Clinical Evaluation of a Data-Driven Respiratory Gating Algorithm for Whole-Body PET with Continuous Bed Motion

Effects of data-driven respiratory gating on visualization and quantification of breast and upper abdominal cancers in FDG PET/CT examinations

OBJECTIVE

Data-driven respiratory gating (DDG) has recently been introduced to improve image quality in the PET portion of PET/CT examinations. The latest DDG system does not require any external equipment or extended examination time. In this study, we investigated the effects of the new DDG system on the visualization and quantification of breast and upper abdominal cancers, comparing the results with those obtained using the standard free-breathing (STD) PET protocol.

METHODS

A total of 223 cancer lesions (138 breast and 85 upper abdominal) evaluated with FDG PET/CT were included in this study. PET images were reconstructed using the STD and DDG algorithms. Lesion blurring and conspicuity were each visually graded on a three-point scale. The longest diameter (LD), SUVmax, and metabolic tumor volume (MTV) of the lesions were used for quantitative analysis. % change in SUVmax or MTV was calculated from the metrics in STD and DDG images. Fifty-six texture features (TFs) were also evaluated. Visual scores and quantitative metrics were compared between STD and DDG images. % change in SUVmax or MTV was compared in the lesion location groups or in the high and low groups based on LD, SUVmax, or MTV in STD images.

RESULTS

Visual scores for lesion blurring and conspicuity were both significantly higher in DDG than in STD PET images. SUVmax and MTV were significantly higher and lower, respectively, in DDG than in STD images. An increase in SUVmax and a decrease in MTV were observed in 96% and 86% of all lesions, respectively. Group analysis revealed that % change in SUVmax was greater in the upper abdominal than the breast lesions and % change in MTV was greater in the high LD and high MTV groups than in the low LD and low MTV groups, respectively. Quantitative changes in TFs were observed between STD and DDG images for most of the features.

CONCLUSION

This study demonstrated that DDG improved visualization and quantification of breast and upper abdominal cancers in FDG PET/CT examinations. DDG PET images exhibited an increase in SUVmax, a decrease in MTV, and changes in TFs.

Evaluation of a motion correction algorithm in lung cancer PET/CT: Phantom validation and patient studies

BACKGROUND

Data-driven gating (DDG) is an emerging technology that can reduce the respiratory motion artifacts in positron emission tomography (PET) images.

PURPOSE

The aim of this study is to use phantom and patient data to validate the performance of DDG with a motion correction algorithm based on the reconstruct, register, and average (RRA) method.

METHODS

A customized motion platform drove the phantom (five spheres with diameters of 10-28 mm) using a periodic motion that had a duration of 3-5 s and amplitudes of 2-4 cm. Normalized ratio of ungated and RRA PET relative to the ground-truth static PET was calculated for RSUVmax, RSUVmean, RSUVpeak, RVolume, and relative contrast-to-noise ratio (RCNR). Additionally, 30 lung cancer patients with 76 lung lesions less than 3 cm in diameter were prospectively studied. The overall image quality of patient examination was scored using a 5-point scale by two radiologists. SUVmax, SUVmean, SUVpeak, volume, and CNR of lesions measured in ungated and RRA PET were compared, and subgroup analysis was conducted.

RESULTS

In RRA PET images, motion artifacts of the spheres in the phantom were effectively mitigated, regardless of changes in movement amplitudes or duration. For all spheres with different ranges of motion and cycles, RSUVmax, RSUVmean, RSUVpeak, and RCNR increased significantly (p ≤ 0.001) and RVolume decreased significantly (p < 0.001) in RRA PET images. The average radiologist scores of image quality were 3.90 ± 0.86 with RRA PET, and 3.03 ± 1.19 with ungated PET. In RRA PET images, the SUVmax (p < 0.001), SUVmean (p < 0.001), SUVpeak (p < 0.001), and CNR (p < 0.001) of the lesions increased, while the volume (p < 0.001) of the lesions decreased. Δ%SUVmax, Δ%SUVmean, Δ%SUVpeak, and Δ%CNR of the lesions increased by 3.9%, 6.5%, 5.6%, and 4.3%, respectively, while Δ%Volume of the lesions decreased by 18.4%. Subgroup analysis showed that in lesions in the upper and middle lobes, only SUVpeak (p < 0.001) significantly increased by 5.6% in RRA PET, while their volume (p < 0.001) notably decreased by 12.4% (p < 0.001).

CONCLUSION

DDG integrated with RRA motion correction algorithm can effectively mitigate motion artifacts, thus enhancing the quantification accuracy and visual quality of images in lung cancer PET/CT.

Validation and clinical impact of motion-free PET imaging using data-driven respiratory gating and elastic PET-CT registration

PURPOSE

Clinical whole-body (WB) PET images can be compensated for respiratory motion using data-driven gating (DDG). However, PET DDG images may still exhibit motion artefacts at the diaphragm if the CT is acquired in a different respiratory phase than the PET image. This study evaluates the combined use of PET DDG and a deep-learning model (AIR-PETCT) for elastic registration of CT (WarpCT) to the non attenuation- and non scatter-corrected PET image (PET NAC), enabling improved PET reconstruction.

METHODS

The validation cohort included 20 patients referred for clinical FDG PET/CT, undergoing two CT scans: a free respiration CTfree and an end-expiration breath-hold CTex. AIR-PETCT registered each CT to the PET NAC and PET DDG NAC images. The image quality of PET and PET DDG images reconstructed using CTs and WarpCTs was evaluated by three blinded readers. Additionally, a clinical impact cohort of 20 patients with significant "banana" artefacts from FDG, PSMA, and DOTATOC scans was assessed for image quality and tumor-to-background ratios.

RESULTS

AIR-PETCT was robust and generated consistent WarpCTs when registering different CTs to the same PET NAC. The use of WarpCT instead of CT consistently led to equivalent or improved PET image quality. The algorithm significantly reduced "banana" artefacts and improved lesion-to-background ratios around the diaphragm. The blinded clinicians clearly preferred PET DDG images reconstructed using WarpCT.

CONCLUSION

AIR-PETCT effectively reduces respiratory motion artefacts from PET images, while improving lesion contrast. The combination of PET DDG and WarpCT holds promise for clinical application, improving PET image evaluation and diagnostic confidence.

Device-Less Data-Driven Cardiac and Respiratory Gating Using LAFOV PET Histo Images

Background: The outstanding capabilities of modern Positron Emission Tomography (PET) to highlight small tumor lesions and provide pathological function assessment are at peril from image quality degradation caused by respiratory and cardiac motion. However, the advent of the long axial field-of-view (LAFOV) scanners with increased sensitivity, alongside the precise time-of-flight (TOF) of modern PET systems, enables the acquisition of ultrafast time resolution images, which can be used for estimating and correcting the cyclic motion. Methods: 0.25 s so-called [18F]FDG PET histo image series were generated in the scope of for detecting respiratory and cardiac frequency estimates applicable for performing device-less data-driven gated image reconstructions. The frequencies of the cardiac and respiratory motion were estimated for 18 patients using Short Time Fourier Transform (STFT) with 20 s and 30 s window segments, respectively. Results: The Fourier analysis provided time points usable as input to the gated reconstruction based on eight equally spaced time gates. The cardiac investigations showed estimates in accordance with the measured pulse oximeter references (p = 0.97) and a mean absolute difference of 0.4 ± 0.3 beats per minute (bpm). The respiratory frequencies were within the expected range of 10-20 respirations per minute (rpm) in 16 out of 18 patients. Using this setup, the analysis of three patients with visible lung tumors showed an increase in tumor SUVmax and a decrease in tumor volume compared to the non-gated reconstructed image. Conclusions: The method can provide signals that were applicable for gated reconstruction of both cardiac and respiratory motion, providing a potential increased diagnostic accuracy.

