Model-based compensation for quantitative 123I brain SPECT imaging

Generation of Digital Brain Phantom for Machine Learning Application of Dopamine Transporter Radionuclide Imaging

While machine learning (ML) methods may significantly improve image quality for SPECT imaging for the diagnosis and monitoring of Parkinson’s disease (PD), they require a large amount of data for training. It is often difficult to collect a large population of patient data to support the ML research, and the ground truth of lesion is also unknown. This paper leverages a generative adversarial network (GAN) to generate digital brain phantoms for training ML-based PD SPECT algorithms. A total of 594 PET 3D brain models from 155 patients (113 male and 42 female) were reviewed and 1597 2D slices containing the full or a portion of the striatum were selected. Corresponding attenuation maps were also generated based on these images. The data were then used to develop a GAN for generating 2D brain phantoms, where each phantom consisted of a radioactivity image and the corresponding attenuation map. Statistical methods including histogram, Fréchet distance, and structural similarity were used to evaluate the generator based on 10,000 generated phantoms. When the generated phantoms and training dataset were both passed to the discriminator, similar normal distributions were obtained, which indicated the discriminator was unable to distinguish the generated phantoms from the training datasets. The generated digital phantoms can be used for 2D SPECT simulation and serve as the ground truth to develop ML-based reconstruction algorithms. The cumulated experience from this work also laid the foundation for building a 3D GAN for the same application.

Evaluation of quantitative accuracy among different scatter corrections for quantitative bone SPECT/CT imaging

Although scatter correction improves SPECT image contrast and thus image quality, the effects of quantitation accuracy under various conditions remain unclear. The present study aimed to empirically define the conditions for the optimal scatter correction of quantitative bone SPECT/CT images. Scatter correction was performed by applying dual and triple energy windows (DEW and TEW) with different sub-energy window widths, and effective scatter source estimation (ESSE) to CT-based scatter correction. Scattered radiation was corrected on images acquired using a triple line source (TLSP) phantom and an uniform cylinder phantom. The TLSP consisted of a line source containing 74.0 MBq of 99mTc in the middle, and a background component containing air, water or a K2HPO4 solution with a density equivalent to that of bone. The sum of all pixels in air, water and the K2HPO4 solution was measured on SPECT images. Scatter fraction (SF) and normalized mean square error (NMSE) based on counts from the air background as a reference were then calculated to assess quantitative errors due to scatter correction. The uniform cylinder phantom contained the same K2HPO4 solution and 222.0 MBq of 99mTc. The coefficient of variation (CV) was calculated from the count profile of this phantom to assess the uniformity of SPECT images across scatter correction under various conditions. Both SF and NMSE in SPECT images of phantoms containing water in the background were lower at a TEW sub-window of 3% (TEW3%), than in other scatter corrections, whereas those in K2HPO4 were lower at a DEW sub-window of 20% (DEW20%). Larger DEW and smaller TEW sub-energy windows allowed more effective correction. The CV of the uniform cylinder phantom, DEW20%, was inferior to all other tested scatter corrections. The quantitative accuracy of bone SPECT images substantially differed according to the method of scatter correction. The optimal scatter correction for quantitative bone SPECT was DEW20% (k = 1), but at the cost of slightly decreased image uniformity.

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

BACKGROUND

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

SPECTnet: a deep learning neural network for SPECT image reconstruction

Background

Single photon emission computed tomography (SPECT) is an important functional tool for clinical diagnosis and scientific research of brain disorders, but suffers from limited spatial resolution and high noise due to hardware design and imaging physics. The present study is to develop a deep learning technique for SPECT image reconstruction that directly converts raw projection data to image with high resolution and low noise, while an efficient training method specifically applicable to medical image reconstruction is presented.

Methods

A custom software was developed to generate 20,000 2-D brain phantoms, of which 16,000 were used to train the neural network, 2,000 for validation, and the final 2,000 for testing. To reduce development difficulty, a two-step training strategy for network design was adopted. We first compressed full-size activity image (128×128 pixels) to a one-D vector consisting of 256×1 pixels, accomplished by an autoencoder (AE) consisting of an encoder and a decoder. The vector is a good representation of the full-size image in a lower-dimensional space and was used as a compact label to develop the second network that maps between the projection-data domain and the vector domain. Since the label had 256 pixels only, the second network was compact and easy to converge. The second network, when successfully developed, was connected to the decoder (a portion of AE) to decompress the vector to a regular 128×128 image. Therefore, a complex network was essentially divided into two compact neural networks trained separately in sequence but eventually connectable.

Results

A total of 2,000 test examples, a synthetic brain phantom, and de-identified patient data were used to validate SPECTnet. Results obtained from SPECTnet were compared with those obtained from our clinic OS-EM method. Images with lower noise and more accurate information in the uptake areas were obtained by SPECTnet.

Conclusions

The challenge of developing a complex deep neural network is reduced by training two separate compact connectable networks. The combination of the two networks forms the full version of SPECTnet. Results show that the developed neural network can produce more accurate SPECT images.

DeepAMO: a multi-slice, multi-view anthropomorphic model observer for visual detection tasks performed on volume images

Purpose: We propose a deep learning-based anthropomorphic model observer (DeepAMO) for image quality evaluation of multi-orientation, multi-slice image sets with respect to a clinically realistic 3D defect detection task. Approach: The DeepAMO is developed based on a hypothetical model of the decision process of a human reader performing a detection task using a 3D volume. The DeepAMO is comprised of three sequential stages: defect segmentation, defect confirmation (DC), and rating value inference. The input to the DeepAMO is a composite image, typical of that used to view 3D volumes in clinical practice. The output is a rating value designed to reproduce a human observer's defect detection performance. In stages 2 and 3, we propose: (1) a projection-based DC block that confirms defect presence in two 2D orthogonal orientations and (2) a calibration method that "learns" the mapping from the features of stage 2 to the distribution of observer ratings from the human observer rating data (thus modeling inter- or intraobserver variability) using a mixture density network. We implemented and evaluated the DeepAMO in the context of   Tc 99 m -DMSA SPECT imaging. A human observer study was conducted, with two medical imaging physics graduate students serving as observers. A 5 × 2 -fold cross-validation experiment was conducted to test the statistical equivalence in defect detection performance between the DeepAMO and the human observer. We also compared the performance of the DeepAMO to an unoptimized implementation of a scanning linear discriminant observer (SLDO). Results: The results show that the DeepAMO's and human observer's performances on unseen images were statistically equivalent with a margin of difference ( Δ AUC ) of 0.0426 at p < 0.05 , using 288 training images. A limited implementation of an SLDO had a substantially higher AUC (0.99) compared to the DeepAMO and human observer. Conclusion: The results show that the DeepAMO has the potential to reproduce the absolute performance, and not just the relative ranking of human observers on a clinically realistic defect detection task, and that building conceptual components of the human reading process into deep learning-based models can allow training of these models in settings where limited training images are available.

