Multiparametric magnetic resonance imaging

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Comparison of initial and tertiary centre second opinion reads of multiparametric magnetic resonance imaging of the prostate prior to repeat biopsy

Comparison of initial and tertiary centre second opinion reads of multiparametric magnetic resonance imaging of the prostate prior to repeat biopsy

Introduction Multiparametric magnetic resonance imaging (mpMRI) of the prostate is increasingly used to identify men with significant prostate cancer [ 1 ]. It has been shown to be effective for the detection and local staging of prostate cancers and can prefer- entially detect clinically relevant index tumours of higher grade and a size >5 mm [ 2 ]. A normal mpMRI has been shown to have a high negative predictive value (NPV) (90- 98 %) for the presence of clinically significant disease in bi- opsy [ 3 – 5 ]. However, these literature-reported rates are typi- cally from tertiary referral centres with optimised MRI proto- cols and subspecialist reporters. Even with expert reads, it is estimated that the use of mpMRI may lead to as many as 25 % of significant cancers being missed, when a radical prostatec- tomy specimen is used as the reference method [ 6 , 7 ]. One reason for inaccurate detection of significant cancer in mpMRI could be that mpMRI interpretation accuracy highly depends on the experience of the reader [ 8 – 14 ]. Currently, it is estimated that 100 mpMRI reports supervised by a systematic double-reader and validated by histopathology are needed to gain sufficient reader competence [ 15 ], and subsequently at least 50 mpMRIs per year are required to maintain experience levels [ 16 ]. Whilst PI-RADS version 1 focused mainly on minimal and optimal MRI protocol standards, the more re- cently updated PI-RADS version 2 concentrates on standardisation of reading, highlighting a perceived problem [ 17 , 18 ].
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Comparison of initial and tertiary centre second opinion reads of multiparametric magnetic resonance imaging of the prostate prior to repeat biopsy

Comparison of initial and tertiary centre second opinion reads of multiparametric magnetic resonance imaging of the prostate prior to repeat biopsy

Introduction Multiparametric magnetic resonance imaging (mpMRI) of the prostate is increasingly used to identify men with significant prostate cancer [ 1 ]. It has been shown to be effective for the detection and local staging of prostate cancers and can prefer- entially detect clinically relevant index tumours of higher grade and a size >5 mm [ 2 ]. A normal mpMRI has been shown to have a high negative predictive value (NPV) (90- 98 %) for the presence of clinically significant disease in bi- opsy [ 3 – 5 ]. However, these literature-reported rates are typi- cally from tertiary referral centres with optimised MRI proto- cols and subspecialist reporters. Even with expert reads, it is estimated that the use of mpMRI may lead to as many as 25 % of significant cancers being missed, when a radical prostatec- tomy specimen is used as the reference method [ 6 , 7 ]. One reason for inaccurate detection of significant cancer in mpMRI could be that mpMRI interpretation accuracy highly depends on the experience of the reader [ 8 – 14 ]. Currently, it is estimated that 100 mpMRI reports supervised by a systematic double-reader and validated by histopathology are needed to gain sufficient reader competence [ 15 ], and subsequently at least 50 mpMRIs per year are required to maintain experience levels [ 16 ]. Whilst PI-RADS version 1 focused mainly on minimal and optimal MRI protocol standards, the more re- cently updated PI-RADS version 2 concentrates on standardisation of reading, highlighting a perceived problem [ 17 , 18 ].
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Investigating the prediction value of multiparametric magnetic resonance imaging at 3 T in response to neoadjuvant chemotherapy in breast cancer

Investigating the prediction value of multiparametric magnetic resonance imaging at 3 T in response to neoadjuvant chemotherapy in breast cancer