Data driven surrogate signal extraction for dynamic PET using selective PCA: time windows versus the combination of components

Objective.Respiratory motion correction is beneficial in positron emission tomography (PET), as it can reduce artefacts caused by motion and improve quantitative accuracy. Methods of motion correction are commonly based on a respiratory trace obtained through an external device (like the real time position management system) or a data driven method, such as those based on dimensionality reduction techniques (for instance principal component analysis (PCA)). PCA itself being a linear transformation to the axis of greatest variation. Data driven methods have the advantage of being non-invasive, and can be performed post-acquisition. However, their main downside being that they are adversely affected by the tracer kinetics of the dynamic PET acquisition. Therefore, they are mostly limited to static PET acquisitions. This work seeks to extend on existing PCA-based data-driven motion correction methods, to allow for their applicability to dynamic PET imaging.Approach.The methods explored in this work include; a moving window approach (similar to the Kinetic Respiratory Gating method from Schleyeret al(2014)), extrapolation of the principal component from later time points to earlier time points, and a method to score, select, and combine multiple respiratory components. The resulting respiratory traces were evaluated on 22 data sets from a dynamic [18F]-FDG study on patients with idiopathic pulmonary fibrosis. This was achieved by calculating their correlation with a surrogate signal acquired using a real time position management system.Main results.The results indicate that all methods produce better surrogate signals than when applying conventional PCA to dynamic data (for instance, a higher correlation with a gold standard respiratory trace). Extrapolating a late time point principal component produced more promising results than using a moving window. Scoring, selecting, and combining components held benefits over all other methods.Significance.This work allows for the extraction of a surrogate signal from dynamic PET data earlier in the acquisition and with a greater accuracy than previous work. This potentially allows for numerous other methods (for instance, respiratory motion correction) to be applied to this data (when they otherwise could not be previously used).

Data-driven gated positron emission tomography/computed tomography for radiotherapy

Purpose

Software-based data-driven gated (DDG) positron emission tomography/computed tomography (PET/CT) has replaced hardware-based 4D PET/CT. The purpose of this article was to review DDG PET/CT, which could improve the accuracy of treatment response assessment, tumor motion evaluation, and target tumor contouring with whole-body (WB) PET/CT for radiotherapy (RT).

Material and methods

This review covered the topics of 4D PET/CT with hardware gating, advancements in PET instrumentation, DDG PET, DDG CT, and DDG PET/CT based on a systematic literature review. It included a discussion of the large axial field-of-view (AFOV) PET detector and a review of the clinical results of DDG PET and DDG PET/CT.

Results

DDG PET matched or outperformed 4D PET with hardware gating. DDG CT was more compatible with DDG PET than 4D CT, which required hardware gating. DDG CT could replace 4D CT for RT. DDG PET and DDG CT for DDG PET/CT can be incorporated in a WB PET/CT of less than 15 min scan time on a PET/CT scanner of at least 25 cm AFOV PET detector.

Conclusions

DDG PET/CT could correct the misregistration and tumor motion artifacts in a WB PET/CT and provide the quantitative PET and tumor motion information of a registered PET/CT for RT.

Correcting CT misregistration in data-driven gated (DDG) PET with PET self-gating and deformable image registration

BACKGROUND

Misregistration between CT and PET data can result in mis-localization and inaccurate quantification of functional uptake in whole body PET/CT imaging. This problem is exacerbated when an abnormal inspiration occurs during the free-breathing helical CT (FB CT) used for attenuation correction of PET data. In data-driven gated (DDG) PET, the data selected for reconstruction is typically derived from the end-expiration (EE) phase of the breathing cycle, making this potential issue worse.

PURPOSE

The objective of this study is to develop a deformable image registration (DIR)-based respiratory motion model to improve the registration and quantification between misregistered FB CT and PET.

METHODS

Twenty-two whole-body 18 F-FDG PET/CT scans encompassing 48 lesions in misregistered regions were analyzed in this study. End-inspiration (EI) and EE PET data were derived from -10% to 15% and 30% to 80% of the breathing cycle, respectively. DIR was used to estimate a motion model from the EE to EI phase of the PET data. The model was then used to generate PET images at any phase of up to four times the amplitude of motion between EE and EI for correlation with the misregistered FB CT. Once a matched phase of the FB CT was determined, FB CT was deformed to a pseudo CT at the EE phase (DIR CT). DIR CT was compared with the ground truth DDG CT for AC and localization of the DDG PET.

RESULTS

Between DDG PET/FB CT and DDG PET/DIR CT, a significant increase in ∆%SUV was observed (p < 0.01), with median values elevating from 26.7% to 42.4%. This new method was most effective for lesions ≤3 cm proximal to the diaphragm (p < 0.001) but showed decreasing efficacy as the distance increased. When FB CT was severely misregistered with DDG PET (>3 cm), DDG PET/DIR CT outperformed DDG PET/FB CT alone (p < 0.05). Even when patients showed varied breathing patterns during the PET/CT scan, DDG PET/DIR CT still surpassed the efficiency of DDG PET/FB CT (p < 0.01). Though DDG PET/DIR CT couldn't match the performance of the DDG PET/CT ground truth (42.4% vs. 53.6%, p < 0.01), it reached 84% of its quantification, demonstrating good agreement and a strong overall correlation (regression coefficient of 0.94, p < 0.0001). In some cases, anatomical distortion and blurring, and misregistration error were observed in DIR CT, rendering it still unable to correct inaccurate localization near the boundaries of two organs.

CONCLUSIONS

Based on the motion model derived from gated PET data, DIR CT can significantly improve the quantification and localization of DDG PET. This approach can achieve a performance level of about 84% of the ground truth established by DDG PET/CT. These results show that self-gated PET and DIR CT may offer an alternative clinical solution to DDG PET and FB CT for quantification without the need for additional cine-CT imaging. DIR CT was at times inferior to DDG CT due to some distortion and blurring of anatomy and misregistration error.

Impact of irregular waveforms on data-driven respiratory gated PET/CT images processed using MotionFree algorithm

OBJECTIVES

MotionFree® (AMF) is a data-driven respiratory gating (DDG) algorithm for image processing that has recently been introduced into clinical practice. The present study aimed to verify the accuracy of respiratory waveform and the effects of normal and irregular respiratory motions using AMF with the DDG algorithm.

METHODS

We used a NEMA IEC body phantom comprising six spheres (37-, 28-, 22-, 17-, 13-, and 10 mm diameter) containing 18F. The sphere-to-background ratio was 4:1 (21.2 and 5.3 kBq/mL). We acquired PET/CT images from a stationary or moving phantom placed on a custom-designed motion platform. Respiratory motions were reproduced based on normal (sinusoidal or expiratory-paused waveforms) and irregular (changed amplitude or shifted baseline waveforms) movements. The "width" parameters in AMF were set at 10-60% and extracted data during the expiratory phases of each waveform. We verified the accuracy of the derived waveforms by comparing those input from the motion platform and output determined using AMF. Quantitative accuracy was evaluated as recovery coefficients (RCs), improvement rate, and %change that were calculated based on sphere diameter or width. We evaluated statistical differences in activity concentrations of each sphere between normal and irregular waveforms.

