the present disclosure provides embodiments of imds that increase the sensitivity and specificity of ventricular tachyarrhythmia event ( vt / vf ) detection by utilizing a combination of sensed ventricular pressure data and sensed impedance data to determine the hemodynamic stability of a rhythm . the hemodynamic stability in turn is utilized to determine which rhythms require aggressive therapy ( i . e ., high energy defibrillation ) and which rhythms require less aggressive therapies ( e . g ., anti - tachy pacing ( atp )) or do not require therapy at all . the imd determines a phase relationship between ventricular pressure and cardiac impedance . the phase relationship provides an accurate and readily discernable indication of hemodynamic stability . during a normal cardiac contraction , the left ventricle ( lv ) fills with blood and expands in volume . during this time , lv pressure increases until reaching a maximum . conversely , as the volume of blood in the lv increases , the measured impedance across this heart chamber decreases due to the conductivity of the blood . when the lv contracts it ejects a substantial portion of the blood volume thereby reducing the volume of blood in the chamber and lowering the lv pressure . with the lower blood volume , the measured impedance is higher . thus , in a normal hemodynamically stable cardiac event cycle , measured pressure and measured impedance will be out of phase with one another . while described with respect to lv values , it should be appreciated that other cardiac pressure and impedance values will vary in a similar fashion and may be utilized accordingly , as will be described herein . fig1 illustrates an imd 10 coupled with a heart 22 via a plurality of leads 14 , 16 , 18 . the imd 10 includes a housing or “ can ” 12 and a header portion 20 . a right atrial ( ra ) lead 14 is coupled with the header 20 and includes one or more ra electrodes 25 disposed near a distal end and located within the right atrium of the heart 22 . a right ventricular ( rv ) lead 16 is also coupled with the header 20 . the rv lead 16 includes a tip electrode 26 , a ring electrode 28 , a pressure sensor 30 and a coil electrode 32 . a left ventricular ( lv ) lead 18 includes a tip electrode 34 . the lv lead 18 is coupled with the header 20 at its proximal end and is passed through the coronary sinus ( cs ) 24 and through a cardiac vein so that the electrode 34 is located proximate the left ventricle of the heart 22 . the can 12 further includes a can electrode 30 . it will be appreciated that the imd 10 may be configured with different leads and / or with leads having different electrode configurations . as an example , imd 10 is illustrated in fig2 having a single rv lead 52 . lead 52 has numerous electrodes and sensors disposed along its length and coupled with the can 12 via separate conductors . as illustrated , rv lead 52 includes a svc coil 54 , atrial electrodes 56 , 58 , rv coil electrode 60 , rv pressure sensor 30 , and rv tip electrode 26 . the components and operation of the imd 10 , configured as an icd are generally conventional and will not be described in detail . fig3 is a block diagram illustrating some of these components . as illustrated , the imd 10 includes a microprocessor 100 coupled with a battery or power supply 110 . a memory 105 is provided and includes a portion dedicated to storing the operational algorithms and parameters for device function as used in combination with the microprocessor . in addition , and typically separate , a portion of writeable memory is provided to store data collected by the imd 10 . the microprocessor 100 controls operation of the therapy deliver module 115 based upon the stored algorithms , parameters and protocols , to deliver , for example , defibrillation waveforms when required . alternative therapies , such as pacing , cardioversion , anti - tachy pacing , and the like may also be provided and delivered via therapy control module 115 . numerous sensors may be included to provide data to the imd 10 . three are illustrated herein . namely , the imd 10 includes an impedance sensor 120 , a pressure sensor 135 and an egm sensor 130 . any pairing of the electrodes illustrates in fig1 and 2 ( as well as other known electrode types / positions ) may be utilized to gather egm data as well as impedance measurements . the pressure sensor 125 utilizes a pressure sensor disposed on , within or proximate the heart 22 . as illustrated , the pressure sensor 125 utilizes a rv pressure sensor 30 disposed within the right ventricle . it should be appreciated the direct measurement of left ventricular ( or arterial ) pressure may be ideal , however placing such a sensor in the left ventricle is challenging . as will be described below , rv pressure data is sufficiently similar to lv pressure data to facilitate implementation . the impedance sensor 120 operates by driving current between a pair of electrodes and measuring the resulting signal , either with the same receiving