Quantitative analysis of dynamic 18F-FDG PET/CT for measurement of lung inflammation

Advances in COPD imaging using CT and MRI: linkage with lung physiology and clinical outcomes

Recent years have witnessed major advances in lung imaging in patients with COPD. These include significant refinements in images obtained by computed tomography (CT) scans together with the introduction of new techniques and software that aim for obtaining the best image whilst using the lowest possible radiation dose. Magnetic resonance imaging (MRI) has also emerged as a useful radiation-free tool in assessing structural and more importantly functional derangements in patients with well-established COPD and smokers without COPD, even before the existence of overt changes in resting physiological lung function tests. Together, CT and MRI now allow objective quantification and assessment of structural changes within the airways, lung parenchyma and pulmonary vessels. Furthermore, CT and MRI can now provide objective assessments of regional lung ventilation and perfusion, and multinuclear MRI provides further insight into gas exchange; this can help in structured decisions regarding treatment plans. These advances in chest imaging techniques have brought new insights into our understanding of disease pathophysiology and characterising different disease phenotypes. The present review discusses, in detail, the advances in lung imaging in patients with COPD and how structural and functional imaging are linked with common resting physiological tests and important clinical outcomes.

High-Temporal-Resolution Kinetic Modeling of Lung Tumors with Dual-Blood Input Function Using Total-Body Dynamic PET

The lungs are supplied by both the pulmonary arteries carrying deoxygenated blood originating from the right ventricle and the bronchial arteries carrying oxygenated blood downstream from the left ventricle. However, this effect of dual blood supply has never been investigated using PET, partially because the temporal resolution of conventional dynamic PET scans is limited. The advent of PET scanners with a long axial field of view, such as the uEXPLORER total-body PET/CT system, permits dynamic imaging with high temporal resolution (HTR). In this work, we modeled the dual-blood input function (DBIF) and studied its impact on the kinetic quantification of normal lung tissue and lung tumors using HTR dynamic PET imaging. Methods: Thirteen healthy subjects and 6 cancer subjects with lung tumors underwent a dynamic 18F-FDG scan with the uEXPLORER for 1 h. Data were reconstructed into dynamic frames of 1 s in the early phase. Regional time-activity curves of lung tissue and tumors were analyzed using a 2-tissue compartmental model with 3 different input functions: the right ventricle input function, left ventricle input function, and proposed DBIF, all with time delay and dispersion corrections. These models were compared for time-activity curve fitting quality using the corrected Akaike information criterion and for differentiating lung tumors from lung tissue using the Mann-Whitney U test. Voxelwise multiparametric images by the DBIF model were further generated to verify the regional kinetic analysis. Results: The effect of dual blood supply was pronounced in the high-temporal-resolution time-activity curves of lung tumors. The DBIF model achieved better time-activity curve fitting than the other 2 single-input models according to the corrected Akaike information criterion. The estimated fraction of left ventricle input was low in normal lung tissue of healthy subjects but much higher in lung tumors (∼0.04 vs. ∼0.3, P < 0.0003). The DBIF model also showed better robustness in the difference in 18F-FDG net influx rate [Formula: see text] and delivery rate [Formula: see text] between lung tumors and normal lung tissue. Multiparametric imaging with the DBIF model further confirmed the differences in tracer kinetics between normal lung tissue and lung tumors. Conclusion: The effect of dual blood supply in the lungs was demonstrated using HTR dynamic imaging and compartmental modeling with the proposed DBIF model. The effect was small in lung tissue but nonnegligible in lung tumors. HTR dynamic imaging with total-body PET can offer a sensitive tool for investigating lung diseases.

Optimisation of the air fraction correction for lung PET/CT: addressing resolution mismatch

BACKGROUND

Increased pulmonary [Formula: see text]F-FDG metabolism in patients with idiopathic pulmonary fibrosis, and other forms of diffuse parenchymal lung disease, can predict measurements of health and lung physiology. To improve PET quantification, voxel-wise air fractions (AF) determined from CT can be used to correct for variable air content in lung PET/CT. However, resolution mismatches between PET and CT can cause artefacts in the AF-corrected image.

METHODS

Three methodologies for determining the optimal kernel to smooth the CT are compared with noiseless simulations and non-TOF MLEM reconstructions of a patient-realistic digital phantom: (i) the point source insertion-and-subtraction method, [Formula: see text]; (ii) AF-correcting with varyingly smoothed CT to achieve the lowest RMSE with respect to the ground truth (GT) AF-corrected volume of interest (VOI), [Formula: see text]; iii) smoothing the GT image to match the reconstruction within the VOI, [Formula: see text]. The methods were evaluated both using VOI-specific kernels, and a single global kernel optimised for the six VOIs combined. Furthermore, [Formula: see text] was implemented on thorax phantom data measured on two clinical PET/CT scanners with various reconstruction protocols.

