Abstract

BackgroundRoutine PET exams are increasingly performed with reduced injected activities, leading to the use of different image reconstruction parameters than the NEMA parameters, in order to prevent from any deleterious decrease in signal-to-noise ratio (SNR) and thus, in lesion detectability. This study aimed to provide a global head-to-head comparison between digital (Vereos, Philips®) and analog (Ingenuity TF, Philips®) PET cameras of the trade-off between SNR and contrast through a wide-ranging number of reconstruction iterations, and with a further reconstruction optimization based on the SNR of small lesions.MethodsImage quality parameters were compared between the two cameras on human and phantom images for a number of OSEM reconstruction iterations ranging from 1 to 10, the number of subsets being fixed at 10, and with the further identification of reconstruction parameters maximizing the SNR of spheres and adenopathies nearing 10 mm in diameter. These reconstructions were additionally obtained with and without time-of-flight (TOF) information (TOF and noTOF images, respectively) for further comparisons.ResultsOn both human and phantom TOF images, the compromise between SNR and contrast was consistently more advantageous for digital than analog PET, with the difference being particularly pronounced for the lowest numbers of iterations and the smallest spheres. SNR was maximized with 1 and 2 OSEM iterations for the TOF images from digital and analog PET, respectively, whereas 4 OSEM iterations were required for the corresponding noTOF images from both cameras. On the TOF images obtained with this SNR optimization, digital PET exhibited a 37% to 44% higher SNR as compared with analog PET, depending on sphere size. These relative differences were however much lower for the noTOF images optimized for SNR (− 4 to + 18%), as well as for images reconstructed according to NEMA standards (− 4 to + 12%).ConclusionSNR may be dramatically higher for digital PET than for analog PET, especially when optimized for small lesions. This superiority is mostly attributable to enhanced TOF resolution and is significantly underestimated in NEMA-based analyses.

Highlights

  • Positron emission tomography (PET) diagnostic procedures are commonly prescribed for a growing number of indications and are increasingly repeated in the same patients for purposes of serial treatment monitoring, thereby explaining a current trend toward reducing the amount of injected activities

  • These changes have been facilitated by the concomitant advances achieved in PET camera technology [1, 2] and by the preferential use of iterative reconstruction parameters preventing against excess noise and against a deleterious decrease in signal-to-noise ratio (SNR) and in the detectability of small lesions [3, 4]

  • This study aimed to provide a global head-to-head comparison between digital (Vereos, Philips®) and analog (Ingenuity TF, Philips®) PET cameras equipped with equivalent reconstruction algorithms, of the trade-off between signal-tonoise ratio (SNR) and contrast through the testing of a wide-ranging number of reconstruction iterations, and with a further reconstruction optimization based on the SNR of small lesions

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Summary

Introduction

Positron emission tomography (PET) diagnostic procedures are commonly prescribed for a growing number of indications and are increasingly repeated in the same patients for purposes of serial treatment monitoring, thereby explaining a current trend toward reducing the amount of injected activities These changes have been facilitated by the concomitant advances achieved in PET camera technology [1, 2] and by the preferential use of iterative reconstruction parameters preventing against excess noise and against a deleterious decrease in signal-to-noise ratio (SNR) and in the detectability of small lesions [3, 4]. This study aimed to provide a global head-to-head comparison between digital (Vereos, Philips®) and analog (Ingenuity TF, Philips®) PET cameras of the trade-off between SNR and contrast through a wide-ranging number of reconstruction iterations, and with a further reconstruction optimization based on the SNR of small lesions

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