RESULTS

Respiratory waveforms derived from AMF were almost identical to the input waveforms on the motion platform. Although the RCs in each sphere for expiratory-paused and ideal stationary waveforms were almost identical, RCs except the expiratory-paused waveform were lower than those for the stationary waveform. The improvement rate decreased more for the irregular, than the normal waveforms with AMF in smaller spheres. The %change was improved by decreasing the width of waveforms with a shifted baseline. Activity concentrations significantly differed between normal waveforms and those with a shifted baseline in spheres < 28 mm.

CONCLUSIONS

The PET images using AMF with the DDG algorithm provided the precise waveform of respiratory motions and the improvement of quantitative accuracy in the four types of respiratory waveforms. The improvement rate was the most obvious in expiratory-paused waveforms, and the most subtle in those with a shifted baseline. Optimizing the width parameter in irregular waveform will benefit patients who breathe like the waveform with the shifted baseline.

Infection Imaging: Focus on New Tracers?

Infections account for relevant morbidity and mortality, especially if the cardiovascular system is affected. Clinical manifestations are often unspecific, resulting in a challenging diagnostic work-up. The use of molecular imaging methods, namely [18F]FDG PET and leukocyte scintigraphy, is increasingly recognized in recently published international guidelines. However, these 2 established methods focus on the host's immune response to the pathogen and are therefore virtually unable to differentiate infection from inflammation. Targeting the microorganism responsible for the infection directly with novel imaging agents is a promising strategy to overcome these limitations. In this review, we discuss clinically approved [18F]FDG PET with its advantages and limitations in cardiovascular infections, followed by new PET-based approaches for the detection of cardiovascular infections by bacteria-specific molecular imaging methods. A multitude of different targeting options has already been preclinically evaluated, but most still lack clinical translation. We give an overview not only on promising tracer candidates for noninvasive molecular imaging of infections but also on issues hampering clinical translation.

Unsupervised deep learning framework for data-driven gating in positron emission tomography

BACKGROUND

Physiological motion, such as respiratory motion, has become a limiting factor in the spatial resolution of positron emission tomography (PET) imaging as the resolution of PET detectors continue to improve. Motion-induced misregistration between PET and CT images can also cause attenuation correction artifacts. Respiratory gating can be used to freeze the motion and to reduce motion induced artifacts.

PURPOSE

In this study, we propose a robust data-driven approach using an unsupervised deep clustering network that employs an autoencoder (AE) to extract latent features for respiratory gating.

METHODS

We first divide list-mode PET data into short-time frames. The short-time frame images are reconstructed without attenuation, scatter, or randoms correction to avoid attenuation mismatch artifacts and to reduce image reconstruction time. The deep AE is then trained using reconstructed short-time frame images to extract latent features for respiratory gating. No additional data are required for the AE training. K-means clustering is subsequently used to perform respiratory gating based on the latent features extracted by the deep AE. The effectiveness of our proposed Deep Clustering method was evaluated using physical phantom and real patient datasets. The performance was compared against phase gating based on an external signal (External) and image based principal component analysis (PCA) with K-means clustering (Image PCA).

RESULTS

The proposed method produced gated images with higher contrast and sharper myocardium boundaries than those obtained using the External gating method and Image PCA. Quantitatively, the gated images generated by the proposed Deep Clustering method showed larger center of mass (COM) displacement and higher lesion contrast than those obtained using the other two methods.

CONCLUSIONS

The effectiveness of our proposed method was validated using physical phantom and real patient data. The results showed our proposed framework could provide superior gating than the conventional External method and Image PCA.

International EANM-SNMMI-ISMRM consensus recommendation for PET/MRI in oncology

PREAMBLE

The Society of Nuclear Medicine and Molecular Imaging (SNMMI) is an international scientific and professional organization founded in 1954 to promote the science, technology, and practical application of nuclear medicine. The European Association of Nuclear Medicine (EANM) is a professional non-profit medical association that facilitates communication worldwide between individuals pursuing clinical and research excellence in nuclear medicine. The EANM was founded in 1985. The merged International Society for Magnetic Resonance in Medicine (ISMRM) is an international, nonprofit, scientific association whose purpose is to promote communication, research, development, and applications in the field of magnetic resonance in medicine and biology and other related topics and to develop and provide channels and facilities for continuing education in the field.The ISMRM was founded in 1994 through the merger of the Society of Magnetic Resonance in Medicine and the Society of Magnetic Resonance Imaging. SNMMI, ISMRM, and EANM members are physicians, technologists, and scientists specializing in the research and practice of nuclear medicine and/or magnetic resonance imaging. The SNMMI, ISMRM, and EANM will periodically define new guidelines for nuclear medicine practice to help advance the science of nuclear medicine and/or magnetic resonance imaging and to improve the quality of service to patients throughout the world. Existing practice guidelines will be reviewed for revision or renewal, as appropriate, on their fifth anniversary or sooner, if indicated. Each practice guideline, representing a policy statement by the SNMMI/EANM/ISMRM, has undergone a thorough consensus process in which it has been subjected to extensive review. The SNMMI, ISMRM, and EANM recognize that the safe and effective use of diagnostic nuclear medicine imaging and magnetic resonance imaging requires specific training, skills, and techniques, as described in each document. Reproduction or modification of the published practice guideline by those entities not providing these services is not authorized. These guidelines are an educational tool designed to assist practitioners in providing appropriate care for patients. They are not inflexible rules or requirements of practice and are not intended, nor should they be used, to establish a legal standard of care. For these reasons and those set forth below, the SNMMI, the ISMRM, and the EANM caution against the use of these guidelines in litigation in which the clinical decisions of a practitioner are called into question. The ultimate judgment regarding the propriety of any specific procedure or course of action must be made by the physician or medical physicist in light of all the circumstances presented. Thus, there is no implication that an approach differing from the guidelines, standing alone, is below the standard of care. To the contrary, a conscientious practitioner may responsibly adopt a course of action different from that set forth in the guidelines when, in the reasonable judgment of the practitioner, such course of action is indicated by the condition of the patient, limitations of available resources, or advances in knowledge or technology subsequent to publication of the guidelines. The practice of medicine includes both the art and the science of the prevention, diagnosis, alleviation, and treatment of disease. The variety and complexity of human conditions make it impossible to always reach the most appropriate diagnosis or to predict with certainty a particular response to treatment. Therefore, it should be recognized that adherence to these guidelines will not ensure an accurate diagnosis or a successful outcome. All that should be expected is that the practitioner will follow a reasonable course of action based on current knowledge, available resources, and the needs of the patient to deliver effective and safe medical care. The sole purpose of these guidelines is to assist practitioners in achieving this objective.

Is Prone Position [18F]FDG PET/CT Useful in Reducing Respiratory Motion Artifacts in Evaluating Hepatic Lesions?

