English:
[0001] Existing medical image storage systems typically store images indexed by patient identifiers. Such systems are well suited to searching for images for a particular patient using simple database queries. However, they are not suited to more complicated search criteria and advanced searches, because more detailed information is not available. Medical professionals may wish to be able to perform more advanced searches .
[0002] A system having a first data storage element storing a first set of data including patient images and a second data storage element storing a second set of data that is derived from the first set of data, the second set of data including searchable data that is descriptive of the first set of data and excludes the patient images.
[0004] Figure 1 shows an exemplary system for providing a medical database with enhanced search features.
[0005] Figure 2 shows an exemplary method for creating and using a medical database with enhanced search features.
[0007] Existing systems for storing patient images, such as Picture Archiving and Communication Systems ("PACS") are typically indexed by patient information. This information may include patient name and birth date, other patient identifiers, or study identifiers. Querying such an index for data using patient or study identifiers is simple and effective; however, searching based on other criteria is difficult or impossible. Therefore, though such databases are useful for some purposes, additional utility can be achieved by adapting existing databases to be queried in newer, more complex ways.
[0008] Fig. 1 illustrates an exemplary system 100. The system 100 includes a repository database 110, which stores patient information and is, for example, a PACS database, a pathology information system, etc. As described, the repository database 110 stores patient images indexed by, for example, a patient identifier, a study identifier, or other similar criteria. Typically, such data is stored according to the Digital Imaging and Communications in Medicine ("DICOM") standard. The user's ability to query the database 110 alone is limited as described above. However, the system 100 also includes a search database 120, which is created from the repository database 110 as will be described herein. The format of the search database 120 may be any database that is appropriate for this purpose; it may be as simple as a spreadsheet, but preferably is a database built specifically for this purpose. The system 100 also includes a bot 130 and a filter 140, which are used to create the search database 120.
[0009] The bot 130 and the filter 140 are typically software applications that reside on the system 100, although they may be located elsewhere, and may be stored in separate locations from one another. For example, different portions of a hospital may have separate PACS databases or there may be separate PACS databases at a series of affiliated hospitals. The bot 130 and the filter 140 may reside at one of these hospitals or portions of the hospital, but may have access to all the PACS databases. Additionally, the search database 120 may be located remotely from the patient image repository database 110 or may be located at the same location. The operation of these elements will be described in further detail below. The system 100 also includes a search interface 150, which may be part of a clinical application provided so that users may access the search database 120 through a user interface.
[0010] Fig. 2 illustrates an exemplary method 200. The method 200 will be described with reference to the process for constructing the search database 120 from the patient image repository database 110; however, the broader concepts illustrated by the exemplary method 200 are also applicable to systems other than that of Fig. 1. In step 210, the patient image repository database 110 is queried by the bot 130 to determine whether it contains new images that have not yet been indexed in the search database 120. As will be understood, when the search database 120 is being created, an initial query will retrieve all images from the repository database 110; subsequent queries will retrieve at least those images that have been added to the repository database 110 since the most recent previous query, and may be performed at regular intervals (e.g., weekly) . In alternative implementations, the query may be structured to retrieve all images from the repository database 110, including those that have recently been added. Preferably, queries are performed during time periods when system and network usage is low, such as overnights or weekends. It should be noted that the bot 130 may automatically query the database 110 based on a schedule or an event, or may be started manually by a user. In step 220, new images are retrieved by the bot 130 from the repository database 110 and passed to the filter 140.
[0011] In step 230, the filter 140 processes the images retrieved from the repository database 110 in order to provide searchable information for the search database 120. This processing step includes filtering images stored in the repository database 110 to extract searchable data. The data may be stored in the images (e.g., in a DICOM format) or derivable therefrom. The exact nature of the data to be extracted depends on the purpose for which the search database 120 is to be used; further, the extracted data is typically limited to that data which is relevant to the purpose of the search database 120. Pixel data stored in the images in the repository database 110 is typically removed from the data in order to obtain a search database 120 of a more manageable size; for a repository database 110 storing images in a DICOM format, pixel data may comprise 95% to 99% of the stored data volume. Thus, removal of the pixel data will result in a manageably sized database.
[0012] In step 240, the extracted data is added to the searchable search database 120. The first time the method 200 is performed, this step 240 includes the creation of a new searchable search database 120; subsequently, data is added to an existing search database 120. As discussed above, the search database 120 may be of any type suitable for storing this data, but preferably is of a type dedicated to this task. Thus, at the completion of step 240, the search database 120 is current and can be searched by a user. As described above, the search database 120 will be significantly smaller than the repository database 110 and is also optimized based on the data that is included. That is, as described herein, the exemplary embodiments create smaller databases that have new searchable indexes from the larger database. However, these new searchable indexes are created using existing indices that are previously generated based on knowledge of the field in the original database resulting in an optimized database. Thus, searching the search database 120 becomes faster and easier than searching the repository database 110. Further, many types of searches may be possible using the search database 120 that could not be accomplished at all using solely the repository database 110.
