Florian Wiesinger

Bio: Florian Wiesinger is an academic researcher from GE Healthcare. The author has contributed to research in topics: Correction for attenuation & Imaging phantom. The author has an hindex of 26, co-authored 101 publications receiving 3354 citations. Previous affiliations of Florian Wiesinger include University of Zurich & General Electric.

B1 mapping by Bloch-Siegert shift.

Abstract: A novel method for amplitude of radiofrequency field (B1+) mapping based on the Bloch-Siegert shift is presented. Unlike conventionally applied double-angle or other signal magnitude-based methods, it encodes the B(1) information into signal phase, resulting in important advantages in terms of acquisition speed, accuracy, and robustness. The Bloch-Siegert frequency shift is caused by irradiating with an off-resonance radiofrequency pulse following conventional spin excitation. When applying the off-resonance radiofrequency in the kilohertz range, spin nutation can be neglected and the primarily observed effect is a spin precession frequency shift. This shift is proportional to the square of the magnitude of B1(2). Adding gradient image encoding following the off-resonance pulse allows one to acquire spatially resolved B(1) maps. The frequency shift from the Bloch-Siegert effect gives a phase shift in the image that is proportional to B(1)(2). The phase difference of two acquisitions, with the radiofrequency pulse applied at two frequencies symmetrically around the water resonance, is used to eliminate undesired off-resonance effects due to amplitude of static field inhomogeneity and chemical shift. In vivo Bloch-Siegert B(1) mapping with 25 sec/slice is demonstrated to be quantitatively comparable to a 21-min double-angle map. As such, this method enables robust, high-resolution B(1)(+) mapping in a clinically acceptable time frame.

Transmit and receive transmission line arrays for 7 Tesla parallel imaging

Abstract: Transceive array coils, capable of RF transmission and independent signal reception, were developed for parallel, 1H imaging applications in the human head at 7 T (300 MHz). The coils combine the advantages of high-frequency properties of transmission lines with classic MR coil design. Because of the short wavelength at the 1H frequency at 300 MHz, these coils were straightforward to build and decouple. The sensitivity profiles of individual coils were highly asymmetric, as expected at this high frequency; however, the summed images from all coils were relatively uniform over the whole brain. Data were obtained with four- and eight-channel transceive arrays built using a loop configuration and compared to arrays built from straight stripline transmission lines. With both the four- and the eight-channel arrays, parallel imaging with sensitivity encoding with high reduction numbers was feasible at 7 T in the human head. A one-dimensional reduction factor of 4 was robustly achieved with an average g value of 1.25 with the eight-channel transmit/receive coils.

Electrodynamics and ultimate SNR in parallel MR imaging

Abstract: The purpose of this article is to elucidate inherent limitations to the performance of parallel MRI. The study focuses on the ultimate signal-to-noise ratio (SNR), which refers to the maximum SNR permitted by the electrodynamics of the signal detection process. Using a spherical model object, it is shown that the behavior of the ultimate SNR imposes distinct limits on the acceleration rate in parallel imaging. For low and moderate acceleration, the ultimate SNR performance is nearly optimal, with geometry factors close to 1. However, for high reduction factors beyond a critical value, the ultimate performance deteriorates rapidly, corresponding to exponential growth of the geometry factor. The transition from optimal to deteriorating performance depends on the electrodynamic characteristics of the detected RF fields. In the near-field regime, i.e., for low B0 and small object size, the critical reduction factor is constant and approximately equal to four for 1D acceleration in the sphere. In the far-field wave regime the critical reduction factor is larger and increases both with B0 and object size. Therefore, it is concluded that parallel techniques hold particular promise for human MR imaging at very high field. Magn Reson Med 52:376–390, 2004. © 2004 Wiley-Liss, Inc.

Zero-Echo-Time and Dixon Deep Pseudo-CT (ZeDD CT): Direct Generation of Pseudo-CT Images for Pelvic PET/MRI Attenuation Correction Using Deep Convolutional Neural Networks with Multiparametric MRI

Abstract: Accurate quantification of uptake on PET images depends on accurate attenuation correction in reconstruction. Current MR-based attenuation correction methods for body PET use a fat and water map derived from a 2-echo Dixon MRI sequence in which bone is neglected. Ultrashort-echo-time or zero-echo-time (ZTE) pulse sequences can capture bone information. We propose the use of patient-specific multiparametric MRI consisting of Dixon MRI and proton-density–weighted ZTE MRI to directly synthesize pseudo-CT images with a deep learning model: we call this method ZTE and Dixon deep pseudo-CT (ZeDD CT). Methods: Twenty-six patients were scanned using an integrated 3-T time-of-flight PET/MRI system. Helical CT images of the patients were acquired separately. A deep convolutional neural network was trained to transform ZTE and Dixon MR images into pseudo-CT images. Ten patients were used for model training, and 16 patients were used for evaluation. Bone and soft-tissue lesions were identified, and the SUVmax was measured. The root-mean-squared error (RMSE) was used to compare the MR-based attenuation correction with the ground-truth CT attenuation correction. Results: In total, 30 bone lesions and 60 soft-tissue lesions were evaluated. The RMSE in PET quantification was reduced by a factor of 4 for bone lesions (10.24% for Dixon PET and 2.68% for ZeDD PET) and by a factor of 1.5 for soft-tissue lesions (6.24% for Dixon PET and 4.07% for ZeDD PET). Conclusion: ZeDD CT produces natural-looking and quantitatively accurate pseudo-CT images and reduces error in pelvic PET/MRI attenuation correction compared with standard methods.

Zero TE MR bone imaging in the head.

