Neurologic Applications of PET/MR Imaging

PET/MR imaging benefits neurologic clinical care and research by providing spatially and temporally matched anatomic MR imaging, advanced MR physiologic imaging, and metabolic PET imaging. MR imaging sequences and PET tracers can be modified to target physiology specific to a neurologic disease process, with applications in neurooncology, epilepsy, dementia, cerebrovascular disease, and psychiatric and neurologic research. Simultaneous PET/MR imaging provides efficient acquisition of multiple temporally matched datasets, and opportunities for motion correction and improved anatomic assignment of PET data. Current challenges include optimizing MR imaging-based attenuation correction and necessity for dual expertise in PET and MR imaging.

Time density curve analysis for C-arm FDCT PBV imaging

INTRODUCTION

Parenchymal blood volume (PBV) estimation using C-arm flat detector computed tomography (FDCT) assumes a steady-state contrast concentration in cerebral vasculature for the scan duration. Using time density curve (TDC) analysis, we explored if the steady-state assumption is met for C-arm CT PBV scans, and how consistent the contrast-material dynamics in cerebral vasculature are across patients.

METHODS

Thirty C-arm FDCT datasets of 26 patients with aneurysmal-SAH, acquired as part of a prospective study comparing C-arm CT PBV with MR-PWI, were analysed. TDCs were extracted from the 2D rotational projections. Goodness-of-fit of TDCs to a steady-state horizontal-line-model and the statistical similarity among the individual TDCs were tested. Influence of the differences in TDC characteristics on the agreement of resulting PBV measurements with MR-CBV was calculated.

RESULTS

Despite identical scan parameters and contrast-injection-protocol, the individual TDCs were statistically non-identical (p < 0.01). Using Dunn's multiple comparisons test, of the total 435 individual comparisons among the 30 TDCs, 330 comparisons (62%) reached statistical significance for difference. All TDCs deviated significantly (p < 0.01) from the steady-state horizontal-line-model. PBV values of those datasets for which the TDCs showed largest deviations from the steady-state model demonstrated poor agreement and correlation with MR-CBV, compared with the PBV values of those datasets for which the TDCs were closer to steady-state.

CONCLUSION

For clinical C-arm CT PBV examinations, the administered contrast material does not reach the assumed 'ideal steady-state' for the duration of scan. Using a prolonged injection protocol, the degree to which the TDCs approximate the ideal steady-state influences the agreement of resulting PBV measurements with MR-CBV.

C-arm flat detector computed tomography parenchymal blood volume imaging: the nature of parenchymal blood volume parameter and the feasibility of parenchymal blood volume imaging in aneurysmal subarachnoid haemorrhage patients

INTRODUCTION

C-arm flat detector computed tomography (FDCT) parenchymal blood volume (PBV) measurements allow assessment of cerebral haemodynamics in the neurointerventional suite. This paper explores the feasibility of C-arm computed tomography (CT) PBV imaging and the relationship between the C-arm CT PBV and the MR-PWI-derived cerebral blood volume (CBV) and cerebral blood flow (CBF) parameters in aneurysmal subarachnoid haemorrhage (SAH) patients developing delayed cerebral ischemia (DCI).

METHODS

Twenty-six patients with DCI following aneurysmal SAH underwent a research C-arm CT PBV scan using a biplane angiography system and contemporaneous MR-PWI scan as part of a prospective study. Quantitative whole-brain atlas-based volume-of-interest analysis in conjunction with Pearson correlation and Bland-Altman tests was performed to explore the agreement between C-arm CT PBV and MR-derived CBV and CBF measurements.

RESULTS

All patients received medical management, while eight patients (31%) underwent selective intra-arterial chemical angioplasty. Colour-coded C-arm CT PBV maps were 91% sensitive and 100% specific in detecting the perfusion abnormalities. C-arm CT rPBV demonstrated good agreement and strong correlation with both MR-rCBV and MR-rCBF measurements; the agreement and correlation were stronger for MR-rCBF relative to MR-rCBV and improved for C-arm CT PBV versus the geometric mean of MR-rCBV and MR-rCBF. Analysis of weighted means showed that the C-arm CT PBV has a preferential blood flow weighting (≈ 60% blood flow and ≈ 40% blood volume weighting).

CONCLUSIONS

C-arm CT PBV imaging is feasible in DCI following aneurysmal SAH. PBV is a composite perfusion parameter incorporating both blood flow and blood volume weightings. That PBV has preferential (≈ 60%) blood flow weighting is an important finding, which is of clinical significance when interpreting the C-arm CT PBV maps, particularly in the setting of acute brain ischemia.