The impact of respiratory motion on tumor quantification and delineation in static PET/CT imaging

Data-driven gating (DDG)-based motion match for improved CTAC registration

BACKGROUND

Respiratory motion artefacts are a pitfall in thoracic PET/CT imaging. A source of these motion artefacts within PET images is the CT used for attenuation correction of the images. The arbitrary respiratory phase in which the helical CT ( CT helical ) is acquired often causes misregistration between PET and CT images, leading to inaccurate attenuation correction of the PET image. As a result, errors in tumour delineation or lesion uptake values can occur. To minimise the effect of motion in PET/CT imaging, a data-driven gating (DDG)-based motion match (MM) algorithm has been developed that estimates the phase of the CT helical , and subsequently warps this CT to a given phase of the respiratory cycle, allowing it to be phase-matched to the PET. A set of data was used which had four-dimensional CT (4DCT) acquired alongside PET/CT. The 4DCT allowed ground truth CT phases to be generated and compared to the algorithm-generated motion match CT (MMCT). Measurements of liver and lesion margin positions were taken across CT images to determine any differences and establish how well the algorithm performed concerning warping the CT helical to a given phase (end-of-expiration, EE).

RESULTS

Whilst there was a minor significance in the liver measurement between the 4DCT and MMCT ( p = 0.045 ), no significant differences were found between the 4DCT or MMCT for lesion measurements ( p = 1.0 ). In all instances, the CT helical was found to be significantly different from the 4DCT ( p < 0.001 ). Consequently, the 4DCT and MMCT can be considered equivalent with respect to warped CT generation, showing the DDG-based MM algorithm to be successful.

CONCLUSION

The MM algorithm successfully enables the phase-matching of a CT helical to the EE of a ground truth 4DCT. This would reduce the motion artefacts caused by PET/CT registration without requiring additional patient dose (required for a 4DCT).

Impact of respiratory motion on 18 F-FDG PET radiomics stability: Clinical evaluation with a digital PET scanner

PURPOSE

18 F-FDG PET quantitative features are susceptible to respiratory motion. However, studies using clinical patient data to explore the impact of respiratory motion on 18 F-FDG PET radiomic features are limited. In this study, we investigated the impact of respiratory motion on radiomics stability with clinical 18 F-FDG PET images using a data-driven gating (DDG) algorithm on the digital PET scanner.

MATERIALS AND METHODS

A total of 101 patients who underwent oncological 18 F-FDG PET scans were retrospectively included. A DDG algorithm combined with a motion compensation technique was used to extract the PET images with respiratory motion correction. 18 F-FDG-avid lesions from the thorax to the upper abdomen were analyzed on the non-DDG and DDG PET images. The lesions were segmented with a 40% threshold of the maximum standardized uptake. A total of 725 radiomic features were computed from the segmented lesions, including first-order, shape, texture, and wavelet features. The intraclass correlation coefficient (ICC) and coefficient of variation (COV) were calculated to evaluate feature stability. An ICC above 0.9 and a COV below 5% were considered high stability.

RESULTS

In total, 168 lesions with and without respiratory motion correction were analyzed. Our results indicated that most 18 F-FDG PET radiomic features are sensitive to respiratory motion. Overall, only 27 out of 725 (3.72%) radiomic features were identified as highly stable, including one from the first-order features (entropy), one from the shape features (sphericity), four from the gray-level co-occurrence matrix features (normalized and unnormalized inverse difference moment, joint entropy, and sum entropy), one from the gray-level run-length matrix features (run entropy), and 20 from the wavelet filter-based features.

CONCLUSION

Respiratory motion has a significant impact on 18 F-FDG PET radiomics stability. The highly stable features identified in our study may serve as potential candidates for further applications, such as machine learning modeling.

Differential privacy preserved federated transfer learning for multi-institutional 68Ga-PET image artefact detection and disentanglement

PURPOSE

Image artefacts continue to pose challenges in clinical molecular imaging, resulting in misdiagnoses, additional radiation doses to patients and financial costs. Mismatch and halo artefacts occur frequently in gallium-68 (68Ga)-labelled compounds whole-body PET/CT imaging. Correcting for these artefacts is not straightforward and requires algorithmic developments, given that conventional techniques have failed to address them adequately. In the current study, we employed differential privacy-preserving federated transfer learning (FTL) to manage clinical data sharing and tackle privacy issues for building centre-specific models that detect and correct artefacts present in PET images.

METHODS

Altogether, 1413 patients with 68Ga prostate-specific membrane antigen (PSMA)/DOTA-TATE (TOC) PET/CT scans from 3 countries, including 8 different centres, were enrolled in this study. CT-based attenuation and scatter correction (CT-ASC) was used in all centres for quantitative PET reconstruction. Prior to model training, an experienced nuclear medicine physician reviewed all images to ensure the use of high-quality, artefact-free PET images (421 patients' images). A deep neural network (modified U2Net) was trained on 80% of the artefact-free PET images to utilize centre-based (CeBa), centralized (CeZe) and the proposed differential privacy FTL frameworks. Quantitative analysis was performed in 20% of the clean data (with no artefacts) in each centre. A panel of two nuclear medicine physicians conducted qualitative assessment of image quality, diagnostic confidence and image artefacts in 128 patients with artefacts (256 images for CT-ASC and FTL-ASC).

RESULTS

The three approaches investigated in this study for 68Ga-PET imaging (CeBa, CeZe and FTL) resulted in a mean absolute error (MAE) of 0.42 ± 0.21 (CI 95%: 0.38 to 0.47), 0.32 ± 0.23 (CI 95%: 0.27 to 0.37) and 0.28 ± 0.15 (CI 95%: 0.25 to 0.31), respectively. Statistical analysis using the Wilcoxon test revealed significant differences between the three approaches, with FTL outperforming CeBa and CeZe (p-value < 0.05) in the clean test set. The qualitative assessment demonstrated that FTL-ASC significantly improved image quality and diagnostic confidence and decreased image artefacts, compared to CT-ASC in 68Ga-PET imaging. In addition, mismatch and halo artefacts were successfully detected and disentangled in the chest, abdomen and pelvic regions in 68Ga-PET imaging.

CONCLUSION

The proposed approach benefits from using large datasets from multiple centres while preserving patient privacy. Qualitative assessment by nuclear medicine physicians showed that the proposed model correctly addressed two main challenging artefacts in 68Ga-PET imaging. This technique could be integrated in the clinic for 68Ga-PET imaging artefact detection and disentanglement using multicentric heterogeneous datasets.

Abdominal Positron Emission Tomography/Magnetic Resonance Imaging

Hybrid positron emission tomography (PET)/magnetic resonance imaging (MRI) is highly suited for abdominal pathologies. A precise co-registration of anatomic and metabolic data is possible thanks to the simultaneous acquisition, leading to accurate imaging. The literature shows that PET/MRI is at least as good as PET/CT and even superior for some indications, such as primary hepatic tumors, distant metastasis evaluation, and inflammatory bowel disease. PET/MRI allows whole-body staging in a single session, improving health care efficiency and patient comfort.

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.

