Magnetic resonance method and apparatus to generate a residual map as an indicator of signal model consistency

Patent metadata

Field	Value
Publication number	US-2016282433-A1
Application number	US-201514724999-A
Country	US
Kind code	A1
Filing date	May 29, 2015
Priority date	Mar 25, 2015
Publication date	Sep 29, 2016
Grant date	—

Abstract

In a magnetic resonance (MR) apparatus and a method for operating an MR apparatus, MR data are acquired and evaluated with regard to multiple tentative signal models for producing a parameter map based on one of those signal models. The parameter map shows multiple parameters that have respective effects on the MR data. Each tentative signal model is initially analyzed to determine whether any of the parameters used therein can be assumed to be at least locally constant, and the initially analyzed tentative signal model is then subjected at least to a quality of fit analysis. The tentative signal model having at least the best quality of fit analysis result is then used to generate a parameter map that is displayed at a display monitor.

First claim

We claim as our invention:

1 . A method for operating a magnetic resonance (MR) apparatus, comprising:
operating an MR apparatus, in which a subject is situated, to acquire MR data from the subject; providing the acquired MR data to a computer and, in said computer, generating a plurality of quantitative parameter maps each representing multiple parameters having an effect on said MR data, by generating each quantitative parameter map by applying a tentative signal model to the MR data; in said computer, for each tentative signal model, performing an initial analysis to determine whether any of said parameters can be set to at least a locally constant value and, if so, setting respective parameters to respective locally constant values, thereby producing an initially analyzed tentative model; in said computer, performing at least a quality of fit analysis of the initially analyzed tentative signal model; in said computer, selecting, as a final signal model, a tentative signal model, among said plurality of tentative signal models, for which at least said quality of fit analysis is best; and generating a parameter map using said tentative signal model for which said quality of fit is best, and displaying that parameter map at a display monitor in communication with said computer.

2 . A method as claimed in claim 1 comprising performing said initial analysis as an ROI analysis.

3 . A method as claimed in claim 1 comprising performing said quality of fit analysis by, in said computer, calculating a residual of the fit of the tentative signal model and the MR data.

4 . A method as claimed in claim 3 comprising generating a map of the quality of fit from the calculated residual, and displaying said parameter map produced from the tentative signal model having the best quality of fit together with the map of the quality of fit from the residual calculated from that tentative signal model.

5 . A method as claimed in claim 1 comprising using, as one of said tentative signal models, a selected tentative signal model comprising F, W, common R2* and noise, applying an ROI analysis as said initial analysis to determine a level of said noise, fixing said noise level as a constant in said selected tentative model, and performing said quality of fit analysis for said selected tentative signal model said noise level as a constant and with free F, W and R2*.

6 . A method as claimed in claim 1 comprising using, as one of said tentative signal models, a selected tentative signal model comprising F, W, R2* of fat, and R2* of water, determining whether said R2* of fat is in a limited range and, if so, fixing R2* of fat as a constant in said selected tentative model, and performing said quality of fit analysis with said selected tentative signal model with R2* fixed as a constant and free F, W and R2* of water.

7 . A method as claimed in claim 1 comprising using, as one of said tentative signal models, a selected tentative signal model comprising F, W, common R2* and noise, determining whether fat values are below a predetermined level and, if so, setting F to be a constant of 0, and performing said goodness of fit analysis for said selected tentative signal model with F=0 and with free W, R2* of water, and noise.

8 . A method as claimed in claim 1 comprising using, as one of said tentative signal models, a selected signal model comprising F, W, common R2* and noise, determining whether fat values are below a predetermined level and, if so, treating R2* of water as a fixed constant and treating noise as a fixed constant, and said goodness-of-fit analysis for said selected tentative signal model with R2* of water as a fixed constant and noise as another fixed constant, and with free W and F.

9 . A magnetic resonance apparatus comprising:
a magnetic resonance scanner configured to receive an examination subject therein; a control computer configured to operate said MR scanner with said examination subject therein, to acquire MR data from the examination subject; an analysis computer provided with the acquired MR data to a computer, said analysis computer being configured to generate a plurality of quantitative parameter maps each representing multiple parameters having an effect on said MR data, by generating each quantitative parameter map by applying a tentative signal model to the MR data; said analysis computer, for each tentative signal model, being configured to perform an initial analysis to determine whether any of said parameters can be set to at least a locally constant value and, if so, setting respective parameters to respective locally constant values, thereby producing an initially analyzed tentative model; said analysis computer being configured to perform at least a quality of fit analysis of the initially analyzed tentative signal model; said analysis computer being configured to select, as a final signal model, a tentative signal model, among said plurality of tentative signal models, for which at least said quality of fit analysis is best; and said analysis computer being configured to generate a parameter map using said tentative signal model for which said quality of fit is best, and to display that parameter map at a display monitor in communication with said analysis computer.

10 . A non-transitory, computer-readable data storage medium encoded with programming instructions, said storage medium being loaded into a control and processing computer of a magnetic resonance (MR) apparatus, said programming instructions causing said control and processing computer to:
operate the MR apparatus, in which a subject is situated, to acquire MR data from the subject; generate a plurality of quantitative parameter maps each representing multiple parameters having an effect on said MR data, by generating each quantitative parameter map by applying a tentative signal model to the MR data; for each tentative signal model, perform an initial analysis to determine whether any of said parameters can be set to at least a locally constant value and, if so, setting respective parameters to respective locally constant values, thereby producing an initially analyzed tentative model; perform at least a quality of fit analysis of the initially analyzed tentative signal model; select, as a final signal model, a tentative signal model, among said plurality of tentative signal models, for which at least said quality of fit analysis is best; and generate a parameter map using said tentative signal model for which said quality of fit is best, and display that parameter map at a display monitor.

Assignees

• Siemens Ag

Inventors

• Kannengiesser Stephan
• Nickel Marcel Dominik
• Zhong Xiaodong

Classifications

• G01R33/50

  based on the determination of relaxation times {, e.g. T1 measurement by IR sequences; T2 measurement by multiple-echo sequences} · CPC title

• G01R33/5608

  Data processing and visualization specially adapted for MR, e.g. for feature analysis and pattern recognition on the basis of measured MR data, segmentation of measured MR data, edge contour detection on the basis of measured MR data, for enhancing measured MR data in terms of signal-to-noise ratio by means of noise filtering or apodization, for enhancing measured MR data in terms of resolution by means for deblurring, windowing, zero filling, or generation of gray-scaled images, colour-coded images or images displaying vectors instead of pixels (image data processing or generation, in general G06T) · CPC title

• G01R33/4828 Primary

  Resolving the MR signals of different chemical species, e.g. water-fat imaging · CPC title

• G01R33/30

  Sample handling arrangements, e.g. sample cells, spinning mechanisms · CPC title

• G01R33/34092

  RF coils specially adapted for NMR spectrometers · CPC title