Generating PET Attenuation Maps via Sim2Real Deep Learning-Based Tissue Composition Estimation Combined with MLACF

Deep learning (DL) has recently attracted attention for data processing in positron emission tomography (PET). Attenuation correction (AC) without computed tomography (CT) data is one of the interests. Here, we present, to our knowledge, the first attempt to generate an attenuation map of the human head via Sim2Real DL-based tissue composition estimation from model training using only the simulated PET dataset. The DL model accepts a two-dimensional non-attenuation-corrected PET image as input and outputs a four-channel tissue-composition map of soft tissue, bone, cavity, and background. Then, an attenuation map is generated by a linear combination of the tissue composition maps and, finally, used as input for scatter+random estimation and as an initial estimate for attenuation map reconstruction by the maximum likelihood attenuation correction factor (MLACF), i.e., the DL estimate is refined by the MLACF. Preliminary results using clinical brain PET data showed that the proposed DL model tended to estimate anatomical details inaccurately, especially in the neck-side slices. However, it succeeded in estimating overall anatomical structures, and the PET quantitative accuracy with DL-based AC was comparable to that with CT-based AC. Thus, the proposed DL-based approach combined with the MLACF is also a promising CT-less AC approach.

Impact of respiratory gating and ECG gating on 18F-FDG PET/CT for cardiac sarcoidosis

BACKGROUND

The aim of this study was to estimate the impact of respiratory and electrocardiogram (ECG)-gated FDG positron emission tomography (PET)/computed tomography (CT) on the diagnosis of cardiac sarcoidosis (CS).

METHODS AND RESULTS

Imaging from thirty-one patients was acquired on a PET/CT scanner equipped with a respiratory- and ECG-gating system. Non-gated PET images and three kinds of gated PET/CT images were created from identical list-mode clinical PET data: respiratory-gated PET during expiration (EX), ECG-gated PET at end diastole (ED), and ECG-gated PET at end systole (ES). The maximum standardized uptake value (SUVmax) and cardiac metabolic volume (CMV) were measured, and the locations of FDG accumulation were analyzed using a polar map. The mean SUVmax of the subjects was significantly higher after application of either respiratory-gated or ECG-gated reconstruction. Conversely, the mean CMV was significantly lower following the application of respiratory-gated or ECG-gated reconstruction. The segment showing maximum accumulation was shifted to the adjacent segment in 25.8%, 38.7%, and 41.9% of cases in EX, ED, and ES images, respectively.

CONCLUSION

In FDG PET/CT scanning for the diagnosis of CS, gated scanning is likely to increase quantitative accuracy, but the effect depends on the location and synchronization method.

Organ-Specific Positron Emission Tomography Scanners for Breast Imaging: Comparison between the Performances of Prior and Novel Models

The performances of photomultiplier tube (PMT)-based dedicated breast positron emission tomography (PET) and silicon photomultiplier tube (SiPM)-based time-of-flight (TOF) PET, which is applicable not only to breast imaging but also to head imaging, were compared using a phantom study. A cylindrical phantom containing four spheres (3–10 mm in diameter) filled with 18F-FDG at two signal-to-background ratios (SBRs), 4:1 and 8:1, was scanned. The phantom images, which were reconstructed using three-dimensional list-mode dynamic row-action maximum likelihood algorithm with various β-values and post-smoothing filters, were visually and quantitatively compared. Visual evaluation showed that the 3 mm sphere was more clearly visualized with higher β and smaller post-filters, while the background was noisier; SiPM-based TOF-PET was superior to PMT-based dbPET in sharpness, smoothness, and detectability, although the background was noisier at the SBR of 8:1. Quantitative evaluation revealed that the detection index (DI) and recovery coefficient (CRC) of SiPM-based TOF-PET images were higher than those of PMT-based PET images, despite a higher background coefficient of variation (CVBG). The two organ-specific PET systems showed that a 3 mm lesion in the breast could be visualized at the center of the detector, and there was less noise in the SiPM-based TOF-PET image.

