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

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.

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Optimization of PET/CT image quality using the GE ‘Sharp IR’ point-spread function reconstruction algorithm

Nuclear Medicine Communications ◽

10.1097/mnm.0000000000000669 ◽

2017 ◽

Vol 38 (6) ◽

pp. 471-479 ◽

Cited By ~ 3

Author(s):

Nicholas J. Vennart ◽

Nicholas Bird ◽

John Buscombe ◽

Heok K. Cheow ◽

Ewa Nowosinska ◽

...

Keyword(s):

Image Quality ◽

Point Spread Function ◽

Reconstruction Algorithm ◽

Ct Image ◽

Point Spread ◽

Pet Ct ◽

Spread Function ◽

Ct Image Quality ◽

Function Reconstruction

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Impact of total variation regularized expectation maximization reconstruction on the image quality of 68Ga-PSMA PET: a phantom and patient study

British Journal of Radiology ◽

10.1259/bjr.20201356 ◽

2021 ◽

pp. 20201356

Author(s):

Feng-Jiao Yang ◽

Shu-Yue Ai ◽

Runze Wu ◽

Yang Lv ◽

Hui-Fang Xie ◽

...

Keyword(s):

Prostate Cancer ◽

Image Quality ◽

Total Variation ◽

Expectation Maximization ◽

Image Noise ◽

Psma Pet ◽

Pet Ct ◽

Digital Pet ◽

The Impact

Objectives: To investigate the impact of total variation regularized expectation maximization (TVREM) reconstruction on the image quality of 68Ga-PSMA-11 PET/CT using phantom and patient data. Methods: Images of a phantom with small hot sphere inserts and 20 prostate cancer patients were acquired with a digital PET/CT using list-mode and reconstructed with ordered subset expectation maximization (OSEM) and TVREM with seven penalisation factors between 0.01 and 0.42 for 2 and 3 minutes-per-bed (m/b) acquisition. The contrast recovery (CR) and background variability (BV) of the phantom, image noise of the liver, and SUVmax of the lesions were measured. Qualitative image quality was scored by two radiologists using a 5-point scale (1-poor, 5-excellent). Results: The performance of CR, BV, and image noise, and the gain of SUVmax was higher for TVREM 2 m/b groups with the penalization of 0.07 to 0.28 compared to OSEM 3 m/b group (all p < 0.05). The image noise of OSEM 3 m/b group was equivalent to TVREM 2 and 3 m/b groups with a penalization of 0.14 and 0.07, while lesions’ SUVmax increased 15 and 20%. The highest qualitative score was attained at the penalization of 0.21 (3.30 ± 0.66) for TVREM 2 m/b groups and the penalization 0.14 (3.80 ± 0.41) for 3 m/b group that equal to or greater than OSEM 3 m/b group (2.90 ± 0.45, p = 0.2 and p < 0.001). Conclusions: TVREM improves lesion contrast and reduces image noise, which allows shorter acquisition with preserved image quality for PSMA PET/CT. Advances in knowledge: TVREM reconstruction with optimized penalization factors can generate higher quality PSMA-PET images for prostate cancer diagnosis.

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Impact of a Bayesian penalized likelihood reconstruction algorithm on image quality in novel digital PET/CT: clinical implications for the assessment of lung tumors

EJNMMI Physics ◽

10.1186/s40658-018-0223-x ◽

2018 ◽

Vol 5 (1) ◽

Cited By ~ 18

Author(s):

Michael Messerli ◽

Paul Stolzmann ◽

Michèle Egger-Sigg ◽

Josephine Trinckauf ◽

Stefano D’Aguanno ◽

...

