Perfusion scanning

About: Perfusion scanning is a research topic. Over the lifetime, 9496 publications have been published within this topic receiving 223860 citations. The topic is also known as: perfusion imaging.

Survival analysis in patients with newly diagnosed glioblastoma using pre- and postradiotherapy MR spectroscopic imaging

Abstract: Glioblastoma multiforme (GBM) is the most common and most malignant type of glioma. Despite advances in multimodal treatments that combine surgery, radiation therapy (RT), and chemotherapy, patients with GBM have a limited prognosis, with a median survival of 15 months.1 Conventional MRI can delineate structural abnormalities such as regions where the blood–brain barrier has been compromised, but it fails to distinguish among edema, gliosis, inflammation, and active tumor. The Macdonald criteria that have been used for many years to assess tumor progression and response to therapy are based upon changes in cross-sectional diameters of the contrast-enhancing lesion in combination with clinical worsening.2 Recent studies have shown that some patients who are treated with standard therapies can suffer from a temporary increase in the contrast-enhancing lesion that later subsides without further treatment.3,4 This phenomenon, which is termed pseudoprogression, complicates clinical decision making and leads to ambiguities in evaluation of the effectiveness of new therapies. While the newer Response Assessment for Neuro-Oncology criteria5 also take into account changes in the size of regions with abnormal signal on T2-weighted images, they are unable to differentiate tumor from nonspecific treatment effects. Proton magnetic resonance spectroscopic imaging (1H-MRSI) is a powerful noninvasive tool for characterizing the spatial extent and metabolic properties of lesions for patients with brain tumors.6 Markers that can be detected include choline-containing compounds (Cho), N-acetyl aspartate (NAA), creatine (Cr), lactate (Lac), and lipid (Lip). Elevations in the level of Cho, due to increased membrane synthesis or cell proliferation, and reductions in levels of the neuronal marker NAA have been used as biomarkers for distinguishing regions of tumor from normal brain tissue. Cr and phosphocreatine, which both resonate as singlets at 3.0 ppm, are involved in ATP metabolism. The level of total Cr is a marker of energy transfer, and storage and has been reported to increase7,8 or decrease9 in gliomas. Lac is a marker of anaerobic metabolism, and its CH3 component (1.3 ppm) often overlaps with CH2 groups in long alkyl chains of Lip that arise from necrosis or subcutaneous Lip. Spectral editing using J-difference methods have been applied to separate Lac from Lip10 for assessing the malignancy of tumors.11 Previous work has shown that the parameters obtained from 3D MRSI data may provide useful information for diagnosis,12,13 directing image-guided surgery and14 radiation planning,15–17 and predicting survival18–22 in patients with glioma. In an earlier study, we showed that integrated anatomic and diffusion- and perfusion-weighted imaging examinations obtained postsurgery but pretreatment and at posttreatment follow-ups could provide parameters that predicted progression-free survival (PFS) and overall survival (OS) in patients with GBM.23 We found that larger volumes of the region with T2 hyperintensity at baseline (pre-RT) and at post-RT were associated with worse OS, while higher blood volumes, peak height, and recirculation factors at pre-RT and larger blood volumes at post-RT, in the T2 hyperintensity lesion, were associated with shorter PFS.23 In the current study, we evaluated data from baseline and post-RT scans for the predictive values of MRSI parameters in relation to 6-month PFS (PFS6) and OS in the same population. Parameters evaluated were the metabolite indices24 and ratios between spectroscopic voxels containing anatomic and/or metabolic lesions and those within normal appearing white matter (NAWM). We hypothesized that metabolic imaging parameters from the pre-/post-RT examinations were more likely to identify the true spatial extent and malignancy of tumors than would conventional MRI. The results of this analysis were also compared with the findings from anatomic, diffusion, and perfusion imaging in order to evaluate the importance of these modalities in understanding the clinical course of the disease.

Imaging of cerebral blood flow in patients with severe traumatic brain injury in the neurointensive care

Abstract: Ischemia is a common and deleterious secondary injury following traumatic brain injury (TBI). A great challenge for the treatment of TBI patients in the neurointensive care unit (NICU) is to detect early signs of ischemia in order to prevent further advancement and deterioration of the brain tissue. Today, several imaging techniques are available to monitor cerebral blood flow (CBF) in the injured brain such as positron emission tomography (PET), single-photon emission computed tomography, xenon computed tomography (Xenon-CT), perfusion-weighted magnetic resonance imaging (MRI), and CT perfusion scan. An ideal imaging technique would enable continuous non-invasive measurement of blood flow and metabolism across the whole brain. Unfortunately, no current imaging method meets all these criteria. These techniques offer snapshots of the CBF. MRI may also provide some information about the metabolic state of the brain. PET provides images with high resolution and quantitative measurements of CBF and metabolism; however, it is a complex and costly method limited to few TBI centers. All of these methods except mobile Xenon-CT require transfer of TBI patients to the radiological department. Mobile Xenon-CT emerges as a feasible technique to monitor CBF in the NICU, with lower risk of adverse effects. Promising results have been demonstrated with Xenon-CT in predicting outcome in TBI patients. This review covers available imaging methods used to monitor CBF in patients with severe TBI.

Fully 4D motion-compensated reconstruction of cardiac SPECT images.

Abstract: In this paper, we investigate the benefits of a spatiotemporal approach for reconstruction of image sequences. In the proposed approach, we introduce a temporal prior in the form of motion compensation to account for the statistical correlations among the frames in a sequence, and reconstruct all the frames collectively as a single function of space and time. The reconstruction algorithm is derived based on the maximum a posteriori estimate, for which the one-step late expectation-maximization algorithm is used. We demonstrated the method in our experiments using simulated single photon emission computed tomography (SPECT) cardiac perfusion images. The four-dimensional (4D) gated mathematical cardiac-torso phantom was used for simulation of gated SPECT perfusion imaging with Tc-99m-sestamibi. In addition to bias-variance analysis and time activity curves, we also used a channelized Hotelling observer to evaluate the detectability of perfusion defects in the reconstructed images. Our experimental results demonstrated that the incorporation of temporal regularization into image reconstruction could significantly improve the accuracy of cardiac images without causing any significant cross-frame blurring that may arise from the cardiac motion. This could lead to not only improved detection of perfusion defects, but also improved reconstruction of the heart wall which is important for functional assessment of the myocardium.