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.

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.

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.

Performance Evaluation of a New Dedicated Breast PET Scanner Using NEMA NU4-2008 Standards.

UNLABELLED: The aim of this work was to evaluate the performance characteristics of a newly developed dedicated breast PET scanner, according to National Electrical Manufacturers Association (NEMA) NU 4-2008 standards. METHODS: The dedicated breast PET scanner consists of 4 layers of a 32 × 32 lutetium oxyorthosilicate-based crystal array, a light guide, and a 64-channel position-sensitive photomultiplier tube. The size of a crystal element is 1.44 × 1.44 × 4.5 mm. The detector ring has a large solid angle with a 185-mm aperture and an axial coverage of 155.5 mm. The energy windows at depth of interaction for the first and second layers are 400-800 keV, and those at the third and fourth layers are 100-800 keV. A fixed timing window of 4.5 ns was used for all acquisitions. Spatial resolution, sensitivity, counting rate capabilities, and image quality were evaluated in accordance with NEMA NU 4-2008 standards. Human imaging was performed in addition to the evaluation. RESULTS: Radial, tangential, and axial spatial resolution measured as minimal full width at half maximum approached 1.6, 1.7, and 2.0 mm, respectively, for filtered backprojection reconstruction and 0.8, 0.8, and 0.8 mm, respectively, for dynamic row-action maximum-likelihood algorithm reconstruction. The peak absolute sensitivity of the system was 11.2%. Scatter fraction at the same acquisition settings was 30.1% for the rat-sized phantom. Peak noise-equivalent counting rate and peak true rate for the ratlike phantom was 374 kcps at 25 MBq and 603 kcps at 31 MBq, respectively. In the image-quality phantom study, recovery coefficients and uniformity were 0.04-0.82 and 1.9%, respectively, for standard reconstruction mode and 0.09-0.97 and 4.5%, respectively, for enhanced-resolution mode. Human imaging provided high-contrast images with restricted background noise for standard reconstruction mode and high-resolution images for enhanced-resolution mode. CONCLUSION: The dedicated breast PET scanner has excellent spatial resolution and high sensitivity. The performance of the dedicated breast PET scanner is considered to be reasonable enough to support its use in breast cancer imaging.