Role of breath-hold lung PET in stage IA pulmonary adenocarcinoma

BACKGROUND

Respiratory motion during PET acquisition may result in image blurring and resolution loss, reduced measurement of radiotracer uptake, and consequently, inaccurate lesion quantification and description. With the introduction of the total-body PET system, short-time PET acquisition is feasible due to its high sensitivity and spatial resolution. The purpose of this study was to evaluate the additional value of 20-s breath-hold (BH) lung PET in patients with stage IA pulmonary adenocarcinoma.

METHODS

Forty-seven patients with confirmed stage IA pulmonary adenocarcinoma were enrolled in this retrospective study. All patients underwent a 300-s FB whole-body PET, followed by a BH lung PET. The SUV_max, TBR of the lesions and the percentage difference in nodule SUV_max (%ΔSUV_max) and TBR (%ΔTBR) between the two acquisitions was also calculated. The lesions were further divided by distance from pleura for subgroup analysis. The lesion detectability on PET images was the percentage of FDG-positive lesions.

RESULTS

Among 47 patients, the BH lung PET images identified all lung nodules, and there was a significant difference in overall nodule SUV_max and TBR between BH PET and FB PET (both p < 0.01). The %ΔSUV_max and %ΔTBR were significantly higher in nodules adjacent to pleura (≤ 10 mm in distance) than those away from pleura (both p < 0.05). The lesion detectability of BH lung PET was significantly higher than that of FB PET (p < 0.01).

CONCLUSION

BH PET acquisition is a practical way to minimize motion artifacts in PET which has the potential to improve lesion detection for stage IA pulmonary adenocarcinoma.

CRITICAL RELEVANCE STATEMENT

BH PET acquisition is a practical way to minimize motion artifacts in PET which has the potential to improve lesion detection for stage IA pulmonary adenocarcinoma.

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 a respiratory motion-corrected image reconstruction algorithm in 2-[18F]FDG and [68Ga]Ga-DOTA-NOC PET/CT: impacts on image quality and tumor quantification

Background

Respiratory motions may cause artifacts on positron emission tomography (PET) images that degrade image quality and quantification accuracy. This study aimed to evaluate the effect of a respiratory motion-corrected image reconstruction (MCIR) algorithm on image quality and tumor quantification compared with nongated/nonmotion-corrected reconstruction.

Methods

We used a phantom consisting of 5 motion spheres immersed in a chamber driven by a motor. The spheres and the background chamber were filled with 18F solution at a sphere-to-background ratio of 5:1. We enrolled 42 and 16 patients undergoing 2-deoxy-2-[¹⁸F]fluoro-D-glucose {2-[¹⁸F]FDG} and ⁶⁸Ga-labeled [1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid]-1-Nal3-octreotide {[⁶⁸Ga]Ga-DOTA-NOC} PET/computed tomography (CT) from whom 74 and 30 lesions were segmented, respectively. Three reconstructions were performed: data-driven gating-based motion correction (DDGMC), external vital signal module-based motion correction (VSMMC), and noncorrection reconstruction. The standardized uptake values (SUVs) and the volume of the spheres and the lesions were measured and compared among the 3 reconstruction groups. The image noise in the liver was measured, and the visual image quality of motion artifacts was scored by radiologists in the patient study.

Results

In the phantom study, the spheres' SUVs increased by 26-36%, and the volumes decreased by 35-38% in DDGMC and VSMMC compared with the noncorrection group. In the 2-[¹⁸F]FDG PET patient study, the lesions' SUVs had a median increase of 10.87-12.65% while the volumes had a median decrease of 14.88-15.18% in DDGMC and VSMMC compared with those of noncorrection. In the [⁶⁸Ga]Ga-DOTA-NOC PET patient study, the lesions' SUVs increased by 14.23-15.45%, and the volumes decreased by 19.11-20.94% in DDGMC and VSMMC. The image noise in the liver was equal between the DDGMC, VSMMC, and noncorrection groups. Radiologists found improved image quality in more than 45% of the cases in DDGMC and VSMMC compared with the noncorrection group. There was no statistically significant difference in SUVs, volumes, or visual image quality scores between DDGMC and VSMMC.

Conclusions

MCIR improves tumor quantification accuracy and visual image quality by reducing respiratory motion artifacts without compromised image noise performance or elongated acquisition time in 2-[¹⁸F]FDG and [⁶⁸Ga]Ga-DOTA-NOC PET/CT tumor imaging. The performance of DDG-driven MCIR is as good as that of the external device-driven solution.

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.

Comparison of protocols with respiratory-gated (4D) motion compensation in PET/CT: open-source package for quantification of phantom image quality

BACKGROUND

Patient's breathing affects the quality of chest images acquired with positron emission tomography/computed tomography (PET/CT) studies. Movement correction is required to optimize PET quantification in clinical settings. We present a reproducible methodology to compare the impact of different movement compensation protocols on PET image quality. Static phantom images were set as reference values, and recovery coefficients (RCs) were calculated from motion compensated images for the phantoms in respiratory movement. Image quality was evaluated in terms of: (1) volume accuracy (VA) with the NEMA phantom; (2) concentration accuracy (CA) by six refillable inserts within the electron density CIRS phantom; and (3) spatial resolution (R) with the Jaszczak phantom. Three different respiratory patterns were applied to the phantoms. We developed an open-source package to automatically analyze VA, CA and R. We compared 10 different movement compensation protocols available in the Philips Gemini TF-64 PET/CT (4-, 6-, 8- and 10-time bins, 20%-, 30%-, 40%-window width in Inhale and Exhale).

RESULTS

The homemade package provided RC values for VA, CA and R of 102 PET images in less than 5 min. Results of the comparison of the 10 different protocols demonstrated the feasibility of the proposed method for quantifying the variations observed qualitatively. Overall, prospective protocols showed better motion compensation than retrospective. The best performance was obtained for the protocol Exhale 30% (0.3 s after maximum Exhale position and window width of 30%) with RC[Formula: see text], RC[Formula: see text] and RC[Formula: see text]. Among retrospective protocols, 8 Phase protocol showed the best performance.

CONCLUSION

We provided an open-source package able to automatically evaluate the impact of motion compensation methods on PET image quality. A setup based on commonly available experimental phantoms is recommended. Its application for the comparison of 10 time-based approaches showed that Exhale 30% protocol had the best performance. The proposed framework is not specific to the phantoms and protocols presented on this study.

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.

Unsupervised inter-frame motion correction for whole-body dynamic PET using convolutional long short-term memory in a convolutional neural network

Subject motion in whole-body dynamic PET introduces inter-frame mismatch and seriously impacts parametric imaging. Traditional non-rigid registration methods are generally computationally intense and time-consuming. Deep learning approaches are promising in achieving high accuracy with fast speed, but have yet been investigated with consideration for tracer distribution changes or in the whole-body scope. In this work, we developed an unsupervised automatic deep learning-based framework to correct inter-frame body motion. The motion estimation network is a convolutional neural network with a combined convolutional long short-term memory layer, fully utilizing dynamic temporal features and spatial information. Our dataset contains 27 subjects each under a 90-min FDG whole-body dynamic PET scan. Evaluating performance in motion simulation studies and a 9-fold cross-validation on the human subject dataset, compared with both traditional and deep learning baselines, we demonstrated that the proposed network achieved the lowest motion prediction error, obtained superior performance in enhanced qualitative and quantitative spatial alignment between parametric Ki and Vb images, and significantly reduced parametric fitting error. We also showed the potential of the proposed motion correction method for impacting downstream analysis of the estimated parametric images, improving the ability to distinguish malignant from benign hypermetabolic regions of interest. Once trained, the motion estimation inference time of our proposed network was around 460 times faster than the conventional registration baseline, showing its potential to be easily applied in clinical settings.

