Phantom and methodology for comparison of small lesion detectability in PET

PURPOSE

The main goal of this work is to describe a phantom design, data acquisition and data analysis methodology enabling comparison of small lesion detectability between PET imaging systems and reconstruction algorithms. Several methods are currently available to characterize intrinsic and image quality performance, but none focus exclusively on small lesion detectability.

METHODS

We previously developed a small-lesion detection phantom and described initial results using a head-size phantom. Unlike most fillable nuclear medicine phantoms, this phantom offers a semi-realistic heterogenous background and wall-less contrast features. In this work, the methodology is extended to include (a) the use of both head- and body-sized phantoms and (b) a multi-scan data collection and analysis method. We present an example use case of the phantom and detection estimation methodology, comparing the small-lesion detection performance across four commercial PET/CT systems.

RESULTS

Repeat acquisitions of the phantom enabled estimation of model observer performance and surrogates of detectability. As anticipated, estimated detectability increased with the square root of system sensitivity and TOF offered marked improvement in detectability, especially for the body sized object. The proposed approach characterizing detectability at different times during the decay of the phantom enabled comparison of small lesion detectability at matched activity concentrations (and scan durations) across different scanners.

CONCLUSION

The proposed approach offers a reproducible tool for evaluating relative tradeoffs of system performance on small lesion detectability.

Multi-Objective Evolutionary Algorithm for PET Image Reconstruction: Concept

In many diagnostic imaging settings, including positron emission tomography (PET), images are typically used for multiple tasks such as detecting disease and quantifying disease. Unlike conventional image reconstruction that optimizes a single objective, this work proposes a multi-objective optimization algorithm for PET image reconstruction to identify a set of images that are optimal for more than one task. This work is reliant on a genetic algorithm to evolve a set of solutions that satisfies two distinct objectives. In this paper, we defined the objectives as the commonly used Poisson log-likelihood function, typically reflective of quantitative accuracy, and a variant of the generalized scan-statistic model, to reflect detection performance. The genetic algorithm uses new mutation and crossover operations at each iteration. After each iteration, the child population is selected with non-dominated sorting to identify the set of solutions along the dominant front or fronts. After multiple iterations, these fronts approach a single non-dominated optimal front, defined as the set of PET images for which none the objective function values can be improved without reducing the opposing objective function. This method was applied to simulated 2D PET data of the heart and liver with hot features. We compared this approach to conventional, single-objective approaches for trading off performance: maximum likelihood estimation with increasing explicit regularization and maximum a posteriori estimation with varying penalty strength. Results demonstrate that the proposed method generates solutions with comparable to improved objective function values compared to the conventional approaches for trading off performance amongst different tasks. In addition, this approach identifies a diverse set of solutions in the multi-objective function space which can be challenging to estimate with single-objective formulations.

Sharing and Selling Images: Ethical and Regulatory Considerations for Radiologists

Opportunities to share or sell images are common in radiology. But because these images typically originate as protected health information, their use admits a host of ethical and regulatory considerations. This article discusses four scenarios that reflect data sharing or selling arrangements in radiology, especially as they might occur in "big data" systems or applications. The objective of this article is to acquaint radiologists with a variety of regulatory standards and ethical perspectives that pertain to certain data use agreements, such that the attitudes and practices of data holders and their sharers or purchasers can withstand ethical or regulatory scrutiny and not invite undesirable outcomes.

Correction to: Ovarian torsion: developing a machine-learned algorithm for diagnosis

The original version of this paper included errors in Fig. 3. The corrected Fig. 3 is presented here.

Technical Note: A digital reference object representing Hoffman's 3D brain phantom for PET scanner simulations

PURPOSE

Physical and digital phantoms play a key role in the development and testing of nuclear medicine instrumentation and processing algorithms for clinical and research applications, including neuroimaging using positron emission tomography (PET). We have developed and tested a digital reference object (DRO) version of the original segmented magnetic resonance imaging (MRI) data used for the three-dimensional (3D) PET brain phantom developed by Hoffman et al., which is used as the basis of a commercially available physical test phantom.

METHODS

The DRO was constructed by subdividing the MRI image planes the original phantom was based on to create equal-thickness slices and re-labeling voxels. The digital data was then embedded in a PET Digital Imaging and Communications in Medicine format and tested for compliance.

RESULTS

We then tested the DRO by comparing it to computed tomography (CT) images of the physical phantom summed to form composite slices with axial extent similar to the DRO, but with a factor of two better in-slice resolution. For composite slices, 91% of voxels were labeled in full agreement, 5% of the voxels were 50-75% accurate, and the remaining 4% of voxels had 25% or less agreement.

CONCLUSIONS

This DRO can be used as an input for PET scanner simulation studies or for comparing simulations to measured Hoffman phantom images.

Comparison of Micro-Computed Tomography and Clinical Computed Tomography Protocols for Visualization of Nasal Cartilage Before Surgical Planning for Rhinoplasty

Importance

There is no imaging standard to model nasal cartilage for the planning of rhinoplasty procedures. Preoperative visualization of cartilage may improve objective evaluation of nasal deformities, surgical planning, and surgical reconstruction.

Objectives

To evaluate the feasibility of visualizing nasal cartilage using high resolution micro-computed tomography (CT) compared with the criterion standard of pathologic findings in a cadaveric specimen and to evaluate its accuracy compared with various clinical CT protocols.

Design, Setting, and Participants

Anatomic study at the University of Washington using single human cadaveric nasal specimens performed from July 10, 2017, to March 30, 2018.

Interventions

A micro-CT acquisition with 60-micron resolution was obtained of a nasal specimen. The specimen was then scanned with 5 different clinical CT protocols to span both clinical care and machine limits. The specimen was then sectioned in 5-mm axial slices for pathologic analysis.

Main Outcomes and Measures

Micro-CT images were registered to pathologic specimen cross-sections using a graphite fiducial system. Cartilage substructures were manually segmented and analyzed. A library of matched images across the micro-CT and various clinical CT protocols was then developed. Region of interest analysis was performed for each of the cartilage structures and their boundaries on clinical CT protocols and micro-CT, with the outcome of mean (SD) density using Hounsfield units.

Results

A single human cadaveric nasal specimen was used to obtain the following results. Lower lateral cartilage, upper lateral cartilage, and septal cartilage were accurately delineated on the micro-CT images compared with pathologic findings. The mean absolute deviation from pathologic findings was 0.30 mm for septal cartilage thickness, 0.98 mm for maximal upper lateral cartilage length, and 1.40 mm for maximal lower lateral cartilage length. On clinical CT protocols, only septal cartilage was well discriminated from boundary. Higher radiation dose resulted in more accurate density measurements of cartilage, but it did not ultimately improve ability to discriminate cartilage.

Conclusions and Relevance

The results of this anatomic study may represent a notable step toward advancing knowledge of the capabilities and pitfalls of nasal cartilage visualization on CT. Nasal cartilage visualization was feasible on the micro-CT compared with pathologic findings. Future research may further examine the barriers to accurately visualizing upper lateral cartilage and lower lateral cartilage, a prerequisite for clinical application.

Level of Evidence

NA.