High-Resolution Silicon Photomultiplier Time-of-Flight Dedicated Head PET System for Clinical Brain Studies

We acquired brain ¹⁸F-FDG and ¹⁸F-flutemetamol PET images using a time-of-flight system dedicated to the head (dhPET) and a conventional whole-body PET/CT (wbPET) system and evaluated the clinical superiority of dhPET over wbPET. Methods: There were 18 subjects for the ¹⁸F-FDG PET study and 17 subjects for the ¹⁸F-flutemetamol PET study. ¹⁸F-FDG PET images were first obtained using wbPET, followed by dhPET. ¹⁸F-flutemetamol PET images were first obtained using wbPET, followed by dhPET. Images acquired using dhPET and wbPET were compared by visual inspection, voxelwise analysis, and SUV ratio (SUVR). Results: All ¹⁸F-FDG and ¹⁸F-flutemetamol images acquired using dhPET were judged as visually better than those acquired using wbPET. The voxelwise analysis demonstrated that accumulations in the cerebellum, in the lateral occipital cortices, and around the central sulcus area in dhPET ¹⁸F-FDG images were lower than those in wbPET ¹⁸F-FDG images, whereas accumulations around the ventricle systems were higher in dhPET ¹⁸F-FDG images than those in wbPET ¹⁸F-FDG images. Accumulations in the cerebellar dentate nucleus, in the midbrain, in the lateral occipital cortices, and around the central sulcus area in dhPET images were lower than those in wbPET images, whereas accumulations around the ventricle systems were higher in dhPET ¹⁸F-flutemetamol images than those in wbPET ¹⁸F-flutemetamol images. The mean cortical SUVRs of ¹⁸F-FDG and ¹⁸F-flutemetamol dhPET images were significantly higher than those of ¹⁸F-FDG and ¹⁸F-flutemetamol wbPET images, respectively. Conclusion: The dhPET images had better image quality by visual inspection and higher SUVRs than wbPET images. Although there were several regional accumulation differences between dhPET and wbPET images, understanding this phenomenon will enable full use of the features of this dhPET system in clinical practice.

Evaluation of the performance of a high-resolution time-of-flight PET system dedicated to the head and breast according to NEMA NU 2-2012 standard

BACKGROUND

This study evaluated the physical performance of a positron emission tomography (PET) system dedicated to the head and breast according to the National Electrical Manufacturers Association (NEMA) NU2-2012 standard.

METHODS

The spatial resolution, sensitivity, scatter fraction, count rate characteristics, corrections for count losses and randoms, and image quality of the system were determined. All measurements were performed according to the NEMA NU2-2012 acquisition protocols, but image quality was assessed using a brain-sized phantom. Furthermore, scans of the three-dimensional (3D) Hoffmann brain phantom and mini-Derenzo phantom were acquired to allow visual evaluation of the imaging performance for small structures.

RESULTS

The tangential, radial, and axial full width at half maximum (FWHM) at a 10-mm offset in half the axial field of view were measured as 2.3, 2.5, and 2.9 mm, respectively. The average system sensitivity at the center of the field of view and at a 10-cm radial offset was 7.18 and 8.65 cps/kBq, respectively. The peak noise-equivalent counting rate was 35.2 kcps at 4.8 kBq/ml. The corresponding scatter fraction at the peak noise-equivalent counting rate was 46.8%. The peak true rate and scatter fraction at 8.6 kBq/ml were 127.8 kcps and 54.3%, respectively. The percent contrast value for a 10-mm sphere was approximately 50%. On the 3D Hoffman brain phantom image, the structures of the thin layers composing the phantom were visualized on the sagittal and coronal images. On the mini-Derenzo phantom, each of the 1.6-mm rods was clearly visualized.

CONCLUSION

Taken together, these results indicate that the head- and breast-dedicated PET system has high resolution and is well suited for clinical PET imaging.

Attenuation correction for phantom tests: an alternative to maximum-likelihood attenuation correction factor-based correction for clinical studies in time-of-flight PET

OBJECTIVES

This study evaluates the phantom attenuation correction (PAC) method as an alternative to maximum-likelihood attenuation correction factor (ML-ACF) correction in time-of-flight (TOF) brain positron emission tomography (PET) studies.

