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1. 发明申请

US20170202520A1 METHOD FOR PREDICTING THE DEVELOPMENT OF ARTHRITIS IN INDIVIDUALS PRIOR TO RADIOGRAPHIC OR SYMPTOMATIC PRESENTATION 审中-公开
公开(公告)号：US20170202520A1
公开(公告)日：2017-07-20
申请号：US15476615
申请日：2017-03-31
申请人： Kenneth L. Urish , Matthew G. Keffalas , Timothy J. Mosher , David J. Miller
发明人： Kenneth L. Urish , Matthew G. Keffalas , Timothy J. Mosher , David J. Miller
IPC分类号： A61B5/00 , A61B5/055
CPC分类号： A61B5/7275 , A61B5/055 , A61B5/4514 , A61B5/4528 , A61B5/4571 , A61B5/4576 , A61B5/458 , A61B5/4585 , A61B5/459 , A61B5/4595 , A61B5/7264 , A61B5/7267 , G01R33/50 , G01R33/5608 , G16H30/40 , G16H50/20 , G16H50/30
摘要： A method for detecting symptomatic osteoarthritis in a human patient who is otherwise asymptomatic comprises: taking a plurality of magnetic resonance (MR) image signal features from MR sequences in a joint of the patient; submitting the MR image signal features to a classifier for performing a feature reduction for redundant or unnecessary features; calculating a signal texture index (STI) value from the remaining image features; comparing that STI value against the STI values of one group of individuals suspected of being vulnerable to developing osteoarthritis at the first point in time; and the same group of individuals years later; predicting from that comparison of STI values a likelihood of the patient developing osteoarthritis; and treating the patient accordingly.

2. 发明申请

US20130137962A1 Method for Detecting Arthritis and Cartilage Damage Using Magnetic Resonance Sequences 审中-公开
标题翻译：使用磁共振序列检测关节炎和软骨损伤的方法
公开(公告)号：US20130137962A1
公开(公告)日：2013-05-30
申请号：US13691359
申请日：2012-11-30
申请人： Kenneth L. Urish , Matthew G. Keffalas , Timothy J. Mosher , David J. Miller
发明人： Kenneth L. Urish , Matthew G. Keffalas , Timothy J. Mosher , David J. Miller
IPC分类号： A61B5/055
CPC分类号： A61B5/055 , A61B5/7264 , A61B5/7267 , G01R33/50
摘要： In this work, a Magnetic Resonance Imaging (MRI)-based automatic classifier was designed to predict changes due to osteoarthritis (OA) years prior to their symptomatic presentation and radiographic detection. For each patient, multiple image texture features were measured from the T2 map of the patella cartilage and the lateral and medial compartments of the femoral condyle. A support vector machine (SVM)-based linear discriminant function was trained to predict health status, as well as the affected knee compartment. Feature selection was integrated into the classifier training to drastically reduce the number of image (biomarker) features without sacrificing classification accuracy. It was found that a dominant knee compartment determined the classification decision for most patients. We demonstrate that the signal texture index (STI) predicts disease progression prior to symptoms or radiographic signs of OA. In symptomatic individuals, the STI correlates with the pain and severity of OA suggesting it is a sensitive measure of the same on T2 Maps. These observed changes localized to one knee compartment demonstrating the method can localize OA to specific regions.
摘要翻译：在这项工作中，设计了基于磁共振成像（MRI）的自动分类器，以预测在其症状呈现和放射照相检测之前由于骨关节炎（OA）年龄的变化。对于每个患者，从髌骨软骨的T2图和股骨髁的外侧和内侧隔室测量多个图像纹理特征。训练了基于支持向量机（SVM）的线性判别函数来预测健康状况，以及受影响的膝盖室。特征选择被集成到分类器训练中，大大减少了图像（生物标记）特征的数量，而不牺牲分类精度。发现显性膝盖室确定了大多数患者的分类决定。我们证明信号纹理指数（STI）预测OA症状或放射学迹象之前的疾病进展。在有症状的个体中，STI与OA的疼痛和严重程度相关，表明它是T2地图上的相同的敏感度量。这些观察到的局限于一个膝盖室的变化表明该方法可以将OA定位到特定区域。

3. 发明申请

US20160213278A1 Method for Detecting Arthritis and Cartilage Damage Using Magnetic Resonance Sequences 审中-公开
标题翻译：使用磁共振序列检测关节炎和软骨损伤的方法
公开(公告)号：US20160213278A1
公开(公告)日：2016-07-28
申请号：US14971782
申请日：2015-12-16
申请人： Kenneth L. Urish , Matthew G. Keffalas , Timothy J. Mosher , David J. Miller
发明人： Kenneth L. Urish , Matthew G. Keffalas , Timothy J. Mosher , David J. Miller
IPC分类号： A61B5/055 , A61B5/00
CPC分类号： A61B5/055 , A61B5/4514 , A61B5/4528 , A61B5/4585 , A61B5/7264 , A61B5/7267 , A61B5/7275 , G01R33/50 , G01R33/5608 , G16H30/40 , G16H50/30 , G16H50/70
摘要： A method for detecting symptomatic osteoarthritis in a human patient who is otherwise asymptomatic comprises: taking a plurality of magnetic resonance (MR) image signal features from MR sequences in a joint of the patient; submitting the MR image signal features to a classifier for performing a feature reduction for redundant or unnecessary features which are then eliminated; calculating a signal texture index (STI) value from the remaining image features; comparing that STI value against two population databases, one for individuals known to develop osteoarthritis and a second for individuals known not to develop osteoarthritis at a given time point; prognosticating from the STI value, a likelihood of the patient developing osteoarthritis; and treating the patient accordingly.
摘要翻译：用于检测否则无症状的人类患者中的症状性骨关节炎的方法包括：从患者的关节中的MR序列获取多个磁共振（MR）图像信号特征; 将MR图像信号特征提交给分类器，以便为冗余或不必要的特征执行特征降低，然后消除该特征; 从剩余图像特征计算信号纹理指数（STI）值; 将STI值与两个人口数据库进行比较，一个针对已知发展为骨关节炎的个体，另一个针对在给定时间点未发生骨关节炎的个体; 从STI值预测，患者出现骨关节炎的可能性; 并相应地对待患者。

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