Qualitative and Quantitative Assessment of Metal Artifacts Arising from Implantable Cardiac Pacing Devices in Oncological PET/CT Studies: A Phantom Study

Purpose: We evaluate the magnitude of metallic artifacts caused by various implantable cardiac pacing devices (without leads) on both attenuation maps (μ-maps) and positron emission tomography (PET) images using experimental phantom studies. We also assess the efficacy of a metal artifact reduction (MAR) algorithm along with the severity of artifacts in the presence of misalignment between μ-maps and PET images. Methods: Four pacing devices including two pacemakers (pacemakers 1 and 2) and two cardiac resynchronization therapy (CRT) devices of pacemaker (CRT-P) and defibrillator (CRT-D) type were placed in three phantoms including a cylindrical Ge-68 phantom, a water-bath phantom and an anthropomorphic heart/thorax phantom. The μ-maps were derived from computed tomography (CT) images reconstructed using the standard method supplied by the manufacturer and those reconstructed using the MAR algorithm. In addition, the standard reconstructed CT images of the last two phantoms were manually misaligned by 10mm along the patient's axis to simulate misalignment between CT and PET images. Results: The least and severest artifacts produced on both μ-maps and PET images of the Ge-68 phantom were induced by CRT-P and pacemaker 1 devices, respectively. In the water-bath phantom, CRT-P induced 17.5% over- and 9.2% underestimation of tracer uptake whereas pacemaker 1 induced 69.6% over- and 65.7% underestimation. In the heart/thorax phantom representing a pacemaker-bearing patient, pacemaker 1 induced 41.8% increase and 36.6% decrease in tracer uptake and attenuation coefficients on average in regions corresponding to bright and dark streak artifacts, respectively. Statistical analysis revealed that the MAR algorithm was successful in reducing bright streak artifacts, yet unsuccessful for dark ones. In the heart/thorax phantom, the MAR algorithm reduced the overestimations to 4.4% and the underestimations to 35.5% on average. Misalignment between μ-maps and PET images increased the peak of pseudo-uptake by approximately 20%. Conclusions: This study demonstrated that, depending on their elemental composition, different implantable cardiac pacing devices result in varying magnitudes of metal artifacts and thus pseudo-uptake on PET images. The MAR algorithm was not successful in compensating for underestimations which calls for a more efficient algorithm. The results showed that misalignments between PET and CT images render metal-related pseudo-uptake more sever

A deep neural network to recover missing data in small animal pet imaging:Comparison between sinogram-and image-domain implementations

Missing areas in PET sinograms and severe image artifacts as a consequence thereof, still gain prominence not only in sparse-ring detector configurations but also in full-ring PET scanners in case of faulty detectors. Empty bins in the projection domain, caused by inter-block gap regions or any failure in the detector blocks may lead to unacceptable image distortions and inaccuracies in quantitative analysis. Deep neural networks have recently attracted enormous attention within the imaging community and are being deployed for various applications, including handling impaired sinograms and removing the streaking artifacts generated by incomplete projection views. Despite the promising results in sparse-view CT reconstruction, the utility of deep-learning-based methods in synthesizing artifact-free PET images in the sparse-crystal setting is poorly explored. Herein, we investigated the feasibility of a modified U-Net to generate artifact-free PET scans in the presence of severe dead regions between adjacent detector blocks on a dedicated high-resolution preclinical PET scanner. The performance of the model was assessed in both projection and image-space. The visual inspection and quantitative analysis seem to indicate that the proposed method is well suited for application on partial-ring PET scanners

Implementation of absolute quantification in small-animal SPECT imaging: Phantom and animal studies