RESULTS

The simulations demonstrated that at [Formula: see text] iterations (200 i), the kernel width was dependent on iteration number and VOI position in the lung. The [Formula: see text] method estimated a lower, more uniform, kernel width in all parts of the lung investigated. However, all three methods resulted in approximately equivalent AF-corrected VOI RMSEs (<10%) at [Formula: see text]200i. The insensitivity of AF-corrected quantification to kernel width suggests that a single global kernel could be used. For all three methodologies, the computed global kernel resulted in an AF-corrected lung RMSE <10%  at [Formula: see text]200i, while larger lung RMSEs were observed for the VOI-specific kernels. The global kernel approach was then employed with the [Formula: see text] method on measured data. The optimally smoothed GT emission matched the reconstructed image well, both within the VOI and the lung background. VOI RMSE was <10%, pre-AFC, for all reconstructions investigated.

CONCLUSIONS

Simulations for non-TOF PET indicated that around 200i were needed to approach image resolution stability in the lung. In addition, at this iteration number, a single global kernel, determined from several VOIs, for AFC, performed well over the whole lung. The [Formula: see text] method has the potential to be used to determine the kernel for AFC from scans of phantoms on clinical scanners.

Quantitation of dynamic total-body PET imaging: recent developments and future perspectives

BACKGROUND

Positron emission tomography (PET) scanning is an important diagnostic imaging technique used in disease diagnosis, therapy planning, treatment monitoring, and medical research. The standardized uptake value (SUV) obtained at a single time frame has been widely employed in clinical practice. Well beyond this simple static measure, more detailed metabolic information can be recovered from dynamic PET scans, followed by the recovery of arterial input function and application of appropriate tracer kinetic models. Many efforts have been devoted to the development of quantitative techniques over the last couple of decades.

CHALLENGES

The advent of new-generation total-body PET scanners characterized by ultra-high sensitivity and long axial field of view, i.e., uEXPLORER (United Imaging Healthcare), PennPET Explorer (University of Pennsylvania), and Biograph Vision Quadra (Siemens Healthineers), further stimulates valuable inspiration to derive kinetics for multiple organs simultaneously. But some emerging issues also need to be addressed, e.g., the large-scale data size and organ-specific physiology. The direct implementation of classical methods for total-body PET imaging without proper validation may lead to less accurate results.

CONCLUSIONS

In this contribution, the published dynamic total-body PET datasets are outlined, and several challenges/opportunities for quantitation of such types of studies are presented. An overview of the basic equation, calculation of input function (based on blood sampling, image, population or mathematical model), and kinetic analysis encompassing parametric (compartmental model, graphical plot and spectral analysis) and non-parametric (B-spline and piece-wise basis elements) approaches is provided. The discussion mainly focuses on the feasibilities, recent developments, and future perspectives of these methodologies for a diverse-tissue environment.

High-Temporal-Resolution Lung Kinetic Modeling Using Total-Body Dynamic PET with Time-Delay and Dispersion Corrections

Tracer kinetic modeling in dynamic PET has the potential to improve the diagnosis, prognosis, and research of lung diseases. The advent of total-body PET systems with much greater detection sensitivity enables high-temporal-resolution (HTR) dynamic PET imaging of the lungs. However, existing models may become insufficient for modeling the HTR data. In this paper, we investigate the necessity of additional corrections to the input function for HTR lung kinetic modeling. Methods: Dynamic scans with HTR frames of as short as 1 s were performed on 13 healthy subjects with a bolus injection of about [Formula: see text] of 18F-FDG using the uEXPLORER total-body PET/CT system. Three kinetic models with and without time-delay and dispersion corrections were compared for the quality of lung time-activity curve fitting using the Akaike information criterion. The impact on quantification of 18F-FDG delivery rate [Formula: see text], net influx rate [Formula: see text] and fractional blood volume [Formula: see text] was assessed. Parameter identifiability analysis was also performed to evaluate the reliability of kinetic quantification with respect to noise. Correlation of kinetic parameters with age was investigated. Results: HTR dynamic imaging clearly revealed the rapid change in tracer concentration in the lungs and blood supply (i.e., the right ventricle). The uncorrected input function led to poor time-activity curve fitting and biased quantification in HTR kinetic modeling. The fitting was improved by time-delay and dispersion corrections. The proposed model resulted in an approximately 85% decrease in [Formula: see text], an approximately 75% increase in [Formula: see text], and a more reasonable [Formula: see text] (∼0.14) than the uncorrected model (∼0.04). The identifiability analysis showed that the proposed models had good quantification stability for [Formula: see text], [Formula: see text], and [Formula: see text] The [Formula: see text] estimated by the proposed model with simultaneous time-delay and dispersion corrections correlated inversely with age, as would be expected. Conclusion: Corrections to the input function are important for accurate lung kinetic analysis of HTR dynamic PET data. The modeling of both delay and dispersion can improve model fitting and significantly impact quantification of [Formula: see text], [Formula: see text], and [Formula: see text].

Diagnostic Performance of Dynamic Whole-Body Patlak [18F]FDG-PET/CT in Patients with Indeterminate Lung Lesions and Lymph Nodes

BACKGROUND

Static [¹⁸F]FDG-PET/CT is the imaging method of choice for the evaluation of indeterminate lung lesions and NSCLC staging; however, histological confirmation of PET-positive lesions is needed in most cases due to its limited specificity. Therefore, we aimed to evaluate the diagnostic performance of additional dynamic whole-body PET.

