Biomedical subjects

Antonello Sotgiu

Publications and source records attributed to Antonello Sotgiu.

6 recordsLinked to original sources

PubMed2004

An open volume, high isolation, radio frequency surface coil system for pulsed magnetic resonance.

We present an open volume, high isolation, RF system suitable for pulsed NMR and EPR spectrometers with reduced dead time. It comprises a set of three RF surface coils disposed with mutually parallel RF fields and a double-channel receiver (RX). Theoretical and experimental results obtained with a prototype operating at about 100 MHz are reported. Each surface RF coil (diameter 5.5 cm) was tuned to f0=100.00+/-0.01 MHz when isolated. Because of the mutual coupling and the geometry of the RF coils, only two resonances at f1=97.94 MHz and f2=101.85 MHz were observed. We show they are associated with two different RF field spatial distributions. In continuous mode (CW) operation the isolation between the TX coil and one of the RX coils (single-channel) was about -10 dB. By setting the double-channel RF assembly in subtraction mode the isolation values at f1 or f2 could be optimised to about -75 dB. Following a TX RF pulse (5 micros duration) an exponential decay with time constant of about 600 ns was observed. The isolation with single-channel RX coil was about -11 dB and it increased to about -47 dB with the double-channel RX in subtraction mode. Similar results were obtained with the RF pulse frequency selected to f2 and also with shorter (500 ns) RF pulses. The above geometrical parameters and operating frequency of the RF assembly were selected as a model for potential applications in solid state NMR and in free radical EPR spectroscopy and imaging.

Equipment Design↗

PubMed2004

A novel algorithm for the reduction of undersampling artefacts in magnetic resonance images.

An innovative algorithm is presented which is effective in reducing the truncation artefacts occurring in magnetic resonance images due to missing k-space samples. The algorithm works first by filling the incomplete matrix of coefficients with zeroes and then adjusting, by an iterative process, the missing coefficients by performing a reduction of the undersampling artefacts. Then, this set of coefficients is used as a basis for a superresolution algorithm that estimates the missing coefficients by modeling the data as a linear combination of increasing and decreasing exponential functions using Prony's method. In fact, the Prony's method consists of the interpolation of a given data set with a sum of exponential functions: the MRI signals can be well represented as a sum of exponential functions and the missing data can be extrapolated by this representation. The algorithm has been proven to perform better than either a simple algorithm, which detects and then reduces the undersampling artefacts, or an algorithm that models the measured data with approximation functions. The presented algorithm is quite simple and is applicable both to missing rows (phase-frequency acquisitions) and to radial-missing angle (acquisition from projections) undersampling. Experimental results are reported; comparisons, made between the results obtained using the presented algorithm and the alternative methods described above, clearly demonstrate the superiority of the algorithm.

Algorithms↗

PubMed2003

Post-processing noise removal algorithm for magnetic resonance imaging based on edge detection and wavelet analysis.

A post-processing noise suppression technique for biomedical MRI images is presented. The described procedure recovers both sharp edges and smooth surfaces from a given noisy MRI image; it does not blur the edges and does not introduce spikes or other artefacts. The fine details of the image are also preserved. The proposed algorithm first extracts the edges from the original image and then performs noise reduction by using a wavelet de-noise method. After the application of the wavelet method, the edges are restored to the filtered image. The result is the original image with less noise, fine detail and sharp edges. Edge extraction is performed by using an algorithm based on Sobel operators. The wavelet de-noise method is based on the calculation of the correlation factor between wavelet coefficients belonging to different scales. The algorithm was tested on several MRI images and, as an example of its application, we report the results obtained from a spin echo (multi echo) MRI image of a human wrist collected with a low field experimental scanner (the signal-to-noise ratio, SNR, of the experimental image was 12). Other filtering operations have been performed after the addition of white noise on both channels of the experimental image, before the magnitude calculation. The results at SNR = 7, SNR = 5 and SNR = 3 are also reported. For SNR values between 5 and 12, the improvement in SNR was substantial and the fine details were preserved, the edges were not blurred and no spikes or other artefacts were evident, demonstrating the good performances of our method. At very low SNR (SNR = 3) our result is worse than that obtained by a simpler filtering procedure.