Purpose: Presence of photon attenuation severely challenges quantitative accuracy in single-photon emission computed tomography (SPECT) imaging. Subsequently, various attenuation correction methods have been developed to compensate for this degradation. The present study aims to implement an attenuation correction method and then to evaluate quantification accuracy of attenuation correction in small-animal SPECT imaging. Methods: Images were reconstructed using an iterative reconstruction method based on the maximum-likelihood expectation maximization (MLEM) algorithm including resolution recovery. This was implemented in our designed dedicated small-animal SPECT (HiReSPECT) system. For accurate quantification, the voxel values were converted to activity concentration via a calculated calibration factor. An attenuation correction algorithm was developed based on the first-order Chang’s method. Both phantom study and experimental measurements with four rats were used in order to validate the proposed method. Results: The phantom experiments showed that the error of �15.5% in the estimation of activity concentration in a uniform region was reduced to +5.1% when attenuation correction was applied. For in vivo studies, the average quantitative error of �22.8 � 6.3% (ranging from �31.2% to �14.8%) in the uncorrected images was reduced to +3.5 � 6.7% (ranging from �6.7 to +9.8%) after applying attenuation correction. Conclusion: The results indicate that the proposed attenuation correction algorithm based on the first-order Chang’s method, as implemented in our dedicated small-animal SPECT system, significantly improves accuracy of the quantitative analysis as well as the absolute quantification

Synergistic impact of motion and acquisition/reconstruction parameters on F-18-FDG PET radiomic features in non-small cell lung cancer:Phantom and clinical studies

Objectives: This study is aimed at examining the synergistic impact of motion and acquisition/reconstruction parameters on 18 F-FDG PET image radiomic features in non-small cell lung cancer (NSCLC) patients, and investigating the robustness of features performance in differentiating NSCLC histopathology subtypes. Methods: An in-house developed thoracic phantom incorporating lesions with different sizes was used with different reconstruction settings, including various reconstruction algorithms, number of subsets and iterations, full-width at half-maximum of post-reconstruction smoothing filter and acquisition parameters, including injected activity and test-retest with and without motion simulation. To simulate motion, a special motor was manufactured to simulate respiratory motion based on a normal patient in two directions. The lesions were delineated semi-automatically to extract 174 radiomic features. All radiomic features were categorized according to the coefficient of variation (COV) to select robust features. A cohort consisting of 40 NSCLC patients with adenocarcinoma (n = 20) and squamous cell carcinoma (n = 20) was retrospectively analyzed. Statistical analysis was performed to discriminate robust features in differentiating histopathology subtypes of NSCLC lesions. Results: Overall, 29% of radiomic features showed a COV ≤5% against motion. Forty-five percent and 76% of the features showed a COV ≤ 5% against the test-retest with and without motion in large lesions, respectively. Thirty-three percent and 45% of the features showed a COV ≤ 5% against different reconstruction parameters with and without motion, respectively. For NSCLC histopathological subtype differentiation, statistical analysis showed that 31 features were significant (p-value &lt; 0.05). Two out of the 31 significant features, namely, the joint entropy of GLCM (AUC = 0.71, COV = 0.019) and median absolute deviation of intensity histogram (AUC = 0.7, COV = 0.046), were robust against the motion (same reconstruction setting). Conclusions: Motion, acquisition, and reconstruction parameters significantly impact radiomic features, just as their synergies. Radiomic features with high predictive performance (statistically significant) in differentiating histopathological subtype of NSCLC may be eliminated due to non-reproducibility.</p

Implementation of absolute quantification in small-animal SPECT imaging: Phantom and animal studies

Purpose: Presence of photon attenuation severely challenges quantitative accuracy in single-photon emission computed tomography (SPECT) imaging. Subsequently, various attenuation correction methods have been developed to compensate for this degradation. The present study aims to implement an attenuation correction method and then to evaluate quantification accuracy of attenuation correction in small-animal SPECT imaging. Methods: Images were reconstructed using an iterative reconstruction method based on the maximum-likelihood expectation maximization (MLEM) algorithm including resolution recovery. This was implemented in our designed dedicated small-animal SPECT (HiReSPECT) system. For accurate quantification, the voxel values were converted to activity concentration via a calculated calibration factor. An attenuation correction algorithm was developed based on the first-order Chang’s method. Both phantom study and experimental measurements with four rats were used in order to validate the proposed method. Results: The phantom experiments showed that the error of �15.5% in the estimation of activity concentration in a uniform region was reduced to +5.1% when attenuation correction was applied. For in vivo studies, the average quantitative error of �22.8 � 6.3% (ranging from �31.2% to �14.8%) in the uncorrected images was reduced to +3.5 � 6.7% (ranging from �6.7 to +9.8%) after applying attenuation correction. Conclusion: The results indicate that the proposed attenuation correction algorithm based on the first-order Chang’s method, as implemented in our dedicated small-animal SPECT system, significantly improves accuracy of the quantitative analysis as well as the absolute quantification

Is metal artefact reduction mandatory in cardiac PET/CT imaging in the presence of pacemaker and implantable cardioverter defibrillator leads?

