Evaluation of principal component analysis-based data-driven respiratory gating for positron emission tomography

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.

Reproducibility of the principal component analysis (PCA)-based data-driven respiratory gating on texture features in non-small cell lung cancer patients with 18 F-FDG PET/CT

OBJECTIVE

Texture analysis is one of the lung cancer countermeasures in the field of radiomics. Even though image quality affects texture features, the reproducibility of principal component analysis (PCA)-based data-driven respiratory gating (DDG) on texture features remains poorly understood. Hence, this study aimed to clarify the reproducibility of PCA-based DDG on texture features in non-small cell lung cancer (NSCLC) patients with ¹⁸ F-Fluorodeoxyglucose (¹⁸ F-FDG) Positron emission tomography/computed tomography (PET/CT).

METHODS

Twenty patients with NSCLC who underwent ¹⁸ F-FDG PET/CT in routine clinical practice were retrospectively analyzed. Each patient's PET data were reconstructed in two PET groups of no gating (NG-PET) and PCA-based DDG gating (DDG-PET). Forty-six image features were analyzed using LIFEx software. Reproducibility was evaluated using Lin's concordance correlation coefficient ( ρ c ${\rho _c}$ ) and percentage difference (%Diff). Non-reproducibility was defined as having unacceptable strength ( ρ c $({\rho _c}$  < 0.8) and a %Diff of >10%. NG-PET and DDG-PET were compared using the Wilcoxon signed-rank test.

RESULTS

A total of 3/46 (6.5%) image features had unacceptable strength, and 9/46 (19.6%) image features had a %Diff of >10%. Significant differences between the NG-PET and DDG-PET groups were confirmed in only 4/46 (8.7%) of the high %Diff image features.

CONCLUSION

Although the DDG application affected several texture features, most image features had adequate reproducibility. PCA-based DDG-PET can be routinely used as interchangeable images for texture feature extraction from NSCLC patients.

Evaluation of data-driven respiratory gating for subcentimeter lesions using digital PET/CT system and three-axis motion phantom

Introduction.The application of data-driven respiratory gating (DDG) for subcentimeter lesions with respiratory movement remains poorly understood. Hence, this study aimed to clarify DDG application for subcentimeter lesions and the ability of digital Positron emission tomography/computed tomography (PET/CT) system combined with DDG to detect these lesions under three-axis respiration.Methods.Discovery MI PET/CT system and National Electrical Manufacturers Association (NEMA) body phantom with Micro Hollow Sphere (4, 5, 6, 8, 10, and 13 mm) were used. The NEMA phantom was filled with¹⁸F-FDG solutions of 42.4 and 5.3 kBq/ml for each hot sphere and background region. The 3.6 s cycles of three-axis respiratory motion were reproduced using the motion platform UniTraQ. The PET data acquisition was performed in stationary and respiratory-moving states. The data were reconstructed in three PET groups: stationary (NM-PET), no gating with respiratory movement (NG-PET), and DDG gating with respiratory movement (DDG-PET) groups. For image quality, percent contrast (Q_H); maximum, peak, and mean standardized uptake value (SUV); background region; and detectability index (DI) were evaluated in each PET group. Visual assessment was also conducted.Results.The groups with respiratory movement had deteriorated Q_Hand SUVs compared with NM-PET. Compared with NG-PET, DDG-PET has significantly improved Q_Hand SUVs in spheres above 6 mm. The background region showed no significant difference between groups. The SUVmax, SUVpeak, and Q_Hvalues of 8 mm sphere were highest in NM-PET, followed by DDG-PET and NG-PET. In visual assessment, the spheres above 6 mm were detected in all PET groups. DDG application did not detect new lesions, but it increased DI and visual score.Conclusions. The application of principal component analysis (PCA)-based DDG algorithm improves both image quality and quantitative SUVs in subcentimeter lesions measuring above 6 mm. Although DDG application cannot detect new subcentimeter lesions, it increases the visual indices.