METHODS

A total of 34 consecutive patients with indeterminate pulmonary lesions were enrolled in this prospective trial. All patients underwent static (60 min p.i.) and dynamic (0-60 min p.i.) whole-body [¹⁸F]FDG-PET/CT (300 MBq) using the multi-bed-multi-timepoint technique (Siemens mCT FlowMotion). Histology and follow-up served as ground truth. Kinetic modeling factors were calculated using a two-compartment linear Patlak model (FDG influx rate constant = Ki, metabolic rate = MR-FDG, distribution volume = DV-FDG) and compared to SUV using ROC analysis.

RESULTS

MR-FDG_mean provided the best discriminatory power between benign and malignant lung lesions with an AUC of 0.887. The AUC of DV-FDG_mean (0.818) and SUV_mean (0.827) was non-significantly lower. For LNM, the AUCs for MR-FDG_mean (0.987) and SUV_mean (0.993) were comparable. Moreover, the DV-FDG_mean in liver metastases was three times higher than in bone or lung metastases.

CONCLUSIONS

Metabolic rate quantification was shown to be a reliable method to detect malignant lung tumors, LNM, and distant metastases at least as accurately as the established SUV or dual-time-point PET scans.

Early Prediction of Radiation-Induced Pulmonary Fibrosis Using Gastrin-Releasing Peptide Receptor-Targeted PET Imaging

Early diagnosis of radiation-induced pulmonary fibrosis (RIPF) in lung cancer patients after radiation therapy is important. A gastrin-releasing peptide receptor (GRPR) mediates the inflammation and fibrosis after irradiation in mice lungs. Previously, our group synthesized a GRPR-targeted positron emission tomography (PET) imaging probe, [⁶⁴Cu]Cu-NODAGA-galacto-bombesin (BBN), an analogue peptide of GRP. In this study, we evaluated the usefulness of [⁶⁴Cu]Cu-NODAGA-galacto-BBN for the early prediction of RIPF. We prepared RIPF mice and acquired PET/CT images of [¹⁸F]F-FDG and [⁶⁴Cu]Cu-NODAGA-galacto-BBN at 0, 2, 5, and 11 weeks after irradiation (n = 3-10). We confirmed that [⁶⁴Cu]Cu-NODAGA-galacto-BBN targets GRPR in irradiated RAW 264.7 cells. In addition, we examined whether [⁶⁴Cu]Cu-NODAGA-galacto-BBN monitors the therapeutic efficacy in RIPF mice (n = 4). As a result, the lung uptake ratio (irradiated-to-normal) of [⁶⁴Cu]Cu-NODAGA-galacto-BBN was the highest at 2 weeks, followed by its decrease at 5 and 11 weeks after irradiation, which matched with the expression of GRPR and was more accurately predicted than [¹⁸F]F-FDG. These uptake results were also confirmed by the cell uptake assay. Furthermore, [⁶⁴Cu]Cu-NODAGA-galacto-BBN could monitor the therapeutic efficacy of pirfenidone in RIPF mice. We conclude that [⁶⁴Cu]Cu-NODAGA-galacto-BBN is a novel PET imaging probe for the early prediction of RIPF-targeting GRPR expressed during the inflammatory response.

Dynamic FDG-PET imaging for differentiating metastatic from non-metastatic lymph nodes of lung cancer

OBJECTIVES

18F-fluorodeoxyglucose (FDG) PET/CT has been widely used in tumor diagnosis, staging, and response evaluation. To determine an optimal therapeutic strategy for lung cancer patients, accurate staging is essential. Semi-quantitative standardized uptake value (SUV) is known to be affected by multiple factors and may fail to differentiate between benign and malignant lesions. Lymph nodes (LNs) in the mediastinal and pulmonary hilar regions with high FDG uptake due to granulomatous lesions such as tuberculosis, which has a high prevalence in China, pose a diagnostic challenge. This study aims to evaluate the diagnostic value of the quantitative metabolic parameters derived from dynamic 18F-FDG PET/CT in differentiating metastatic and non-metastatic LNs in lung cancer.

METHODS

One hundred and eight patients with pulmonary nodules were enrolled to perform 18F-FDG PET/CT dynamic + static imaging with informed consent. One hundred and thirty-five LNs in 29 lung cancer patients were confirmed by pathology. Static image analysis parameters including LN-SUVmax, LN-SUVmax/primary tumor SUVmax (LN-SUVmax/PT-SUVmax), mediastinal blood pool SUVmax (MBP-SUVmax), LN-SUVmax/MBP-SUVmax, and LN-SUVmax/short diameter. Quantitative parameters including K1, k2, k3 and Ki and of each LN were obtained by applying the irreversible two-tissue compartment model using in-house Matlab software. Ki/K1 was computed subsequently as a separate marker. We further divided the LNs into mediastinal LNs (N=82) and pulmonary hilar LNs (N=53). Wilcoxon rank-sum test or Independent-samples T-test and receiver-operating characteristic (ROC) analysis was performed on each parameter to compare the diagnostic efficacy in differentiating lymph node metastases from inflammatory uptake. P<0.05 were considered statistically significant.

