Abstract:
A method of generating an image of a coronary artery tree for a patient. The method can include acquiring data from the patient for coronary artery segments and generating a coronary artery tree image including the coronary artery segments. The method can also include accessing coronary artery tree patterns, comparing the coronary artery tree image to the coronary artery tree patterns, and automatically selecting one of the coronary artery tree patterns as a representative coronary artery tree image for the patient. The method can further include measuring lesions and automatically adding the lesion measurements to the coronary artery tree image for the patient.

Description:
BACKGROUND OF THE INVENTION 
     The coronary artery tree is a system of arteries that supplies oxygen and nutrient-rich blood directly to the heart muscle. When these arteries begin to calcify, or build up fatty deposits along their walls, adverse cardiac events can occur, such as myocardial infractions or coronary artery disease. Proper diagnosis and treatment of these calcifications (also referred to as stenoses or lesions) are critical to reducing the high fatality rate associated with such adverse cardiac events. 
     Medical procedures, such as cardiac catheterization, generally result in reports created by the performing clinician that detail the procedure, including the diagnosis and the intervention performed. Such reports typically include graphics representative of the coronary artery tree pattern for the patient. Conventionally, the clinician creating the report must manually select an appropriate coronary artery tree pattern that represents the coronary anatomy of the patient. In addition, the clinician must remember the location and quantity of lesions in the patient&#39;s arteries or must manually input the lesion data into coronary annotation software. 
     Conventional imaging systems may include Quantitative Coronary Analysis (QCA) software. A clinician uses the QCA software during a QCA session to measure lesions in a patient&#39;s coronary arteries. Conventional imaging systems may also include coronary annotation software that is used to generate a coronary artery tree image for the patient. Currently, the clinician can use the coronary annotation software to only manually annotate the coronary artery tree image with information regarding lesions measured during the QCA session. The results of the QCA session currently cannot be saved and cannot be automatically transferred to the coronary annotation software for display on the coronary artery tree image for the patient. Also, conventional coronary annotation software only offers visual size interpretation of the lesions. In addition, the manual annotation and the visual size interpretation generally occur on different screens and at different times during the clinician&#39;s use of the coronary annotation software. 
     BRIEF DESCRIPTION OF THE INVENTION 
     In light of the problems and limitations described above, a need exists for the automatic input of the patient-specific data from QCA software into coronary annotation software in order to increase the efficiency and accuracy of coronary artery lesion mapping. Automatic input can eliminate or drastically reduce report time for the clinician, can ensure inclusion and accurate location of all lesions, and can ensure secure data transfer. 
     One embodiment of the invention includes a method of generating an image of a coronary artery tree for a patient. The method can include acquiring data from the patient for one or more coronary artery segments of the coronary artery tree, generating a coronary artery tree image including the coronary artery segments, and accessing coronary artery tree patterns. The method can also include comparing the coronary artery tree image to the coronary artery tree patterns using a pattern recognition module and automatically selecting one of the coronary artery tree patterns as a representative coronary artery tree image for the patient. The method can further include detecting a lesion in one of the coronary artery segments, and automatically adding a measurement of the lesion to the coronary artery tree image. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a schematic illustration of a coronary imaging system according to one embodiment of the invention. 
         FIGS. 2A and 2B  include a flowchart illustrating the operation of the coronary imaging system of  FIG. 1  according to one embodiment of the invention. 
         FIG. 3  is an illustration of a computer screen including original coronary artery tree images that are displayed using the coronary imaging system of  FIG. 1 . 
         FIG. 4  is an illustration of a computer screen including a graphical user interface that is displayed using the coronary imaging system of  FIG. 1 . 
         FIG. 5  is an illustration of a computer screen including an annotated coronary artery tree image that is displayed using the coronary imaging system of  FIG. 1 . 
     
    
    
     DETAILED DESCRIPTION 
     Before any embodiments of the invention are explained in detail, it is to be understood that the invention is not limited in its application to the details of construction and the arrangement of components set forth in the following description or illustrated in the following drawings. The invention is capable of other embodiments and of being practiced or of being carried out in various ways. Also, it is to be understood that the phraseology and terminology used herein is for the purpose of description and should not be regarded as limited. The use of “including,” “comprising” or “having” and variations thereof herein is meant to encompass the items listed thereafter and equivalents thereof as well as additional items. The terms “mounted,” “connected” and “coupled” are used broadly and encompass both direct and indirect mounting, connecting and coupling. Further, “connected” and “coupled” are not restricted to physical or mechanical connections or couplings, and can include electrical connections or couplings, whether direct or indirect. 