[0013] In step 250, the search database 120 is queried by the search interface 150. As described above, the query may take a more detailed form than what would be possible with the patient image repository database 110. For example, a user may search for all mammography structured reports containing more than three findings, or all dynamic contrast-enhanced MRI scans of the prostate with a temporal resolution of better than two seconds. The specific form of the query may vary from embodiment to embodiment, and may take any of various forms depending on the specific information that a user desires. For example, in one embodiment, the query may be text-based; in another, it may use a set of filters.
[0014] In step 260, the results of the query of step 250 are provided to the user. This may involve displaying results as a list, in a table, or in various other formats known in the art. Results will typically include references to entries in the patient image repository database 110, which can then be retrieved by the user via methods that are known in the art .
[0015] By the implementation of the above exemplary embodiments, users may be able to search for patient information using queries that are more detailed than those possible with existing methods. Further, such searches may utilize multiple search terms in a manner not allowed by existing methods. In addition, since the search database 120 contains only the relevant data (e.g., with image data being removed), faster searches may be performed.
[0016] In the above example, the search database 120 contains data for a single image repository database 110. However, it should be understood that the search database 120 may include data from multiple image databases or from other types of databases, allowing a user to search multiple storage locations using a single search database 120.
[0017] It will be apparent to those skilled in the art that various modifications may be made, without departing from the spirit or the scope of the invention. Thus, it is intended that the present disclosure cover modifications and variations, provided they come within the scope of the appended claims and their equivalents.
[0018] It is also noted that the claims may include reference signs/numerals in accordance with PCT Rule 6.2 (b) . However, the present claims should not be considered to be limited to the exemplary embodiments corresponding to the reference signs/numerals .

中文:
[0001]现有的医学图像存储系统典型地存储按患者标识符而索引的图像。这样的系统非常适合于使用简单的数据库查询来搜索针对特定患者的图像。然而,它们不适合于更复杂的搜索准则和高级搜索,因为不可获得更详细的信息。医学专业人员可能希望能够执行更高级的搜索。
[0002]一种系统,具有:第一数据存储元件,其存储包括患者图像的第一组数据;和第二数据存储元件,其存储从第一组数据中导出的第二组数据,第二组数据包括描述第一组数据且不包括患者图像的可搜索数据。
[0004]图1示出了用于提供具有增强的搜索特征的医学数据库的示范性系统;
[0005]图2示出了用于创建并使用具有增强的搜索特征的医学数据库的示范性方法。
