Count-Rate Dependent Event Mispositioning and NEC in PET

Badawi, Ramsey D.; Domigan, Paul; Johnson, O. E.; Kemp, Brad; Kudrolli, Haris; Rempel, T.D.; Rohatgi, Rajat; Romanov, L.; Surti, Suleman; Worstell, W.; Zimmerman, R.E.

doi:10.1109/tns.2003.823045

Cited by 16 publications

(4 citation statements)

References 4 publications

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“…Furthermore, the NECR does not account for possible count rate bias such as the systematic mispositioning of data because of spatial pile-up effects. 28 The aim of this study is to evaluate using phantoms the relationship between the NECR and the SNR in PET imaging when a fully 3D OSEM reconstruction algorithm is applied. To our knowledge, this relationship has not been previously studied for a fully 3D OSEM reconstruction model.…”

Section: Introductionmentioning

confidence: 99%

Reliability of predicting image signal‐to‐noise ratio using noise equivalent count rate in PET imaging

Chang

Clark

et al. 2012

Medical Physics

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For the scanners and reconstruction algorithm used in this study, our results suggest that the image SNR cannot be predicted by the NEC when using 3D-OSEM reconstruction particularly for those clinical applications requiring high activity concentration. Instead, our results suggest that image SNR varies with activity concentration and is dominated by the 3D-OSEM reconstruction algorithm and its associated parameters, while not being affected by the scanner type for the range of activity concentrations usually found in the clinic.

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Section: Introductionmentioning

confidence: 99%

Reliability of predicting image signal‐to‐noise ratio using noise equivalent count rate in PET imaging

Chang

Clark

et al. 2012

Medical Physics

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“…At the starting activity of 20 MBq of these measurements, the singles data loss of the 1st prototype was 10% as shown in figure 11(b). At this activity, multi-event pileups degraded imaging performance by mispositioning on the Anger calculation (Badawi et al 2004). This was because our four layered DOI detector had a burden in separating 1024 GSOZ crystal responses on a flood histogram (Yoshida et al 2017).…”

Section: Discussionmentioning

confidence: 99%

245 ps-TOF brain-dedicated PET prototype with a hemispherical detector arrangement

et al. 2020

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Brain PET, which has led research in molecular imaging and diagnosis of brain cancer, epilepsy and neurodegenerative disorders, is being spotlighted again to promote earlier diagnosis of dementia with the advent of amyloid and tau tracers. To meet this demand, in this paper, we developed a brain-dedicated PET imaging device with a hemispherical detector arrangement, which provides comparable sensitivity with fewer detectors than conventional cylindrical geometries. The introduction of the time-of-flight (TOF) measurement capability was a key point for the development to get a gain in the image signal-to-noise ratio. Currently, whole-body PET scanners with around 200–400 ps coincidence resolving time (CRT) are commercially available. In order to obtain the same TOF gain which can be obtained with 400 ps CRT for a 30 cm diameter object, 267 ps CRT will be required for a 20 cm diameter object such as the human head. In this work, therefore, we aimed at developing a TOF brain-dedicated PET prototype with the hemisphere detector arrangement and the CRT faster than 267 ps. The detector was composed of a 12 × 12 lutetium fine silicate (LFS) array coupled with a 12 × 12 multi-pixel photon counter (MPPC) array. Each LFS crystal with a size of 4.14 × 4.14 × 10 mm3 was individually coupled to a separate MPPC. Singles list-mode data from each detector were stored, and coincidences were identified using a coincidence-detection software algorithm. The CRT of 245 ps was finally achieved as the system average after a fine timing correction. For image reconstruction, we implemented the list-mode TOF-OSEM. For a small rod phantom, rods of 3 mm diameter were clearly separated. Also, images of the 3D Hoffman brain phantom, which demonstrated clear contrast between gray and white matter, supported the effect of TOF information.

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“…However, unlike that reported by Chang et al (2012), we did not reach the peak NECR. Additional experiments at higher count rates for the Biograph mCT must be conducted to assess the possible dependence of count-rate on event mispositioning (Badawi et al 2004), and make possible a comparison with existing published data. Additionally, the quadratic relationship between SNR 2 and NEC found with the phantom data did not hold true when considering patient data, unlike the relationship between SNR 2 and the number of true events.…”

Section: Discussionmentioning

confidence: 99%

Clinical NECR in 18F-FDG PET scans: optimization of injected activity and variable acquisition time. Relationship with SNR

Carlier¹,

Ferrer²,

Necib³

et al. 2014

Phys. Med. Biol.

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The injected activity and the acquisition time per bed position for 18F-FDG PET scans are usually optimized by using metrics obtained from phantom experiments. However, optimal activity and time duration can significantly vary from a phantom set-up and from patient to patient. An approach using a patient-specific noise equivalent count rate (NECR) modelling has been previously proposed for optimizing clinical scanning protocols. We propose using the clinical NECR on a large population as a function of the body mass index (BMI) for deriving the optimal injected activity and acquisition duration per bed position. The relationship between the NEC and the signal-to-noise ratio (SNR) was assessed both in a phantom and in a clinical setting. 491 consecutive patients were retrospectively evaluated and divided into 4 BMI subgroups. Two criteria were used to optimize the injected activity and the time per bed position was adjusted using the NECR value while keeping the total acquisition time constant. Finally, the relationship between NEC and SNR was investigated using an anthropomorphic phantom and a population of 507 other patients. While the first dose regimen suggested a unique injected activity (665 MBq) regardless of the BMI, the second dose regimen proposed a variable activity and a total acquisition time according to the BMI. The NEC improvement was around 35% as compared with the local current injection rule. Variable time per bed position was derived according to BMI and anatomical region. NEC and number of true events were found to be highly correlated with SNR for the phantom set-up and partially confirmed in the patient study for the BMI subgroup under 28 kg m(-2) suggesting that for the scanner, the nonlinear reconstruction algorithm used in this study and BMI < 28 kg m(-2), NEC, or the number of true events linearly correlated with SNR(2).

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Count-Rate Dependent Event Mispositioning and NEC in PET

Cited by 16 publications

References 4 publications

Reliability of predicting image signal‐to‐noise ratio using noise equivalent count rate in PET imaging

Reliability of predicting image signal‐to‐noise ratio using noise equivalent count rate in PET imaging

245 ps-TOF brain-dedicated PET prototype with a hemispherical detector arrangement

Clinical NECR in 18F-FDG PET scans: optimization of injected activity and variable acquisition time. Relationship with SNR

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