Quantitative Monte Carlo-based brain dopamine transporter SPECT imaging

OBJECTIVE

Brain dopamine transporter imaging with I-123-labeled radioligands is technically demanding due to the small size of the imaging target relative to the spatial resolution of most SPECT systems. In addition, I-123 has high-energy peaks which can penetrate or scatter in the collimator and be detected in the imaging energy window. The aim of this study was to implement Monte Carlo (MC)-based full collimator-detector response (CDR) compensation algorithm for I-123 into a third-party commercial SPECT reconstruction software package and to evaluate its effect on the quantitative accuracy of dopaminergic-image analysis compared to a method where only the geometric component of the CDR is compensated.

METHODS

In this work, we utilized a full Monte Carlo collimator-detector model and incorporated it into an iterative SPECT reconstruction algorithm. The full Monte Carlo model reconstruction was compared to standard reconstruction using an anthropomorphic striatal phantom filled with different I-123 striatal/cortex uptake ratios and with clinical I-123 Ioflupane DaTScan studies.

RESULTS

Reconstruction with the full model yielded higher (13-25%) striatal uptake ratios than the conventional reconstruction, but the uptake ratios were still much lower than the true ratios due to partial volume effect. Visually, images reconstructed with the full Monte Carlo model had better contrast and resolution than the conventional images, with both phantom and patient studies.

CONCLUSIONS

Reconstruction with full Monte Carlo collimator-detector model yields higher quantitative accuracy than conventional reconstruction. Additional work to reduce the partial volume effect related errors would improve the accuracy further.

A Learned Reconstruction Network for SPECT Imaging

A neural network designed specifically for SPECT image reconstruction was developed. The network reconstructed activity images from SPECT projection data directly. Training was performed through a corpus of training data including that derived from digital phantoms generated from custom software and the corresponding projection data obtained from simulation. When using the network to reconstruct images, input projection data were initially fed to two fully connected (FC) layers to perform a basic reconstruction. Then the output of the FC layers and an attenuation map were delivered to five convolutional layers for signal-decay compensation and image optimization. To validate the system, data not used in training, simulated data from the Zubal human brain phantom, and clinical patient data were used to test reconstruction performance. Reconstructed images from the developed network proved closer to the truth with higher resolution and quantitative accuracy than those from conventional OS-EM reconstruction. To understand better the operation of the network for reconstruction, intermediate results from hidden layers were investigated for each step of the processing. The network system was also retrained with noisy projection data and compared with that developed with noise-free data. The retrained network proved even more robust after having learned to filter noise. Finally, we showed that the network still provided sharp images when using reduced view projection data (retrained with reduced view data).

Quantitative SPECT/CT-Technique and Clinical Applications

The continuous development of SPECT over the past 50 years has led to improved image quality and increased diagnostic confidence. The most influential developments include the realization of hybrid SPECT/CT devices, as well as the implementation of attenuation correction and iterative image reconstruction techniques. These developments have led to a preference for SPECT/CT devices over SPECT-only systems and to the widespread adoption of the former, strengthening the role of SPECT/CT as the workhorse of Nuclear Medicine imaging. New trends in the ongoing development of SPECT/CT are diverse. For example, whole-body SPECT/CT images, consisting of acquisitions from multiple consecutive bed positions in the manner of PET/CT, are increasingly performed. Additionally, in recent years, some interesting approaches in detector technology have found their way into commercial products. For example, some SPECT cameras dedicated to specific organs employ semiconductor detectors made of cadmium telluride or cadmium zinc telluride, which have been shown to increase the obtainable image quality by offering a higher sensitivity and energy resolution. However, the advent of quantitative SPECT/CT which, like PET, can quantify the amount of tracer in terms of Bq/mL or as a standardized uptake value could be regarded as most important development. It is a major innovation that will lead to increased diagnostic accuracy and confidence, especially in longitudinal studies and in the monitoring of treatment response. The current work comprises two main aspects. At first, physical and technical fundamentals of SPECT image formation are described and necessary prerequisites of quantitative SPECT/CT are reviewed. Additionally, the typically achievable quantitative accuracy based on reports from the literature is given. Second, an extensive list of studies reporting on clinical applications of quantitative SPECT/CT is provided and reviewed.

Analysis of quantitative [I-123] mIBG SPECT/CT in a phantom and in patients with neuroblastoma

Purpose

To determine the accuracy of quantitative SPECT, intersystem and interpatient standardized uptake value (SUV) calculation consistency for a manufacturer-independent quantitative SPECT/CT reconstruction algorithm, and the range of SUVs of normal and neoplastic tissue.

Methods

A NEMA body phantom with 6 spheres (ranging 10–37 mm) was filled with a known activity-to-volume ratio and used to determine the contrast recovery coefficient (CRC) for each visible sphere, and the measured SUV accuracy of those spheres and background water solution. One hundred eleven 123I-metaiodobenzylguanidine ([I-123] mIBG) SPECT/CT examinations from 43 patients were reconstructed using SUV SPECT® (HERMES Medical Solutions Inc.); 42 examinations were acquired using a GE Infinia Hawkeye 4 SPECT/CT, and 69 were acquired on a Siemens Symbia Intevo SPECT/CT. Inter scanner SUV analysis of 9 regions of normal [I-123] mIBG tissue uptake was conducted. Intrapatient mean SUV variability was calculated by measuring normal liver uptake within patients scanned on both cameras. The intensity of uptake by neoplastic tissue in the images was quantified using maximum SUV and, if present, compared over time.

Results

The phantom results of the visible spheres and background resulted in accuracy calculations better than 5–10% with CRC correction. Interscanner SUV variability showed no statistical difference (average p value 0.559; range 0.066–1.0) among the 9 normal tissues analyzed. Intrapatient liver mean SUV varied ≤ 16% as calculated for 28 patients (87 examinations) studied on both scanners. In one patient, a thoracic tumor evaluated over 10 time points (18 months) underwent a 74% (3.1/12.0) reduction in maximum SUV with treatment.

Conclusion

The results demonstrate quantitative accuracy to better than 10%, and both consistent SUV calculation between 2 different SPECT/CT scanners for 9 tissues, and low intrapatient measurement variability for quantitative SPECT/CT analysis in a pediatric population with neuroblastoma. Quantitative SPECT/CT offers the opportunity for objective analysis of tumor response using [I-123] mIBG by normalizing the uptake to injected dose and patient weight, as is done for PET.

Current pediatric administered activity guidelines for 99m Tc-DMSA SPECT based on patient weight do not provide the same task-based image quality

PURPOSE

In the current clinical practice, administered activity (AA) for pediatric molecular imaging is often based on the North American expert consensus guidelines or the European Association of Nuclear Medicine dosage card, both of which were developed based on the best clinical practice. These guidelines were not formulated using a rigorous evaluation of diagnostic image quality (IQ) relative to AA. In the guidelines, AA is determined by a weight-based scaling of the adult AA, along with minimum and maximum AA constraints. In this study, we use task-based IQ assessment methods to rigorously evaluate the efficacy of weight-based scaling in equalizing IQ using a population of pediatric patients of different ages and body weights.

