Abstract

PurposeMany neurological diseases affect small structures in the brain and, as such, reliable visual evaluation and accurate quantification are required. Recent technological developments made the clinical use of hybrid positron emission tomography/magnetic resonance (PET/MR) systems possible, providing both functional and anatomical information in a single imaging session. Nevertheless, there is a trade-off between spatial resolution and image quality (contrast and noise), which is dictated mainly by the chosen acquisition and reconstruction protocols. Image reconstruction algorithms using spherical symmetric basis functions (blobs) for image representation have a number of additional parameters that impact both the qualitative and quantitative image characteristics. Hence, a detailed investigation of the blob-based reconstruction characteristics using different parameters is needed to achieve optimal reconstruction results.ProceduresThis work evaluated the impact of a range of blob parameters on image quality and quantitative accuracy of brain PET images acquired on the Ingenuity Time-of-Flight (TOF) PET/MR system. Two different phantoms were used to simulate brain imaging applications. Image contrast and noise characteristics were assessed using an image quality phantom. Quantitative performance in a clinical setting was investigated using the Hoffman 3D brain phantom at various count levels. Furthermore, the visual quality of four clinical studies was scored blindly by two experienced physicians to qualitatively evaluate the influence of different reconstruction protocols, hereby providing indications on parameters producing the best image quality.ResultsQuantitative evaluation using the image quality phantom showed that larger basis function radii result in lower contrast recovery (∼2 %) and lower variance levels (∼15 %). The brain phantom and clinical studies confirmed these observations since lower contrast was seen between anatomical structures. High and low count statistics gave comparable values. The qualitative evaluation of the clinical studies, based on the assessment performed by the physicians, showed a preference towards lower image variance levels with a slightly lower contrast, favoring higher radii and four iterations.ConclusionThis study systematically evaluated a number of basis function parameters and their quantitative and qualitative effect within PET image reconstruction in the context of brain imaging. A range of blob parameters can minimize error and provided optimal image quality, where the anatomical structures could be recognized but the exact delineation of these structures is simplified in scans with lower image variance levels and thus, higher radii should be preferred. With the optimization of blob parameters, the reconstructed images were found to be qualitatively improved (optimum parameters {d = 2.0375, alpha = 10.4101, radius = 3.9451}) as assessed by the physicians compared to the current clinical protocol. However, this qualitative improvement is task specific, depending on the desired image characteristics to be extracted. Finally, this work could be used as a guide for application-specific optimal parameter selection.Electronic supplementary materialThe online version of this article (doi:10.1007/s11307-015-0824-x) contains supplementary material, which is available to authorized users.

Highlights

  • A number of neurological diseases, such as epilepsy, dementia, or brain tumors, produce important alterations in small brain structures that are frequently not detectable using conventional anatomical imaging techniques [1]

  • This study systematically evaluated a number of basis function parameters and their quantitative and qualitative effect within Positron emission tomography (PET) image reconstruction in the context of brain imaging

  • The results of the phantom studies demonstrated that larger blob radii result in higher noise suppression but lower contrast recovery

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Summary

Introduction

A number of neurological diseases, such as epilepsy, dementia, or brain tumors, produce important alterations in small brain structures that are frequently not detectable using conventional anatomical imaging techniques [1]. The recent development of MR-compatible PET components made hybrid PET/MR systems a reality These systems facilitate co-registration of structural and functional images and enable simultaneous in vivo assessment of multimodality imaging probes. Such acquisition protocols potentially create a more convenient workflow for the patients as they undergo two examinations within a single scanning session. The actual combination of PET and MRI faces two major technical challenges, namely reducing the potential interference between the two systems and developing reliable and robust MR-based attenuation correction (MRAC) schemes [5, 6]

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