Diagnostic performance of total-body 18F-FDG PET/CT with fast 2-min acquisition for liver tumours: comparison with conventional PET/CT

PURPOSE

To comparatively evaluate the diagnostic performances of total-body ¹⁸F-fluorodeoxyglucose positron-emission tomography/computed tomography (¹⁸F-FDG PET/CT) with fast 2-min acquisition and conventional PET/CT in liver cancer patients.

METHODS

This study included 156 patients with liver tumours. Seventy-eight patients underwent total-body PET/CT. PET raw data were reconstructed using acquisition durations of 2 min (G2) and 15 min (G15). Another 78 patients with liver lesions (control patients) underwent conventional uMI780 PET/CT (G780). All patients were evaluated based on TNM staging. The maximum tumour standardized uptake value (tumour SUVmax), mean normal liver SUV (SUVmean), and tumour SUVmax-to-liver SUVmean ratio (TLR) were determined for all patients. G15 data were used as the reference in the lesion detectability analysis. The diagnostic performances of PET/CT in terms of visual parameters and of PET in terms of semi-quantitative parameters such as SUVmax and TLR were evaluated. Receiver operating characteristics (ROC) curve analysis of SUVmax and TLR at G2 was performed. Pathologic findings of surgical specimens served as the gold standard for all patients.

RESULTS

The lesions found in G15 were also noted in G2; three lymph nodes were missed in G2. However, no significant difference was found in the TNM stage among G2, G15, and G780. For benign and malignant lesions, the liver SUVmean in G2 and G15 was higher than that in G780 (all P < 0.05). The tumour SUVmax and TLR in G2 were equivalent to those in G15 and G780 regardless of whether the lesions were benign or malignant. ROC curve analysis (SUVmax cutoff: 4.34, TLR cutoff: 1.34) demonstrated that G2 also had good sensitivity in detecting liver cancer.

CONCLUSION

The diagnostic performance of total-body PET/CT in G2 was comparable to that in G15 among liver cancer patients. Further, the diagnostic efficiency of total-body PET/CT imaging with fast 2-min acquisition and conventional PET/CT was similar.

Evaluation of Multisource Adaptive MRI Fusion for Gross Tumor Volume Delineation of Hepatocellular Carcinoma

Purpose

Tumor delineation plays a critical role in radiotherapy for hepatocellular carcinoma (HCC) patients. The incorporation of MRI might improve the ability to correctly identify tumor boundaries and delineation consistency. In this study, we evaluated a novel Multisource Adaptive MRI Fusion (MAMF) method in HCC patients for tumor delineation.

Methods

Ten patients with HCC were included in this study retrospectively. Contrast-enhanced T1-weighted MRI at portal-venous phase (T1W_PP), contrast-enhanced T1-weighted MRI at 19-min delayed phase (T1W_DP), T2-weighted (T2W), and diffusion-weighted MRI (DWI) were acquired on a 3T MRI scanner and imported to in-house-developed MAMF software to generate synthetic MR fusion images. The original multi-contrast MR image sets were registered to planning CT by deformable image registration (DIR) using MIM. Four observers independently delineated gross tumor volumes (GTVs) on the planning CT, four original MR image sets, and the fused MRI for all patients. Tumor contrast-to-noise ratio (CNR) and Dice similarity coefficient (DSC) of the GTVs between each observer and a reference observer were measured on the six image sets. Inter-observer and inter-patient mean, SD, and coefficient of variation (CV) of the DSC were evaluated.

Results

Fused MRI showed the highest tumor CNR compared to planning CT and original MR sets in the ten patients. The mean ± SD tumor CNR was 0.72 ± 0.73, 3.66 ± 2.96, 4.13 ± 3.98, 4.10 ± 3.17, 5.25 ± 2.44, and 9.82 ± 4.19 for CT, T1W_PP, T2W, DWI, T1W_DP, and fused MRI, respectively. Fused MRI has the minimum inter-observer and inter-patient variations as compared to original MR sets and planning CT sets. GTV delineation inter-observer mean DSC across the ten patients was 0.81 ± 0.09, 0.85 ± 0.08, 0.88 ± 0.04, 0.89 ± 0.08, 0.90 ± 0.04, and 0.95 ± 0.02 for planning CT, T1W_PP, T2W, DWI, T1W_DP, and fused MRI, respectively. The patient mean inter-observer CV of DSC was 3.3%, 3.2%, 1.7%, 2.6%, 1.5%, and 0.9% for planning CT, T1W_PP, T2W, DWI, T1W_DP, and fused MRI, respectively.

Conclusion

The results demonstrated that the fused MRI generated using the MAMF method can enhance tumor CNR and improve inter-observer consistency of GTV delineation in HCC as compared to planning CT and four commonly used MR image sets (T1W_PP, T1W_DP, T2W, and DWI). The MAMF method holds great promise in MRI applications in HCC radiotherapy treatment planning.

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.

Metabolic Volume Measurements in Multiple Myeloma

Multiple myeloma (MM) accounts for 10-15% of all hematologic malignancies, as well as 20% of deaths related to hematologic malignant tumors, predominantly affecting bone and bone marrow. Positron emission tomography/computed tomography with 18F-fluorodeoxyglucose (FDG-PET/CT) is an important method to assess the tumor burden of these patients. It is often challenging to classify the extent of disease involvement in the PET scans for many of these patients because both focal and diffuse bone lesions may coexist, with varying degrees of FDG uptake. Different metrics involving volumetric parameters and texture features have been proposed to objectively assess these images. Here, we review some metabolic parameters that can be extracted from FDG-PET/CT images of MM patients, including technical aspects and predicting MM outcome impact. Metabolic tumor volume (MTV) and total lesion glycolysis (TLG) are volumetric parameters known to be independent predictors of MM outcome. However, they have not been adopted in clinical practice due to the lack of measuring standards. CT-based segmentation allows automated, and therefore reproducible, calculation of bone metabolic metrics in patients with MM, such as maximum, mean and standard deviation of the standardized uptake values (SUV) for the entire skeleton. Intensity of bone involvement (IBI) is a new parameter that also takes advantage of this approach with promising results. Other indirect parameters obtained from FDG-PET/CT images, such as visceral adipose tissue glucose uptake and subcutaneous adipose tissue radiodensity, may also be useful to evaluate the prognosis of MM patients. Furthermore, the use and quantification of new radiotracers can address different metabolic aspects of MM and may have important prognostic implications.

