The use of noise equivalent count rate and the NEMA phantom for PET image quality evaluation

PET image quality is directly associated with two important parameters among others: count-rate performance and image signal-to-noise ratio (SNR). The framework of noise equivalent count rate (NECR) was developed back in the 1990s and has been widely used since then to evaluate count-rate performance for PET systems. The concept of NECR is not entirely straightforward, however, and among the issues requiring clarification are its original definition, its relationship to image quality, and its consistency among different derivation methods. In particular, we try to answer whether a higher NECR measurement using a standard NEMA phantom actually corresponds to better imaging performance. The paper includes the following topics: 1) revisiting the original analytical model for NECR derivation; 2) validating three methods for NECR calculation based on the NEMA phantom/standard; and 3) studying the spatial dependence of NECR and quantitative relationship between NECR and image SNR.     

State of the art and challenges of time-of-flight PET

After a brief review of the history of time-of-flight (TOF) positron emission tomography (PET) instrumentation from the 1980s to present, the principles of TOF PET are introduced, the concept of time resolution and its effect on TOF gain in signal-to-noise ratio (SNR) are discussed. The factors influencing the time resolution of a TOF PET scanner are presented, with focus on the intrinsic properties of scintillators of particular interest for TOF PET. Finally, some open issues, challenges and achievements of today's TOF PET reconstruction are reviewed: the structure of the data organization, the choice of analytical or iterative method, the recent experimental assessment of TOF image quality, and the most promising applications of TOF PET.     

Small-animal imaging using clinical positron emission tomography/computed tomography and super-resolution

Considering the high cost of dedicated small-animal positron emission tomography/computed tomography (PET/CT), an acceptable alternative in many situations might be clinical PET/CT. However, spatial resolution and image quality are of concern. The utility of clinical PET/CT for small-animal research and image quality improvements from super-resolution (spatial subsampling) were investigated. National Electrical Manufacturers Association (NEMA) NU 4 phantom and mouse data were acquired with a clinical PET/CT scanner, as both conventional static and stepped scans. Static scans were reconstructed with and without point spread function (PSF) modeling. Stepped images were postprocessed with iterative deconvolution to produce super-resolution images. Image quality was markedly improved using the super-resolution technique, avoiding certain artifacts produced by PSF modeling. The 2 mm rod of the NU 4 phantom was visualized with high contrast, and the major structures of the mouse were well resolved. Although not a perfect substitute for a state-of-the-art small-animal PET/CT scanner, a clinical PET/CT scanner with super-resolution produces acceptable small-animal image quality for many preclinical research studies.     

Robust framework for PET image reconstruction incorporating system and measurement uncertainties

In Positron Emission Tomography (PET), an optimal estimate of the radioactivity concentration is obtained from the measured emission data under certain criteria. So far, all the well-known statistical reconstruction algorithms require exactly known system probability matrix a priori, and the quality of such system model largely determines the quality of the reconstructed images. In this paper, we propose an algorithm for PET image reconstruction for the real world case where the PET system model is subject to uncertainties. The method counts PET reconstruction as a regularization problem and the image estimation is achieved by means of an uncertainty weighted least squares framework. The performance of our work is evaluated with the Shepp-Logan simulated and real phantom data, which demonstrates significant improvements in image quality over the least squares reconstruction efforts.     

Validation of low-dose lung cancer PET-CT protocol and PET image improvement using machine learning

