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Acute Pulmonary Embolism: Correlation of CT Pulmonary Artery Obstruction Index with Blood Gas Values

¹ Department of Radiology, University Hospital of Ioannina, Panepistimiou Ave., Ioannina 45500, Greece.
² Department of Pneumonology, University Hospital of Ioannina, Ioannina 45500, Greece.
³ Department of Statistics, University Hospital of Ioannina, Ioannina 45500, Greece.

Received August 23, 2004; accepted after revision January 17, 2005.

 
Address correspondence to Z. Metafratzi (zafmet{at}otenet.gr).

Abstract

Top Abstract Introduction Subjects and Methods Results Discussion References

 
OBJECTIVE. The purpose of our study was to investigate the relation between the pulmonary artery obstruction index assessed with helical CT and impairment in blood gases in patients with acute pulmonary embolism.

SUBJECTS AND METHODS. Helical CT pulmonary angiography was performed in 78 patients who were suspected of having acute pulmonary embolism and selected as being free of underlying cardiopulmonary disease. Findings consistent with acute pulmonary embolism were observed in 34 patients. The severity was assessed by the pulmonary artery obstruction index, defined as (n x d), where n is the number of segmental arteries occluded and d is the degree of obstruction. Spearman's rank correlation coefficients were used to assess the correlation between the index of arterial obstruction and arterial partial pressure of oxygen (PaO₂); alveolar–arterial difference in partial pressure of oxygen (PAO₂–PaO₂); arterial partial pressure of carbon dioxide (PaCO₂); and arterial oxygen saturation (SaO₂). The statistical difference of the arterial blood gas values between the two groups of patients (those with and those without pulmonary embolism) was evaluated using the Mann-Whitney U test. Blood gases were comparatively evaluated below and above different index values (from 40% to 70%) and different PaCO₂ values (25, 30, and 35 mm Hg) as possible indexes of embolism severity using the same test. The level of significance was set at 95% (p = 0.05).

RESULTS. The values of PaO₂, SaO₂, and PaCO₂ were significantly lower (p = 0.024, p = 0.0062, and p = 0.000075, respectively) and the values of PAO₂–PaO₂ were significantly higher (p = 0.0169) in the pulmonary embolism group than in the no-pulmonary-embolism group. A significant correlation was observed between the obstruction index and PaO₂ (r = –0.33, p = 0.05), PaCO₂ (r = –0.34, p = 0.05), PAO₂–PaO₂ (r = 0.39, p = 0.02), and SaO₂ (r = –0.35, p = 0.04). Using cutoff values for the pulmonary artery obstruction index of 40%, 50%, 60%, and 70%, we observed that PaCO₂ and PAO₂–PaO₂ differed significantly between above and below the 40% (p = 0.018 and p = 0.03), 50% (p = 0.0087 and p = 0.029), and 60% (p = 0.005 and p = 0.003) cutoffs. PaO₂ differed significantly for the cutoff values of 60% (p = 0.03) and 70% (p = 0.004). The same was observed for SaO₂ at 60% (p = 0.05) and 70% (p = 0.03). Comparisons for PaCO₂ showed that a value of 30 mm Hg significantly separates levels of the pulmonary artery obstruction index (p = 0.002), with 78% sensitivity and 82% specificity indicating a pulmonary artery obstruction index greater than 50%.

CONCLUSION. In patients with acute pulmonary embolism but no other underlying cardiopulmonary disease, the severity of the pulmonary arterial tree obstruction assessed using the CT obstruction index is significantly correlated to the blood gas values. The strongest correlation was observed between the index and the PAO₂–PaO₂. Furthermore, a PaCO₂ value of 30 mm Hg or less is highly suggestive of an obstruction index of more than 50% of the arterial bed.

Keywords: angiography, CT • chest • embolism • lungs • pulmonary artery obstruction index

Introduction

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Helical CT of the pulmonary arteries (CTPA) has become the first-line technique for the detection of emboli in the large and segmental vessels [1–3]. More recently, the development of MDCT enables scanning of the entire thorax during the peak enhancement of the pulmonary arterial tree using submillimeter collimation, thus increasing the sensitivity and specificity of the method [4–6]. However, when reporting positive CTPA findings in routine clinical practice, attention is mainly focused on the presence of pulmonary emboli, a description of their location (main pulmonary artery, lobar, segmental, and subsegmental branches), and a gross estimate of their extent (massive, extensive, or isolated). More precise and objective estimation of the severity of obstruction of the arterial bed relevant to the patient's treatment and prognosis has not been established [7]. A few studies have addressed this issue [8–11] and, to our knowledge, in only one was the severity of obstruction as assessed on CTPA quantified using the obstruction index of Qanadli et al. [9], which is related to clinical data and, more specifically, to the clinical outcome [12].

