Patent Publication Number: US-6671535-B1

Title: Method and system for controlling heat delivery to a target

Description:
PRIORITY APPLICATION 
     This application is a continuation of U.S. application Ser. No. 09/710,694, filed on Nov. 8, 2000, now U.S. Pat. No. 6,542,767 B1, issued on Apr. 1, 2003 entitled METHOD AND SYSTEM FOR CONTROLLING HEAT DELIVERY TO A TARGET, which claims benefit of U.S. Provisional Patent Application Serial No. 60/164,416 filed Nov. 9, 1999, entitled “METHOD AND SYSTEM FOR CONTROLLING HEAT DELIVERY TO A TARGET” of common assignee herewith. 
    
    
     FIELD OF THE INVENTION 
     The present invention relates generally to controlling heat delivered to a target, and more particularly to controlling heat delivered to a target based upon temperature sensitive information from a device that interrogates a target with radiation as part of acquiring input data used for controlling heat delivery. 
     BACKGROUND OF THE INVENTION 
     It is recognized in the medical industry that undesirable lesions can be treated through their removal. It is known to have a practitioner, such as a doctor, physically remove such lesions through surgery. It is also known to have a practitioner destroy lesions by controlling an application of heat local to the lesion. Known processes whereby a practitioner destroys the lesion by using heat require the practitioner to control the process based on visual data and temperature data. Based upon this information, the practitioner will modify the heat source to change an attribute of the heat, such as its location, direction, and intensity. The proper application of the heat delivery process is dependent upon the ability of the practitioner to interpret available visual and temperature data, and to implement an appropriate treatment in response. As a result, the ability to control processes in a predictable manner varies between practitioners, and even varies day-to-day for a given practitioner. 
     Therefore, a method and or system that allows for improved control in treating a target, such as a lesion, would be useful. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     FIG. 1 is a diagram illustrating a real time feedback-controlled energy delivery system according to at least one embodiment of the present invention; 
     FIG. 2 is a diagram illustrating a data processor according to at least one embodiment of the present invention; 
     FIG. 3 is a diagram illustrating a heat generating system according to at least one embodiment of the present invention; 
     FIG. 4 is diagram illustrating a graphical user interface according to at least one embodiment of the present invention; 
     FIG. 5 is a diagram illustrating a fuzzy logic membership tuning interface according to at least one embodiment of the present invention; 
     FIG. 6 is a diagram illustrating a fuzzy logic rule set tuning interface according to at least one embodiment of the present invention; 
     FIG. 7 is a flow diagram illustrating a method for real-time feedback control of an energy delivery system according to at least one embodiment of the present invention; and 
     FIG. 8 is a diagram illustrating an implementation of an energy delivery system according to at least one embodiment of the present invention. 
    
    
     DETAILED DESCRIPTION OF THE DRAWINGS 
     In accordance with at least one embodiment of the present invention, data is received at a data processor from a temperature detection system, wherein the data corresponds to a material, such as a tissue portion, and includes temperature sensitive information. The data processor determines a first characteristic for a heat generating device based on the temperature information. Additionally, the data processor provides the heat generating device control data based on the first characteristic to control the heat generating device. One advantage of the present invention is that it is possible to provide a method for non-invasively determining the temperature distribution inside of an object, and in real time or near real time using the temperature distribution and/or damage distribution of the material to control an excessive heat output and/or to avoid an insufficient heat output, or to otherwise effect a desired result. 
     FIGS. 1-8 illustrate an energy delivery system in accordance with a specific embodiment of the present invention having one or more temperature detection systems, one or more data processors, and one or more heat generating systems, as well as a method for its use. As described in greater detail below, the energy delivery system uses a temperature detection system to either periodically or continuously measure the temperature and/or cell damage of a target receiving heat energy. In at least one embodiment, a user inputs desired parameters to define a control strategy for the heat generating system. The data processor uses the control strategy to govern the behavior of the heat generating system in real time, or near real time, using feedback from the temperature detection system. The data processor is also capable of displaying temperature, damage, and structure images to the user, as well as inputting user-defined parameters, with a graphical user interface (GUI). 
     Referring now to FIG. 1, a feedback-controlled energy delivery system  100  is illustrated according to one embodiment of the present invention. Energy delivery system  100  includes temperature detection system  110 , data processor  120 , and heat generating system  130 . Temperature detection system  110  includes a device that uses radiation to interrogate a target or other suitable system capable of acquiring temperature information of target  140 . In one embodiment, target  140  includes a biological tissue to be destroyed by heating, or any other object having specific localized areas to be heated without damaging surrounding areas. Temperature detection system  110  may include a magnetic resonance device, an ultrasound device, an infrared device, a radio frequency device, x-ray device, infrared detection device, computerized topography (CT) device, and the like. 
     Data processor  120  can include any data processing system capable of receiving and processing data from temperature detection system  110  to control, on a real-time or near real-time basis, heat generating system  130 . Data processor  120  may include a workstation, personal computer, supercomputer, dedicated hardware, and the like. Heat generating system  130  can include any device capable of generating heat, or energy that may be transformed to heat, and further capable of conveying this heat or energy to target  140  via one or more applicators. Heat generating system  130  may include a laser device, a microwave device, a resistive heater, and the like. It will be appreciated that data processor  120  may be either locally or remotely connected to temperature detection system  110  and heat generating system  130 . It will also be appreciated that energy delivery system  100  may include more than one of each of temperature measuring system  110 , data processor  120 , and heat generating system  130  without departing from the spirit or the scope of the present invention. 
     In one embodiment of the present invention, temperature detection system  110  is capable of obtaining temperature sensitive data on a periodic or continuing basis. The temperature sensitive data can represent the absolute or relative temperature distribution of a point, area, plane, contour, or volume of a portion of target  140 . For example, a magnetic resonance device can be used to capture data to be processed for determining the structure of selected portions of target  140 , as well as the selected portions&#39; relative temperature distribution at a given point in time. After temperature detection system  110  captures data  105  from target  140  for one cycle, data  105  may be either stored in a database in temperature detection system  110  and transmitted at a later time to data processor  120 , or the captured data (data  105 ) may be immediately sent to data processor  120 . It will be appreciated that temperature detection system  110  may pre-process data  105  before it is transmitted to data processor  120 . 
     In a specific embodiment of the present invention, data processor  120  is capable of receiving data  105  as input data from temperature detection system  110  and processing data  105  to control the operation of heat generating system  130  and/or to display information to the user via a graphical user interface (GUI)  250 . Some of the information displayed to the user using GUI  250  may include images displaying the temperature of a portion of target  140 , the structure of a portion of target  140 , the dead and dying cells in a portion of target  140  (where target  140  is biological tissue), and the like. Other information displayed may include the status of heat generating system  130 , the temperature history of one or more points, areas, contours, planes, or volumes of a portion of target  140 , etc. In one embodiment, data processor  120  also is capable of accepting user-defined parameters input through GUI  250 . For example, a user may be capable of using a contrast adjuster on GUI  250  to change the contrast of an image, or to select points, areas, planes, or volumes of a portion of target  140  for monitoring of temperatures or tissue damage. 