Prone position is useful in reducing respiratory motion artifacts in lung nodules on 2-Deoxy-2-[18F] fluoro-D-glucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT). However, whether prone position PET/CT is useful in evaluating hepatic lesions is unknown. Thirty-five hepatic lesions from 20 consecutive patients were evaluated. The maximum standardized uptake value (SUVmax) and metabolic tumor volume (MTV) of both standard supine position PET/CT and additional prone position PET/CT were evaluated. No significant difference in SUVmax (4.41 ± 2.0 vs. 4.23 ± 1.83; p = 0.240) and MTV (5.83 ± 6.69 vs. 5.95 ± 6.24; p = 0.672) was observed between supine position PET/CT and prone position PET/CT. However, SUVmax changes in prone position PET/CT varied compared with those in supine position PET/CT (median, -4%; range: -30-71%). Prone position PET/CT was helpful when [18F]FDG uptake of the hepatic lesions was located outside the liver on supine position PET/CT (n = 4, SUVmax change: median 15%; range: 7-71%) and there was more severe blurring on supine position PET/CT (n = 6, SUVmax change: median 11%; range: -3-32%). Unlike in lung nodules, prone position PET/CT is not always useful in evaluating hepatic lesions, but it may be helpful in individual cases such as hepatic dome lesions.

Evaluation of Data-Driven Respiration Gating in Continuous Bed Motion in Lung Lesions

Respiration gating is used in PET to prevent image quality degradation due to respiratory effects. In this study, we evaluated a type of data-driven respiration gating for continuous bed motion, OncoFreeze AI, which was implemented to improve image quality and the accuracy of semiquantitative uptake values affected by respiratory motion. Methods: ¹⁸F-FDG PET/CT was performed on 32 patients with lung lesions. Two types of respiration-gated images (OncoFreeze AI with data-driven respiration gating, device-based amplitude-based OncoFreeze with elastic motion compensation) and ungated images (static) were reconstructed. For each image, we calculated SUV and metabolic tumor volume (MTV). The improvement rate (IR) from respiration gating and the contrast-to-noise ratio (CNR), which indicates the improvement in image noise, were also calculated for these indices. IR was also calculated for the upper and lower lobes of the lung. As OncoFreeze AI assumes the presence of respiratory motion, we examined quantitative accuracy in regions where respiratory motion was not present using a ⁶⁸Ge cylinder phantom with known quantitative accuracy. Results: OncoFreeze and OncoFreeze AI showed similar values, with a significant increase in SUV and decrease in MTV compared with static reconstruction. OncoFreeze and OncoFreeze AI also showed similar values for IR and CNR. OncoFreeze AI increased SUV_max by an average of 18% and decreased MTV by an average of 25% compared with static reconstruction. From the IR results, both OncoFreeze and OncoFreeze AI showed a greater IR from static reconstruction in the lower lobe than in the upper lobe. OncoFreeze and OncoFreeze AI increased CNR by 17.9% and 18.0%, respectively, compared with static reconstruction. The quantitative accuracy of the ⁶⁸Ge phantom, assuming a region of no respiratory motion, was almost equal for the static reconstruction and OncoFreeze AI. Conclusion: OncoFreeze AI improved the influence of respiratory motion in the assessment of lung lesion uptake to a level comparable to that of the previously launched OncoFreeze. OncoFreeze AI provides more accurate imaging with significantly larger SUVs and smaller MTVs than static reconstruction.

Reproducibility of lung cancer radiomics features extracted from data-driven respiratory gating and free-breathing flow imaging in [18F]-FDG PET/CT

BACKGROUND

Quality and reproducibility of radiomics studies are essential requirements for the standardisation of radiomics models. As recent data-driven respiratory gating (DDG) [18F]-FDG has shown superior diagnostic performance in lung cancer, we evaluated the impact of DDG on the reproducibility of radiomics features derived from [18F]-FDG PET/CT in comparison to free-breathing flow (FB) imaging.

METHODS

Twenty four lung nodules from 20 patients were delineated. Radiomics features were derived on FB flow PET/CT and on the corresponding DDG reconstruction using the QuantImage v2 platform. Lin's concordance factor (Cb) and the mean difference percentage (DIFF%) were calculated for each radiomics feature using the delineated nodules which were also classified by anatomical localisation and volume. Non-reproducible radiomics features were defined as having a bias correction factor Cb  < 0.8 and/or a mean difference percentage DIFF% > 10.

RESULTS

In total 141 features were computed on each concordance analysis, 10 of which were non-reproducible on all pulmonary lesions. Those were first-order features from Laplacian of Gaussian (LoG)-filtered images (sigma = 1 mm): Energy, Kurtosis, Minimum, Range, Root Mean Squared, Skewness and Variance; Texture features from Gray Level Cooccurence Matrix (GLCM): Cluster Prominence and Difference Variance; First-order Standardised Uptake Value (SUV) feature: Kurtosis. Pulmonary lesions located in the superior lobes had only stable radiomics features, the ones from the lower parts had 25 non-reproducible radiomics features. Pulmonary lesions with a greater size (defined as long axis length > median) showed a higher reproducibility (9 non-reproducible features) than smaller ones (20 non-reproducible features).

CONCLUSION

Calculated on all pulmonary lesions, 131 out of 141 radiomics features can be used interchangeably between DDG and FB PET/CT acquisitions. Radiomics features derived from pulmonary lesions located inferior to the superior lobes are subject to greater variability as well as pulmonary lesions of smaller size.

Respiratory motion correction in F-18-FDG PET/CT impacts lymph node assessment in lung cancer patients

BACKGROUNDS

Elastic motion correction in PET has been shown to increase image quality and quantitative measurements of PET datasets affected by respiratory motion. However, little is known on the impact of respiratory motion correction on clinical image evaluation in oncologic PET. This study evaluated the impact of motion correction on expert readers' lymph node assessment of lung cancer patients.

METHODS

Forty-three patients undergoing F-18-FDG PET/CT for the staging of suspected lung cancer were included. Three different PET reconstructions were investigated: non-motion-corrected ("static"), belt gating-based motion-corrected ("BG-MC") and data-driven gating-based motion-corrected ("DDG-MC"). Assessment was conducted independently by two nuclear medicine specialists blinded to the reconstruction method on a six-point scale [Formula: see text] ranging from "certainly negative" (1) to "certainly positive" (6). Differences in [Formula: see text] between reconstruction methods, accounting for variation caused by readers, were assessed by nonparametric regression analysis of longitudinal data. From [Formula: see text], a dichotomous score for N1, N2, and N3 ("negative," "positive") and a subjective certainty score were derived. SUV and metabolic tumor volumes (MTV) were compared between reconstruction methods.

RESULTS

BG-MC resulted in higher scores for N1 compared to static (p = 0.001), whereas DDG-MC resulted in higher scores for N2 compared to static (p = 0.016). Motion correction resulted in the migration of N1 from tumor free to metastatic on the dichotomized score, consensually for both readers, in 3/43 cases and in 2 cases for N2. SUV was significantly higher for motion-corrected PET, while MTV was significantly lower (all p < 0.003). No significant differences in the certainty scores were noted.

CONCLUSIONS

PET motion correction resulted in significantly higher lymph node assessment scores of expert readers. Significant effects on quantitative PET parameters were seen; however, subjective reader certainty was not improved.