We designed this study to investigate whether the quantification of acute pulmonary embolism using the pulmonary artery obstruction index as proposed by Qanadli et al. [9] correlates with the functional lung impairment of acute pulmonary embolism and, more specifically, with hypoxemia, alveolar–arterial gradient of oxygen (PAO₂–PaO₂), hypocapnia, and hemoglobin desaturation.

Subjects and Methods

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Seventy-eight patients (36 men and 42 women) with a high clinical suspicion of pulmonary embolism and with no underlying cardiopulmonary disease participated in this study. The mean age of the population was 62 ± 16 years (range, 30–87 years), and all were in stable hemodynamic condition. Underlying cardiopulmonary disease was excluded in all patients by history, physical examination, CT findings, and ECG. Cardiac echo was performed in a minority of patients (n = 5). Prior cardiopulmonary disease was defined as valvular, myocardial, or pericardial disease; myocardial infarction; prior left or right heart failure; chronic obstructive disease or other parenchymal and pleural disease; or chronic thromboembolic disease and concurrent pneumonia. The CT criteria used to exclude patients with cardiopulmonary disease were signs of emphysema; interstitial lung disease (according to the Nomenclature Committee of the Fleischner Society [13]); other chronic parenchymal, pleural, or thromboembolic disease; pulmonary edema; and chronic pericardial disease. All patients underwent CTPA within 12 hr of admission. Fifty-three patients were scanned on a single-detector CT scanner (Secura, Philips Medical Systems) and 25 patients on a 16-MDCT scanner (MX IDT 8000, Philips Medical Systems).

The imaging parameters used for each type of scanner were as follows: for single-detector CT, slice thickness of 3 mm with a pitch of 1, reconstruction thickness of 2 mm, and gantry rotation of 0.75/1 sec; for 16-MDCT, collimation of 16 x 0.75 with a pitch of 1.238, slice thickness of 0.8 mm, reconstruction thickness of 0.4 mm, and gantry rotation of 0.5 sec. The lungs were scanned in a craniocaudal direction from the level of the lower pulmonary veins to 3 cm above the aortic arch in 25–28 sec for single-detector CT, whereas the scanning time for the whole chest (from lung bases to the apex) was 10–12 sec for 16-MDCT. The patients were scanned in suspended inspiration or during quiet breathing if they were unable to breath-hold. A total of 60–130 mL of low-osmolar contrast material (iopromide, 300 mg I/mL [Ultravist, Schering]) was administered IV with an automated injector at a rate of 3 mL/sec for single-detector CT and 4 mL/sec for 16-MDCT. To optimize the pulmonary arterial tree opacification, a timing bolus technique was used.

The studies were interpreted on a workstation (Brilliance, Philips Medical Systems) by two radiologists experienced in thoracic imaging (> 5 years of experience) in a combined interpretation. Both observers were blinded to the severity of the patient's clinical condition and the blood gas values. All axial images were viewed on the workstation using the cine stack technique and standard mediastinal windows (center, 50 H; level, 350 H). However, the observers were free to review multiplanar reconstructions and to change the window and level settings in real time to optimize visualization of the opacified vessels. The criterion used for the diagnosis of pulmonary emboli was the presence of an endoluminal filling defect on CTPA. The degree of obstruction was quantified according to obstruction index of Qanadli et al. [9], defined as the product (n x d) expressed in percentage of vascular obstruction, where n is the value of the proximal clot site that equals the number of segmental branches arising distally, and d is the degree of obstruction where partial obstruction is scored as 1 and complete obstruction as 2. Values for n range from a minimum of 1 (one segment obstructed) to a maximum of 20 (obstruction of both right and left pulmonary arteries). The total (n x d) product for each patient was divided by the maximum total score (20 segments x 2) and multiplied by 100 according to the formula ([ (n x d) / 40] x 100) to obtain to a percentage of vascular obstruction [9].

Arterial blood gases, including arterial partial pressure of oxygen (PaO₂); arterial partial pressure of carbon dioxide (PaCO₂); and arterial oxygen saturation (SaO₂). were measured on admission to the emergency department with the patient breathing room air. Furthermore, the alveolar–arterial gradient for oxygen (PAO₂–PaO₂) was calculated according to the formula:

The study was approved by the ethics committee of our institution; informed consent was not required.