     Data processor  120  processes data  105  using control strategy  127  to produce control parameters that direct the behavior of heat generating system  130 . In one embodiment, heat generating system  130  receives and implements the control parameters from data processor  120  to perform the desired action. For example, data processor  120  may determine, using control strategy  127  and data  105 , that the temperature of a portion of target  140  is exceeding a desired maximum temperature. In this example, data processor  120  may develop and send heating system parameter set  135  to heat generating system  130  that direct heat generating system  130  to lessen the intensity and/or duration of heat output. Heat generating system  130 , upon receiving the heating system parameter set  135 , modifies its heat energy output as directed. It will be appreciated that the term “intensity”, as used herein, may refer to the relative instantaneous output, or the term may refer to the measure of the fraction of a cycle that heat generating system  130  is outputting energy, such as a duty cycle. 
     In at least one embodiment, energy delivery system  100  continuously or periodically measures a temperature distribution and/or a tissue damage distribution of a select portion of target  140  and processes the measurements (data  105 ) for feedback used in controlling the behavior of heat generating system  130  on a real-time, or near real-time basis. It will be appreciated that the periodic measurement of the select portion of target  140  may include measurements taken on a fixed frequency, intermittently, randomly, as directed by a user, and the like. It will also be appreciated that the term “real-time”, as used herein, refers to the ability of energy delivery system  100  to measure and process data obtained from a select portion of target  140  and control the output of heat generating system  130  in a manner fast enough so that undesired results occurring to target  140  are minimized before being detected. For example, if temperature detection system  110  and data processor  120  capture and process data every ten seconds for real time operation, the heat output of heat generating system  130  should be limited such that undesired results, such as healthy tissue damage, tissue charring, and the like, are unlikely to occur between the ten second data capturing and processing cycle. Similarly, in at least one embodiment, the term “near real time” refers to the ability of energy delivery system  100  to affect control before significant undesired results occur in target  140 . 
     The degree to which energy delivery system  100  approximates real-time feedback may be dependent on one or more of the following: the speed in which temperature detection system  110  is capable of measuring with a desired accuracy a portion of target  140 ; the size, shape, and/or resolution of the measured portion of target  140 ; the data transfer rate between temperature detection system  110  and data processor  120 ; the speed at which data processor  120  is capable of processing data  105  received from temperature detection system  110 , producing control parameters for heat generating system  130 , and producing images and information on GUI  250  for the user; the speed at which heat generating system  130  is capable of responding and producing the desired outcome of the heating system parameter set  135  transmitted from data processor  120 ; and the data transfer rate between data processor  120  and heat generating device  130 . The desired resolution of the images representative of characteristics of the measured portion of target  140  may also affect the real-time capacity of energy delivery system  100 . For example, an image with a higher signal-to-noise ratio (SNR) may take longer to measure and/or process than an image with a lower SNR. The desired SNR may be defined by the user, the limitations of the hardware and/or software of energy delivery system  100 , etc. 
     Referring next to FIG. 2, data processor  120  is illustrated in greater detail, according to at least one embodiment of the present invention. Reference numerals in FIG. 2 that are common to reference numerals in FIG. 1 indicate like, similar or identical features or elements. Data processor  120  includes thermal detection system interface  200 , data route  202 , image processor  210 , heating device control processor  220 , heating device system interface  230 , control route  232 , and connections to graphical user interface (GUI)  250  implemented using display  255 . In one embodiment, data processor  120  further includes data server  205  and/or log file  260 . It will be appreciated that one or more elements of data processor  120  may be physically or logically located on one or more processing devices. It will also be appreciated that one or more elements of data processor  120  may be physically or logically located on temperature detection system  110  or heat generating system  130  without departing from the spirit or scope of the present invention. In addition, one or more of the elements illustrated in FIG. 2 can be implemented in software or firmware. 
     It should be understood that the specific steps indicated in the methods herein, and/or the functions of specific systems herein, may generally be implemented in hardware and/or software. For example, a specific step or function may be performed using software and/or firmware executed on one or more processing systems. 
     Typically, a system for processing of data associated with temperature measurements will include generic or specific processors. The processors can be based on a single processing device or a plurality of processing devices. Such a processing device may be a microprocessor, a microcontroller, a digital processor, a microcomputer, a portion of a central processing unit, a state machine, logic circuitry, and/or any device that manipulates the data. 
     The manipulation of the data is generally based upon operational instructions represented in a memory. The memory may be a single memory device or a plurality of memory devices. Such a memory device (machine readable media) may be a read only memory, a random access memory, a floppy disk memory, magnetic tape memory, erasable memory, a portion of a system memory, any other device that stores operational instructions in a digital format. Note that when the processor implements one or more of its functions, it may do so where the memory storing in the corresponding operational instructions is embedded within the circuitry comprising a state machine and/or other logic circuitry. 
     In at least one embodiment of the present invention, data processor  120  continuously or periodically receives data  105  collected by temperature detection system  110  as it becomes available-and processes data  105  to provide real-time feedback control of heat generating system  130 . In one embodiment, data  105  is transmitted from temperature detection system  110  to data server  205  via temperature detection system interface  200  and data route  202 . When temperature detection system  110  is local to data processor  120 , data route  202  may include a serial connection, a parallel connection, an infrared connection, a wireless connection (such as a radio frequency or microwave connection), a point-to-point connection, and the like. In implementations where temperature detection system  110  is remote to data processor  120 , data route  202  may include an Ethernet connection, a modem connection, a digital subscriber line connection, a satellite connection, etc. Accordingly, temperature detection system interface  200  includes an input/output interface compatible with data route  202 . For example, if data route  202  is an Ethernet network, temperature detection system interface  200  could include an Ethernet card. In at least one embodiment, temperature detection system interface  200  includes a point-to-point interface, such as a RS-232 interface, an IEEE-488 interface, a digital I/O interface, and the like. 
     It will be understood that data  105  is to be transmitted, relayed, or communicated across data route  202  by means or protocols appropriate to the particular data route  202  and interface  200  employed in a particular embodiment. For example, when an Ethernet network is used, it is likely that data  105  will be transmitted over data route  202  using a Transmission Control Protocol (TCP) over an Internet Protocol (IP), or, more commonly, TCP/IP. These standardized data communication protocols are commonly in use on Ethernet networks, and their details are at least partially specified in Defense Advanced Research Projects Agency (DARPA) documents RFC793 and RFC791, respectively. It will also be appreciated that additional communications protocols may be used instead of or on top of the TCP/IP layers. For example, the UNIX network file sharing (NFS) protocol, the details of which are at least partially specified in Network Working Group document RFC 1094, may be used to transfer data  105  across data route  202  when also using an Ethernet network and TCP/IP protocol. The File Transfer Protocol (FTP), the details of which are at least partially specified in Network Working Group document RFC959, may also be used with data  105  transmitted over data route  202 . The NetBIOS protocol, the details of which are at least partially specified in documents RFC1001 and RFC1002 and IEEE802.2 can similarly be used, as can its relatives including the server message block (SMB) protocol common to Microsoft Windows networks. Similarly, the Apple Talk or Apple Filing Protocol File Sharing (afpfs) protocols may be used to transfer data  105  over data route  202 . Besides TCP/IP, other networking protocols may be used including, for example, Internetworking Packet Exchange/Sequential Packet Exchange (IPX/SPX). It is meant to be recognized that the foregoing in no way limit the implementation with which data route may be realized, and other realizations which are known to those of ordinary skill in the art are also within the scope of the invention. For example “wireless” networking protocols such as those specified in IEEE 802.11a and/or 802.11b may be used. 