RESULTS

Among the 135 FDG-avid LNs confirmed by pathology, 49 LNs were non-metastatic, and 86 LNs were metastatic. LN-SUVmax, MBP-SUVmax, LN-SUVmax/MBP-SUVmax, and LN-SUVmax/short diameter couldn't well differentiate metastatic from non-metastatic LNs (P>0.05). However, LN-SUVmax/PT-SUVmax have good performance in the differential diagnosis of non-metastatic and metastatic LNs (P=0.039). Dynamic metabolic parameters in addition to k3, the parameters including K1, k2, Ki, and Ki/K1, on the other hand, have good performance in the differential diagnosis of metastatic and non-metastatic LNs (P=0.045, P=0.001, P=0.001, P=0.001, respectively). For ROC analysis, the metabolic parameters Ki (AUC of 0.672 [0.579-0.765], sensitivity 0.395, specificity 0.918) and Ki/K1 (AUC of 0.673 [0.580-0.767], sensitivity 0.570, specificity 0.776) have good performance in the differential diagnosis of metastatic from non-metastatic LNs than SUVmax (AUC of 0.596 [0.498-0.696], sensitivity 0.826, specificity 0.388), included the mediastinal region and pulmonary hilar region.

CONCLUSION

Compared with SUVmax, quantitative parameters such as K1, k2, Ki and Ki/K1 showed promising results for differentiation of metastatic and non-metastatic LNs with high uptake. The Ki and Ki/K1 had a high differential diagnostic value both in the mediastinal region and pulmonary hilar region.

Overview of positron emission tomography in functional imaging of the lungs for diffuse lung diseases

Positron emission tomography (PET) is a quantitative molecular imaging modality increasingly used to study pulmonary disease processes and drug effects on those processes. The wide range of drugs and other entities that can be radiolabeled to study molecularly targeted processes is a major strength of PET, thus providing a noninvasive approach for obtaining molecular phenotyping information. The use of PET to monitor disease progression and treatment outcomes in DLD has been limited in clinical practice, with most of such applications occurring in the context of research investigations under clinical trials. Given the high costs and failure rates for lung drug development efforts, molecular imaging lung biomarkers are needed not only to aid these efforts but also to improve clinical characterization of these diseases beyond canonical anatomic classifications based on computed tomography. The purpose of this review article is to provide an overview of PET applications in characterizing lung disease, focusing on novel tracers that are in clinical development for DLD molecular phenotyping, and briefly address considerations for accurately quantifying lung PET signals.

First results on kinetic modelling and parametric imaging of dynamic 18F-FDG datasets from a long axial FOV PET scanner in oncological patients

PURPOSE

To investigate the kinetics of ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) by positron emission tomography (PET) in multiple organs and test the feasibility of total-body parametric imaging using an image-derived input function (IDIF).

METHODS

Twenty-four oncological patients underwent dynamic ¹⁸F-FDG scans lasting 65 min using a long  axial FOV (LAFOV) PET/CT system. Time activity curves (TAC) were extracted from semi-automated segmentations of multiple organs, cerebral grey and white matter, and from vascular structures. The tissue and tumor lesion TACs were fitted using an irreversible two-tissue compartment (2TC) and a Patlak model. Parametric images were also generated using direct and indirect Patlak methods and their performances were evaluated.

RESULTS

We report estimates of kinetic parameters and metabolic rate of glucose consumption (MR_FDG) for different organs and tumor lesions. In some organs, there were significant differences between MR_FDG values estimated using 2TC and Patlak models. No statistically significant difference was seen between MR_FDG values estimated using 2TC and Patlak methods in tumor lesions (paired t-test, P = 0.65). Parametric imaging showed that net influx (K_i) images generated using direct and indirect Patlak methods had superior tumor-to-background ratio (TBR) to standard uptake value (SUV) images (3.1- and 3.0-fold mean increases in TBR_mean, respectively). Influx images generated using the direct Patlak method had twofold higher contrast-to-noise ratio in tumor lesions compared to images generated using the indirect Patlak method.

CONCLUSION

We performed pharmacokinetic modelling of multiple organs using linear and non-linear models using dynamic total-body ¹⁸F-FDG images. Although parametric images did not reveal more tumors than SUV images, the results confirmed that parametric imaging furnishes improved tumor contrast. We thus demonstrate the feasibility of total-body kinetic modelling and parametric imaging in basic research and oncological studies. LAFOV PET can enhance dynamic imaging capabilities by providing high sensitivity parametric images and allowing total-body pharmacokinetic analysis.

Quantitative 18F-fluorodeoxyglucose positron emission tomography/computed tomography to assess pulmonary inflammation in COPD

Rationale

COPD and smoking are characterised by pulmonary inflammation. ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) imaging may improve knowledge of pulmonary inflammation in COPD patients and aid early development of novel therapies as an imaging biomarker.