PurposeTo conduct a simplified lesion-detection task of a low-dose (LD) PET-CT protocol for frequent lung screening using 30% of the effective PETCT dose and to investigate the feasibility of increasing clinical value of low-statistics scans using machine learning.MethodsWe acquired 33 SD PET images, of which 13 had actual LD (ALD) PET, and simulated LD (SLD) PET images at seven different count levels from the SD PET scans. We employed image quality transfer (IQT), a machine learning algorithm that performs patch-regression to map parameters from low-quality to high-quality images. At each count level, patches extracted from 23 pairs of SD/SLD PET images were used to train three IQT models – global linear, single tree, and random forest regressions with cubic patch sizes of 3 and 5 voxels. The models were then used to estimate SD images from LD images at each count level for 10 unseen subjects. Lesion-detection task was carried out on matched lesion-present and lesion-absent images.ResultsLD PET-CT protocol yielded lesion detectability with sensitivity of 0.98 and specificity of 1. Random forest algorithm with cubic patch size of 5 allowed further 11.7% reduction in the effective PETCT dose without compromising lesion detectability, but underestimated SUV by 30%.ConclusionLD PET-CT protocol was validated for lesion detection using ALD PET scans. Substantial image quality improvement or additional dose reduction while preserving clinical values can be achieved using machine learning methods though SUV quantification may be biased and adjustment of our research protocol is required for clinical use.     

Ultra-low dose whole-body CT for attenuation correction in a dual tracer PET/CT protocol for multiple myeloma

PurposeTo investigate within phantoms the minimum CT dose allowed for accurate attenuation correction of PET data and to quantify the effective dose reduction when a CT for this purpose is incorporated in the clinical setting.MethodsThe NEMA image quality phantom was scanned within a large parallelepiped container. Twenty-one different CT images were acquired to correct attenuation of PET raw data. Radiation dose and image quality were evaluated.Thirty-one patients with proven multiple myeloma who underwent a dual tracer PET/CT scan were retrospectively reviewed. ¹⁸F-fluorodeoxyglucose PET/CT included a diagnostic whole-body low dose CT (WBLDCT: 120 kV-80mAs) and ¹¹C-Methionine PET/CT included a whole-body ultra-low dose CT (WBULDCT) for attenuation correction (100 kV-40mAs). Effective dose and image quality were analysed.ResultsOnly the two lowest radiation dose conditions (80 kV-20mAs and 80 kV-10mAs) produced artifacts in CT images that degraded corrected PET images. For all the other conditions (CTDI_vol ≥ 0.43 mGy), PET contrast recovery coefficients varied less than ± 1.2%.Patients received a median dose of 6.4 mSv from diagnostic CT and 2.1 mSv from the attenuation correction CT. Despite the worse image quality of this CT, 94.8% of bone lesions were identifiable.ConclusionPhantom experiments showed that an ultra-low dose CT can be implemented in PET/CT procedures without any noticeable degradation in the attenuation corrected PET scan. The replacement of the standard CT for this ultra-low dose CT in clinical PET/CT scans involves a significant radiation dose reduction.     

不同放射剂量CT在早期非小细胞肺癌中筛检价值对比

摘要 目的：探讨与对比不同放射剂量计算机断层扫描(Computed Tomography,CT)在早期非小细胞肺癌中筛检价值。方法：2020年1月到2020年12月选择在本院经病理确诊为肺内磨玻璃样结节患者98例作为研究对象,所有患者都给予常规剂量正电子发射计算机断层扫描(Positron emission tomography,PET)/CT检查与低剂量PET/CT检查,记录成像特征、辐射剂量并判定筛检价值。结果：低剂量PET/CT对肺部增厚、边界不规则、钙化、囊变的检出率高于常规剂量PET/CT(P<0.05)。低剂量PET/CT与常规剂量PET/CT的图像质量优良率为98.0 %和96.9 %,对比差异无统计学意义(P>0.05)。低剂量PET/CT的有效放射剂量、剂量长度乘积低于常规剂量PET/CT(P<0.05)。低剂量PET/CT的最大标准摄取值(maximum standardized uptake value,SUVmax)值低于常规剂量PET/CT(P<0.05)。低剂量PET/CT与常规剂量PET/CT分别筛检非小细胞肺癌51例与37例,筛检敏感性分别为98.1 %和69.2 %,特异性分别为100.0 %和97.8 %。结论：低放射剂量PET/CT在肺结节中的应用不会影响图像质量,且能降低辐射剂量,提高对早期非小细胞肺癌患者的筛检效果。     

