The relevance of cortical grey matter pathology in multiple sclerosis has become increasingly recognized over the past decade. Unfortunately, a large part of cortical lesions remain undetected on ...magnetic resonance imaging using standard field strength. In vivo studies have shown improved detection by using higher magnetic field strengths up to 7 T. So far, a systematic histopathological verification of ultra-high field magnetic resonance imaging pulse sequences has been lacking. The aim of this study was to determine the sensitivity of 7 T versus 3 T magnetic resonance imaging pulse sequences for the detection of cortical multiple sclerosis lesions by directly comparing them to histopathology. We obtained hemispheric coronally cut brain sections of 19 patients with multiple sclerosis and four control subjects after rapid autopsy and formalin fixation, and scanned them using 3 T and 7 T magnetic resonance imaging systems. Pulse sequences included T1-weighted, T2-weighted, fluid attenuated inversion recovery, double inversion recovery and T2*. Cortical lesions (type I-IV) were scored on all sequences by an experienced rater blinded to histopathology and clinical data. Staining was performed with antibodies against proteolipid protein and scored by a second reader blinded to magnetic resonance imaging and clinical data. Subsequently, magnetic resonance imaging images were matched to histopathology and sensitivity of pulse sequences was calculated. Additionally, a second unblinded (retrospective) scoring of magnetic resonance images was performed. Regardless of pulse sequence, 7 T magnetic resonance imaging detected more cortical lesions than 3 T. Fluid attenuated inversion recovery (7 T) detected 225% more cortical lesions than 3 T fluid attenuated inversion recovery (Z = 2.22, P < 0.05) and 7 T T2* detected 200% more cortical lesions than 3 T T2* (Z = 2.05, P < 0.05). Sensitivity of 7 T magnetic resonance imaging was influenced by cortical lesion type: 100% for type I (T2), 11% for type II (FLAIR/T2), 32% for type III (T2*), and 68% for type IV (T2). We conclude that ultra-high field 7 T magnetic resonance imaging more than doubles detection of cortical multiple sclerosis lesions, compared to 3 T magnetic resonance imaging. Unfortunately, (subpial) cortical pathology remains more extensive than 7 T magnetic resonance imaging can reveal.
Purpose
Assess the potential gain in acceleration performance of a 256‐channel versus 32‐channel receive coil array at 7 T in combination with a 2D CAIPIRINHA sequence for 3D data sets.
Methods
A ...256‐channel receive setup was simulated by placing 2 small 16‐channel high‐density receive arrays at 2 × 8 different locations on the head of healthy participants. Multiple consecutive measurements were performed and coil sensitivity maps were combined to form a complete 256‐channel data set. This setup was compared with a standard 32‐channel head coil, in terms of SNR, noise correlation, and acceleration performance (g‐factor).
Results
In the periphery of the brain, the receive SNR was on average a factor 1.5 higher (ranging up to a factor 2.7 higher) than the 32‐channel coil; in the center of the brain the SNR was comparable or lower, depending on the size of the region of interest, with a factor 1.0 on average (ranging from 0.7 up to a factor of 1.6). The average noise correlation between coil elements was 3% for the 256‐channel coil, and 5% for the 32‐channel coil. At acceptable g‐factors (< 2), the achievable acceleration factor using SENSE and 2D CAIPIRINHA was 24 and 28, respectively, versus 9 and 12 for the 32‐channel coil.
Conclusion
The receive performance of the simulated 256 channel array was better than the 32‐channel reference. Combined with 2D CAIPIRINHA, a peak acceleration factor of 28 was assessed, showing great potential for high‐density receive arrays.
Objectives
Several intracranial vessel wall sequences have been described in recent literature, with either 3-T or 7-T magnetic resonance imaging (MRI). In the current study, we compared 3-T and 7-T ...MRI in visualising both the intracranial arterial vessel wall and vessel wall lesions.