Accuracy of Myocardial Blood Flow Estimation From Dynamic Contrast-Enhanced Cardiac CT Compared With PET

Background The accuracy of absolute myocardial blood flow (MBF) from dynamic contrast-enhanced cardiac computed tomography acquisitions has not been fully characterized. We evaluate computed tomography (CT) compared with rubidium-82 positron emission tomography (PET) MBF estimates in a high-risk population. Methods In a prospective trial, patients receiving clinically indicated rubidium-82 PET exams were recruited to receive a dynamic contrast-enhanced cardiac computed tomography exam. The CT protocol included a rest and stress dynamic portion each acquiring 12 to 18 cardiac-gated frames. The global MBF was estimated from the PET and CT exam. Results Thirty-four patients referred for cardiac rest-stress PET were recruited. Of the 68 dynamic contrast-enhanced cardiac computed tomography scans, 5 were excluded because of injection errors or mismatched hemodynamics. The CT-derived global MBF was highly correlated with the PET MBF (r=0.92; P<0.001) with a mean difference of 0.7±26.4%. The CT MBF estimates were within 20% of PET estimates ( P<0.02) with a mean of (1) MBF for resting flow of PET versus CT of 0.9±0.3 versus 1.0±0.2 mL/min per gram and (2) MBF for stress flow of 2.1±0.7 versus 2.0±0.8 mL/min per gram. Myocardial flow reserve was -14±28% underestimated with CT (PET versus CT myocardial flow reserve, 2.5±0.6 versus 2.2±0.6). The proposed rest+stress+computed tomography angiography protocol had a dose length product of 598±76 mGy×cm resulting in an approximate effective dose of 8.4±1.1 mSv. Conclusions In a high-risk clinical population, a clinically practical dynamic contrast-enhanced cardiac computed tomography provided unbiased MBF estimates within 20% of rubidium-82 PET. Although unbiased, the CT estimates contain substantial variance with an standard error of the estimate of 0.44 mL/min per gram. Myocardial flow reserve estimation was not as accurate as individual MBF estimates.

Performance evaluation of the 5-Ring GE Discovery MI PET/CT system using the national electrical manufacturers association NU 2-2012 Standard

The GE Discovery MI PET/CT system has a modular digital detector design allowing three, four, or five detector block rings that extend the axial field-of-view (FOV) from 15 to 25 cm in 5 cm increments. This study investigated the performance of the 5-ring system and compared it to 3- and 4-ring systems; the GE Discovery IQ system that uses conventional photomultiplier tubes; and the GE Signa PET/MR system that has a reduced transaxial FOV.

METHODS

PET performance was evaluated at three different institutions. Spatial resolution, sensitivity, counting rate performance, accuracy, and image quality were measured in accordance with National Electrical Manufacturers Association NU 2-2012 standards. The mean energy resolution, mean timing resolution, and PET/CT subsystem alignment were also measured. Phantoms were used to determine the effects of varying acquisition time and reconstruction parameters on image quality. Retrospective patient scans were reconstructed with various scan durations to evaluate the impact on image quality.

RESULTS

Results from all three institutions were similar. Radial/tangential/axial full width at half maximum spatial resolution measurements using the filtered back projection algorithm were 4.3/4.3/5.0 mm, 5.5/4.6/6.5 mm, and 7.4/5.0/6.6 mm at 1, 10, and 20 cm from the center of the FOV, respectively. Measured sensitivity at the center of the FOV (20.84 cps/kBq) was significantly higher than systems with reduced axial FOV. The peak noise-equivalent counting rate was 266.3 kcps at 20.8 kBq/ml, with a corresponding scatter fraction of 40.2%. The correction accuracy for count losses up to the peak noise-equivalent counting rate was 3.6%. For the 10-, 13-, 17-, 22-, 28-, and 37-mm spheres, contrast recoveries in the image quality phantom were measured to be 46.2%, 54.3%, 66.1%, 71.1%, 85.3%, and 89.3%, respectively. The mean energy and timing resolution were 9.55% and 381.7 ps, respectively. Phantom and patient images demonstrated excellent image quality, even at short acquisition times or low injected activity.

CONCLUSION

Compared to other PET/CT models, the extended axial FOV improved the overall PET performance of the 5-ring GE Discovery MI scanner. This system offers the potential to reduce scan times or injected activities through increased sensitivity.

Patient body motion correction for dynamic cardiac PET-CT by attenuation-emission alignment according to projection consistency conditions

INTRODUCTION

Patient body motion is known to cause large deviations in the determination of myocardial blood flow (MBF) with errors exceeding 300%. Accurate correction for patient whole-body motion is still a largely unsolved problem in cardiac positron emission tomography (PET) imaging.

OBJECTIVE

This study evaluated the efficacy of using Natterer's formulation of the Helgason-Ludwig consistency conditions on the two-dimensional Radon transform to align computed tomography to PET projection data in multiple time frames of a dynamic sequence for the purpose of frame-by-frame correction of rigid whole-body motion.

METHODS

The correction algorithm was evaluated with digital NCAT phantoms using realistic noise added by the analytical simulator. Count rates used in the simulation were derived from clinical patient data. In addition, a proof of concept test using measured data with a cardiac torso phantom was conducted.

RESULTS

Motion correction resulted in significant improvement in the accuracy of MBF estimates, especially for high count-rate acquisitions. Maximum errors for 2 cm of motion dropped from 325% to 25% and from 250% to 25% using global and regional partial-volume correction, respectively. Median MBF errors dropped from 33% to 4.5% and 27% to 3.8%, respectively. Importantly, the correction algorithm performed equally well to compensate for body motion in both early and late time frames.

CONCLUSION

Cardiac PET-CT data used for attenuation correction (CTAC) alignment using projection consistency conditions was effective for reducing errors in MBF measurements due to simulated patient motion, and can be integrated into the image reconstruction workflow.

Establishment of normative values for the fetal posterior fossa by magnetic resonance imaging

OBJECTIVE

Suspected Dandy-Walker continuum anomalies constitute a significant percentage of prenatal cases evaluated by magnetic resonance imaging (MRI). To unify the description of posterior fossa malformations, we sought to establish objective measurements for the posterior fossa in normal fetuses between 18 and 37 weeks gestation.

METHODS

T2-weighted images of normal fetal brains in sagittal projection were obtained from fetal magnetic resonance (MR) studies of normal brains performed from 2009 to 2017.121 fetal brains were included in the analysis. Three radiologists reviewed images and recorded the following for each case: superior posterior fossa angle (SPFA), posterior fossa perimeter, and tegmento-vermian angle (TVA).

RESULTS

For each feature, the mean of the measurements, the percentage of absolute difference of the reader measurement compared with mean measurement, and the interclass correlation (ICC) were calculated. Values are reported as mean ± standard deviation. Perimeter increases linearly with age, whereas the SPFA and the TVA are independent of gestational age. For all included cases, the SPFA averaged 100.9° ± 8° and the TVA averaged 2.5° ± 2.3°.

CONCLUSION

The superior posterior fossa angle, a novel measurement, and the posterior fossa perimeter can be used for establishing the expected size of the posterior fossa in second- and third-trimester fetuses by MRI.