     In one embodiment, data  105  is stored on temperature detection system  110  until retrieved by data processor  120 . Data processor  120  may either poll temperature detection system  110  for updated data  105 , or temperature detection system  110  may signal data processor  120  that updated data  105  is ready for retrieval. One method of polling is to use the creation of a file as a signal. For example, temperature detection system  110  can use a UNIX file system to store data  105  in a file data_file.dat. When temperature detection system  110  has completed the measurement of target  140  and stored all measured data  105  for a given cycle in data_file.dat, temperature detection system  110  creates a file data.new. Data processor  120  periodically checks for the existence of the file data.new. After temperature detection system  110  creates the file data.new and it is detected by data processor  120 , data processor  120  may then download the file data_file.dat. After data processor  120  has downloaded data_file.dat, data processor  120  erases the file data.new, and temperature detection system  110  may then start storing data for the next control cycle in data_file.dat. 
     An alternate method of polling is to use a file system and semaphores for mutual exclusion. For example, temperature detection system  110  and data processor  120  may make use of a UNIX file system to store data  105  in a file temp_data. 001 , and use a semaphore associated with this file. When temperature detection system  110  is updating data  105 , it places a mutual exclusion lock using the semaphore on the temp_data. 001  file and begins to store updated data  105  in the temp_data. 001  file. Once temperature detection system  110  is finished storing data  105  in the temp_data. 001  file, it releases, or unlocks, its mutual exclusion lock on temp_data. 001 . Data processor  120  continuously attempts to place a mutual exclusion lock using the semaphore associated with the temp_data. 001  file. When temperature detection system  110  releases its mutual exclusion lock, data processor  120  is then capable of placing its own lock on temp_data. 001  and begins to download the data in the temp_data. 001 . When data processor  120  is finished downloading data  105 , it releases its lock on the temp_data. 001  file, and temperature detection system  110  may begin to store newly updated data  105  in temp_data. 001  for the next cycle, and so on. It will be appreciated that other methods of retrieving data  105  from temperature detection system  110  may be used, such as interprocess communication (IPC). IPC generally refers to the data exchange between one process and another, either within the same processor or over a network. EPC is often accomplished using a transmission protocol that guarantees a response to a request. Examples of IPC include UNIX sockets, OS/2 named pipes, etc. IPC often utilizes many types of system calls. For example, one or more Unix sockets could be opened up between temperature detection system  110  and data processor  120 , and data  105  could be transmitted over data route  202  according to methods known to those skilled in the art. It will be appreciated that data  105  may be transferred all at once when temperature detection system  110  is finished capturing all of data  105  for one cycle, or data  105  may be continuously transmitted as it is captured. 
     In one embodiment, data  105  is transferred from temperature detection system  110  to central data server  270  accessible by at least one temperature detection system  110  and at least one data processor  120 . Data processor  120  may then retrieve data  105  when data processor  120  is ready for it. Use of central data server  270  has the benefit of allowing more than one data processor  120  to access data  105  from temperature detection system  110 , and more than one temperature detection system  110  may provide data  105  to data processor  120 . For example, many hospitals use a digital imaging and communications in medicine (DICOM) protocol server (central data server  270 ) to centrally store images captured by medical imaging devices (temperature detecting system  110 ) and make those images accessible to a wide variety of users. The medical imaging devices may be locally or remotely connected to the DICOM protocol server using a network interface, such as an Ethernet interface or a point-to-point interface. In one embodiment, one or more elements of data processor  120  may also function as central data server  270 . 
     In one embodiment, image processor  210  retrieves data  105  from data server  205  and processes data  105  to develop a plurality of images for display on GUI  250  implemented using display  255  and for further processing to construct heat generating system control parameters or characteristics that can be used to determine actual control parameters. In one embodiment, image processor  210  constructs one or more of magnitude image  235 , temperature image  240 , and damage image  245  for each cycle of feedback in energy delivery system  100 . Magnitude image  235 , in at least one embodiment, includes an image representative of the physical structure of the measured portion of target  140 . Temperature image  240  includes an image representative of the temperature mapping of the measured portion of target  140 . Damage image  245  includes an image representative of an estimate of the location of biological tissue (target  140 ) that is dead or dying. Magnitude image  235 , temperature image  240 , and damage image  245  are formatted and displayed on display  255  using GUI  250 . GUI  250  is discussed in further detail with reference to FIG.  4 . In one embodiment, images  235 ,  240 , and/or  245  are representative of a three-dimensional distribution of the structure, temperature, and/or damage. It will be appreciated that images  235 ,  240 , and/or  245  may be black and white, grayscale, or color images. For example, different colors could represent different temperature ranges. In one embodiment, a plurality of images  235 ,  240 , and/or  245  of different selection portions of target  140  may be displayed. The plurality of images  235 ,  240 , and/or  245  may be displayed on a periodically alternating basis, or on demand as directed by a user. 
     As previously discussed, image processor  210  processes data  105  and/or images  235 ,  240 , and  245  to produce target data  215  for heating device control processor  220 . Target data  215  may include a temperature distribution, a damage distribution, structure information, and the like. Heating device control processor  220  uses target data  215  and control strategy  127  to produce heating system parameter set  135  for use in controlling heat generating system  130 . Control strategy  127  uses one or more rule sets  262  and strategy parameter sets  264  to determine the desired operation of heat generating system  130 . Rule set  262  includes an algorithm to determine the desired action of heat generating system  130  using target data  215  and at least one strategy parameter set  264 . Strategy parameter set  264  may include parameters such as temperature membership values for lexical temperature values, damage membership values for lexical damage values, heat generating system  130  intensity levels, and the like. For example, one rule of rule set  262  may state that the heat source of heat generating system  130  is to be shut off if a maximum temperature (lexically defined by strategy parameter set  264  as “too hot”) of a selected portion of target  140  is reached. In this example, analysis of target data  215  by heating device control processor  220  determines that the temperature of the portion of target  140  has exceeded the maximum temperature (“too hot”), so heating device control processor  220  produces, using control strategy  127 , heating system parameter set  135  that will cause heat generating system  130  to shut off the heat source. In at least one embodiment, control strategy  127  includes fuzzy logic control and is discussed in greater detail with reference to FIGS. 5 and 6. 
     In at least one embodiment, after heating system parameter set  135  is produced by heating device control processor  220 , it is transmitted to heat generating system  130  via heat generating system interface  230  and control route  232 . When heat generating system  130  is local to data processor  120 , control route  232  may include a serial connection, a parallel connection, an infrared connection, a wireless connection, a direct connection, such as a data bus or shared memory, and the like. In implementations where heat generating system  130  is remote to data processor  120 , control route  232  may include an Ethernet connection, a modem connection, a digital subscriber line connection, a satellite connection, etc. Accordingly, heat generating system interface  230  includes an input/output interface compatible with control route  232 . For example, if control route  232  is a serial cable, heat generating device interface  230  may include a serial input/output (I/O) card. In at least one embodiment, heat generating system interface  230  includes a point-to-point interface, such as a RS-232 interface, an IEEE-488 interface, a digital I/O interface, and the like. 