electrode or by utilizing one or more electrodes other than the driving pair . impedance may be measured between one or more electrode pairs within a single heart chamber ( e . g ., the right ventricle ). a constant current stimulation field is established between electrode pairs disposed within the ventricle . impedance ( or its inverse , conductance ) is measured between adjacent electrode pairs and the value from each electrode pair is summed to derive an impedance / conductance signal that is proportional to the volume of the heart chamber measured . specifically , wherein , v is equal to the total heart chamber volume , g is equal to conductivity , ρ is equal to the resistivity of blood , 1 is the interelectrode distance , and v p and α are correction factors accounting for current leakage out of the electrical field and non - homogeneity of the electrical field . alternatively , direct impedance measurements from an rv electrode ( e . g ., rv tip electrode 26 ) across the lv to e . g ., the lv tip electrode 34 or the can electrode 36 will approximate lv impedance . fig4 is a graph 400 illustrating sampled data of various types and for various cardiac rhythms correlated together . as illustrated , for each type of data collected , the results for a sinus rhythm 405 , vt 410 , and vf 415 are illustrated . ecg ( or egm ) data 420 illustrate a stable sinus rhythm 405 with discernable r waves . for vt 410 , the ecg signal 410 illustrates signals of similar amplitude ; however , due to the greatly increased rate the frequency is greater than that of the sinus rhythm 405 . with vf 415 , the signal 420 becomes irregular but still has a high frequency . for the impedance values 425 , the amplitudes of the waveforms tend to decrease , measured values decrease , and of course , frequency increases as the rhythms progress from sinus 405 , to vt 410 and vf 415 . for lv pressure 430 and rv pressure 435 , there is also a notable decrease in amplitudes and an increase in frequency . it will be appreciated that ex post facto analysis of these rhythms is deceptive . that is , to take idealized data during known rhythms for purposes of correlation and discussion tends to diminish the difficulty in processing these signals in real time . for example , on an analysis of ecg data 420 the distinction between sinus rhythm 405 and vt 410 may simply be rate , which as discussed above may be generally categorized but is often overlapping . the impedance values 425 illustrated tend to show a distinction between the rhythms ; however , in a real world environment noise and other normal variation may obscure these differences ; rendering both false positives and false negatives . further , the amplitude changes may not be sufficiently discernable and the differences in actual measured values may be so patient specific as to make rhythm classification quite difficult . similarly , with the pressure data 430 , 435 there may be difficulty in establishing thresholds that reliably discriminate rhythms across patient populations . what this data set does illustrate is that the nature of the rhythm does have an effect on each of these parameters . as previously stated , when in a normal sinus rhythm ( nsr ), cardiac pressure ( more specifically ventricular pressure ) is out of phase with ( ventricular ) impedance . this relationship is illustrated in the phase plots of fig5 a and 5b . fig5 a is a phase plot based upon lv pressure data and fig5 b is a phase plot based upon rv pressure data . in both graphs , conductance ( inverse of impedance ) is plotted on the x axis while pressure is plotted on the y axis . as illustrated , the out of phase relationship during nsr leads to a phase loop plot 500 a , 500 b that defines a substantial internal area . this indicates hemodynamic stability . that is , in efficient cardiac cycles changes in pressure inversely correlate to changes in the volume of the heart chamber ( which correlated to impedance / conductance ). conversely , in hemodynamically unstable rhythms blood flow ( i . e ., output ) is reduced . for example , in vf the ventricle may be rapidly quivering which produces fluctuations in pressure . without substantial cardiac output , the blood volume is not changing substantially despite these pressure variations ; hence impedance changes will fail to correspond . in the phase plots of fig5 a and 5b a hemodynamically unstable vt 505 a , 505 b and vf 510 a , 510 b are illustrated . as pressure and impedance are no longer out of phase , the resulting phase plot is chaotic and fails to define a substantive area . this result is further illustrated in the bar graphs of fig6 a and 6b , which show the area defined by the phase plots of fig5 a and 5b respectively . area may be calculated using any of a variety of mathematical techniques , such as integrating an equation representing the phase plot . these graphs also define a parameter of stroke work , which corresponds to the integral of pressure with respect to volume ( approximated