Abstract Purpose Cardiac PET/CT imaging is often performed in patients with pacemakers and implantable cardioverter defibrillator (ICD) leads. However, metallic implants usually produce artefacts on CT images which might propagate to CTbased attenuation-corrected (CTAC) PET images. The impact of metal artefact reduction (MAR) for CTAC of cardiac PET/ CT images in the presence of pacemaker, ICD and ECG leads was investigated using both qualitative and quantitative analysis in phantom and clinical studies. Methods The study included 14 patients with various leads undergoing perfusion and viability examinations using dedicated cardiac PET/CT protocols. The PET data were corrected for attenuation using both artefactual CT images and CT images corrected using the MAR algorithm. The severity and magnitude of metallic artefacts arising from these leads were assessed on both linear attenuation coefficient maps (μ-maps) and attenuation-corrected PET images. CT and PET emission data were obtained using an anthropomorphic thorax phantom and a dedicated heart phantom made in-house incorporating pacemaker and ICD leads attached at the right ventricle of the heart. Volume of interest-based analysis and regression plots were performed for regions related to the lead locations. Bull&apos;s eye view analysis was also performed on PET images corrected for attenuation with and without the MAR algorithm. Results In clinical studies, the visual assessment of PET images by experienced physicians and quantitative analysis did not reveal erroneous interpretation of the tracer distribution or significant differences when PET images were corrected for attenuation with and without MAR. In phantom studies, the mean differences between tracer Nucl Med Mol Imaging (2011) 38:252-262 DOI 10.1007/s00259-010-1635 uptake obtained without and with MAR were 10.16±2.1% and 6.86±2.1% in the segments of the heart in the vicinity of metallic ICD or pacemaker leads, and were 4.43±0.5% and 2.98±0.5% in segments far from the leads. Conclusion Although the MAR algorithm was able to effectively improve the quality of μ-maps, its clinical impact on the interpretation of PET images was not significant. Therefore cardiac PET images corrected for attenuation using CTAC in the presence of metallic leads can be interpreted without correction for metal artefacts. It should however be emphasized that in some special cases with multiple ICD leads attached to the myocardium wall, MAR might be useful for accurate attenuation correction. Eur

