Electricity: measuring and testing – Particle precession resonance – Spectrometer components
Reexamination Certificate
2002-09-06
2004-05-11
Fulton, Christopher W. (Department: 2859)
Electricity: measuring and testing
Particle precession resonance
Spectrometer components
C324S307000, C324S309000
Reexamination Certificate
active
06734673
ABSTRACT:
BACKGROUND OF THE INVENTION
The present invention is directed in general to magnetic resonance tomography (MRT) as employed in medicine for examining patients. The present invention is particularly directed to a magnetic resonance tomography apparatus as well as to a method for operating such an apparatus wherein data are acquired by a technique known as “partially parallel acquisition” (PPA).
DESCRIPTION OF THE PRIOR ART
MRT is based on the physical phenomenon of nuclear magnetic resonance and has been successfully utilized as an imaging method in medicine and in biophysics for more than 15 years. In this examination method, the subject is exposed to a strong, constant magnetic field. As a result, the nuclear spins of the atoms in the subject, which were previously irregularly oriented, are aligned. Radio frequency waves can then excite these “ordered” nuclear spins to a specific oscillation. This oscillation generates the actual measured signal in MRT that is picked up with suitable reception coils. By utilizing non-uniform magnetic fields generated by gradient coils, signals from the examination subject can thereby be spatially encoded in all three spatial directions. The method allows a free selection of the slice to be imaged, so that tomograms of the human body can be registered in all directions. MRT as a tomographic method in medical diagnostics is mainly distinguished as a “non-invasive” examination method on the basis of a versatile contrast capability. Due to the excellent presentation of soft tissue, MRT has developed into a method that is often superior to X-ray computed tomography (CT). MRT is currently based on the application of spin echo and gradient echo sequences that enable an excellent image quality given measurement times on the order of magnitude of minutes.
The constant technical improvement of the components of MRT apparatus and the introduction of fast imaging sequences have increased the areas of employment in medicine for MRT. Real-time imaging for supporting minimally invasive surgery, functional imaging in neurology and perfusion measurement in cardiology represent only a few examples. Despite the technical progress designing the components of an MRT apparatus, the exposure time of an MRT image remains the limiting factor for many applications of MRT in medical diagnostics. A limit is placed on a further enhancement of the performance of MRT apparatus from a technical point of view (feasibility) and for reasons of patient protection (stimulation and tissue heating). In recent years, many efforts therefore were made to develop and establish new approaches in order to achieve further shortening of the image measurement time.
One approach for shortening the acquisition time is to reduce the quantity of image data to be recorded. In order to obtain a complete image from such a reduced dataset, either the missing data must be reconstructed with suitable algorithms or the faulty image from the reduced data must be corrected. The registration of the data in MRT occurs in an arrangement referred to as k-space (synonym: frequency domain). The MRT image in the image domain is obtained by an operation on the MRT data in the k-space by means of Fourier transformation. The location coding of the subject that arises the k-space occurs by means of gradients in all three spatial directions. A distinction is made between the slice selection (determines an exposure slice in the subject, usually the z-axis), the frequency coding (determines a direction in the slice, usually the x-axis), and the phase coding (defines the second dimension within the slice, usually the y-axis). Without limitation placed on the universality, a Cartesian k-space is assumed below, this being sampled row-by-row. The data of a single k-space row are frequency-coded with a gradient when read out. Each row in the k-space has the spacing &Dgr;k
y
that is generated by a phase-coding step. Since the phase coding requires a long time compared to the other location codings, most methods for shortening the image measurement time are based on a reduction in the number of time-consuming phase coding steps. All method of the type known as “partially parallel acquisition” (referred to below as PPA) are based on this approach.
The basic idea in PPA imaging is that the k-space data are not registered by a single coil but by, for example, a linear arrangement of component coils, a coil array. Each of the spatially independent coils of the array carries certain spatial information that is used in order to achieve a complete location coding by a combination of the simultaneously acquired coil data. This means that a number of shifted data rows in the k-space that are omitted, i.e. not acquired, can be identified from a single registered k-space row.
PPA methods thus employ spatial information that is contained in (represented by) the components of the coil arrangement in order to partially replace the time-consuming phase coding that is normally generated employing a phase gradient. As a result, the image measurement time is reduced corresponding to the ratio of the number of rows of the reduced dataset to the number of rows of the conventional (i.e. complete) dataset. Compared to the conventional acquisition, only a fraction (½, ⅓, ¼, etc.) of the phase coding rows are acquired in a typical PPA acquisition. A specific reconstruction is then applied to the data in order to reconstruct the missing k-space rows, and thus to obtain the full field-of-view (FOV) image in a fraction of the time.
Some of these PPA techniques (SMASH, SENSE, GSMASH) are successfully utilized in many areas of MRT. The most noteworthy is the SMASH method that was invented by Sodickson in 1997 (D. K. Sodickson, W. J. Manning, Simultaneous Acquisition of Spatial Harmonics (SMASH): Fast Imaging with Radio frequency Coil Arrays, Magn. Reson. Med. 38:591-603 (1997)) that is described in brief below.
SMASH stands for “Simultaneous Acquisition of Spatial Harmonics”. As mentioned above, this is a PPA method. Data are simultaneously acquired from spatially separate and independent coils that are arranged in the phase-coding direction. By a linear combination of these coil data, a spatial modulation of the signal that is achieved in conventional methods by activating a phase-coding gradient is achieved, with time-consuming phase-coding steps being saved as a result. Only a reduced k-space is thus registered, and the exposure time is shortened by an amount corresponding to the reduction of this k-space. This missing data are then reconstructed using suitable linear combinations of the coil datasets only after the actual data acquisition.
Sodickson et al. thus shows that a row of the k-space can be reconstructed upon employing of linear combinations of the signals that have been acquired by an arrangement of coils according to the SMASH technique whenever
∑
l
=
1
L
n
l
(
m
)
i
l
(
y
)
=
ⅇ
ⅈ
m
Δ
k
y
(
1
)
applies. The exponential term describes a sinusoidal modulation of the real part and of the imaginary part of the data. The number of oscillations of this modulation over the FOV is defined by the number m. For m=0, 1, 2, . . . , the spatial harmonic of the 0
th
, 1
st
, 2
nd
, . . . order of the coil sensitivities is referred to in this context.
The quantity i
1
(y) is the coil sensitivity of coil
1
from a total of L coils. Further, n
1
(m)
SMASH weighting factors are required for the linear combination of the coil sensitivities in order to generate spatial harmonics of the order m. The coil sensitivity profiles i
1
(y) are normally determined by a separate exposure using a proton density-weighted FLASH sequence or similar sequence. When the coil sensitivities are known, the spatial harmonics can be calculated therewith in a purely mathematical manner. Only the weighting factors n
1
(m)
thus remain as the sole unknown quantity in Equation (1). The determination of these coefficients is implemented such that the sensitivity profile
Fulton Christopher W.
Schiff & Hardin LLP
Siemens Aktiengesellschaft
Vargas Dixomara
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