weighted sequences with fat suppression were used during the period of this study – both were gradient echo-based: i) a high- spatial and high-temporal resolution sequence (time-resolved angiography with stochastic trajectories – TWIST) with a tem- poral resolution of 14 s, spatial isotropic resolution of 1.1 mm 3 , field of view 248 × 350 mm 2 , matrix size 240 × 320, 144 slices per slab, one average, TR/TE of 6.81/ 2.84 ms, and a flip angle of 11° [ 20 ]; or ii) a fast low angle shot (FLASH) sequence with a duration of 2 min, isotropic 1 mm 3 spatial resolution, field of view 320 × 134 mm 2 , matrix size 320 × 134, 96 slices per slab, one average, TR/TE of 877/ 3.82 ms, and a flip angle of 9°, interleaved with high temporal resolution (13 s) volumetric interpolated breath-hold exami- nation (VIBE) imaging [ 21 , 22 ]. Images from these two dif- ferent protocols were considered equivalent because of similar resolution and timing of images used for tumour size evalua- tion. The whole protocol is also represented on the block chart in Fig. 2 . Only one pre-contrast image and one maximum contrast image measured at 2 min 12 s after the contrast agent injection were used in data processing from each sequence. Gadoterate meglumine contrast agent (Dotarem, Guerbet, IN, USA) was injected intravenously as a bolus (0.1 mmol/kg of body weight) 2 min after the start of CE-MRI.
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Multiparametric cardiac magnetic resonance imaging with motion compensation

Multiparametric cardiac magnetic resonance imaging with motion compensation

In contrast to qualitative imaging, quantitative MRI provides direct information of intrinsic biophysical parameters. In MRI a range of different biophysical parameters can be measured allowing for diagnosis of different diseases. The spatially resolved measurement of biophysical parameters is often called mapping, providing images with the relaxation time of the tissue in each voxel. For cardiac applications, the relaxation time T1 has been shown to be a good marker for myocardial diseases [ 7 , 8 , 9 , 10 ]. In contrast to LGE, T1 mapping does not require healthy reference tissue and is the only non-invasive imaging modality that allows for the detection of diffuse myocardial fibrosis. This could be important in the context of diseases such as rheumatoid arthritis, systemic sclerosis, amyloidosis or hypertrophic cardiomyopathy [ 11 , 12 , 7 , 13 ]. Beyond this, not only the presence of a pathology could be detected, but the exact T1 times of the myocardium could be used as an indication for the classification of a disease. For example, T1 values are elevated in amyloidosis and myocardial infarction, but lowered in iron-overload and intracellular lipid disorders [ 7 ]. The quantitative property of T1 mapping provides comparability between measurements, patients and scanner. Hence, it can also be employed for monitoring of treatment response. More important, T1 mapping can be applied without the need for contrast agents.
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Evaluation of multi-parametric Magnetic Resonance Imaging for the detection of
prostate cancer

Evaluation of multi-parametric Magnetic Resonance Imaging for the detection of prostate cancer

Publikation 2: Tobias Franiel, Carsten Stephan, Andreas Erbersdobler, Andreas Maxeiner, Bernd Hamm; Areas Suspicious for Prostate Cancer: MR–guided Biopsy in Patients with at Least One Transrectal US-guided Biopsy with a Negative Finding - Multiparametric MR Imaging for Detection and Biopsy Planning; Radiology: 2011 Apr 259(1):162-72.: Entwicklung des Studienkonzepts und Designs, Datenakquise, Analyse und Interpretation. Verfassen einzelner Passagen und kritisches Überarbeiten des Manuskripts. Finale Zustimmung der zu publizierenden Version des Artikels.
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Multiparametric [C]Acetate positron emission tomography-magnetic resonance imaging in the assessment and staging of prostate cancer

Multiparametric [C]Acetate positron emission tomography-magnetic resonance imaging in the assessment and staging of prostate cancer

Statistical analyses were performed using SPSS (SPSS Statistics ver. 22.0, IBM Corp., USA) and Medcalc 15.8 (Medcalc software bvba, Ostend, Belgium). The calculations were performed patient-wise (Obuchowski level 2 analysis—requirement to correctly localize the lesion). Receiver operating characteristics (ROC) were calculated and plotted for the PSA score and all imaging modalities and their combinations. The following parameters were derived from the ROC curves: area under the curve (AUC) (std. error, statistical significance, as well as upper and lower 95%-CI bound); sensitivity; specificity; positive predictive value (PPV); and negative predictive value (NPV).
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Analysis of functional magnetic resonance imaging time series by independent component analysis

Analysis of functional magnetic resonance imaging time series by independent component analysis

