KR20140058369A - Adaptive and interactive assessment of tissue properties in mr imaging - Google Patents

Abstract

The present invention relates to adaptive and interactive assessment of tissue properties in MR imaging. A system for assessing tissue properties in MR imaging according to one embodiment of the present invention comprises an image data processor; and a display processor which generates data representing an MR image. According to one embodiment of the present invention, Fe deposition in tissue can be assessed by using a relaxation rate which can be easily measured by the MR images.

Description

[0001] ADAPTIVE AND INTERACTIVE ASSESSMENT OF TISSUE PROPERTIES IN MR IMAGING [0002]

This application claims priority to U.S. Provisional Patent Application No. 61 / 722,281, filed November 5, 2012, which application is hereby incorporated by reference in its entirety.

FIELD OF THE INVENTION The present invention relates generally to evaluating the properties of tissues using magnetic resonance imaging (MRI), and more particularly to assessing iron deposition in tissues from values obtained from MR images .

또는

) 또는 이완율들(

또는

)에 영향을 끼친다는 것과 이들 값들이 MRI에 의해 측정될 수 있다는 것이 알려져 있다. 맵들로서 또한 지칭되는 MR 이미지들 상에서 픽셀-단위

또는

값들과 대응하는

또는

값들을 측정하기 위해 상이한 알려진 방법들이 사용될 수 있다.Because many diseases affect the iron deposition in tissues or organs, evaluation of iron deposition in tissues is of clinical interest. Assessment of iron deposition can be achieved through magnetic resonance imaging (MRI). MRI is a technology that is desired because the MRI is non-invasive and imaging the entire organ. Iron deposition is the tissue relaxation values (

or

) Or relaxation rates (

or

) And that these values can be measured by MRI. On MR images, also referred to as maps,

or

Corresponding to the values

or

Different known methods can be used to measure the values.

값들을 갖는다. 수분

값이 대부분의 조직들 또는 기관들 내 철 침착을 정확하게 반영하는 반면에, 상기 수분

값은 높은 지방률을 갖는 구역들과 같은 몇몇의 구역들에 대해 부정확할 수 있다. 통상적으로, 철 침착은 지방

에 거의 영향을 끼치지 않는다. 유효한

값은 수분-지방 혼합물의

값이고, 그리고 일반적으로 철 침착 평가를 위해 사용된다. 그러나, 유효한

값은 또한 높은 지방률을 갖는 구역들 내 철 침착을 정확하게 반영하지 않는다. 그러므로, 조직의 철 침착을 평가하기 위해 유효한

, 수분

, 및 지방

맵들을 나란히 판독 및 비교하는데 방사선전문의들 또는 의사들이 요구될 수 있다. 이는 실제로 불편하고, 어렵고, 그리고 혼란스럽다.Different species in tissues, such as water and fat,

Lt; / RTI > moisture

Value accurately reflects iron deposition in most tissues or organs, while the water

The value may be inaccurate for some zones, such as zones with high fat percentage. Typically,

It has almost no influence on. Effective

The value of the water-fat mixture

Value, and is generally used for iron deposition assessment. However,

The value also does not accurately reflect iron deposition in zones with high fat content. Therefore, it is possible to evaluate the iron deposition

, moisture

, And fat

Radiologists or physicians may be required to read and compare maps side-by-side. This is actually uncomfortable, difficult, and confusing.

, 수분

, 및 지방

의 알려진 값들에 기초하여 임상적 관련

맵을 제공하기 위한 방법 및 시스템을 설명한다.This document is valid

, moisture

, And fat

RTI ID = 0.0 > related < / RTI >

Methods and systems for providing maps are described.

Embodiments of the present invention provide a system and method for evaluating characteristics of tissue from magnetic resonance (MR) signal data of tissue. The image data processor is configured to select one of a plurality of parameters of the tissue for each of the plurality of individual image elements of the MR image of the tissue; And the display processor is configured to generate data representing the MR image using the selected parameters to represent individual image elements.

In an embodiment, the parameters of the tissue include parameters related to iron deposition in the tissue. The parameters may include at least one of tissue transverse relaxation values and tissue transverse relaxation rates. In an embodiment, the parameters are: (i) transverse relaxation rate of fat; (Ii) transverse relaxation rate of water; And (iii) a composite transverse relaxation ratio of both water and fat; And wherein the selected transverse relaxation rate by the image data processor is selected from the group consisting of: (i) fat; (Ii) moisture; And (iii) individual image elements representing a proportion of one of the water-fat mixtures.

According to an embodiment, the input processor is configured to receive a plurality of MR image representative signal data sets of a portion of the patient's body acquired using a pulse sequence type, and wherein the plurality of MR image representative signal data sets comprise a plurality of individual Represents an image containing image elements. An image data processor determines selected parameters in response to receiving the plurality of MR image representative signal data sets.

According to an embodiment, each individual image element of the plurality of individual image elements comprises (i) a pixel; (Ii) a group of pixels; (Iii) a voxel; And (iv) a group of voxels.