CT Detectability of Small Low-Contrast Hypoattenuating Focal Lesions: Iterative Reconstructions versus Filtered Back Projection

Purpose To investigate performance in detectability of small (≤1 cm) low-contrast hypoattenuating focal lesions by using filtered back projection (FBP) and iterative reconstruction (IR) algorithms from two major CT vendors across a range of 11 radiation exposures. Materials and Methods A low-contrast detectability phantom consisting of 21 low-contrast hypoattenuating focal objects (seven sizes between 2.4 and 10.0 mm, three contrast levels) embedded into a liver-equivalent background was scanned at 11 radiation exposures (volume CT dose index range, 0.5-18.0 mGy; size-specific dose estimate [SSDE] range, 0.8-30.6 mGy) with four high-end CT platforms. Data sets were reconstructed by using FBP and varied strengths of image-based, model-based, and hybrid IRs. Sixteen observers evaluated all data sets for lesion detectability by using a two-alternative-forced-choice (2AFC) paradigm. Diagnostic performances were evaluated by calculating area under the receiver operating characteristic curve (AUC) and by performing noninferiority analyses. Results At benchmark exposure, FBP yielded a mean AUC of 0.79 ± 0.09 (standard deviation) across all platforms which, on average, was approximately 2% lower than that observed with the different IR algorithms, which showed an average AUC of 0.81 ± 0.09 (P = .12). Radiation decreases of 30%, 50%, and 80% resulted in similar declines of observer detectability with FBP (mean AUC decrease, -0.02 ± 0.05, -0.03 ± 0.05, and -0.05 ± 0.05, respectively) and all IR methods investigated (mean AUC decrease, -0.00 ± 0.05, -0.04 ± 0.05, and -0.04 ± 0.05, respectively). For each radiation level and CT platform, variance in performance across observers was greater than that across reconstruction algorithms (P = .03). Conclusion Iterative reconstruction algorithms have limited radiation optimization potential in detectability of small low-contrast hypoattenuating focal lesions. This task may be further complicated by a high degree of variation in radiologists' performances, seemingly exceeding real performance differences among reconstruction algorithms. © RSNA, 2018 Online supplemental material is available for this article.

Quantitative myocardial perfusion from static cardiac and dynamic arterial CT

Quantitative myocardial blood flow (MBF) estimation by dynamic contrast enhanced cardiac computed tomography (CT) requires multi-frame acquisition of contrast transit through the blood pool and myocardium to inform the arterial input and tissue response functions. Both the input and the tissue response functions for the entire myocardium are sampled with each acquisition. However, the long breath holds and frequent sampling can result in significant motion artifacts and relatively high radiation dose. To address these limitations, we propose and evaluate a new static cardiac and dynamic arterial (SCDA) quantitative MBF approach where (1) the input function is well sampled using either prediction from pre-scan timing bolus data or measured from dynamic thin slice 'bolus tracking' acquisitions, and (2) the whole-heart tissue response data is limited to one contrast enhanced CT acquisition. A perfusion model uses the dynamic arterial input function to generate a family of possible myocardial contrast enhancement curves corresponding to a range of MBF values. Combined with the timing of the single whole-heart acquisition, these curves generate a lookup table relating myocardial contrast enhancement to quantitative MBF. We tested the SCDA approach in 28 patients that underwent a full dynamic CT protocol both at rest and vasodilator stress conditions. Using measured input function plus single (enhanced CT only) or plus double (enhanced and contrast free baseline CT's) myocardial acquisitions yielded MBF estimates with root mean square (RMS) error of 1.2 ml/min/g and 0.35 ml/min/g, and radiation dose reductions of 90% and 83%, respectively. The prediction of the input function based on timing bolus data and the static acquisition had an RMS error compared to the measured input function of 26.0% which led to MBF estimation errors greater than threefold higher than using the measured input function. SCDA presents a new, simplified approach for quantitative perfusion imaging with an acquisition strategy offering substantial radiation dose and computational complexity savings over dynamic CT.

Hepatotoxic Dose Thresholds by Positron-Emission Tomography After Yttrium-90 Radioembolization of Liver Tumors: A Prospective Single-Arm Observational Study

PURPOSE

To define a threshold radiation dose to non-tumoral liver from ⁹⁰Y radioembolization that results in hepatic toxicity using pair-production PET.

MATERIALS AND METHODS

This prospective single-arm study enrolled 35 patients undergoing radioembolization. A total of 34 patients (27 with HCC and 7 with liver metastases) were included in the final analysis. Of 27 patients with underlying cirrhosis, 22 and 5 patients were Child-Pugh A and B, respectively. Glass and resin microspheres were used in 32 (94%) and 2 (6%) patients, respectively. Lobar and segmental treatment was done in 26 (76%) and 8 (24%) patients, respectively. Volumetric analysis was performed on post-radioembolization time-of-flight PET imaging to determine non-tumoral parenchymal dose. Hepatic toxicity was evaluated up to 120 days post-treatment, with CTCAE grade ≤ 1 compared to grade ≥ 2.

RESULTS

The median dose delivered to the non-tumoral liver in the treated lobe was 49 Gy (range 0-133). A total of 15 patients had grade ≤ 1 hepatic toxicity, and 19 patients had grade ≥ 2 toxicity. Patients with a grade ≥ 2 change in composite toxicity (70.7 vs. 43.8 Gy), bilirubin (74.1 vs. 43.3 Gy), albumin (84.2 vs. 43.8 Gy), and AST (94.5 vs. 47.1 Gy) have significantly higher non-tumoral parenchymal doses than those with grade ≤ 1. Liver parenchymal dose and Child-Pugh status predicted grade ≥ 2 toxicity, observed above a dose threshold of 54 Gy.

CONCLUSION

Increasing delivered ⁹⁰Y dose to non-tumoral liver measured by internal pair-production PET correlates with post-treatment hepatic toxicity. The likelihood of toxicity exceeds 50% at a dose threshold of 54 Gy. ClinicalTrials.gov identifier: NCT02848638.

Variable temporal sampling and tube current modulation for myocardial blood flow estimation from dose-reduced dynamic computed tomography

Quantification of myocardial blood flow (MBF) can aid in the diagnosis and treatment of coronary artery disease. However, there are no widely accepted clinical methods for estimating MBF. Dynamic cardiac perfusion computed tomography (CT) holds the promise of providing a quick and easy method to measure MBF quantitatively. However, the need for repeated scans can potentially result in a high patient radiation dose, limiting the clinical acceptance of this approach. In our previous work, we explored techniques to reduce the patient dose by either uniformly reducing the tube current or by uniformly reducing the number of temporal frames in the dynamic CT sequence. These dose reduction techniques result in noisy time-attenuation curves (TACs), which can give rise to significant errors in MBF estimation. We seek to investigate whether nonuniformly varying the tube current and/or sampling intervals can yield more accurate MBF estimates for a given dose. Specifically, we try to minimize the dose and obtain the most accurate MBF estimate by addressing the following questions: when in the TAC should the CT data be collected and at what tube current(s)? We hypothesize that increasing the sampling rate and/or tube current during the time frames when the myocardial CT number is most sensitive to the flow rate, while reducing them elsewhere, can achieve better estimation accuracy for the same dose. We perform simulations of contrast agent kinetics and CT acquisitions to evaluate the relative MBF estimation performance of several clinically viable variable acquisition methods. We find that variable temporal and tube current sequences can be performed that impart an effective dose of 5.5 mSv and allow for reductions in MBF estimation root-mean-square error on the order of 20% compared to uniform acquisition sequences with comparable or higher radiation doses.

Direct Reconstruction of CT-based Attenuation Correction Images for PET with Cluster-Based Penalties

Extremely low-dose CT acquisitions used for PET attenuation correction have high levels of noise and potential bias artifacts due to photon starvation. This work explores the use of a priori knowledge for iterative image reconstruction of the CT-based attenuation map. We investigate a maximum a posteriori framework with cluster-based multinomial penalty for direct iterative coordinate decent (dICD) reconstruction of the PET attenuation map. The objective function for direct iterative attenuation map reconstruction used a Poisson log-likelihood data fit term and evaluated two image penalty terms of spatial and mixture distributions. The spatial regularization is based on a quadratic penalty. For the mixture penalty, we assumed that the attenuation map may consist of four material clusters: air+background, lung, soft tissue, and bone. Using simulated noisy sinogram data, dICD reconstruction was performed with different strengths of the spatial and mixture penalties. The combined spatial and mixture penalties reduced the RMSE by roughly 2 times compared to a weighted least square and filtered backprojection reconstruction of CT images. The combined spatial and mixture penalties resulted in only slightly lower RMSE compared to a spatial quadratic penalty alone. For direct PET attenuation map reconstruction from ultra-low dose CT acquisitions, the combination of spatial and mixture penalties offers regularization of both variance and bias and is a potential method to reconstruct attenuation maps with negligible patient dose. The presented results, using a best-case histogram suggest that the mixture penalty does not offer a substantive benefit over conventional quadratic regularization and diminishes enthusiasm for exploring future application of the mixture penalty.