METHODS

A previously developed projection image database was used. We measured task-based IQ, with respect to the detection of a renal functional defect at six different AA levels (AA relative to the AA obtained from the guidelines). IQ was assessed using an anthropomorphic model observer. Receiver-operating characteristics (ROC) analysis was applied; the area under the ROC curve (AUC) served as a figure-of-merit for task performance. In addition, we investigated patient girth (circumference) as a potential improved predictor of the IQ.

RESULTS

The data demonstrate a monotonic and modestly saturating increase in AUC with increasing AA, indicating that defect detectability was limited by quantum noise and the effects of object variability were modest over the range of AA levels studied. The AA for a given value of the AUC increased with increasing age. The AUC vs AA plots for all the patient ages indicate that, for the current guidelines, the newborn and 10- and 15-yr phantoms had similar IQ for the same AA suggested by the North American expert consensus guidelines, but the 5- and 1-yr phantoms had lower IQ. The results also showed that girth has a stronger correlation with the needed AA to provide a constant AUC for ^99m Tc-DMSA renal SPECT.

CONCLUSIONS

The results suggest that (a) weight-based scaling is not sufficient to equalize task-based IQ for patients of different weights in pediatric ^99m Tc-DMSA renal SPECT; and (b) patient girth should be considered instead of weight in developing new administration guidelines for pediatric patients.

Recent advances in cardiac SPECT instrumentation and imaging methods

Cardiac SPECT continues to play a critical role in detecting and managing cardiovascular disease, in particularly coronary artery disease (CAD) (Jaarsma et al 2012 J. Am. Coll. Cardiol. 59 1719-28), (Agostini et al 2016 Eur. J. Nucl. Med. Mol. Imaging 43 2423-32). While conventional dual-head SPECT scanners using parallel-hole collimators and scintillation crystals with photomultiplier tubes are still the workhorse of cardiac SPECT, they have the limitations of low photon sensitivity (~130 count s^-1 MBq^-1), poor image resolution (~15 mm) (Imbert et al 2012 J. Nucl. Med. 53 1897-903), relatively long acquisition time, inefficient use of the detector, high radiation dose, etc. Recently our field observed an exciting growth of new developments of dedicated cardiac scanners and collimators, as well as novel imaging algorithms for quantitative cardiac SPECT. These developments have opened doors to new applications with potential clinical impact, including ultra-low-dose imaging, absolute quantification of myocardial blood flow (MBF) and coronary flow reserve (CFR), multi-radionuclide imaging, and improved image quality as a result of attenuation, scatter, motion, and partial volume corrections (PVCs). In this article, we review the recent advances in cardiac SPECT instrumentation and imaging methods. This review mainly focuses on the most recent developments published since 2012 and points to the future of cardiac SPECT from an imaging physics perspective.

Evaluation of quantitative 123I and 131I SPECT with Monte Carlo-based down-scatter compensation

OBJECTIVE

Quantitative I and I single-photon emission computed tomography (SPECT) is hampered by down-scatter from the high-energy peaks. This paper presents a down-scatter compensation method, where down-scatter generated in the patient and gamma camera collimator and detector is modelled using Monte Carlo simulation in the ordered subsets expectation maximization SPECT reconstruction algorithm.

MATERIALS AND METHODS

The new down-scatter compensation method was compared with conventional triple energy window (TEW) scatter compensation and Gaussian convolution-based forced detection Monte Carlo methods. The comparison was made with the NEMA-IEC phantom using six spherical inserts (diameters from 10 to 37 mm) and a lung compartment. The phantom was filled with I and I solutions to known sphere-to-background concentration ratios. Spherical volumes of interest with the same diameter as the inserts were drawn on the images, and recovery coefficients for the spheres were calculated in addition to lung-to-background ratio.

RESULTS

The new down-scatter compensation method provided higher recovery coefficients than the TEW scatter compensation or Gaussian convolution-based forced detection Monte Carlo algorithm for both isotopes. Background activity concentration could be accurately estimated with the new down-scatter compensation method and with the TEW scatter compensation, whereas activity concentration of the spheres was severely underestimated even with the new method.

CONCLUSION

Down-scatter compensation with Monte Carlo-simulation effectively reduces down-scatter effects in I and I SPECT imaging.

Scatter Correction of Septal Penetration for 123I-IMP Cerebral Blood Flow SPECT Adding Radioactivity from the Outside of Field of View-Comparison between Simulation-based and Multi-window Scatter Corrections

PURPOSE

The N-Isopropyl-p-[123I] Iodoamphetamine (¹²³I-IMP) SPECT imaging reduces the image quality and quantitative accuracy due to scatter and septal penetration occurred by radioactive uptake from outside of the field of view such as the lungs. We evaluated the influence of scatter and septal penetration using phantom-simulated radioactivity from outside of the field of view, and subsequently compared the effect of scatter and septal penetration corrections between the simulation-based effective scatter source estimation (ESSE) method and the multi-window method (ellipse approximation method).

METHODS

We used the phantom filled with 10 and 25 kBq/mL for the brain and lung parts corresponding to radioactive concentration in the clinical study. The SPECT images were acquired with and without lung phantom using low-energy high-resolution (LEHR) and cardiac high-resolution (CHR) collimators. We quantitatively evaluated a brain phantom by count analysis and coefficient of variation as reference data without lung phantom simulated the radioactivity from outside of the field of view, and compared between two scatter corrections by each collimator.

RESULTS

The brain count in cerebral base with the ESSE method using LEHR collimator was higher than that of the ellipse approximation method. The whole brain count with the ellipse approximation method using CHR collimator shows 28.8% lower than the ESSE method, so that it suggests that the ellipse approximation method for LEHR collimator and the ESSE method for CHR collimator was close to reference counts. The coefficient of variation of the ESSE method was lower than that of the ellipse approximation method for both two collimators.

CONCLUSIONS

It was possible to correct the scatter and penetration from outside the field of view with high accuracy, by using the ellipse approximation method with LEHR collimator and the ESSE method with CHR collimator.

Use of quantitative SPECT/CT reconstruction in 99mTc-sestamibi imaging of patients with renal masses

OBJECTIVE

Technetium-99m (^99mTc)-sestamibi single-photon emission computed tomography/computed tomography (SPECT/CT) has previously been shown to allow for the accurate differentiation of benign renal oncocytomas and hybrid oncocytic/chromophobe tumors (HOCTs) apart from other malignant renal tumor histologies, with oncocytomas/HOCTs showing high uptake and renal cell carcinoma (RCC) showing low uptake based on uptake ratios from non-quantitative single-photon emission computed tomography (SPECT) reconstructions. However, in this study, several tumors fell close to the uptake ratio cutoff, likely due to limitations in conventional SPECT/CT reconstruction methods. We hypothesized that application of quantitative SPECT/CT (QSPECT) reconstruction methods developed by our group would provide more robust separation of hot and cold lesions, serving as an imaging framework on which quantitative biomarkers can be validated for evaluation of renal masses with ^99mTc-sestamibi.