Feasibility of ultra-low 18F-FDG activity acquisitions using total-body PET/CT

The present study aimed to evaluate the feasibility of ultra-low ¹⁸F-fluorodeoxyglucose (FDG) activity in total-body positron emission tomography (PET)/computed tomography (CT) oncological studies. Methods: Thirty patients with cancer were enrolled prospectively and underwent a total-body PET/CT examination with an ultra-low ¹⁸F-FDG activity (0.37 MBq/kg) after an uptake time of 60 minutes. Among the enrolled patients, 11 were diagnosed with colorectal cancer (CRC). PET raw data were acquired within 15 minutes and reconstructed using data from the first 1, 2, 4, 8, 10 and the entire 15 min (G1, G2, G4, G8, G10, G15). Image quality was assessed qualitatively by two readers using a 5-point Likert scale twice. Cohen's kappa test was performed to investigate the intra-reader and inter-reader agreement. The standard uptake value (SUV)max of lesions, SUV_max, SUVmean, and standard deviation (SD) of the livers, the tumor-to-background ratio (TBR), and the signal-to-noise ratio (SNR) were measured and compared. The acquisition time for a clinically acceptable image quality was determined using an ultra low activity injection. In a matched-pair study, 11 patients with CRC who received a full FDG activity (3.7 MBq/kg) with a 2-min PET acquisition were selected retrospectively with matched sex, height, weight, body mass index, glucose level, uptake time, and pathological types with the 11 CRC subjects in the prospective study. Qualitative and quantitative analyses were performed and compared between the 11 patients with CRC in the ultra-low activity group and their matched full activity controls. Results: Qualitative analysis of image quality showed good intra- and inter-reader agreements (all kappa > 0.7). All the images acquired for 8-min or longer scored over 3 (indicating clinical acceptability). There was no significant difference in TBR and liver SNR among all the images acquired for 8-min or longer. In the matched study, no significant difference was found in the image quality score and quantitative parameters between the ultra-low activity group with an 8-min acquisition and the full activity group with a 2-min acquisition. Conclusion: Ultra-low FDG activity injection with 8-min acquisition in a total-body PET/CT study can achieve acceptable image quality equivalent to that in the full activity group using 2-min acquisition.

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.

Pitfalls on PET/CT Due to Artifacts and Instrumentation

PET/CT has become a preferred imaging modality over PET-only scanners in clinical practice. However, along with the significant improvement in diagnostic accuracy and patient throughput, pitfalls on PET/CT are reported as well. This review provides a general overview on the potential influence of the limitations with respect to PET/CT instrumentation and artifacts associated with the modality integration on the image appearance and quantitative accuracy of PET. Approaches proposed in literature to address the limitations or minimize the artifacts are discussed as well as their current challenges for clinical applications. Although the CT component can play an important role in assisting clinical diagnosis, we concentrate on the imaging scenarios where CT is used to provide auxiliary information for attenuation compensation and scatter correction in PET.

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.

Evaluation and optimization of radiomics features stability to respiratory motion in 18 F-FDG 3D PET imaging

PURPOSE

To evaluate the impact of respiratory motion on radiomics features in ¹⁸ F-fluoro-2-deoxy-D-glucose three dimensional positron emission tomography (¹⁸ F-FDG 3D PET) imaging and optimize feature stability by combining preprocessing configurations and aggregation strategies.

METHODS

An in-house developed respiratory motion phantom was imaged in 3D PET scanner under nine respiratory patterns including one reference pattern. In total, 487 radiomics features were extracted for each respiratory pattern. Feature stability to respiratory motion was first evaluated by metrics of coefficient of variation (COV) and relative difference (RD) in a fixed preprocessing configuration. Further, one-way ANOVA and trend analysis were performed to evaluate the impact of preprocessing configuration (voxel size, discretization scheme) and aggregation strategy on feature stability. Finally, an optimization framework was proposed by selected feature-specific configurations with minimum COV value, and the diagnostic performance was validated in stable versus unstable features and fixed versus optimal features by a set of 46 patients with lung disease.

RESULTS

PET radiomics features were sensitive to respiratory motion, only 79/487 (16%) features were identified to be very stable in the fixed configuration. Preprocessing configuration and aggregation strategy had an impact on feature stability. For different voxel size, bin number, bin size and aggregation strategy, 188/487 (39%), 70/487 (15%), 148/487 (30%), and 38/95 (29%) features appeared significant changes in feature stability. The optimized configuration had the potential to improve feature stability compared to fixed configuration, with the COV decreased from 22% ±24% to 16% ±20%. Regarding the diagnostic performance, the stable and optimal configuration features outperformed the unstable and fixed configuration features, respectively (AUC 0.88, 0.87 vs. 0.83, 0.85).

CONCLUSIONS

Respiratory motion shows considerable impact on feature stability in 3D PET imaging, while optimizing preprocessing configuration may improve feature stability and diagnostic performance.

Improvement of image quality using amplitude-based respiratory gating in PET-computed tomography scanning

OBJECTIVES

This study sought to provide data supporting the expanded clinical use of respiratory gating by assessing the diagnostic accuracy of breathing motion correction using amplitude-based respiratory gating.

METHODS

A respiratory movement tracking device was attached to a PET-computed tomography scanner, and images were obtained in respiratory gating mode using a motion phantom that was capable of sensing vertical motion. Specifically, after setting amplitude changes and intervals according to the movement cycle using a total of nine combinations of three waveforms and three amplitude ranges, respiratory motion-corrected images were reconstructed using the filtered back projection method. After defining areas of interest in the acquired images in the same image planes, statistical analyses were performed to compare differences in standardized uptake value (SUV), lesion volume, full width at half maximum (FWHM), signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR).

RESULTS

SUVmax increased by 89.9%, and lesion volume decreased by 27.9%. Full width at half maximum decreased by 53.9%, signal-to-noise ratio increased by 11% and contrast-to-noise ratio increased by 16.3%. Optimal results were obtained when using a rest waveform and 35% duty cycle, in which the change in amplitude in the respiratory phase signal was low, and a constant level of long breaths was maintained.

CONCLUSIONS

These results demonstrate that respiratory-gated PET-CT imaging can be used to accurately correct for SUV changes and image distortion caused by respiratory motion, thereby providing excellent imaging information and quality.

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.

A patient-specific approach for quantitative and automatic analysis of computed tomography images in lung disease: Application to COVID-19 patients

PURPOSE

Quantitative metrics in lung computed tomography (CT) images have been widely used, often without a clear connection with physiology. This work proposes a patient-independent model for the estimation of well-aerated volume of lungs in CT images (WAVE).

METHODS

A Gaussian fit, with mean (Mu.f) and width (Sigma.f) values, was applied to the lower CT histogram data points of the lung to provide the estimation of the well-aerated lung volume (WAVE.f). Independence from CT reconstruction parameters and respiratory cycle was analysed using healthy lung CT images and 4DCT acquisitions. The Gaussian metrics and first order radiomic features calculated for a third cohort of COVID-19 patients were compared with those relative to healthy lungs. Each lung was further segmented in 24 subregions and a new biomarker derived from Gaussian fit parameter Mu.f was proposed to represent the local density changes.

RESULTS

WAVE.f resulted independent from the respiratory motion in 80% of the cases. Differences of 1%, 2% and up to 14% resulted comparing a moderate iterative strength and FBP algorithm, 1 and 3 mm of slice thickness and different reconstruction kernel. Healthy subjects were significantly different from COVID-19 patients for all the metrics calculated. Graphical representation of the local biomarker provides spatial and quantitative information in a single 2D picture.

CONCLUSIONS

Unlike other metrics based on fixed histogram thresholds, this model is able to consider the inter- and intra-subject variability. In addition, it defines a local biomarker to quantify the severity of the disease, independently of the observer.