Independent component analysis is a method for blind signal separation formed on the basis of assumed statistical independence of the source signals. The problem of blind source sep- aration or blind signal separation (BSS) appears in many contexts. Blind source separation is a class of explorative tools originally developed for the analysis of images and sound. BSS has received wide attention in various fields such as speech enhancement, geophysical data processing, data mining, wireless communications, image processing, and biomedical signal analysis and processing (EEG, MEG, fMRI). The method is called ’blind’ because it aims to recover source signals from mixtures with unknown coefficients. The most simple situation occurs for two speakers speaking simultaneously. Imagine that the mixture of their voices reaches two microphones, and one wants to separate both sources such that each detector registers only one voice. The problem is called the cocktail party problem which can also be extended to N people standing around and chatting with each other. This mixture of signals is recorded by N microphones. Again, the aim is to extract the voices of the speaker (the sources) from the mixture of speech signals without knowing the sources and the mixture process assuming that the voices are independent of each other. In this project the problem of BSS is applied to the field of functional magnetic resonance imaging (fMRI), especially to fMRI time series, For the fMRI time series it is assumed that the measured signal of neuronal activity are mixed linearly with multiple other signals like noise or movement artifacts, contributing to the measurement. The aim of blind signal sep- aration in fMRI is to detect the intrinsic signals, i.e. the neuronal activity, from the mixed signals measured during the fMRI study. ICA is a statistical approach of transforming multidimensional data into components that are as independent of each other as possible.
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A navigator based rigid body motion correction for magnetic Resonance imaging

A navigator based rigid body motion correction for magnetic Resonance imaging

One approach not relying on external hardware is to introduce virtual rotations. That is, the imaged object is kept steady while the gradient waveforms are rotated. One drawback of this method is that the inhomogeneities of the static magnetic field and the RF excitation field on the rotation estimation are likely to be underes- timated. On the other hand, the best possible gold standard for the rotation parameters is obtained: the exact input value. For this rea- son, virtual rotations were implemented into the sequence described in Section 7.1. The rotation parameters used throughout the mea- surements presented in this chapter consisted of sinusoidal rotations between -30 ◦ and 30 ◦ . Rotations were applied around a single phys- ical gradient axis at a time, that is, sequentially for all three axes. Figure 7.2 depicts a plot of the virtual rotation parameters used. For measurements with more than 300 navigators, the rotation pattern was repeated until the end of the measurement.
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Three-dimensional In vivo magnetic resonance imaging (MRI) of mouse facial nerve regeneration

Three-dimensional In vivo magnetic resonance imaging (MRI) of mouse facial nerve regeneration

FIGURE 2 | MR imaging of the intact mouse facial nerve. (A) Scheme of facial nerve branches including the buccal (b) and marginal (m) branch in the adult mouse. (B) Light microscopical picture of the buccal and marginal facial nerve branches before MR imaging. Both nerves appear as white structures localized on top of the masseter muscle. (C) Fat-suppressed, T 2 -weighted MR image depicting the buccal and marginal branch in rostro-caudal slice orientation. The orientation of the picture is identical to the scheme in (A). Both nerve branches are hyperintense compared to the surrounding muscle tissue. The marginal branch is split in a thicker and a thinner branch (arrowheads) with approximately only 100 µm or less in thickness. The red dotted lines indicate the four positions of cross-section through the nerve provided in (F–I). (D,E) Representation of the buccal (D) and marginal (E) branch in longitudinal orientation, clearly showing the thickness variation of the respective nerves along its course. (F–I) Four cross-sections at different rostro-caudal positions of the marginal branch in (C). Several smaller fascicles of the marginal branch are visible in (I). Scale-bar = 1 mm (B–E), 0.5 mm (F–I).
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Development and application of electrical conductivity mapping using magnetic resonance imaging

Development and application of electrical conductivity mapping using magnetic resonance imaging