Objectives

To evaluate pulmonary inflammation, assessed by FDG uptake, in whole and regional lung in “usual” (smoking-related) COPD patients, alpha-1 antitrypsin deficiency (α₁ATD) COPD patients, smokers without COPD and never-smokers using FDG PET/CT. Secondly, to explore cross-sectional associations between FDG PET/CT and systemic inflammatory markers in COPD patients and repeatability of the technique in COPD patients.

Methods

Data from two imaging studies were evaluated. Pulmonary FDG uptake (normalised K_i; nK_i) was measured by Patlak graphical analysis in four subject groups: 84 COPD patients, 11 α₁ATD-COPD patients, 12 smokers and 10 never-smokers. Within the COPD group, associations between nK_i and systemic markers of inflammation were assessed. Repeatability was evaluated in 32 COPD patients comparing nK_i values at baseline and at 4-month follow-up.

Results

COPD patients, α₁ATD-COPD patients and smokers had increased whole lung FDG uptake (nK_i) compared with never-smokers (0.0037±0.001, 0.0040±0.001, 0.0040±0.001 versus 0.0028±0.001 mL·cm⁻³·min⁻¹, respectively, p<0.05 for all). Similar results were observed in upper and middle lung regions. In COPD participants, plasma fibrinogen was associated with whole lung nK_i (β=0.30, p=0.02) in multivariate analysis adjusted for current smoking, forced expiratory volume in 1 s % predicted, systemic neutrophils and C-reactive protein levels. Mean percentage difference in nK_i between the baseline and follow-up was 3.2%, and the within subject coefficient of variability was 7.7%.

Conclusions

FDG PET/CT has potential as a noninvasive tool to enable whole lung and regional quantification of FDG uptake to assess smoking- and COPD-related pulmonary inflammation.

FDG PET/CT has potential utility to noninvasively evaluate pulmonary inflammation in COPD. Pulmonary FDG uptake is increased in COPD patients, positively associated with systemic inflammatory markers and shows low inter-occasion variability.https://bit.ly/3dELYAW

Molecular Imaging of Inflammatory Disease

Inflammatory diseases include a wide variety of highly prevalent conditions with high mortality rates in severe cases ranging from cardiovascular disease, to rheumatoid arthritis, to chronic obstructive pulmonary disease, to graft vs. host disease, to a number of gastrointestinal disorders. Many diseases that are not considered inflammatory per se are associated with varying levels of inflammation. Imaging of the immune system and inflammatory response is of interest as it can give insight into disease progression and severity. Clinical imaging technologies such as computed tomography (CT) and magnetic resonance imaging (MRI) are traditionally limited to the visualization of anatomical information; then, the presence or absence of an inflammatory state must be inferred from the structural abnormalities. Improvement in available contrast agents has made it possible to obtain functional information as well as anatomical. In vivo imaging of inflammation ultimately facilitates an improved accuracy of diagnostics and monitoring of patients to allow for better patient care. Highly specific molecular imaging of inflammatory biomarkers allows for earlier diagnosis to prevent irreversible damage. Advancements in imaging instruments, targeted tracers, and contrast agents represent a rapidly growing area of preclinical research with the hopes of quick translation to the clinic.

PET Parametric Imaging: Past, Present, and Future

Positron emission tomography (PET) is actively used in a diverse range of applications in oncology, cardiology, and neurology. The use of PET in the clinical setting focuses on static (single time frame) imaging at a specific time-point post radiotracer injection and is typically considered as semi-quantitative; e.g. standardized uptake value (SUV) measures. In contrast, dynamic PET imaging requires increased acquisition times but has the advantage that it measures the full spatiotemporal distribution of a radiotracer and, in combination with tracer kinetic modeling, enables the generation of multiparametric images that more directly quantify underlying biological parameters of interest, such as blood flow, glucose metabolism, and receptor binding. Parametric images have the potential for improved detection and for more accurate and earlier therapeutic response assessment. Parametric imaging with dynamic PET has witnessed extensive research in the past four decades. In this paper, we provide an overview of past and present activities and discuss emerging opportunities in the field of parametric imaging for the future.

Consensus Recommendations on the Use of 18F-FDG PET/CT in Lung Disease

PET with ¹⁸F-FDG has been increasingly applied, predominantly in the research setting, to study drug effects and pulmonary biology and to monitor disease progression and treatment outcomes in lung diseases that interfere with gas exchange through alterations of the pulmonary parenchyma, airways, or vasculature. To date, however, there are no widely accepted standard acquisition protocols or imaging data analysis methods for pulmonary ¹⁸F-FDG PET/CT in these diseases, resulting in disparate approaches. Hence, comparison of data across the literature is challenging. To help harmonize the acquisition and analysis and promote reproducibility, we collated details of acquisition protocols and analysis methods from 7 PET centers. From this information and our discussions, we reached the consensus recommendations given here on patient preparation, choice of dynamic versus static imaging, image reconstruction, and image analysis reporting.

