allow investigation of the effects of misregistration on the accuracy and precision of the QPlanar method. We observed that accurate registration is especially important for small organs or ones with low activity concentrations compared to neighboring organs. In addition, residual misregistration gave rise to a loss of precision in the activity estimates that was on the order of the loss of precision due to Poisson noise in the projection data. These results serve as a lower bound on the effects of misregistration on the accuracy and precision of QPlanar activity estimate and demonstrate that misregistration errors must be taken into account when assessing the overall precision of organ dose estimates.

The impact of 3D volume of interest definition on accuracy and precision of activity estimation in quantitative SPECT and planar processing methods

Accurate and precise estimation of organ activities is essential for treatment planning in targeted radionuclide therapy. We have previously evaluated the impact of processing methodology, statistical noise and variability in activity distribution and anatomy on the accuracy and precision of organ activity estimates obtained with quantitative SPECT (QSPECT) and planar (QPlanar) processing. Another important factor impacting the accuracy and precision of organ activity estimates is accuracy of and variability in the definition of organ regions of interest (ROI) or volumes of interest (VOI). The goal of this work was thus to systematically study the effects of VOI definition on the reliability of activity estimates. To this end, we performed Monte Carlo simulation studies using randomly perturbed and shifted VOIs to assess the impact on organ activity estimates. The 3D NCAT phantom was used with activities that modeled clinically observed (111)In ibritumomab tiuxetan distributions. In order to study the errors resulting from misdefinitions due to manual segmentation errors, VOIs of the liver and left kidney were first manually defined. Each control point was then randomly perturbed to one of the nearest or next-nearest voxels in three ways: with no, inward or outward directional bias, resulting in random perturbation, erosion or dilation, respectively, of the VOIs. In order to study the errors resulting from the misregistration of VOIs, as would happen, e.g. in the case where the VOIs were defined using a misregistered anatomical image, the reconstructed SPECT images or projections were shifted by amounts ranging from -1 to 1 voxels in increments of with 0.1 voxels in both the transaxial and axial directions. The activity estimates from the shifted reconstructions or projections were compared to those from the originals, and average errors were computed for the QSPECT and QPlanar methods, respectively. For misregistration, errors in organ activity estimations were linear in the shift for both the QSPECT and QPlanar methods. QPlanar was less sensitive to object definition perturbations than QSPECT, especially for dilation and erosion cases. Up to 1 voxel misregistration or misdefinition resulted in up to 8% error in organ activity estimates, with the largest errors for small or low uptake organs. Both types of VOI definition errors produced larger errors in activity estimates for a small and low uptake organs (i.e. -7.5% to 5.3% for the left kidney) than for a large and high uptake organ (i.e. -2.9% to 2.1% for the liver). We observed that misregistration generally had larger effects than misdefinition, with errors ranging from -7.2% to 8.4%. The different imaging methods evaluated responded differently to the errors from misregistration and misdefinition. We found that QSPECT was more sensitive to misdefinition errors, but less sensitive to misregistration errors, as compared to the QPlanar method. Thus, sensitivity to VOI definition errors should be an important criterion in evaluating quantitative imaging methods.

Effects of shortened acquisition time on accuracy and precision of quantitative estimates of organ activity

PURPOSE

Quantitative estimation of in vivo organ uptake is an essential part of treatment planning for targeted radionuclide therapy. This usually involves the use of planar or SPECT scans with acquisition times chosen based more on image quality considerations rather than the minimum needed for precise quantification. In previous simulation studies at clinical count levels (185 MBq 111In), the authors observed larger variations in accuracy of organ activity estimates resulting from anatomical and uptake differences than statistical noise. This suggests that it is possible to reduce the acquisition time without substantially increasing the variation in accuracy.

METHODS

To test this hypothesis, the authors compared the accuracy and variation in accuracy of organ activity estimates obtained from planar and SPECT scans at various count levels. A simulated phantom population with realistic variations in anatomy and biodistribution was used to model variability in a patient population. Planar and SPECT projections were simulated using previously validated Monte Carlo simulation tools. The authors simulated the projections at count levels approximately corresponding to 1.5-30 min of total acquisition time. The projections were processed using previously described quantitative SPECT (QSPECT) and planar (QPlanar) methods. The QSPECT method was based on the OS-EM algorithm with compensations for attenuation, scatter, and collimator-detector response. The QPlanar method is based on the ML-EM algorithm using the same model-based compensation for all the image degrading effects as the QSPECT method. The volumes of interests (VOIs) were defined based on the true organ configuration in the phantoms. The errors in organ activity estimates from different count levels and processing methods were compared in terms of mean and standard deviation over the simulated phantom population.

