Comparative assessment of energy-mapping approaches in CT-based attenuation correction for PET

Effect of Gaussian Smoothing Filter Size for CT-Based Attenuation Correction on Quantitative Assessment of Bone SPECT/CT: A Phantom Study

This study aims to determine the effect of Gaussian filter size for CT-based attenuation correction (CTAC) on the quantitative assessment of bone SPECT. An experiment was performed using a cylindrical phantom containing six rods, of which one was filled with water and five were filled with various concentrations of K2HPO4 solution (120-960 mg/cm3) to simulate different bone densities. 99mTc-solution of 207 kBq/ml was also included within the rods. SPECT data were acquired at 120 views for 30 s/view. CT for attenuation correction were obtained at 120 kVp and 100 mA. Sixteen different CTAC maps processed with different Gaussian filter sizes (ranging from 0 to 30 mm in 2 mm increments) were generated. SPECT images were reconstructed for each of the 16 CTAC maps. Attenuation coefficients and radioactivity concentrations in the rods were compared with those in the water-filled rod without K2HPO4 solution as a reference. Gaussian filter sizes below 14-16 mm resulted in an overestimation of radioactivity concentrations for rods with high concentrations of K2HPO4 (≥ 666 mg/cm3). The overestimation of radioactivity concentration measurement was 3.8% and 5.5% for 666 mg/cm3 and 960 mg/cm3 K2HPO4 solutions, respectively. The difference in radioactivity concentration between the water rod and the K2HPO4 rods was minimal at 18-22 mm. The use of Gaussian filter sizes smaller than 14-16 mm caused an overestimation of radioactivity concentration in regions of high CT values. Setting the Gaussian filter size to 18-22 mm enables radioactivity concentration to be measured with the least influence on bone density.

Attenuation Correction for Dedicated Cardiac SPECT Imaging Without Using Transmission Data

Objectives

Attenuation correction (AC) using transmission scanning-like computed tomography (CT) is the standard method to increase the accuracy of cardiac single-photon emission computed tomography (SPECT) images. Recently developed dedicated cardiac SPECT do not support CT, and thus, scans on these systems are vulnerable to attenuation artifacts. This study presented a new method for generating an attenuation map directly from emission data by segmentation of precisely non-rigid registration extended cardiac-torso (XCAT)-digital phantom with cardiac SPECT images.

Methods

In-house developed non-rigid registration algorithm automatically aligns the XCAT- phantom with cardiac SPECT image to precisely segment the contour of organs. Pre-defined attenuation coefficients for given photon energies were assigned to generate attenuation maps. The CT-based attenuation maps were used for validation with which cardiac SPECT/CT data of 38 patients were included. Segmental myocardial counts of a 17-segment model from these databases were compared based on the basis of the paired t-test.

Results

The mean, and standard deviation of the mean square error and structural similarity index measure of the female stress phase between the proposed attenuation maps and the CT attenuation maps were 6.99±1.23% and 92±2.0%, of the male stress were 6.87±3.8% and 96±1.0%. Proposed attenuation correction and computed tomography based attenuation correction average myocardial perfusion count was significantly higher than that in non-AC in the mid-inferior, mid-lateral, basal-inferior, and lateral regions (p<0.001).

Conclusion

The proposed attenuation maps showed good agreement with the CT-based attenuation map. Therefore, it is feasible to enable AC for a dedicated cardiac SPECT or SPECT standalone scanners.

Impact of CT tube-voltage and bone density on the quantitative assessment of tracer uptake in Tc-99m bone SPECT/CT: A phantom study

PURPOSE

To evaluate the effect of computed tomography (CT) tube voltage and CT density for CT-based attenuation correction (CTAC) on quantification of tracer uptake in single photon emission computed tomography (SPECT)/CT.