What factors influence the R value in data-driven respiratory gating technique? A phantom study

OBJECTIVE

The R value is adopted as a metric for the effectiveness of the respiratory waveform in the Advanced Motion Free implemented in the PET scanner as the data-driven respiratory gating (DDG) algorithm. The effects of changes in various factors on R values were evaluated by phantom analysis.

METHODS

We used a programmable respiratory motion phantom QUASAR with a sphere filled with an 18F solution. Respiratory motion simulation was performed by changing the sphere diameter, radioactivity concentration, amplitude, respiratory cycle, and respiratory waveform shape. Three evaluations were performed. (1) The power spectra calculated from the input waveforms were evaluated. (2) The effects of changes in the factors on the R value were evaluated. (3) DDG waveforms and inspiratory peak intervals were compared with the input waveform data set.

RESULTS

The R values were increased and converged to a certain value as sphere diameter, radioactivity concentration, and amplitude gradually increased. The respiratory cycle showed the highest R value at 7.5 s, and the graph showed an upward convex pattern. The R value of the sinusoid waveform was higher than that of the typical waveform. There was a relationship between the power spectrum of the input waveform and R value. The visual score was also lower in the condition with a lower R value. In cases of no sphere, radioactivity, or motion, and a fast respiratory cycle, peak intervals were not accurately acquired.

CONCLUSIONS

Factors affecting the R value were sphere diameter, radioactivity concentration, amplitude, respiratory cycle, and respiratory waveform shape.

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.

Design of an anthropomorphic PET phantom with elastic lungs and respiration modeling

PURPOSE

Respiratory motion during positron emission tomography (PET) scans can be a major detriment to image quality in oncological imaging. The impact of motion on lesion quantification and detectability can be assessed using phantoms with realistic anatomy representation and motion modeling. In this work, we develop an anthropomorphic phantom for PET imaging that combines anatomic fidelity and a realistic breathing mechanism with deformable lungs.

METHODS

We start from a previously developed anatomically accurate but static phantom of a human torso, and add elastic lungs with a highly controllable actuation mechanism which replicates the physics of breathing. The space outside the lungs is filled with a radioactive water solution. To maintain anatomical accuracy and realistic gamma ray attenuation in the torso, all motion mechanisms and actuators are positioned outside of the phantom compartment. The actuation mechanism can produce custom respiratory waveforms with breathing rates up to 25 breaths per minute and tidal volumes up to 1200 mL.

RESULTS

Several tests were performed to validate the performance of the phantom assembly, in which the phantom was filled with water and given respiratory waveforms to execute. All parts demonstrated expected performance. Force requirements were not exceeded and no leaks were detected, although continued use of the phantom is required to evaluate wear. The motion of the lungs was determined to be within a reasonable realistic range.

CONCLUSIONS

The full mechanical design is described in this paper, as well as a software application with graphical user interface which was developed to plan and visualize respiratory patterns. Both are available online as open source files. The developed phantom will facilitate future work in evaluating the impact of respiratory motion on lesion quantification and detectability in clinical practice.

Image Registration of 18F-FDG PET/CT Using the MotionFree Algorithm and CT Protocols through Phantom Study and Clinical Evaluation

We evaluated the benefits of the MotionFree algorithm through phantom and patient studies. The various sizes of phantom and vacuum vials were linked to RPM moving with or without MotionFree application. A total of 600 patients were divided into six groups by breathing protocols and CT scanning time. Breathing protocols were applied as follows: (a) patients who underwent scanning without any breathing instructions; (b) patients who were instructed to hold their breath after expiration during CT scan; and (c) patients who were instructed to breathe naturally. The length of PET/CT misregistration was measured and we defined the misregistration when it exceeded 10 mm. In the phantom tests, the images produced by the MotionFree algorithm were observed to have excellent agreement with static images. There were significant differences in PET/CT misregistration according to CT scanning time and each breathing protocol. When applying the type (c) protocol, decreasing the CT scanning time significantly reduced the frequency and length of misregistrations (p < 0.05). The MotionFree application is able to correct respiratory motion artifacts and to accurately quantify lesions. The shorter time of CT scan can reduce the frequency, and the natural breathing protocol also decreases the lengths of misregistrations.