From SARS and MERS to COVID-19: a brief summary and comparison of severe acute respiratory infections caused by three highly pathogenic human coronaviruses

Within two decades, there have emerged three highly pathogenic and deadly human coronaviruses, namely SARS-CoV, MERS-CoV and SARS-CoV-2. The economic burden and health threats caused by these coronaviruses are extremely dreadful and getting more serious as the increasing number of global infections and attributed deaths of SARS-CoV-2 and MERS-CoV. Unfortunately, specific medical countermeasures for these hCoVs remain absent. Moreover, the fast spread of misinformation about the ongoing SARS-CoV-2 pandemic uniquely places the virus alongside an annoying infodemic and causes unnecessary worldwide panic. SARS-CoV-2 shares many similarities with SARS-CoV and MERS-CoV, certainly, obvious differences exist as well. Lessons learnt from SARS-CoV and MERS-CoV, timely updated information of SARS-CoV-2 and MERS-CoV, and summarized specific knowledge of these hCoVs are extremely invaluable for effectively and efficiently contain the outbreak of SARS-CoV-2 and MERS-CoV. By gaining a deeper understanding of hCoVs and the illnesses caused by them, we can bridge knowledge gaps, provide cultural weapons for fighting and controling the spread of MERS-CoV and SARS-CoV-2, and prepare effective and robust defense lines against hCoVs that may emerge or reemerge in the future. To this end, the state-of-the-art knowledge and comparing the biological features of these lethal hCoVs and the clinical characteristics of illnesses caused by them are systematically summarized in the review.

From SARS and MERS to COVID-19: a brief summary and comparison of severe acute respiratory infections caused by three highly pathogenic human coronaviruses

Within two decades, there have emerged three highly pathogenic and deadly human coronaviruses, namely SARS-CoV, MERS-CoV and SARS-CoV-2. The economic burden and health threats caused by these coronaviruses are extremely dreadful and getting more serious as the increasing number of global infections and attributed deaths of SARS-CoV-2 and MERS-CoV. Unfortunately, specific medical countermeasures for these hCoVs remain absent. Moreover, the fast spread of misinformation about the ongoing SARS-CoV-2 pandemic uniquely places the virus alongside an annoying infodemic and causes unnecessary worldwide panic. SARS-CoV-2 shares many similarities with SARS-CoV and MERS-CoV, certainly, obvious differences exist as well. Lessons learnt from SARS-CoV and MERS-CoV, timely updated information of SARS-CoV-2 and MERS-CoV, and summarized specific knowledge of these hCoVs are extremely invaluable for effectively and efficiently contain the outbreak of SARS-CoV-2 and MERS-CoV. By gaining a deeper understanding of hCoVs and the illnesses caused by them, we can bridge knowledge gaps, provide cultural weapons for fighting and controling the spread of MERS-CoV and SARS-CoV-2, and prepare effective and robust defense lines against hCoVs that may emerge or reemerge in the future. To this end, the state-of-the-art knowledge and comparing the biological features of these lethal hCoVs and the clinical characteristics of illnesses caused by them are systematically summarized in the review.

Potential Applications of PET Scans, CT Scans, and MR Imaging in Inflammatory Diseases: Part II: Cardiopulmonary and Vascular Inflammation

Detecting inflammation is among the most important aims of medical imaging. Inflammatory process involves immune system activity and local tissue response. The role of PET with fludeoxyglucose F 18 has been expanded. Systemic vasculitides and cardiopulmonary inflammatory disorders constitute a wide range of diseases with multisystemic manifestations. PET with fludeoxyglucose F 18 is useful in their diagnosis, assessment, and follow-up. This article provides an overview of the current status and potentials of hybrid molecular imaging in evaluating cardiopulmonary and vascular inflammatory diseases focusing on the potential for PET with fludeoxyglucose F 18/MR imaging and PET/CT scans.

Quantification and reliability of [11C]VC - 002 binding to muscarinic acetylcholine receptors in the human lung - a test-retest PET study in control subjects

BACKGROUND

The radioligand [11C]VC-002 was introduced in a small initial study long ago for imaging of muscarinic acetylcholine receptors (mAChRs) in human lungs using positron emission tomography (PET). The objectives of the present study in control subjects were to advance the methodology for quantification of [11C]VC-002 binding in lung and to examine the reliability using a test-retest paradigm. This work constituted a self-standing preparatory step in a larger clinical trial aiming at estimating mAChR occupancy in the human lungs following inhalation of mAChR antagonists.

METHODS

PET measurements using [11C]VC-002 and the GE Discovery 710 PET/CT system were performed in seven control subjects at two separate occasions, 2-19 days apart. One subject discontinued the study after the first measurement. Radioligand binding to mAChRs in lung was quantified using an image-derived arterial input function. The total distribution volume (VT) values were obtained on a regional and voxel-by-voxel basis. Kinetic one-tissue and two-tissue compartment models (1TCM, 2TCM), analysis based on linearization of the compartment models (multilinear Logan) and image analysis by data-driven estimation of parametric images based on compartmental theory (DEPICT) were applied. The test-retest repeatability of VT estimates was evaluated by absolute variability (VAR) and intraclass correlation coefficients (ICCs).