Keyword(s):

Image Quality ◽

Penalized Likelihood ◽

Reconstruction Algorithm ◽

Lung Tumors ◽

Clinical Implications ◽

Pet Ct ◽

Digital Pet

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PET/CT BiographTM Sensation 16

Nuklearmedizin ◽

10.1055/s-0038-1625926 ◽

2006 ◽

Vol 45 (03) ◽

pp. 126-133 ◽

Cited By ~ 18

Author(s):

Y. Bercier ◽

M. Schwaiger ◽

S. I. Ziegler ◽

M.-J. Martínez

Keyword(s):

Image Quality ◽

Count Rate ◽

Signal To Noise Ratio ◽

Reconstruction Algorithm ◽

Considerable Change ◽

Acquisition Time ◽

Average Increase ◽

Scatter Fraction ◽

Pet Ct ◽

Before And After

SummaryAim: The new PET/CT Biograph Sensation 16 (BS16) tomographs have faster detector electronics which allow a reduced timing coincidence window and an increased lower energy threshold (from 350 to 400 keV). This paper evaluates the performance of the BS16 PET scanner before and after the Pico-3D electronics upgrade. Methods: Four NEMA NU 2–2001 protocols, (i) spatial resolution, (ii) scatter fraction, count losses and random measurement, (iii) sensitivity, and (iv) image quality, have been performed. Results: A considerable change in both PET count-rate performance and image quality is observed after electronics upgrade. The new scatter fraction obtained using Pico-3D electronics showed a 14% decrease compared to that obtained with the previous electronics. At the typical patient background activity (5.3 kBq/ml), the new scatter fraction was approximately 0.42. The noise equivalent count-rate (RNEC) performance was also improved. The value at which the RNEC curve peaked, increased from 3.7·104s-1 at 14 kBq/ml to 6.4·104s-1 at 21 kBq/ml (2R-NEC rate). Likewise, the peak true count-rate value increased from 1.9·105s-1 at 22 kBq/ml to 3.4·105s-1 at 33 kBq/ml. An average increase of 45% in contrast was observed for hot spheres when using AW-OSEM (4ix8s) as the reconstruction algorithm. For cold spheres, the average increase was 12%. Conclusion: The performance of the PET scanners in the BS16 tomographs is improved by the optimization of the signal processing. The narrower energy and timing coincidence windows lead to a considerable increase of signal- to-noise ratio. The existing combination of fast detectors and adapted electronics in the BS16 tomographs allow imaging protocols with reduced acquisition time, providing higher patient throughput.

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

EJNMMI Physics ◽

10.1186/s40658-019-0264-9 ◽

2019 ◽

Vol 6 (1) ◽

Cited By ~ 6

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.

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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 ◽

10.3390/diagnostics11040630 ◽

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.

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

Nuclear Medicine Communications ◽

10.1097/mnm.0000000000000604 ◽

2017 ◽

Vol 38 (1) ◽

pp. 57-66 ◽

Cited By ~ 15

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

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A PET/CT Phantom for Evaluating The PET Image Quality of Micro-Lesion and CT Performance Parameters

10.21203/rs.3.rs-108386/v1 ◽

2020 ◽

Author(s):

Shujie Lu ◽

Peng Zhang ◽

Chengwei Li ◽

Jie Sun ◽

Wenli Liu ◽

...

Keyword(s):

