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    METHOD FOR ASSESSING REPETITIVE HEAD INJURIES WITH TWO-DIMENSIONAL MAGNETIC RESONANCE SPECTROSCOPY
    1.
    发明申请
    METHOD FOR ASSESSING REPETITIVE HEAD INJURIES WITH TWO-DIMENSIONAL MAGNETIC RESONANCE SPECTROSCOPY 有权
    用二维磁共振光谱法评估重复性头部损伤的方法

    公开(公告)号：US20140002075A1

    公开(公告)日：2014-01-02

    申请号：US13988813

    申请日：2011-11-28

    申请人： Alexander Lin ,  Carolyn Mountford ,  Saadallah Ramadan ,  Robert Stern

    发明人： Alexander Lin ,  Carolyn Mountford ,  Saadallah Ramadan ,  Robert Stern

    IPC分类号： G01R33/483

    CPC分类号： G01R33/483 ,  A61B5/055 ,  A61B5/4064 ,  A61B2503/00 ,  A61B2503/04 ,  A61B2503/10 ,  G01R33/485

    摘要： A method for producing a biomarker indicative of a repetitive head injury in a subject using a magnetic resonance imaging (MRI) system is provided. Two-dimensional spectroscopic data is acquired from a subject using an MRI system. From the two-dimensional spectroscopic data, a two-dimensional spectrum is produced. The two-dimensional spectrum contains spectral information indicated by a first spectral dimension and a second spectral dimension. Such a two-dimensional spectrum may include diagonal peaks and off-diagonal, or cross-peaks. In such an instance, each cross peak may indicate, for example, scalar coupling between the two protons it connects on the diagonal. However, depending on the type of method used, different types of coupling may also be present. Using the two-dimensional spectrum, a biomarker indicative of repetitive head injury in the subject is identified, and may be used to produce a report indicating a status or regression of a neurological dysfunction.

    摘要翻译： 提供了使用磁共振成像（MRI）系统来产生指示受试者的重复性头部损伤的生物标志物的方法。 使用MRI系统从受试者获取二维光谱数据。 从二维光谱数据生成二维光谱。 二维光谱包含由第一光谱维度和第二光谱维度指示的光谱信息。 这样的二维光谱可以包括对角峰和非对角线或交叉峰。 在这种情况下，每个交叉峰值可以表示例如它在对角线上连接的两个质子之间的标量耦合。 然而，根据所使用的方法的类型，也可以存在不同类型的耦合。 使用二维光谱，鉴定出指示受试者重复性头部损伤的生物标志物，并且可用于产生指示神经功能障碍的状态或消退的报告。

    System and Method for Detecting Pain and Its Components Using Magnetic Resonance
    2.
    发明申请
    System and Method for Detecting Pain and Its Components Using Magnetic Resonance 审中-公开
    使用磁共振检测疼痛及其成分的系统和方法

    公开(公告)号：US20100152569A1

    公开(公告)日：2010-06-17

    申请号：US12644315

    申请日：2009-12-22

    申请人： Philip John Siddall ,  Carolyn Mountford ,  Anne Woodhouse ,  Peter Stanwell ,  Rajmund Somorjai

    发明人： Philip John Siddall ,  Carolyn Mountford ,  Anne Woodhouse ,  Peter Stanwell ,  Rajmund Somorjai

    IPC分类号： A61B5/055

    CPC分类号： A61B5/4824 ,  A61B5/055 ,  A61B5/14532 ,  G01R33/483

    摘要： A system and method identifies different components of the pain experience (nociceptive (tissue damage), neuropathic (nerve damage) and psychological) and their relative contributions by the use of magnetic resonance spectroscopy (MRS) to measure absolute and relative concentrations of metabolites in specific brain regions in the central nervous system or brain. The system and method can be used as a diagnostic tool for the assessment of the relative contribution of different aspects of the pain experience as well as monitoring of response to interventions directed at modifying these components.