Phantom-based acquisition time and image reconstruction parameter optimisation for oncologic FDG PET/CT examinations using a digital system

Background

New-generation silicon-photomultiplier (SiPM)-based PET/CT systems exhibit an improved lesion detectability and image quality due to a higher detector sensitivity. Consequently, the acquisition time can be reduced while maintaining diagnostic quality. The aim of this study was to determine the lowest ¹⁸F-FDG PET acquisition time without loss of diagnostic information and to optimise image reconstruction parameters (image reconstruction algorithm, number of iterations, voxel size, Gaussian filter) by phantom imaging. Moreover, patient data are evaluated to confirm the phantom results.

Methods

Three phantoms were used: a soft-tissue tumour phantom, a bone-lung tumour phantom, and a resolution phantom. Phantom conditions (lesion sizes from 6.5 mm to 28.8 mm in diameter, lesion activity concentration of 15 kBq/mL, and signal-to-background ratio of 5:1) were derived from patient data. PET data were acquired on an SiPM-based Biograph Vision PET/CT system for 10 min in list-mode format and resampled into time frames from 30 to 300 s in 30-s increments to simulate different acquisition times. Different image reconstructions with varying iterations, voxel sizes, and Gaussian filters were probed. Contrast-to-noise-ratio (CNR), maximum, and peak signal were evaluated using the 10-min acquisition time image as reference. A threshold CNR value ≥ 5 and a maximum (peak) deviation of ± 20% were considered acceptable. 20 patient data sets were evaluated regarding lesion quantification as well as agreement and correlation between reduced and full acquisition time standard uptake values (assessed by Pearson correlation coefficient, intraclass correlation coefficient, Bland–Altman analyses, and Krippendorff’s alpha).

Results

An acquisition time of 60 s per bed position yielded acceptable detectability and quantification results for clinically relevant phantom lesions ≥ 9.7 mm in diameter using OSEM-TOF or OSEM-TOF+PSF image reconstruction, a 4-mm Gaussian filter, and a 1.65 × 1.65 x 2.00-mm³ or 3.30 × 3.30 x 3.00-mm³ voxel size. Correlation and agreement of patient lesion quantification between full and reduced acquisition times were excellent.

Conclusion

A threefold reduction in acquisition time is possible. Patients might benefit from more comfortable examinations or reduced radiation exposure, if instead of the acquisition time the applied activity is reduced.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09993-4.

Impact of low injected activity on data driven respiratory gating for PET/CT imaging with continuous bed motion

Data driven respiratory gating (DDG) in positron emission tomography (PET) imaging extracts respiratory waveforms from the acquired PET data obviating the need for dedicated external devices. DDG performance, however, degrades with decreasing detected number of coincidence counts. In this paper, we assess the clinical impact of reducing injected activity on a new DDG algorithm designed for PET data acquired with continuous bed motion (CBM_DDG) by evaluating CBM_DDG waveforms, tumor quantification, and physician's perception of motion blur in resultant images. Forty patients were imaged on a Siemens mCT scanner in CBM mode. Reduced injected activity was simulated by generating list mode datasets with 50% and 25% of the original data (100%). CBM_DDG waveforms were compared to that of the original data over the range between the aortic arch and the center of the right kidney using the Pearson correlation coefficient (PCC). Tumor quantification was assessed by comparing the maximum standardized uptake value (SUVmax) and peak SUV (SUVpeak) of reconstructed images from the various list mode datasets using elastic motion deblurring (EMDB) reconstruction. Perceived motion blur was assessed by three radiologists of one lesion per patient on a continuous scale from no motion blur (0) to significant motion blur (3). The mean PCC of the 50% and 25% dataset waveforms was 0.74 ± 0.18 and 0.59 ± 0.25, respectively. In comparison to the 100% datasets, the mean SUVmax increased by 2.25% (p = 0.11) for the 50% datasets and by 3.91% (p = 0.16) for the 25% datasets, while SUVpeak changes were within ±0.25%. Radiologist evaluations of motion blur showed negligible changes with average values of 0.21, 0.3, and 0.28 for the 100%, 50%, and 25% datasets. Decreased injected activities degrades the resultant CBM_DDG respiratory waveforms; however this decrease has minimal impact on quantification and perceived image motion blur.

Impact of acquisition time and misregistration with CT on data-driven gated PET

Objective. Data-driven gating (DDG) can address patient motion issues and enhance PET quantification but suffers from increased image noise from utilization of <100% of PET data. Misregistration between DDG-PET and CT may also occur, altering the potential benefits of gating. Here, the effects of PET acquisition time and CT misregistration were assessed with a combined DDG-PET/DDG-CT technique.Approach. In the primary PET bed with lesions of interest and likely respiratory motion effects, PET acquisition time was extended to 12 min and a low-dose cine CT was acquired to enable DDG-CT. Retrospective reconstructions were created for both non-gated (NG) and DDG-PET using 30 s to 12 min of PET data. Both the standard helical CT and DDG-CT were used for attenuation correction of DDG-PET data. SUVmax, SUVpeak, and CNR were compared for 45 lesions in the liver and lung from 27 cases.Main results. For both NG-PET (p= 0.0041) and DDG-PET (p= 0.0028), only the 30 s acquisition time showed clear SUVmaxbias relative to the 3 min clinical standard. SUVpeakshowed no bias at any change in acquisition time. DDG-PET alone increased SUVmaxby 15 ± 20% (p< 0.0001), then was increased further by an additional 15 ± 29% (p= 0.0007) with DDG-PET/CT. Both 3 min and 6 min DDG-PET had lesion CNR statistically equivalent to 3 min NG-PET, but then increased at 12 min by 28 ± 48% (p= 0.0022). DDG-PET/CT at 6 min had comparable counts to 3 min NG-PET, but significantly increased CNR by 39 ± 46% (p< 0.0001).Significance. 50% counts DDG-PET did not lead to inaccurate or biased SUV-increased SUV resulted from gating. Improved registration from DDG-CT was equally as important as motion correction with DDG-PET for increasing SUV in DDG-PET/CT. Lesion detectability could be significantly improved when DDG-PET used equivalent counts to NG-PET, but only when combined with DDG-CT in DDG-PET/CT.

Clinical feasibility and impact of data-driven respiratory motion compensation studied in 200 whole-body 18F-FDG PET/CT scans

Background

This study examines the clinical feasibility and impact of implementing a fully automated whole-body PET protocol with data-driven respiratory gating in patients with a broad range of oncological and non-oncological pathologies 592 FDG PET/CT patients were prospectively included. 200 patients with lesions in the torso were selected for further analysis, and ungated (UG), belt gated (BG) and data-driven gating (DDG) images were reconstructed. All images were reconstructed using the same data and without prolonged acquisition time for gated images. Images were quantitatively analysed for lesion uptake and metabolic volume, complemented by a qualitative analysis of visual lesion detection. In addition, the impact of gating on treatment response evaluation was evaluated in 23 patients with malignant lymphoma.

Results

Placement of the belt needed for BG was associated with problems in 27% of the BG scans, whereas no issues were reported using DDG imaging. For lesion quantification, DDG and BG images had significantly greater SUV values and smaller volumes than UG. The physicians reported notable image blurring in 44% of the UG images that was problematic for clinical evaluation in 4.5% of cases.

