Ashish Singal, Sheiphali A. Gandhi, Marc Pritzker, Thenappan Thenappan
The human body has two circulation systems: the systemic circulation and the pulmonary circulation. An elevation of blood pressure in either system is referred to as hypertension. PH is elevated blood pressure in the arteries of the lungs. Normal mean PA pressure is about 14 mm Hg at rest. If this pressure is greater than 25 mm Hg at rest, it is classified as PH. According to the World Health Organization, PH is classified in five groups (I–V), with each group characterized by its etiology and pathogenesis. It is important to accurately diagnose the type of PH for treatment planning and disease management. A right heart catheterization (RHC) procedure remains the gold standard that can definitively diagnose PH. Numerous other techniques are being developed that, in conjunction with RHC, can aid in diagnoses of type, severity, cause, treatment options, and functional classification of PH [1].In this study, we developed time-domain digital signal processing methodologies for assessing PA pressure waveforms. We hypothesize that a correlation between PA waveform parameters will allow determination of whether a patient suffers from PH, and potentially the type of PH. This information could prove to be an essential aid for physicians in treatment and management of patients suffering from PH.Minnesota PH repository (measure) is a prospective registry that collects information on all PH patients followed by the PH clinic at the University of Minnesota. All patients gave informed consent before enrolling in this registry. From the measure registry, we identified 66 patients with PH (mean PA pressure ≥25 mm Hg at rest).Patients underwent RHC using a fluid-filled Swan–Ganz catheter at the time of diagnosis of PH. PA tracings from the procedure were digitally acquired at a sampling rate of 240 Hz. Custom matlab programs/routines were developed to postprocess the data and analyze the PA tracings for PH and wave reflections.For every patient, typically ten individual waveforms segments were extracted from the PA waveform tracings (for 66 subjects a total of 842 individual waveforms). These individual waveforms were time sequenced from the initiation of PA pressure systolic upstroke and averaged to create an average waveform (Fig. 1). For every individual waveform and the time averaged waveform, 15 waveform parameters were calculated, which are: (1) pulmonary artery pulse pressure (mm Hg); (2) systolic pulmonary artery pressure (mm Hg); (3) diastolic pulmonary artery pressure (mm Hg); (4) mean pulmonary artery pressure (MPAP, mm Hg); (5) pulmonary artery fractional pulse pressure; (6) augmentation pressure (AP, mm Hg); (7) augmentation index (AI); (8) systolic time (TS, s); (9) diastolic time (TD, s); (10) total time (TT, s); (11) inflection time (TI, s); (12) systolic area under curve (AUCS, mm Hg s); (13) diastolic area under curve (AUCD, mm Hg s); (14) total area under curve (AUCT, mm Hg s); and (15) diastolic decay (mm Hg/s).The characteristics of wave reflections (timing, amplitude, and index) were quantified by performing pressure waveform analysis in time domain as described previously [2]. The human pulmonary pressure waveform may encounter a characteristic impedance change as it flows into the pulmonary vasculature, which manifests itself as wave reflections in the PA waveform. In normal subjects, little wave reflections are expected, however, with underlying pathology (e.g., pulmonary thromboembolism, reduced PA compliance, lung disease, and heart disease), the wave reflections can be significant. The temporal location where the wave reflection occurs is referred to as the inflection point (Fig. 2). The relative change in pressure amplitude above the inflection point is an estimate of the magnitude of the reflected pressure wave and defined as the AP. Measurement of these wave reflections in temporal and spatial domain may allow diagnoses of PH that can further aid in risk stratification and therapy planning.The first derivative of the PA pressure tracing (dP/dt) was calculated for every individual waveform and the time averaged waveform (Fig. 3). If the inflection point occurred before the peak pulse pressure (i.e., in the systolic phase), then the first local-minima or a zero-crossing of dP/dt was defined as the inflection point. If the inflection point occurred after the peak pulse pressure (i.e., in the diastolic phase), then the second local-minima or zero-crossing was defined as the inflection point. Note that one of the local-minima or zero-crossing would signify the peak pulse pressure and another one would signify the dicrotic notch.The correlation between AP, AI, and inflection time is shown in Figs. 4 and 5. AI was defined as the ratio of AP to the pulse pressure, and it could have either a positive or negative value based on the location of the inflection point relative to the peak pulse pressure. In normal subjects, since there are minimal to no wave reflections, both the AP and AI are expected to have a negative value as compared to subjects who have severe form of PH. In PH subjects, wave reflections occurring in the systolic phase make both the AP and AI positive. This correlation is illustrated in Fig. 4. Similarly, inflection times (duration to inflection point) are smaller in PH patients as illustrated in Fig. 5. These markers could be used as a screening tool to stratify patients who require further evaluation.We have developed an automated way of differentiating patients with different types of PH based on time-domain analysis of PA waveform and wave reflections. As a proof of concept, in this study, we identified a subset of patients suffering from PH to understand how PA waveform and wave reflections changes in various states of PH. The fact that we observed correlation between various pulse parameters must be viewed as one of the strengths of this study. These results coupled with further refinement of detection algorithms would allow us to make this process specific, sensitive, and automated.These findings are consistent with results from other studies suggesting that changes in pulmonary tree elasticity and pulse pressure are primarily due to an increase in MPAP in patients with PH. Wave reflections occurring in the systolic phase of the PA pressure tracing are considered abnormal and can be identified using the techniques developed in this investigation. A decrease in pulmonary elasticity or an obstructive pulmonary disease would exhibit greater wave reflections resulting in higher APs, higher AIs, and decreased inflection times as compared to normal subjects.These findings may provide novel insights into the etiology and pathophysiology of PH, which may allow further improvements in risk stratification of patients with PH and development of diagnostic tools for better delivery of care. Knowledge gained from these diagnostic tools may be used as aids in diagnoses, for treatment planning, medication optimization, and disease management. It is clear that a thorough understanding of PH will be important to the future of this evolving era of diagnostic tools.