In an embodiment, the selected transverse relaxation rate by the image data processor is (i) in the tissue represented by the individual image elements; fat; (Ii) moisture; And (iii) individual image elements representing a proportion of one of the water-fat mixtures. In an embodiment, the selected transverse relaxation rate is selected from the group consisting of (a) a ratio of fat exceeding the first threshold, and (b) a ratio of water below the second threshold in the tissue represented by the individual image elements. Relaxation rate. In another embodiment, the selected transverse relaxation rate is selected from the group consisting of (a) a proportion of water in excess of the third threshold, and (b) a proportion of water based on at least one of a ratio of fats below the fourth threshold The horizontal relaxation rate. In yet another embodiment, the selected transverse relaxation rate is based on at least one of (a) a ratio of water between predetermined thresholds in the tissue represented by the individual image elements and (b) a ratio of fat, and Is the composite transverse relaxation rate.

In an embodiment, the first threshold and the fourth threshold are predetermined and substantially the same, and wherein the second threshold and the third threshold are predetermined and substantially the same.

According to an embodiment, the image data processor is further configured to adaptively select at least one of the thresholds in response to data indicative of the clinical procedure being performed.

In another embodiment, the image data processor comprises: (i) localized magnetization of tissue represented by an individual image element; (Ii) the magnetization of water; And (iii) at least one of the magnetization of the water-fat mixture, (i) fat; (Ii) moisture; And (iii) a ratio of at least one of the water-fat mixture.

In an embodiment, the display processor comprises: (i) a plurality of selected transverse relaxation rates of fat for a corresponding first subset of the individual image elements; (Ii) a plurality of selected transverse relaxation rates of moisture for a corresponding second subset of individual image elements; And (iii) one or more of a composite transverse relaxation rate of both moisture and fat for a third subset of the individual image elements.

The foregoing and other aspects of the invention are best understood from the following detailed description when read in conjunction with the accompanying drawings. For the purpose of illustrating the invention, there are shown in the drawings presently preferred embodiments, but it is understood that the invention is not limited to the instrumentalities described. The drawings include the following figures:
Figures 1 and 2 are exemplary representations used to evaluate tissue properties acquired via MRI.
Figure 3 illustrates a system for evaluating characteristics of tissue using MRI, in accordance with embodiments provided herein.
4 is an exemplary computing environment in which the embodiments described herein may be implemented.

또는

) 또는 이완율들(

또는

)에 영향을 끼친다는 것이 알려져 있다.Embodiments of the present invention are directed to evaluating the characteristics of tissues using magnetic resonance imaging (MRI). In particular, MR images are used to characterize features that affect specific chemical properties of tissue. In an exemplary embodiment, tissue transverse relaxation values or relaxation rates that can be easily measured from MR images are used to evaluate iron deposition in tissue. Iron deposition is the tissue relaxation values (

or

) Or relaxation rates (

or

≪ / RTI >

, 수분

, 및 지방

의 알려진 값들에 기초하여 조직에 대한 임상적 관련

맵을 제공하기 위한 방법 및 시스템으로 지향된다. 임상적 관련

맵은 하나의 맵을 사용하여 조직의 임의의 구역 내 철 침착의 정확한 평가를 제공한다. 실시예들이 임상적 관련

맵을 획득하기 위해

을 프로세싱하는 것으로서 본 명세서에서 설명되지만, 대응하는 임상적 관련 맵을 획득하기 위해

,

, 또는

값들 및 맵들이 동일한 방법 및 시스템에 의해 대안적으로 활용될 수 있다. 부가하여, 몇몇의 실시예들이 간 이미징에 대하여 설명되지만, 이는 예시적이고 그리고 시스템 및 방법은 파라미터들의 동적 조절에 의해 다른 기관 또는 조직에 적용된다.Embodiments include, but are not limited to,

, moisture

, And fat

RTI ID = 0.0 > related < / RTI >

A method and system for providing maps. Clinical relevance

The map uses a single map to provide an accurate assessment of iron deposition in any region of the tissue. When the embodiments are used for clinical relevance

To acquire the map

To obtain a corresponding clinical relevancy map, as described herein as < RTI ID = 0.0 >

,

, or

Values and maps may alternatively be utilized by the same method and system. In addition, although some embodiments are described for liver imaging, this is illustrative and the system and method are applied to other organs or tissues by dynamic adjustment of parameters.

값이 대부분의 조직들 또는 기관들 내 철 침착을 정확하게 반영할 수 있지만, 상기 수분

값은 높은 지방률을 갖는 구역들과 같은 몇몇의 구역들에 대해 부정확할 수 있다. 통상적으로, 철 침착은 지방

에 거의 영향을 끼치지 않는다. 유효한

값은 수분-지방 혼합물의

값이고, 그리고 일반적으로 철 침착 평가를 위해 사용된다. 그러나, 유효한

값은 또한 높은 지방률을 갖는 구역들 내 철 침착을 정확하게 반영하지 않는다. 본 명세서에 제공되는 실시예들의 임상적 관련

맵은, 조직의 MR 이미지의 복수의 이미지 엘리먼트들 중 각각의 개별 이미지 엘리먼트에 대해 가장 관련된 값을 포함함으로써, 유효한

, 수분

, 및 지방

의 알려진 값들에 기초하여 계산된다. 이러한 방식으로, 철 침착 평가를 가능케 하기 위해 관심 대상인 전체 조직에 대한 단일 맵 내에 가장 관련된 값이 제시된다. 또한, 부가 실시예에서, 임상적 관련