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.

Impact of PET data driven respiratory motion correction and BSREM reconstruction of 68Ga-DOTATATE PET/CT for differentiating neuroendocrine tumors (NET) and intrapancreatic accessory spleens (IPAS)

To evaluate whether quantitative PET parameters of motion-corrected ⁶⁸Ga-DOTATATE PET/CT can differentiate between intrapancreatic accessory spleens (IPAS) and pancreatic neuroendocrine tumor (pNET). A total of 498 consecutive patients with neuroendocrine tumors (NET) who underwent ⁶⁸Ga-DOTATATE PET/CT between March 2017 and July 2019 were retrospectively analyzed. Subjects with accessory spleens (n = 43, thereof 7 IPAS) and pNET (n = 9) were included, resulting in a total of 45 scans. PET images were reconstructed using ordered-subsets expectation maximization (OSEM) and a fully convergent iterative image reconstruction algorithm with β-values of 1000 (BSREM₁₀₀₀). A data-driven gating (DDG) technique (MOTIONFREE, GE Healthcare) was applied to extract respiratory triggers and use them for PET motion correction within both reconstructions. PET parameters among different samples were compared using non-parametric tests. Receiver operating characteristics (ROC) analyzed the ability of PET parameters to differentiate IPAS and pNETs. SUVmax was able to distinguish pNET from accessory spleens and IPAs in BSREM₁₀₀₀ reconstructions (p < 0.05). This result was more reliable using DDG-based motion correction (p < 0.003) and was achieved in both OSEM and BSREM₁₀₀₀ reconstructions. For differentiating accessory spleens and pNETs with specificity 100%, the ROC analysis yielded an AUC of 0.742 (sensitivity 56%)/0.765 (sensitivity 56%)/0.846 (sensitivity 62%)/0.840 (sensitivity 63%) for SUVmax 36.7/41.9/36.9/41.7 in OSEM/BSREM₁₀₀₀/OSEM + DDG/BSREM₁₀₀₀ + DDG, respectively. BSREM₁₀₀₀ + DDG can accurately differentiate pNET from accessory spleen. Both BSREM₁₀₀₀ and DDG lead to a significant SUV increase compared to OSEM and non-motion-corrected data.

The impact of data-driven respiratory gating in clinical F-18 FDG PET/CT: comparison of free breathing and deep-expiration breath-hold CT protocol

BACKGROUND

Respiratory motion can diminish PET image quality and lead to inaccurate lesion quantifications. Data-driven gating (DDG) was recently introduced as an effective respiratory gating technique for PET. In the current study, we investigated the clinical impact of DDG on respiratory movement in ¹⁸F-FDG PET/CT.

METHOD

PET list-mode data were collected for each subject and DDG software was utilized for extracting respiratory waveforms. PET images was reconstructed using Q.clear and Q.clear + DDG, respectively. We evaluated SUVmax, SUVmean, the coefficient of variance (CoV), metabolic tumor volume (MTV), and tumor heterogeneity using the area under the curve of cumulative SUV histogram (AUC-CSH). Metabolic parameter changes were compared between each reconstruction method. The Deep-Expiration Breath Hold (DEBH) protocol was introduced for CT scans to correct spatial misalignment between PET and CT and compared with conventional free breathing. The DEBH and free breathing (FB) protocol comparison was made in a separate matching cohort using propensity core matching rather than the same patient.