Imaging coronary plaques using 3D motion-compensated [18F]NaF PET/MR

Background

Cardiac PET has recently found novel applications in coronary atherosclerosis imaging using [¹⁸F]NaF as a radiotracer, highlighting vulnerable plaques. However, the resulting uptakes are relatively small, and cardiac motion and respiration-induced movement of the heart can impair the reconstructed images due to motion blurring and attenuation correction mismatches. This study aimed to apply an MR-based motion compensation framework to [¹⁸F]NaF data yielding high-resolution motion-compensated PET and MR images.

Methods

Free-breathing 3-dimensional Dixon MR data were acquired, retrospectively binned into multiple respiratory and cardiac motion states, and split into fat and water fraction using a model-based reconstruction framework. From the dynamic MR reconstructions, both a non-rigid cardiorespiratory motion model and a motion-resolved attenuation map were generated and applied to the PET data to improve image quality. The approach was tested in 10 patients and focal tracer hotspots were evaluated concerning their target-to-background ratio, contrast-to-background ratio, and their diameter.

Results

MR-based motion models were successfully applied to compensate for physiological motion in both PET and MR. Target-to-background ratios of identified plaques improved by 7 ± 7%, contrast-to-background ratios by 26 ± 38%, and the plaque diameter decreased by −22 ± 18%. MR-based dynamic attenuation correction strongly reduced attenuation correction artefacts and was not affected by stent-related signal voids in the underlying MR reconstructions.

Conclusions

The MR-based motion correction framework presented here can improve the target-to-background, contrast-to-background, and width of focal tracer hotspots in the coronary system. The dynamic attenuation correction could effectively mitigate the risk of attenuation correction artefacts in the coronaries at the lung-soft tissue boundary. In combination, this could enable a more reproducible and reliable plaque localisation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-020-05180-4.

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.

Motion correction for PET data using subspace-based real-time MR imaging in simultaneous PET/MR

Image quality of positron emission tomography (PET) reconstructions is degraded by subject motion occurring during the acquisition. Magnetic resonance (MR)-based motion correction approaches have been studied for PET/MR scanners and have been successful at capturing regular motion patterns, when used in conjunction with surrogate signals (e.g. navigators) to detect motion. However, handling irregular respiratory motion and bulk motion remains challenging. In this work, we propose an MR-based motion correction method relying on subspace-based real-time MR imaging to estimate motion fields used to correct PET reconstructions. We take advantage of the low-rank characteristics of dynamic MR images to reconstruct high-resolution MR images at high frame rates from highly undersampled k-space data. Reconstructed dynamic MR images are used to determine motion phases for PET reconstruction and estimate phase-to-phase nonrigid motion fields able to capture complex motion patterns such as irregular respiratory and bulk motion. MR-derived binning and motion fields are used for PET reconstruction to generate motion-corrected PET images. The proposed method was evaluated on in vivo data with irregular motion patterns. MR reconstructions accurately captured motion, outperforming state-of-the-art dynamic MR reconstruction techniques. Evaluation of PET reconstructions demonstrated the benefits of the proposed method in terms of motion artifacts reduction, improving the contrast-to-noise ratio by up to a factor 3 and achieveing a target-to-background ratio up to 90% superior compared to standard/uncorrected methods. The proposed method can improve the image quality of motion-corrected PET reconstructions in clinical applications.

Data-driven, projection-based respiratory motion compensation of PET data for cardiac PET/CT and PET/MR imaging

BACKGROUND

Respiratory patient motion causes blurring of the PET images that may impact accurate quantification of perfusion and infarction extents in PET myocardial viability studies. In this study, we investigate the feasibility of correcting for respiratory motion directly in the PET-listmode data prior to image reconstruction using a data-driven, projection-based, respiratory motion compensation (DPR-MoCo) technique.

METHODS

The DPR-MoCo method was validated using simulations of a XCAT phantom (Biograph mMR PET/MR) as well as experimental phantom acquisitions (Biograph mCT PET/CT). Seven patient studies following a dual-tracer (18F-FDG/13N-NH3) imaging-protocol using a PET/MR-system were also evaluated. The performance of the DPR-MoCo method was compared against reconstructions of the acquired data (No-MoCo), a reference gate method (gated) and an image-based MoCo method using the standard reconstruction-transform-average (RTA-MoCo) approach. The target-to-background ratio (TBRLV) in the myocardium and the noise in the liver (CoVliver) were evaluated for all acquisitions. For all patients, the clinical effect of the DPR-MoCo was assessed based on the end-systolic (ESV), the end-diastolic volumes (EDV) and the left ventricular ejection fraction (EF) which were compared to functional values obtained from the cardiac MR.

RESULTS

The DPR-MoCo and the No-MoCo images presented with similar noise-properties (CoV) (P = .12), while the RTA-MoCo and reference-gate images showed increased noise levels (P = .05). TBRLV values increased for the motion limited reconstructions when compared to the No-MoCo reconstructions (P > .05). DPR-MoCo results showed higher correlation with the functional values obtained from the cardiac MR than the No-MoCo results, though non-significant (P > .05).

CONCLUSION

The projection-based DPR-MoCo method helps to improve PET image quality of the myocardium without the need for external devices for motion tracking.

Neural correlates of head restraint: Unsolicited neuronal activation and dopamine release

To minimize motion-related distortion of reconstructed images, conventional positron emission tomography (PET) measurements of the brain inevitably require a firm and tight head restraint. While such a restraint is now a routine procedure in brain imaging, the physiological and psychological consequences resulting from the restraint have not been elucidated. To address this problem, we developed a restraint-free brain PET system and conducted PET scans under both restrained and non-restrained conditions. We examined whether head restraint during PET scans could alter brain activities such as regional cerebral blood flow (rCBF) and dopamine release along with psychological stress related to head restraint. Under both conditions, 20 healthy male participants underwent [¹⁵O]H₂O and [¹¹C]Raclopride PET scans during working memory tasks with the same PET system. Before, during, and after each PET scan, we measured physiological and psychological stress responses, including the State-Trait Anxiety Inventory (STAI) scores. Analysis of the [¹⁵O]H₂O-PET data revealed higher rCBF in regions such as the parahippocampus in the restrained condition. We found the binding potential (BP_ND) of [¹¹C]Raclopride in the putamen was significantly reduced in the restrained condition, which reflects an increase in dopamine release. Moreover, the restraint-induced change in BP_ND was correlated with a shift in the state anxiety score of the STAI, indicating that less anxiety accompanied smaller dopamine release. These results suggest that the stress from head restraint could cause unsolicited responses in brain physiology and emotional states. The restraint-free imaging system may thus be a key enabling technology for the natural depiction of the mind.

Performing an Additional Lateral Decubitus PET/CT Scan to Resolve a Respiratory Motion Artifact

Respiratory motion artifacts may affect interpretation of whole-body ¹⁸F-FDG PET/CT scans, especially when lesions are localized between the liver and the lung. We report a case of a patient with breast cancer who underwent PET/CT after therapy and in whom focal ¹⁸F-FDG uptake of equivocal interpretation was observed between the liver and the pleura. A subsequent imaging acquisition of the right lateral decubitus showed that the lesion had a pleural location, thus improving the diagnostic accuracy of the PET/CT finding.