Comparison Between Pre-Log and Post-Log Statistical Models in Ultra-Low-Dose CT Reconstruction

X-ray detectors in clinical computed tomography (CT) usually operate in current-integrating mode. Their complicated signal statistics often lead to intractable likelihood functions for practical use in model-based image reconstruction (MBIR). It is therefore desirable to design simplified statistical models without losing the essential factors. Depending on whether the CT transmission data are logarithmically transformed, pre-log and post-log models are two major categories of choices in CT MBIR. Both being approximations, it remains an open question whether one model can notably improve image quality over the other on real scanners. In this study, we develop and compare several pre-log and post-log MBIR algorithms under a unified framework. Their reconstruction accuracy based on simulation and clinical datasets are evaluated. The results show that pre-log MBIR can achieve notably better quantitative accuracy than post-log MBIR in ultra-low-dose CT, although in less extreme cases, post-log MBIR with handcrafted pre-processing remains a competitive alternative. Pre-log MBIR could play a growing role in emerging ultra-low-dose CT applications.

Optimization of Pediatric PET/CT

PET/CT, the most common form of hybrid imaging, has transformed oncologic imaging and is increasingly being used for nononcologic applications as well. Performing PET/CT in children poses unique challenges. Not only are children more sensitive to the effects of radiation than adults but, following radiation exposure, children have a longer postexposure life expectancy in which to exhibit adverse radiation effects. Both the PET and CT components of the study contribute to the total patient radiation dose, which is one of the most important risks of the study in this population. Another risk in children, not typically encountered in adults, is potential neurotoxicity related to the frequent need for general anesthesia in this patient population. Optimizing pediatric PET/CT requires making improvements to both the PET and the CT components of the procedure while decreasing the potential for risk. This can be accomplished through judicious performance of imaging, the use of recommended pediatric ¹⁸fluorine-2-fluoro-2-deoxy-d-glucose (¹⁸F-FDG) administered activities, thoughtful selection of pediatric-specific CT imaging parameters, careful patient preparation, and use of appropriate patient immobilization. In this article, we will review a variety of strategies for radiation dose optimization in pediatric ¹⁸F-FDG-PET/CT focusing on these processes. Awareness of and careful selection of pediatric-specific CT imaging parameters designed for appropriate diagnostic, localization, or attenuation correction only CT, in conjunction with the use of recommended radiotracer administered activities, will help to ensure image quality while limiting patient radiation exposure. Patient preparation, an important determinant of image quality, is another focus of this review. Appropriate preparative measures are even more crucial in children in whom there is a higher incidence of brown fat, which can interfere with study interpretation. Finally, we will discuss measures to improve the patient experience, the resource use, the departmental workflow, and the diagnostic performance of the study through the use of appropriate technology, all in the context of minimizing procedure-related risks.

Fast analytical approach of application specific dose efficient spectrum selection for diagnostic CT imaging and PET attenuation correction

Computed tomography (CT) has been used for a variety of applications, two of which include diagnostic imaging and attenuation correction for PET or SPECT imaging. Ideally, the x-ray tube spectrum should be optimized for the specific application to minimize the patient radiation dose while still providing the necessary information. In this study, we proposed a projection-based analytic approach for the analysis of contrast, noise, and bias. Dose normalized contrast to noise ratio (CNRD), inverse noise normalized by dose (IND) and bias are used as evaluation metrics to determine the optimal x-ray spectrum. Our simulation investigated the dose efficiency of the x-ray spectrum ranging from 40 kVp to 200 kVp. Water cylinders with diameters of 15 cm, 24 cm, and 35 cm were used in the simulation to cover a variety of patient sizes. The effects of electronic noise and pre-patient copper filtration were also evaluated. A customized 24 cm CTDI-like phantom with 13 mm diameter inserts filled with iodine (10 mg ml^-1), tantalum (10 mg ml^-1), water, and PMMA was measured with both standard (1.5 mGy) and ultra-low (0.2 mGy) dose to verify the simulation results at tube voltages of 80, 100, 120, and 140 kVp. For contrast-enhanced diagnostic imaging, the simulation results indicated that for high dose without filtration, the optimal kVp for water contrast is approximately 100 kVp for a 15 cm water cylinder. However, the 60 kVp spectrum produces the highest CNRD for bone and iodine. The optimal kVp for tantalum has two selections: approximately 50 and 100 kVp. The kVp that maximizes CNRD increases when the object size increases. The trend in the CTDI phantom measurements agrees with the simulation results, which also agrees with previous studies. Copper filtration improved the dose efficiency for water and tantalum, but reduced the iodine and bone dose efficiency in a clinically-relevant range (70-140 kVp). Our study also shows that for CT-based attenuation correction applications for PET or SPECT, a higher-kVp spectrum with copper filtration is preferable. This method is developed based on filter back projection and does not require image reconstruction or Monte Carlo dose estimates; thus, it could potentially be used for patient-specific and task-based on-the-fly protocol optimization.

Mixed Confidence Estimation for Iterative CT Reconstruction

Dynamic (4D) CT imaging is used in a variety of applications, but the two major drawbacks of the technique are its increased radiation dose and longer reconstruction time. Here we present a statistical analysis of our previously proposed Mixed Confidence Estimation (MCE) method that addresses both these issues. This method, where framed iterative reconstruction is only performed on the dynamic regions of each frame while static regions are fixed across frames to a composite image, was proposed to reduce computation time. In this work, we generalize the previous method to describe any application where a portion of the image is known with higher confidence (static, composite, lower-frequency content, etc.) and a portion of the image is known with lower confidence (dynamic, targeted, etc). We show that by splitting the image space into higher and lower confidence components, MCE can lower the estimator variance in both regions compared to conventional reconstruction. We present a theoretical argument for this reduction in estimator variance and verify this argument with proof-of-principle simulations. We also propose a fast approximation of the variance of images reconstructed with MCE and confirm that this approximation is accurate compared to analytic calculations of and multi-realization image variance. This MCE method requires less computation time and provides reduced image variance for imaging scenarios where portions of the image are known with more certainty than others allowing for potentially reduced radiation dose and/or improved dynamic imaging.

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.

Evaluation of static and dynamic perfusion cardiac computed tomography for quantitation and classification tasks

Cardiac computed tomography (CT) acquisitions for perfusion assessment can be performed in a dynamic or static mode. Either method may be used for a variety of clinical tasks, including (1) stratifying patients into categories of ischemia and (2) using a quantitative myocardial blood flow (MBF) estimate to evaluate disease severity. In this simulation study, we compare method performance on these classification and quantification tasks for matched radiation dose levels and for different flow states, patient sizes, and injected contrast levels. Under conditions simulated, the dynamic method has low bias in MBF estimates (0 to [Formula: see text]) compared to linearly interpreted static assessment (0.45 to [Formula: see text]), making it more suitable for quantitative estimation. At matched radiation dose levels, receiver operating characteristic analysis demonstrated that the static method, with its high bias but generally lower variance, had superior performance ([Formula: see text]) in stratifying patients, especially for larger patients and lower contrast doses [area under the curve [Formula: see text] to 96 versus 0.86]. We also demonstrate that static assessment with a correctly tuned exponential relationship between the apparent CT number and MBF has superior quantification performance to static assessment with a linear relationship and to dynamic assessment. However, tuning the exponential relationship to the patient and scan characteristics will likely prove challenging. This study demonstrates that the selection and optimization of static or dynamic acquisition modes should depend on the specific clinical task.