     Referring next to FIG. 3, heat generating system  130  is illustrated in greater detail according to at least one embodiment of the present invention. Reference numerals in FIG. 3 that are common to reference numerals in FIGS. 1 and 2 indicate like, similar or identical features or elements. Heat generating system  130  includes input/output (I/O) interface  300 , control unit  310 , heat generator  320 , and applicator  330 . In at least one embodiment, heat generating system  130  receives heating system parameter set  135  (FIG. 2) from data processor  120  via I/O interface  300  and control route  232 . 
     Control unit  310  processes heating system parameter set  135  transmitted from data processor  120  to control heat generator  320 . For example, if heat generator  320  is a laser device, and heating system parameter set  135  indicates a specified laser intensity, duration, and/or duty cycle, control unit  310  produces the proper voltage and/or current for the proper duration and/or duty cycle to the laser device (heat generator  320 ) to cause the laser to have the specified intensity, duration, and/or duty cycle. In one embodiment, control unit  310  can monitor the operation of one or more elements of heat generating system  130  and transmits their statuses to data processor  120  via I/O interface  300  and control route  232 . Data processor  120  may utilize the status of one or more elements of heat generating system  130  to modify control strategy  127  (FIG.  1 ). 
     Heat generator  320  is capable of producing heat or energy to be transformed into heat. In at least one embodiment, heat generator  320  is further capable of producing a varied intensity, duration, and/or duty cycle of energy based on input from control unit  310 . Heat generator  320  can include, but is not limited to, a laser, a microwave device, a resistive heating element, a focused ultrasound device, an incoherent light device, a radio frequency (RF) probe, or other suitable application device. In an alternate embodiment, heat generator  320  includes a plurality of homogeneous or heterogeneous heat generating devices. For example, a laser device may be used in concert with a microwave device to deliver heat to target  140  (FIG.  1 ). The heat or energy produced by heat generator  320  is transmitted to target  140  via at least one applicator  330 . Applicator  330  can include one or more optical fibers, one or more antennae, one or more transducers, and the like. For example, heat generator  320  may be implemented using a laser, and applicator  330  may be implemented as an optical fiber to deliver the energy produced by the laser into target  140 . The optical fiber applicator may include one or more features known to those skilled in the art to produce desireable heating effects or patterns, including, but not limited to, an optically diffusive tip, or a specially shaped tip. In at least one embodiment, one or more applicators  330  may be used to create a spatial radiation pattern of heat energy. For example, multiple ultrasound transducers (heat generators  320  and applicators  330 ) may be implemented using phase delays to create a specific energy radiation pattern. It will be appreciated that in some implementations of the present invention, applicator  330  and heat generator  320  may be integrated into a single element. For example, a resistive wire placed in target  140  may act as both heat generator  320  and applicator  330  when a voltage potential is placed across the resistive wire. 
     Referring next to FIG. 4, GUI  250  is illustrated in greater detail, according to at least one embodiment of the present invention. Reference numerals in FIG. 4 that are common to reference numerals in FIGS. 1-3 indicate like, similar or identical features or elements. In at least one embodiment, GUI  250  includes magnitude image  235 , temperature image  240 , damage image  245 , image adjustment display  410 , temperature history display  435 , image selector  445 , heating device status display  455 , and utility panel display  465 . It will be appreciated GUI  250  may further include one or more additional interactive displays without departing from the spirit and the scope of the present invention. 
     As discussed previously, magnitude image  235 , temperature image  240 , and damage image  245  can be derived from measurements of target  140  taken by temperature detection system  110  and transmitted to data processor  120  in the form of data  105  (FIG.  1 ). Magnitude image  235  displays an image representative of structure  401  of a selected portion of target  140  (FIG. 1) and temperature image  240  displays an image representative of temperature distribution  402  of a selected portion of target  140 . In cases where target  140  is biological tissue, damage image  245  displays, in one embodiment, an image representative of cell damage region  400 , which may be displayed alone or superimposed on either an image representative of temperature distribution  402  or an image representative of structure  401 . In one embodiment, cell damage region  400  represents the portions of a selected portion of target  140  where cell death has occurred or is likely to occur as a result of the heat energy applied. Images  235 ,  240 , and  245  may be a two-dimensional view representative of a selected section of target  140 , such as a sagittal, coronal, axial section, or other arbitrary plane, or may be a three-dimensional view representative of a selected volume of target  140 . 
     Image adjustment display  410  may be used to modify the display of images  235 ,  240 , and/or  245  by GUI  250 . Image adjustment display  410  includes contrast adjustment  415 , brightness adjustment  420 , color adjustment  425 , and zoom adjustment  430 . Contrast adjustment  415  adjusts the contrast of images  235 ,  240 , and  245 . Brightness adjustment  420  adjusts the brightness of images  235 ,  240 , and  245 . Color adjustment  245  adjusts the color properties when images  235 ,  240 , and  245  are in color. Zoom adjustment  430  adjusts the magnification factor of images  235 ,  240 , and  245  displayed. Adjustments  410 ,  415 ,  420 ,  425 , and  430  may be modified through GUI  250  using a sliding knob, a turning dial, a value input field, or other methods known to those skilled in the art. It will be appreciated that additional image adjustments may be implemented without departing from the spirit and the scope of the present invention. For example, a user may strike the up and down arrow keys on a keyboard attached to data processor  120  to increase or decrease the zoom value of zoom adjustment  430 . 
     In at least one embodiment, a user of energy delivery system  100  (FIG. 1) uses image selector  445  to select a portion of target  140  for monitoring and control. Image selector  445  includes, in one embodiment, structural image  235 , but can also include temperature image  240  or damage image  245 . Such image may be constructed from one set of MR data or from mathematical manipulation of one or more sets of MR data. The image may also comprise representation of one or more sets of MR data acquired previously. The user may select one or more image interest selections  450  for monitoring by energy delivery system  100  using an input device, such as a mouse, a touchpad, a touchscreen, a trackball, and the like. Image interest selections  450  may include individual points, areas, planes, or contours in implementations where the image (magnitude image  235 , temperature image  240 , or damage image  245 ) is displayed in two dimensions, or points, areas, contours, planes, or volumes in implementations where the image is displayed in three dimensions. In one embodiment, image interest selections  450  are associated with one or more membership sets, such as cold, medium, hot, and too hot temperature sets, or healthy, dying, and dead cell sets, and the like. Image interest selections  450  are input by GUI  250  to data processor  120  as elements of a strategy parameter set for use in controlling the operation of heat generating system  130 . Membership sets and strategy parameter sets are discussed in greater detail with respect to FIG.  5 . 
     As described previously, the user may use continuously or periodically updated temperature image  240 , damage image  245 , and magnitude image  235  to select image interest selections  450  in image selector  445  of GUI  250  (FIG.  4 ). In one embodiment, the image displayed in image selector  445  may include temperature image  240 , damage image  245 , magnitude image  235 , or a combination thereof. For example, a combination image of temperature image  240  and damage image  245  may be displayed in image selector  445 . In this example, the temperature distribution could be represented by pixels with a color spectrum between blue and red, and cells considered dead or dying could be represented by pixels with a white color. If image selector display is a two dimensional image, the user could select, using an input device such as a trackball, one or more points or contours (image interest selections  450 ) for data processor  120  to monitor and use in control strategy  127  (FIG.  2 ). These points could be associated with a temperature membership or cell damage membership, as discussed in greater detail with reference to FIGS. 5 and 6. Additionally, in at least one embodiment, multiple images representative of the structure, temperature distribution and/or damage distribution of different areas, planes, or volumes of a plurality of selected portions of target  140  may be displayed. The different areas, planes, or volumes of the selected portions may be parallel or perpendicular to each other, or they may be oriented at any angle to one another. One or more of the plurality of images may be displayed simultaneously, or groups of one or more may be displayed sequentially. The selection of the desired areas, planes, and/or volumes and display of the plurality of images representative of the areas, planes, and/or volumes may occur on a periodic basis or may be initiated and directed by the user. The selection and display of the images may also be determined by data processor  120  or temperature detection system  110  based on characteristics of the selection portion of target  140 , such as the locations of the hottest temperature or the area with the greatest damage. 