5.2 Methods 71 Magnetic susceptibility The QSM processing was done using in-house-developed Matlab-based software as follows. To obtain QSM maps from the GRE phase images, two crucial preliminary steps are required: phase unwrapping and background phase removal. All echoes were first spatially unwrapped using an algorithm proposed by Abdul-Rahman [97]. Thereafter, echoes were correctly aligned in the temporal dimension using temporal unwrap of the phase from voxels with very small field inhomogeneity. The field maps were computed by applying a linear regression to the temporal evolution of the unwrapped phase during the echo times. The liner regression also gives the TE=0ms phase information, which is used as a starting point in the electrical conductivity processing (see next section). The 2D field maps were interpolated in the through-plane direction in order to provide an isotropic sampling of the volume-of-interest. The contribution of background fields was then eliminated using MUBAFIRE [98]. Finally, the dipole inversion was carried out using a Tikhonov- and gradient-regularised minimisation algorithm, resulting in the susceptibility map [99]. The results of the resampled 2D QSM and the isotropic 3D QSM were compared. The CSF value was then chosen as the reference value and set to zero. The regions of interests (ROIs) were drawn for iron-rich nuclei and subcortical gray matter, white matter areas. These include the caudate nucleus (CN), putamen (PU), globus pallidus (GP), internal capsule (IC), red nucleus (RN), substantia nigra (SN), cortical gray matter (C-GM) and cortical white matter (C-WM).
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Optimisation of Phase Data Processing for Susceptibility Reconstruction in Magnetic Resonance Imaging

Optimisation of Phase Data Processing for Susceptibility Reconstruction in Magnetic Resonance Imaging

7.4. RECONSTRUCTING SUSCEPTIBILITY DISTRIBUTIONS 7.4 Reconstructing Susceptibility Distributions All strategies for estimating susceptibility distributions in soft tissue are based on the a priori estimation of fieldmaps, and thus on phase imaging. Single-echo GRE measurements are not useful for this aim, since fieldmaps derived of such data may contain deviations from the true field due to unconsidered phase offsets (see Section 6.1). Fieldmaps used for susceptibility recon- struction should at least rely on double-echo, or offset-corrected phase data. Furthermore it is evident, that the estimation of susceptibility requires knowledge of the magnetic field in all spatial dimensions. Ideally, an isotropic sampling of space should be attempted. This is best achieved using an isotropically sampled, full 3D GRE sequence with slab- or non-selective excitation. Sev- eral strategies for the reconstruction of tissue magnetic susceptibility were introduced during the last years. Two main categories can be defined, single and multiple orientation measurements. Furthermore, reconstruction can be performed directly or by using a minimisation approach. All methods presented below use the model of scalar susceptibility (Section 7.3.1), and will be shown in application examples using optimised parametrisation. Parameter optimisation will be discussed later on in Section 7.6. A comprehensive discussion of the current reconstruction techniques and applications for susceptibility imaging in MRI can be found in Reichenbach [ 2012 ].
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Optimisation of Phase Data Processing for Susceptibility Reconstruction in Magnetic Resonance Imaging

Optimisation of Phase Data Processing for Susceptibility Reconstruction in Magnetic Resonance Imaging

7.4. RECONSTRUCTING SUSCEPTIBILITY DISTRIBUTIONS 7.4 Reconstructing Susceptibility Distributions All strategies for estimating susceptibility distributions in soft tissue are based on the a priori estimation of fieldmaps, and thus on phase imaging. Single-echo GRE measurements are not useful for this aim, since fieldmaps derived of such data may contain deviations from the true field due to unconsidered phase offsets (see Section 6.1). Fieldmaps used for susceptibility recon- struction should at least rely on double-echo, or offset-corrected phase data. Furthermore it is evident, that the estimation of susceptibility requires knowledge of the magnetic field in all spatial dimensions. Ideally, an isotropic sampling of space should be attempted. This is best achieved using an isotropically sampled, full 3D GRE sequence with slab- or non-selective excitation. Sev- eral strategies for the reconstruction of tissue magnetic susceptibility were introduced during the last years. Two main categories can be defined, single and multiple orientation measurements. Furthermore, reconstruction can be performed directly or by using a minimisation approach. All methods presented below use the model of scalar susceptibility (Section 7.3.1), and will be shown in application examples using optimised parametrisation. Parameter optimisation will be discussed later on in Section 7.6. A comprehensive discussion of the current reconstruction techniques and applications for susceptibility imaging in MRI can be found in Reichenbach [ 2012 ].
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Foci on breast magnetic resonance imaging in high-risk women: cancer or not?