Statistical Analysis
Results are expressed as mean ± SD and median. Spearman's rank correlation coefficients were used to assess the correlation between the pulmonary artery obstruction index and PaO₂, PAO₂–PaO₂, PaCO₂, and SaO₂. The Mann-Whitney U test was applied to discriminate differences of the blood gas values between the two patient groups (those with positive and those with negative CTPA findings). The same test was used to evaluate differences of the same blood gas values above and below certain pulmonary artery obstruction index levels (40%, 50%, 60%, and 70%) and to compare different PaCO₂ levels (35, 30, or 25 mm Hg) with the pulmonary artery obstruction index as possible cutoff values. The level of significance was set at 95% (p = 0.05).

Results

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Six CTPA images sets (6/78, 8%) were excluded from the study because of poor image quality: three caused by suboptimal vessel opacification and three because of motion artifacts. Thus, 72 patients remained for the analysis. Pulmonary embolism was identified in 34 patients (34/72, 47%). The mean percentage of obstruction of the pulmonary arterial tree (the pulmonary artery obstruction index) and the blood gases profile of the two patient groups (positive and negative CTPA findings for pulmonary embolism) are presented in Table 1. The values of PaO₂, SaO₂, and PaCO₂ were significantly lower (p = 0.024, p = 0.0062, and p = 0.000075, respectively), and PAO₂–PaO₂ significantly higher (p = 0.0169), in the pulmonary embolism group than in the no-pulmonary-embolism group. Furthermore, correlations between the pulmonary artery obstruction index and all blood gas values were found to be statistically significant. More specifically, the pulmonary artery obstruction index was significantly correlated with PaO₂ (r = –0.33, p = 0.05), PAO₂–PaO₂ (r = 0.39, p = 0.02), PaCO₂ (r = –0.34, p = 0.05), and SaO₂ (r = –0.35, p = 0.04). These correlations are graphically depicted in the x–y scatter diagrams of Figures 1A, 1B, 1C, and 1D.

View larger version (23K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1A —Scatter diagrams show negative correlation with pulmonary artery obstruction index for 34 studied patients with acute pulmonary embolism. Note negative correlation between pulmonary artery obstruction index and blood gas values. PaO2 (arterial partial pressure of oxygen) (r = –0.33, p = 0.057).

View larger version (21K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1B —Scatter diagrams show negative correlation with pulmonary artery obstruction index for 34 studied patients with acute pulmonary embolism. Note negative correlation between pulmonary artery obstruction index and blood gas values. PaCO2 (arterial partial pressure of carbon dioxide) (r = –0.34, p = 0.05).

View larger version (21K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1C —Scatter diagrams show negative correlation with pulmonary artery obstruction index for 34 studied patients with acute pulmonary embolism. Note negative correlation between pulmonary artery obstruction index and blood gas values. SaO2 (arterial oxygen saturation) (r = –0.35, p = 0.045).

View larger version (24K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1D —Scatter diagrams show negative correlation with pulmonary artery obstruction index for 34 studied patients with acute pulmonary embolism. Note negative correlation between pulmonary artery obstruction index and blood gas values. PAO2–PaO2 (alveolar–arterial difference in partial pressure of oxygen) (r = 0.39, p = 0.02).

Of the 34 patients with pulmonary embolism, the pulmonary artery obstruction index exceeded 50% in 13 patients (13/34, 38%) and 60% in 11 patients (11/34, 32%) (Figs. 2A and 2B). The pulmonary artery obstruction index ranged between 40% and 49% in two (2/34, 6%), between 30% and 39% in three (3/34, 9%), and between 2.5% and 29% in 16 patients (16/34, 47%) (Figs. 3A and 3B).

View larger version (90K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 2A —76-year-old man with multiple large emboli. Coronal multiplanar reconstructions of CT pulmonary angiography performed with 16-MDCT scanner show endoluminal defects (arrows). Patient received pulmonary artery obstruction index of 87.5%, and his blood gas values were PaO2 (arterial partial pressure of oxygen), 43.4 mm Hg; PaCO2 (arterial partial pressure of carbon dioxide), 25.5 mm Hg; SaO2 (arterial oxygen saturation), 82.5%; and PAO2–PaO2 (alveolar–arterial difference in partial pressure of oxygen), 74.7 mm Hg.