Morphology supporting function: attenuation correction for SPECT/CT, PET/CT, and PET/MR imaging

Both SPECT, and in particular PET, are unique in medical imaging for their high sensitivity and direct link to a physical quantity, i.e. radiotracer concentration. This gives PET and SPECT imaging unique capabilities for accurately monitoring disease activity for the purposes of clinical management or therapy development. However, to achieve a direct quantitative connection between the underlying radiotracer concentration and the reconstructed image values several confounding physical effects have to be estimated, notably photon attenuation and scatter. With the advent of dual-modality SPECT/CT, PET/CT, and PET/MR scanners, the complementary CT or MR image data can enable these corrections, although there are unique challenges for each combination. This review covers the basic physics underlying photon attenuation and scatter and summarizes technical considerations for multimodal imaging with regard to PET and SPECT quantification and methods to address the challenges for each multimodal combination.

Ultra-low dose CT attenuation correction for PET/CT: analysis of sparse view data acquisition and reconstruction algorithms

For PET/CT systems, PET image reconstruction requires corresponding CT images for anatomical localization and attenuation correction. In the case of PET respiratory gating, multiple gated CT scans can offer phase-matched attenuation and motion correction, at the expense of increased radiation dose. We aim to minimize the dose of the CT scan, while preserving adequate image quality for the purpose of PET attenuation correction by introducing sparse view CT data acquisition.We investigated sparse view CT acquisition protocols resulting in ultra-low dose CT scans designed for PET attenuation correction. We analyzed the tradeoffs between the number of views and the integrated tube current per view for a given dose using CT and PET simulations of a 3D NCAT phantom with lesions inserted into liver and lung. We simulated seven CT acquisition protocols with {984, 328, 123, 41, 24, 12, 8} views per rotation at a gantry speed of 0.35 s. One standard dose and four ultra-low dose levels, namely, 0.35 mAs, 0.175 mAs, 0.0875 mAs, and 0.043 75 mAs, were investigated. Both the analytical Feldkamp, Davis and Kress (FDK) algorithm and the Model Based Iterative Reconstruction (MBIR) algorithm were used for CT image reconstruction. We also evaluated the impact of sinogram interpolation to estimate the missing projection measurements due to sparse view data acquisition. For MBIR, we used a penalized weighted least squares (PWLS) cost function with an approximate total-variation (TV) regularizing penalty function. We compared a tube pulsing mode and a continuous exposure mode for sparse view data acquisition. Global PET ensemble root-mean-squares-error (RMSE) and local ensemble lesion activity error were used as quantitative evaluation metrics for PET image quality.With sparse view sampling, it is possible to greatly reduce the CT scan dose when it is primarily used for PET attenuation correction with little or no measureable effect on the PET image. For the four ultra-low dose levels simulated, sparse view protocols with 41 and 24 views best balanced the tradeoff between electronic noise and aliasing artifacts. In terms of lesion activity error and ensemble RMSE of the PET images, these two protocols, when combined with MBIR, are able to provide results that are comparable to the baseline full dose CT scan. View interpolation significantly improves the performance of FDK reconstruction but was not necessary for MBIR. With the more technically feasible continuous exposure data acquisition, the CT images show an increase in azimuthal blur compared to tube pulsing. However, this blurring generally does not have a measureable impact on PET reconstructed images.Our simulations demonstrated that ultra-low-dose CT-based attenuation correction can be achieved at dose levels on the order of 0.044 mAs with little impact on PET image quality. Highly sparse 41- or 24- view ultra-low dose CT scans are feasible for PET attenuation correction, providing the best tradeoff between electronic noise and view aliasing artifacts. The continuous exposure acquisition mode could potentially be implemented in current commercially available scanners, thus enabling sparse view data acquisition without requiring x-ray tubes capable of operating in a pulsing mode.

Impact of CT attenuation correction method on quantitative respiratory-correlated (4D) PET/CT imaging

PURPOSE

Respiratory-correlated positron emission tomography (PET/CT) 4D PET/CT is used to mitigate errors from respiratory motion; however, the optimal CT attenuation correction (CTAC) method for 4D PET/CT is unknown. The authors performed a phantom study to evaluate the quantitative performance of CTAC methods for 4D PET/CT in the ground truth setting.

METHODS

A programmable respiratory motion phantom with a custom movable insert designed to emulate a lung lesion and lung tissue was used for this study. The insert was driven by one of five waveforms: two sinusoidal waveforms or three patient-specific respiratory waveforms. 3DPET and 4DPET images of the phantom under motion were acquired and reconstructed with six CTAC methods: helical breath-hold (3DHEL), helical free-breathing (3DMOT), 4D phase-averaged (4DAVG), 4D maximum intensity projection (4DMIP), 4D phase-matched (4DMATCH), and 4D end-exhale (4DEXH) CTAC. Recovery of SUV(max), SUV(mean), SUV(peak), and segmented tumor volume was evaluated as RC(max), RC(mean), RC(peak), and RC(vol), representing percent difference relative to the static ground truth case. Paired Wilcoxon tests and Kruskal-Wallis ANOVA were used to test for significant differences.

RESULTS

For 4DPET imaging, the maximum intensity projection CTAC produced significantly more accurate recovery coefficients than all other CTAC methods (p < 0.0001 over all metrics). Over all motion waveforms, ratios of 4DMIP CTAC recovery were 0.2 ± 5.4, -1.8 ± 6.5, -3.2 ± 5.0, and 3.0 ± 5.9 for RC(max), RC(peak), RC(mean), and RC(vol). In comparison, recovery coefficients for phase-matched CTAC were -8.4 ± 5.3, -10.5 ± 6.2, -7.6 ± 5.0, and -13.0 ± 7.7 for RC(max), RC(peak), RC(mean), and RC(vol). When testing differences between phases over all CTAC methods and waveforms, end-exhale phases were significantly more accurate (p = 0.005). However, these differences were driven by the patient-specific respiratory waveforms; when testing patient and sinusoidal waveforms separately, patient waveforms were significantly different between phases (p < 0.0001) while the sinusoidal waveforms were not significantly different (p = 0.98). When considering only the subset of 4DMATCH images that corresponded to the end-exhale image phase, 4DEXH, mean and interquartile range were similar to 4DMATCH but variability was considerably reduced.

CONCLUSIONS

Comparative advantages in accuracy and precision of SUV metrics and segmented volumes were demonstrated with the use of the maximum intensity projection and end-exhale CT attenuation correction. While respiratory phase-matched CTAC should in theory provide optimal corrections, image artifacts and differences in implementation of 4DCT and 4DPET sorting can degrade the benefit of this approach. These results may be useful to guide the implementation, analysis, and development of respiratory-correlated thoracic PET/CT in the radiation oncology and diagnostic settings.