RESULTS

There was little degradation in quantitative reliability when the acquisition time was reduced by half for the QSPECT method (the mean error changed by < 1%, e.g., 0.9%-0.3% = 0.6% for the spleen). The magnitude of the errors and variations in errors for large organ with high uptake were still acceptable for 1.5 min scans, even though the errors were slightly larger than those for the 30 min scans (i.e., < 2% for liver, < 3% for heart). The errors over the ranges of scan times studied for the QPlanar method were all within 0.3% for all organs.

CONCLUSIONS

These data indicate that, for the purposes of organ activity estimation, acquisition times could be reduced at least by a factor of 2 for the QSPECT and QPlanar methods with little effect on the errors in organ activity estimates. The acquisition time can be further reduced for the QPlanar method, assuming well-registered VOIs are available and the activity distribution in organs can be treated as uniform. Although the differences in accuracy and precision were statistically significant for all the acquisition times shorter than 30 min, the magnitude of the changes in accuracy and precision were small and likely not clinically important. The reduction in SPECT acquisition time justified by this study makes the use of SPECT a more clinically practical alternative to conventional planar scanning for targeted radiotherapy treatment planning.

Performance Characteristics of BGO Detectors for a Low Cost Preclinical PET Scanner

PETbox is a low-cost benchtop PET scanner dedicated to high throughput preclinical imaging that is currently under development at our institute. This paper presents the design and characterization of the detectors that are used in the PETbox system. In this work, bismuth germanate scintillator was used for the detector, taking advantage of its high stopping power, high photoelectric event fraction, lack of intrinsic background radiation and low cost. The detector block was segmented into a pixelated array consisting of 20 × 44 elements, with a crystal pitch of 2.2 mm and a crystal cross section of 2 mm × 2 mm. The effective area of the array was 44 mm × 96.8 mm. The array was coupled to two Hamamatsu H8500 position sensitive photomultiplier tubes, forming a flat-panel type detector head with a sensitive area large enough to cover the whole body of a typical laboratory mouse. Two such detector heads were constructed and their performance was characterized. For one detector head, the energy resolution ranged from 16.1% to 38.5% full width at half maximum (FWHM), with a mean of 20.1%; for the other detector head, the energy resolution ranged from 15.5% to 42.7% FWHM, with a mean of 19.6%. The intrinsic spatial resolution was measured to range from 1.55 mm to 2.39 mm FWHM along the detector short axis and from 1.48 mm to 2.33 mm FWHM along the detector long axis, with an average of 1.78 mm. Coincidence timing resolution for the detector pair was measured to be 4.1 ns FWHM. These measurement results show that the detectors are suitable for our specific application.

Quantitative accuracy of clinical 99mTc SPECT/CT using ordered-subset expectation maximization with 3-dimensional resolution recovery, attenuation, and scatter correction

We present a calibration method of a clinical SPECT/CT device for quantitative (99m)Tc SPECT. We use a commercially available reconstruction package including ordered-subset expectation maximization (OSEM) with depth-dependent 3-dimensional resolution recovery (OSEM-3D), CT-based attenuation correction, and scatter correction. We validated the method in phantom studies and applied it to images from patients injected with (99m)Tc-diphosponate.

METHODS

The following 3 steps were performed to derive absolute quantitative values from SPECT reconstructed images. In step 1, we used simulations to characterize the SPECT/CT system and derive emission recovery values for various imaging parameter settings. We simulated spheres of varying diameters and focused on the dependencies of activity estimation errors on structure size and position, pixel size, count density, and reconstruction parameters. In step 2, we cross-calibrated our clinical SPECT/CT system with the well counter using a large cylinder phantom. This step provided the mapping from image counts to kBq/mL. And in step 3, correction factors from steps 1 and 2 were applied to reconstructed images. We used a cylinder phantom with variable-sized spheres for verification of the method. For in vivo validation, SPECT/CT datasets from 16 patients undergoing (99m)Tc-diphosponate SPECT/CT examinations of the pelvis including the bladder were acquired. The radioactivity concentration in the patients' urine served as the gold standard. Mean quantitative accuracy and SEs were calculated.

RESULTS

In the phantom experiments, the mean accuracy in quantifying radioactivity concentration in absolute terms was within 3.6% (SE, 8.0%), with a 95% confidence interval between -19.4% and +12.2%. In the patient studies, the mean accuracy was within 1.1% (SE, 8.4%), with a 95% confidence interval between -15.4% and +17.5%.