Conclusion

Respiratory motion compensation using DDG is readily integrated into clinical routine and produce images with more accurate and significantly greater SUV values and smaller metabolic volumes. In our broad cohort of patients, the physicians overwhelmingly preferred gated over ungated images, with a slight preference for DDG images. However, even in patients with malignant disease in the torso, no additional diagnostic information was obtained by the gated images that could not be derived from the ungated images.

Data-driven gated (DDG) CT: An automated respiratory gating method to enable DDG PET/CT

BACKGROUND

The accuracy of PET quantification and localization can be compromised if a misregistered CT is used for attenuation correction (AC) in PET/CT. As data-driven gating (DDG) continues to grow in clinical use, these issues are becoming more relevant with respect to solutions for gated CT.

PURPOSE

In this work, a new automated data-driven gated (DDG) CT method was developed to provide average CT and DDG CT for AC of PET and DDG PET, respectively.

METHODS

An automatic DDG CT was developed to provide the end-expiratory (EE) and end-inspiratory (EI) phases of images from low-dose cine CT images, with all phases being averaged to generate an average CT. The respiratory phases of EE and EI were determined according to lung region Hounsfield unit (HU) values and body outline contours. The average CT was used for AC of baseline PET and DDG CT at EE phase was used for AC of DDG PET at the quiescent or EE phase. The EI and EE phases obtained with DDG CT were used for assessing the magnitude of respiratory motion. The proposed DDG CT was compared to two commercial CT gating methods: 1) 4D CT (external device based) and 2) D4D CT (DDG based) in 38 patient data sets with respect to respiratory phase image selection, lung HU, lung volume, and image artifacts. In a separate set of twenty consecutive PET/CT studies containing a mix of ¹⁸ F-FDG, ⁶⁸ Ga-Dotatate, and ⁶⁴ Cu-Dotatate scans, the proposed DDG CT was compared with D4D CT for impacts on registration and quantification in DDG PET/CT.

RESULTS

In the EE phase, the images selected by DDG CT and 4D CT were identical 62.5±21.6% of the time, while DDG CT and D4D CT were 6.5±9.7%, and 4D CT and D4D CT were 8.6±12.2%. These differences in EE phase image selection were significant (p<0.0001). In the EI phase, the images selected by DDG CT and 4D CT were identical 68.2±18.9% of the time, DDG CT and D4D CT were 63.9±18.8%, and 4D CT and D4D CT were 61.2±19.8%. These differences were not significant. The mean lung HU and volumes were not statistically different (p > 0.1) among the three methods. In some studies, DDG CT was better than D4D or 4D CT in appropriate selection of the EE and EI phases, and D4D CT was found to reverse the EE and EI phases or not select the correct images by visual inspection. A statistically significant improvement of DDG CT over D4D CT for AC of DDG PET was also demonstrated with PET quantification analysis. When irregular breath cycles were present in the cine CT, DDG CT could be used to replace average CT for improved AC of baseline PET.

CONCLUSION

A new automatic DDG CT was developed to tackle the issues of misregistration and tumor motion in PET/CT imaging. DDG CT was significantly more consistent than D4D CT in selecting the EE phase images as the clinical standard of 4D CT. When compared to both commercial gated CT methods of 4D CT and D4D CT, DDG CT appeared to be more robust in the lower lung and upper diaphragm regions where misregistration and tumor motion often occur. DDG CT offered improved AC for DDG PET relative to D4D CT. In cases with irregular respiratory motion, DDG CT improved AC over average CT for baseline PET. The new DDG CT provides the benefits of 4D CT without the need for external device gating. This article is protected by copyright. All rights reserved.

Evaluating two respiratory correction methods for abdominal PET/MRI imaging

Background

To evaluate two respiratory correction methods for abdominal PET/MRI images and further to analyse the effects on standard uptake values (SUVs) of respiratory motion correction, 17 patients with 25 abdominal lesions on ¹⁸F-FDG PET/CT were scanned with PET/MRI. PET images were reconstructed using end-expiratory respiratory gating and multi-bin respiratory gating. Meanwhile, full data and the first 3 min and 20 s of data acquired both without respiratory gating were reconstructed for evaluation. Five parameters, including the SUV_max and SUV_mean in the lesions, the SUV_mean and standard deviation (SD) in the background, and the signal-to-noise ratio (SNR), were calculated and used for statistical comparisons. The differences in multi-bin respiratory gating and reconstruction of full data, relative to the reconstruction of the first 3 min and 20 s of data acquired, were calculated.

Results

Compared with PET/CT, the longer scanning time of abdominal PET/MRI makes respiratory motion correction necessary. The multi-bin respiratory gating correction could reduce the PET image blur and increase the SUV_max (11.98%) and SUV_mean (13.12%) of the lesions significantly (p = 0.00), which was much more effective than end-expiratory respiratory gating for abdominal PET/MRI. The added value of SUV_max caused by respiratory motion correction has no significant difference compared with that caused by count loss with the correction (p = 0.39), which was rarely reported by previous studies.

Conclusion

Based on the current parameters, the method of multi-bin respiratory gating was more effective for respiratory motion correction in abdominal PET/MRI in comparisons with the method of end-respiratory gating. However, the increased noise in gated images, due to the fact that PET data get discarded, is partly responsible for the increase in SUV_max.

PET respiratory motion correction: quo vadis?

Positron emission tomography (PET) respiratory motion correction has been a subject of great interest for the last twenty years, prompted mainly by the development of multimodality imaging devices such as PET/computed tomography (CT) and PET/magnetic resonance imaging (MRI). PET respiratory motion correction involves a number of steps including acquisition synchronization, motion estimation and finally motion correction. The synchronization steps include the use of different external device systems or data driven approaches which have been gaining ground over the last few years. Patient specific or generic motion models using the respiratory synchronized datasets can be subsequently derived and used for correction either in the image space or within the image reconstruction process. Similar overall approaches can be considered and have been proposed for both PET/CT and PET/MRI devices. Certain variations in the case of PET/MRI include the use of MRI specific sequences for the registration of respiratory motion information. The proposed review includes a comprehensive coverage of all these areas of development in field of PET respiratory motion for different multimodality imaging devices and approaches in terms of synchronization, estimation and subsequent motion correction. Finally, a section on perspectives including the potential clinical usage of these approaches is included.

Advances in PET-CT technology: An update

This article reviews the current evolution and future directions in PET-CT technology focusing on three areas: time of flight, image reconstruction, and data-driven gating. Image reconstruction is considered with advances in point spread function modelling, Bayesian penalised likelihood reconstruction, and artificial intelligence approaches. Data-driven gating is examined with reference to respiratory motion, cardiac motion, and head motion. For each of these technological advancements, theory will be briefly discussed, benefits of their use in routine practice will be detailed and potential future developments will be discussed. Representative clinical cases will be presented, demonstrating the huge opportunities given to the PET community by hardware and software advances in PET technology when it comes to lesion detection, disease characterization, accurate quantitation and quicker scans. Through this review, hospitals are encouraged to embrace, evaluate and appropriately implement the wide range of new PET technologies that are available now or in the near future, for the improvement of patient care.

Clinical evaluation of data-driven respiratory gating for PET/CT in an oncological cohort of 149 patients: impact on image quality and patient management

OBJECTIVES

To evaluate the impact of fully automatic motion correction by data-driven respiratory gating (DDG) on positron emission tomography (PET) image quality, lesion detection and patient management.

