CT Angiography

ARTICLE IN PRESS

Original Investigation

CT Angiography: Post-processed Contrast Enhancement for Improved Detection of Pulmonary Embolism Daniela Muenzel, MD, Alexander A. Fingerle, MD, Tina Zahel, MD, Andreas Sauter, MD, Alain Vlassenbroek, PhD, Martin Dobritz, MD, Ernst J. Rummeny, MD, Peter B. Noël, PhD Rationale and Objectives: The study aimed to improve the detection of pulmonary embolism via an iodine contrast enhancement tool in patients who underwent suboptimal enhanced computed tomography angiography (CTA). Materials and Methods: We evaluated the CT examinations of 41 patients who underwent CTA for evaluation of the pulmonary arteries which suffered from suboptimal contrast enhancement. The contrast enhancement of the reconstructed images was increased via a post-processing tool (vContrast). Image noise and contrast-to-noise ratio (CNR) were assessed in eight different regions: main pulmonary artery, right and left pulmonary arteries, right and left segment arteries, muscle, subcutaneous fat, and bone. For subjective image assessment, three experienced radiologists evaluated the diagnostic quality. Results: While employing the post-processing algorithm, the CNR for contrast-filled lumen and thrombus/muscle improves significantly by a factor of 1.7 (CNR without vContrast = 8.48 ± 6.79/CNR with vContrast = 14.46 ± 5.29) (P < 0.01). No strengthening of artifacts occurred, and the mean Hounsfield unit values of the muscle, subcutaneous fat, and the bone showed no significant changes. Subjective image analysis illustrated a significant improvement using post-processing for clinically relevant criteria such as diagnostic confidence. Conclusions: vContrast makes CT angiograms with inadequate contrast applicable for diagnostic evaluation, offering an improved visualization of the pulmonary arteries. In addition, vContrast can help in the significant reduction of the iodine contrast material. Key Words: Computed tomography; non-ionic iodine contrast agent; pulmonary embolism; contrast enhancement; post-processing software. © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

INTRODUCTION

P

ulmonary embolism (PE) is a leading cause of morbidity and mortality among hospitalized patients, with an overall incidence of 15.9% in adult medical autopsies (1,2). Therefore, it is important to have a diagnostic procedure offering a fast and reliable detection of PE. Computed tomography angiography (CTA) of the pulmonary arteries is a safe and highly accurate tool to detect or rule out PE (3,4). Nowadays, CT has become the standard imaging modality for patients with suspected PE (3–5), with the CTA representing a highly relevant diagnostic feature in clinical routine (6,7). In day-to-day clinical routine, CTA is a robust imaging technique to evaluate pulmonary arteries. However, some

examinations suffer from a suboptimal contrast opacification of the pulmonary vessels, eg, because of delayed image acquisition, heart failure, or dilution by non-contrasted blood from the inferior vena cava. As a consequence, image quality may be substantially decreased, and the CT images may be non-diagnostic with regard to PE. Potential improvement of arterial opacification can be achieved, for example, by a higher injection rate or a higher concentration, ie, a higher dose of contrast agent (8). However, an increase in contrast agent arises the risks of contrast medium-induced nephropathy and acute renal failure, respectively (9–11). The purpose of our study was to improve image quality in suboptimal enhanced CT examinations in patients with suspected PE via an iodine contrast enhancement tool (vContrast, Philips Healthcare, Cleveland, OH).

Acad Radiol 2016; ■:■■–■■ From the Department of Radiology, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany (D.M., A.A.F., T.Z., A.S., M.D., E.J.R., P.B.N.); CT Clinical Science, Philips HealthCare, Brussels, Belgium (A.V.). Received August 7, 2016; revised September 29, 2016; accepted September 30, 2016. Address correspondence to: D.M. e-mail: [email protected] © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.acra.2016.09.024

MATERIALS AND METHODS Patient Population

Forty-one patients (25 men and 16 women; mean age: 59.49 ± 16.86 years; age range: 25–95 years) with suspected 1