     In addition, it should be understood that embodiments of the invention include both hardware and electronic components or modules that, for purposes of discussion, may be illustrated and described as if the majority of the components were implemented solely in hardware. However, one of ordinary skill in the art, and based on a reading of this detailed description, would recognize that, in at least one embodiment, the electronic based aspects of the invention may be implemented in software. As such, it should be noted that a plurality of hardware and software based devices, as well as a plurality of different structural components may be utilized to implement the invention. Furthermore, and as described in subsequent paragraphs, the specific mechanical configurations illustrated in the drawings are intended to exemplify embodiments of the invention and that other alternative mechanical configurations are possible. 
       FIG. 1  illustrates a coronary imaging system  10  according to one embodiment of the invention. The coronary imaging system  10  can include an imaging device  14 , a pattern recognition module  18 , coronary artery tree patterns  22  stored in a database  26 , a quantitative coronary analysis (QCA) module  30 , a coronary tree generation module  38 , and a display device  42 . The imaging device  14  can include any one or more of the following imaging devices: an x-ray machine, a magnetic resonance imaging system, a computerized axial tomography system, a digital imaging and communications in medicine (DICOM) image review system, and a positron emission tomography system. The imaging device  14  can acquire data from a patient in order to generate an original coronary artery tree image  34 , as shown in  FIGS. 3 and 4 . 
     In some embodiments, the pattern recognition module  18  can access the coronary artery tree patterns  22  in the database  26 . The database  26  can store coronary artery tree patterns  22  having a known condition, a known diagnosis, and/or a known physiology. Using pattern matching algorithms, the pattern recognition module  18  can compare the original coronary artery tree image  34  to the coronary artery tree patterns  22 . In one embodiment, the pattern recognition module  18  can automatically select one of the coronary artery tree patterns  22  as a representative coronary artery tree that can be annotated to indicate the patient&#39;s lesions (as shown in  FIG. 5 ). In some embodiments, the pattern recognition module  18  receives image positioning information from the imaging device  14  to assist in selecting the representative coronary artery tree pattern for the patient. In another embodiment of the invention, the pattern recognition module  18  can be omitted and the coronary tree generation module  38  can generate a coronary artery tree image including each coronary artery segment of the patient&#39;s actual coronary artery tree. In other words, rather than choosing a representative coronary artery tree that is similar to the patient&#39;s coronary artery tree, the coronary tree generation module  38  can generate a patient-specific coronary artery tree that is a replication of the patient&#39;s actual coronary artery tree. Whether the coronary artery tree image is a representative image or an actual image, an annotated coronary artery tree image  36  for the patient can be displayed as shown in  FIG. 5 . 
     Referring to  FIG. 3 , the QCA module  30  can be used by a clinician to measure any lesions shown in the original coronary artery tree image  34 . The clinician can calibrate a measurement device of the QCA module  30  and can then use a mouse (or any other suitable pointer device) to select a lesion  66  located in a coronary artery tree segment  94 . The QCA module  30  can detect the edge of the coronary artery and can measure the diameter and/or the cross-sectional area of the coronary artery along the length of the lesion, including the diameter at an obstructed point and the diameter at an unobstructed point. As shown in  FIG. 3 , the lesion  66  has resulted in a diameter of 0.96 mm at the most obstructed point. Also, the coronary artery has a diameter of 2.25 mm at an unobstructed point. 
     The QCA module  30  or the coronary tree generation module  38  can generate a graphical user interface  100  (as shown in  FIG. 4 ) for the display device  42 . The graphical user interface  100  can include a list of parameters  102  and values  104  corresponding to each of the parameters  102 . The parameters  102  can include stenosis ratio, reference diameter, stenosis diameter, ideal diameter at stenosis, and lesion length. The stenosis ratio parameter can include a first percentage (which is 56.42% in  FIG. 4 ) indicating the amount by which the diameter of the coronary artery has been reduced by the lesion. The stenosis ratio parameter can include a second percentage (which is 81.01% in  FIG. 4 ) indicating the amount by which the cross-sectional area of the coronary artery has been reduced by the lesion. 
