scholarly journals Direct comparison of [18F]FDG brain images acquired from a phantom and patients using SiPM- and PMT-PET/CT

2020 ◽  
Author(s):  
Kei Wagatsuma ◽  
Muneyuki Sakata ◽  
Kenji Ishibashi ◽  
Akira Hirayama ◽  
Hirofumi Kawakami ◽  
...  

Abstract Background Silicon photomultiplier-positron emission tomography (SiPM-PET) has better sensitivity, spatial resolution, and timing resolution than photomultiplier tubes (PMT)-PET. The present study aimed to clarify the advantages of SiPM-PET in 18F-fluoro-2-deoxy-D-glucose ([18F]FDG) brain imaging in a head-to-head comparison with PMT-PET in phantom and clinical studies. Methods Image contrast was calculated from images acquired from a Hoffman 3D brain phantom and image noise and uniformity were calculated from pooled images acquired from a pool phantom using SiPM- and PMT-PET. Sequential PMT-PET and SiPM-PET [18F]FDG images were acquired over a period of 10 min from 22 individuals. All images were separately normalized to a standard [18F]FDG PET template, then mean standardized uptake values (SUVmean) and Z-score were calculated by MIMneuro and Cortex ID Suite, respectively. Results Image contrast, image noise, and uniformity in SiPM-PET changed 27.5%, -2.1%, and − 138.2% from PMT-PET, respectively. These physical indices of SiPM-PET satisfied the criteria for acceptable image quality published by the Japanese Society of Nuclear Medicine of > 55%, ≤ 15% and ≤ 0.0249, respectively. The residual background count was reduced with time-of-flight algorithm especially in SiPM-PET. The SUVmean using SiPM-PET was significantly higher than PMT-PET and did not correlate with a time delay. Z-scores were also significantly higher in images acquired from SiPM-PET (except for the bilateral posterior cingulate) than PMT-PET because the peak signal that was extracted by the calculation of Z-score in Cortex ID Suite was raised. Conclusions The better spatial and timing resolution, and sensitivity in SiPM-PET were contributed to better image contrast, image noise, and uniformity on brain [18F]FDG images. SiPM-PET offers better quality and more accurate quantitation of brain PET images. The SUVmean and Z-score in SiPM-PET was higher than PMT-PET. [18F]FDG images acquired using SiPM-PET will help to improve diagnostic outcomes based on the statistical image analysis because the SiPM-PET was more localized the distribution of glucose metabolism on Z-score maps.

2020 ◽  
Author(s):  
Kei Wagatsuma ◽  
Muneyuki Sakata ◽  
Kenji Ishibashi ◽  
Akira Hirayama ◽  
Hirofumi Kawakami ◽  
...  

Abstract Background: Silicon photomultiplier-positron emission tomography (SiPM-PET) has better sensitivity, spatial resolution, and timing resolution than photomultiplier tube (PMT)-PET. The present study aimed to clarify the advantages of SiPM-PET in 18F-fluoro-2-deoxy-D-glucose ([18F]FDG) brain imaging in a head-to-head comparison with PMT-PET in phantom and clinical studies.Methods: Contrast was calculated from images acquired from a Hoffman 3D brain phantom and image noise and uniformity were calculated from images acquired from a pool phantom using SiPM- and PMT-PET. Sequential PMT-PET and SiPM-PET [18F]FDG images were acquired over a period of 10 min from 22 controls and 10 patients. All images were separately normalized to a standard [18F]FDG PET template, then mean standardized uptake values (SUVmean) and Z-score were calculated using MIMneuro and CortexID Suite, respectively.Results: Image contrast, image noise, and uniformity in SiPM-PET changed 19.2%, 3.5%, and -40.0% from PMT-PET, respectively. These physical indices of both PET scanners satisfied the criteria for acceptable image quality published by the Japanese Society of Nuclear Medicine of contrast > 55%, CV ≤ 15% and SD ≤ 0.0249, respectively. Contrast was 70.0% for SiPM-PET without TOF and 59.5% for PMT-PET without TOF. The TOF improved contrast by 3.5% in SiPM-PET. The SUVmean using SiPM-PET was significantly higher than PMT-PET and did not correlate with a time delay. Z-scores were also significantly higher in images acquired from SiPM-PET (except for the bilateral posterior cingulate) than PMT-PET because the peak signal that was extracted by the calculation of Z-score in CortexID Suite was increased. The hypometabolic area in statistical maps was reduced and localized using SiPM-PET. The trend was independent of whether the images were derived from controls or patients.Conclusions: The improved spatial resolution and sensitivity of SiPM-PET contributed to better image contrast and uniformity in brain [18F]FDG images. The SiPM-PET offers better quality and more accurate quantitation of brain PET images. The SUVmean and Z-scores were higher in SiPM-PET than PMT-PET due to improved PVE. [18F]FDG images acquired using SiPM-PET will help to improve diagnostic outcomes based on statistical image analysis because SiPM-PET would localize the distribution of glucose metabolism on Z-score maps.