맵을 보는 것에 부가하여, 사용자는 보려고 하는 유효한

, 수분

, 및 지방

맵들 중 임의의 것의 조합을 선택할 수 있어, 따라서 임상적 관련

맵의 하위-변형들 중 임의의 것의 선택적 디스플레이가 제공된다. 다른 실시예에서, 임상적 관련

맵에 기여하는 값들의 특정한 변형을 나타내기 위해 색 코딩이 사용될 수 있다.moisture

Although the value can accurately reflect iron deposition in most tissues or organs,

The value may be inaccurate for some zones, such as zones with high fat percentage. Typically,

It has almost no influence on. Effective

The value of the water-fat mixture

Value, and is generally used for iron deposition assessment. However,

The value also does not accurately reflect iron deposition in zones with high fat content. The clinical relevance of the embodiments provided herein

The map includes the most relevant values for each individual image element of the plurality of image elements of the MR image of the organization,

, moisture

, And fat

Lt; / RTI > In this way, the most relevant values are presented within a single map for the entire organization of interest to enable the iron deposition assessment. Further, in additional embodiments,

In addition to viewing the map,

, moisture

, And fat

A combination of any of the maps can be selected,

Optional displays of any of the sub-variants of the map are provided. In another embodiment, the clinical relevance

Color coding may be used to indicate a particular variation of the values contributing to the map.

값들이 아래에 표시된 바와 같이 측정될 수 있다. 데이터 취득을 위해 낮은 플립 각도들이 사용되고, 그래서 T1 효과들이 신호 모델에서 합리적으로 무시될 수 있다. n-번째 에코 시간(TE) 동안, 취득된 MR 신호가 아래에 의해 주어진다:In the equation [1] by the equation of the signal model, three

The values can be measured as indicated below. Low flip angles are used for data acquisition, so that T1 effects can be reasonably ignored in the signal model. During the n-th echo time (TE), the acquired MR signal is given by:

[1].

[One].

, n번째 에코에 측정된 MR 신호; c_n, 알려진 지방 스펙트럼 모델을 이용하여 계산된 스펙트럼에서 지방 및 수분의 차이로 인해 n번째

에서의 복소수 계수; 및

, n-번째 에코 시간을 포함한다. 알려지지 않은 변수들은:

및

, 각각, 조직 내 수분 및 지방의 자화 또는 양성자 밀도; 각각, 수분 및 지방의 이완율들을 표현하는

및

; 및

, 1의 진폭을 갖는 복소수 페이저(complex phasor) ― 조직적 결함으로 인한, 예컨대 오프-공명, 와전류, 및 구배 지연으로 인한 페이즈 오류를 포함함 ― 를 포함한다. 간략성을 위해, 상이한 지방 종들은 하나의 공통

을 갖는 것으로 가정된다. 알려지지 않은 변수들 중에서,

는 통상적으로 임상적 관심 대상이 아니다. 그러므로,

에 대해 풀이하는 것은 필요하지 않다. 신호 모델 방정식으로부터

를 제거하기 위해 방정식 [1]의 양측의 크기를 취하는 것은 아래를 제공한다:In this equation, the known or measured variables are:

an MR signal measured at an n-th echo; c _n , due to fat and moisture differences in the spectrum calculated using the known fat spectrum model,

The complex coefficient at; And

, and an n-th echo time. The unknown variables are:

And

, Respectively, magnetization or proton density of water and fat in the tissue; Expressing the relaxation rates of water and fat, respectively

And

; And

, A complex phasor with an amplitude of 1, including phase errors due to systematic defects, such as off-resonance, eddy currents, and gradient delays. For simplicity, different lipid species are common

. Among the unknown variables,

Is not usually of clinical interest. therefore,

It is not necessary to solve for. From the signal model equation

Taking the size of both sides of equation [1] to eliminate it provides the following:

[2].

[2].

,

,

, 및

을 갖는다.Equation [2] shows that four unknown variables that can be solved using acquisitions with echoes equal to or greater than four

,

,

, And

Respectively.

및

를 수분-지방 혼합물에 대한 단일의 유효한

로 교체함으로써 추가로 단순화된다. 신호 방정식들 [1] 및 [2]가 각각 아래와 같이 된다:In some situations, in order to reduce the complexity of the equation,

And

Lt; RTI ID = 0.0 > water-lipid < / RTI &

Lt; / RTI > The signal equations [1] and [2] are as follows:

[3]; 및

[3]; And

[4].

[4].

,

, 및

로 감소시키고, 그리고 3과 같거나 또는 그보다 더 많은 에코들을 갖는 취득들을 이용하여 풀이될 수 있다. Equation [4] uses three unknown variables, namely

,

, And

, And can be solved using acquisitions with echoes equal to or greater than three.