METHODS

A cylindrical phantom contained 7 cylinders with diameter of 30 mm. The central cylinder and background part were filled with 17 kBq/ml of ^99mTc-pertechnetate solution. Of the remaining 6 cylinders, one cylinder was filled with water and 5 cylinders were filled with each own different concentration of K₂HPO₄ solution (120, 275, 450, 666, and 960 mg/cm³) to simulate different bone densities. The 6 cylinders also contained ^99mTc-pertechnetate solution with the same radioactivity concentration (207 kBq/ml). CT scans were performed with 4 different tube voltages of 80, 100, 120, and 140 kVp for CTAC. The radioactivity concentration in the 6 cylinders were measured on the SPECT images processed with 4 different attenuation coefficient maps derived from each tube voltage of CT images.

RESULTS

Compared with the water cylinder without K₂HPO₄ solution, the measured radioactivity of the highest density cylinder (K₂HPO₄ solution concentration: 960 mg/cm³) was found to be overestimated by 3.3 % and 4.3 %, respectively, when the tube voltage was 120 kVp and 140 kVp (p = 0.022). The use of low-tube voltage, such as 80 kVp, has improved the quantitative accuracy of bone SPECT/CT.

CONCLUSIONS

SPECT quantitative evaluation of tracers in high-density objects tends to overestimate as tube voltage for CTAC increases. However, the overestimation in quantitative SPECT/CT evaluation in simulated bone area is less than 5% at most.

Delayed PET imaging using image synthesis network and nonrigid registration without additional CT scan

PURPOSE

Attenuation correction is critical for positron emission tomography (PET) image reconstruction. The standard protocol for obtaining attenuation information in a clinical PET scanner is via the coregistered computed tomography (CT) images. Therefore for delayed PET imaging, the CT scan is repeated twice, which increases the radiation dose for the patient. In this paper, we propose a zero-extra-dose delayed PET imaging method which requires no additional CT scans.

METHODS

A deep learning based synthesis network is designed to convert the PET data into a pseudo CT image for the delayed scan. Then, nonrigid registration is performed between this pseudo CT image and the CT image of the first scan, warping the CT image of the first scan to an estimated CT images for the delayed scan. Finally, the PET image attenuation correction in the delayed scan is obtained from this estimated CT image. Experiments with clinical datasets are implemented to assess the effectiveness of the proposed method with the well-recognized GAN method. The average peak signal-to-noise ratio (PSNR) and the mean absolute percent error (MAPE) are used in comparison. We also use scoring from three experienced radiologists as subjective measurement means, based on the diagnostic consistency of the PET images reconstructed from GAN and the proposed method with respect to the ground truth images.

RESULTS

The experiments show that the average PSNR is 47.04 dB (the proposed method) v.s. 44.41 dB (the traditional GAN method) for the reconstructed delayed PET images in our evaluation dataset. The average MAPEs are 1.59% for the proposed method and 3.32% for the traditional GAN method across five organ Regions of Interest (ROIs). The scores for the GAN and the proposed method rated by three experienced radiologists are 8.08±0.60 and 9.02±0.52, indicating that the proposed method yields more consistent PET images with the ground truth.

CONCLUSIONS

This work proposes a novel method for CT-less delayed PET imaging based on image synthesis network and nonrigid image registration. The PET image reconstructed using the proposed method yields delayed PET images with high image quality without artifacts, and is quantitatively more accurate compared with the traditional GAN method. This article is protected by copyright. All rights reserved.

A novel supervised learning method to generate CT images for attenuation correction in delayed pet scans

BACKGROUND AND OBJECTIVES

Attenuation correction is important for PET image reconstruction. In clinical PET/CT scans, the attenuation information is usually obtained by CT. However, additional CT scans for delayed PET imaging may increase the risk of cancer. In this paper, we propose a novel CT generation method for attenuation correction in delayed PET imaging that requires no additional CT scans.