2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Kei Wagatsuma ◽  
Muneyuki Sakata ◽  
Kenji Ishibashi ◽  
Akira Hirayama ◽  
Hirofumi Kawakami ◽  
...  

Abstract Background Silicon photomultiplier-positron emission tomography (SiPM-PET) has better sensitivity, spatial resolution, and timing resolution than photomultiplier tube (PMT)-PET. The present study aimed to clarify the advantages of SiPM-PET in 18F-fluoro-2-deoxy-D-glucose ([18F]FDG) brain imaging in a head-to-head comparison with PMT-PET in phantom and clinical studies. Methods Contrast was calculated from images acquired from a Hoffman 3D brain phantom, and image noise and uniformity were calculated from images acquired from a pool phantom using SiPM- and PMT-PET. Sequential PMT-PET and SiPM-PET [18F]FDG images were acquired over a period of 10 min from 22 controls and 10 patients. All images were separately normalized to a standard [18F]FDG PET template, then the mean standardized uptake values (SUVmean) and Z-score were calculated using MIMneuro and CortexID Suite, respectively. Results Image contrast, image noise, and uniformity in SiPM-PET changed 19.2, 3.5, and − 40.0% from PMT-PET, respectively. These physical indices of both PET scanners satisfied the criteria for acceptable image quality published by the Japanese Society of Nuclear Medicine of contrast > 55%, CV ≤ 15%, and SD ≤ 0.0249, respectively. Contrast was 70.0% for SiPM-PET without TOF and 59.5% for PMT-PET without TOF. The TOF improved contrast by 3.5% in SiPM-PET. The SUVmean using SiPM-PET was significantly higher than PMT-PET and did not correlate with a time delay. Z-scores were also significantly higher in images acquired from SiPM-PET (except for the bilateral posterior cingulate) than PMT-PET because the peak signal that was extracted by the calculation of Z-score in CortexID Suite was increased. The hypometabolic area in statistical maps was reduced and localized using SiPM-PET. The trend was independent of whether the images were derived from controls or patients. Conclusions The improved spatial resolution and sensitivity of SiPM-PET contributed to better image contrast and uniformity in brain [18F]FDG images. The SiPM-PET offers better quality and more accurate quantitation of brain PET images. The SUVmean and Z-scores were higher in SiPM-PET than PMT-PET due to improved PVE. [18F]FDG images acquired using SiPM-PET will help to improve diagnostic outcomes based on statistical image analysis because SiPM-PET would localize the distribution of glucose metabolism on Z-score maps.


2020 ◽  
Author(s):  
Kei Wagatsuma ◽  
Muneyuki Sakata ◽  
Kenji Ishibashi ◽  
Akira Hirayama ◽  
Hirofumi Kawakami ◽  
...  