     In at least one embodiment, the user-selected image interest selections  450  can be used to provide feedback to temperature detection system  110 . For example, a user may select one or more of the hottest points and have temperature detection system  110  monitor the temperature of these points more frequently than the rest. In one embodiment, either temperature detection system  110  or data processor  120  is capable of automatically adjusting the monitoring of a selected portion of target  140  based on image interest selections  450 . For example, suppose a user selects an area of target  140  to be monitored and data processor  120  determines that the upper half of the selected area has no appreciable temperature change, or the temperature distribution of the upper half is well within the acceptable temperature limits. In this example, it is determined that the bottom edge of the selected area is approaching a user-defined critical temperature. In this case, data processor  120  may instruct temperature detection system  110  to alter the area being monitored, and place the bottom edge of the previously monitored area in the center of the newly monitored area. This action would allow the user and data processor  120  to monitor the critical areas of the selected portion of target  140  by readjusting the image to focus on areas of interest. Likewise, in addition to shifting the area, plane, or volume of interest, data processor  120  may instruct temperature system  110  to change to an entirely different area, plane, or volume of interest in order to more accurately monitor critical features. 
     Temperature history display  435  includes one or more temperature history plots  440  associated with the one or more image interest selections  450 . Temperature history plots  440  can be plots of the temperature of the associated image interest selection  450  as a function of time. It will be appreciated that one or more temperature history plots  440  may be illustrated on a single plot display with a common axis, on a separate plot display for each temperature history plot  440 , or a combination thereof. In cases where image interest selections  450  are not single points, such as a plane or a volume, it will be appreciated that temperature history plot  440  may consist of an average temperature history, a temperature history of a single hottest point, etc. 
     In at least one embodiment, heating device status display  455  is capable of displaying information regarding the status of heat generating system  130 . In one embodiment, heating device status display  455  includes intensity indicator  460 . Intensity indicator  460  displays the intensity of heat output of heat generating system  130 . The intensity may be displayed as a relative percent, such as 0 to 100% of heating capacity, as an actual measurement, such as 0 to 5 Watts, as a graph representative of the duty cycle, or as another physical quantity as may be appropriate to the heat generation method employed. Heating device status display  455  may also include emergency shut off button  462  capable of turning off the energy output of heat generating system  130 . For example, a user may determine that a portion of target  140  has exceeded a desired maximum temperature. The user may then activate emergency shutoff button  462  to prevent or stop any damage to target  140 . It will be appreciated that heating device status display  455  may also display additional information, such as time in use, total power output, and the like. In one embodiment, utility panel display  465  is capable of executing utility programs and processes using one or more buttons  470 . Utility programs and processes can include startup and shutdown processes, add/remove display processes, data saving processes, GUI setup processes, and the like. 
     Referring now to FIG. 5, fuzzy logic membership tuning interface  500  is illustrated according to at least one embodiment of the present invention. Reference numerals in FIG. 5 that are common to reference numerals in FIGS. 1-4 indicate like, similar or identical features or elements. Fuzzy logic membership tuning interface  500 , herein referred to as membership tuning interface  500 , includes temperature membership group  510 , heating device power membership group  520 , duration membership group  530 , temperature display  540 , power display  550 , duration display  560 , quit button  595 , load button  585 , save button  590 , and update button  575 . In one embodiment, tuning interface  500  is accessed by when a user selects one of buttons  470  in utility panel display  465  (FIG.  4 ). In implementations where energy delivery system  100  (FIG. 1) is used to produce lesions in biological tissue (target  140 ), membership tuning interface  500  further includes damage membership group  570  and damage display  580 . It will be appreciated that membership tuning interface  500  may include other membership groups with out departing from the spirit and the scope of the present invention. 
     As discussed previously, heating device control processor  220  (FIG. 2) uses control strategy  127 , one or more rule sets  262 , and one or more strategy parameter sets  264  to control the energy output of heat generating system  130 . In one embodiment, a user employs membership tuning interface  500  to input user-preferred parameters into one or more strategy parameter sets  262 . In one embodiment, a user may modify four types of memberships: temperature, tissue damage, heating device power, and heating device output duration. Temperature membership group  510  is capable of setting membership values for cool temperature membership  511 , warm membership  512 , hot membership  513 , and too hot membership  514 . Heating device power membership group  520  is capable of setting membership values for low membership  521 , medium membership  522 , and high membership  523 . Duration membership group  530  is capable of setting membership values for short membership  531 , medium membership  532 , and long membership  533 . Damage membership group  570  is capable of setting membership values for dead membership group  571 , dying membership group  572 , and healthy membership group  573 . The user may modify the values of each membership by use of a sliding knob, a turning dial, a numerical input box, and the like. 
     Temperature display  540 , damage display  580 , power display  550 , and duration display  560  are capable of visually displaying the relationships between their associated membership groups (temperature membership group  510 , damage membership group  570 , heating device power membership group  520 , and duration membership group  530 , respectively). As a user modifies the values for a given membership, the associated membership display dynamically updates to reflect the new membership group composition. For example, an increase in the value of cool membership  511  updates the graph representing cool membership  511  in temperature graph  540 . It will be appreciated that various types of charts and graphs may be used to display membership groups  510 ,  520 ,  530 , and  570 , such as line graphs, bar graphs, pie charts, etc. Additionally, in one embodiment, temperature display  540 , and the associated values for memberships  510 ,  520 ,  530 , and  570  may be adjusted by direct manipulation of temperature display  540  and/or damage display  580  by the user. For example, a user could use a mouse to click on one of the graph lines for cool membership  511  and drag and position the graph line into the desired location, and thereby dynamically altering the values and distribution of cool membership  511 . It will be appreciated that a specific membership value and distribution may be modified separately from the other associated memberships, or memberships may be adjusted in relation to one another. 
     When a user is satisfied with the results of modification of the values of the memberships, the user may save, load, and/or update these values. Save button  590  is capable of saving the displayed membership values in a file, database, and the like. For example, a user may set up membership values for a specific tissue (target  140 ) type and select save button  590  to save the setup in a file. Load button  585  is capable, when selected, of loading and displaying membership values previously saved in a file or database. Update button  575  is capable of dynamically updating membership values that are in strategy parameter set  262  that is currently being used by heating device control processor  220 . By selecting update button  575 , the user dynamically modifies the parameters used by data processor  120  to control heat generating system  130 . When selected by the user, quit button  595  terminates membership tuning interface  500  without saving any changes to membership values made since the save button  590  was last selected. In at least one embodiment, membership tuning interface  500  is capable of evaluating strategy parameter set  264  before updating for safety reasons or to prevent unintended results. 