Methods
Twenty-one elderly asymptomatic volunteers were scanned by 3-T and 7-T MRI with an intracranial vessel wall sequence, both before and after contrast administration. Two raters scored image quality, and presence and characteristics of vessel wall lesions.
Results
Vessel wall visibility was equal or significantly better at 7 T for the studied arterial segments, even though there were more artefacts hampering assessment. The better visualisation of the vessel wall at 7 T was most prominent in the proximal anterior cerebral circulation and the posterior cerebral artery. In the studied elderly asymptomatic population, 48 vessel-wall lesions were identified at 3 T, of which 7 showed enhancement. At 7 T, 79 lesions were identified, of which 29 showed enhancement. Seventy-one percent of all 3-T lesions and 59 % of all 7-T lesions were also seen at the other field strength.
Conclusions
Despite the large variability in detected lesions at both field strengths, we believe 7-T MRI has the highest potential to identify the total burden of intracranial vessel wall lesions.
Key Points
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Intracranial vessel wall visibility was equal or significantly better at 7-T MRI
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Most vessel wall lesions in the cerebral arteries were found at 7-T MRI
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Many intracranial vessel wall lesions showed enhancement after contrast administration
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Large variability in detected intracranial vessel wall lesions at both field strengths
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Seven-tesla MRI has the highest potential to identify total burden of intracranial atherosclerosis
Purpose
In this work a simulation study is performed to gain insights in the patterns of induced radiofrequency (RF) currents for various implant‐like structures at 1.5 T. The previously introduced ...transfer matrix (TM) is used to determine why certain current patterns have a tendency to naturally occur. This can benefit current safety assessment techniques and may enable the identification of critical exposure conditions.
Theory and Methods
The induced current on an elongated implant can be determined by multiplication of the incident electric field along the implant with its TM. The eigenmode spectrum of the TMs for various lengths and various types of implants are determined. The eigenvector with the highest eigenvalue describes the incident electric field pattern that induces the highest current which in turn will lead to highest heating. Subsequently, a statistical probability analysis is performed using a wide range of potential incident electric field distributions in a representative human subject model during a 1.5 T MR exam which are determined by means of electromagnetic FDTD simulations. These incident electric field distributions and the resulting induced current patterns are projected onto eigenvectors of the TM to determine which eigenmodes of the implant dominate the current patterns.
Results
The eigenvectors of the TM of bare and insulated wires resemble sinusoidal harmonics of a string fixed at both ends similar to the natural‐current distribution on thin antennas(1). The currents on implants shorter than 20 cm are generally dominated by the first harmonic (similar to half a sine wave). This is firstly because for these implant lengths (relative to the RF wavelength), the first eigenvalue is more than three times bigger than the second showing the ability of an implant to accommodate one eigenmode better than another. Secondly, the incident electric fields have a high likelihood (≳95,7%) to project predominantly on this first eigenmode.
Conclusion
The eigenmode spectrum of the TM of an implant provides insight into the expected shape of induced current distributions and worst‐case exposure conditions. For short implants, the first eigenvector is dominant. In addition, realistic incident electric field distributions project more heavily on this eigenvector. Both effects together cause significant currents to always resemble the dominant eigenmode of the TM for short implants at 1.5 T.
The purpose of this work was to investigate noninvasive early detection of treatment response of breast cancer patients to neoadjuvant chemotherapy (NAC) using chemical exchange saturation transfer ...(CEST) measurements sensitive to amide proton transfer (APT) at 7 T.
CEST images were acquired in 10 tumors of nine breast cancer patients treated with NAC. APT signals in the tumor, before and after the first cycle of NAC, were quantified using a three-pool Lorentzian fit of the z-spectra in the region of interest. The changes in APT were subsequently related to pathological response after surgery defined by the Miller-Payne system.
Significant differences (P < 0.05, unpaired Mann-Whitney test) were found in the APT signal before and after the first cycle of NAC in six out of 10 lesions, of which two showed a pathological complete response. Of the remaining four lesions, one showed a pathological complete response. No significant difference in changes of APT signal were found between the different pathological responses to NAC treatment (P > 0.05, Kruskal-Wallis test).
