scholarly journals Comparison between silicon photomultiplier-based and conventional PET/CT in patients with suspected lung cancer—a pilot study

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Johan Economou Lundeberg ◽  
Jenny Oddstig ◽  
Ulrika Bitzén ◽  
Elin Trägårdh
Keyword(s):  
Lung Cancer ◽  
Expectation Maximization ◽  
Image Interpretation ◽  
Imaging Study ◽  
Reconstruction Algorithm ◽  
Tnm Staging ◽  
Reconstruction Algorithms ◽  
Silicon Photomultiplier ◽  
Standardized Uptake Values ◽  
Pet Ct

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.

scholarly journals Phantom and clinical assessment of small pulmonary nodules using Q.Clear reconstruction on a silicon-photomultiplier-based time-of-flight PET/CT system

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhifang Wu ◽  
Binwei Guo ◽  
Bin Huang ◽  
Xinzhong Hao ◽  
Ping Wu ◽  
...  
Keyword(s):  
Time Of Flight ◽  
Pulmonary Nodules ◽  
Medium Size ◽  
Ct Reconstruction ◽  
Reconstruction Algorithms ◽  
Silicon Photomultiplier ◽  
Standardized Uptake Values ◽  
Pet Ct ◽  
Quantification Accuracy ◽  
Small Pulmonary Nodules

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.

scholarly journals Evaluation of 68Ga-PSMA PET/CT Images Acquired with a Reduced Scan Time Duration in Prostate Cancer Patients using the Digital Biograph Vision

2020 ◽  
Author(s):  
Manuel Weber ◽  
Regina Hofferber ◽  
Ken Herrmann ◽  
Wolfgang Peter Fendler ◽  
Maurizio Conti ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Image Reconstruction ◽  
Diagnostic Performance ◽  
Reconstruction Algorithm ◽  
Reconstruction Algorithms ◽  
Time Duration ◽  
Acquisition Protocol ◽  
Scan Time ◽  
Psma Pet ◽  
Pet Ct

Abstract Aim 68Ga-PSMA PET/CT allows for a superior detection of prostate cancer (PC) tissue, especially in context of a low tumor burden. Digital PET/CT bears the potential of reducing scan time duration / administered tracer activity due to, for instance, its higher sensitivity and improved time coincidence resolution. It might thereby expand 68Ga-PSMA PET/CT that is currently limited by 68Ge/68Ga-generator yield. Our aim was to clinically evaluate the influence of a reduced scan time duration in combination with different image reconstruction algorithms on the diagnostic performance. Methods Twenty PC patients (11 for biochemical recurrence, 5 for initial staging, 4 for metastatic disease) sequentially underwent 68Ga-PSMA PET/CT on a digital Siemens Biograph Vision. PET data were collected in continuous-bed-motion mode with a scan time duration of approximately 17 min (reference acquisition protocol) and 5 min (reduced acquisition protocol). 4 iterative reconstruction algorithms were applied using a time-of-flight (TOF) approach alone or combined with point-spread-function (PSF) correction, each with 2 or 4 iterations. To evaluate the diagnostic performance, the following metrics were chosen: (a) per-region detectability, (b) the tumor maximum and peak standardized uptake values (SUVmax and SUVpeak) and (c) image noise using the liver’s activity distribution. Results Overall, 98% of regions (91% of affected regions) were correctly classified in the reduced acquisition protocol independent of the image reconstruction algorithm. Two nodal lesions (each ≤ 4 mm) were not identified (leading to downstaging in 1/20 cases). Mean absolute percentage deviation of SUVmax (SUVpeak) was approximately 9% (6%) for each reconstruction algorithm. The mean image noise increased from 13–21% (4 iterations) and from 10–15% (2 iterations) for PSF + TOF and TOF images. Conclusions High agreement at 3.5-fold reduction of scan time in terms of per-region detection (98% of regions) and image quantification (mean deviation ≤ 10%) was demonstrated; however, small lesions can be missed in about 10% of patients leading to downstaging (T1N0M0 instead of T1N1M0) in 5% of patients. Our results suggest that a reduction of scan time duration or administered 68Ga-PSMA activities can be considered in metastatic patients, where missing small lesions would not impact patient management.