METHODS

Single-photon emission computed tomography data were reconstructed using the clinical Flash 3D reconstruction and QSPECT methods. Two blinded readers then characterized each tumor as hot or cold. Semi-quantitative uptake ratios were calculated by dividing lesion activity by background renal activity for both Flash 3D and QSPECT reconstructions.

RESULTS

The difference between median (mean) hot and cold tumor uptake ratios measured 0.655 (0.73) with the QSPECT method and 0.624 (0.67) with the conventional method, resulting in increased separation between hot and cold tumors. Sub-analysis of 7 lesions near the separation point showed a higher absolute difference (0.16) between QPSECT and Flash 3D mean uptake ratios compared to the remaining lesions.

CONCLUSIONS

Our finding of improved separation between uptake ratios of hot and cold lesions using QSPECT reconstruction lays the foundation for additional quantitative SPECT techniques such as SPECT-UV in the setting of renal ^99mTc-sestamibi and other SPECT/CT exams. With robust quantitative image reconstruction and biomarker analysis, there may be an expanded role for SPECT/CT imaging in renal masses and other pathologic conditions.

A phantom study: Should 124 I-mIBG PET/CT replace 123 I-mIBG SPECT/CT?

PURPOSE

The isotope ¹²³ I is commonly labeled with meta-iodobenzylguanidine (mIBG) for imaging of neuroendocrine tumors, such as pheochromocytomas and neuroblastomas. ¹²³ I-mIBG SPECT/CT imaging is performed for staging, follow-up and selection of patients for treatment with ¹³¹ I mIBG. As an alternative to ¹²³ I, ¹²⁴ I-mIBG PET/CT may be used, potentially taking advantage of the superior PET image quality. The purpose of this study was to investigate whether ¹²⁴ I PET/CT improves image quality as compared with ¹²³ I SPECT/CT for equal patient effective radiation dose (in mSv).

METHODS

Phantom measurements were performed using the NEMA-2007 image quality phantom. SPECT and PET reconstruction settings were used with and without time-of-flight (TOF) and point-spread-function (PSF) modeling. As a measure of image quality, the contrast-to-noise ratio (CNR) was calculated. The ratio of the ¹²³ I to ¹²⁴ I activity concentration was determined at which the contrast-to-noise ratio was equal for both modalities. This metric was defined as the contrast equivalent activity ratio (CEAR).

RESULTS

CEARs of 47.7, 25.6, 23.1, 14.6, 10.0, and 9.1 were obtained for a TOF and PSF modeled ¹²⁴ I reconstruction method and an attenuation and scatter-corrected ¹²³ I reconstruction method for sphere sizes of 10 to 37 mm, respectively. As the effective radiation dose of ¹²⁴ I-mIBG is higher than of ¹²³ I-mIBG (in mSv/MBq), an equal effective dose corresponds to a CEAR of 5 to 10. Therefore, CEARs higher than 5 to 10 indicate that ¹²⁴ I PET/CT outperforms ¹²³ I SPECT/CT in the sense of image quality for equal patient effective radiation dose.

CONCLUSION

The CEAR is much larger than a factor of 5 to 10 (needed for equal patient effective radiation dose) for most of the reconstruction methods and sphere sizes. Therefore, ¹²⁴ I-mIBG PET/CT is expected to improve image quality and/or may be used to reduce effective patient dose as compared with ¹²³ I-mIBG SPECT/CT.

Simplifying volumes-of-interest (VOIs) definition in quantitative SPECT: Beyond manual definition of 3D whole-organ VOIs

PURPOSE

We investigated the feasibility of using simpler methods than manual whole-organ volume-of-interest (VOI) definition to estimate the organ activity concentration in single photon emission computed tomography (SPECT) in cases where the activity in the organ can be assumed to be uniformly distributed on the scale of the voxel size. In particular, we investigated an anatomic region-of-interest (ROI) defined in a single transaxial slice, and a single sphere placed inside the organ boundaries.

METHODS

The evaluation was carried out using Monte Carlo simulations based on patient indium ¹¹¹ In pentetreotide SPECT and computed tomography (CT) images. We modeled constant activity concentrations in each organ, validating this assumption by comparing the distribution of voxel values inside the organ VOIs of the simulated data with the patient data. We simulated projection data corresponding to 100, 50, and 25% of the clinical count level to study the effects of noise level due to shortened acquisition time. Images were reconstructed using a previously validated quantitative SPECT reconstruction method. The evaluation was performed in terms of the accuracy and precision of the activity concentration estimates.

RESULTS

The results demonstrated that the non-uniform image intensity observed in the reconstructed images in the organs with normal uptake was consistent with uniform activity concentration in the organs on the scale of the voxel size; observed non-uniformities in image intensity were due to a combination of partial-volume effects at the boundaries of the organ, artifacts in the reconstructed image due to collimator-detector response compensation, and noise. Using an ROI defined in a single transaxial slice produced similar biases compared to the three-dimensional (3D) whole-organ VOIs, provided that the transaxial slice was near the central plane of the organ and that the pixels from the organ boundaries were not included in the ROI. Although this slice method was sensitive to noise, biases were less than 10% for all the noise levels studied. The use of spherical VOIs was more sensitive to noise. The method was more accurate for larger spheres and larger organs such as the liver in comparison to the kidneys. Biases lower than 7% were found in the liver when using large enough spheres (radius ≥ 28 mm), regardless of the position, of the VOI inside the organ even with shortened acquisition times. The biases were more position-dependent for smaller organs.

CONCLUSIONS

Both of the simpler methods provided suitable surrogates in terms of accuracy and precision. The results suggested that a spherical VOI was more appropriate for estimating the activity concentration in larger organs such as the liver, regardless of the position of the sphere inside the organ. Larger spheres resulted in better estimates. A single-slice ROI was more suitable for activity estimation in smaller organs such as the kidneys, providing that the transaxial slice selected was near the central plane of the organ and that voxels from the organ boundaries were excluded. Under those conditions, activity concentrations with biases lower than 5% were observed for all the studied count levels and coefficients of variation were less than 9% and 5% for the 25% and 100% count levels, respectively.

Comparison of quantitative Y-90 SPECT and non-time-of-flight PET imaging in post-therapy radioembolization of liver cancer

PURPOSE

Radioembolization with yttrium-90 microspheres may be optimized with patient-specific pretherapy treatment planning. Dose verification and validation of treatment planning methods require quantitative imaging of the post-therapy distribution of yttrium-90 (Y-90). Methods for quantitative imaging of Y-90 using both bremsstrahlung SPECT and PET have previously been described. The purpose of this study was to compare the two modalities quantitatively in humans.