MATERIALS AND METHODS

A total of 149 patients undergoing PET/CT for cancer (re-)staging were retrospectively included. Patients underwent a PET/CT on a digital detector scanner and for every patient a PET data set where DDG was enabled (PET_DDG) and as well as where DDG was not enabled (PET_nonDDG) was reconstructed. All PET data sets were evaluated by two readers which rated the general image quality, motion effects and organ contours. Further, both readers reviewed all scans on a case-by-case basis and evaluated the impact of PET_DDG on additional apparent lesion, change of report, and change of management.

RESULTS

In 85% (n = 126) of the patients, at least one bed position was acquired using DDG, resulting in mean scan time increase of 4:37 min per patient in the whole study cohort (n = 149). General image quality was not rated differently for PET_nonDDG and PET_DDG images (p = 1.000) while motion effects (i.e. indicating general blurring) was rated significantly lower in PET_DDG images and organ contours, including liver and spleen, were rated significantly sharper using PET_DDG as compared to PET_nonDDG (all p < 0.001). In 27% of patients, PET_DDG resulted in a change of the report and in a total of 12 cases (8%), PET_DDG resulted in a change of further clinical management.

CONCLUSION

Deviceless DDG provided reliable fully automatic motion correction in clinical routine and increased lesion detectability and changed management in a considerable number of patients.

ADVANCES IN KNOWLEDGE

DDG enables PET/CT with respiratory gating to be used routinely in clinical practice without external gating equipment needed.

Data-driven gated PET/CT: implications for lesion segmentation and quantitation

Background

Data-driven gating (DDG) can improve PET quantitation and alleviate many issues with patient motion. However, misregistration between DDG-PET and CT may occur due to the distinct temporal resolutions of PET and CT and can be mitigated by DDG-CT. Here, the effects of misregistration and respiratory motion on PET quantitation and lesion segmentation were assessed with a new DDG-PET/CT method.

Methods

A low-dose cine-CT was acquired in misregistered regions to enable both average CT (ACT) and DDG-CT. The following were compared: (1) baseline PET/CT, (2) PET/ACT (attenuation correction, AC = ACT), (3) DDG-PET (AC = helical CT), and (4) DDG-PET/CT (AC = DDG-CT). For DDG-PET, end-expiration (EE) data were derived from 50% of the total PET data at 30% from end-inspiration. For DDG-CT, EE phase CT data were extracted from cine-CT data by lung Hounsfield unit (HU) value and body contour. A total of 91 lesions from 16 consecutive patients were assessed for changes in standard uptake value (SUV), lesion glycolysis (LG), lesion volume, centroid-to-centroid distance (CCD), and DICE coefficients.

Results

Relative to baseline PET/CT, median changes in SUV_max ± σ for all 91 lesions were 20 ± 43%, 26 ± 23%, and 66 ± 66%, respectively, for PET/ACT, DDG-PET, and DDG-PET/CT. Median changes in lesion volume were 0 ± 58%, − 36 ± 26%, and − 26 ± 40%. LG for individual lesions increased for PET/ACT and decreased for DDG-PET, but was not different for DDG-PET/CT. Changes in mean HU from baseline PET/CT were dramatic for most lesions in both PET/ACT and DDG-PET/CT, especially for lesions with mean HU < 0 at baseline. CCD and DICE were both affected more by motion correction with DDG-PET than improved registration with ACT or DDG-CT.

Conclusion

As misregistration becomes more prominent, the impact of motion correction with DDG-PET is diminished. The potential benefits of DDG-PET toward accurate lesion segmentation and quantitation could only be fully realized when combined with DDG-CT. These results impress upon the necessity of ensuring both misregistration and motion correction are accounted for together to optimize the clinical utility of PET/CT.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40658-021-00411-5.

An Extremely Rare, Atypical and Genetically-undetermined Form of Osteopetrosis

INTRODUCTION

Osteopetrosis is an uncommon skeletal disorder characterized by generalized sclerosis of bones due to defective osteoclast function. A wide variation in clinical severity of the disease has been observed. Radiographic features and genetic testing are commonly used to diagnose the condition.

CASE PRESENTATION

In the present study, we present a case of an extremely rare, atypical and genetically- undetermined form of Osteopetrosis.

CONCLUSION

This patient had some clinical and radiological features of craniometaphyseal dysplasia along with atypical radiological signs of osteopetrosis.

PET/CT limitations and pitfalls in urogenital cancers

Hybrid FDG PET/CT plays a vital role in oncologic imaging and has been widely adopted for the staging and restaging of a variety of malignancies. Its diagnostic value in urogenital malignancies is less well-known, not at least because of the variable FDG avidity of these tumor entities, the sites of these tumors, and technical challenges associated with sequential imaging of CT and PET. PET/CT interpretation thus can be especially challenging and is associated with many pitfalls, which can lead to both false-positive and false-negative diagnoses as well as incorrect assessment of metabolic change following therapy. Currently, FDG PET/CT is not the standard of care for the initial diagnosis or staging of early-stage or low-risk urogenital cancers; however, it can help evaluate distant metastatic disease, response to therapy, and disease recurrence in high-risk patients. Knowledge of imaging features of tumor metabolic avidity and pitfalls is essential for accurate interpretation.

Prone position [18F]FDG PET/CT to reduce respiratory motion artefacts in the evaluation of lung nodules

OBJECTIVES

2-Deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]FDG) positron-emission tomography/computed tomography (PET/CT) is widely used to evaluate lung nodules, although respiratory motion artefacts may occur. We investigated the value of prone position PET/CT (pPET/CT) in lung nodule evaluation compared with standard supine position PET/CT (sPET/CT).

METHODS

We retrospectively reviewed 28 consecutive patients (20 men; age, 65.6 ± 12.1 years) with a lung nodule (size, 16.8 ± 5.5 mm) located below the sub-carinal level who underwent [¹⁸F]FDG PET/CT in a standard supine position and additional prone position. The maximum standardised uptake value (SUV_max), metabolic tumour volume (MTV), difference of diaphragm position between PET and CT (DDP), Dice's similarity coefficient (DSC) and occurrence of mis-registration were analysed. The [¹⁸F]FDG uptake of 20 biopsy-confirmed (15 malignant) nodules was evaluated visually.

RESULTS

pPET/CT yielded a significantly higher SUV_max, lower MTV and shorter DDP than with sPET/CT (p = 0.043, 0.007 and 0.021, respectively). Mis-registration occurred in 53.6% of cases in sPET/CT and in 28.6% of cases in pPET/CT (p = 0.092). Among the 15 patients with mis-registration in sPET/CT, 10 patients (66.7%) did not show mis-registration in pPET/CT. DSC was higher in pPET/CT than in sPET/CT in 18 out of 28 patients (64.3%). In visual analysis, malignant nodules exhibited a higher [¹⁸F]FDG uptake positivity than benign nodules in pPET/CT (93.3% vs. 40.0%, p = 0.032) but not in sPET/CT (80.0% vs. 40.0%, p = 0.131).

CONCLUSIONS

pPET/CT reduces respiratory motion artefact and enables more-precise measurements of PET parameters.