, 수분 , 및 지방

값들 및 맵들을 계산하는데 사용될 수 있다. 예컨대, 이 목적을 위해,

,

, 유효한

, 수분

, 및/또는 지방

를 동시에 측정하기 위해 에코 비대칭성 및 최소-자승 추정을 이용한 수분 및 지방의 반복적 분해(IDEAL:iterative decomposition of water and fat with echo asymmetry and least-squares estimation)로 불리는 알려진 방법의 변형들을 사용하는 것이 알려져 있다. 다른 알려진 방법은 비-선형 피팅(fitting) 방법, 예컨대 (방정식들 [2] 및 [4]와 같이)

에 관련된 비-선형 방정식들에서 레벤버그-마콰트(Levenberg-Marquardt) 알고리즘(댐핑(damping)된 최소-자승 방법으로서 또한 알려짐)을 이용하는 것을 포함한다. 레벤버그-마콰트 알고리즘은 함수 ― 일반적으로, 비선형 ― 의 파라미터들의 공간에 걸쳐 상기 함수를 최소화하는 문제점에 수치적 솔루션을 제공한다. 레벤버그-마콰트 기반 방법들은

,

, 유효한

, 수분

, 및/또는 지방

맵들의 결과적 솔루션들을 피팅시키는데 사용되었다.Known methods are available from multi-echo data

, moisture , And fat

Values and maps. For example, for this purpose,

,

, Effective

, moisture

, And / or fat

It is known to use variants of known methods called echo asymmetry and minimum-squares estimation, called iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) have. Other known methods are non-linear fitting methods, such as (as in equations [2] and [4]),

(Also known as the damped least-squares method) in the non-linear equations associated with the < RTI ID = 0.0 > The Lebenberg-Makquat algorithm provides a numerical solution to the problem of minimizing the function over the space of the function - generally nonlinear - parameters. Leavenberg-Makquit-based methods

,

, Effective

, moisture

, And / or fat

Maps were used to fit the resulting solutions.

이 아래와 같이 정의된다:Depending on the embodiment,

Is defined as follows:

[5].

[5].

In equation [5], a and b are application specific constant values, and 0? A? B? 1. For example, for liver imaging applications, a and b may be selected as a = b = 0.6. FP is the fat rate defined as:

[6].

[6].

맵(140), 지방

맵(150), 유효한

맵(160), 및 임상적 관련

맵(170)이 제공된다. 도 2에 도시된 바와 같이, 수분 이미지(210), 지방 이미지(220), FP 맵(230), 수분

맵(240), 지방

맵(250), 유효한

맵(260), 및 임상적 관련

맵(270)이 제공된다.Referring to Figures 1 and 2, exemplary data sets of abdominal imaging are provided. As shown in FIG. 1, a water image 110, a fat image 120, an FP map 130,

Map 140, fat

Map 150,

Map 160, and clinical relevance

A map 170 is provided. As shown in FIG. 2, a water image 210, a fat image 220, an FP map 230,

Map 240, fat

Map 250,

Map 260, and clinical relevance

A map 270 is provided.

이더라도, 수분

맵들(140, 240)은 저-수분 영역들(즉, 피하 지방)에 대해 정확하고 신뢰성 있는 값들을 갖지 않는다. 실제로, 피하 지방 구역에 대해, 지방

는 관심 대상이고, 그리고 수분

맵들(140, 240) 내에서 피하 지방 구역 내

값들을 살피는 것은 유용하지 않을 수 있다. 유사한 상황이 지방

맵들(150, 250) 내에서 보인다; 간 구역에 대해, 지방

값들은 잡음이고 그리고 간 내 철 침착을 반영하지 않는다. 유효한

는 수분-지방 혼합물의 R2* 값들을 단순히 표현하고, 그리고 구역 내에 상당한 지방이 있을 때(유효한

맵들(160, 260)을 보라) 철 침착 반영시 바이어스를 갖는다.It is the moisture that reflects iron deposition

Even if moisture

Maps 140 and 240 do not have accurate and reliable values for low-moisture regions (i.e., subcutaneous fat). Indeed, for subcutaneous fat areas, fat

Are of interest, and moisture

Within the maps 140, 240,

It may not be useful to look at the values. A similar situation exists in the province

Visible within maps 150 and 250; For the liver area,

Values are noise and do not reflect iron deposition in the liver. Effective

RTI ID = 0.0 > R2 * < / RTI > values of the water-fat mixture, and when there is significant fat in the zone

See maps 160 and 260) have a bias when reflecting iron deposits.

맵들(160, 260)과 유사한 외양을 갖지만, 임상적 관련

맵들(170, 270)은, 둘 다 정확하고 그리고 대응하는 바디 구역 내 각각의 픽셀에 임상적 관심이 있는

값들을 나타낸다. 도시된 복부 이미징 경우에, 임상적 관련

맵들(170, 270)은, 각각 수분 관심 대상이거나 지방 관심 대상인 구역들 내의 수분

및 지방

를 나타내고; 그리고 임상적 관련

맵들(170, 270)은 유효한

맵들(160, 260)보다 더욱 직접적으로 간 내 철 침착을 반영하는데, 그 이유는 임상적 관련

맵들(170, 270)이 간 구역 내 수분

를 나타내고 있기 때문이다.Effective

Having a similar appearance to the maps 160 and 260,

Maps 170 and 270 are both accurate and clinically relevant to each pixel in the corresponding body region

Values. In the illustrated abdominal imaging case, the clinical relevance

The maps 170 and 270 may be used to map the water content of the regions of interest,

And fat

Lt; / RTI > And clinical relevance

The maps 170 and 270 are valid

It reflects liver iron deposition more directly than maps 160 and 260,

When the maps 170,

.