     The graphical user interface  100  can also include an X-Y graph  105  with the X-axis representing a length of a coronary artery segment and the Y-axis representing a diameter of the coronary artery. For example, as shown in  FIG. 4 , the lesion is 22.27 mm long as represented by the X-axis of the X-Y graph  105 . At its most unobstructed point, the coronary artery has a diameter of 3.55 mm as represented by a first data point  106 . The beginning of the lesion can be represented by a second data point  108 . The most obstructed point of the lesion can be represented by a third data point  110 . At its most obstructed point, the coronary artery has a diameter of 1.55 mm, which is located 7.6 mm from beginning of the lesion and the first data point  106 . The end of the lesion can be represented by a fourth data point  112 , which is located 22.7 mm from the beginning of the lesion and the first data point  106 . The X-Y graph  105  can also include a curve  114  that represents the change in diameter along the length of the lesion. In addition, the X-Y graph  105  can include a lesion length indicator  116  indicating that the lesion is 22.3 mm long. 
     The QCA module  30  can automatically provide data to the coronary tree generation module  38  through an internal software connection. In some embodiments, the coronary imaging system  10  includes an application program interface (API) that automatically reads and transmits the results of the QCA session to the coronary tree generation module  38 . The QCA module  30  can automatically update the coronary tree generation module  38  with a patient-specific coronary artery tree image generated from actual measurements and accumulated analyses. 
     The coronary tree generation module  38  can output an annotated coronary artery tree image  36  (as shown in  FIG. 5 ) to the display device  42 . The annotated coronary artery tree image  36  can be displayed in a window with various menus for performing various tasks (such as the conventional save, open, and print functions, along with any other suitable functions). The annotated coronary artery tree image  36  can include labels  117  for many of the coronary arteries and other blood vessels (such as the aorta). A clinician can use the QCA module  30  or the coronary tree generation module  38  to assign a descriptor to each lesion from a drop-down list of lesion descriptors. A clinician can use the QCA module  30  or the coronary tree generation module  38  to place a comparable percentage stenosis mark  118  and/or a length measurement for each lesion on the annotated coronary artery tree image  36 . In addition to the annotated coronary artery tree image  36 , additional patient data  120 , input fields  122 , and a tree check list  124  can be displayed adjacent to the annotated coronary artery tree image  36 . The additional patient data  120  can include the patient&#39;s name, a study identification, and a procedure date. The input fields  122  can include Procedure (Diagnostic or Intervention), Dominance (Left, Right, or Mixed), Valve Disease (Yes, No, Unknown), and Injected (LAD, RCA, and Circumflex). The tree check list  124  can include a listing of the coronary arteries that are currently displayed. 
     In some embodiments, the coronary tree generation module  38  automatically updates the annotated coronary artery tree image  36  with any lesions detected throughout the course of the QCA session. Upon completion or during the course of the QCA session, the clinician can view the annotated coronary artery tree image  36  shown in  FIG. 5 , including any descriptors, comparable percentage stenosis marks, and length measurements. 
       FIGS. 2A and 2B  include a flowchart illustrating the operation of the coronary imaging system  10  according to one embodiment of the invention. The clinician can acquire (at  46 ) data from the patient using the imaging device  14 . The imaging device  14  can generate (at  50 ) the original coronary artery tree image  34  (as shown in  FIGS. 3 and 4 ). The pattern recognition module  18  can compare (at  54 ) the original coronary artery tree image  34  to the coronary artery tree patterns  22  stored in the database  26 . The pattern recognition module  18  can automatically select (at  58 ) a representative coronary artery tree pattern for the patient. 
     Referring to  FIG. 2B , the clinician can initiate (at  62 ) a Quantitative Coronary Analysis (QCA) session. The clinician can measure (at  70 ) a lesion  66  (as shown in  FIG. 3 ). The QCA module  30  can automatically transfer (at  74 ) the results of the QCA session to the coronary artery tree generation module  38 . The coronary tree generation module  38  can automatically populate (at  78 ) the annotated coronary artery tree image  36  (as shown in  FIG. 5 ) with the results of the QCA session. In other words, the coronary tree generation module  38  can automatically add a measurement of the lesion  66  to the annotated coronary artery tree image  36  for the patient. 
     The clinician can use the QCA module  30  to determine (at  82 ) if there are additional lesions in the patient&#39;s coronary artery tree. If there are additional lesions, the QCA module  30  can measure (at  70 ) the additional lesions, transfer (at  74 ) the results, and populate (at  78 ) the annotated coronary artery tree image  36 . If there are no additional lesions, the coronary tree generation module  38  can display (at  86 ) the annotated coronary artery tree image  36  populated with the lesions. 
     Various features and advantages of the invention are set forth in the following claims.