METHODS

As only PET raw data is available for the delayed PET scan, routine image registration methods are difficult to use directly. To solve this problem, a reconstruction network is developed to produce pseudo PET images from raw data first. Then a second network is used to generate the CT image through mapping PET/CT images from the first scan to the delayed scan. The inputs of the second network are the two pseudo PET images from the first and delayed scans, and the CT image from the first scan. The labels are taken from the ground truth CT image in the delayed scan. The loss function contains an image similarity term and a regularization term, which reflect the anatomy matching accuracy and the smoothness of the non-rigid deformation field, respectively.

RESULTS

We evaluated the proposed method with simulated and clinical PET/CT datasets. Standard Uptake Value was computed and compared with the gold standard (with coregistered CT for attenuation correction). The results show that the proposed supervised learning method can generate PET images with high quality and quantitative accuracy. For the test cases in our study, the average MAE and RMSE of the proposed supervised learning method were 4.61 and 22.75 respectively, and the average PSNR between the reconstructed PET image and the ground truth PET image was 62.13 dB.

CONCLUSIONS

The proposed method is able to generate accurate CT images for attenuation correction in delayed PET scans. Experiments indicate that the proposed method outperforms traditional methods with respect to quantitative PET image accuracy.

Investigating the feasibility of generating dual-energy CT from one 120-kVp CT scan: a phantom study

Introduction

This study aimed to investigate the feasibility of generating pseudo dual‐energy CT (DECT) from one 120‐kVp CT by using convolutional neural network (CNN) to derive additional information for quantitative image analysis through phantom study.

Methods

Dual‐energy scans (80/140 kVp) and single‐energy scans (120 kVp) were performed for five calibration phantoms and two evaluation phantoms on a dual‐source DECT scanner. The calibration phantoms were used to generate training dataset for CNN optimization, while the evaluation phantoms were used to generate testing dataset. A CNN model which takes 120‐kVp images as input and creates 80/140‐kVp images as output was built, trained, and tested by using Caffe CNN platform. An in‐house software to quantify contrast enhancement and synthesize virtual monochromatic CT (VMCT) for CNN‐generated pseudo DECT was implemented and evaluated.

Results

The CT numbers in 80‐kVp pseudo images generated by CNN are differed from the truth by 11.57, 16.67, 13.92, 12.23, 10.69 HU for syringes filled with iodine concentration of 2.19, 4.38, 8.75, 17.5, 35 mg/ml, respectively. The corresponding results for 140‐kVp CT are 3.09, 9.10, 7.08, 9.81, 7.59 HU. The estimates of iodine concentration calculated based on the proposed method are differed from the truth by 0.104, 0.603, 0.478, 0.698, 0.795 mg/ml for syringes filled with iodine concentration of 2.19, 4.38, 8.75, 17.5, 35 mg/ml, respectively. With regards to image quality enhancement, VMCT synthesized by using pseudo DECT shows the best contrast‐to‐noise ratio at 40 keV.

Conclusion

In conclusion, the proposed method should be a practicable strategy for iodine quantification in contrast enhanced 120‐kVp CT without using specific scanner or scanning procedure.

PET/MRI attenuation estimation in the lung: A review of past, present, and potential techniques

Positron emission tomography/magnetic resonance imaging (PET/MRI) potentially offers several advantages over positron emission tomography/computed tomography (PET/CT), for example, no CT radiation dose and soft tissue images from MR acquired at the same time as the PET. However, obtaining accurate linear attenuation correction (LAC) factors for the lung remains difficult in PET/MRI. LACs depend on electron density and in the lung, these vary significantly both within an individual and from person to person. Current commercial practice is to use a single‐valued population‐based lung LAC, and better estimation is needed to improve quantification. Given the under‐appreciation of lung attenuation estimation as an issue, the inaccuracy of PET quantification due to the use of single‐valued lung LACs, the unique challenges of lung estimation, and the emerging status of PET/MRI scanners in lung disease, a review is timely. This paper highlights past and present methods, categorizing them into segmentation, atlas/mapping, and emission‐based schemes. Potential strategies for future developments are also presented.

