Grand challenges in biomedical physics

Townsend, David W.; Cheng, Zhen; Georg, Dietmar; Drexler, Wolfgang; Moser, Ewald

doi:10.3389/fphy.2013.00001

Cited by 10 publications

(7 citation statements)

References 76 publications

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“…The MRI quantification values also varied in relation to the ICP-MS values, but were underestimated at 29, 7, 2, 16, 9 and 6% for 5, 10, 20, 30, 40 and 50 µg Fe/mL, respectively, and the largest difference occurred in the lowest concentrations of nanoparticle tested (29% lower for 5 µg Fe/mL). This variability of results can be explained by a difference in sensitivity under each imaging modality, as MRI shows low sensitivity for small concentrations above 10 -3 moles, whereas NIRF presents good sensitivity for ranges between 10 -9 and 10 -12 moles[45]. However, whether MRI and NIRF tracking of stem cells can reliably evaluate long-term cell engraftment and cell survival remains a controversial issue[46].…”

Section: Discussionmentioning

confidence: 99%

Triple-modal imaging of stem-cells labeled with multimodal nanoparticles, applied in a stroke model

Silva

Mamani

Nucci

et al. 2019

WJSC

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BACKGROUND Mesenchymal stem cells (MSCs) have been widely tested for their therapeutic efficacy in the ischemic brain and have been shown to provide several benefits. A major obstacle to the clinical translation of these therapies has been the inability to noninvasively monitor the best route, cell doses, and collateral effects while ensuring the survival and effective biological functioning of the transplanted stem cells. Technological advances in multimodal imaging have allowed in vivo monitoring of the biodistribution and viability of transplanted stem cells due to a combination of imaging technologies associated with multimodal nanoparticles (MNPs) using new labels and covers to achieve low toxicity and longtime residence in cells. AIM To evaluate the sensitivity of triple-modal imaging of stem cells labeled with MNPs and applied in a stroke model. METHODS After the isolation and immunophenotypic characterization of human bone marrow MSCs (hBM-MSCs), our team carried out lentiviral transduction of these cells for the evaluation of bioluminescent images (BLIs) in vitro and in vivo . In addition, MNPs that were previously characterized (regarding hydrodynamic size, zeta potential, and optical properties), and were used to label these cells, analyze cell viability via the 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide assay and BLI analysis, and quantify the internalization process and iron load in different concentrations of MNPs via magnetic resonance imaging (MRI), near-infrared fluorescence (NIRF), and inductively coupled plasma-mass spectrometry (ICP-MS). In in vivo analyses, the same labeled cells were implanted in a sham group and a stroke group at different times and under different MNP concentrations (after 4 h or 6 d of cell implantation) to evaluate the sensitivity of triple-modal images. RESULTS hBM-MSC collection and isolation after immunophenotypic characterization were demonstrated to be adequate in hBM samples. After transduction of these cells with luciferase (hBM-MSC Luc ), we detected a maximum BLI intensity of 2.0 x 10 8 photons/s in samples of 10 6 hBM-MSCs. Analysis of the physicochemical characteristics of the MNPs showed an average hydrodynamic diameter of 38.2 ± 0.5 nm, zeta potential of 29.2 ± 1.9 mV and adequate colloidal stability without agglomeration over 18 h. The signal of iron load internalization in hBM-MSC Luc showed a close relationship with the corresponding MNP-labeling concentrations based on MRI, ICP-MS and NIRF. Under the highest MNP concentration, cellular viability showed a reduction of less than 10% compared to the control. Correlation analysis of the MNP load internalized into hBM-MSC ...

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Section: Discussionmentioning

confidence: 99%

Triple-modal imaging of stem-cells labeled with multimodal nanoparticles, applied in a stroke model

Silva

Mamani

Nucci

et al. 2019

WJSC

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“…For instance, the connection seen in Figure 4 between the visual cortex and more anterior regions of the brain, including areas around the brain stem and the amygdala, might not necessarily reflect a pattern of local neuronal activation, but is more likely caused by signal changes in the nearby V. basiliaris (Rosenthal) as seen in Figure 2D (transversal SWI slab) and corroborated by many anatomical studies (e.g., 71, Figures 4, 5). Such a connection could result in stimulus-correlated BOLD signal fluctuations in venous vessels running close to the amygdalae, potentially masking any “true” neuronal activity related BOLD signal in the amygdala [72, 73]. As discussed by Turner [17], this may not be a serious limitation in cortical areas—in regions like the amygdala or insula, however, this might be the cause of inconsistent results concerning left and/or right amygdala activation [74–76].…”

Section: Discussion and Outlookmentioning

confidence: 99%

Scanning fast and slow: current limitations of 3 Tesla functional MRI and future potential

et al. 2014

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Functional MRI at 3T has become a workhorse for the neurosciences, e.g., neurology, psychology, and psychiatry, enabling non-invasive investigation of brain function and connectivity. However, BOLD-based fMRI is a rather indirect measure of brain function, confounded by physiology related signals, e.g., head or brain motion, brain pulsation, blood flow, intermixed with susceptibility differences close or distant to the region of neuronal activity. Even though a plethora of preprocessing strategies have been published to address these confounds, their efficiency is still under discussion. In particular, physiological signal fluctuations closely related to brain supply may mask BOLD signal changes related to “true” neuronal activation. Here we explore recent technical and methodological advancements aimed at disentangling the various components, employing fast multiband vs. standard EPI, in combination with fast temporal ICA. Our preliminary results indicate that fast (TR <0.5 s) scanning may help to identify and eliminate physiologic components, increasing tSNR and functional contrast. In addition, biological variability can be studied and task performance better correlated to other measures. This should increase specificity and reliability in fMRI studies. Furthermore, physiological signal changes during scanning may then be recognized as a source of information rather than a nuisance. As we are currently still undersampling the complexity of the brain, even at a rather coarse macroscopic level, we should be very cautious in the interpretation of neuroscientific findings, in particular when comparing different groups (e.g., age, sex, medication, pathology, etc.). From a technical point of view our goal should be to sample brain activity at layer specific resolution with low TR, covering as much of the brain as possible without violating SAR limits. We hope to stimulate discussion toward a better understanding and a more quantitative use of fMRI.

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“…Thus, the control of flexibility is potentially a powerful way for targeting applications for metal complexes. One such application is biomedical thermometry by magnetic resonance imaging (MRI),7,8 where the temperature-dependent structure of a flexible complex induces highly temperature-dependent spin-Hamiltonian parameters or relaxation times. If this variation could be harnessed to develop an imaging technique, such an application would circumvent many of the challenges associated with invasive thermometry, e.g.…”

Section: Introductionmentioning

confidence: 99%