METHODS

Calibration correction factors for both quantitative Y-90 bremsstrahlung SPECT and a non-time-of-flight PET system without compensation for prompt coincidences were developed by imaging three phantoms. The consistency of these calibration correction factors for the different phantoms was evaluated. Post-therapy images from both modalities were obtained from 15 patients with hepatocellular carcinoma who underwent hepatic radioembolization using Y-90 glass microspheres. Quantitative SPECT and PET images were rigidly registered and the total liver activities and activity distributions estimated for each modality were compared. The activity distributions were compared using profiles, voxel-by-voxel correlation and Bland-Altman analyses, and activity-volume histograms.

RESULTS

The mean ± standard deviation of difference in the total activity in the liver between the two modalities was 0% ± 9% (range -21%-18%). Voxel-by-voxel comparisons showed a good agreement in regions corresponding roughly to treated tumor and treated normal liver; the agreement was poorer in regions with low or no expected activity, where PET appeared to overestimate the activity. The correlation coefficients between intrahepatic voxel pairs for the two modalities ranged from 0.86 to 0.94. Cumulative activity volume histograms were in good agreement.

CONCLUSIONS

These data indicate that, with appropriate reconstruction methods and measured calibration correction factors, either Y-90 SPECT/CT or Y-90 PET/CT can be used for quantitative post-therapy monitoring of Y-90 activity distribution following hepatic radioembolization.

Optimization and comparison of simultaneous and separate acquisition protocols for dual isotope myocardial perfusion SPECT

Dual-isotope simultaneous-acquisition (DISA) rest-stress myocardial perfusion SPECT (MPS) protocols offer a number of advantages over separate acquisition. However, crosstalk contamination due to scatter in the patient and interactions in the collimator degrade image quality. Compensation can reduce the effects of crosstalk, but does not entirely eliminate image degradations. Optimizing acquisition parameters could further reduce the impact of crosstalk. In this paper we investigate the optimization of the rest Tl-201 energy window width and relative injected activities using the ideal observer (IO), a realistic digital phantom population and Monte Carlo (MC) simulated Tc-99m and Tl-201 projections as a means to improve image quality. We compared performance on a perfusion defect detection task for Tl-201 acquisition energy window widths varying from 4 to 40 keV centered at 72 keV for a camera with a 9% energy resolution. We also investigated 7 different relative injected activities, defined as the ratio of Tc-99m and Tl-201 activities, while keeping the total effective dose constant at 13.5 mSv. For each energy window and relative injected activity, we computed the IO test statistics using a Markov chain Monte Carlo (MCMC) method for an ensemble of 1,620 triplets of fixed and reversible defect-present, and defect-absent noisy images modeling realistic background variations. The volume under the 3-class receiver operating characteristic (ROC) surface (VUS) was estimated and served as the figure of merit. For simultaneous acquisition, the IO suggested that relative Tc-to-Tl injected activity ratios of 2.6-5 and acquisition energy window widths of 16-22% were optimal. For separate acquisition, we observed a broad range of optimal relative injected activities from 2.6 to 12.1 and acquisition energy window of widths 16-22%. A negative correlation between Tl-201 injected activity and the width of the Tl-201 energy window was observed in these ranges. The results also suggested that DISA methods could potentially provide image quality as good as that obtained with separate acquisition protocols. We compared observer performance for the optimized protocols and the current clinical protocol using separate acquisition. The current clinical protocols provided better performance at a cost of injecting the patient with approximately double the injected activity of Tc-99m and Tl-201, resulting in substantially increased radiation dose.

Optimization of energy window and evaluation of scatter compensation methods in myocardial perfusion SPECT using the ideal observer with and without model mismatch and an anthropomorphic model observer

We used the ideal observer (IO) and IO with model mismatch (IO-MM) applied in the projection domain and an anthropomorphic channelized Hotelling observer (CHO) applied to reconstructed images to optimize the acquisition energy window width and to evaluate various scatter compensation methods in the context of a myocardial perfusion single-photon emission computed tomography (SPECT) defect detection task. The IO has perfect knowledge of the image formation process and thus reflects the performance with perfect compensation for image-degrading factors. Thus, using the IO to optimize imaging systems could lead to suboptimal parameters compared with those optimized for humans interpreting SPECT images reconstructed with imperfect or no compensation. The IO-MM allows incorporating imperfect system models into the IO optimization process. We found that with near-perfect scatter compensation, the optimal energy window for the IO and CHO was similar; in its absence, the IO-MM gave a better prediction of the optimal energy window for the CHO using different scatter compensation methods. These data suggest that the IO-MM may be useful for projectiondomain optimization when MM is significant and that the IO is useful when followed by reconstruction with good models of the image formation process.

Extrastriatal binding of [¹²³I]FP-CIT in the thalamus and pons: gender and age dependencies assessed in a European multicentre database of healthy controls

PURPOSE

Apart from binding to the dopamine transporter (DAT), [(123)I]FP-CIT shows moderate affinity for the serotonin transporter (SERT), allowing imaging of both monoamine transporters in a single imaging session in different brain areas. The aim of this study was to systematically evaluate extrastriatal binding (predominantly due to SERT) and its age and gender dependencies in a large cohort of healthy controls.

METHODS

SPECT data from 103 healthy controls with well-defined criteria of normality acquired at 13 different imaging centres were analysed for extrastriatal binding using volumes of interest analysis for the thalamus and the pons. Data were examined for gender and age effects as well as for potential influence of striatal DAT radiotracer binding.

RESULTS

Thalamic binding was significantly higher than pons binding. Partial correlations showed an influence of putaminal DAT binding on measured binding in the thalamus but not on the pons. Data showed high interindividual variation in extrastriatal binding. Significant gender effects with 31 % higher binding in women than in men were observed in the thalamus, but not in the pons. An age dependency with a decline per decade (±standard error) of 8.2 ± 1.3 % for the thalamus and 6.8 ± 2.9 % for the pons was shown.

CONCLUSION

The potential to evaluate extrastriatal predominant SERT binding in addition to the striatal DAT in a single imaging session was shown using a large database of [(123)I]FP-CIT scans in healthy controls. For both the thalamus and the pons, an age-related decline in radiotracer binding was observed. Gender effects were demonstrated for binding in the thalamus only. As a potential clinical application, the data could be used as a reference to estimate SERT occupancy in addition to nigrostriatal integrity when using [(123)I]FP-CIT for DAT imaging in patients treated with selective serotonin reuptake inhibitors.

Personalized image-based radiation dosimetry for routine clinical use in peptide receptor radionuclide therapy: pretherapy experience

Patient-specific dose calculations are not routinely performed for targeted radionuclide therapy procedures, partly because they are time consuming and challenging to perform. However, it is becoming widely recognized that a personalized dosimetry approach can help plan treatment and improve understanding of the dose-response relationship. In this chapter, we review the procedures and essential elements of an accurate internal dose calculation and propose a simplified approach that is aimed to be practical for use in a busy nuclear medicine department.