RESULTS

Total 147 PET/CT scans with excessive respiratory movements were used to study DDG-mediated correction. After DDG application, SUVmax (P < 0.0001; 8.15 ± 4.77 vs. 9.03 ± 5.02) and SUVmean (P < 0.0001; 4.91 ± 2.44 vs. 5.49 ± 2.68) of lung and upper abdomen lesions increased, while MTV significantly decreased (P < 0.0001; 7.07 ± 15.46 vs. 6.58 ± 15.14). In addition, the percent change of SUVs was greater in lower lung lesions compared to upper lobe lesions. Likewise, the MTV reduction was significantly greater in lower lobe lesions. No significant difference dependent on location was observed in liver lesions. DEBH-mediated CT breathing correction did not make a significant difference in lesion metabolic parameters compared to conventional free breathing.

CONCLUSIONS

These results suggest that DDG correction enables more corrected quantification from respiratory movements for lesions located in the lung and upper abdomen. Therefore, we suggest that DDG is worth using as a standard protocol during ¹⁸F-FDG PET/CT imaging.

Gentle Touch: Noninvasive Approaches to Improve Patient Comfort and Cooperation for Pediatric Imaging

Pediatric imaging presents unique challenges related to patient anxiety, cooperation, and safety. Techniques to reduce anxiety and patient motion in adults must often be augmented in pediatrics, because it is always mentioned in the field of pediatrics, children are not miniature adults. This article will review methods that can be considered to improve patient experience and cooperation in imaging studies. Such techniques can range from modifications to the scanner suite, different ways of preparing and interacting with children, collaborating with parents for improved patient care, and technical advances such as accelerated acquisition and motion correction to reduce artifact. Special considerations for specific populations including transgender patients, neonates, and pregnant women undergoing fetal imaging will be described. The unique risks of sedation in children will also be briefly reviewed.

A data-driven respiratory motion estimation approach for PET based on time-of-flight weighted positron emission particle tracking

Purpose

Respiratory motion of patients during positron emission tomography (PET)/computed tomography (CT) imaging affects both image quality and quantitative accuracy. Hardware‐based motion estimation, which is the current clinical standard, requires initial setup, maintenance, and calibration of the equipment, and can be associated with patient discomfort. Data‐driven techniques are an active area of research with limited exploration into lesion‐specific motion estimation. This paper introduces a time‐of‐flight (TOF)‐weighted positron emission particle tracking (PEPT) algorithm that facilitates lesion‐specific respiratory motion estimation from raw listmode PET data.

Methods

The TOF‐PEPT algorithm was implemented and investigated under different scenarios: (a) a phantom study with a point source and an Anzai band for respiratory motion tracking; (b) a phantom study with a point source only, no Anzai band; (c) two clinical studies with point sources and the Anzai band; (d) two clinical studies with point sources only, no Anzai band; and (e) two clinical studies using lesions/internal regions instead of point sources and no Anzai band. For studies with radioactive point sources, they were placed on patients during PET/CT imaging. The motion tracking was performed using a preselected region of interest (ROI), manually drawn around point sources or lesions on reconstructed images. The extracted motion signals were compared with the Anzai band when applicable. For the purposes of additional comparison, a center‐of‐mass (COM) algorithm was implemented both with and without the use of TOF information. Using the motion estimate from each method, amplitude‐based gating was applied, and gated images were reconstructed.

Results

The TOF‐PEPT algorithm is shown to successfully determine the respiratory motion for both phantom and clinical studies. The derived motion signals correlated well with the Anzai band; correlation coefficients of 0.99 and 0.94‐0.97 were obtained for the phantom study and the clinical studies, respectively. TOF‐PEPT was found to be 13–38% better correlated with the Anzai results than the COM methods. Maximum Standardized Uptake Values (SUVs) were used to quantitatively compare the reconstructed‐gated images. In comparison with the ungated image, a 14–39% increase in the max SUV across several lesion areas and an 8.7% increase in the max SUV on the tracked lesion area were observed in the gated images based on TOF‐PEPT. The distinct presence of lesions with reduced blurring effect and generally sharper images were readily apparent in all clinical studies. In addition, max SUVs were found to be 4–10% higher in the TOF‐PEPT‐based gated images than in those based on Anzai and COM methods.