     Referring now to FIG. 6, a fuzzy logic rule set tuning interface is illustrated according to one embodiment of the present invention. Reference numerals in FIG. 6 that are common to reference numerals in FIGS. 1-5 indicate like, similar or identical features or elements. Fuzzy logic rule set tuning interface  600 , herein referred to as rule set tuning interface  600  includes one or more rules  610 , one or more rule activation boxes  650 , load button  675 , save button  680 , update button  690 , and quit button  685 . Rule  610  includes at least one control variable  612  associated with the temperature of a given location of target  140  and/or the cell damage of a given location of a biological tissue (target  140 ), one or more control membership fields  620 , one or more power membership fields  630 , and one or more duration membership fields  640 . Rule  610  may further include one or more fuzzy logic operators  615 . Rule activation box  650  includes an ON box and an OFF box. 
     In one embodiment of the present invention, rule set tuning interface  600  allows a user to construct and/or modify a fuzzy logic control strategy (an embodiment of control strategy  127 ), which in turn governs the feedback control process of energy delivery system  100  (FIG.  1 ). The user is capable of building one or more rules  610  combined into rule set  262  that govern the behavior of heat generating system  130  (FIG. 1) using if-then statements and fuzzy logic operators and variables. Using fuzzy logic control, the truthfulness of each variable of each premise (the “if” statement) is evaluated based on its membership to specific membership groups. The extent to which the conclusion (the “then” statement) is performed is based on the evaluated truthfulness of the premise. To construct each of at least one rule  610 , the user selects control variable  612  corresponding to an image interest selection  450  (FIG. 4) selected using image selector  445  displayed on GUI  250 . If more than one control variable  612  is selected for rule  610 , the user also selects an operator for fuzzy logic operator  615 . Fuzzy logic operators represented in fuzzy logic operator  615  may include, but are not limited to, AND, OR, NAND (NOT AND), NOR (NOT OR), or other fuzzy logic operators. Additionally, the user selects a lexical value for each control membership field  620  corresponding to the one or more control variables  612 . In one embodiment, the lexical values for control membership field  620  include temperature lexical values of cool, warm, hot, and too hot. Lexical values for control membership field  620  may also include damage lexical values, such as healthy, dying, and dead. The user also selects a lexical value for power membership field  630  and duration membership field  640 . In one embodiment, the lexical values for power membership field  630  include off, low, medium, high, and same, and the lexical values for duration membership field  640  include short, medium, long, and same. In one embodiment, the numerical equivalents of the lexical values of membership fields  620 ,  630 , and  640  are determined by user input to tuning interface  600 . It will be appreciated that the numerical equivalents may also be hard-coded into GUI  250 , loaded from a database or a file, and the like. 
     In an alternate embodiment, a more traditional control methodology is used. For example, a software-based algorithm may be used for closed-loop control of the heat output of energy delivery system  100  (FIG.  1 ). Alternately, the control method may be hardwired into the hardware of data processor  120 . The user may input user-defined parameters for these types of control methodologies in a manner similar to the one presented with reference to FIGS. 5 and 6. It will be appreciated that other control methods may be used without departing from the spirit and scope of the present invention. 
     In one embodiment, rule  610  implements fuzzy logic to define a response to a situation defined by control variables  612 , fuzzy logic operator  615 , control membership field  620 , power membership field  630 , and duration membership field  640 . Fuzzy logic, as opposed to Boolean logic with absolute truth and absolute false, uses a range of values to represent the truthfulness or falseness of a variable. As a result, the truthfulness of a given statement using fuzzy logic can be represented as a probability. Using an if-then statement, rule  610  determines whether a statement of one or more temperature variables  612  is true using logical operator  612  to evaluate the degree of truthfulness. The values for corresponding power membership field  630  and duration membership field  640  are set according to the degree of truthfulness of the “if” statement of a fuzzy logic operation (logical operator  612 ) between two or more fuzzy logic variables (control membership fields  620 ). The power membership field  630  and duration membership field  640  values are implemented by heating device control processor  220  (FIG. 2) to create heating system parameter set  135  (FIG.  1 ). After heating system parameter set  135  is created, it is transmitted to heat generating system  130 . Heat generating system  130  receives heating system parameter set  135  and modifies its heat output to match the parameters set by power membership field  630  and duration membership field  640 . 
     A user also has the capability of shutting off a particular rule  610  using rule activation box  650 . For example, if a user determines that one or more rules  610  are interfering with the correct operation of energy delivery system  100  (FIG.  1 ), the user may dynamically disable the interfering rules  610  by selecting the associated OFF box. Similarly, if the user wishes to enable a disabled rule  610 , the user may select ON box to dynamically enable the associated rule  610 . 
     In at least one embodiment of the present invention, rule set  262  further includes one or more hard rules  695 . Hard rules  695  include rules used to limit the operating boundaries of heat generating system  130  for safety and/or device limitation reasons. For example, heat generating system  130  may include a diode laser that may have a maximum power setting that exceeds the maximum safe level. In this example, hard rules  695  would include rules that limit the power output of the laser to safe levels only. Hard rules  695 , in one embodiment, supercede all user-defined rules  610 , and normal users are not capable of modifying or disabling any hard rules  695 . In one embodiment, rule set tuning interface  600  is capable of determining if a given rule  610  interferes with one or more hard rules  695 . If a rule  610  does interfere, rule set tuning interface  600  is capable of disabling the interfering rule  610  by selecting the OFF box of associated rule activation box  650 . It will be appreciated that hard rules  695  may be loaded from a file or database, input by an authorized administrator, etc. In an alternate embodiment, hard rules  695  are hardcoded into the software of data processor  120  or hardwired into the hardware of data processor  120 . In this case, hard rules  695  may have been coded or implemented in hardware by the user or by the manufacturer, or a combination therein. Alternately, hard rules  695  may be implemented using data from image interest selections  450  (FIG.  4 ). For example, a user could pick a point at the source of the heat in target  140  and a point in an outlying area. In this case, the user could define a hard rule (hard rule  695 ) that prohibits the temperature of the point at the heat source from exceeding a user-defined temperature and similarly may set a maximum temperature for the outlying point. 
     In addition to creating rule sets  262  (FIG.  2 ), rule set tuning interface  600  is capable of saving created rule sets  262 , or loading preexisting rule sets  262  from a file or database. Rule sets  262  may be saved by selecting save button  680 , which is capable of saving rule sets  262  as a file or in a database. Preexisting rule sets  262  may be loaded by a user from a database or file by selecting load button  675 . Update button  690  is capable of dynamically updating rule set  262  currently used by control strategy  127  to govern the operation of heat generating system  130  (FIG.  1 ). In the event that a user desires to terminate rule set tuning interface  600  without saving any changes to a given rule set  262 , the user can select quit button  685 . Additionally, rules  610  for rule set  262  used by control strategy  127  and heating device control processor  220  (FIG. 2) may dynamically be updated during operation by using update button  690 . 