Academic Radiology, Vol ■, No ■■, 2016

MUENZEL ET AL

PE and CT angiograms with suboptimal contrast opacification of the pulmonary arteries were enrolled in this retrospective study. An institutional review board approval (blinded) was acquired and written informed consent was obtained from all patients before enrollment in the study. In seven patients, PE was detected by CT. Suboptimal contrast opacification was defined as CT values of the contrastfilled lumen <210 Hounsfield units (HU). The exclusion criteria for CT examinations were pregnancy and lactation, any contraindication to iodinated contrast agent such as severe anaphylactic reaction in the past, renal failure (serum creatinine level >1.3 mg/dL), or hyperthyroidism (serum ThyroidStimulating Hormone [TSH] level <0.4 mIU/L). A total of 41 CT examinations performed between April 2009 and August 2013 matched these criteria and were enrolled in our study. In patients with PE, diagnosis was substantiated by repeated CT examination and consistent laboratory parameters (elevated D-dimer), symptoms, and electrocardiographic finding, respectively. CT Technique and Image Reconstruction

CT angiograms were performed using a 256-slice multidetector CT (Philips Brilliance iCT; Philips Healthcare) with a tube voltage of 100 kV and 120 kV, respectively, and an effective tube current of 133.47 ± 83.95 mAs depending on the body mass index. One milliliter per kilogram body weight of nonionic contrast agent (Imeron 400, Bracco Imaging, Konstanz, Germany) was injected intravenously using a mechanical dualhead power injector (Stellant, Medrad, Inc., Indianola, PA) at a flow of 3.5 mL/s. CT scans were started using a bolus tracking technique with a region of interest (ROI) in the main pulmonary artery and a 150 HU threshold. Post-processing Tool

Noël et al. reported on further details concerning the vContrast algorithm (12). The algorithm has two main components: low contrast clustering estimate and structures enhancement. Low Contrast Clustering (LCC) Estimate By this component, the study images are approximated with a piece-wise smoothed approximation. This component has high sensitivity to low contrast structures, and it has the special capability of preserving very accurately the shape and the intensity values of the low contrast structures. Structures Enhancement By this component, the low contrast structures are enhanced. As the LCC approximation is available, it enables the structures in the study to be enhanced without the introduction of new artifacts to the study and without the amplification of the study noise. Thus, it enables the study of contrast-tonoise to be improved. In this component, an enhancement map is derived by enhancement of the structures in the LCC approximation. 2

The final vContrast images were obtained by adding the enhancement map obtained from the structures enhancement component to the original study. To enhance the contrast, vContrast (Philips Healthcare) was applied to the axial CT data in the arterial phase to improve the contrast differences within a given density range (low threshold of 50/upper threshold of 300, amplification of 150%).

Quantitative Image Analysis

All quantitative measurements were performed by a radiologist (6 years of experience in chest CT) at a commercially available post-processing workstation. CT attenuation values (HUs) were obtained for the main pulmonary artery, the right and left pulmonary arteries, segment arteries of the right upper lobe and left lower lobe, embolus (if existent), muscle (M. pectoralis), subcutaneous fat, and bone (corticalis of the scapula). Therefore, several ROIs were placed at the same image position with and without using vContrast. Image noise was defined as the standard deviation of the CT values for each ROI. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated as follows:

SNR = CNR =

μv σm

(1)

( μv − μm ) σm

(2)

where μv is the mean HU value of the vessel lumen, μm is the mean HU value of the muscle, and σm is the image noise. The mean values of the CNR with and without employing vContrast were assessed for the pulmonary arteries by averaging the values of the five pulmonary arteries. In addition, we assessed the differences between vessel and embolus CT values for all PEs, and the contrast-to-embolus ratio was calculated. Therefore, the CT values of the contrastfilled vessel proximal to the embolus were divided by the CT values of the embolus.

Qualitative Image Analysis

CT examinations have been independently evaluated by three experienced radiologists (mean clinical experience of 6 years, range: 4–9 years) with and without employing vContrast. The images were read on a commercially available diagnostic workstation and were presented in a random order. Observers were asked to rank the image quality and to define whether or not they would diagnose PE.