ارزیابی اثر پروتکل‌های مختلف بازسازی تصویر در آنالیز کمی تصاویر پت/ سی‌تی

زمینه: در سال‌های اخیر اسکن پت/ سی‌تی کاربرد زیاد در انکولوژی به منظور بهبود در تشخیص سرطان، طراحی نقشه درمان و بررسی پاسخ به درمان بیماران دارد. کیفیت مناسب تصاویر پت/ سی‌تی به تشخیص دقیق‌تر کمک می کند. هدف از این مطالعه بررسی تاثیر تکنیک‌های مختلف بازسازی تصویر از جمله TOF و PSF بر آنالیز کمی تصاویر می باشد، سپس اثر پارامترهای مختلف بازسازی بر کیفیت تصویر در بیماران با شاخص توده ‌بدنی اضافه وزن و طبیعی مورد بررسی قرار گرفت. روش: تصاویر پت/ سی‌تی بیماران به کمک دستگاه دیسکاوری 690&nbsp; نصب شده در بیمارستان مسیح دانشوری گرفته شد. در این مطالعه تکنیک‌های بازسازی OSEM ، OSEM+PSF، OSEM+TOF و OSEM+PSF+TOF با حاصل‌ضرب های ایتریشن در ساب ست 36، 48، 64 و 72 و فیلتر های 4.5 ، 5.5 و 6.5 میلی‌متری ارزیابی شد. در این مطالعه پارامترهای COV، SNR و SUVmax محاسبه گردید. از تست‌های آماری اسمیرنوف کولموگراف برای نرمال بودن داده‌ها، کروسکال والیس و من‌ویتنی به منظور مقایسه گروه‌ها و فاکتور‌های کیفیت تصویر استفاده گردید. یافته ها: با تغییر تکنیک بازسازی از OSEM به OSEM+PSF+TOF ، COV تصاویر بیماران با شاخص توده‌بدنی اضافه وزن از0.63±4.85 به 0.78±2.61 کاهش و میزان &nbsp;SUVmax، از 2.61±5.74 به 2.55±6.71 افزایش یافت . در بیماران با شاخص‌توده بدنی طبیعی COV از0.30±4.53 به 0.46±4.44 کاهش و میزان &nbsp;SUVmax، از 1.75±5.06 به 2.28±5.81 افزایش یافت. کمترین میزان COV و بیشترین میزان SNR و SUVmax در هر دو گروه بیماران مربوط به حاصل‌ضرب 36 بود. نتیجه گیری: در بیماران با شاخص توده‌بدنی اضافه وزن، پروتکل OSEM+PSF+TOF با حاصل‌ضرب های 36 و 48 و با اندازه ی فیلتر 5.5 و 6.5 میلی متری توصیه می‌گردد که دارای COV کمتر و SNR بالاتر است. در بیماران با شاخص توده‌بدنی طبیعی، همچنان OSEM+PSF+TOF پارامترهای کیفیت تصویر بهتری را نشان می‌دهد اما می‌توان با رعایت احتیاط از OSEM+PSF و OSEM+TOF با حاصل‌ضرب‌های متوسط نیز استفاده نمود اما انتخاب فیلتر با اندازه ی کوچکتر می‌تواند انتخاب بهتری باشد

Accurate modeling and performance evaluation of a total‐body pet scanner using Monte Carlo simulations

Background: The limited axial field‐of‐view (FOV) of conventional clinical positron emission tomography (PET) scanners (∼15 to 26 cm) allows detecting only 1% of all coincidence photons, hence limiting significantly their sensitivity. To overcome this limitation, the EXPLORER consortium developed the world's first total‐body PET/CT scanner that significantly increased the sensitivity, thus enabling to decrease the scan duration or injected dose. Purpose: The purpose of this study is to perform and validate Monte Carlo simulations of the uEXPLORER PET scanner, which can be used to devise novel conceptual designs and geometrical configurations through obtaining features that are difficult to obtain experimentally. Methods: The total‐body uEXPLORER PET scanner was modeled using GATE Monte Carlo (MC) platform. The model was validated through comparison with experimental measurements of various performance parameters, including spatial resolution, sensitivity, count rate performance, and image quality, according to NEMA‐NU2 2018 standards. Furthermore, the effects of the time coincidence window and maximum ring difference on the count rate and noise equivalent count rate (NECR) were evaluated. Results: Overall, the validation study showed that there was a good agreement between the simulation and experimental results. The differences between the simulated and experimental total sensitivity for the NEMA and extended phantoms at the center of the FOV were 2.3% and 0.0%, respectively. The difference in peak NECR was 9.9% for the NEMA phantom and 1.0% for the extended phantom. The average bias between the simulated and experimental results of the full‐width‐at‐half maximum (FWHM) for six different positions and three directions was 0.12 mm. The simulations showed that using a variable coincidence time window based on the maximum ring difference can reduce the effect of random coincidences and improve the NECR compared to a constant time coincidence window. The NECR corresponding to 252‐ring difference was 2.11 Mcps, which is larger than the NECR corresponding to 336‐ring difference (2.04 Mcps). Conclusion: The developed MC model of the uEXPLORER PET scanner was validated against experimental measurements and can be used for further assessment and design optimization of the scanner.</p

Qualitative and quantitative assessment of metal artifacts arising from implantable cardiac pacing devices in oncological PET/CT studies: a phantom study

We evaluate the magnitude of metallic artifacts caused by various implantable cardiac pacing devices (without leads) on both attenuation maps (μ-maps) and positron emission tomography (PET) images using experimental phantom studies. We also assess the efficacy of a metal artifact reduction (MAR) algorithm along with the severity of artifacts in the presence of misalignment between μ-maps and PET images