Foci on breast magnetic resonance imaging in high-risk women: cancer or not?

In conclusion, we found that foci are a relatively fre- quent finding in screening breast MRI performed in high- risk women, but they are rarely related to malignancy. Malignant lesions were more frequent in women with dense breast, while no relation with background parenchy- mal enhancement was found. Malignancy rate of foci does not seem to be higher, as compared to the general popula- tion, thus suggesting that the same management could be adopted. When a focus increases in size, or shows suspi- cious imaging characteristics, biopsy must always be per- formed. Whether the best management of a newly detected focus is biopsy, short-term follow-up or 1-year follow-up is still under discussion; and further studies will be necessary to clarify this issue.
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Ultra-high field magnetic resonance diffusion tensor imaging of the hyaline articular cartilage

Ultra-high field magnetic resonance diffusion tensor imaging of the hyaline articular cartilage

Large, rapidly switched magnetic field gradients during the diffusion sequence produce electric fields that result from changing magnetic flux (Faraday’s law). These electric fields induce eddy currents in the MR system. In turn, the eddy currents produce additional unwanted, rapidly and slowly decaying magnetic fields ( Basser 2002; Bernstein 2004). Depending on their spatial dependence, eddy currents will be classified into B 0 eddy currents which are spatially constant over the image volume, and linear eddy currents, which have a linear spatial dependency similar to imaging gradient fields (Bernstein 2004). Linear eddy currents results in two undesirable effects: first, the effective magnetic gradient at the sample differs from the set magnetic gradient, resulting in a difference between the effective and calculated b-matrix; second, the eddy current produces a slowly decaying field during readout of the image causing geometrical distortions of the diffusion-weighted image. (Basser 2002). In our measurements, the linear eddy currents were predominant compared to the B 0 eddy currents. The resulting preemphasized waveform for the linear component looks like a high-pass-filtered version of the original gradient waveform (Bernstein 2004). The result was that geometrical distortions were corrected. Nevertheless, the eddy current induced an apparent anisotropy in the isotropic phantom. To reduce this effect, correction strategies based on the acquisition of diffusion-weighted data with opposite polarity diffusion gradients were adopted (Bodammer 2004; Neeman 1991).
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Elucidating the ionic liquid distribution in monolithic SILP hydroformylation catalysts by magnetic resonance imaging

Elucidating the ionic liquid distribution in monolithic SILP hydroformylation catalysts by magnetic resonance imaging

nation, but the distribution of the catalyst system on the monolith is challenging to reveal. For surface-sensitive analytic techniques, such as scanning electron microscopy (SEM) or transmission elec- tron microscopy (TEM), the monoliths need to be divided into small samples, which might inuence the catalyst system. To this end, less invasive techniques are therefore preferred. X-ray absorption techniques, such as computed tomography (CT), are sensitive to heavy elements and therefore lack in contrast between IL in the pores and the solid SiC matrix. For high resolution, micro- tomography (micro-CT) is favorable but also requires invasive cutting of the monolith. An alternative, non-invasive technique with lower resolution focusing on the liquid catalyst system is magnetic resonance imaging (MRI) being one of the modes of nuclear magnetic resonance (NMR). MRI applies radiofrequency radiation and provides therefore access to optically opaque materials while unique contrast parameters such as NMR relaxation, can be exploited to increase the information content. Accordingly, MRI has been used for the examination of a wide range of both, so and hard materials such as polymers, food, plants and wood 18–22 as well
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A flexible coil array for high resolution magnetic resonance imaging at 7 Tesla

A flexible coil array for high resolution magnetic resonance imaging at 7 Tesla

105 mechanical deformation of the TLR array. The proposed decoupling technique is especially favorable for form-fitting TLR arrays comprising a large number of elements, because readily decoupled arrays can be fabricated on a single flexible substrate in one standard photo-lithographic etching process. Also, in contrast to previous work proposing the principle of magnetic flux sharing for physically separated coils [113,114], no soldering is necessary. Such flexible arrays are well-suited for studying anatomical regions, which may vary strongly in size and shape from patient to patient and require both a large FOV and high SNR. Potential biomedical applications include high-resolution imaging of skin and joints like wrist, elbow or knee, or dynamic imaging of moving organs such as the heart. In this respect, the performance of the developed prototype array will be further improved by increasing the number of coil elements and by adapting the size of the individual elements to the targeted organ or structure.
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Hippocampal Subfields in Acute and Remitted Depressionan Ultra-High Field Magnetic Resonance Imaging Study