     Referring next to FIG. 7, a method for utilizing real-time, or near real-time, feedback to control an energy delivery system is discussed according to one embodiment of the present invention. Reference numerals in FIG. 7 that are common to reference numerals in FIGS. 1-6 indicate like, similar or identical features or elements. In step  700 , temperature detection system  110  (FIG. 1) obtains data  105  from measurements conducted on target  140  for use as initial reference data for data processor  120 . This initial reference data may be utilized to develop an initial image representing magnitude image  235 , temperature image  240 , and damage image  245  (FIG.  2 ). The initial reference data may also be used to develop an initial reference temperature distribution in implementations where temperature detection system  110  is only capable of detecting temperature differences, rather than absolute temperature. 
     In step  705 , initial data  105  is transmitted from temperature detection system  110  to data processor  120  (FIG.  2 ). Data  105  may be stored in a database on temperature detection system  110 , transmitted immediately after the data capture cycle is completed, transmitted to central data server  270 , or transmitted continuously as data  105  is captured. In step  706 , data  105  received from temperature detection system  110  is processed by data processor  120 . Data  105  is used by image processor  210  (FIG. 2) to develop magnitude image  235 , temperature image  240 , and damage image  245  for display by GUI  250 . In addition, data processor  120  uses data  105  to initiate control of the heat output of heat generating system  130 , as described previously. In step  707 , data  105  is used by GUI  250  (FIG. 2) to display the initial images for magnitude image  235 , temperature image  240 , and damage image  245 . As no heat has been applied to target  140  when initial data  105  was measured, damage image  245  and temperature image  240  have no temperature or damage related information to display. Similarly, temperature history  435  (FIG. 4) does not have any information to display yet. A user may use the information presented in the images to determine and input user-defined parameters. 
     One or more image interest selections  450  (FIG.  4 ), one or more rule sets  262  (FIG. 2) and strategy parameter sets  264  used to develop control strategy  127  (FIG. 1) are input to data processor  120  via GUI  250  (FIG. 2) by a user in step  710 . As discussed previously, the user may select one or more points, contours, areas, planes, or volumes of interest for monitoring using an input device in image selector  445 . The user may select the one or more image interest selections  450  using an input device, such as a mouse, touch screen, trackball, etc. Alternatively, image interest selections may be predetermined using data from a file or database. 
     In at least one embodiment, control strategy  127  is implemented using membership tuning interface  500  (FIG. 5) and rule set tuning interface  600  (FIG. 6) to set the values of strategy parameter set  264  and one or more rule sets  262  (FIG.  2 ). The user may define strategy parameter set  264 , in at least one embodiment, by entering or modifying values for memberships groups  510 ,  520 ,  530 , and  570  (FIG.  5 ). The inputted values may be determined using past experience as a guide, a standardized table of values, and/or by loading a previously constructed strategy parameter set  264  from a file or a database as described previously. Similarly, one or more rule sets  262  may be input by the user based on experience, tables, or by loading previously constructed rules sets  262  from a file or database. 
     In step  720 , data processor  120  uses control strategy  127  developed in step  710  and information extracted from data  105  obtained by temperature detection system  110  to construct heating system parameter set  135  (FIG.  1 ). Heating system parameter set  135  is used to govern the behavior of heat generating system  130 . Heating system parameter set  135  is generated by heating device control processor  220  by using temperature data extracted from data  105 , and/or cell damage data calculated from data  105  if target  140  (FIG. 1) includes biological tissue. For example, one rule set  610  (FIG. 6) states that heat generating system  130  is to be shut off (power membership field  630  value set to off) if the temperature of a given image interest selection  450  (control variable  612 ) is too hot (control membership field  620  set to too hot). In this example, heating device control processor  220  would construct heating system parameter set  135  in a way that would shut of heat generating system  130  when it received and enacted heating system parameter set  135 . 
     In step  722 , heating system parameter set  135  is transmitted to heat generating system  130 . In one embodiment, heat generating system  130  is local to data processor  120 . In this case, heating system parameter set  135  may be transmitted from data processor  120  to heat generating system  130  using a direct connection, such as shared memory, a serial connection, a parallel connection, universal serial bus connection, and the like. In another embodiment, heat generating system  130  is remotely connected to data processor  120 . In this implementation, data processor  120  and heat generating system  130  may be connected by a microwave connection, a satellite link, by Ethernet, by telephone modem, and the like. In either embodiment, heating system parameter set  135  is received by heat generating system  130  and processed to produce the desired heat output. In one embodiment, heat generating system  130  is capable of transmitting an error signal to data processor  120  if heat generating system  130  is unable to perform as directed by heating system parameter set  135 . Data processor  120  may then take the error signal into account when constructing subsequent heating system parameter set  135  for the next cycle. 
     In step  730 , the next cycle of data  105  is collected by temperature detection system  110 . Temperature detection system  110  (FIG. 2) obtains data  105  from measurements conducted on target  140  for processing by data processor  120 . In step  735 , data is transmitted to data processor  120  as discussed with reference to step  705 . In step  740 , data  105  received from temperature detection system  110  is processed by data processor  120 . Data  105  is used by image processor  210  (FIG. 2) to develop updated images of magnitude image  235 , temperature image  240 , and damage image  245  for display by GUI  250 . In one embodiment, the initial reference data collected in step  700  is used in conjunction with data  105  obtained in the current cycle to develop an updated temperature image  240  and damage image  245  in implementations where temperature detection system  110  is only capable of detecting temperature differences, rather than absolute temperature. Additionally, data  105  is processed by image processor  210  to produce target data  215  (FIG. 2) for the next cycle of the real-time closed loop feedback control. Steps  720  through  740  are continuously repeated until the user terminates the process, or data processor  120  determines that termination is necessary for safety or other reasons. For example, the temperature of a image interest selection  450  (FIG. 4) selected by the user may have exceeded the desired maximum temperature as defined by strategy parameter set  264  and rule set  262  (FIG.  2 ). In this situation, data processor  120  would terminate the heat output of heat generating system  130 , and may notify the user of the impending shut down. 
     Referring next to FIG. 8, a magnetic resonance guided laser energy thermal therapy system is illustrated according to one embodiment of the present invention. Reference numerals in FIG. 8 that are common to reference numerals in FIGS. 1-7 indicate like, similar or identical features or elements. Magnetic resonance guided laser energy thermal therapy system  800 , herein referred to as MR thermal therapy system  800 , includes data processor  120 , display  255 , laser device  805  (an embodiment of heat generating system  130 ), optic fiber  810  (an embodiment of applicator  330 ), network  830 , MR system  870  (an embodiment of temperature detection system  110 ), and tissue  860  (an embodiment of target  140 ). MR system  870  includes magnet  840 , radio frequency (RF) coil  850 , and MR console  820 . 
     In one embodiment of the present invention, MR thermal therapy system  800  is used to produce lesions in biological tissue (tissue  860 ), such as muscle, organs, and the like. For example, MR thermal therapy system  800  may be used to cause cell necrosis in cancerous cells in a tumor, while leaving most or all of the healthy cells surrounding the tumor intact. 
     In one embodiment, data processor  120 , discussed in greater detail with reference to FIG. 2, is connected to laser  805  and MR system  870  via network  830 . Network  830  may include the Internet, a wireless network, a satellite network, and the like. One reason for a remote connection between data processor  120  and laser  805  and MR system  870  is that a doctor/practitioner may consult on the operation of MR thermal therapy system  200  from a remote location without having to be located near MR system  870  or laser  805 . For example, MR thermal therapy system  800  could be transported to a difficult to access remote region by a technician, and an experienced doctor located elsewhere who is unable to reach the remote region could direct the actions of the technician, or control the system himself, based on the images displayed to the doctor by GUI  250  (FIG. 2) on display  255  connected to data processor  120 . It will also be appreciated that laser  805  may be remotely located from tissue  860  with the laser energy delivered to tissue  860  via optic fiber  810 . 