RESULTS

The 1TCM was the statistically preferred model for description of [11C]VC-002 binding in the lungs. Low VAR (< 10%) across analysis methods indicated good reliability of the PET measurements. The VT estimates were stable after 60 min.

CONCLUSIONS

The kinetic behaviour and good repeatability of [11C]VC-002 as well as the novel lung image analysis methodology support its application in applied studies on drug-induced mAChR receptor occupancy and the pathophysiology of pulmonary disorders.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT03097380, registered: 31 March 2017.

Integrin αvβ6 Positron Emission Tomography Imaging in Lung Cancer Patients Treated With Pulmonary Radiation Therapy

PURPOSE

Post radiation therapy (RT) lung fibrosis is a major barrier to improved cure rate in lung cancer. Integrin αvβ6 plays a key role in fibrogenesis by activating transforming growth factor-β. Positron emission tomography (PET) studies with a fluorine-18 radiolabelled αvβ6 radioligand, [¹⁸F]-FBA-A20FMDV2, were performed to assess uptake, and the relationship to RT dose parameters was explored.

METHODS AND MATERIALS

Recently treated non-small cell lung cancer patients (<6 months after RT) had [¹⁸F]-FBA-A20FMDV2-PET scans, coregistered with the RT planning computed tomography and segmented to RT doses of >40 Gy (excluding tumor), 25 to 40 Gy, 15 to 25 Gy, 8 to 15 Gy, and <8 Gy. PET uptake (standardized uptake value; SUV) corrected for tissue density between 10 and 60 minutes (SUV_10-60) was calculated and compared with RT dose, dose per fraction, and biological effective dose (BED). PET uptake was also evaluated in healthy volunteers.

RESULTS

Six non-small cell lung cancer (3 male; 3 female) subjects scanned between 6 and 22 weeks after RT and 6 healthy volunteers (3 males; 3 females) were evaluated. Higher mean PET uptake (SUV_10-60) was observed in the irradiated lung compared with the healthy lung (2.97 vs 1.99; P < .05). A significant and positive pharmacodynamic relationship was observed between radioligand uptake (SUV_10-60) and dose per RT fraction (r² = 0.63; P < .001) and with BED for fibrosis (r² = 0.38; P < .001 for α/β 3 Gy and r² = 0.33; P < 0.001 for α/β 5 Gy).

CONCLUSIONS

Higher uptake in the irradiated lung and a pharmacodynamic relationship between αvβ6 radioligand uptake versus RT dose per fraction and BED for lung fibrosis is consistent with RT induced activation of αvβ6 integrin and supports a role for αvβ6 in the induction of lung fibrosis after pulmonary RT. αvβ6-PET imaging may potentially aid in the assessment and management of radiation-induced pulmonary fibrosis.

Reproducibility of compartmental modelling of 18F-FDG PET/CT to evaluate lung inflammation

Introduction

Compartmental modelling is an established method of quantifying ¹⁸F-FDG uptake; however, only recently has it been applied to evaluate pulmonary inflammation. Implementation of compartmental models remains challenging in the lung, partly due to the low signal-to-noise ratio compared to other organs and the lack of standardisation. Good reproducibility is a key requirement of an imaging biomarker which has yet to be demonstrated in pulmonary compartmental models of ¹⁸F-FDG; in this paper, we address this unmet need.

Methods

Retrospective subject data were obtained from the EVOLVE observational study: Ten COPD patients (age =66±9; 8M/2F), 10 α₁ATD patients (age =63±8; 7M/3F) and 10 healthy volunteers (age =68±8; 9M/1F) never smokers. PET and CT images were co-registered, and whole lung regions were extracted from CT using an automated algorithm; the descending aorta was defined using a manually drawn region. Subsequent stages of the compartmental analysis were performed by two independent operators using (i) a MIAKAT^TM based pipeline and (ii) an in-house developed pipeline. We evaluated the metabolic rate constant of ¹⁸F-FDG (K_im) and the fractional blood volume (V_b); Bland-Altman plots were used to compare the results. Further, we adjusted the in-house pipeline to identify the salient features in the analysis which may help improve the standardisation of this technique in the lung.

Results

The initial agreement on a subject level was poor: Bland-Altman coefficients of reproducibility for K_im and V_b were 0.0031 and 0.047 respectively. However, the effect size between the groups (i.e. COPD, α₁ATD and healthy subjects) was similar using either pipeline. We identified the key drivers of this difference using an incremental approach: ROI methodology, modelling of the IDIF and time delay estimation. Adjustment of these factors led to improved Bland-Altman coefficients of reproducibility of 0.0015 and 0.027 for K_im and V_b respectively.

Conclusions

Despite similar methodology, differences in implementation can lead to disparate results in the outcome parameters. When reporting the outcomes of lung compartmental modelling, we recommend the inclusion of the details of ROI methodology, input function fitting and time delay estimation to improve reproducibility.