Conclusion

A PEPT‐ based algorithm has been presented for determining movement due to respiratory motion during PET/CT imaging. Gating based on the motion estimate is shown to quantifiably improve the image quality in both a controlled point source phantom study and in clinical data patient studies. The algorithm has the potential to facilitate true motion correction where the reconstruction algorithm can use all data available.

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.

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

Respiratory gating is the standard to prevent respiration effects from degrading image quality in PET. Data-driven gating (DDG) using signals derived from PET raw data is a promising alternative to gating approaches requiring additional hardware (e.g., pressure-sensitive belt gating [BG]). However, continuous-bed-motion (CBM) scans require dedicated DDG approaches for axially extended PET, compared with DDG for conventional step-and-shoot scans. In this study, a CBM-capable DDG algorithm was investigated in a clinical cohort and compared with BG using optimally gated (OG) and fully motion-corrected (elastic motion correction [EMOCO]) reconstructions. Methods: Fifty-six patients with suspected malignancies in the thorax or abdomen underwent whole-body ¹⁸F-FDG CBM PET/CT using DDG and BG. Correlation analyses were performed on both gating signals. Besides static reconstructions, OG and EMOCO reconstructions were used for BG and DDG. The metabolic volume, SUV_max, and SUV_mean of lesions were compared among the reconstructions. Additionally, the quality of lesion delineation in the different PET reconstructions was independently evaluated by 3 experts. Results: The global correlation coefficient between BG and DDG signals was 0.48 ± 0.11, peaking at 0.89 ± 0.07 when scanning the kidney and liver region. In total, 196 lesions were analyzed. SUV measurements were significantly higher in BG-OG, DDG-OG, BG-EMOCO, and DDG-EMOCO than in static images (P < 0.001; median SUV_max: static, 14.3 ± 13.4; BG-EMOCO, 19.8 ± 15.7; DDG-EMOCO, 20.5 ± 15.6; BG-OG, 19.6 ± 17.1; and DDG-OG, 18.9 ± 16.6). No significant differences between BG-OG and DDG-OG or between BG-EMOCO and DDG-EMOCO were found. Visual lesion delineation was significantly better in BG-EMOCO and DDG-EMOCO than in static reconstructions (P < 0.001); no significant difference was found when comparing BG and DDG for either EMOCO or OG reconstruction. Conclusion: DDG-based motion compensation of CBM PET acquisitions outperforms static reconstructions, delivering qualities comparable to BG approaches. The new algorithm may be a valuable alternative for CBM PET systems.

Radiotherapy Planning and Molecular Imaging in Lung Cancer

INTRODUCTION

In patients suitable for radical chemoradiotherapy for lung cancer, 18F-FDGPET/ CT is a proposed management to improve the accuracy of high dose radiotherapy. However, there is a high rate of locoregional failure in patients with locally advanced non-small cell lung cancer (NSCLC), probably due to the fact that standard dosing may not be effective in all patients. The aim of the present review was to address some criticisms associated with the radiotherapy image-guided in NSCLC.

MATERIALS AND METHODS

A systematic literature search was conducted. Only published articles that met the following criteria were included: articles, only original papers, radiopharmaceutical ([18F]FDG and any tracer other than [18F]FDG), target, only specific for lung cancer radiotherapy planning, and experimental design (eventually "in vitro" studies were excluded). Peer-reviewed indexed journals, regardless of publication status (published, ahead of print, in press, etc.) were included. Reviews, case reports, abstracts, editorials, poster presentations, and publications in languages other than English were excluded. The decision to include or exclude an article was made by consensus and any disagreement was resolved through discussion.