Validation of Computed Tomography-based Attenuation Correction of Deviation between Theoretical and Actual Values in Four Computed Tomography Scanners

Objective(s):

In this study, we aimed to validate the accuracy of computed tomography-based attenuation correction (CTAC), using the bilinear scaling method.

Methods:

The measured attenuation coefficient (μ_m) was compared to the theoretical attenuation coefficient (μ_t), using four different CT scanners and an RMI 467 phantom. The effective energy of CT beam X-rays was calculated, using the aluminum half-value layer method and was used in conjunction with an attenuation coefficient map to convert the CT numbers to μ_m values for the photon energy of 140 keV. We measured the CT number of RMI 467 phantom for each of the four scanners and compared the μ_m and μ_t values for the effective energies of CT beam X-rays, effective atomic numbers, and physical densities.

Results:

The μ_m values for CT beam X-rays with low effective energies decreased in high construction elements, compared with CT beam X-rays of high effective energies. As the physical density increased, the μ_m values elevated linearly. Compared with other scanners, the μ_m values obtained from the scanner with CT beam X-rays of maximal effective energy increased once the effective atomic number exceeded 10.00. The μ_m value of soft tissue was equivalent to the μ_t value. However, the ratios of maximal difference between μ_m and μ_t values were 25.4% (lung tissue) and 21.5% (bone tissue), respectively. Additionally, the maximal difference in μ_m values was 6.0% in the bone tissue for each scanner.

Conclusion:

The bilinear scaling method could accurately convert CT numbers to μ values in soft tissues.

Sinogram-based attenuation correction in PET/CT

In a typical positron emission tomography/computed tomography (PET/CT) system, the attenuation correction is necessary for PET image reconstruction, which involves a transformation from the CT Hounsfield units (HU) to its linear attenuation coefficient (LAC) at 511 keV. This transformation is usually aided by an empirical bilinear function, followed by the forward projection of the transformed attenuation image. In this paper, we propose a direct method that calculates attenuation factors from CT projections, without using a reconstructed CT image. In this method, the human body is considered as a mixture of three distinct components: air, water and bone. Then, we estimate the proportions of these three components along each x-ray path and restore the attenuation factor at 511 keV with the known water and bone LACs. Our numerical results show that the proposed method produces as accurate estimation as the conventional HU mapping method.

Attenuation correction synthesis for hybrid PET-MR scanners: application to brain studies

Attenuation correction is an essential requirement for quantification of positron emission tomography (PET) data. In PET/CT acquisition systems, attenuation maps are derived from computed tomography (CT) images. However, in hybrid PET/MR scanners, magnetic resonance imaging (MRI) images do not directly provide a patient-specific attenuation map. The aim of the proposed work is to improve attenuation correction for PET/MR scanners by generating synthetic CTs and attenuation maps. The synthetic images are generated through a multi-atlas information propagation scheme, locally matching the MRI-derived patient's morphology to a database of MRI/CT pairs, using a local image similarity measure. Results show significant improvements in CT synthesis and PET reconstruction accuracy when compared to a segmentation method using an ultrashort-echo-time MRI sequence and to a simplified atlas-based method.

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.

Respiratory-induced errors in tumor quantification and delineation in CT attenuation-corrected PET images: effects of tumor size, tumor location, and respiratory trace: a simulation study using the 4D XCAT phantom

PURPOSE

We investigated the magnitude of respiratory-induced errors in tumor maximum standardized uptake value (SUVmax), localization, and volume for different respiratory motion traces and various lesion sizes in different locations of the thorax and abdomen in positron emission tomography (PET) images.