맵은 세 개의 소스

맵들 중 하나를 완전히 포함할 수 있다. 특정하게, The system adaptively selects (or selects) a and b (see equation [5]) in response to the type of clinical application and the procedure being performed,

The map consists of three sources

It can completely contain one of the maps. Specifically,

[7].

[7].

맵은 세 개의 소스

맵들: 수분

맵, 지방

맵, 및 유효한

맵으로부터의 정보를 효과적으로 표현한다. 상호작용 디스플레이 실시예에서, a 및 b는,

의 하위-변형들 중 한 개 또는 두 개만을 선택적으로 디스플레이하도록 선택될 수 있다. 실시예에서, 임상적 관련

의 소스 변형을 식별하기 위해 색 코딩이 사용된다.Therefore,

The map consists of three sources

Maps: Moisture

Map, fat

Maps, and valid

Effectively express information from the map. In an interactive display embodiment, a and b are < RTI ID = 0.0 >

Lt; RTI ID = 0.0 > of < / RTI > In an embodiment, the clinical relevance

Color coding is used to identify the source transformations of the image.

Turning to FIG. 3, a system 300 is provided for evaluating tissue characteristics from magnetic resonance (MR) signal data of tissue. System 300 includes a source 310 of tissue, such as a patient. 312, 314 and 316 represent the coils and magnets of the MRI system and in the exemplary embodiment are high field magnets 312, gradient coils 314, and radio-frequency (RF) coils 316 . Processors 318 (gradient and seam coil controller) and 320 (radio-frequency controller) control the MR magnets and coils. The MRI system components 312, 314, and 316 and processors 318 and 320 depicted in FIG. 3 are one example of an MRI system; Other components and processors may be used as known to those skilled in the art for acquiring an MR image of an organization.

The system 300 further includes an input processor 330, an image data processor 340, a display processor 360, and an interface 370. The central control system 350 controls the overall operation of each of the processors 318, 320, 330, 340 and 360 and the data communication between the processors 318, 320, 330, 340 and 360, respectively.

Turning now to a more detailed description of system 300, MRI system components 312, 314, and 316 and processors 318 and 320 are configured to obtain an MR image of the tissue of patient 310. The MR image consists of a plurality of individual image elements. The image data processor 340 is configured to select, for each individual image element of the plurality of individual image elements of the tissue MR image, one of a plurality of parameters of the tissue corresponding to the individual image elements . Display processor 360 is configured to generate data representing the MR image using the selected parameters to represent individual image elements. In this way, a map can be generated using data representing the MR image, wherein each individual image element is represented by a parameter that accurately reflects the individual image elements. The map is displayed on the interface 370.

또는

) 또는 이완율들(

또는

)일 수 있다. 일 실시예에서, 파라미터들은 (ⅰ) 지방의 가로 이완율; (ⅱ) 수분의 가로 이완율; 및 (ⅲ) 수분 및 지방 둘 다의 복합 가로 이완율 중 하나이다. 이미지 데이터 프로세서(340)는, 특정한 기준들을 충족시키고 그리고 따라서 개별 이미지 엘리먼트의 정확한 표현인 파라미터(예컨대, 가로 이완율)를 선택한다. 일 실시예에서, 이미지 데이터 프로세서(340)에 의한 선택된 가로 이완율은 개별 이미지 엘리먼트에 의해 표현되는 조직 내에서 (ⅰ) 지방; (ⅱ) 수분; 및 (ⅲ) 수분-지방 혼합물 중 하나의 비율을 표현하는 개별 이미지 엘리먼트에 각각 기초할 수 있다.In particular, in one embodiment, the parameters relate to iron deposition in tissue. For example, the parameters may include tissue relaxation values (

or

) Or relaxation rates (

or

). In one embodiment, the parameters are (i) transverse relaxation rate of fat; (Ii) transverse relaxation rate of water; And (iii) a complex transverse relaxation rate of both water and fat. The image data processor 340 selects parameters (e.g., transverse relaxation rates) that meet certain criteria and thus are an accurate representation of the individual image elements. In one embodiment, the selected transverse relaxation rate by the image data processor 340 is (i) fat in the tissue represented by the individual image elements; (Ii) moisture; And (iii) individual image elements representing a proportion of one of the water-fat mixtures.

According to an embodiment, the input processor 330 is configured to receive a plurality of MR image representative signal data sets of a portion (e.g., tissue) of the patient's body using a pulse sequence type, and wherein the plurality of MR image representative signals The data sets represent images containing a plurality of individual image elements. In response to receiving the plurality of MR image representative signal data sets from the input processor 330, the image data processor 340 determines the selected parameters.

In an embodiment, the individual image elements include (i) a pixel; (Ii) a group of pixels; (Iii) a voxel; And (iv) one of the groups of voxels.

In an exemplary embodiment in which the parameters are transverse relaxation rates and the selected rate is based on a respective image element representing a ratio of fat, moisture, and / or water-fat mixture, respectively, the image data processor 340 may be used. In an embodiment, the selected transverse relaxation rate is selected from the group consisting of (a) a ratio of fat exceeding the first threshold, and (b) a ratio of water below the second threshold in the tissue represented by the individual image elements. Relaxation rate. In another embodiment, the selected transverse relaxation rate is selected from the group consisting of (a) a proportion of water in excess of the third threshold, and (b) a proportion of water based on at least one of a ratio of fats below the fourth threshold The horizontal relaxation rate. The selected transverse relaxation rate is a composite transverse relaxation rate of both moisture and fat based on at least one of (a) the ratio of water between predetermined thresholds in the tissue represented by the individual image elements and (b) the ratio of fat . See above equations [5], [6], and [7].