scholarly journals Lymph Node Maximum Uptake of 18F-ALF-NOTA-PRGD2 II PET/CT Predicts Lung Cancer Survival

2020 ◽  
Author(s):  
Yuchun Wei ◽  
Li Ma ◽  
Jinsong Zheng ◽  
Yanqing Pei ◽  
Xueting Qin ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cox Regression ◽  
Early Stage ◽  
Statistical Significance ◽  
Tnm Staging ◽  
Tnm Stage ◽  
Receiver Operating Curve ◽  
Cox Regression Analysis ◽  
Pet Ct

Abstract Background:Tumor angiogenesis plays a key role in tumor growth, development, and metastasis, so the exploratory study of tumor neovascularization imaging is one of the potential methods to predict survival. This study aims to examine the predictive capacity of 18F-ALF-NOTA-PRGD2 II (denoted 18F-Alfatide II) positron emission tomography (PET)/computed tomography (CT) before antitumor therapy (ATR) in patients with lung cancer.Results The median follow-up was 31 (1.3~57.0) months. Among the patients, 6 were lost to follow-up. The overall survival (OS) and progression-free survival (PFS) were 40.0 (3.50~57.0) months and 21.30 (2.0~56.0) months, respectively. The maximum uptake values (SUVmax) of the metastatic lymph nodes (SUVLN) and tumor node metastasis (TNM) staging were significant predictors of PFS and OS (all P<0.05) in a multivariate Cox regression analysis. Statistical significance was not reached by any other variable in the multivariate analysis. Receiver operating curve (ROC) analysis for survival revealed an area under the curve of 0.93 (P<0.001) for SUVLN and 0.96 for the TNM stage (P<0.001). The SUVLN and TNM stage cutoff values were 2.50 and II, and their sensitivity, specificity and positive and negative prediction were 77.42%, 80.0% and 82.76% and 74.07%; and 87.10%, 60.0% and 72.97% and 78.95%, respectively. Patients with a lower SUVLN and early stage had a longer PFS and OS (all P<0.05).Conclusions For lung cancer, low SUVLN and an early TNM stage (≤stage II) as assessed before ATR by 18F-alfatide II PET/CT represents a favorable subgroup with increased PFS and OS.

scholarly journals Impact of penalizing factor in a block-sequential regularized expectation maximization reconstruction algorithm for 18F-fluorocholine PET-CT regarding image quality and interpretation

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Mimmi Bjöersdorff ◽  
Jenny Oddstig ◽  
Nina Karindotter-Borgendahl ◽  
Helén Almquist ◽  
Sophia Zackrisson ◽  
...  
Keyword(s):  
Image Quality ◽  
Expectation Maximization ◽  
Reconstruction Algorithm ◽  
Pet Ct

scholarly journals Noise reduction using a Bayesian penalized-likelihood reconstruction algorithm on a time-of-flight PET-CT scanner

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Paulo R. R. V. Caribé ◽  
M. Koole ◽  
Yves D’Asseler ◽  
B. Van Den Broeck ◽  
S. Vandenberghe
Keyword(s):  
Noise Reduction ◽  
Expectation Maximization ◽  
Time Of Flight ◽  
Penalized Likelihood ◽  
Reconstruction Algorithm ◽  
Patient Data ◽  
Noise Levels ◽  
Patient Study ◽  
Phantom Data ◽  
Pet Ct