Sinogram smoothing techniques for myocardial blood flow estimation from dose-reduced dynamic computed tomography

Dynamic contrast-enhanced computed tomography (CT) could provide an accurate and widely available technique for myocardial blood flow (MBF) estimation to aid in the diagnosis and treatment of coronary artery disease. However, one of its primary limitations is the radiation dose imparted to the patient. We are exploring techniques to reduce the patient dose by either reducing the tube current or by reducing the number of temporal frames in the dynamic CT sequence. Both of these dose reduction techniques result in noisy data. In order to extract the MBF information from the noisy acquisitions, we have explored several data-domain smoothing techniques. In this work, we investigate two specific smoothing techniques: the sinogram restoration technique in both the spatial and temporal domains and the use of the Karhunen-Loeve (KL) transform to provide temporal smoothing in the sinogram domain. The KL transform smoothing technique has been previously applied to dynamic image sequences in positron emission tomography. We apply a quantitative two-compartment blood flow model to estimate MBF from the time-attenuation curves and determine which smoothing method provides the most accurate MBF estimates in a series of simulations of different dose levels, dynamic contrast-enhanced cardiac CT acquisitions. As measured by root mean square percentage error (% RMSE) in MBF estimates, sinogram smoothing generally provides the best MBF estimates except for the cases of the lowest simulated dose levels (tube current = 25 mAs, 2 or 3 s temporal spacing), where the KL transform method provides the best MBF estimates. The KL transform technique provides improved MBF estimates compared to conventional processing only at very low doses (<7 mSv). Results suggest that the proposed smoothing techniques could provide high fidelity MBF information and allow for substantial radiation dose savings.

Assessment of patient selection criteria for quantitative imaging with respiratory-gated positron emission tomography

The objective of this investigation was to propose techniques for determining which patients are likely to benefit from quantitative respiratory-gated imaging by correlating respiratory patterns to changes in positron emission tomography (PET) metrics. Twenty-six lung and liver cancer patients underwent PET/computed tomography exams with recorded chest/abdominal displacements. Static and adaptive amplitude-gated [[Formula: see text]]fluoro-D-glucose (FDG) PET images were generated from list-mode acquisitions. Patients were grouped by respiratory pattern, lesion location, or degree of lesion attachment to anatomical structures. Respiratory pattern metrics were calculated during time intervals corresponding to PET field of views over lesions of interest. FDG PET images were quantified by lesion maximum standardized uptake value ([Formula: see text]). Relative changes in [Formula: see text] between static and gated PET images were tested for association to respiratory pattern metrics. Lower lung lesions and liver lesions had significantly higher changes in [Formula: see text] than upper lung lesions (14 versus 3%, [Formula: see text]). Correlation was highest ([Formula: see text], [Formula: see text], [Formula: see text]) between changes in [Formula: see text] and nonstandard respiratory pattern metrics. Lesion location had a significant impact on changes in PET quantification due to respiratory gating. Respiratory pattern metrics were correlated to changes in [Formula: see text], though sample size limited statistical power. Validation in larger cohorts may enable selection of patients prior to acquisition who would benefit from respiratory-gated PET imaging.

Dual energy CT for attenuation correction with PET/CT

PURPOSE

The authors evaluate the energy dependent noise and bias properties of monoenergetic images synthesized from dual-energy CT (DECT) acquisitions. These monoenergetic images can be used to estimate attenuation coefficients at energies suitable for positron emission tomography (PET) and single-photon emission computed tomography (SPECT) imaging. This is becoming more relevant with the increased use of quantitative imaging by PET/CT and SPECT/CT scanners. There are, however, potential variations in the noise and bias of synthesized monoenergetic images as a function of energy.

METHODS

The authors used analytic approximations and simulations to estimate the noise and bias of synthesized monoenergetic images of water-filled cylinders with different shapes and the NURBS-based cardiac-torso (NCAT) phantom from 40 to 520 keV, the range of SPECT and PET energies. The dual-kVp spectra were based on the GE Lightspeed VCT scanner at 80 and 140 kVp with added filtration of 0.5 mm Cu. The authors evaluated strategies of noise suppression with sinogram smoothing and dose minimization with reduction of tube currents at the two kVp settings. The authors compared the impact of DECT-based attenuation correction with single-kVp CT-based attenuation correction on PET quantitation for the NCAT phantom for soft tissue and high-Z materials of bone and iodine contrast enhancement.

RESULTS

Both analytic calculations and simulations displayed the expected minimum noise value for a synthesized monoenergetic image at an energy between the mean energies of the two spectra. In addition the authors found that the normalized coefficient of variation in the synthesized attenuation map increased with energy but reached a plateau near 160 keV, and then remained constant with increasing energy up to 511 keV and beyond. The bias was minimal, as the linear attenuation coefficients of the synthesized monoenergetic images were within 2.4% of the known true values across the entire energy range. Compared with no sinogram smoothing, sinogram smoothing can dramatically reduce noise in the DECT-derived attenuation map. Through appropriate selection of tube currents for high and low kVp scans, DECT can deliver roughly the same amount of radiation dose as that of a single kVp CT scan, but could be used for PET attenuation correction with reduced bias in contrast agent regions by a factor of ≈ 2.6 and slightly reduced RMSE for the total image.

CONCLUSIONS

When DECT is used for attenuation correction at higher energies, there is a noise amplification that is dependent on the energy of the synthesized monoenergetic image of linear attenuation coefficients. Sinogram smoothing reduces the noise amplification in DECT-derived attenuation maps without increasing bias. With an appropriate selection of CT techniques, a DECT scan with the same radiation dose as a single CT scan can result in a PET image with improved quantitative accuracy.

Simulation Evaluation of Quantitative Myocardial Perfusion Assessment from Cardiac CT

Contrast enhancement on cardiac CT provides valuable information about myocardial perfusion and methods have been proposed to assess perfusion with static and dynamic acquisitions. There is a lack of knowledge and consensus on the appropriate approach to ensure 1) sufficient diagnostic accuracy for clinical decisions and 2) low radiation doses for patient safety. This work developed a thorough dynamic CT simulation and several accepted blood flow estimation techniques to evaluate the performance of perfusion assessment across a range of acquisition and estimation scenarios. Cardiac CT acquisitions were simulated for a range of flow states (Flow = 0.5, 1, 2, 3 ml/g/min, cardiac output = 3,5,8 L/min). CT acquisitions were simulated with a validated CT simulator incorporating polyenergetic data acquisition and realistic x-ray flux levels for dynamic acquisitions with a range of scenarios including 1, 2, 3 sec sampling for 30 sec with 25, 70, 140 mAs. Images were generated using conventional image reconstruction with additional image-based beam hardening correction to account for iodine content. Time attenuation curves were extracted for multiple regions around the myocardium and used to estimate flow. In total, 2,700 independent realizations of dynamic sequences were generated and multiple MBF estimation methods were applied to each of these. Evaluation of quantitative kinetic modeling yielded blood flow estimates with an root mean square error (RMSE) of ∼0.6 ml/g/min averaged across multiple scenarios. Semi-quantitative modeling and qualitative static imaging resulted in significantly more error (RMSE = ∼1.2 and ∼1.2 ml/min/g respectively). For quantitative methods, dose reduction through reduced temporal sampling or reduced tube current had comparable impact on the MBF estimate fidelity. On average, half dose acquisitions increased the RMSE of estimates by only 18% suggesting that substantial dose reductions can be employed in the context of quantitative myocardial blood flow estimation. In conclusion, quantitative model-based dynamic cardiac CT perfusion assessment is capable of accurately estimating MBF across a range of cardiac outputs and tissue perfusion states, outperforms comparable static perfusion estimates, and is relatively robust to noise and temporal subsampling.

