Tracking Cellular Functions by Exploiting the Paramagnetic Properties of X‐Nuclei

The term X‐nuclei summarises all nuclei (except protons) that occur in biological systems carrying a non‐zero nuclear spin. Significant involvement in physiological processes such as maintaining the transmembrane potential of living cells and energy metabolism make these nuclei highly interesting for nuclear magnetic resonance (NMR) experiments. In this chapter, a discussion of the basic physics of nuclei with a nuclear spin >1/2 is presented. On this basis, pulse sequences for the detection of multi quantum coherences (MQCs) are presented and explained. Information contained in the obtained MQC signal is linked to biophysical processes. Applications to study energy metabolism, oxygen consumption, and to track brain metabolites by means of X‐nuclei NMR are discussed as well as the use of functional phantoms, which can bridge the gap between basic biological research and NMR data interpretation

Highly cited articles in “Zeitschrift für Medizinische Physik”

This editorial describes the publishing guidelines of the journal "Zeitschrift für Medizinische Physik" and the development of its impact factors. The articles with the most number of citations in the databases of ISI Web of Science™ and Scopus are listed

An open source software for analysis of dynamic contrast enhanced magnetic resonance images: UMMPerfusion revisited

Background: Perfusion imaging has become an important image based tool to derive the physiological information in various applications, like tumor diagnostics and therapy, stroke, (cardio-) vascular diseases, or functional assessment of organs. However, even after 20 years of intense research in this field, perfusion imaging still remains a research tool without a broad clinical usage. One problem is the lack of standardization in technical aspects which have to be considered for successful quantitative evaluation; the second problem is a lack of tools that allow a direct integration into the diagnostic workflow in radiology. Results: Five compartment models, namely, a one compartment model (1CP), a two compartment exchange (2CXM), a two compartment uptake model (2CUM), a two compartment filtration model (2FM) and eventually the extended Toft’s model (ETM) were implemented as plugin for the DICOM workstation OsiriX. Moreover, the plugin has a clean graphical user interface and provides means for quality management during the perfusion data analysis. Based on reference test data, the implementation was validated against a reference implementation. No differences were found in the calculated parameters. Conclusion: We developed open source software to analyse DCE-MRI perfusion data. The software is designed as plugin for the DICOM Workstation OsiriX. It features a clean GUI and provides a simple workflow for data analysis while it could also be seen as a toolbox providing an implementation of several recent compartment models to be applied in research tasks. Integration into the infrastructure of a radiology department is given via OsiriX. Results can be saved automatically and reports generated automatically during data analysis ensure certain quality control

Improved reproducibility for myocardial ASL: Impact of physiological and acquisition parameters

PURPOSE: To investigate and mitigate the influence of physiological and acquisition-related parameters on myocardial blood flow (MBF) measurements obtained with myocardial Arterial Spin Labeling (myoASL). METHODS: A Flow-sensitive Alternating Inversion Recovery (FAIR) myoASL sequence with bSSFP and spoiled GRE (spGRE) readout is investigated for MBF quantification. Bloch-equation simulations and phantom experiments were performed to evaluate how variations in acquisition flip angle (FA), acquisition matrix size (AMS), heart rate (HR) and blood T 1 $${\mathrm{T}}_1$$ relaxation time ( T 1 , B $${\mathrm{T}}_{1,B}$$ ) affect quantification of myoASL-MBF. In vivo myoASL-images were acquired in nine healthy subjects. A corrected MBF quantification approach was proposed based on subject-specific T 1 , B $${\mathrm{T}}_{1,B}$$ values and, for spGRE imaging, subtracting an additional saturation-prepared baseline from the original baseline signal. RESULTS: Simulated and phantom experiments showed a strong dependence on AMS and FA ( R 2 $${R}^2$$ >0.73), which was eliminated in simulations and alleviated in phantom experiments using the proposed saturation-baseline correction in spGRE. Only a very mild HR dependence ( R 2 $${R}^2$$ >0.59) was observed which was reduced when calculating MBF with individual T 1 , B $${\mathrm{T}}_{1,B}$$ . For corrected spGRE, in vivo mean global spGRE-MBF ranged from 0.54 to 2.59 mL/g/min and was in agreement with previously reported values. Compared to uncorrected spGRE, the intra-subject variability within a measurement (0.60 mL/g/min), between measurements (0.45 mL/g/min), as well as the inter-subject variability (1.29 mL/g/min) were improved by up to 40% and were comparable with conventional bSSFP. CONCLUSION: Our results show that physiological and acquisition-related factors can lead to spurious changes in myoASL-MBF if not accounted for. Using individual T 1 , B $${\mathrm{T}}_{1,B}$$ and a saturation-baseline can reduce these variations in spGRE and improve reproducibility of FAIR-myoASL against acquisition parameters