Abstract Background: The silicon photomultiplier-positron emission tomography (SiPM-PET) developed by GE Healthcare has better sensitivity, spatial resolution, and timing resolution than photomultiplier tubes (PMT)-PET. The present study aimed to clarify the advantages of SiPM-PET in 18F-fluoro-2-deoxy-D-glucose ([18F]FDG) brain imaging in a head-to-head comparison with PMT-PET in phantom and clinical studies. Methods: Image contrast was calculated from images acquired from a Hoffman 3D brain phantom and image noise and uniformity were calculated from pooled images acquired from a pool phantom using SiPM- and PMT-PET. Sequential PMT-PET and SiPM-PET [18F]FDG images were acquired over a period of 10 min from 22 controls and 10 patients. All images were separately normalized to a standard [18F]FDG PET template, then mean standardized uptake values (SUVmean) and Z-score were calculated by MIMneuro and CortexID Suite, respectively. Results: Image contrast, image noise, and uniformity in SiPM-PET changed 19.2%, 3.5%, and -40.0% from PMT-PET, respectively. These physical indices of both PET scanners satisfied the criteria for acceptable image quality published by the Japanese Society of Nuclear Medicine of > 55%, ≤ 15% and ≤ 0.0249, respectively. The contrast in SiPM-PET was slightly improved using TOF. The SUVmean using SiPM-PET was significantly higher than PMT-PET and did not correlate with a time delay. Z-scores were also significantly higher in images acquired from SiPM-PET (except for the bilateral posterior cingulate) than PMT-PET because the peak signal that was extracted by the calculation of Z-score in CortexID Suite was raised. The area of hypometabolism in statistical maps was reduced and localized by SiPM-PET compared with PMT-PET regardless of whether the images were derived from controls or patients. Conclusions: The improved spatial resolution and sensitivity of SiPM-PET contributed to better image contrast and uniformity in brain [18F]FDG images. The SiPM-PET offers better quality and more accurate quantitation of brain PET images. The SUVmean and Z-score in SiPM-PET was higher than PMT-PET due to improving the PVEs. [18F]FDG images acquired using SiPM-PET will help to improve diagnostic outcomes based on statistical image analysis becausethe SiPM-PET would localize the distribution of glucose metabolism on Z-score maps.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Johan Economou Lundeberg ◽  
Jenny Oddstig ◽  
Ulrika Bitzén ◽  
Elin Trägårdh

Abstract Background Lung cancer is one of the most common cancers in the world. Early detection and correct staging are fundamental for treatment and prognosis. Positron emission tomography with computed tomography (PET/CT) is recommended clinically. Silicon (Si) photomultiplier (PM)-based PET technology and new reconstruction algorithms are hoped to increase the detection of small lesions and enable earlier detection of pathologies including metastatic spread. The aim of this study was to compare the diagnostic performance of a SiPM-based PET/CT (including a new block-sequential regularization expectation maximization (BSREM) reconstruction algorithm) with a conventional PM-based PET/CT including a conventional ordered subset expectation maximization (OSEM) reconstruction algorithm. The focus was patients admitted for 18F-fluorodeoxyglucose (FDG) PET/CT for initial diagnosis and staging of suspected lung cancer. Patients were scanned on both a SiPM-based PET/CT (Discovery MI; GE Healthcare, Milwaukee, MI, USA) and a PM-based PET/CT (Discovery 690; GE Healthcare, Milwaukee, MI, USA). Standardized uptake values (SUV) and image interpretation were compared between the two systems. Image interpretations were further compared with histopathology when available. Results Seventeen patients referred for suspected lung cancer were included in our single injection, dual imaging study. No statically significant differences in SUVmax of suspected malignant primary tumours were found between the two PET/CT systems. SUVmax in suspected malignant intrathoracic lymph nodes was 10% higher on the SiPM-based system (p = 0.026). Good consistency (14/17 cases) between the PET/CT systems were found when comparing simplified TNM staging. The available histology results did not find any obvious differences between the systems. Conclusion In a clinical setting, the new SiPM-based PET/CT system with a new BSREM reconstruction algorithm provided a higher SUVmax for suspected lymph node metastases compared to the PM-based system. However, no improvement in lung cancer detection was seen.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhifang Wu ◽  
Binwei Guo ◽  
Bin Huang ◽  
Xinzhong Hao ◽  
Ping Wu ◽  
...  