as conductance ). stroke work approximates the work done by the ventricle to eject the stroke volume . thus , higher stroke work corresponds with hemodynamic stability . as illustrated , the hemodynamically stable sinus rhythm has a significantly larger area as compared to the hemodynamically unstable vt and vf rhythms . in practice , this classification would be utilized to determine whether particular therapy options were necessary or appropriate . in the illustrated examples , both the vt and vf episodes are hemodynamically unstable and a high power therapy ( defibrillation ) would be appropriate . in most instances , vf would be hemodynamically unstable and require such therapy . vt , on the other hand , while an arrhythmia may in fact be hemodynamically stable . that is , despite the high rate , cardiac output may be sufficient . through not illustrated , if a vt were present and hemodynamically stable the proper phase relationship between pressure and impedance would be maintained and the phase loop diagram for this vt rhythm would more closely approximate that of nsr . in such a case , alternative therapy options become available and may be attempted for a longer period of time . for example , anti - tachy pacing ( atp ) is a viable option . further , because the current data monitors hemodynamic stability , atp may be given a longer period of time before resorting to a more aggressive therapy . spontaneous termination of the arrhythmia may also occur before the rhythm becomes unstable , thus eliminating the need for therapy . fig7 is another mechanism to illustrate the relationship between pressure and impedance . specifically , fig7 is a cross - correlation plot between right ventricular pressure and intrathoracic impedance during sinus rhythm ( solid line ) and vt / vt ( solid / dashed line ) derived from the same data used to produce the previous figures . as illustrated , vt / vf results in a dramatic shift in both the amplitude and time lag of the maximum correlation . these changes indicate a hemodynamically unstable arrhythmia . fig8 is a flowchart describing a method of utilizing the phase relationship between pressure and impedance to determine hemodynamic stability in the selection and application of therapy . in this embodiment , a patient specific baseline is determined ( 800 ). a patient with an imd 10 is monitored during a period of confirmed normal sinus rhythm ( nsr ). pressure and impedance values are collected and correlated . it should be appreciated that in other embodiments , baseline data may be estimated from relevant patient populations . the imd 10 operates normally in accordance with known processing algorithms until vt / vf is suspected ( 810 ). this would most likely be based upon rate . at this point , pressure and impedance values are again measured ( 820 ), the phase relationship calculated , and the results are compared ( 830 ) with the previously established baseline to determine ( 840 ) if there is a difference . this may be done algorithmically by calculating an area defined by a phase plot between impedance / conductance measures verses pressure or plotting a cross - correlation between pressure and impedance . it should be appreciated that other mathematical or algorithmic techniques may be utilized to denote and quantify the phase relationship between pressure and impedance will remaining within the spirit and scope of the present disclosure . if there is no difference or the difference is less than a threshold , the imd 10 determines ( 850 ) that the rhythm is hemodynamically stable ( 850 ). in this instance , the imd 10 may ( depending upon the other parameters of the rhythm ) leave the rhythm untreated or deliver therapies that are less aggressive than defibrillation ( such as atp ). if the comparison between the current pressure / impedance data indicates a large difference ( 840 ), then the imd 10 determines ( 870 ) that the rhythm is hemodynamically unstable and that high power therapy ( defibrillation ) is warranted ( 880 ). the particular thresholds set may be based upon patient population data or set to patient specific parameters . referring to fig5 a , 5 b , 6 a , and 6 b there is a clear distinction between hemodynamically stable and unstable rhythms . in one embodiment , the threshold is set to a particular percentage of the baseline nsr area taken from the phase plots . thus , if the measured values fall below x percent of baseline , the rhythm is declared unstable . for example , in one embodiment if the measured data is less than 50 % of the baseline , the rhythm is declared unstable . in another embodiment , if the measured data is less than 10 % of the baseline , the rhythm is declared unstable . as described , the imd 10 relies upon other parameters ( e . g ., rate ) to trigger a suspected vt / vf ( 810 ), at which point , impedance and pressure are measured ( 820 ) and compared ( 830 ) with a baseline . it should be appreciated that in an alternative embodiment , impedance and