3D TOF-PET image reconstruction using total variation regularization

In this paper we introduce a semi-analytic algorithm for 3-dimensional image reconstruction for positron emission tomography (PET). The method consists of the back-projection of the acquired data into the most likely image voxel according to time-of-flight (TOF) information, followed by the filtering step in the image space using an iterative optimization algorithm with a total variation (TV) regularization. TV regularization in image space is more computationally efficient than usual iterative optimization methods for PET reconstruction with full system matrix that use TV regularization. The efficiency comes from the one-time TOF back-projection step that might also be described as a reformatting of the acquired data. An important aspect of our work concerns the evaluation of the filter operator of the linear transform mapping an original radioactive tracer distribution into the TOF back-projected image. We obtain concise, closed-form analytical formula for the filter operator. The proposed method is validated with the Monte Carlo simulations of the NEMA IEC phantom using a one-layer, 50 cm-long cylindrical device called Jagiellonian PET scanner. The results show a better image quality compared with the reference TOF maximum likelihood expectation maximization algorithm.     

Tumour functional imaging by PET

Carcinogenesis is a complex multistep process, characterized by changes at different levels, both genetic and epigenetic, which alter cell metabolism. Positron emission tomography (PET) is a very sensitive image modality that allows to evaluate oncometabolism. PET functionalities are immense, since by labelling a molecule that specifically intervenes in a biochemical regulatory pathway of interest with a positron-emitting radionuclide, we can easily image that pathway. Thus, PET makes possible imaging several metabolic processes and assessing risk prediction, screening, diagnosis, response to therapy, metastization and recurrence.In this paper, we provide an overview of different radiopharmaceuticals developed for PET use in oncology, with a focus on brain tumours, breast cancer, hepatocellular carcinoma, neuroendocrine tumours, bladder cancer and prostate cancer because for these cancer types PET has been shown to be valuable. Most of the described tracers are just used in the research environment, with the aim to assess if these tracers could be able to offer an improvement concerning staging/restaging, characterization and stratification of different types of cancer, as well as therapeutic response assessment.In pursuit of personalized therapy, we briefly discuss the more established metabolic tracers and describe recent work on the development of new radiopharmaceuticals, aware that there will continue to exist diagnostic challenges to face modern cancer medicine.     

Conceptual Design and Simulation Study of an ROI-Focused Panel-PET Scanner

Positron emission tomography (PET) is an important imaging modality for clincial use. Conventionally, the PET scanner is generally built to provide a roomy enough transverse field-of-view (FOV) for imaging most adults’ torsos. However, in many cases, the region-of-interest (ROI) for imaging is usually a small area inside the human body. Therefore, to fulfill a PET system which provides an FOV comparable in size to the target ROI seems appealing and more cost effective. Meanwhile, such a PET system has the potential for portable or bedside application with the reduced system size. In this work, we have investigated the feasibility of using dual-headed panel-detectors to build an ROI-focused PET scanner. A novel windowed list-mode ordered subset expectation maximization method was developed to perform the ROI image reconstruction. With this method, the ROI of the object can be reconstructed from the coincidences whose position determined by time-of-flight (TOF) measurements was inside the ROI. Monte Carlo simulation demonstrates the feasibility of detecting lesions not less than 1 cm in diameter, with a 300 ps full width at half maximum timing resolution. As a critical system performance, the impact of TOF information on image quality has been studied and the required TOF capability was assessed. With enhanced timing resolution, the distortions and artifacts were reduced effectively. The further improved TOF capability also shows a noticeable improvement of detection performance for low uptake lesions, as well as the recovery speed of lesion contrast, which is of practical significance in the lesion detection task.     

Image Quality of 3rd Generation Spiral Cranial Dual-Source CT in Combination with an Advanced Model Iterative Reconstruction Technique: A Prospective Intra-Individual Comparison Study to Standard Sequential Cranial CT Using Identical Radiation Dose

Objectives

To prospectively intra-individually compare image quality of a 3^rd generation Dual-Source-CT (DSCT) spiral cranial CT (cCT) to a sequential 4-slice Multi-Slice-CT (MSCT) while maintaining identical intra-individual radiation dose levels.