Abstract: Purpose To investigate proton density (PD)-weighted zero TE (ZT) imaging for morphological depiction and segmentation of cranial bone structures. Methods A rotating ultra-fast imaging sequence (RUFIS) type ZT pulse sequence was developed and optimized for 1) efficient capture of short T2 bone signals and 2) flat PD response for soft-tissues. An inverse logarithmic image scaling (i.e., −log(image)) was used to highlight bone and differentiate it from surrounding soft-tissue and air. Furthermore, a histogram-based bias-correction method was developed for subsequent threshold-based air, soft-tissue, and bone segmentation. Results PD-weighted ZT imaging in combination with an inverse logarithmic scaling was found to provide excellent depiction of cranial bone structures. In combination with bias correction, also excellent segmentation results were achieved. A two-dimensional histogram analysis demonstrates a strong, approximately linear correlation between inverse log-scaled ZT and low-dose CT for Hounsfield units (HU) between −300 HU and 1,500 HU (corresponding to soft-tissue and bone). Conclusions PD-weighted ZT imaging provides robust and efficient depiction of bone structures in the head, with an excellent contrast between air, soft-tissue, and bone. Besides structural bone imaging, the presented method is expected to be of relevance for attenuation correction in positron emission tomography (PET)/MR and MR-based radiation therapy planning. Magn Reson Med 75:107–114, 2016. © 2015 Wiley Periodicals, Inc.

Multiband Multislice GE-EPI at 7 Tesla, With 16-Fold Acceleration Using Partial Parallel Imaging With Application to High Spatial and Temporal Whole-Brain FMRI

Abstract: Parallel imaging in the form of multiband radiofrequency excitation, together with reduced k-space coverage in the phase-encode direction, was applied to human gradient echo functional MRI at 7 T for increased volumetric coverage and concurrent high spatial and temporal resolution. Echo planar imaging with simultaneous acquisition of four coronal slices separated by 44mm and simultaneous 4-fold phase-encoding undersampling, resulting in 16-fold acceleration and up to 16-fold maximal aliasing, was investigated. Task/stimulus-induced signal changes and temporal signal behavior under basal conditions were comparable for multiband and standard single-band excitation and longer pulse repetition times. Robust, whole-brain functional mapping at 7 T, with 2 x 2 x 2mm(3) (pulse repetition time 1.25 sec) and 1 x 1 x 2mm(3) (pulse repetition time 1.5 sec) resolutions, covering fields of view of 256 x 256 x 176 mm(3) and 192 x 172 x 176 mm(3), respectively, was demonstrated with current gradient performance.

An Introduction to Medical Statistics

Abstract: QUITE apart from the academic consideration that vital and medical statistics now form an obligatory part of the education of students seeking the University of London's diploma in public health, the demand for information about the methods of vital and medical statistics is increasing. The most casual reader of the newspapers is now aware that population problems are of serious practical importance and that the publications of the General Register Office cannot be ignored. It is scarcely an exaggeration to say that the recently issued preliminary report on the census of 1931 is one of the most sensational documents which has appeared for years, and that he who reads it intelligently will understand what is meant by saying that civilisation is in the melting pot. An Introduction to Medical Statistics. By Hilda M. Woods William T. Russell. Pp. x + 125. (London: P. S. King and Son, Ltd., 1931.) 7s. 6d.

Multiplexed echo planar imaging for sub-second whole brain fmri and fast diffusion imaging

Abstract: Echo planar imaging (EPI) is an MRI technique of particular value to neuroscience, with its use for virtually all functional MRI (fMRI) and diffusion imaging of fiber connections in the human brain. EPI generates a single 2D image in a fraction of a second; however, it requires 2–3 seconds to acquire multi-slice whole brain coverage for fMRI and even longer for diffusion imaging. Here we report on a large reduction in EPI whole brain scan time at 3 and 7 Tesla, without significantly sacrificing spatial resolution, and while gaining functional sensitivity. The multiplexed-EPI (M-EPI) pulse sequence combines two forms of multiplexing: temporal multiplexing (m) utilizing simultaneous echo refocused (SIR) EPI and spatial multiplexing (n) with multibanded RF pulses (MB) to achieve m×n images in an EPI echo train instead of the normal single image. This resulted in an unprecedented reduction in EPI scan time for whole brain fMRI performed at 3 Tesla, permitting TRs of 400 ms and 800 ms compared to a more conventional 2.5 sec TR, and 2–4 times reductions in scan time for HARDI imaging of neuronal fibertracks. The simultaneous SE refocusing of SIR imaging at 7 Tesla advantageously reduced SAR by using fewer RF refocusing pulses and by shifting fat signal out of the image plane so that fat suppression pulses were not required. In preliminary studies of resting state functional networks identified through independent component analysis, the 6-fold higher sampling rate increased the peak functional sensitivity by 60%. The novel M-EPI pulse sequence resulted in a significantly increased temporal resolution for whole brain fMRI, and as such, this new methodology can be used for studying non-stationarity in networks and generally for expanding and enriching the functional information.

Deep learning in medical imaging and radiation therapy.

Abstract: The goals of this review paper on deep learning (DL) in medical imaging and radiation therapy are to (a) summarize what has been achieved to date; (b) identify common and unique challenges, and strategies that researchers have taken to address these challenges; and (c) identify some of the promising avenues for the future both in terms of applications as well as technical innovations. We introduce the general principles of DL and convolutional neural networks, survey five major areas of application of DL in medical imaging and radiation therapy, identify common themes, discuss methods for dataset expansion, and conclude by summarizing lessons learned, remaining challenges, and future directions.