Image Quality ◽

Pure Water ◽

Performance Testing ◽

Reconstruction Algorithm ◽

Performance Parameters ◽

Imaging Quality ◽

Imaging Results ◽

Pet Ct ◽

Testing Module

Abstract Background: Recent years, PET/CT equipment has played an increasingly important role in the medical field, and its quality control and evaluation requirements have become more stringent. Correspondingly, the performance testing phantom used for PET/CT quality control needs to be upgraded and optimized to meet the requirement of equipment imaging quality testing. The commonly used NEMA IEC Body performance testing phantom has the defects that it cannot detect micro-lesion and cannot measure CT performance parameters. This article proposes a NIM PET/CT phantom capable of simultaneously testing the performance of PET and CT equipment, and evaluates its imaging quality.Methods: Compared with the NEMA IEC Body phantom, the PET performance testing module in the phantom has new balls with inner diameters of 4mm and 7mm. Combined with the CT performance testing module, it can be used for both PET and CT performance testing. The 28mm and 37mm balls are filled with pure water as a cold stove, and the remaining balls are filled with F-FDG solution as a hot stove. The activity concentration ratio of the hot ball to the background is 4:1. This study compares the imaging results of the NIM PET/CT phantom and the NEMA IEC Body phantom to verify its effectiveness; compares the imaging results of 3 different brands of PET/CT on the NIM phantom to verify that it is on different equipment The generalization ability of the system; apply PSF and TOF technology to the reconstruction algorithm and compare the improvement of the image quality; finally, the accuracy of the CT low-contrast module and the uniformity of the background are verified.Results: The imaging quality of the NIM PET/CT phantom and the NEMA IEC Body phantom is relatively consistent. The NIM phantom under different types of PET/CT scans can detect 7mm balls without affecting the imaging quality of other areas, which is better The device can detect 4mm small balls, which can clearly classify the ability of different devices to present images of small lesions; the integration of PSF technology into the reconstruction algorithm significantly improves the image resolution and hot bulb contrast, but the edges of the lesions are still blurred , TOF technology improves the detection limit of the equipment and improves the overall quality of the image. PSF&TOF technology combines the advantages of the two, significantly reducing image noise and strengthening image details, so that the image quality has been comprehensively improved; the measurement in the CT module The result is consistent with the true value, and the relative error is within ±5%. The CT value transition between the background and pure water area is smooth, and the background uniformity is good.Conclusion: NIM PET/CT Phantom and NEMA IEC Body phantom are comparability, and the former includes all the functions of the latter. In addition, the phantom can meet the testing requirement of different grades of PET/CT.

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The clinical effectiveness of reconstructing 18F-sodium fluoride PET/CT bone using Bayesian penalized likelihood algorithm for evaluation of metastatic bone disease in obese patients

British Journal of Radiology ◽

10.1259/bjr.20210043 ◽

2021 ◽

Vol 94 (1120) ◽

pp. 20210043

Author(s):

Sharjeel Usmani ◽

Najeeb Ahmed ◽

Gopinath Gnanasegaran ◽

Rashid Rasheed ◽

Fahad Marafi ◽

...

Keyword(s):

Image Quality ◽

Sodium Fluoride ◽

Penalized Likelihood ◽

Clinical Effectiveness ◽

Reconstruction Algorithm ◽

Whole Body ◽

Obese Patients ◽

Positron Emission ◽

Pet Ct ◽

Clinical Cases

Objective: A new Bayesian penalized likelihood reconstruction algorithm for positron emission tomography (PET) (Q.Clear) is now in clinical use for fludeoxyglucose (FDG) PET/CT. However, experience with non-FDG tracers and in special patient populations is limited. This pilot study aims to compare Q.Clear to standard PET reconstructions for 18F sodium fluoride (18F-NaF) PET in obese patients. Methods: 30 whole body 18F-NaF PET/CT scans (10 patients with BMI 30–40 Kg/m2 and 20 patients with BMI >40 Kg/m2) and a NEMA image quality phantom scans were analyzed using ordered subset expectation maximization (OSEM) and Q.Clear reconstructions methods with B400, 600, 800 and 1000. The images were assessed for overall image quality (IQ), noise level, background soft tissue, and lesion detectability, contrast recovery (CR), background variability (BV) and contrast-to-noise ratio (CNR) for both algorithms. Results: CNR for clinical cases was higher for Q.Clear than OSEM (p < 0.05). Mean CNR for OSEM was (21.62 ± 8.9), and for Q.Clear B400 (31.82 ± 14.6), B600 (35.54 ± 14.9), B800 (39.81 ± 16.1), and B1000 (40.9 ± 17.8). As the β value increased the CNR increased in all clinical cases. B600 was the preferred β value for reconstruction in obese patients. The phantom study showed Q.Clear reconstructions gave lower CR and lower BV than OSEM. The CNR for all spheres was significantly higher for Q.Clear (independent of β) than OSEM (p < 0.05), suggesting superiority of Q.Clear. Conclusion: This pilot clinical study shows that Q.Clear reconstruction algorithm improves overall IQ of 18F-NaF PET in obese patients. Our clinical and phantom measurement results demonstrate improved CNR and reduced BV when using Q.Clear. A β value of 600 is preferred for reconstructing 18F-NaF PET/CT with Q.Clear in obese patients. Advances in knowledge: 18F-NaF PET/CT is less susceptible to artifacts induced by body habitus. Bayesian penalized likelihood reconstruction with18F-NaF PET improves overall IQ in obese patients.

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