[Examination of Optimal Window Size and Acquisition Time of Respiratory-gated PET Image: Phantom Study with a SiPM-based PET/CT Scanner]

PURPOSE

This phantom study aimed to determine the optimal acquisition window size for phase-based respiratory gating in silicon photomultiplier (SiPM)-based fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) and its acquisition time in respiratory-gated imaging with the optimal window size.

METHODS

Images of a moving NEMA IEC Body Phantom Set^TM with hot spheres were acquired. First, the tumor volume and the maximum standardized uptake value (SUV_max) of images reconstructed using a different window size were evaluated to define the optimal window size. Second, the quality of the images reconstructed using the optimal window size and different acquisition times was evaluated using the detectability score of the 10-mm hot sphere and physical indices.

RESULTS

The volume and the SUV_max of the 10-mm hot sphere were improved when the window size was narrow, and there were no significant differences among images reconstructed using a window size narrower than 20%. To reconstruct an image using the 20% window size, an acquisition time of 5 min was required to visualize the 10-mm hot sphere.

CONCLUSIONS

The optimal window size for phase-based respiratory gating is 20%. Further, an acquisition time of 5 min should be taken for respiratory-gated imaging with the 20% window size on SiPM-based FDG-PET/CT.

Clinical evaluation of three respiratory gating schemes for different respiratory patterns on cardiac SPECT

PURPOSE

Respiratory gating reduces respiratory blur in cardiac single photon emission computed tomography (SPECT). It can be implemented as three gating schemes: (a) equal amplitude-based gating (AG); (b) phase or time-based gating (TG); or (c) equal count-based gating (CG), that is, a variant of amplitude-based method. The goal of this study is to evaluate the effectiveness of these respiratory gating methods for patients with different respiratory patterns in myocardial perfusion SPECT.

METHODS

We reviewed 1274 anonymized patient respiratory traces obtained via the Vicon motion-tracking system during their ^99m Tc-sestamibi SPECT scans and grouped them into four breathing categories: (a) regular respiration (RR); (b) periodic respiration (PR); (c) respiration with apnea (AR); and (d) unclassified respiration (UR). For each respiratory pattern, 15 patients were randomly selected and their list-mode data were rebinned using the three gating schemes. A preliminary reconstruction was performed for each gate with the heart region segmented and registered to a reference gate to estimate the respiratory motion. A final reconstruction incorporating respiratory motion correction was done to get a final image set. The estimated respiratory motion, the full-width-at-half-maxima (FWHM) measured across the image intensity profile of the left ventricle wall, as well as the normalized standard deviation measured in a uniform cuboid region of the thorax were analyzed.

RESULTS

There are 47.1%, 24.3%, 13.5%, and 15.1% RR, PR, AR, and UR patients, respectively, among the 1274 patients in this study. The differences among the three gating schemes in RR were smaller than other respiratory patterns. The AG and CG methods showed statistically larger motion estimation than TG particularly in the AR and PR patterns. Noise of AG varied more in different gates, especially for AR and UR patterns.

CONCLUSION

More than half of the patients reviewed exhibited nonregular breathing patterns. Amplitude-based gating, that is, AG and CG, is a preferred gating method for such patterns and is a robust respiratory gating implementation method given the respiratory pattern of the patients is unknown before data acquisition. Phase gating is also a feasible option for regular respiratory pattern.

Comparison of two elastic motion correction approaches for whole-body PET/CT: motion deblurring vs gate-to-gate motion correction

Background

Respiratory motion in PET/CT leads to well-known image degrading effects commonly compensated using elastic motion correction approaches. Gate-to-gate motion correction techniques are promising tools for improving clinical PET data but suffer from relatively long reconstruction times. In this study, the performance of a fast elastic motion compensation approach based on motion deblurring (DEB-MC) was evaluated on patient and phantom data and compared to an EM-based fully 3D gate-to-gate motion correction method (G2G-MC) which was considered the gold standard.

Methods

Twenty-eight patients were included in this study with suspected or confirmed malignancies in the thorax or abdomen. All patients underwent whole-body [¹⁸F]FDG PET/CT examinations applying hardware-based respiratory gating. In addition, a dynamic anthropomorphic thorax phantom was studied with PET/CT simulating tumour motion under controlled but realistic conditions. PET signal recovery values were calculated from phantom scans by comparing lesion activities after motion correction to static ground truth data. Differences in standardized uptake values (SUV) and metabolic volume (MV) between both reconstruction methods as well as between motion-corrected (MC) and non motion-corrected (NOMC) results were statistically analyzed using a Wilcoxon signed-rank test.

Results

Phantom data analysis showed high lesion recovery values of 91% (2 cm motion) and 98% (1 cm) for G2G-MC and 83% (2 cm) and 90% (1 cm) for DEB-MC. The statistical analysis of patient data found significant differences between NOMC and MC reconstructions for SUV _max, SUV _mean, MV, and contrast-to-noise ratio (CNR) for both reconstruction algorithms. Furthermore, both methods showed similar increases of 11–12% in SUV _max and SUV _mean after MC. The statistical analysis of the MC/NOMC ratio found no significant differences between the methods.

Conclusion

Both motion correction techniques deliver comparable improvements of SUV _max, SUV _mean, and CNR after MC on clinical and phantom data. The fast elastic motion compensation technique DEB-MC may thereby be a valuable alternative to state-of-the art motion correction techniques.

Clinical comparison of the positron emission tracking (PeTrack) algorithm with the real-time position management system for respiratory gating in cardiac positron emission tomography

PURPOSE

A data-driven motion tracking system was developed for respiratory gating in positron emission tomography (PET)/computed tomography (CT) studies. The positron emission tracking system (PeTrack) estimates the position of a low-activity fiducial marker placed on the patient during imaging. The aim of this study was to compare the performance of PeTrack against that of the real-time position management (RPM) system as applied to respiratory gating in cardiac PET/CT studies.

METHODS

The list-mode data of 35 patients that were referred for ⁸² Rb myocardial perfusion studies were retrospectively processed with PeTrack to generate respiratory motion signals and triggers. Fifty acquisitions from the initial cohort, conducted under physiologic rest and stress, were considered for analysis. Respiratory-gated reconstructions were performed using reconstruction software provided by the vendor. The respiratory signals and triggers of the gating systems were compared using quantitative measurements of the respiratory signal correlation, median, and interquartiles range (IQR) of observed respiratory rates and the relative frequencies of respiratory cycle outliers. Quantitative measurements of left-ventricular wall thicknesses and motion due to respiration were also compared. Real-time position management signals were also retrospectively processed using the trigger detection method of PeTrack for a third comparator ("RPMretro") that allowed direct comparison of the motion tracking quality independently of differences in the trigger detection methods. The comparison of PeTrack to the original RPM data represent a practical comparison of the two systems, whereas that of PeTrack and RPMretro represents an equal comparison of the two. Nongated images were also reconstructed to provide reference left-ventricular wall thicknesses. LV wall thickness and motion measurements were repeated for a subset of cases with motion ≥7 mm as image artifacts were expected to be more severe in these cases.