In an embodiment, the first threshold and the fourth threshold are predetermined and substantially equal, and the second threshold and the third threshold are predetermined and substantially the same. In an embodiment, the image data processor 340 is further configured to adaptively select one or more of the thresholds in response to data indicative of the clinical procedure being performed. For example, as noted above, for liver imaging applications, a and b may be selected as a = b = 0.6.

The proportions of fat, moisture, and water-fat mixture may each be based on the localized magnetization of the tissue, the magnetization of the water, and the magnetization of the water-fat mixture, represented by the individual image elements.

The display processor 360 includes (i) a plurality of selected transverse relaxation rates of fat for a corresponding first subset of the individual image elements; (Ii) a plurality of selected transverse relaxation rates of moisture for a corresponding second subset of individual image elements; And (iii) one or more of a composite transverse relaxation rate of both moisture and fat for a third subset of the individual image elements. The generated data is displayed on the interface 370. In this way, each individual image element is represented by a transverse relaxation rate that best represents the corresponding individual image element. As described above, the user can manipulate the generated image to display individual sub-transforms, and the generated image can be color coded to display various sub-transforms.

FIG. 4 illustrates an exemplary computing environment 400, and embodiments of the invention may be implemented within the exemplary computing environment 400. The computing environment 400 may include a computer system 410, which is an example of a computing system, and embodiments of the present invention may be implemented on the computing system. Computers and computing environments, such as computer 410 and computing environment 400, are known to those skilled in the art and are therefore briefly described herein.

4, the computer system 410 may include a communication mechanism such as a bus 421 or other communication mechanism for communicating information within the computer system 410. System 410 further includes one or more processors 420 coupled with bus 421 for processing information. Processors 420 may include one or more central processing units (CPUs), graphics processing units (GPUs), or any other processor known in the art.

The computer system 410 also includes a system memory 430 coupled to a bus 421 for storing instructions and information to be executed by the processors 420. [ The system memory 430 may include a computer readable storage medium in the form of volatile and / or nonvolatile memory such as read only memory (ROM) 431 and / or random access memory (RAM) The system memory RAM 432 may include other dynamic storage device (s) (e.g., dynamic RAM, static RAM, and synchronous DRAM). The system memory ROM 431 may include other static storage device (s) (e.g., programmable ROM, erasable PROM, and electrically erasable PROM). In addition, the system memory 430 may be used to store temporary variables or other intermediate information during execution of instructions by the processors 420. A basic input / output system 433 (BIOS), containing the basic routines that help to transfer information between elements within the computer system 410 during start-up, for example, may be stored in the ROM 431. RAM 432 may include program modules and / or data that are immediately accessible by processors 420 and / or are currently being operated on by processors 420. [ In addition, the system memory 430 may include, for example, an operating system 434, application programs 435, other program modules 436, and program data 437.

Computer system 410 may also store information and instructions, such as magnetic hard disk 441 and removable media drive 442 (e.g., floppy disk drive, compact disk drive, tape drive, and / And a disk controller 440 coupled to the bus 421 for controlling one or more storage devices for storage. The storage devices may be added to the computer system 410 using an appropriate device interface (e.g., a small computer system interface (SCSI), integrated device electronics (IDE), universal serial bus (USB), or FireWire).

The computer system 410 also includes a display controller (not shown) coupled to the bus 421 for controlling a display or monitor 466, such as a cathode ray tube (CRT) or liquid crystal display (LCD) 465). Computer system 410 includes one or more input devices such as keyboard 462 and pointing device 461 and input interface 460 such as a pointing device 461 to interact with a computer user and to provide information to processors 420. [ ). For example, the pointing device 461 may be a mouse, a trackball, or a pointing stick for communicating instruction information and command selections to the processors 420 and for controlling cursor movement on the display 466. [ The display 466 may provide a touch screen interface that allows the input to supplement or replace the communication of the command information and command information by the pointing device 461. [

The computer system 410 may be configured to perform the processing steps of embodiments of the present invention in response to processors 420 executing one or more sequences of one or more instructions contained in memory, Some or all of < / RTI > Such instructions may be read into the system memory 430 from another computer readable medium, such as the hard disk 441 or the removable media drive 442. Hard disk 441 may include one or more data stores and data files used by embodiments of the present invention. To improve security, data store content and data files can be encrypted. In addition, the processors 420 may be used within a multi-processing arrangement to execute one or more sequences of instructions contained within the system memory 430. [ In alternative embodiments, hard-wired circuitry may be used in place of or in conjunction with software instructions. Thus, embodiments are not limited to any specific combination of hardware circuitry and software.