CONCLUSION

Current commercially available SPECT/CT technology using OSEM-3D reconstruction, scatter correction, and CT-based attenuation correction allows quantification of (99m)Tc radioactivity concentration in absolute terms within 3.6% in phantoms and 1.1% in patients with a focus on the bladder. This opens up the opportunity of SPECT quantitation entering the routine clinical arena. Still, the imprecision caused by unavoidable measurement errors is a dominant factor for absolute quantitation in a clinical setup.

Evaluation of a method for activity estimation in Sm-153 EDTMP imaging

Absolute activity evaluation is fundamental for internal radionuclide dosimetry when patient-specific therapy optimization is wanted. Often, quantification is attempted with 3D SPECT image based (IB) methods, but the true concentration values can be underestimated due to the partial volume effect (PVE). This is especially true when small diffuse lesions are present. In this paper, we describe a 3D region of interest (ROI) based quantification method (LS-ROI), which estimates the ROI concentration values directly from the projection data acquired in the tomographic scan once ROIs have been segmented on a CT and/or a SPECT image. The method, which has inherent PVE correction capabilities, was applied both on simulated and on real phantom data. Simulations reflected the case of a patient with bone metastases treated with 153Sm-EDTMP: Both the activity in the metastases and the total retention in the skeleton were evaluated. Thirty noisy data sets were produced in order to evaluate the accuracy and precision of the method. The effect of region segmentation errors on estimated concentrations was thoroughly investigated. Real data were acquired on a NEMA phantom, where a cylindrical central region (283 cm3) simulated the bone and two spheres (10.3 and 25.5 cm3) simulated the metastases. The results obtained with the LS-ROI method were compared with those of a conventional 3D IB method and those of a quantitative conjugate view approach derived from LS-ROI and applied to the anterior and posterior views acquired in the tomographic scan (LS-ROI anterior-posterior: LS-ROI-AP). Simulations showed that when the geometry of regions is known, the LS-ROI method recovered the simulated concentration values within 20%, while the IB method underestimated the concentration in high activity small lesions by as much as 49%. Segmentation errors, up to 44% of the true region volume, produced a higher variation in LS-ROI estimates than in IB ones; however, the overall bias of the LS-ROI estimates (< or = 25%) remained lower than that of IB estimates. In the case of the evaluation of the total retention in the skeleton, the LS-ROI method recovered the simulated value within 2%, while IB underestimated it up to 13%. In all the cases, the LS-ROI-AP method showed an accuracy comparable with that of the LS-ROI one, and a worse precision just because of the lower number of counts used in the analysis. However, a worsening of LS-ROI-AP performances was demonstrated in the case of strong overlap of regions: In this case, a bias of up to 40% was observed. The results obtained on real phantom data confirmed the simulation results: The IB method underestimated activity up to 47% in the smallest sphere, while the bias was reduced to 13% with LS-ROI and LS-ROI-AP estimates. The good quantification capabilities of the LS-ROI method can be useful for absolute activity quantification in the case of small active diffused lesions and constitute the basis for the development of an accurate patient-specific planning strategy in internal radionuclide treatments, provided there is a reliable segmentation of lesions.

Evaluation of quantitative imaging methods for organ activity and residence time estimation using a population of phantoms having realistic variations in anatomy and uptake