Correction for collimator-detector response in SPECT using point spread function template

Compensating for the collimator-detector response (CDR) in SPECT is important for accurate quantification. The CDR consists of both a geometric response and a septal penetration and collimator scatter response. The geometric response can be modeled analytically and is often used for modeling the whole CDR if the geometric response dominates. However, for radionuclides that emit medium or high-energy photons such as I-131, the septal penetration and collimator scatter response is significant and its modeling in the CDR correction is important for accurate quantification. There are two main methods for modeling the depth-dependent CDR so as to include both the geometric response and the septal penetration and collimator scatter response. One is to fit a Gaussian plus exponential function that is rotationally invariant to the measured point source response at several source-detector distances. However, a rotationally-invariant exponential function cannot represent the star-shaped septal penetration tails in detail. Another is to perform Monte-Carlo (MC) simulations to generate the depth-dependent point spread functions (PSFs) for all necessary distances. However, MC simulations, which require careful modeling of the SPECT detector components, can be challenging and accurate results may not be available for all of the different SPECT scanners in clinics. In this paper, we propose an alternative approach to CDR modeling. We use a Gaussian function plus a 2-D B-spline PSF template and fit the model to measurements of an I-131 point source at several distances. The proposed PSF-template-based approach is nearly non-parametric, captures the characteristics of the septal penetration tails, and minimizes the difference between the fitted and measured CDR at the distances of interest. The new model is applied to I-131 SPECT reconstructions of experimental phantom measurements, a patient study, and a MC patient simulation study employing the XCAT phantom. The proposed model yields up to a 16.5 and 10.8% higher recovery coefficient compared to the results with the conventional Gaussian model and the Gaussian plus exponential model, respectively.

MIRD pamphlet No. 23: quantitative SPECT for patient-specific 3-dimensional dosimetry in internal radionuclide therapy

In internal radionuclide therapy, a growing interest in voxel-level estimates of tissue-absorbed dose has been driven by the desire to report radiobiologic quantities that account for the biologic consequences of both spatial and temporal nonuniformities in these dose estimates. This report presents an overview of 3-dimensional SPECT methods and requirements for internal dosimetry at both regional and voxel levels. Combined SPECT/CT image-based methods are emphasized, because the CT-derived anatomic information allows one to address multiple technical factors that affect SPECT quantification while facilitating the patient-specific voxel-level dosimetry calculation itself. SPECT imaging and reconstruction techniques for quantification in radionuclide therapy are not necessarily the same as those designed to optimize diagnostic imaging quality. The current overview is intended as an introduction to an upcoming series of MIRD pamphlets with detailed radionuclide-specific recommendations intended to provide best-practice SPECT quantification-based guidance for radionuclide dosimetry.

Quantification and reduction of the collimator-detector response effect in SPECT by applying a system model during iterative image reconstruction: a simulation study

BACKGROUND

Detector blurring and non-ideal collimation decrease the spatial resolution of the single-photon emission computed tomography (SPECT) images. Iterative reconstruction algorithms such as ordered subsets expectation maximization (OSEM) can incorporate degrading factors during reconstruction. We investigated the quantitative errors associated with poor SPECT resolution and evaluated the importance of two-dimensional (2D) and three-dimensional (3D) resolution recovery by modelling system response during iterative image reconstruction.

METHODS

Different phantoms consisted of the NURBS-based cardiac-torso (NCAT) liver phantom with small tumors, the Zubal brain phantom and the NCAT heart phantom were used in this study. Monte Carlo simulation was used to create SPECT projections. Gaussian functions were used to model collimator detector response (CDR). Modeled CDRs were applied during OSEM. Both noise-free and noisy projections were created.

RESULTS

Even with noise-free projections, conventional OSEM algorithm provided limited quantitative accuracy compared to both 2D and 3D resolution recovery. The 3D implementation of resolution recovery, however, yielded superior results compared to its 2D implementation. For the liver phantom, the ability to distinguish small tumors in both transverse and axial planes was improved. For the brain phantom, gray to white matter activity ratio was increased from 3.14 ± 0.04 in simple OSEM to 3.84 ± 0.06 in 3D OSEM. For the NCAT heart phantom, 3D resolution recovery, results in images with thinner wall and higher contrast for different noise levels.

CONCLUSION

There are considerable quantitative errors associated with CDR, especially when the size of the target is comparable with the spatial resolution of the system. Between different reconstruction algorithms, 3D OSEM that consider the 3D nature of CDR, improve both the visual quality and the quantitative accuracy of any SPECT studies.

Evaluation of a method for projection-based tissue-activity estimation within small volumes of interest

A new method of compensating for tissue-fraction and count-spillover effects, which require tissue segmentation only within a small volume surrounding the primary lesion of interest, was evaluated for SPECT imaging. Tissue-activity concentration estimates are obtained by fitting the measured projection data to a statistical model of the segmented tissue projections. Multiple realizations of two simulated human-torso phantoms, each containing 20 spherical 'tumours', 1.6 cm in diameter, with tumour-to-background ratios of 8:1 and 4:1, were simulated. Estimates of tumour- and background-activity concentration values for homogeneous as well as inhomogeneous tissue activities were compared to the standard uptake value (SUV) metrics on the basis of accuracy and precision. For perfectly registered, high-contrast, superficial lesions in a homogeneous background without scatter, the method yielded accurate (<0.4% bias) and precise (<6.1%) recovery of the simulated activity values, significantly outperforming the SUV metrics. Tissue inhomogeneities, greater tumour depth and lower contrast ratios degraded precision (up to 11.7%), but the estimates remained almost unbiased. The method was comparable in accuracy but more precise than a well-established matrix inversion approach, even when errors in tumour size and position were introduced to simulate moderate inaccuracies in segmentation and image registration. Photon scatter in the object did not significantly affect the accuracy or precision of the estimates.