As mentioned above, the computer system 410 may include one or more computer-readable media for holding instructions programmed in accordance with the embodiments provided herein and for storing data structures, tables, records, or other data described herein At least one computer readable medium or memory. The term "computer readable medium " as used herein refers to any medium that participates in providing instructions to processors 420 for execution. Computer-readable media can take many forms, including, but not limited to, non-volatile media, volatile media, and transmission media. Non-limiting examples of non-volatile media include optical disks, solid state drives, magnetic disks, and magneto-optical disks such as hard disk 441 or removable media drive 442. Non-limiting examples of volatile media include dynamic memory, such as system memory 430. Non-limiting examples of transmission media include coaxial cables, copper wires, and wires that make up the fiber optics bus 421. The transmission medium may also take the form of acoustic waves or light waves, such as those generated during radio waves and infrared data communications.

The computing environment 400 may further include a computer system 410 that operates using logical connections to one or more remote computers, such as a remote computer 480, in a networked environment. The remote computer 480 may be a personal computer (laptop or desktop), a mobile device, a server, a router, a network PC, a peer device or other common network node and is typically connected to the elements Lt; RTI ID = 0.0 > and / or < / RTI > When used in a networking environment, the computer system 410 may include a modem 472 for establishing communications over a network 471, such as the Internet. The modem 472 may be connected to the system bus 421 via the user network interface 470 or through other appropriate mechanisms.

The network 471 may be connected to the Internet via an Internet, an intranet, a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), direct connection or serial connections, Or any other network or medium that is capable of facilitating communication between a remote computing system 480 (e. G., Remote computing system 480). The network 471 may be wired, wireless, or a combination thereof. Wired connections may be implemented using Ethernet, Universal Serial Bus (USB), RJ-11, or any other wired connection commonly known in the art. Wireless connections may be implemented using Wi-Fi, WiMAX, and Bluetooth, infrared, cellular networks, satellite, or any other wireless connection method commonly known in the art. In addition, the various networks may operate alone or in communication with one another to facilitate communication within the network 471. [

As described herein, the various systems, subsystems, agents, managers and processes may be implemented using hardware components, software components, and / or combinations thereof.

While the present invention has been described with reference to exemplary embodiments, the invention is not limited to the exemplary embodiments. Those skilled in the art will recognize that many changes and modifications can be made to the preferred embodiments of the invention and that such changes and modifications can be made without departing from the true spirit of the invention. It is, therefore, to be understood that the appended claims are intended to cover all such equivalent variations as fall within the true spirit and scope of the present invention.

Claims (23)