RESULTS

Hundred eligible full-text articles were assessed. Diverse information is now available in the literature about the role of FDG and new alternative radiopharmaceuticals for the planning of radiotherapy in NSCLC. In particular, the role of alternative technologies for the segmentation of FDG uptake is essential, although indeterminate for RT planning. The pros and cons of the available techniques have been extensively reported.

CONCLUSION

PET/CT has a central place in the planning of radiotherapy for lung cancer and, in particular, for NSCLC assuming a substantial role in the delineation of tumor volume. The development of new radiopharmaceuticals can help overcome the problems related to the disadvantage of FDG to accumulate also in activated inflammatory cells, thus improving tumor characterization and providing new prognostic biomarkers.

Real-time data-driven motion correction in PET

PET imaging has been, and continues to be, an evolving diagnostic technology. In recent years, the modernizing digital landscape has opened new opportunities for data-driven innovation. One such facet has been data-driven motion correction (DDMC) in PET. As both research and industry propel this technology forward, we can recognize prospects and opportunities for further development. The concept of clinical practicality is supported by DDMC approaches—it is what sets them apart from traditional hardware-driven motion correction strategies that have largely not gained acceptance in routine diagnostic PET; the ease of use of DDMC may help propel acceptance of motion correction solutions in clinical practice. As we reflect on the present field, we should consider that DDMC can be made even more practical, and likely more impactful, if further developed to fit within a real-time acquisition framework. This vision for development is not new, but has been made more feasible with contemporary electronics, and has begun to be revisited in contemporary literature. The opportunities for development lie on a new forefront of innovation where medical physics integrates with engineering, data science, and modern computing capacities. Real-time DDMC is a systems integration challenge, and achieving it will require cooperation between hardware and software developers, and likely academia and industry. While challenges for development do exist, it is likely that we will see real-time DDMC come to fruition in the coming years. This effort may establish groundwork for developing similar innovations in the emerging digital innovation age.

Evaluation of data-driven respiratory gating waveforms for clinical PET imaging

BACKGROUND

We aimed to evaluate the clinical robustness of a commercially developed data-driven respiratory gating algorithm based on principal component analysis, for use in routine PET imaging.

METHODS

One hundred fifty-seven adult FDG PET examinations comprising a total of 1149 acquired bed positions were used for the assessment. These data are representative of FDG scans currently performed at our institution. Data were acquired for 4 min/bed position (3 min/bed for legs). The data-driven gating (DDG) algorithm was applied to each bed position, including those where minimal respiratory motion was expected. The algorithm provided a signal-to-noise measure of respiratory-like frequencies within the data, denoted as R. Qualitative evaluation was performed by visual examination of the waveforms, with each waveform scored on a 3-point scale by two readers and then averaged (score S of 0 = no respiratory signal, 1 = some respiratory-like signal but indeterminate, 2 = acceptable signal considered to be respiratory). Images were reconstructed using quiescent period gating and compared with non-gated images reconstructed with a matched number of coincidences. If present, the SUV_max of a well-defined lesion in the thorax or abdomen was measured and compared between the two reconstructions.

RESULTS

There was a strong (r = 0.86) and significant correlation between R and scores S. Eighty-six percent of waveforms with R ≥ 15 were scored as acceptable for respiratory gating. On average, there were 1.2 bed positions per patient examination with R ≥ 15. Waveforms with high R and S were found to originate from bed positions corresponding to the thorax and abdomen: 90% of waveforms with R ≥ 15 had bed centres in the range 5.6 cm superior to 27 cm inferior from the dome of the liver. For regions where respiratory motion was expected to be minimal, R tended to be < 6 and S tended to be 0. The use of DDG significantly increased the SUV_max of focal lesions, by an average of 11% when considering lesions in bed positions with R ≥ 15.

CONCLUSIONS

The majority of waveforms with high R corresponded to the part of the patient where respiratory motion was expected. The waveforms were deemed suitable for respiratory gating when assessed visually, and when used were found to increase SUV_max in focal lesions.