Comparison of blood flow models and acquisitions for quantitative myocardial perfusion estimation from dynamic CT

Myocardial blood flow (MBF) can be estimated from dynamic contrast enhanced (DCE) cardiac CT acquisitions, leading to quantitative assessment of regional perfusion. The need for low radiation dose and the lack of consensus on MBF estimation methods motivates this study to refine the selection of acquisition protocols and models for CT-derived MBF. DCE cardiac CT acquisitions were simulated for a range of flow states (MBF = 0.5, 1, 2, 3 ml (min g)(-1), cardiac output = 3, 5, 8 L min(-1)). Patient kinetics were generated by a mathematical model of iodine exchange incorporating numerous physiological features including heterogenenous microvascular flow, permeability and capillary contrast gradients. CT acquisitions were simulated for multiple realizations of realistic x-ray flux levels. CT acquisitions that reduce radiation exposure were implemented by varying both temporal sampling (1, 2, and 3 s sampling intervals) and tube currents (140, 70, and 25 mAs). For all acquisitions, we compared three quantitative MBF estimation methods (two-compartment model, an axially-distributed model, and the adiabatic approximation to the tissue homogeneous model) and a qualitative slope-based method. In total, over 11 000 time attenuation curves were used to evaluate MBF estimation in multiple patient and imaging scenarios. After iodine-based beam hardening correction, the slope method consistently underestimated flow by on average 47.5% and the quantitative models provided estimates with less than 6.5% average bias and increasing variance with increasing dose reductions. The three quantitative models performed equally well, offering estimates with essentially identical root mean squared error (RMSE) for matched acquisitions. MBF estimates using the qualitative slope method were inferior in terms of bias and RMSE compared to the quantitative methods. MBF estimate error was equal at matched dose reductions for all quantitative methods and range of techniques evaluated. This suggests that there is no particular advantage between quantitative estimation methods nor to performing dose reduction via tube current reduction compared to temporal sampling reduction. These data are important for optimizing implementation of cardiac dynamic CT in clinical practice and in prospective CT MBF trials.

Mixed Confidence Estimation for Iterative CT Reconstruction

We present a statistical analysis of our previously proposed Constrain-Static Target-Kinetic algorithm for 4D CT reconstruction. This method, where framed iterative reconstruction is only performed on the dynamic regions of each frame, while static regions are fixed across frames to a composite image, was proposed to reduce computation time. In this work, we generalize the previous method to describe any application where a portion of the image is known with higher confidence (static, composite, lower-frequency content, etc.) and a portion of the image is known with lower confidence (dynamic, targeted, etc). We show that by splitting the image space into higher and lower confidence components, CSTK can lower the estimator variance in both regions compared to conventional reconstruction. We present a theoretical argument for this reduction in estimator variance and verify this argument with proof-of-principle simulations. This method allows for reduced computation time and improved image quality for imaging scenarios where portions of the image are known with more certainty than others.

Direct Reconstruction of CT-based Attenuation Correction Images for PET with Cluster-Based Penalties

Extremely low-dose CT acquisitions for the purpose of PET attenuation correction will have a high level of noise and biasing artifacts due to factors such as photon starvation. This work explores a priori knowledge appropriate for CT iterative image reconstruction for PET attenuation correction. We investigate the maximum a posteriori (MAP) framework with cluster-based, multinomial priors for the direct reconstruction of the PET attenuation map. The objective function for direct iterative attenuation map reconstruction was modeled as a Poisson log-likelihood with prior terms consisting of quadratic (Q) and mixture (M) distributions. The attenuation map is assumed to have values in 4 clusters: air+background, lung, soft tissue, and bone. Under this assumption, the MP was a mixture probability density function consisting of one exponential and three Gaussian distributions. The relative proportion of each cluster was jointly estimated during each voxel update of direct iterative coordinate decent (dICD) method. Noise-free data were generated from NCAT phantom and Poisson noise was added. Reconstruction with FBP (ramp filter) was performed on the noise-free (ground truth) and noisy data. For the noisy data, dICD reconstruction was performed with the combination of different prior strength parameters (β and γ) of Q- and M-penalties. The combined quadratic and mixture penalties reduces the RMSE by 18.7% compared to post-smoothed iterative reconstruction and only 0.7% compared to quadratic alone. For direct PET attenuation map reconstruction from ultra-low dose CT acquisitions, the combination of quadratic and mixture priors offers regularization of both variance and bias and is a potential method to derive attenuation maps with negligible patient dose. However, the small improvement in quantitative accuracy relative to the substantial increase in algorithm complexity does not currently justify the use of mixture-based PET attenuation priors for reconstruction of CT images for PET attenuation correction.

Quantitative material characterization from multi-energy photon counting CT

PURPOSE

To quantify the concentration of soft-tissue components of water, fat, and calcium through the decomposition of the x-ray spectral signatures in multi-energy CT images.

METHODS

Decomposition of dual-energy and multi-energy x-ray data into basis materials can be performed in the projection domain, image domain, or during image reconstruction. In this work, the authors present methodology for the decomposition of multi-energy x-ray data in the image domain for the application of soft-tissue characterization. To demonstrate proof-of-principle, the authors apply several previously proposed methods and a novel content-aware method to multi-energy images acquired with a prototype photon counting CT system. Data from phantom and ex vivo specimens are evaluated.

RESULTS

The number and type of materials in a region can be limited based on a priori knowledge or classification strategies. The proposed difference classifier successfully classified the image into air only, water+fat, water+fat+iodine, and water+calcium regions. Then, the content-aware material decomposition based on weighted least-square optimization generated quantitative maps of concentration. Bias in the estimation of the concentration of water and oil components in a phantom study was <0.10 ± 0.15 g/cc on average. Decomposition of ex vivo carotid endarterectomy specimens suggests the presence of water, lipid, and calcium deposits in the plaque walls.

CONCLUSIONS

Initial application of the proposed methodology suggests that it can decompose multi-energy CT images into quantitative maps of water, adipose, iodine, and calcium concentrations.

Performance Evaluation of Small Animal PET Scanners With Different System Designs

This study evaluated the image quality metrics of small animal PET scanners based upon measured single detector module positioning performance. A semi-analytical approach was developed to study PET scanner performance in the scenario of multiple realizations. Positron range blurring, scanner system response function (SRF) and statistical noise were included in the modeling procedure. The scanner sensitivity map was included in the system matrix during maximum likelihood expectation maximization (MLEM) reconstruction. Several image quality metrics were evaluated for octagonal ring PET scanners consisting of continuous miniature crystal element (cMiCE) detector modules with varying designs. These designs included 8 mm and 15 mm thick crystal detectors using conventional readout with the photosensors on the exit surface of the crystal and a 15 mm thick crystal detector using our proposed sensor-on-the-entrance (SES) design. For the conventional readout design, the results showed that there was a tradeoff between bias and variance with crystal thickness. The 15 mm crystal detector had better detection task performance, while quantitation task performance was degraded. On the other hand, our SES detector had similar detection efficiency as the conventional design using a 15 mm thick crystal and had similar intrinsic spatial resolution as the conventional design using an 8 mm thick crystal. The end result was that by using the SES design, one could improve scanner quantitation task performance without sacrificing detection task performance.

Pediatric CT: strategies to lower radiation dose

OBJECTIVE

The introduction of MDCT has increased the utilization of CT in pediatric radiology along with concerns for radiation sequelae. This article reviews general principles of lowering radiation dose, the basic physics that impact radiation dose, and specific CT integrated dose-reduction tools focused on the pediatric population.

CONCLUSION

The goal of this article is to provide a comprehensive review of the recent literature regarding CT dose reduction methods, their limitations, and an outlook on future developments with a focus on the pediatric population. The discussion will initially focus on general considerations that lead to radiation dose reduction, followed by specific technical features that influence the radiation dose.

Validation of an axially distributed model for quantification of myocardial blood flow using ¹³N-ammonia PET

BACKGROUND

Estimation of myocardial blood flow (MBF) with cardiac PET is often performed with conventional compartmental models. In this study, we developed and evaluated a physiologically and anatomically realistic axially distributed model. Unlike compartmental models, this axially distributed approach models both the temporal and the spatial gradients in uptake and retention along the capillary.