View larger version (85K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 2B —76-year-old man with multiple large emboli. Coronal multiplanar reconstructions of CT pulmonary angiography performed with 16-MDCT scanner show endoluminal defects (arrows). Patient received pulmonary artery obstruction index of 87.5%, and his blood gas values were PaO2 (arterial partial pressure of oxygen), 43.4 mm Hg; PaCO2 (arterial partial pressure of carbon dioxide), 25.5 mm Hg; SaO2 (arterial oxygen saturation), 82.5%; and PAO2–PaO2 (alveolar–arterial difference in partial pressure of oxygen), 74.7 mm Hg.

View larger version (120K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 3A —23-year-old woman with chest pain and dyspnea. CT pulmonary angiography performed with 16-MDCT in sagittal multiplanar reconstruction (A) and axial projection (B) shows endoluminal defects (arrows). Patient had segmental clot receiving pulmonary artery obstruction index of 7.5%. Blood gas values were PaO2 (arterial partial pressure of oxygen), 91.8 mm Hg; PaCO2 (arterial partial pressure of carbon dioxide), 33.8 mm Hg; SaO2 (arterial oxygen saturation), 97%; and PAO2–PaO2 (alveolar–arterial difference in partial pressure of oxygen), 15.95 mm Hg.

View larger version (80K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 3B —23-year-old woman with chest pain and dyspnea. CT pulmonary angiography performed with 16-MDCT in sagittal multiplanar reconstruction (A) and axial projection (B) shows endoluminal defects (arrows). Patient had segmental clot receiving pulmonary artery obstruction index of 7.5%. Blood gas values were PaO2 (arterial partial pressure of oxygen), 91.8 mm Hg; PaCO2 (arterial partial pressure of carbon dioxide), 33.8 mm Hg; SaO2 (arterial oxygen saturation), 97%; and PAO2–PaO2 (alveolar–arterial difference in partial pressure of oxygen), 15.95 mm Hg.

View larger version (11K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 4 —Scatter diagram of pulmonary artery obstruction index versus PaCO2 (arterial partial pressure of carbon dioxide) illustrates sensitivity (78%) and specificity (82%) of PaCO2 = 30 mm Hg (dotted line) for indicating severe pulmonary embolism (pulmonary artery obstruction index > 50%).

Discussion

Top Abstract Introduction Subjects and Methods Results Discussion References

 
CTPA has dramatically improved the quality of imaging of the pulmonary vasculature in the last decade and has changed the diagnostic approach to suspected acute pulmonary embolism. The average sensitivity and specificity for detecting pulmonary embolism has been shown to be 88% [6] and 92–96%, respectively [2, 15–18]. The introduction of MDCT has made it possible to image the pulmonary arterial tree faster with submillimeter collimation, thus improving the overall quality and increasing the sensitivity for isolated subsegmental pulmonary embolism [4–6]. However, the interpretation of CTPA is mainly focused on the presence or absence of emboli and a rough estimation of their severity (massive, extensive, or isolated). A few published articles confront the challenge of quantifying pulmonary arterial tree obstruction [8–11] by developing an obstruction index. In our study, the obstruction index of Qanadli et al. [9] was used because of the simplicity of applying it in routine clinical practice. This index is based on the number of segmental arteries occluded and those arising distally to an occluded proximal branch, with the integration of a weighting factor of 1 for partial and 2 for complete obstruction.

Six of 78 CTPA image sets were inconclusive because of inadequate imaging quality, which is in accordance with the published data in a recent review article [16, 17]. The mean value of the pulmonary artery obstruction index in patients was 39% ± 27%, which is higher than that described by other investigators [9]. This difference could be explained by the improved sensitivity of 16-MDCT in assessing pulmonary embolism as a result of overall improved image quality. The index of Qanadli et al. [9] for pulmonary artery obstruction has been validated by the Miller index [19] and has shown a strong correlation (r = 0.867, p < 0.0001). A significant correlation also exists between the index of Qanadli et al. and right ventricle dilatation [9]. However, to our knowledge no attempt has been made to relate the severity of obstruction expressed by this index to clinical parameters such as arterial blood gas measurements.