PROCEDURES

Respiratory motion traces were simulated based on the common patient breathing cycle and three diaphragm motions used to drive the 4D XCAT phantom. Lesions with different diameters were simulated in different locations of lungs and liver. The generated PET sinograms were subsequently corrected using computed tomography attenuation correction involving the end exhalation, end inhalation, and average of the respiratory cycle. By considering respiration-averaged computed tomography as a true value, the lesion volume, displacement, and SUVmax were measured and analyzed for different respiratory motions.

RESULTS

Respiration with 35-mm diaphragm motion results in a mean lesion SUVmax error of 24 %, a mean superior inferior displacement of 7.6 mm and a mean lesion volume overestimation of 129 % for a 9-mm lesion in the liver. Respiratory motion results in lesion volume overestimation of 50 % for a 9-mm lower lung lesion near the liver with just 15-mm diaphragm motion. Although there are larger errors in lesion SUVmax and volume for 35-mm motion amplitudes, respiration-averaged computed tomography results in smaller errors than the other two phases, except for the lower lung region.

CONCLUSIONS

The respiratory motion-induced errors in tumor quantification and delineation are highly dependent upon the motion amplitude, tumor location, tumor size, and choice of the attenuation map for PET image attenuation correction.

Anomaly Detection and Artifact Recovery in PET Attenuation-Correction Images Using the Likelihood Function

In dual modality PET/CT, CT data are used to generate the attenuation correction applied in the reconstruction of the PET emission image. This requires converting the CT image into a 511-keV attenuation map. Algorithms for making this transformation require assumptions about the makeup of material within the patient. Anomalous material such as contrast agent administered to enhance the CT scan confounds conversion algorithms and has been observed to result in inaccuracies, i.e., inconsistencies with the true 511-keV attenuation present at the time of the PET emission scan. These attenuation artifacts carry through to the final attenuation-corrected PET emission image and can resemble diseased tissue. We propose an approach to correcting this problem that employs the attenuation information carried by the PET emission data. A likelihood-based algorithm for identifying and correcting of contrast is presented and tested. The algorithm exploits the fact that contrast artifacts manifest as too-high attenuation values in an otherwise high quality attenuation image. In a separate study, the performance of the loglikelihood as an objective-function component of a detection/correction algorithm, independent of any particular algorithm was mapped out for several imaging scenarios as a function of statistical noise. Both the full algorithm and the loglikelihood performed well in studies with simulated data. Additional studies including those with patient data are required to fully understand their capabilities.

Effects of attenuation map accuracy on attenuation-corrected micro-SPECT images

Background

In single-photon emission computed tomography (SPECT), attenuation of photon flux in tissue affects quantitative accuracy of reconstructed images. Attenuation maps derived from X-ray computed tomography (CT) can be employed for attenuation correction. The attenuation coefficients as well as registration accuracy between SPECT and CT can be influenced by several factors. Here we investigate how such inaccuracies influence micro-SPECT quantification.

Methods

Effects of (1) misalignments between micro-SPECT and micro-CT through shifts and rotation, (2) globally altered attenuation coefficients and (3) combinations of these were evaluated. Tests were performed with a NEMA NU 4–2008 phantom and with rat cadavers containing sources with known activity.

Results

Changes in measured activities within volumes of interest in phantom images ranged from <1.5% (¹²⁵I) and <0.6% (²⁰¹Tl, ^99mTc and ¹¹¹In) for 1-mm shifts to <4.5% (¹²⁵I) and <1.7% (²⁰¹Tl, ^99mTc and ¹¹¹In) with large misregistration (3 mm). Changes induced by 15° rotation were smaller than those by 3-mm shifts. By significantly altering attenuation coefficients (±10%), activity changes of <5.2% for ¹²⁵I and <2.7% for ²⁰¹Tl, ^99mTc and ¹¹¹In were induced. Similar trends were seen in rat studies.

Conclusions

While getting sufficient accuracy of attenuation maps in clinical imaging is highly challenging, our results indicate that micro-SPECT quantification is quite robust to various imperfections of attenuation maps.

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.