Abstract Purpose Q.Clear is a block sequential regularized expectation maximization (BSREM) penalized-likelihood reconstruction algorithm for PET. It tries to improve image quality by controlling noise amplification during image reconstruction. In this study, the noise properties of this BSREM were compared to the ordered-subset expectation maximization (OSEM) algorithm for both phantom and patient data acquired on a state-of-the-art PET/CT. Methods The NEMA IQ phantom and a whole-body patient study were acquired on a GE DMI 3-rings system in list mode and different datasets with varying noise levels were generated. Phantom data was evaluated using four different contrast ratios. These were reconstructed using BSREM with different β-factors of 300–3000 and with a clinical setting used for OSEM including point spread function (PSF) and time-of-flight (TOF) information. Contrast recovery (CR), background noise levels (coefficient of variation, COV), and contrast-to-noise ratio (CNR) were used to determine the performance in the phantom data. Findings based on the phantom data were compared with clinical data. For the patient study, the SUV ratio, metabolic active tumor volumes (MATVs), and the signal-to-noise ratio (SNR) were evaluated using the liver as the background region. Results Based on the phantom data for the same count statistics, BSREM resulted in higher CR and CNR and lower COV than OSEM. The CR of OSEM matches to the CR of BSREM with β = 750 at high count statistics for 8:1. A similar trend was observed for the ratios 6:1 and 4:1. A dependence on sphere size, counting statistics, and contrast ratio was confirmed by the CNR of the ratio 2:1. BSREM with β = 750 for 2.5 and 1.0 min acquisition has comparable COV to the 10 and 5.0 min acquisitions using OSEM. This resulted in a noise reduction by a factor of 2–4 when using BSREM instead of OSEM. For the patient data, a similar trend was observed, and SNR was reduced by at least a factor of 2 while preserving contrast. Conclusion The BSREM reconstruction algorithm allowed a noise reduction without a loss of contrast by a factor of 2–4 compared to OSEM reconstructions for all data evaluated. This reduction can be used to lower the injected dose or shorten the acquisition time.

scholarly journals Comparison of Regularized Reconstruction and Ordered Subset Expectation Maximization Reconstruction in the Diagnostics of Prostate Cancer Using Digital Time-of-Flight 68Ga-PSMA-11 PET/CT Imaging

Diagnostics ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 630
Author(s):  
Olof Jonmarker ◽  
Rimma Axelsson ◽  
Ted Nilsson ◽  
Stefan Gabrielson
Keyword(s):  
Prostate Cancer ◽  
Bone Metastasis ◽  
Lymph Nodes ◽  
Expectation Maximization ◽  
Reconstruction Algorithm ◽  
Lesion Detection ◽  
Detection Methods ◽  
Cohen’S Kappa ◽  
Cohen's Kappa ◽  
Pet Ct

In prostate cancer, the early detection of distant spread has been shown to be of importance. Prostate-specific membrane antigen (PSMA)-binding radionuclides in positron emission tomography (PET) is a promising method for precise disease staging. PET diagnostics depend on image reconstruction techniques, and ordered subset expectation maximization (OSEM) is the established standard. Block sequential regularized expectation maximization (BSREM) is a more recent reconstruction algorithm and may produce fewer equivocal findings and better lesion detection. Methods: 68Ga PSMA-11 PET/CT scans of patients with de novo or suspected recurrent prostate cancer were retrospectively reformatted using both the OSEM and BSREM algorithms. The lesions were counted and categorized by three radiologists. The intra-class correlation (ICC) and Cohen’s kappa for the inter-rater reliability were calculated. Results: Sixty-one patients were reviewed. BSREM identified slightly fewer lesions overall and fewer equivocal findings. ICC was excellent with regards to definitive lymph nodes and bone metastasis identification and poor with regards to equivocal metastasis irrespective of the reconstruction algorithm. The median Cohen’s kappa were 0.66, 0.74, 0.61 and 0.43 for OSEM and 0.61, 0.63, 0.66 and 0.53 for BSREM, with respect to the tumor, local lymph nodes, metastatic lymph nodes and bone metastasis detection, respectively. Conclusions: BSREM in the setting of 68Ga PMSA PET staging or restaging is comparable to OSEM.

scholarly journals Clinical evaluation of a block sequential regularized expectation maximization reconstruction algorithm in 18F-FDG PET/CT studies