RESULTS

A significant correlation (P < 0.05) was observed between the RPM and PeTrack respiratory signals in 45/50 acquisitions; the mean correlation coefficient was 0.43. Similar results were found between PeTrack and RPMretro. No significant difference was observed between the RPM and PeTrack with respect to median respiratory rates and the percentage of respiratory cycles outliers. Respiratory rate variability (IQR) was significantly higher with PeTrack vs RPM (P = 0.002) and RPMretro (P = 0.04). Both PeTrack and RPM had a significant increase in the percentage of respiratory rate outliers compared to RPMretro (P < 0.001 and P = 0.001, respectively). All methods indicated significant differences in LV thickness compared to nongated images (P < 0.02). LV thickness was significantly larger for PeTrack compared to RPMretro in the highest motion subset (P = 0.009). Images gated with RPMretro showed significant increases in motion compared to both PeTrack (P < 0.001) and prospective RPM (P = 0.002). In the subset of highest motion cases, the difference between RPM and RPMretro was no longer present.

CONCLUSIONS

The data-driven PeTrack algorithm performed similarly to the well-established RPM system for respiratory gating of ⁸² Rb cardiac perfusion PET/CT studies. Real-time position management performance improved after retrospective processing and led to enhanced performance compared to both PeTrack and prospective RPM. With further development PeTrack has the potential to reduce the need for ancillary hardware systems to monitor respiratory motion.

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.

Quantitative PET/MR imaging of lung cancer in the presence of artifacts in the MR-based attenuation correction maps

Background

Positron emission tomography (PET)/magnetic resonance (MR) imaging may become increasingly important for assessing tumor therapy response. A prerequisite for quantitative PET/MR imaging is reliable and repeatable MR-based attenuation correction (AC).

Purpose

To investigate the frequency and test–retest reproducibility of artifacts in MR-AC maps in a lung cancer patient cohort and to study the impact of artifact corrections on PET-based tumor quantification.

Material and Methods

Twenty-five lung cancer patients underwent single-day, test–retest, 18F-fluorodeoxyglucose (FDG) PET/MR imaging. The acquired MR-AC maps were inspected for truncation, susceptibility, and tissue inversion artifacts. An anatomy-based bone template and a PET-based estimation of truncated arms were employed, while susceptibility artifacts were corrected manually. We report the frequencies of artifacts and the relative difference (RD) on standardized uptake value (SUV) based quantification in PET images reconstructed with the corrected AC maps.

Results

Truncation artifacts were found in all 50 acquisitions (100%), while susceptibility and tissue inversion artifacts were observed in six (12%) and 26 (52%) of the scans, respectively. The RD in lung tumor SUV was < 5% from bone and truncation corrections, while up to 20% RD was introduced after susceptibility artifact correction, with large inconsistencies between test–retest scans.

Conclusion

The absence of bone and truncation artifacts have limited effect on the PET quantification of lung lesions. In contrast, susceptibility artifacts caused significant and inconsistent underestimations of the lung tumor SUVs, between test–retest scans. This may have clinical implications for patients undergoing serial imaging for tumor therapy response assessment.

Characterization of continuous bed motion effects on patient breathing and respiratory motion correction in PET/CT imaging

Continuous bed motion (CBM) was recently introduced as an alternative to step‐and‐shoot (SS) mode for PET/CT data acquisition. In CBM, the patient is continuously advanced into the scanner at a preset speed, whereas in SS, the patient is imaged in overlapping bed positions. Previous investigations have shown that patients preferred CBM over SS for PET data acquisition. In this study, we investigated the effect of CBM versus SS on patient breathing and respiratory motion correction. One hundred patients referred for PET/CT were scanned using a Siemens mCT scanner. Patient respiratory waveforms were recorded using an Anzai system and analyzed using four methods: Methods 1 and 2 measured the coefficient of variation (COV) of the respiratory cycle duration (RCD) and amplitude (RCA). Method 3 measured the respiratory frequency signal prominence (RSP) and method 4 measured the width of the HDChest optimal gate (OG) window when using a 35% duty cycle. Waveform analysis was performed over the abdominothoracic region which exhibited the greatest respiratory motion and the results were compared between CBM and SS. Respiratory motion correction was assessed by comparing the ratios of SUVmax, SUVpeak, and CNR of focal FDG uptake, as well as Radiologists’ visual assessment of corresponding image quality of motion corrected and uncorrected images for both acquisition modes. The respiratory waveforms analysis showed that the RCD and RCA COV were 3.7% and 33.3% lower for CBM compared to SS, respectively, while the RSP and OG were 30.5% and 2.0% higher, respectively. Image analysis on the other hand showed that SUVmax, SUVpeak, and CNR were 8.5%, 4.5%, and 3.4% higher for SS compared to CBM, respectively, while the Radiologists’ visual comparison showed similar image quality between acquisition modes. However, none of the results showed statistically significant differences between SS and CBM, suggesting that motion correction is not impacted by acquisition mode.

Management implications of fluorodeoxyglucose positron emission tomography/magnetic resonance in untreated intrahepatic cholangiocarcinoma

PURPOSE

Intrahepatic cholangiocarcinoma (ICC) is associated with a poor prognosis with surgical resection offering the best chance for long-term survival and potential cure. However, in up to 36% of patients who undergo surgery, more extensive disease is found at time of operation requiring cancellation of surgery. PET/MR is a novel hybrid technology that might improve local and whole-body staging in ICC patients, potentially influencing clinical management. This study was aimed to investigate the possible management implications of PET/MR, relative to conventional imaging, in patients affected by untreated intrahepatic cholangiocarcinoma.

METHODS

Retrospective review of the clinicopathologic features of 37 patients with iCCC, who underwent PET/MR between September 2015 and August 2018, was performed to investigate the management implications that PET/MR had exerted on the affected patients, relative to conventional imaging.

RESULTS

Of the 37 patients enrolled, median age 63.5 years, 20 (54%) were female. The same day PET/CT was performed in 26 patients. All patients were iCCC-treatment-naïve. Conventional imaging obtained as part of routine clinical care demonstrated early-stage resectable disease for 15 patients and advanced stage disease beyond the scope of surgical resection for 22. PET/MR modified the clinical management of 11/37 (29.7%) patients: for 5 patients (13.5%), the operation was cancelled due to identification of additional disease, while 4 "inoperable" patients (10.8%) underwent an operation. An additional 2 patients (5.4%) had a significant change in their operative plan based on PET/MR.

CONCLUSIONS

When compared with standard imaging, PET/MR significantly influenced the treatment plan in 29.7% of patients with iCCC.

TRIAL REGISTRATION

2018P001334.

Body motion detection and correction in cardiac PET: Phantom and human studies

PURPOSE

Patient body motion during a cardiac positron emission tomography (PET) scan can severely degrade image quality. We propose and evaluate a novel method to detect, estimate, and correct body motion in cardiac PET.