METHODS

We validated PET-derived flow estimates with microsphere studies in 19 (9 rest, 10 stress) studies in five dogs. The radiotracer, (13)N-ammonia, was injected intravenously while microspheres were administered into the left atrium. A regional reduction in hyperemic flow was forced by an external occluder in five of the stress studies. The flow estimates from the axially distributed model were compared with estimates from conventional compartmental models.

RESULTS

The mean difference between microspheres and the axially distributed blood flow estimates in each of the 17 segments was 0.03 mL/g/minute (95% CI [-0.05, 0.11]). The blood flow estimates were highly correlated with each regional microsphere value for the axially distributed model (y = 0.98x + 0.06 mL/g/minute; r = 0.74; P < .001), for the two-compartment (y = 0.64x + 0.34; r = 0.74; P < .001), and for three-compartment model (y = 0.69x + 0.54; r = 0.74; P < .001). The variance of the error of the estimates is higher with the axially distributed model than the compartmental models (1.7 [1.3, 2.1] times higher).

CONCLUSION

The proposed axially distributed model provided accurate regional estimates of MBF. The axially distributed model estimated blood flow with more accuracy, but less precision, than the evaluated compartmental models.

Accuracy of CT-based attenuation correction in PET/CT bone imaging

We evaluate the accuracy of scaling CT images for attenuation correction of PET data measured for bone. While the standard tri-linear approach has been well tested for soft tissues, the impact of CT-based attenuation correction on the accuracy of tracer uptake in bone has not been reported in detail. We measured the accuracy of attenuation coefficients of bovine femur segments and patient data using a tri-linear method applied to CT images obtained at different kVp settings. Attenuation values at 511 keV obtained with a (68)Ga/(68)Ge transmission scan were used as a reference standard. The impact of inaccurate attenuation images on PET standardized uptake values (SUVs) was then evaluated using simulated emission images and emission images from five patients with elevated levels of FDG uptake in bone at disease sites. The CT-based linear attenuation images of the bovine femur segments underestimated the true values by 2.9 ± 0.3% for cancellous bone regardless of kVp. For compact bone the underestimation ranged from 1.3% at 140 kVp to 14.1% at 80 kVp. In the patient scans at 140 kVp the underestimation was approximately 2% averaged over all bony regions. The sensitivity analysis indicated that errors in PET SUVs in bone are approximately proportional to errors in the estimated attenuation coefficients for the same regions. The variability in SUV bias also increased approximately linearly with the error in linear attenuation coefficients. These results suggest that bias in bone uptake SUVs of PET tracers ranges from 2.4% to 5.9% when using CT scans at 140 and 120 kVp for attenuation correction. Lower kVp scans have the potential for considerably more error in dense bone. This bias is present in any PET tracer with bone uptake but may be clinically insignificant for many imaging tasks. However, errors from CT-based attenuation correction methods should be carefully evaluated if quantitation of tracer uptake in bone is important.

Ultra-low dose CT attenuation correction for PET/CT

A challenge for positron emission tomography/computed tomography (PET/CT) quantitation is patient respiratory motion, which can cause an underestimation of lesion activity uptake and an overestimation of lesion volume. Several respiratory motion correction methods benefit from longer duration CT scans that are phase matched with PET scans. However, even with the currently available, lowest dose CT techniques, extended duration cine CT scans impart a substantially high radiation dose. This study evaluates methods designed to reduce CT radiation dose in PET/CT scanning. We investigated selected combinations of dose reduced acquisition and noise suppression methods that take advantage of the reduced requirement of CT for PET attenuation correction (AC). These include reducing CT tube current, optimizing CT tube voltage, adding filtration, CT sinogram smoothing and clipping. We explored the impact of these methods on PET quantitation via simulations on different digital phantoms. CT tube current can be reduced much lower for AC than that in low dose CT protocols. Spectra that are higher energy and narrower are generally more dose efficient with respect to PET image quality. Sinogram smoothing could be used to compensate for the increased noise and artifacts at radiation dose reduced CT images, which allows for a further reduction of CT dose with no penalty for PET image quantitation. When CT is not used for diagnostic and anatomical localization purposes, we showed that ultra-low dose CT for PET/CT is feasible. The significant dose reduction strategies proposed here could enable respiratory motion compensation methods that require extended duration CT scans and reduce radiation exposure in general for all PET/CT imaging.

Myocardial hypo-enhancement on resting computed tomography angiography images accurately identifies myocardial hypoperfusion

OBJECTIVE

The objective of this study was to test the diagnostic accuracy of myocardial CT perfusion (CTP) imaging using color and gray-scale image analysis.

BACKGROUND

Current myocardial CTP techniques have varying diagnostic accuracy and are prone to artifacts that impair detection. This study evaluated the diagnostic accuracy of color and/or gray-scale CTP and the application of artifact criteria to detect hypoperfusion.

METHODS

Fifty-nine prospectively enrolled patients with abnormal single-photon emission computed tomography (SPECT) studies were analyzed. True hypoperfusion was defined if SPECT hypoperfusion corresponded to obstructive coronary stenoses on CT angiography (CTA). CTP applied color and gray-scale myocardial perfusion maps to resting CTA images. Criteria for identifying artifacts were also applied during interpretation.

RESULTS

Using combined SPECT plus CTA as the diagnostic standard, abnormal myocardial CTP was present in 33 (56%) patients, 19 suggesting infarction and 14 suggesting ischemia. Patient-level color and gray-scale myocardial CTP sensitivity to detect infarction was 90%, with specificity 80%, and negative and positive predictive value of 94% and 68%. To detect ischemia or infarction, CTP specificity and positive predictive value were 92% whereas sensitivity was 70%. Gray-scale myocardial CTP had slightly lower specificity but similar sensitivity. Myocardial CTP artifacts were present in 88% of studies and were identified using our criteria.

CONCLUSIONS

Color and gray-scale myocardial CTP using resting CTA images identified myocardial infarction with high sensitivity as well as infarction or ischemia with high specificity and positive predictive value without additional testing or radiation. Color and gray-scale CTP had slightly better specificity than gray-scale alone.

Respiratory motion correction for quantitative PET/CT using all detected events with internal-external motion correlation

PURPOSE

We present a method to correct respiratory motion blurring in PET/CT imaging using internal-external (INTEX) motion correlation. The internal motion of a known tumor is derived from respiratory-gated PET images; this internal motion is then correlated with external respiratory signals to determine the complete information of tumor motion during the scan.

METHODS

For each PET/CT data, PET listmode data were phase-gated into five bins and reconstructed. The centroid of a targeted tumor in each bin was determined and correlated with the corresponding mean displacement of externally monitored respiratory motion signal. Based on this correlation, the external motion signal was converted into internal tumor motion information in the superior-inferior direction. Then, the PET listmode data were binned sequentially to multiple 1-s sinograms. According to the converted internal tumor motion signal, each 1-s sinogram was registered to a reference frame, which best matched the helical CT attenuation map based on consistency conditions. The registered sinograms were summed and reconstructed to form an image, corrected for the motion of the specific tumor. In this study, the proposed INTEX method was evaluated with phantom and patient studies in terms of tracer concentration and volume.

RESULTS

The INTEX method effectively recovered the tracer concentration to the level of the stationary scan data in the phantom experiment. In the patient study, the INTEX method yielded a (17 +/- 22)% tumor volume decrease and a (10 +/- 10)% tumor SUVmax increase compared to non-gated images.

CONCLUSIONS

The proposed INTEX method reduces respiratory motion degradation of PET tumor quantification and delineation in an effective manner. This can be used to improve the assessment of response to therapy for a known tumor by minimizing residual motion and matching the attenuation correction, without increasing image noise.