Tracking protein function with sodium multi quantum spectroscopy in a 3D-tissue culture based on microcavity arrays

The aim of this study was to observe the effects of strophanthin induced inhibition of the Na-/KATPase in liver cells using a magnetic resonance (MR) compatible bioreactor. A microcavity array with a high density three-dimensional cell culture served as a functional magnetic resonance imaging (MRI) phantom for sodium multi quantum (MQ) spectroscopy. Direct contrast enhanced (DCE) MRI revealed the homogenous distribution of biochemical substances inside the bioreactor. NMR experiments using advanced bioreactors have advantages with respect to having full control over a variety of physiological parameters such as temperature, gas composition and fluid flow. Simultaneous detection of single quantum (SQ) and triple quantum (TQ) MR signals improves accuracy and was achieved by application of a pulse sequence with a time proportional phase increment (TQTPPI). The time course of the Na-/KATPase inhibition in the cell culture was demonstrated by the corresponding alterations of sodium TQ/ SQ MR signals

Neural Mechanism of a Sex-Specific Risk Variant for Posttraumatic Stress Disorder in the Type I Receptor of the Pituitary Adenylate Cyclase Activating Polypeptide

AbstractBackgroundPosttraumatic stress disorder (PTSD) is a frequent anxiety disorder with higher prevalence rates in female patients than in male patients (2.5:1). Association with a single nucleotide polymorphism (rs2267735) in the gene ADCYAP1R1 encoding the type I receptor (PAC1-R) of the pituitary adenylate cyclase activating polypeptide has been reported with PTSD in female patients. We sought to identify the neural correlates of the described PAC1-R effects on associative learning.MethodsIn a reverse genetic approach, we examined two independent healthy samples (N1 = 112, N2 = 73) using functional magnetic resonance imaging during cued and contextual fear conditioning. Skin conductance responses and verbal self-reports of arousal, valence, and contingency were recorded.ResultsWe found that PAC1-R modulates the blood oxygenation level–dependent response of the hippocampus. Specifically, we observed decreased hippocampal activity during contextual, but not during cued, fear conditioning in female participants carrying the PAC1-R risk allele. We observed no significant differences in conditionability for skin conductance responses, verbal reports, or activation in other brain regions between the genotype groups in female participants.ConclusionsOur results suggest that impaired contextual conditioning in the hippocampal formation may mediate the association between PAC1-R and PTSD symptoms. Our findings potentially identify a missing link between the involvement of PAC1-R in PTSD and the well-established structural and functional hippocampal deficits in these patients

Generation of annotated multimodal ground truth datasets for abdominal medical image registration