Methods

35 patients, who had a non-contrast enhanced sequential cCT examination on a 4-slice MDCT within the past 12 months, underwent a spiral cCT scan on a 3^rd generation DSCT. CTDI_vol identical to initial 4-slice MDCT was applied. Data was reconstructed using filtered backward projection (FBP) and 3^rd-generation iterative reconstruction (IR) algorithm at 5 different IR strength levels. Two neuroradiologists independently evaluated subjective image quality using a 4-point Likert-scale and objective image quality was assessed in white matter and nucleus caudatus with signal-to-noise ratios (SNR) being subsequently calculated.

Results

Subjective image quality of all spiral cCT datasets was rated significantly higher compared to the 4-slice MDCT sequential acquisitions (p<0.05). Mean SNR was significantly higher in all spiral compared to sequential cCT datasets with mean SNR improvement of 61.65% (p*_{Bonferroni0.05}<0.0024). Subjective image quality improved with increasing IR levels.

Conclusion

Combination of 3^rd-generation DSCT spiral cCT with an advanced model IR technique significantly improves subjective and objective image quality compared to a standard sequential cCT acquisition acquired at identical dose levels.     

Improving Signal-to-Noise Ratio in Susceptibility Weighted Imaging: A Novel Multicomponent Non-Local Approach

In susceptibility-weighted imaging (SWI), the high resolution required to obtain a proper contrast generation leads to a reduced signal-to-noise ratio (SNR). The application of a denoising filter to produce images with higher SNR and still preserve small structures from excessive blurring is therefore extremely desirable. However, as the distributions of magnitude and phase noise may introduce biases during image restoration, the application of a denoising filter is non-trivial. Taking advantage of the potential multispectral nature of MR images, a multicomponent approach using a Non-Local Means (MNLM) denoising filter may perform better than a component-by-component image restoration method. Here we present a new MNLM-based method (Multicomponent-Imaginary-Real-SWI, hereafter MIR-SWI) to produce SWI images with high SNR and improved conspicuity. Both qualitative and quantitative comparisons of MIR-SWI with the original SWI scheme and previously proposed SWI restoring pipelines showed that MIR-SWI fared consistently better than the other approaches. Noise removal with MIR-SWI also provided improvement in contrast-to-noise ratio (CNR) and vessel conspicuity at higher factors of phase mask multiplications than the one suggested in the literature for SWI vessel imaging. We conclude that a proper handling of noise in the complex MR dataset may lead to improved image quality for SWI data.     

Illustrations pratiques — Pièges et artefacts/Trucs et astuces

Artifacts result from discrepancy between the estimated density values coming from the reconstructed CT image and the real value. They may come from many reasons (patient, device, algorithm, RX physical) and lead to deterioration of image quality and bad attenuation correction for SPECT or PET.     

MR-Based PET Motion Correction Procedure for Simultaneous MR-PET Neuroimaging of Human Brain

Positron Emission Tomography (PET) images are prone to motion artefacts due to the long acquisition time of PET measurements. Recently, simultaneous magnetic resonance imaging (MRI) and PET have become available in the first generation of Hybrid MR-PET scanners. In this work, the elimination of artefacts due to head motion in PET neuroimages is achieved by a new approach utilising MR-based motion tracking in combination with PET list mode data motion correction for simultaneous MR-PET acquisitions. The method comprises accurate MR-based motion measurements, an intra-frame motion minimising and reconstruction time reducing temporal framing algorithm, and a list mode based PET reconstruction which utilises the Ordinary Poisson Algorithm and avoids axial and transaxial compression. Compared to images uncorrected for motion, an increased image quality is shown in phantom as well as in vivo images. In vivo motion corrected images show an evident increase of contrast at the basal ganglia and a good visibility of uptake in tiny structures such as superior colliculi.     

Image Quality in Children with Low-Radiation Chest CT Using Adaptive Statistical Iterative Reconstruction and Model-Based Iterative Reconstruction

Objective

To evaluate noise reduction and image quality improvement in low-radiation dose chest CT images in children using adaptive statistical iterative reconstruction (ASIR) and a full model-based iterative reconstruction (MBIR) algorithm.