QModeling: a Multiplatform, Easy-to-Use and Open-Source Toolbox for PET Kinetic Analysis

Kinetic modeling is at the basis of most quantification methods for dynamic PET data. Specific software is required for it, and a free and easy-to-use kinetic analysis toolbox can facilitate routine work for clinical research. The relevance of kinetic modeling for neuroimaging encourages its incorporation into image processing pipelines like those of SPM, also providing preprocessing flexibility to match the needs of users. The aim of this work was to develop such a toolbox: QModeling. It implements four widely-used reference-region models: Simplified Reference Tissue Model (SRTM), Simplified Reference Tissue Model 2 (SRTM2), Patlak Reference and Logan Reference. A preliminary validation was also performed: The obtained parameters were compared with the gold standard provided by PMOD, the most commonly-used software in this field. Execution speed was also compared, for time-activity curve (TAC) estimation, model fitting and image generation. QModeling has a simple interface, which guides the user through the analysis: Loading data, obtaining TACs, preprocessing the model for pre-evaluation, generating parametric images and visualizing them. Relative differences between QModeling and PMOD in the parameter values are almost always below 10^-8. The SRTM2 algorithm yields relative differences from 10^-3 to 10^-5 when [Formula: see text] is not fixed, since different, validated methods are used to fit this parameter. The new toolbox works efficiently, with execution times of the same order as those of PMOD. Therefore, QModeling allows applying reference-region models with reliable results in efficient computation times. It is free, flexible, multiplatform, easy-to-use and open-source, and it can be easily expanded with new models.

[18F]Fluorocholine and [18F]Fluoroacetate PET as Imaging Biomarkers to Assess Phosphatidylcholine and Mitochondrial Metabolism in Preclinical Models of TSC and LAM

PURPOSE

Tuberous sclerosis complex (TSC) is an autosomal dominant disorder caused by inactivating mutations of the TSC1 or TSC2 gene, characterized by neurocognitive impairment and benign tumors of the brain, skin, heart, and kidneys. Lymphangioleiomyomatosis (LAM) is a diffuse proliferation of α-smooth muscle actin-positive cells associated with cystic destruction of the lung. LAM occurs almost exclusively in women, as a TSC manifestation or a sporadic disorder (TSC1/TSC2 somatic mutations). Biomarkers of whole-body tumor burden/activity and response to rapalogs or other therapies remain needed in TSC/LAM.

EXPERIMENTAL DESIGN

These preclinical studies aimed to assess feasibility of [¹⁸F]fluorocholine (FCH) and [¹⁸F]fluoroacetate (FACE) as TSC/LAM metabolic imaging biomarkers.

RESULTS

We previously reported that TSC2-deficient cells enhance phosphatidylcholine synthesis via the Kennedy pathway. Here, we show that TSC2-deficient cells exhibit rapid uptake of [¹⁸F]FCH in vivo and can be visualized by PET imaging in preclinical models of TSC/LAM, including subcutaneous tumors and pulmonary nodules. Treatment with rapamycin (72 hours) suppressed [¹⁸F]FCH standardized uptake value (SUV) by >50% in tumors. Interestingly, [¹⁸F]FCH-PET imaging of TSC2-deficient xenografts in ovariectomized mice also showed a significant decrease in tumor SUV. Finally, we found rapamycin-insensitive uptake of FACE by TSC2-deficient cells in vitro and in vivo, reflecting its mitochondrial accumulation via inhibition of aconitase, a TCA cycle enzyme.

CONCLUSIONS

Preclinical models of TSC2 deficiency represent informative platforms to identify tracers of potential clinical interest. Our findings provide mechanistic evidence for testing the potential of [¹⁸F]FCH and [¹⁸F]FACE as metabolic imaging biomarkers for TSC and LAM proliferative lesions, and novel insights into the metabolic reprogramming of TSC tumors.

Tuberculosis

Tuberculosis (TB) is currently the world's leading cause of infectious mortality. Imaging plays an important role in the management of this disease. The complex immune response of the human body to Mycobacterium tuberculosis results in a wide array of clinical manifestations, making clinical and radiological diagnosis challenging. ¹⁸F-FDG-PET/CT is very sensitive in the early detection of TB in most parts of the body; however, the lack of specificity is a major limitation. ¹⁸F-FDG-PET/CT images the whole body and provides a pre-therapeutic metabolic map of the infection, enabling clinicians to accurately assess the burden of disease. It enables the most appropriate site of biopsy to be selected, stages the infection, and detects disease in previously unknown sites. ¹⁸F-FDG-PET/CT has recently been shown to be able to identify a subset of patients with latent TB infection who have subclinical disease. Lung inflammation as detected by ¹⁸F-FDG-PET/CT has shown promising signs that it may be a useful predictor of progression from latent to active infection. A number of studies have identified imaging features that might improve the specificity of ¹⁸F-FDG-PET/CT at some sites of extrapulmonary TB. Other PET tracers have also been investigated for their use in TB, with some promising results. The potential role and future perspectives of PET/CT in imaging TB is considered. Literature abounds on the very important role of ¹⁸F-FDG-PET/CT in assessing therapy response in TB. The use of ¹⁸F-FDG for monitoring response to treatment is addressed in a separate review.