A system for evaluating characteristics of tissue from magnetic resonance (MR) signal data of tissue,
An image data processor configured to select, for each of the plurality of individual image elements of the tissue MR image, one parameter of the plurality of parameters of the tissue; And
A display processor configured to generate data representative of the MR image using the selected parameters to represent the individual image elements;
/ RTI >
A system for evaluating characteristics of tissue from magnetic resonance (MR) signal data of tissue. The method according to claim 1,
Wherein the parameters of the tissue comprise parameters related to iron deposition in the tissue,
A system for evaluating characteristics of tissue from magnetic resonance (MR) signal data of tissue. 3. The method of claim 2,
Wherein the parameters include at least one of tissue transverse relaxation values and tissue transverse relaxation rates.
A system for evaluating characteristics of tissue from magnetic resonance (MR) signal data of tissue. 3. The method of claim 2,
The parameters are: (i) transverse relaxation rate of fat; (Ii) transverse relaxation rate of water; And (iii) a composite transverse relaxation ratio of both water and fat;
Wherein the selected transverse relaxation rate by the image data processor is (i) fat in the tissue represented by the individual image elements; (Ii) moisture; And (iii) each of the individual image elements representing a proportion of one of the water-
A system for evaluating characteristics of tissue from magnetic resonance (MR) signal data of tissue. The method according to claim 1,
Further comprising an input processor configured to receive a plurality of sets of MR image representative signal data of a portion of the patient body acquired using a pulse sequence type and wherein the plurality of MR image representative signal data sets comprise a plurality of individual image elements Represents an embedded image;
Wherein the image data processor is further adapted to determine, in response to receiving the plurality of MR image representative signal data sets,
A system for evaluating characteristics of tissue from magnetic resonance (MR) signal data of tissue. The method according to claim 1,
Wherein each individual image element of the plurality of individual image elements comprises: (i) a pixel; (Ii) a group of pixels; (Iii) a voxel; And (iv) a group of voxels.
A system for evaluating characteristics of tissue from magnetic resonance (MR) signal data of tissue. A system for evaluating iron deposition of tissue from magnetic resonance (MR) signal data of tissue,
For each of the plurality of individual image elements of the MR image of the tissue, (i) transverse relaxation rate of fat; (Ii) transverse relaxation rate of water; And (iii) a composite transverse relaxation rate of both water and fat; And
A display processor configured to generate data representative of the MR image using the selected transverse relaxation rate to represent the individual image elements;
/ RTI >
A system for evaluating iron deposition of tissue from magnetic resonance (MR) signal data of tissue. 8. The method of claim 7,
Wherein the selected transverse relaxation rate by the image data processor is (i) fat in the tissue represented by the individual image elements; (Ii) moisture; And (iii) each of the individual image elements representing a proportion of one of the water-
A system for evaluating iron deposition of tissue from magnetic resonance (MR) signal data of tissue. 9. The method of claim 8,
Wherein the selected transverse relaxation rate is selected from the group consisting of (a) a ratio of fat exceeding a first threshold, and (b) a ratio of moisture below a second threshold within the tissue represented by the individual image elements. Rate,
A system for evaluating iron deposition of tissue from magnetic resonance (MR) signal data of tissue. 9. The method of claim 8,
Wherein the selected transverse relaxation rate is a transverse relaxation of moisture in the tissue represented by the individual image elements based on at least one of (a) a ratio of water exceeding a third threshold and (b) a ratio of fat below a fourth threshold Rate,
A system for evaluating iron deposition of tissue from magnetic resonance (MR) signal data of tissue. 11. The method of claim 10,
Wherein the first threshold and the fourth threshold are predetermined and substantially identical, and wherein the second threshold and the third threshold are predetermined and substantially the same,
A system for evaluating iron deposition of tissue from magnetic resonance (MR) signal data of tissue. 11. The method of claim 10,
Wherein the image data processor is further configured to adaptively select at least one of the thresholds in response to data indicative of a clinical procedure being performed,
A system for evaluating iron deposition of tissue from magnetic resonance (MR) signal data of tissue. 9. The method of claim 8,
Wherein the selected transverse relaxation rate is a composite of both water and fat based on at least one of (a) a ratio of water that is between predetermined thresholds in the tissue represented by the individual image elements and (b) The transverse relaxation rate,
A system for evaluating iron deposition of tissue from magnetic resonance (MR) signal data of tissue. 9. The method of claim 8,
Wherein the image data processor comprises: (i) localized magnetization of the tissue represented by the individual image elements; (Ii) the magnetization of water; And (iii) at least one of the magnetization of the water-fat mixture, (i) fat; (Ii) moisture; And (iii) a water-fat mixture.
A system for evaluating iron deposition of tissue from magnetic resonance (MR) signal data of tissue. 8. The method of claim 7,
Further comprising an input processor configured to receive a plurality of sets of MR image representative signal data of a portion of the patient body acquired using a pulse sequence type and wherein the plurality of MR image representative signal data sets comprise a plurality of individual image elements Represents an embedded image;
Wherein the image data processor is adapted to determine, in response to receiving the plurality of MR image representative signal data sets, selected transverse relaxation rates,
A system for evaluating iron deposition of tissue from magnetic resonance (MR) signal data of tissue. 8. The method of claim 7,
Wherein each individual image element of the plurality of individual image elements comprises: (i) a pixel; (Ii) a group of pixels; (Iii) a voxel; And (iv) a group of voxels.
A system for evaluating iron deposition of tissue from magnetic resonance (MR) signal data of tissue. 8. The method of claim 7,
Wherein the display processor comprises: (i) a plurality of selected transverse relaxation rates of fat for a corresponding first subset of individual image elements; (Ii) a plurality of selected transverse relaxation rates of moisture for a corresponding second subset of individual image elements; And (iii) generating data representing the MR image using one or more of a composite transverse relaxation rate of both moisture and fat for a third subset of the individual image elements.
A system for evaluating iron deposition of tissue from magnetic resonance (MR) signal data of tissue. 8. The method of claim 7,
The transverse relaxation rates (i)

; (Ii)

; (Iii)

; And (iv)

≪ / RTI >
A system for evaluating iron deposition of tissue from magnetic resonance (MR) signal data of tissue. A method of evaluating characteristics of tissue from magnetic resonance (MR) signal data of tissue,
Receiving, by the data image processor, a plurality of individual image elements of the MR image of the tissue;
Selecting, by the data image processor, one of a plurality of parameters of the tissue for each of the plurality of individual image elements of the plurality of individual image elements of the MR image of the tissue; And
In the display processor, generating data representing the MR image using the selected parameters to represent the individual image elements
/ RTI >
A method for evaluating characteristics of tissue from magnetic resonance (MR) signal data of tissue. 20. The method of claim 19,
Wherein the parameters of the tissue comprise parameters related to iron deposition in the tissue,
A method for evaluating characteristics of tissue from magnetic resonance (MR) signal data of tissue. 20. The method of claim 19,
The parameters are: (i) transverse relaxation rate of fat; (Ii) transverse relaxation rate of water; And (iii) a composite transverse relaxation ratio of both water and fat;
Wherein the image data processor comprises: (i) a fat in the tissue represented by the individual image elements; (Ii) moisture; And (iii) selecting the transverse relaxation rate based on each of the individual image elements representing a ratio of one of the water-
A method for evaluating characteristics of tissue from magnetic resonance (MR) signal data of tissue. 20. The method of claim 19,
Further comprising: receiving, by an input processor, a plurality of MR image representative signal data sets of a portion of a patient's body acquired using a pulse sequence type, and wherein the plurality of MR image representative signal data sets comprises the plurality of individual Represent images containing image elements;
Wherein the image data processor is adapted to determine, in response to receiving the plurality of MR image representative signal data sets,
A method for evaluating characteristics of tissue from magnetic resonance (MR) signal data of tissue. 20. The method of claim 19,
Wherein each individual image element of the plurality of individual image elements comprises: (i) a pixel; (Ii) a group of pixels; (Iii) a voxel; And (iv) a group of voxels.
A method for evaluating characteristics of tissue from magnetic resonance (MR) signal data of tissue.

Images