[0007]诸如图片存档及通信系统(“PACS”)的用于存储患者图像的现有系统典型地按患者信息索引。该信息可以包括患者姓名及出生日期、其他患者标识符或研究标识符。使用患者或研究标识符而查询这样的数据索引是简单的且有效的;然而,基于其他准则而搜索是困难的或不可能的。因此,尽管这样的数据库对某些目的是有用的,但能够通过调整现有的数据库以按更新的且更复杂的方式对其进行查询,从而获得额外的效用。
[0008]图1图解说明了示范性系统100。系统100包括仓库(repository)数据库110,该仓库数据库110存储患者信息,并且,例如是PACS数据库、病理学信息系统等。如上所述,仓库数据库110存储按例如患者标识符、研究标识符或其他类似的准则而索引的患者图像。典型地,这样的数据根据医学数字成像及通信(“DICOM”)标准而存储。如上所述,仅用户查询数据库110的能力是有限的。然而,系统100还包括搜索数据库120,如本文将描述的,该搜索数据库120从仓库数据库110创建。搜索数据库120的格式可以是适合于该目的的任何数据库;可以像电子表格那样简单,但是优选为专门针对该目的而构建的数据库。系统100还包括用于创建搜索数据库120的机器人程序(bot)130和过滤器140。
[0009]机器人程序130和过滤器140典型地是驻留在系统100上的软件应用,尽管如此它们也可以位于其他位置,并且,也可以存储在彼此独立的位置处。例如,医院的不同部分可以具有独立的PACS数据库,或者,在一系列附属医院可以存在着独立的PACS数据库。机器人程序130和过滤器140可以驻留在这些医院之一或医院的各部分之一,但可以访问所有PACS数据库。另外,搜索数据库120可以位于远离患者图像仓库数据库110或可以位于相同的位置处。以下,将进一步详细地描述这些元件的运行。系统100还包括搜索界面150,该搜索界面150可以是所提供的临床应用的一部分,从而用户可以通过用户界面而访问搜索数据库120。
[0010]图2图解说明示范性方法200。将参考用于从患者图像仓库数据库110构造搜索数据库120的过程而描述方法200;然而,由示范性方法200图解说明的更广泛的概念还适用于除了图1的系统以外的系统。在步骤210中,由机器人程序130查询患者图像仓库数据库110,以确定其是否含有尚未在搜索数据库120中被索引的新图像。如将被理解的,当正在创建搜索数据库120时,初始查询将从仓库数据库110检索所有图像;后续查询将检索至少自最近的先前查询以来已添加至仓库数据库110的那些图像,并且,可以定期地(例如,每周)执行。在备选实现方式中,查询可以构造为从仓库数据库110检索所有图像,包括最近添加的那些图像。优选地,在诸如夜晚或周末的系统和网络使用率低的时间段期间执行查询。应当注意到,机器人程序130可以基于安排或事件而自动地查询数据库110,或可以由用户手动地开始。在步骤220中,由机器人程序130从仓库数据库110检索新图像,并且,将新图像传递至过滤器140。
[0011]在步骤230中,过滤器140处理从仓库数据库110检索的图像,以便为搜索数据库120提供可搜索的信息。该处理步骤包括过滤存储在仓库数据库110中的图像,以提取可搜索的数据。数据可以存储在图像中(例如,以DICOM格式)或可从其导出。将被提取的数据的确切性质取决于使用搜索数据库120的目的;而且,所提取的数据典型地限于与搜索数据库120的目的有关的数据。典型地将存储在仓库数据库110中的图像中的像素数据从数据移除,以便得到更易管理的大小的搜索数据库120;对于以DICOM格式存储图像的仓库数据库110,像素数据可能包括所存储的数据量的95%至99%。因而,像素数据的移除将得到易管理的大小的数据库。
[0012]在步骤240中,将所提取的数据添加至可搜索的搜索数据库120。在第一次执行方法200时,该步骤240包括创建新的可搜索的搜索数据库120;随后,将数据添加至现有的搜索数据库120。如以上所讨论地,搜索数据库120可以是适合于存储该数据的任何类型,但优选为该任务专用的类型。因而,在步骤240完成时,搜索数据库120是当前的,并且,能够由用户进行搜索。如上所述,搜索数据库120明显小于仓库数据库110,并且,还基于所包括的数据而进行优化。那就是,如本文所描述地,示范性实施例从较大的数据库创建具有新的可搜索的索引的较小的数据库。然而,这些新的可搜索的索引是使用先前基于原始数据库的领域的知识而生成的现有索引来创建的,得到优化数据库。因而,对搜索数据库120进行搜索变得比对仓库数据库110进行搜索更快且更容易。而且,仅使用仓库数据库110根本不能完成的许多类型的搜索可以使用搜索数据库120来进行。
[0013]在步骤250中,通过搜索界面150而查询搜索数据库120。如上所述,该查询可以采取比利用患者图像仓库数据库110而可能进行的形式更详细的形式。例如,用户可以搜索包含多于三个发现的所有乳腺摄影构造的报告或具有比两秒更好的时间分辨率的所有前列腺动态对比增强MRI扫描。查询的具体形式可以因实施例而异,并且,可以根据用户期望的具体信息而采取任何各种形式。例如,在一个实施例中,查询可以是基于文本的;在另一实施例中,查询可以使用一组过滤器。
[0014]在步骤260中,将步骤250的查询的结果提供给用户。这可能涉及将结果作为列表、以表格或者本领域中已知的各种其他格式显示。结果典型地包括对患者图像仓库数据库110中的条目的参考,然后,用户能够经由本领域中已知的方法而检索该参考。
[0015]通过实施以上的示范性实施例,用户可能能够使用比利用现有的方法可能进行的查询更详细的查询来搜索患者信息。而且,这样的搜索可以以现有的方法所不允许的方式利用多个搜索项。另外,由于搜索数据库120只包含相关数据(例如,图像数据被移除),可以执行更快的搜索。
[0016]在以上的示例中,搜索数据库120包含单个图像仓库数据库110的数据。然而,应当理解的是,搜索数据库120可以包括来自多个图像数据库或来自其他类型的数据库的数据,从而允许用户使用单个搜索数据库120来搜索多个存储位置。
[0017]对本领域技术人员显而易见的是,在不背离本发明的精神或范围的情况下,可以作出各种修改。因而,本公开旨在涵盖修改和变化,只要它们落入所附权利要求书及其等同物的范围内。
[0018]还注意到,根据PCT细则6.2(b),权利要求书可以包括参考符号/数字。然而,本权利要求书不应当被视为限于与参考符号/数字相对应的示范性实施例。