Hippocampal Subfields in Acute and Remitted Depressionan Ultra-High Field Magnetic Resonance Imaging Study

Hippocampal formation volumes represent a surrogate of neuronal plasticity and can be measured in MDD patients in vivo with structural magnetic resonance imaging (MRI) and automatic or manual volume analysis. Several previous studies reported hippocampal formation volume increases after treatment. After 8 weeks of antidepressant treatment with citalopram, hippocampal formation volume increases were demonstrated in patients with MDD ( Arnone et al., 2013 ). An earlier study reported volume increases after 12 weeks of treatment with paroxetine in patients with posttraumatic stress disorder ( Vermetten et  al., 2003 ). A  third study with a naturalistic inpatient setting and a mixed antidepressant treat- ment regime detailed posterior hippocampal volume increases after approximately 23 weeks of treatment ( Schermuly et  al., 2011 ). Those studies highlight that pro-neuroplastic effects of monoaminergic antidepressants supported by animal litera- ture ( Pittenger and Duman, 2008 ; Malykhin and Coupland, 2015 ; Duman et  al., 2016 ) could mediate hippocampal volume in- creases in humans. In contrast, several results found no volume increases after treatment ( Frodl et al., 2004 ; Vythilingam et al., 2004 ; Phillips et al., 2015 ). Still, subgroup analyses in 2 of these studies found hippocampal volume increases in remitted and acute patients continuously taking antidepressants ( Frodl et al., 2004 ; Phillips et  al., 2015 ). While the reasons for discrepancies between these results remain unclear, further studies using re- fined methods are warranted.
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Quantitative assessment of the equine hoof using digital radiography and magnetic resonance imaging

Quantitative assessment of the equine hoof using digital radiography and magnetic resonance imaging

Following MR imaging, the distal extremities were sectioned in a sagittal plane using a band saw. (Figure 8 a) Tissue specimens were collected from the distal half of the dorsal hoof wall and lateral, medial and mid-sagittal aspects of the sole. The samples were fixed in 10% neutral-buffered formalin for at least 48 hours, trimmed for paraffin embedding and tissue sectioning. Slides were stained with hematoxylin and eosin and contained the stratum lamellatum and stratum reticulare. Histopathologic evaluation was performed by a board-certified veterinary pathologist to confirm absence of lamellar disease. Only feet without lamellar disease were included in the study.
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Accuracy of various lymph node staging criteria in rectal cancer with magnetic
resonance imaging

Accuracy of various lymph node staging criteria in rectal cancer with magnetic resonance imaging

„Ich, Florian Nino Loch, versichere an Eides statt durch meine eigenhändige Unterschrift, dass ich die vorgelegte Dissertation mit dem Thema: „Accuracy of various lymph node staging criteria in rectal cancer with magentic resonance imaging“ selbstständig und ohne nicht offengelegte Hilfe Dritter verfasst und keine anderen als die angegebenen Quellen und Hilfsmittel genutzt habe.

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Exploring novel magnetic resonance imaging markers for ischemic stroke in the
application of vessel size imaging and amide proton transfer imaging

Exploring novel magnetic resonance imaging markers for ischemic stroke in the application of vessel size imaging and amide proton transfer imaging

The APT imaging provides an in vivo estimation of the pH value. However, its clini- cal application has been limited, since it requires multiple scans with an off-resonance saturation, which leads to a long measurement time and a high SAR. In this work, we designed a sequence integrated a field-map measurement in the reference scan and in- troduced a turbo factor to accelerate the data acquisition during the RF off-duty time after the saturation. The edge-in sampling scheme ensured that the central portion of k-space was acquired during the steady state. This technique was applied to two stroke patients to enable the pH-weighted APTR mapping for the first time in clinical stroke studies. Preliminary hypointensities of the APTR in the ischemic penumbra and the acute infarction suggested that the ischemic acidosis in the tissue may indicate the fate of infarction.
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