Algorithms↗

PubMed2003

A calculation method for semi automatic follow up of multiple sclerosis by magnetic resonance eco planar perfusion imaging.

Multiple sclerosis (MS) is one of the most common chronic and disabling inflammatory and demyelinating disorders of the central nervous system (CNS). Magnetic Resonance Imaging (MRI) allows the observation of pathological changes in vivo. It has provided a number of important insights into the spatial-temporal evolution of MS pathology in vivo. Conventional MRI with T2-weighted images is useful in the assessment of oedema early in the inflammatory stage, tissue destruction with demyelination and axonal loss, and gliosis later in the chronic stage. Examination by conventional MRI usually requires more than one hour and it does not completely reveal rapid dynamic changes in blood flow. Recently introduced rapid MRI techniques, MR perfusion imaging and MR diffusion imaging, allow measurement of pathophysiological changes at the cellular level with a good temporal resolution. Nevertheless, until now there were no adequate analytical methods available within the clinical routine to differentiate between types of MS lesions using fast perfusion MRI. We present an analytical method capable of recognizing, and distinguishing, the status of MS lesions by calculating some numerical parameters from the MR perfusion images. The method has been tested on 14 patients affected by MS with different lesions and the results have been compared with those obtained with more expensive conventional MRI examinations. The proposed method made it possible to recognize the nature of the MS lesions in 100% of the examined cases without the need to perform long conventional MRI examinations, using instead perfusion MRI eco planar imaging which takes no more than two minutes. Moreover, the reduced time also allowed reduction of the quantity of contrast medium administered to the patient. Further studies may lead to the use of this technique for differential diagnoses in other white matter diseases.

Disease Management↗

PubMed2002

First imaging results obtained with a multimodal apparatus combining low-field (35.7 mT) MRI and pulsed EPRI.

Nuclear magnetic resonance imaging (MRI) provides excellent images of organs and is an essential diagnostic tool in the medical field. Electron paramagnetic resonance imaging (EPRI) is being increasingly used in the biomedical field because of recent hardware advances. We present the first images obtained with a low-field (35.7 mT) multimodal apparatus that combines MRI and pulsed EPRI. For this purpose, the sample is composed of two sections, one sensitive to MRI and the other sensitive to EPRI. The MRI section of the sample is composed of three tubes containing 7 ml of a 10 mM CuSO4 water solution. The EPR section of the sample is composed of two tubes containing 350 mg of lithium phthalocyanine. The EPR image represents the two-dimensional projection of the whole sample and is reconstructed from 32 one-dimensional projections by using the Fourier reconstruction method. The MRI image is obtained by selecting a sample slice, 10 mm in thickness, by using a spin-echo sequence and the two-dimensional fast Fourier transform. The experimental results obtained with this apparatus show that the spatial resolution is better than 1 mm for the MRI section and better than 7 mm for the EPRI section. The measured SNR of the MRI and EPRI images were about 60 and 160, respectively. A detailed description of the hardware, pulse sequences and image reconstruction techniques is reported.

Electron Spin Resonance Spectroscopy↗

PubMed2002

A general algorithm for magnetic resonance imaging simulation: a versatile tool to collect information about imaging artefacts and new acquisition techniques.

An innovative algorithm for Magnetic Resonance Imaging (MRI) capable of demonstrating the source of various artefacts and driving the hardware and software acquisition process is presented. The algorithm is based on the application of the Bloch equations to the magnetization vector of each point of the simulated object, as requested by the instructions of the MRI pulse sequence. The collected raw data are then used to reconstruct the image of the object. The general structure of the algorithm makes it possible to simulate a great range of imaging situations in order to explain the nature of unwanted artefacts and to study new acquisition techniques. The way the algorithm structures the sequence has also allowed the easy implementation of MRI data acquisition on a commercial general-purpose DSP-based data acquisition board, thus facilitating the comparison between simulated and experimental results.

Algorithms↗