Improved regional activity quantitation in nuclear medicine using a new approach to correct for tissue partial volume and spillover effects

We have developed a new method of compensating for effects of partial volume and spillover in dual-modality imaging. The approach requires segmentation of just a few tissue types within a small volume-of-interest (VOI) surrounding a lesion; the algorithm estimates simultaneously, from projection data, the activity concentration within each segmented tissue inside the VOI. Measured emission projections were fitted to the sum of resolution-blurred projections of each such tissue, scaled by its unknown activity concentration, plus a global background contribution obtained by reprojection through the reconstructed image volume outside the VOI. The method was evaluated using multiple-pinhole μSPECT data simulated for the MOBY mouse phantom containing two spherical lung tumors and one liver tumor, as well as using multiple-bead phantom data acquired on μSPECT and μCT scanners. Each VOI in the simulation study was 4.8 mm (12 voxels) cubed and, depending on location, contained up to four tissues (tumor, liver, heart, lung) with different values of relative (99m)Tc concentration. All tumor activity estimates achieved bias after ∼ 15 ordered-subsets expectation maximization (OSEM) iterations (×10 subsets) , with better than 8% precision ( ≤ 25% greater than the Cramer-Rao lower bound). The projection-based fitting approach also outperformed three standardized uptake value (SUV)-like metrics, one of which was corrected for count spillover. In the bead phantom experiment, the mean ± standard deviation of the bias of VOI estimates of bead concentration were 0.9±9.5%, comparable to those of a perturbation geometric transfer matrix (pGTM) approach (-5.4±8.6%); however, VOI estimates were more stable with increasing iteration number than pGTM estimates, even in the presence of substantial axial misalignment between μCT and μSPECT image volumes.

Potential of discrete Gaussian edge feathering method for improving abutment dosimetry in eMLC-delivered segmented-field electron conformal therapy

PURPOSE

The purpose of this work was to investigate the potential of discrete Gaussian edge feathering of the higher energy electron fields for improving abutment dosimetry in the planning volume when using an electron multileaf collimator (eMLC) to deliver segmented-field electron conformal therapy (ECT).

METHODS

A discrete (five-step) Gaussian edge spread function was used to match dose penumbras of differing beam energies (6-20 MeV) at a specified depth in a water phantom. Software was developed to define the leaf eMLC positions of an eMLC that most closely fit each electron field shape. The effect of 1D edge feathering of the higher energy field on dose homogeneity was computed and measured for segmented-field ECT treatment plans for three 2D PTVs in a water phantom, i.e., depth from the water surface to the distal PTV surface varied as a function of the x-axis (parallel to leaf motion) and remained constant along the y-axis (perpendicular to leaf motion). Additionally, the effect of 2D edge feathering was computed and measured for one radially symmetric, 3D PTV in a water phantom, i.e., depth from the water surface to the distal PTV surface varied as a function of both axes. For the 3D PTV, the feathering scheme was evaluated for 0.1-1.0-cm leaf widths. Dose calculations were performed using the pencil beam dose algorithm in the Pinnacle(3) treatment planning system. Dose verification measurements were made using a prototype eMLC (1-cm leaf width).

RESULTS

1D discrete Gaussian edge feathering reduced the standard deviation of dose in the 2D PTVs by 34, 34, and 39%. In the 3D PTV, the broad leaf width (1 cm) of the eMLC hindered the 2D application of the feathering solution to the 3D PTV, and the standard deviation of dose increased by 10%. However, 2D discrete Gaussian edge feathering with simulated eMLC leaf widths of 0.1-0.5 cm reduced the standard deviation of dose in the 3D PTV by 33-28%, respectively.

CONCLUSIONS

A five-step discrete Gaussian edge spread function applied in 2D improves the abutment dosimetry but requires an eMLC leaf resolution better than 1 cm.

Fast Monte Carlo-simulator with full collimator and detector response modelling for SPECT

OBJECTIVE

Monte Carlo (MC)-simulations have proved to be a valuable tool in studying SPECT-reconstruction algorithms. Despite their popularity, the use of Monte Carlo-simulations is still often limited by their large computation demand. This is especially true in situations where full collimator and detector modelling with septal penetration, scatter and X-ray fluorescence needs to be included. This paper presents a rapid and simple MC-simulator, which can effectively reduce the computation times.

METHODS

The simulator was built on the convolution-based forced detection principle, which can markedly lower the number of simulated photons. Full collimator and detector response look-up tables are pre-simulated and then later used in the actual MC-simulations to model the system response. The developed simulator was validated by comparing it against (123)I point source measurements made with a clinical gamma camera system and against (99m)Tc software phantom simulations made with the SIMIND MC-package.

RESULTS

The results showed good agreement between the new simulator, measurements and the SIMIND-package. The new simulator provided near noise-free projection data in approximately 1.5 min per projection with (99m)Tc, which was less than one-tenth of SIMIND's time.

CONCLUSION

The developed MC-simulator can markedly decrease the simulation time without sacrificing image quality.

Experimental determination of the weighting factor for the energy window subtraction-based downscatter correction for I-123 in brain SPECT studies

Correction for downscatter in I-123 SPECT can be performed by the subtraction of a secondary energy window from the main window, as in the triple-energy window method. This is potentially noise sensitive. For studies with limited amount of counts (e.g. dynamic studies), a broad subtraction window with identical width is preferred. This secondary window needs to be weighted with a factor higher than one, due to a broad backscatter peak from high-energy photons appearing at 172 keV. Spatial dependency and the numerical value of this weighting factor and the image contrast improvement of this correction were investigated in this study. Energy windows with a width of 32 keV were centered at 159 keV and 200 keV. The weighting factor was measured both with an I-123 point source and in a dopamine transporter brain SPECT study in 10 human subjects (5 healthy subjects and 5 patients) by minimizing the background outside the head. Weighting factors ranged from 1.11 to 1.13 for the point source and from 1.16 to 1.18 for human subjects. Point source measurements revealed no position dependence. After correction, the measured specific binding ratio (image contrast) increased significantly for healthy subjects, typically by more than 20%, while the background counts outside of all subjects were effectively removed. A weighting factor of 1.1–1.2 can be applied in clinical practice. This correction effectively removes downscatter and significantly improves image contrast inside the brain.

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.

Absolute quantification in SPECT

Single-photon emission computed tomography (SPECT) allows the three-dimensional visualization of radioactivity within the human body and is widely used for clinical purposes. In SPECT, image quality is compromised by several factors including photon attenuation, photon scatter, the partial volume effect, and motion artefacts. These variables also confound the capacity of SPECT to quantify the concentration of radioactivity within given volumes of interest in absolute units, e.g. as kilobecquerels per cubic centimetre. In the last decade, considerable technical progress has been achieved in SPECT image reconstruction, involving, in particular, the development of iterative image reconstruction techniques. Furthermore, hybrid cameras integrating a SPECT camera with an X-ray CT scanner have become commercially available. These systems allow the acquisition of SPECT and CT datasets registered to each other with a high anatomical accuracy. First studies have shown that iterative SPECT image reconstruction techniques incorporating information from SPECT/CT image datasets greatly increase the accuracy of SPECT in quantifying radioactivity concentrations in phantoms and also in humans. This new potential of SPECT may improve not only diagnostic accuracy, but also dosimetry for internal radiotherapy.

