Simultaneous acquisition of dynamic PET-MRI: arterial input function using DSC-MRI and [18F]-FET

Caldeira, Liliana; Yun, Seong Dae; Silva, Nuno da; Filß, Christian; Scheins, Juergen; Telmann, Lutz; Herzog, Hans; Shah, Jon

doi:10.1186/2197-7364-2-s1-a70

Cited by 4 publications

(2 citation statements)

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“…This is of great importance, in particular for the region of the tumour where the blood‐brain barrier is disrupted, and might allow for a reduction in measurement time or the introduction of new sequences in the clinical protocols. In addition to the standard PWI metrics, obtaining DCE time courses opens up the possibility of calculating the permeability characteristics of the tumour (Calamante, 2013; Caldeira et al, 2015; Schmiedeskamp et al, 2013; Schmiedeskamp, Straka, & Bammer, 2012; Skinner, Moots, Ayers, & Quarles, 2016). Combination of GESE‐EPIK and MR‐PET data, such as combined AIF estimation (Caldeira et al, 2015; Poulin et al, 2013; Silva et al, 2015), PET modelling (Erlandsson et al, 2015; Sari, Erlandsson, & Thielemans, 2015) and angiogenic modelling (Hutterer, Hattingen, Palm, Proescholdt, & Hau, 2015) can be further investigated using GESE‐EPIK and the high‐resolution, hybrid BrainPET, avoiding co‐registration and interpolation errors.…”

Section: Discussionmentioning

confidence: 99%

Perfusion weighted imaging using combined gradient/spin echo EPIK: Brain tumour applications in hybrid MR‐PET

Shah

Silva

Yun

2019

Human Brain Mapping

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Advanced perfusion‐weighted imaging (PWI) methods that combine gradient echo (GE) and spin echo (SE) data are important tools for the study of brain tumours. In PWI, single‐shot, EPI‐based methods have been widely used due to their relatively high imaging speed. However, when used with increasing spatial resolution, single‐shot EPI methods often show limitations in whole‐brain coverage for multi‐contrast applications. To overcome this limitation, this work employs a new version of EPI with keyhole (EPIK) to provide five echoes: two with GEs, two with mixed GESE and one with SE; the sequence is termed “GESE‐EPIK.” The performance of GESE‐EPIK is evaluated against its nearest relative, EPI, in terms of the temporal signal‐to‐noise ratio (tSNR). Here, data from brain tumour patients were acquired using a hybrid 3T MR‐BrainPET scanner. GESE‐EPIK resulted in reduced susceptibility artefacts, shorter TEs for the five echoes and increased brain coverage when compared to EPI. Moreover, compared to EPI, EPIK achieved a comparable tSNR for the first and second echoes and significantly higher tSNR for other echoes. A new method to obtain multi‐echo GE and SE data with shorter TEs and increased brain coverage is demonstrated. As proposed here, the workflow can be shortened and the integration of multimodal clinical MR‐PET studies can be facilitated.

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Section: Discussionmentioning

confidence: 99%

Perfusion weighted imaging using combined gradient/spin echo EPIK: Brain tumour applications in hybrid MR‐PET

Shah

Silva

Yun

2019

Human Brain Mapping

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“…To achieve more reliable tissue segmentation, several 3D approaches with higher spatial resolution have been proposed for determination of IDIF (Caldeira et al, 2015). Magnetic resonance angiography (MRA) is a group of MRI techniques to image blood vessels including the arteries inside the brain and neck.…”

Section: Mri-based Quantitative Analysismentioning

confidence: 99%

MRI-Driven PET Image Optimization for Neurological Applications

Zhu

2019

Front. Neurosci.

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Positron emission tomography (PET) and magnetic resonance imaging (MRI) are established imaging modalities for the study of neurological disorders, such as epilepsy, dementia, psychiatric disorders and so on. Since these two available modalities vary in imaging principle and physical performance, each technique has its own advantages and disadvantages over the other. To acquire the mutual complementary information and reinforce each other, there is a need for the fusion of PET and MRI. This combined dual-modality (either sequential or simultaneous) could generate preferable soft tissue contrast of brain tissue, flexible acquisition parameters, and minimized exposure to radiation. The most unique superiority of PET/MRI is mainly manifested in MRI-based improvement for the inherent limitations of PET, such as motion artifacts, partial volume effect (PVE) and invasive procedure in quantitative analysis. Head motion during scanning significantly deteriorates the effective resolution of PET image, especially for the dynamic scan with lengthy time. Hybrid PET/MRI device can offer motion correction (MC) for PET data through MRI information acquired simultaneously. Regarding the PVE associated with limited spatial resolution, the process and reconstruction of PET data can be further optimized by using acquired MRI either sequentially or simultaneously. The quantitative analysis of dynamic PET data mainly relies upon an invasive arterial blood sampling procedure to acquire arterial input function (AIF). An image-derived input function (IDIF) method without the need of arterial cannulization, can serve as a potential alternative estimation of AIF. Compared with using PET data only, combining anatomical or functional information from MRI for improving the accuracy in IDIF approach has been demonstrated. Yet, due to the interference and inherent disparity between the two modalities, these methods for optimizing PET image based on MRI still have many technical challenges. This review discussed upon the most recent progress, current challenges and future directions of MRI-driven PET data optimization for neurological applications, with either sequential or simultaneous acquisition approach.

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