     MR system  870  continuously or periodically measures and stores data obtained by measurement conducted on tissue  860 . One implementation of MR system  870  may be an imaging system equipped to generate proton resonance images. In this implementation, the system is capable of exhibiting a spatial-temperature resolution of 0.16° C.·cm or better. MR system  870  uses a magnetic field, created by magnet  840 , and radio emissions, emitted from RF coil  850 , to continuously obtain MR data  825  (data  105 ) from an area, plane, or volume of tissue  860 . In one embodiment, MR data  825  includes a complex number for each pixel of an MR image obtained by MR console  820 . For example, if MR data  825  includes the data for a 256 by 256 pixel resolution MR image, MR data  825  includes 65536 complex numbers. Because of the time involved in interrogating the selected portion of tissue  860  using magnetic resonance imaging techniques, MR system  870  is generally the limiting factor in the degree to which MR thermal therapy system  800  behaves in a real-time fashion. For example, in one implementation of MR thermal therapy system  800 , MR system  870  takes an average of seventeen seconds to measure and collect MR data  825  on an MR image with a resolution of 256 by 256 pixels. It will be appreciated that as the signal-to-noise ratio of a desired MR image decreases, and/or as the measurement speed of MR system  870  for a given signal-to-noise ratio increases, the delay in real-time feedback control will be reduced. 
     MR data  825  is continuously updated and transmitted to data processor  120  for real-time, or near real-time, feedback control. Data processor  120  processes updated MR data  825  to generate images for GUI  250  and to control the output of laser  805 . In one embodiment, data processor  120  performs Fourier transform decoding on MR data  825  to produce image data. In an alternate embodiment, MR system  870  processes MR data  825  to produce image data and transmits the image data to data processor  120  for further processing. For example, data processor  120  could perform a frequency domain analysis on MR data  825  and produce a complex number representative of each pixel of an image to be displayed on GUI  250 . It will also be appreciated that the formatting of MR data  825  into image data could be performed by MR console  820 . MR console  820  would then transmit the image data to data processor  120 . The magnitudes of the pixels&#39; values may be used to create magnitude image  235  (FIG.  2 ), which represents the physical structure of an area, cross-section or volume of tissue  860 . In one embodiment, the physical structure of the area, cross-section, or volume is determined using the localized calculated spin density of hydrogen molecules measured by MR system  870 . It will be appreciated by those skilled in the art that the MR image may be obtained using any of a number of techniques designed to elucidate the structure of the object being imaged. For example, so called “T 1 -weighted” or “T 2 -weighted” images may be obtained, where T 1  and T 2  refer to intrinsic magnetic resonance sensitive properties of all tissues, and weighted implies that the contrast of the image has been adjusted to exemplify local difference in a particular parameter. Additionally, it is well-known that certain magnetic resonance contrast agents may be administered prior to or during imaging. Such agents are preferentially deposited in tissues such as tumor and affect the local MR imaging environment in a way that makes the tumor easier to identify. Imaging methods such as gradient recalled echo (GRE) sequences may also be used to generate temperature sensitive images. As well, aforementioned T 1 -weighted images may be used to generate temperature sensitive images, as the T 1  property of tissue is temperature-dependent. In at least one embodiment, a reference image is obtained before laser  805  applies any heat. After heat is applied and MR data  825  representing an updated image of tissue  860  is obtained, the resulting phase difference between the reference image pixel and the updated image pixel represents the temperature change. In order to determine the absolute temperature of a pixel, the change in temperature between the updated image and the reference image must be added to the reference image absolute temperature, which is known by measurement, empirical data, etc. In one embodiment, MR system  870  is capable of determining the absolute temperature of tissue  860 . It will be appreciated that other methods of processing MR data  825  to produce images displayed by GUI  250  and/or to process to control the output of heat generating system  130  may be used without departing from the spirit or the scope of the present invention. 
     Irreversibly damaged tissue is displayed using damage image  245  (FIG. 2) in GUI  250 . A portion of tissue  860  is considered irreversibly damaged when the cells of the tissue portion are dead, or damaged enough, through protein denaturization, water vaporization, etc., that it is determined, using empirical data, previous experience, or models, that the cells will likely die within a relatively short time span. In one embodiment, damage image  245  is constructed using the temperature history for a given portion of tissue  860 . One method of determining tissue damage using temperature history is to determine a total amount of heat absorbed by tissue in an area. This may be achieved by keeping a summation of all temperatures measured for a given portion of tissue  860 . If the sum total of heat for the given portion exceeds a predetermined value, the cells in that portion are considered dead or dying. In one embodiment, the Arrhenius rate equation may be used to calculate irreversible cell damage as a function of the temperature history. The Arrhenius rate equations is commonly expressed as follows: 
     
       
         Ω=∫ A*e   −Ea/(RT)   dt   
       
     
     Wherein: 
     A is the frequency factor constant for a given tissue type; 
     Ea is the activation energy value specific to the type of tissue; 
     R is the Universal Gas Constant; and 
     T is the temperature history of the tissue as a function of time; and 
     a cell is considered dead or dying if the value of Ω is greater than or equal to one when the equation is evaluated. 
     The Arrhenius rate equation is integrated with respect to time for a given location of tissue  860 , and if the integrated value is greater than a determined value, then the cells in the location are considered irreversibly damaged. It will be appreciated that the determined value, based on tissue type, may be a result of empirical analysis, a user&#39;s experience, models, or theory. As it is very rare to have a defined, continuous equation for cell temperature as a function of time, the Arrhenius rate equation is usually evaluated numerically by using linear interpolation between temperature history points. It will be appreciated that as the time difference between temperature history points decreases, the degree to which linear interpolation emulates the real temperature history of a given location of tissue  860  increases. 
     As discussed previously, damage distribution data, in addition to (or in place of) temperature data, may be used to determine the feedback control of laser  805 . Since the damage to a cell in many cases is dependent on the properties of the cell type, location, and the like, the appropriate values for constants of the Arrhenius equation must be determined. The user may use previous experience, tables, or may load the values from a database or a file. Alternately, the values could be hardcoded into software used by data processor  120 , automatically uploaded from a database, etc. Incorrectly determining the total heat needed may result in charring of the cells if the history of heat received is enough to char the cells or if an absolute maximum temperature is exceeded. Similarly, if not enough heat is absorbed by the cells in tissue  870 , or if a minimum temperature needed to cause cell death or irreversible damage is never reached, the cells will not be dead or dying, although they are displayed as dead or dying cells in damage image  245  (FIG.  2 ). 
     In the previous detailed description of the embodiments of the present invention, reference is made to the accompanying drawings that form a part hereof, and in which is shown by way of illustration specific embodiments in which the invention may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the invention, and it is to be understood that other embodiments may be utilized and that logical, mechanical, chemical and electrical changes may be made without departing from the spirit or scope of the invention. To avoid detail not necessary to enable those skilled in the art to practice the invention, the description may omit certain information known to those skilled in the art. The previous detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present invention is defined only by the appended claims.