METHODS

In the PAC algorithm, a template emission image [Formula: see text] and a template attenuation coefficient image [Formula: see text] are prepared as a data set based on phantom geometry. Position-aligned attenuation coefficient image [Formula: see text] is derived by aligning [Formula: see text] using parameters that match the template emission image [Formula: see text] to measured emission image [Formula: see text]. Then, attenuation coefficient image [Formula: see text] combined with a headrest image is used for scatter and attenuation correction in the image reconstruction. To evaluate the PAC algorithm as an alternative to ML-ACF, Hoffman 3D brain and cylindrical phantoms were measured to obtain the image quality indexes of contrast and uniformity. These phantoms were also wrapped with a radioactive sheet to obtain attenuation coefficient images using ML-ACF. Emission images were reconstructed with attenuation correction by PAC and ML-ACF, and the results were compared using contrast and uniformity as well as visual assessment. CT attenuation correction (CT-AC) was also applied as a reference.

RESULTS

The contrast obtained by ML-ACF was slightly overestimated due to its unique experimental condition for applying ML-ACF in Hoffman 3D brain phantom but the uniformity was almost equivalent among ML-ACF, CT-AC, and PAC. PAC showed reasonable result without overestimation compared to ML-ACF and CT-AC.

CONCLUSIONS

PAC is an attenuation correction method that can ensure the performance in phantom test, and is considered to be a reasonable alternative to clinically used ML-ACF-based attenuation correction.

Metabolites Alterations and Liver Injury in Hepatic Encephalopathy Models Evaluated by Use of 7T-MRI

This study is to observe a thioacetamide (TAA) administered Hepatic encephalopathy (HE) model rats at three and ten days after TAA administration using liver MRI and brain MR Spectroscopy (MRS) by use of 7T-MRI. Forty-two Wistar rats (control group, n = 14) were intraperitoneally administered at 300 mg/kg (low-dose group, n = 14) or 400 mg/kg (high-dose group, n = 14) doses of TAA for induced of HE. At three days after TAA administration, glutamine (Gln) measured by MRS in high-dose and low-dose TAA groups showed significant increases in comparison to those of the control group (p < 0.05). Other metabolites measured by MRS showed no significant changes. Liver T1ρ and T2 relaxation times significantly increased three days after TAA injection compared to pre-injection. There was a correlation between Gln levels in the brain and the relaxation time of the liver. Furthermore, Gln levels and relaxation time changed depending on the TAA dose. The Gln concentration in the brain increased with the deterioration of liver function, as inferred from the prolonged relaxation time of the liver. The prolonged relaxation time of the liver corresponded with the level of Gln in the brain. Gln concentration for the alterations of brain metabolites and T1ρ relaxation time for the assessment of liver damage are useful markers for inter-organ association analysis in the HE model.

Initial evaluation of a new maximum-likelihood attenuation correction factor-based attenuation correction for time-of-flight brain PET

AIM

The aim of this study was to evaluate an image reconstruction algorithm, including a new maximum-likelihood attenuation correction factor (ML-ACF) for time of flight (TOF) brain positron emission tomography (PET).

METHODS

The implemented algorithm combines an ML-ACF method that simultaneously estimates both the emission image and attenuation sinogram from TOF emission data, and a scaling method based on anatomical features. To evaluate the algorithm's quantitative accuracy, three-dimensional brain phantom images were acquired and soft-tissue attenuation coefficients and emission values were analyzed.

RESULTS

The heterogeneous distributions of attenuation coefficients in soft tissue, skull, and nasal cavity were sufficiently visualized. The attenuation coefficient of soft tissue remained within 5% of theoretical value. Attenuation-corrected emission showed no lateral differences, and significant differences among soft tissue were within the error range.

CONCLUSION

The ML-ACF-based attenuation correction implemented for TOF brain PET worked well and obtained practical levels of accuracy.