AbstractTo evaluate the quantification accuracy of different positron emission tomography-computed tomography (PET/CT) reconstruction algorithms, we measured the recovery coefficient (RC) and contrast recovery (CR) in phantom studies. The results played a guiding role in the partial-volume-effect correction (PVC) for following clinical evaluations. The PET images were reconstructed with four different methods: ordered subsets expectation maximization (OSEM), OSEM with time-of-flight (TOF), OSEM with TOF and point spread function (PSF), and Bayesian penalized likelihood (BPL, known as Q.Clear in the PET/CT of GE Healthcare). In clinical studies, SUVmax and SUVmean (the maximum and mean of the standardized uptake values, SUVs) of 75 small pulmonary nodules (sub-centimeter group: < 10 mm and medium-size group: 10–25 mm) were measured from 26 patients. Results show that Q.Clear produced higher RC and CR values, which can improve quantification accuracy compared with other methods (P < 0.05), except for the RC of 37 mm sphere (P > 0.05). The SUVs of sub-centimeter fludeoxyglucose (FDG)-avid pulmonary nodules with Q.Clear illustrated highly significant differences from those reconstructed with other algorithms (P < 0.001). After performing the PVC, highly significant differences (P < 0.001) still existed in the SUVmean measured by Q.Clear comparing with those measured by the other algorithms. Our results suggest that the Q.Clear reconstruction algorithm improved the quantification accuracy towards the true uptake, which potentially promotes the diagnostic confidence and treatment response evaluations with PET/CT imaging, especially for the sub-centimeter pulmonary nodules. For small lesions, PVC is essential.


2021 ◽  
Vol 11 (5) ◽  
pp. 1991
Author(s):  
Alexander P. Seiffert ◽  
Adolfo Gómez-Grande ◽  
Eva Milara ◽  
Sara Llamas-Velasco ◽  
Alberto Villarejo-Galende ◽  
...  

Amyloid positron emission tomography (PET) brain imaging with radiotracers like [18F]florbetapir (FBP) or [18F]flutemetamol (FMM) is frequently used for the diagnosis of Alzheimer’s disease. Quantitative analysis is usually performed with standardized uptake value ratios (SUVR), which are calculated by normalizing to a reference region. However, the reference region could present high variability in longitudinal studies. Texture features based on the grey-level co-occurrence matrix, also called Haralick features (HF), are evaluated in this study to discriminate between amyloid-positive and negative cases. A retrospective study cohort of 66 patients with amyloid PET images (30 [18F]FBP and 36 [18F]FMM) was selected and SUVRs and 6 HFs were extracted from 13 cortical volumes of interest. Mann–Whitney U-tests were performed to analyze differences of the features between amyloid positive and negative cases. Receiver operating characteristic (ROC) curves were computed and their area under the curve (AUC) was calculated to study the discriminatory capability of the features. SUVR proved to be the most significant feature among all tests with AUCs between 0.692 and 0.989. All HFs except correlation also showed good performance. AUCs of up to 0.949 were obtained with the HFs. These results suggest the potential use of texture features for the classification of amyloid PET images.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Junichi Tsuchiya ◽  
Kota Yokoyama ◽  
Ken Yamagiwa ◽  
Ryosuke Watanabe ◽  
Koichiro Kimura ◽  
...  