Methods

Forty-five children (age ranging from 28 days to 6 years, median of 1.8 years) who received low-dose chest CT scans were included. Age-dependent noise index (NI) was used for acquisition. Images were retrospectively reconstructed using three methods: MBIR, 60% of ASIR and 40% of conventional filtered back-projection (FBP), and FBP. The subjective quality of the images was independently evaluated by two radiologists. Objective noises in the left ventricle (LV), muscle, fat, descending aorta and lung field at the layer with the largest cross-section area of LV were measured, with the region of interest about one fourth to half of the area of descending aorta. Optimized signal-to-noise ratio (SNR) was calculated.

Result

In terms of subjective quality, MBIR images were significantly better than ASIR and FBP in image noise and visibility of tiny structures, but blurred edges were observed. In terms of objective noise, MBIR and ASIR reconstruction decreased the image noise by 55.2% and 31.8%, respectively, for LV compared with FBP. Similarly, MBIR and ASIR reconstruction increased the SNR by 124.0% and 46.2%, respectively, compared with FBP.

Conclusion

Compared with FBP and ASIR, overall image quality and noise reduction were significantly improved by MBIR. MBIR image could reconstruct eligible chest CT images in children with lower radiation dose.     

基于多孔小波融合的PET/CT 图像增强及其评价

目的:为解决融合图像视觉效果增强与量化信息损失之间的矛盾,本文提出一种基于非降采样的多孔小波(àtrous wavelet)分解的PET/CT图像融合方法,使得融合图像既有利于肿瘤诊断又能用于放疗靶区勾画和放射性定量分析。方法:对PET和CT图像分别进行多孔小波分解,以包含肿瘤目标的适当大小的感兴趣区域的清晰度为目标函数,采用Nelder-Mead算法对PET和CT图像高频分解系数之比进行优化获得最终的融合系数,使融合图像充分增加解剖学信息的同时又尽量保持PET图像原有的局部和整体灰度信息。结果:融合图像质量评价表明,本文方法能将有价值的PET功能信息与精确的CT解剖信息结合在一起,并克服传统小波融合损失图像量化信息的不足。结论:基于多孔小波融合的PET/CT图像既能用于肿瘤诊断,又能同时用于肿瘤学放射性计算和适形放疗计划制定等量化研究。     

A novel nicotinic acetylcholine receptor antagonist radioligand for PET studies

Using positron emission tomography (PET) with a specific and selective radioligand targeting nicotinic acetylcholine receptor (nAChR) would allow us to better understand various nAChR related CNS disorders. The use of radiolabeled nAChR antagonists would provide a much safer pharmacological profile, avoiding most peripheral side effects that might be generated from radiolabeled nAChR agonists even at the tracer level; thus, PET imaging with nAChR antagonists would facilitate clinical application. A potent and selective nAChR antagonist was labeled and characterized with PET in non-human primates. Its high brain uptake, high signal-to-noise ratio, and high specific binding strongly suggest a great potential to carry out imaging studies in humans. In addition, the use of a C-11 radiotracer would allow us to perform multiple PET studies in the same individual within a short time frame. The presence of an iodine atom in the molecule also allows the possibility to label with radioiodine for SPECT studies.     

Software controlling algorithms for the system performance optimization of confocal laser scanning microscope

The relative slow scanning speed of a galvanometer commonly used in a confocal laser scanning microscopy system can dramatically limit the system performance in scanning speed and image quality, if the data collection is simply synchronized with the galvanometric scanning. Several algorithms for the optimization of the galvanometric CLSM system performance are discussed in this work, with various hardware controlling techniques for the image distortion correction such as pixel delay and interlace line switching; increasing signal-to-noise ratio with data binning; or enhancing the imaging speed with region of interest imaging. Moreover, the pixel number can be effectively increased with Acquire-On-Fly scan, which can be used for the imaging of a large field-of-view with a high resolution.