This preliminary study shows the feasibility of using APT CEST magnetic resonance imaging as a noninvasive biomarker to assess the effect of NAC in an early stage of NAC treatment of breast cancer patients.
Registration number, NL49333.041.14/ NTR4980 . Registered on 16 October 2014.
High-field gradient-echo (GE) BOLD fMRI enables very high resolution imaging, and has great potential for detailed investigations of brain function. However, as spatial resolution increases, ...confounds due to signal from non-capillary vessels increasingly impact the fidelity of GE BOLD fMRI signals. Here we report on an assessment of the microvascular weighting of the GE BOLD response across the cortical depth in human cortex using spin-echo fMRI which is thought to be dominated by microvasculature (albeit not completely). BOLD responses were measured with a hemodynamic impulse response (HRF) obtained from the spin-echo (SE) and gradient-echo (GE) BOLD contrast using very short stimuli (0.25 s) and a fast event-related functional paradigm. We show that the onset (≈ 1.25 s) and the rising slope of the GE and SE HRFs are strikingly similar for voxels in deep gray matter presumably containing the most metabolically demanding neurons (layers III-IV). This finding provides a strong indication that the onset of the GE HRF in deep gray matter is predominantly associated with microvasculature.
In the radiofrequency (RF) range, the electrical properties of tissues (EPs: conductivity and permittivity) are modulated by the ionic and water content, which change for pathological conditions. ...Information on tissues EPs can be used e.g. in oncology as a biomarker. The inability of MR-Electrical Properties Tomography techniques (MR-EPT) to accurately reconstruct tissue EPs by relating MR measurements of the transmit RF field to the EPs limits their clinical applicability. Instead of employing electromagnetic models posing strict requirements on the measured MRI quantities, we propose a data driven approach where the electrical properties reconstruction problem can be casted as a supervised deep learning task (DL-EPT). DL-EPT reconstructions for simulations and MR measurements at 3 Tesla on phantoms and human brains using a conditional generative adversarial network demonstrate high quality EPs reconstructions and greatly improved precision compared to conventional MR-EPT. The supervised learning approach leverages the strength of electromagnetic simulations, allowing circumvention of inaccessible MR electromagnetic quantities. Since DL-EPT is more noise-robust than MR-EPT, the requirements for MR acquisitions can be relaxed. This could be a major step forward to turn electrical properties tomography into a reliable biomarker where pathological conditions can be revealed and characterized by abnormalities in tissue electrical properties.
Purpose
The introduction of a linear safety factor to address peak local specific absorption rate (pSAR10g) uncertainties (eg, intersubject variation, modeling inaccuracies) bears one considerable ...drawback: It often results in over‐conservative scanning constraints. We present a more efficient approach to define a variable safety margin based on the conditional probability density function of the effectively obtained pSAR10g value, given the estimated pSAR10g value.
Methods
The conditional probability density function can be estimated from previously simulated data. A representative set of true and estimated pSAR10g samples was generated by means of our database of 23 subject‐specific models with an 8‐fractionated dipole array for prostate imaging at 7 T. The conditional probability density function was calculated for each possible estimated pSAR10g value and used to determine the corresponding safety margin with an arbitrary low probability of underestimation. This approach was applied to five state‐of‐the‐art local SAR estimation methods, namely: (1) using just the generic body model “Duke”; (2) using our model library to assess the maximum pSAR10g value over all models; (3) using the most representative “local SAR model”; (4) using the five most representative local SAR models; and (5) using a recently developed deep learning–based method.
Results
Compared with the more conventional safety factor, the conditional safety‐margin approach results in lower (up to 30%) mean overestimation for all investigated local SAR estimation methods.
Conclusion
The proposed probabilistic approach for pSAR10g correction allows more accurate local SAR assessment with much lower overestimation, while a predefined level of underestimation is accepted (eg, 0.1%).
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