KEY POINTS

• In prone position PET/CT, the decrease in the blurring effect caused by reduced respiratory motion resulted in a higher SUV_max and lower MTV in lung nodules than that with supine position PET/CT. • Prone position PET/CT was useful to interpret correctly malignant lung nodules as being positive in individual cases that had a negative result in supine position PET/CT.

Quantitative comparison of data-driven gating and external hardware gating for 18F-FDG PET-MRI in patients with esophageal tumors

Background

Respiratory motion during PET imaging reduces image quality. Data-driven gating (DDG) based on principal component analysis (PCA) can be used to identify respiratory signals. The use of DDG, without need for external devices, would greatly increase the feasibility of using respiratory gating in a routine clinical setting. The objective of this study was to evaluate data-driven gating in relation to external hardware gating and regular static image acquisition on PET-MRI data with respect to SUV_max and lesion volumes.

Methods

Sixteen patients with esophageal or gastroesophageal cancer (Siewert I and II) underwent a 6-min PET scan on a Signa PET-MRI system (GE Healthcare) 1.5–2 h after injection of 4 MBq/kg ¹⁸F-FDG. External hardware gating was done using a respiratory bellow device, and DDG was performed using MotionFree (GE Healthcare). The DDG raw data files and the external hardware-gating raw files were created on a Matlab-based toolbox from the whole 6-min scan LIST-file. For comparison, two 3-min static raw files were created for each patient. Images were reconstructed using TF-OSEM with resolution recovery with 2 iterations, 28 subsets, and 3-mm post filter. SUV_max and lesion volume were measured in all visible lesions, and noise level was measured in the liver. Paired t-test, linear regression, Pearson correlation, and Bland-Altman analysis were used to investigate difference, correlation, and agreement between the methods.

Results

A total number of 30 lesions were included in the study. No significant differences between DDG and external hardware-gating SUV_max or lesion volumes were found, but the noise level was significantly reduced in the DDG images. Both DDG and external hardware gating demonstrated significantly higher SUV_max (9.4% for DDG, 10.3% for external hardware gating) and smaller lesion volume (− 5.4% for DDG, − 6.6% for external gating) in comparison with non-gated static images.

Conclusions

Data-driven gating with MotionFree for PET-MRI performed similar to external device gating for esophageal lesions with respect to SUV_max and lesion volume. Both gating methods significantly increased the SUV_max and reduced the lesion volume in comparison with non-gated static acquisition. DDG resulted in reduced image noise compared to external device gating and static images.

Emerging role of 18F-FDG PET/CT in Castleman disease: a review

Castleman disease (CD) describes a group of rare hematologic conditions involving lymphadenopathy with characteristic histopathology and a spectrum of clinical abnormalities. CD is divided into localized or unicentric CD (UCD) and multicentric CD (MCD) by imaging. MCD is further divided based on etiological driver into human herpesvirus-8-associated MCD, POEMS-associated MCD, and idiopathic MCD. There is notable heterogeneity across MCD, but increased level of pro-inflammatory cytokines, particularly interleukin-6, is an established disease driver in a portion of patients. FDG-PET/CT can help determine UCD versus MCD, evaluate for neoplastic conditions that can mimic MCD clinico-pathologically, and monitor therapy responses. CD requires more robust characterization, earlier diagnosis, and an accurate tool for both monitoring and treatment response evaluation; FDG-PET/CT is particularly suited for this. Moving forward, future prospective studies should further characterize the use of FDG-PET/CT in CD and specifically explore the utility of global disease assessment and dual time point imaging.

Trial registration ClinicalTrials.gov, NCT02817997, Registered 29 June 2016, https://clinicaltrials.gov/ct2/show/NCT02817997

Hepatic alveolar echinococcosis: correlation between computed tomography morphology and inflammatory activity in positron emission tomography

Positron emission tomography-computed tomography (PET-CT) with 18F-fluorodesoxyglucose (FDG) is the imaging modality of choice for assessing inflammation surrounding hepatic alveolar echinococcosis (AE) lesions. This study is the first to evaluate FDG uptake in hepatic AE (n = 51) based on the standardized uptake value (SUV) and to correlate the SUVs with primary morphology and calcification patterns, based on the Echinococcus multilocularis Ulm Classification for Computed-Tomography (EMUC-CT). Our results show that the SUVs were increased for lesions with EMUC-CT types I-IV primary morphology, compared to the surrounding healthy liver tissue (SUV = 2.5 ± 0.4; p < 0.05). Type IV lesions included, by far, the highest number of PET-negative lesions. A comparison of lesions with different primary morphologies showed clear differences. The highest SUVs were found for types I and III, and the lowest was found for type IV. Type IV lesions (SUV, 3.8 ± 1.5) showed significantly lower uptake compared to type I (SUV, 6.9 ± 3.5; p = 0.030) and type III (SUV, 7.4 ± 3.9; p = 0.031) lesions. For type II lesions, the results showed only a statistical trend (SUV, 6.1 ± 3.1; p = 0.073). Due to the small number of cases, an evaluation of type V (n = 1) lesions was not possible. The different SUVs of lesions with different primary morphologies, particularly the lower FDG uptake observed in type IV lesions, suggested that these SUVs might reflect different stages of the disease.

Data-Driven Respiratory Gating Outperforms Device-Based Gating for Clinical 18F-FDG PET/CT

A data-driven method for respiratory gating in PET has recently been commercially developed. We sought to compare the performance of the algorithm with an external, device-based system for oncologic ¹⁸F-FDG PET/CT imaging. Methods: In total, 144 whole-body ¹⁸F-FDG PET/CT examinations were acquired, with a respiratory gating waveform recorded by an external, device-based respiratory gating system. In each examination, 2 of the bed positions covering the liver and lung bases were acquired with a duration of 6 min. Quiescent-period gating retaining approximately 50% of coincidences was then able to produce images with an effective duration of 3 min for these 2 bed positions, matching the other bed positions. For each examination, 4 reconstructions were performed and compared: data-driven gating (DDG) (we use the term DDG-retro to distinguish that we did not use the real-time R-threshold-based application of DDG that is available within the manufacturer's product), external device-based gating (real-time position management (RPM)-gated), no gating but using only the first 3 min of data (ungated-matched), and no gating retaining all coincidences (ungated-full). Lesions in the images were quantified and image quality scored by a radiologist who was masked to the method of data processing. Results: Compared with the other reconstruction options, DDG-retro increased the SUV_max and decreased the threshold-defined lesion volume. Compared with RPM-gated, DDG-retro gave an average increase in SUV_max of 0.66 ± 0.1 g/mL (n = 87, P < 0.0005). Although the results from the masked image evaluation were most commonly equivalent, DDG-retro was preferred over RPM-gated in 13% of examinations, whereas the opposite occurred in just 2% of examinations. This was a significant preference for DDG-retro (P = 0.008, n = 121). Liver lesions were identified in 23 examinations. Considering this subset of data, DDG-retro was ranked superior to ungated-full in 6 of 23 (26%) cases. Gated reconstruction using the external device failed in 16% of examinations, whereas DDG-retro always provided a clinically acceptable image. Conclusion: In this clinical evaluation, DDG-retro provided performance superior to that of the external device-based system. For most examinations the performance was equivalent, but DDG-retro had superior performance in 13% of examinations, leading to a significant preference overall.