pressure are measured continuously or at a high frequency and either continuously ( or frequently ) compared with the baseline . in this manner , the phase relationship between pressure and impedance would be useful to initially indicate a hemodynamically unstable rhythm , rather than to just confirm the same . further , when used in this manner , the phase relationship may identify a declining cardiac rhythm and permit less aggressive therapy prior to reaching hemodynamic instability . as described , various embodiments utilize a phase relationship between sensed pressure and impedance data to determine the hemodynamic stability of a given cardiac rhythm . this determination is then utilized to select an appropriate therapy . techniques and technologies described herein in terms of functional and / or logical block components and various processing steps . it should be appreciated that such block components may be realized by any number of hardware , software , and / or firmware components configured to perform the specified functions . for example , an embodiment of a system or a component may employ various integrated circuit components , e . g ., memory elements , digital signal processing elements , logic elements , look - up tables , or the like , which may carry out a variety of functions under the control of one or more microprocessors or other control devices . in addition , those skilled in the art will appreciate that embodiments may be practiced in conjunction with any number of imd configurations , medical device therapies , and monitoring / diagnostic equipment , and that the system described herein is merely one suitable example . for the sake of brevity , conventional techniques related to signal sensing and signal processing , and other functional aspects of the systems ( and the individual operating components of the systems ) may not have been described in detail herein . furthermore , the connecting lines shown in the various figures contained herein are intended to represent example functional relationships and / or physical couplings between the various elements . it should be noted that many alternative or additional functional relationships or physical connections may be present in an embodiment of the subject matter . the system embodiments may be described herein with reference to symbolic representations of operations , processing tasks , and functions that may be performed by various computing components or devices . such operations , tasks , and functions are sometimes referred to as being computer - executed , computerized , software - implemented , or computer - implemented . in practice , one or more processor devices can carry out the described operations , tasks , and functions by manipulating electrical signals representing data bits at memory locations in the system memory , as well as other processing of signals . the memory locations where data bits are maintained are physical locations that have particular electrical , magnetic , optical , or organic properties corresponding to the data bits . when implemented in software or firmware , various elements of the systems described herein ( which may reside at an imd , an external monitor device , or elsewhere in the system environment ) are essentially the code segments or instructions that perform the various tasks . the program or code segments can be stored in a processor - readable medium or transmitted by a computer data signal embodied in a carrier wave over a transmission medium or communication path . the “ processor - readable medium ” or “ machine - readable medium ” may include any medium that can store or transfer information . examples of the processor - readable medium include an electronic circuit , a semiconductor memory device , a rom , a flash memory , an erasable rom ( erom ), a floppy diskette , a cd - rom , an optical disk , a hard disk , a fiber optic medium , a radio frequency ( rf ) link , or the like . the computer data signal may include any signal that can propagate over a transmission medium such as electronic network channels , optical fibers , air , electromagnetic paths , or rf links . while the system and method have been described in terms of what are presently considered to be specific embodiments , the disclosure need not be limited to the disclosed embodiments . it is intended to cover various modifications and similar arrangements included within the spirit and scope of the claims , the scope of which should be accorded the broadest interpretation so as to encompass all such modifications and similar structures . the present disclosure includes any and all embodiments of the following claims .
an implantable cardioverter defibrillator evaluates the hemodynamic stability of an arrhythmia to determine whether or not to defibrillate . the device obtains cardiac pressure and cardiac impedance data and evaluates a phase relationship between these parameters . hemodynamically stable rhythms will result in an out of phase relationship .