METHODS

Our method consists of three key components: motion detection, motion estimation, and motion-compensated image reconstruction. For motion detection, we first divide PET list-mode data into 1-s bins and compute the center of mass (COM) of the coincidences' distribution in each bin. We then compute the covariance matrix within a 25-s sliding window over the COM signals inside the window. The sum of the eigenvalues of the covariance matrix is used to separate the list-mode data into "static" (i.e., body motion free) and "moving" (i.e. contaminated by body motion) frames. Each moving frame is further divided into a number of evenly spaced sub-frames (referred to as "sub-moving" frames), in which motion is assumed to be negligible. For motion estimation, we first reconstruct the data in each static and sub-moving frame using a rapid back-projection technique. We then select the longest static frame as the reference frame and estimate elastic motion transformations to the reference frame from all other static and sub-moving frames using nonrigid registration. For motion-compensated image reconstruction, we reconstruct all the list-mode data into a single image volume in the reference frame by incorporating the estimated motion transformations in the PET system matrix. We evaluated the performance of our approach in both phantom and human studies.

RESULTS

Visually, the motion-corrected (MC) PET images obtained using the proposed method have better quality and fewer motion artifacts than the images reconstructed without motion correction (NMC). Quantitative analysis indicates that MC yields higher myocardium to blood pool concentration ratios. MC also yields sharper myocardium than NMC.

CONCLUSIONS

The proposed body motion correction method improves image quality of cardiac PET.

A Computational Framework for Data Fusion in MEMS-Based Cardiac and Respiratory Gating

Dual cardiac and respiratory gating is a well-known technique for motion compensation in nuclear medicine imaging. In this study, we present a new data fusion framework for dual cardiac and respiratory gating based on multidimensional microelectromechanical (MEMS) motion sensors. Our approach aims at robust estimation of the chest vibrations, that is, high-frequency precordial vibrations and low-frequency respiratory movements for prospective gating in positron emission tomography (PET), computed tomography (CT), and radiotherapy. Our sensing modality in the context of this paper is a single dual sensor unit, including accelerometer and gyroscope sensors to measure chest movements in three different orientations. Since accelerometer- and gyroscope-derived respiration signals represent the inclination of the chest, they are similar in morphology and have the same units. Therefore, we use principal component analysis (PCA) to combine them into a single signal. In contrast to this, the accelerometer- and gyroscope-derived cardiac signals correspond to the translational and rotational motions of the chest, and have different waveform characteristics and units. To combine these signals, we use independent component analysis (ICA) in order to obtain the underlying cardiac motion. From this cardiac motion signal, we obtain the systolic and diastolic phases of cardiac cycles by using an adaptive multi-scale peak detector and a short-time autocorrelation function. Three groups of subjects, including healthy controls (n = 7), healthy volunteers (n = 12), and patients with a history of coronary artery disease (n = 19) were studied to establish a quantitative framework for assessing the performance of the presented work in prospective imaging applications. The results of this investigation showed a fairly strong positive correlation (average r = 0.73 to 0.87) between the MEMS-derived (including corresponding PCA fusion) respiration curves and the reference optical camera and respiration belt sensors. Additionally, the mean time offset of MEMS-driven triggers from camera-driven triggers was 0.23 to 0.3 ± 0.15 to 0.17 s. For each cardiac cycle, the feature of the MEMS signals indicating a systolic time interval was identified, and its relation to the total cardiac cycle length was also reported. The findings of this study suggest that the combination of chest angular velocity and accelerations using ICA and PCA can help to develop a robust dual cardiac and respiratory gating solution using only MEMS sensors. Therefore, the methods presented in this paper should help improve predictions of the cardiac and respiratory quiescent phases, particularly with the clinical patients. This study lays the groundwork for future research into clinical PET/CT imaging based on dual inertial sensors.

PET/CT-guided biopsy with respiratory motion correction

PURPOSE

Given the ability of positron emission tomography (PET) imaging to localize malignancies in heterogeneous tumors and tumors that lack an X-ray computed tomography (CT) correlate, combined PET/CT-guided biopsy may improve the diagnostic yield of biopsies. However, PET and CT images are naturally susceptible to problems due to respiratory motion, leading to imprecise tumor localization and shape distortion. To facilitate PET/CT-guided needle biopsy, we developed and investigated the feasibility of a workflow that allows to bring PET image guidance into interventional CT suite while accounting for respiratory motion.

METHODS

The performance of PET/CT respiratory motion correction using registered and summed phases method was evaluated through computer simulations using the mathematical 4D extended cardiac-torso phantom, with motion simulated from real respiratory traces. The performance of PET/CT-guided biopsy procedure was evaluated through operation on a physical anthropomorphic phantom. Vials containing radiolabeled 18F-fluorodeoxyglucose were placed within the physical phantom thorax as biopsy targets. We measured the average distance between target center and the simulated biopsy location among multiple trials to evaluate the biopsy localization accuracy.

RESULTS

The computer simulation results showed that the RASP method generated PET images with a significantly reduced noise of 0.10 ± 0.01 standardized uptake value (SUV) as compared to an end-of-expiration image noise of 0.34 ± 0.04 SUV. The respiratory motion increased the apparent liver lesion size from 5.4 ± 1.1 to 35.3 ± 3.0 cc. The RASP algorithm reduced this to 15.7 ± 3.7 cc. The distances between the centroids for the static image lesion and two moving lesions in the liver and lung, when reconstructed with the RASP algorithm, were 0.83 ± 0.72 mm and 0.42 ± 0.72 mm. For the ungated imaging, these values increased to 3.48 ± 1.45 mm and 2.5 ± 0.12 mm, respectively. For the ungated imaging, this increased to 1.99 ± 1.72 mm. In addition, the lesion activity estimation (e.g., SUV) was accurate and constant for images reconstructed using the RASP algorithm, whereas large activity bias and variations (± 50%) were observed for lesions in the ungated images. The physical phantom studies demonstrated a biopsy needle localization error of 2.9 ± 0.9 mm from CT. Combined with the localization errors due to respiration for the PET images from simulations, the overall estimated lesion localization error would be 3.08 mm for PET-guided biopsies images using RASP and 3.64 mm when using ungated PET images. In other words, RASP reduced the localization error by approximately 0.6 mm. The combined error analysis showed that replacing the standard end-of-expiration images with the proposed RASP method in PET/CT-guided biopsy workflow yields comparable lesion localization accuracy and reduced image noise.

CONCLUSION

The RASP method can produce PET images with reduced noise, attenuation artifacts and respiratory motion, resulting in more accurate lesion localization. Testing the PET/CT-guided biopsy workflow using computer simulation and physical phantoms with respiratory motion, we demonstrated that guided biopsy procedure with the RASP method can benefit from improved PET image quality due to noise reduction, without compromising the accuracy of lesion localization.

Self-Gated Respiratory Motion Rejection for Optoacoustic Tomography

Respiratory motion in living organisms is known to result in image blurring and loss of resolution, chiefly due to the lengthy acquisition times of the corresponding image acquisition methods. Optoacoustic tomography can effectively eliminate in vivo motion artifacts due to its inherent capacity for collecting image data from the entire imaged region following a single nanoseconds-duration laser pulse. However, multi-frame image analysis is often essential in applications relying on spectroscopic data acquisition or for scanning-based systems. Thereby, efficient methods to correct for image distortions due to motion are imperative. Herein, we demonstrate that efficient motion rejection in optoacoustic tomography can readily be accomplished by frame clustering during image acquisition, thus averting excessive data acquisition and post-processing. The algorithm’s efficiency for two- and three-dimensional imaging was validated with experimental whole-body mouse data acquired by spiral volumetric optoacoustic tomography (SVOT) and full-ring cross-sectional imaging scanners.