    摘要翻译： 系统和方法通过使用磁共振光谱（MRS）来测定疼痛经验（伤害性（组织损伤），神经损伤（神经损伤）和心理）的不同组成部分及其相对贡献来测量特异性的代谢物的绝对和相对浓度 中枢神经系统或大脑中的脑区。 该系统和方法可用作诊断工具，用于评估疼痛经验的不同方面的相对贡献以及监测针对修改这些组件的干预措施的响应。

    System and method for detecting pain and its components using magnetic resonance
    3.
    发明授权
    System and method for detecting pain and its components using magnetic resonance 有权
    使用磁共振检测疼痛及其成分的系统和方法

    公开(公告)号：US08755862B2

    公开(公告)日：2014-06-17

    申请号：US13426324

    申请日：2012-03-21

    申请人： Phillip John Siddall ,  Carolyn Mountford ,  Anne Woodhouse ,  Peter Stanwell ,  Rajmund Somorjai

    发明人： Phillip John Siddall ,  Carolyn Mountford ,  Anne Woodhouse ,  Peter Stanwell ,  Rajmund Somorjai

    IPC分类号： A61B5/055

    CPC分类号： A61B5/4824 ,  A61B5/055 ,  A61B5/14532 ,  G01R33/483

    摘要： A system and method identifies different components of the pain experience (nociceptive (tissue damage), neuropathic (nerve damage) and psychological) and their relative contributions by the use of magnetic resonance spectroscopy (MRS) to measure absolute and relative concentrations of metabolites in specific brain regions in the central nervous system or brain. The system and method can be used as a diagnostic tool for the assessment of the relative contribution of different aspects of the pain experience as well as monitoring of response to interventions directed at modifying these components.

    摘要翻译： 系统和方法通过使用磁共振光谱（MRS）来测定疼痛经验（伤害性（组织损伤），神经损伤（神经损伤）和心理）的不同组成部分及其相对贡献来测量特异性的代谢物的绝对和相对浓度 中枢神经系统或大脑中的脑区。 该系统和方法可用作诊断工具，用于评估疼痛经验的不同方面的相对贡献以及监测针对修改这些组件的干预措施的响应。

    Magnetic resonance spectroscopy to classify tissue
    5.
    发明申请
    Magnetic resonance spectroscopy to classify tissue 有权
    磁共振光谱法分类组织

    公开(公告)号：US20050107683A1

    公开(公告)日：2005-05-19

    申请号：US11012959

    申请日：2004-12-15

    申请人： Carolyn Mountford ,  Peter Russell ,  Ian Smith ,  Rajmund Somorjai

    发明人： Carolyn Mountford ,  Peter Russell ,  Ian Smith ,  Rajmund Somorjai

    IPC分类号： G01N24/08 ,  G01R33/46 ,  G01R33/465 ,  A61B5/05

    CPC分类号： G06F19/366 ,  G01N24/08 ,  G01R33/20 ,  G01R33/4625 ,  G01R33/465 ,  G16H10/40 ,  Y10T436/24

    摘要： Robust classification methods analyse magnetic resonance spectroscopy (MRS) data (spectra) of fine needle aspirates taken from breast tumours. The resultant data when compared with the histopathology and clinical criteria provide computerized classification-based diagnosis and prognosis with a very high degree of accuracy and reliability. Diagnostic correlation performed between the spectra and standard synoptic pathology findings contain detail regarding the pathology (malignant versus benign), vascular invasion by the primary cancer and lymph node involvement of the excised axillary lymph nodes. The classification strategy consisted of three stages: pre-processing of MR magnitude spectra to identify optimal spectral regions, cross-validated Linear Discriminant Analysis, and classification aggregation via Computerised Consensus Diagnosis. Malignant tissue was distinguished from benign lesions with an overall accuracy of 93%. From the same spectrum, lymph node involvement was predicted with an accuracy of 95% and tumour vascularisation with an overall accuracy of 92%.

    摘要翻译： 鲁棒分类方法分析从乳腺肿瘤获取的细针抽吸物的磁共振谱（MRS）数据（光谱）。 与组织病理学和临床标准相比，得到的数据提供了非常高的精度和可靠性的基于计算机分类的诊断和预后。 在光谱和标准天气病理学发现之间进行的诊断相关性包括关于病理学（恶性与良性），原发性癌症的血管浸润和切除的腋窝淋巴结的淋巴结的细节的细节。 分类策略包括三个阶段：预处理MR幅度谱以识别最佳光谱区域，交叉验证线性判别分析和通过计算机共识诊断分类聚合。 恶性组织与良性病变区分开，总体准确率为93％。 从同一频谱，预测淋巴结参与率为95％，肿瘤血管形成的准确度为92％。