2017 ◽  
Vol 38 (1) ◽  
pp. 57-66 ◽  
Author(s):  
Bert-Ram Sah ◽  
Paul Stolzmann ◽  
Gaspar Delso ◽  
Scott D. Wollenweber ◽  
Martin Hüllner ◽  
...  
Keyword(s):  
Clinical Evaluation ◽  
Expectation Maximization ◽  
Fdg Pet ◽  
Reconstruction Algorithm ◽  
Pet Ct ◽  
18F Fdg ◽  
Fdg Pet Ct ◽  
Ct Studies

scholarly journals Direct comparison of brain [18F]FDG images acquired by SiPM-based and PMT-based PET/CT: phantom and clinical studies

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Kei Wagatsuma ◽  
Muneyuki Sakata ◽  
Kenji Ishibashi ◽  
Akira Hirayama ◽  
Hirofumi Kawakami ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Clinical Studies ◽  
Image Noise ◽  
Image Contrast ◽  
Silicon Photomultiplier ◽  
Timing Resolution ◽  
Standardized Uptake Values ◽  
Positron Emission ◽  
Pet Ct ◽  
Pet Scanners

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.

scholarly journals Evaluation of [68Ga]Ga-PSMA PET/CT Images Acquired with a Reduced Scan Time Duration in Prostate Cancer Patients using the Digital Biograph Vision

2020 ◽  
Author(s):  
Manuel Weber ◽  
Walter Jentzen ◽  
Regina Hofferber ◽  
Ken Herrmann ◽  
Wolfgang Peter Fendler ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Image Reconstruction ◽  
Cancer Patients ◽  
Diagnostic Performance ◽  
Reconstruction Algorithm ◽  
Reconstruction Algorithms ◽  
Time Duration ◽  
Acquisition Protocol ◽  
Scan Time ◽  
Pet Ct

Abstract Aim: [68Ga]Ga-PSMA-11 PET/CT allows for a superior detection of prostate cancer tissue, especially in the context of a low tumor burden. Digital PET/CT bears the potential of reducing scan time duration / administered tracer activity due to, for instance, its higher sensitivity and improved time coincidence resolution. It might thereby expand [68Ga]Ga-PSMA-11 PET/CT that is currently limited by 68Ge/68Ga-generator yield. Our aim was to clinically evaluate the influence of a reduced scan time duration in combination with different image reconstruction algorithms on the diagnostic performance.Methods: Twenty prostate cancer patients (11 for biochemical recurrence, 5 for initial staging, 4 for metastatic disease) sequentially underwent [68Ga]Ga-PSMA-11 PET/CT on a digital Siemens Biograph Vision. PET data were collected in continuous-bed-motion mode with a mean scan time duration of 16.7 min (reference acquisition protocol) and 4.6 min (reduced acquisition protocol). 4 iterative reconstruction algorithms were applied using a time-of-flight (TOF) approach alone or combined with point-spread-function (PSF) correction, each with 2 or 4 iterations. To evaluate the diagnostic performance, the following metrics were chosen: (a) per-region detectability, (b) the tumor maximum and peak standardized uptake values (SUVmax and SUVpeak) and (c) image noise using the liver’s activity distribution.Results: Overall, 98% of regions (91% of affected regions) were correctly classified in the reduced acquisition protocol independent of the image reconstruction algorithm. Two nodal lesions (each ≤4 mm) were not identified (leading to downstaging in 1/20 cases). Mean absolute percentage deviation of SUVmax (SUVpeak) was approximately 9% (6%) for each reconstruction algorithm. The mean image noise increased from 13% to 21% (4 iterations) and from 10% to 15% (2 iterations) for PSF+TOF and TOF images.Conclusions: High agreement at 3.5-fold reduction of scan time in terms of per-region detection (98 % of regions) and image quantification (mean deviation ≤ 10 %) was demonstrated; however, small lesions can be missed in about 10% of patients leading to downstaging (T1N0M0 instead of T1N1M0) in 5 % of patients. Our results suggest that a reduction of scan time duration or administered [68Ga]Ga-PSMA-11 activities can be considered in metastatic patients, where missing small lesions would not impact patient management. Limitations include the small and heterogeneous sample size and the lack of follow-up.

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