The Role of CT-Based Attenuation Correction and Collimator Blurring Correction in Striatal Spect Quantification

Purpose. Striatal single photon emission computed tomography (SPECT) imaging of the dopaminergic system is becoming increasingly used for clinical and research studies. The question about the value of nonuniform attenuation correction has become more relevant with the increasing availability of hybrid SPECT-CT scanners. In this study, the value of nonuniform attenuation correction and correction for collimator blurring were determined using both phantom data and patient data. Methods. SPECT imaging was performed using 7 anthropomorphic phantom measurements, and 14 patient studies using [I-123]-FP-CIT (DATSCAN). SPECT reconstruction was performed using uniform and nonuniform attenuation correction and collimator blurring corrections. Recovery values (phantom data) or average-specific uptake ratios (patient data) for the different reconstructions were compared at similar noise levels. Results. For the phantom data, improved recovery was found with nonuniform attenuation correction and collimator blurring corrections, with further improvement when performed together. However, for patient data the highest average specific uptake ratio was obtained using collimator blurring correction without nonuniform attenuation correction, probably due to subtle SPECT-CT misregistration. Conclusions. This study suggests that an optimal brain SPECT reconstruction (in terms of the lowest bias) in patients would include a correction for collimator blurring and uniform attenuation correction.

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.

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.

Dopamine D2 receptor SPECT with (123)I-IBZM: evaluation of collimator and post-filtering when using model-based compensation-a Monte Carlo study

In (123)I-IBZM brain SPECT, the main interest is the activity uptake in the striatum relative to the background, and semi-quantitative techniques using regions of interest are typically used for this purpose. Uncertainties in the measured uptakes can however be a problem due to low contrasts and high noise levels. Like SPECT in general, IBZM SPECT should benefit from reconstruction methods that include model-based compensation, but it is important that image acquisition is optimized for this technique. An important factor is the choice of collimator. In this study we compare four different parallel-hole collimators for IBZM SPECT regarding overall quantitative accuracy and measured uptake ratio as a function of image noise and uncertainty. The collimators are low-energy high-resolution (LEHR), low-energy general-purpose (LEGP), extended LEGP (ELEGP) and medium-energy general-purpose (MEGP). The effect of three Butterworth post-filters with cut-off frequencies of 0.3, 0.45 and 0.6 cm(-1) (power factor 8) is also studied. All raw-data projections are produced using Monte Carlo simulations. Of the investigated collimators, the one that is most sensitive to the primary photons, ELEGP, proved to be the most optimal for realistic noise levels. Butterworth post-filtering is advantageous, and the cut-off frequency 0.45 cm(-1) was the best compromise in this study.

The impact of reconstruction method on the quantification of DaTSCAN images

PURPOSE

Reconstruction of DaTSCAN brain studies using OS-EM iterative reconstruction offers better image quality and more accurate quantification than filtered back-projection. However, reconstruction must proceed for a sufficient number of iterations to achieve stable and accurate data. This study assessed the impact of the number of iterations on the image quantification, comparing the results of the iterative reconstruction with filtered back-projection data.

METHODS

A striatal phantom filled with (123)I using striatal to background ratios between 2:1 and 10:1 was imaged on five different gamma camera systems. Data from each system were reconstructed using OS-EM (which included depth-independent resolution recovery) with various combinations of iterations and subsets to achieve up to 200 EM-equivalent iterations and with filtered back-projection. Using volume of interest analysis, the relationships between image reconstruction strategy and quantification of striatal uptake were assessed.

RESULTS

For phantom filling ratios of 5:1 or less, significant convergence of measured ratios occurred close to 100 EM-equivalent iterations, whereas for higher filling ratios, measured uptake ratios did not display a convergence pattern. Assessment of the count concentrations used to derive the measured uptake ratio showed that nonconvergence of low background count concentrations caused peaking in higher measured uptake ratios. Compared to filtered back-projection, OS-EM displayed larger uptake ratios because of the resolution recovery applied in the iterative algorithm.

CONCLUSION

The number of EM-equivalent iterations used in OS-EM reconstruction influences the quantification of DaTSCAN studies because of incomplete convergence and possible bias in areas of low activity due to the nonnegativity constraint in OS-EM reconstruction. Nevertheless, OS-EM using 100 EM-equivalent iterations provides the best linear discriminatory measure to quantify the uptake in DaTSCAN studies.

Quantitative evaluation of simultaneous reconstruction with model-based crosstalk compensation for 99mTc/123I dual-isotope simultaneous acquisition brain SPECT

A model-based method has been previously developed to estimate and compensate for the crosstalk and downscatter contamination in simultaneous 123I/99mTc dual-isotope SPECT imaging. In this method, photon scatter in the object is modeled using the effective source scatter estimate technique. Photon interactions with the collimator-detector are estimated using precalculated Monte Carlo simulated point response functions. Two different approaches, simultaneous and alternating model-based compensations, have been proposed for iterative reconstruction-based crosstalk and downscatter contamination compensation. In this work, both model-based approaches were evaluated in the context of quantitative accuracy when imaging the dopaminergic system using both Monte Carlo simulated and experimentally acquired data. Results indicate that mddel-based estimates of the crosstalk and downscatter contamination in both energy windows were in good agreement with the truth for the simulated data. The effects of the contamination reduced image contrast and overestimated absolute activity in all structures by up to 66%. Compensation using both model-based approaches improved image contrast. Errors in absolute activity quantitation were also reduced to less than +/-5% for most brain structures. The accuracy of striatal specific binding potentials, calculated as the ratio of activity in various striatal structures to the background, was also greatly improved after model-based compensation. In conclusion, model-based compensation of simultaneously acquired images of 99mTc and 123I labeled brain imaging agents provided image quality and quantitative accuracy that were comparable to the image without crosstalk. Both proposed compensation approaches can potentially be applied clinically, but when reconstruction time is a limiting factor, the alternating model-based compensation may be preferable.

Striatal dopamine D2 binding is related to frontal BOLD response during updating of long-term memory representations

Multi-modal brain imaging was used to examine the relation between individual differences in resting-state striatal dopamine D2 binding and the magnitude of prefrontal BOLD activation during updating of long-term memory (LTM) representations. Increased activity in the left prefrontal cortex was observed when LTM updating was required, and there was a positive correlation between striatal D2 activity and the magnitude of left prefrontal activity during updating. These findings support predictions from neurocomputational models of a relation of dopaminergic neurotransmission to transient cognitive operations and related brain activity.

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.

Accuracy of quantitative reconstructions in SPECT/CT imaging

The goal of this study was to determine the quantitative accuracy of our OSEM-APDI reconstruction method based on SPECT/CT imaging for Tc-99m, In-111, I-123, and I-131 isotopes. Phantom studies were performed on a SPECT/low-dose multislice CT system (Infinia-Hawkeye-4 slice, GE Healthcare) using clinical acquisition protocols. Two radioactive sources were centrally and peripherally placed inside an anthropometric Thorax phantom filled with non-radioactive water. Corrections for attenuation, scatter, collimator blurring and collimator septal penetration were applied and their contribution to the overall accuracy of the reconstruction was evaluated. Reconstruction with the most comprehensive set of corrections resulted in activity estimation with error levels of 3-5% for all the isotopes.

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.