Estimating organ residence times is an essential part of patient-specific dosimetry for radioimmunotherapy (RIT). Quantitative imaging methods for RIT are often evaluated using a single physical or simulated phantom but are intended to be applied clinically where there is variability in patient anatomy, biodistribution, and biokinetics. To provide a more relevant evaluation, the authors have thus developed a population of phantoms with realistic variations in these factors and applied it to the evaluation of quantitative imaging methods both to find the best method and to demonstrate the effects of these variations. Using whole body scans and SPECT/CT images, organ shapes and time-activity curves of 111In ibritumomab tiuxetan were measured in dosimetrically important organs in seven patients undergoing a high dose therapy regimen. Based on these measurements, we created a 3D NURBS-based cardiac-torso (NCAT)-based phantom population. SPECT and planar data at realistic count levels were then simulated using previously validated Monte Carlo simulation tools. The projections from the population were used to evaluate the accuracy and variation in accuracy of residence time estimation methods that used a time series of SPECT and planar scans, Quantitative SPECT (QSPECT) reconstruction methods were used that compensated for attenuation, scatter, and the collimator-detector response. Planar images were processed with a conventional (CPlanar) method that used geometric mean attenuation and triple-energy window scatter compensation and a quantitative planar (QPlanar) processing method that used model-based compensation for image degrading effects. Residence times were estimated from activity estimates made at each of five time points. The authors also evaluated hybrid methods that used CPlanar or QPlanar time-activity curves rescaled to the activity estimated from a single QSPECT image. The methods were evaluated in terms of mean relative error and standard deviation of the relative error in the residence time estimates taken over the phantom population. The mean errors in the residence time estimates over all the organs were < 9.9% (pure QSPECT), < 13.2% (pure QPLanar), < 7.2% (hybrid QPlanar/QSPECT), < 19.2% (hybrid CPlanar/QSPECT), and 7%-159% (pure CPlanar). The standard deviations of the errors for all the organs over all the phantoms were < 9.9%, < 11.9%, < 10.8%, < 22.0%, and < 107.9% for the same methods, respectively. The processing methods differed both in terms of their average accuracy and the variation of the accuracy over the population of phantoms, thus demonstrating the importance of using a phantom population in evaluating quantitative imaging methods. Hybrid CPlanar/QSPECT provided improved accuracy compared to pure CPlanar and required the addition of only a single SPECT acquisition. The QPlanar or hybrid QPlanar/QSPECT methods had mean errors and standard deviations of errors that approached those of pure QSPECT while providing simplified image acquisition protocols, and thus may be more clinically practical.

Three-dimensional imaging-based radiobiological dosimetry

Targeted radionuclide therapy holds promise as a new treatment for cancer. Advances in imaging are making it possible for researchers to evaluate the spatial distribution of radioactivity in tumors and normal organs over time. Matched anatomical imaging, such as combined single-photon emission computed tomography/computed tomography and positron emission tomography/computed tomography, has also made it possible to obtain tissue density information in conjunction with the radioactivity distribution. Coupled with sophisticated iterative reconstruction algorithms, these advances have made it possible to perform highly patient-specific dosimetry that also incorporates radiobiological modeling. Such sophisticated dosimetry techniques are still in the research investigation phase. Given the attendant logistical and financial costs, a demonstrated improvement in patient care will be a prerequisite for the adoption of such highly-patient specific internal dosimetry methods.

Brain single-photon emission CT physics principles

The basic principles of scintigraphy are reviewed and extended to 3D imaging. Single-photon emission computed tomography (SPECT) is a sensitive and specific 3D technique to monitor in vivo functional processes in both clinical and preclinical studies. SPECT/CT systems are becoming increasingly common and can provide accurately registered anatomic information as well. In general, SPECT is affected by low photon-collection efficiency, but in brain imaging, not all of the large FOV of clinical gamma cameras is needed: The use of fan- and cone-beam collimation trades off the unused FOV for increased sensitivity and resolution. The design of dedicated cameras aims at increased angular coverage and resolution by minimizing the distance from the patient. The corrections needed for quantitative imaging are challenging but can take advantage of the relative spatial uniformity of attenuation and scatter. Preclinical systems can provide submillimeter resolution in small animal brain imaging with workable sensitivity.

Fast hybrid SPECT simulation including efficient septal penetration modelling (SP-PSF)

Single photon emission computed tomography (SPECT) images are degraded by the detection of scattered photons and photons that penetrate the collimator septa. In this paper, a previously proposed Monte Carlo software that employs fast object scatter simulation using convolution-based forced detection (CFD) is extended towards a wide range of medium and high energy isotopes measured using various collimators. To this end, a fast method was developed for incorporating effects of septal penetrating (SP) photons. The SP contributions are obtained by calculating the object attenuation along the path from primary emission to detection followed by sampling a pre-simulated and scalable septal penetration point spread function (SP-PSF). We found that with only a very slight reduction in accuracy, we could accelerate the SP simulation by four orders of magnitude. To achieve this, we combined: (i) coarse sampling of the activity and attenuation distribution; (ii) simulation of the penetration only for a coarse grid of detector pixels followed by interpolation and (iii) neglection of SP-PSF elements below a certain threshold. By inclusion of this SP-PSF-based simulation it became possible to model both primary and septal penetrated photons while only 10% extra computation time was added to the CFD-based Monte Carlo simulator. As a result, a SPECT simulation of a patient-like distribution including SP now takes less than 5 s per projection angle on a dual processor PC. Therefore, the simulator is well-suited as an efficient projector for fully 3D model-based reconstruction or as a fast data-set generator for applications such as image processing optimization or observer studies.