Gas exchange abnormalities observed in patients with acute pulmonary embolism are related to the size of the emboli, the presence of underlying cardiopulmonary disease, the degree of obstruction, and the time since embolization [20]. Mechanisms responsible for hypoxemia in patients with acute pulmonary embolism are the degree of ventilation–perfusion (V/Q) mismatch, the amount of right-to-left shunt, the level of cardiac output, and diffusion impairment, with V/Q abnormalities accounting for most of the hypoxemia and diffusion impairment playing a limited role [20–24]. Moreover, PAO₂–PaO₂ is mainly disturbed by the V/Q mismatch and intrapulmonary shunt, whereas oxygen saturation of hemoglobin falls in parallel with the PaO₂ reduction. Hypocapnia is the result of hyperventilation triggered by hypoxemia and reflexes initiated in the lung parenchyma [20, 22]. Therefore, the degree of hypocapnia is closely and inversely related to the amount of excess ventilation.

Blood gas analysis is a useful part of the diagnostic workup and follow-up of patients with suspected or documented pulmonary embolism because it is performed at the bedside. The patients included in this study had no other underlying cardiopulmonary disease. The blood gas values and the CTPA findings were assessed on admission, with the patient breathing room air before anticoagulant therapy, assuming that the blood gas levels measured at that time expressed purely the effects of the acute pulmonary embolism and the specific compensatory responses.

The pulmonary artery obstruction index correlated significantly with all blood gas values. However, the strongest correlation was observed between the pulmonary artery obstruction index and PAO₂–PaO₂. This finding is in accordance with the study by McFarlane and Imperiale [25], in which the PAO₂–PaO₂ gradient showed a linear correlation with the severity of pulmonary embolism, assessed by the pulmonary artery mean pressure gradient and by the number of mismatch vascular–perfusion defects on V/Q scans. In addition, our results are in agreement with those of McIn-tyre and Sasahara [26], who reported a linear relationship between pulmonary embolism severity and PaO₂ levels (p < 0.05), although in their study pulmonary embolism was proven by selective angiography, a different obstruction index was used for the quantification, and they did not include correlation with the PaCO₂ and PAO₂–PaO₂ values.

Ventilation and PaCO₂ are closely and inversely related, and our results suggest that the extent of pulmonary artery obstruction regulates the level of hyperventilation response. This might explain the higher sensitivity shown by PaCO₂ for revealing the severity of acute pulmonary embolism in our study. Among our patients with a pulmonary artery obstruction index greater than 50%, only two patients showed PaO₂ of less than 55 mm Hg. Conversely, 12 of 13 patients had a PaCO₂ of less than 30 mm Hg. The high sensitivity and specificity of PaCO₂ of 30 mm Hg for detecting severe acute pulmonary embolism (pulmonary artery obstruction index > 50%) offers additional confirmation of its clinical usefulness. PaCO₂ and PAO₂–PaO₂ were significantly different between above and below the four tested values of the pulmonary artery obstruction index, whereas PaO₂ and SaO₂ were significantly different only for the 60% and 70% values of the pulmonary artery obstruction index. Although overlapping gas values were present in all comparisons, PaCO₂ was clearly more sensitive for reflecting the degree of pulmonary artery obstruction. We consider our results to be strongly indicative; however, their validity should be reinforced with further studies with larger number of patients.

A limitation of our study was that two different scanning protocols were used with different collimations and scanning times. However, this is not expected to influence the results much, not only because thin collimation was used with the single-detector CT scanner (2–3 mm) but also because the pulmonary artery obstruction index depends on the presence of emboli on main, lobar, and segmental arteries that can be accurately documented with thin-collimation helical CT. Another limitation of our study was the lack of evaluation of the degree of agreement between the two observers because CTPA images were interpreted by consensus interpretation between the two radiologists. However, Qanadli et al. [9], who first described the CT obstruction index, observed a high correlation between scores obtained by two observers. Finally, the lack of baseline arterial blood gas measurements should be considered another limitation of the study.

In summary, the CT obstruction index used in this study showed a strong correlation between the severity of arterial bed obstruction and the blood gas values in patients with acute pulmonary embolism and no underlying cardiopulmonary disease. The strongest correlation was observed between the index and PAO₂–PaO₂. Moreover, an obstruction index of greater than 50% of the arterial bed may be expected for PaCO₂ of 30 mm Hg or less. This preliminary observation suggests that PAO₂–PaO₂ and PaCO₂, which are routinely available in the initial evaluation of suspected pulmonary embolism, in combination with other clinical parameters, can assist the primary care physician in suspecting severe acute pulmonary embolism and referring the patient for further evaluation.

Acknowledgments
 
We thank Dr. M. Remy-Jardin for her review of the manuscript, her support, and her advice.

References

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