Sparsity of annotated data is a major limitation in medical image processing tasks such as registration. Registered multimodal image data are essential for the diagnosis of medical conditions and the success of interventional medical procedures. To overcome the shortage of data, we present a method that allows the generation of annotated multimodal 4D datasets. We use a CycleGAN network architecture to generate multimodal synthetic data from the 4D extended cardiac-torso (XCAT) phantom and real patient data. Organ masks are provided by the XCAT phantom, therefore the generated dataset can serve as ground truth for image segmentation and registration. Realistic simulation of respiration and heartbeat is possible within the XCAT framework. To underline the usability as a registration ground truth, a proof of principle registration is performed. Compared to real patient data, the synthetic data showed good agreement regarding the image voxel intensity distribution and the noise characteristics. The generated T1-weighted magnetic resonance imaging (MRI), computed tomography (CT), and cone beam CT (CBCT) images are inherently co-registered. Thus, the synthetic dataset allowed us to optimize registration parameters of a multimodal non-rigid registration, utilizing liver organ masks for evaluation. Our proposed framework provides not only annotated but also multimodal synthetic data which can serve as a ground truth for various tasks in medical imaging processing. We demonstrated the applicability of synthetic data for the development of multimodal medical image registration algorithms.Comment: 12 pages, 5 figures. This work has been published in the International Journal of Computer Assisted Radiology and Surgery volum

The effect of adipose tissue-derived stem cells in a middle cerebral artery occlusion stroke model depends on their engraftment rate

Background: In the field of experimental stem cell therapy, intra-arterial (IA) delivery yields the best results concerning, for example, migrated cell number at the targeted site. However, IA application also appears to be associated with increased mortality rates and infarction. Since many rodent studies systemically apply 1 × 106 cells, this could also be a consequence of engrafted cell number. The aim of this study was therefore to investigate the effect of different doses of adipose tissue-derived stem cells (ASCs) on engraftment rates and stroke outcome measured in vivo using 9.4-T high-field magnetic resonance imaging (MRI). Methods: Male Wistar rats (n = 43) underwent a middle cerebral artery occlusion (MCAo) for 45 or 90 min, followed by IA delivery of either saline or 1 × 106, 3 × 105, or 5 × 104 ASCs pre-labelled with very small superparamagnetic iron oxide particles (VSOPs). MRI (9.4-T) analysis was performed 48 h and 9 days post-MCAo. Lesion volumes were assessed by analysis of T2-weighted images and cell signal tracking showing cell engraftment and active cell migration by an improved T2*-analysis. Results: The ASC-derived signal intensity increased in the affected hemisphere 48 h post MCAo with injected cell number (p < 0.05). The analysis of stroke volumes revealed an increased infarction after injection of 1 × 106 ASCs compared to controls or application of 5 × 104 ASCs (p < 0.05). At 9 days post-MCAo, injection of 3 × 105 ASCs resulted in reduced infarct volumes (p < 0.05). Correspondingly, MRI analysis revealed no changes in cell numbers between both MRI examinations but showed active ASC migration to the site of infarction. Conclusion: Our results confirm that IA injection is an efficient way of targeting damaged brain tissue but its usefulness strongly depends on the right dose of delivered stem cells since this factor has a strong influence on migration rate and infarct volume, with better results for doses below 1 × 106 cells. Future challenges will include the determination of therapeutic doses for best cellular engraftment and stroke outcome

Polyphonic sonification of electrocardiography signals for diagnosis of cardiac pathologies

Kather JN, Hermann T, Bukschat Y, Kramer T, Schad LR, Zöllner FG. Polyphonic sonification of electrocardiography signals for diagnosis of cardiac pathologies. Scientific Reports. 2017;7(1): 44549.Electrocardiography (ECG) data are multidimensional temporal data with ubiquitous applications in the clinic. Conventionally, these data are presented visually. It is presently unclear to what degree data sonification (auditory display), can enable the detection of clinically relevant cardiac pathologies in ECG data. In this study, we introduce a method for polyphonic sonification of ECG data, whereby different ECG channels are simultaneously represented by sound of different pitch. We retrospectively applied this method to 12 samples from a publicly available ECG database. We and colleagues from our professional environment then analyzed these data in a blinded. Based on these analyses, we found that the sonification technique can be intuitively understood after a short training session. On average, the correct classification rate for observers trained in cardiology was 78%, compared to 68% and 50% for observers not trained in cardiology or not trained in medicine at all, respectively. These values compare to an expected random guessing performance of 25%. Strikingly, 27% of all observers had a classification accuracy over 90%, indicating that sonification can be very successfully used by talented individuals. These findings can serve as a baseline for potential clinical applications of ECG sonification