Abstract Background Deep learning (DL)-based image quality improvement is a novel technique based on convolutional neural networks. The aim of this study was to compare the clinical value of 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) images obtained with the DL method with those obtained using a Gaussian filter. Methods Fifty patients with a mean age of 64.4 (range, 19–88) years who underwent 18F-FDG PET/CT between April 2019 and May 2019 were included in the study. PET images were obtained with the DL method in addition to conventional images reconstructed with three-dimensional time of flight-ordered subset expectation maximization and filtered with a Gaussian filter as a baseline for comparison. The reconstructed images were reviewed by two nuclear medicine physicians and scored from 1 (poor) to 5 (excellent) for tumor delineation, overall image quality, and image noise. For the semi-quantitative analysis, standardized uptake values in tumors and healthy tissues were compared between images obtained using the DL method and those obtained with a Gaussian filter. Results Images acquired using the DL method scored significantly higher for tumor delineation, overall image quality, and image noise compared to baseline (P < 0.001). The Fleiss’ kappa value for overall inter-reader agreement was 0.78. The standardized uptake values in tumor obtained by DL were significantly higher than those acquired using a Gaussian filter (P < 0.001). Conclusions Deep learning method improves the quality of PET images.


2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Hans-Jonas Meyer ◽  
Sandra Purz ◽  
Osama Sabri ◽  
Alexey Surov

Multimodal imaging has been increasingly used in oncology, especially in cervical cancer. By using a simultaneous positron emission (PET) and magnetic resonance imaging (MRI, PET/MRI) approach, PET and MRI can be obtained at the same time which minimizes motion artefacts and allows an exact imaging fusion, which is especially important in anatomically complex regions like the pelvis. The associations between functional parameters from MRI and 18F-FDG-PET reflecting different tumor aspects are complex with inconclusive results in cervical cancer. The present study correlates histogram analysis and 18F-FDG-PET parameters derived from simultaneous FDG-PET/MRI in cervical cancer. Overall, 18 female patients (age range: 32–79 years) with histopathologically confirmed squamous cell cervical carcinoma were retrospectively enrolled. All 18 patients underwent a whole-body simultaneous 18F-FDG-PET/MRI, including diffusion-weighted imaging (DWI) using b-values 0 and 1000 s/mm2. Apparent diffusion coefficient (ADC) histogram parameters included several percentiles, mean, min, max, mode, median, skewness, kurtosis, and entropy. Furthermore, mean and maximum standardized uptake values (SUVmean and SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were estimated. No statistically significant correlations were observed between SUVmax or SUVmean and ADC histogram parameters. TLG correlated inversely with p25 (r=−0.486,P=0.041), p75 (r=−0.490,P=0.039), p90 (r=−0.513,P=0.029), ADC median (r=−0.497,P=0.036), and ADC mode (r=−0.546,P=0.019). MTV also showed significant correlations with several ADC parameters: mean (r=−0.546,P=0.019), p10 (r=−0.473,P=0.047), p25 (r=−0.569,P=0.014), p75 (r=−0.576,P=0.012), p90 (r=−0.585,P=0.011), ADC median (r=−0.577,P=0.012), and ADC mode (r=−0.597,P=0.009). ADC histogram analysis and volume-based metabolic 18F-FDG-PET parameters are related to each other in cervical cancer.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Hongkai Wang ◽  
Yang Tian ◽  
Yang Liu ◽  
Zhaofeng Chen ◽  
Haoyu Zhai ◽  
...  

AbstractStatistical Parametric Mapping (SPM) is a computational approach for analysing functional brain images like Positron Emission Tomography (PET). When performing SPM analysis for different patient populations, brain PET template images representing population-specific brain morphometry and metabolism features are helpful. However, most currently available brain PET templates were constructed using the Caucasian data. To enrich the family of publicly available brain PET templates, we created Chinese-specific template images based on 116 [18F]-fluorodeoxyglucose ([18F]-FDG) PET images of normal participants. These images were warped into a common averaged space, in which the mean and standard deviation templates were both computed. We also developed the SPM analysis programmes to facilitate easy use of the templates. Our templates were validated through the SPM analysis of Alzheimer’s and Parkinson’s patient images. The resultant SPM t-maps accurately depicted the disease-related brain regions with abnormal [18F]-FDG uptake, proving the templates’ effectiveness in brain function impairment analysis.


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