Ranking Score

I

Subjective image noise: 1—minimal noise, 2—less than average noise, 3—average noise, 4—above average noise, 5—unacceptable noise

Academic Radiology, Vol ■, No ■■, 2016

IMPROVED CONTRAST ENHANCEMENT IN PE CTA

II Artifacts: 1—no artifacts, 2—minor artifacts not interfering with diagnostic decision, 3—major artifacts affecting visualization of major structures, 4—substantial artifacts making the image non-diagnostic III Overall image quality: 1—excellent, 2—good, 3—suboptimal, 4—unacceptable IV Diagnostic confidence (with regard to PE): 1—completely confident, 2—probably confident, 3—confident only for limited clinical situation, 4—poor confidence V Artificial image appearance: 1—none, 2—weak, 3—moderate, 4—strong VI Pulmonary embolism: 1—yes, 2—no Statistical Analysis

Continuous data are expressed as arithmetic mean ± standard deviation. A two-tailed Student’s t test was performed for comparison of CT values, image noise, and CNR values on images with and without employing vContrast. The results of the subjective image quality assessment are shown as medians and were analyzed using the sign test. Cohen’s kappa was calculated for assessment of inter-reader agreement in qualitative image analysis. A P value ≤0.05 was considered to indicate statistical significance. All statistics were computed with Microsoft (Redmond, Washington, U.S.) Excel and SPSS (Chicago, Illinois, U.S.). RESULTS Quantitative Image Analysis

The mean CT value of the main pulmonary artery was 166 ± 38 HU using the standard protocol and 285 ± 43 HU in vContrast enhanced images, representing an increase of CT values of the contrast-filled vessels by a factor of 1.72 (P < 0.05). The SNR and CNR of all pulmonary arteries were significantly increased on vContrast images, with a mean SNR of 11.58 ± 7.64 versus 17.22 ± 6.09 and a mean CNR of 8.48 ± 6.79 versus 14.46 ± 5.29 for standard and vContrast images, respectively (Fig 1). Table 1 illustrates the CT values, SNR, and CNR of the different pulmonary arteries in detail. There were no significant differences on image noise between normal and vContrast post-processed images, with 15.95 ± 4.15 HU versus 17.54 ± 4.53 HU, P > 0.05, respectively. In addition, no significant differences were seen in the CT values of the muscles, the subcutaneous fat, and the corticalis of the bones, as shown in Figure 2. There was a significant increase in the contrast-toembolus ratio from 3.81 ± 1.31 to 5.67 ± 2.13 (P < 0.05). The mean CT values of emboli and vessel lumen are shown in Figure 3. Figure 4 illustrates an example of standard and vContrast CT images in a patient with PE of a segmental artery of the right lower lobe, and another patient with an embolus in a segmental artery of the left upper lobe. The CT density of

Figure 1. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of the pulmonary arteries in standard and vContrast images. SNR and CNR were significantly increased using vContrast by a factor of 1.48 and 1.71, respectively. * Statistically significant difference, P > 0.05.

the contrast-filled pulmonary arteries is increased on vContrast images (Figs 4b and 4d), and the discrimination of embolus and enhanced vessels is better on vContrast images compared to the standard images with low contrast of the pulmonary arteries (Figs 4a and 4c). Subjective Image Analysis

The CT images post-processed by vContrast were rated as superior to conventional CT data for the evaluation of the pulmonary arteries and the assessment of PE. The diagnostic confidence of vContrast images was judged better on vContrast images than on standard images (score 1 [5% percentile: 1; 95% percentile: 3] vs score 2 [5% percentile: 1; 95% percentile: 4], P < 0.05, respectively). No significant differences were seen in image noise (score 3 [5% percentile: 2; 95% percentile: 4], P > 0.05, respectively) and image quality (score 2 [5% percentile: 1; 95% percentile: 3], P > 0.05, respectively). In addition, no increase in artifacts was found when employing vContrast (P > 0.05). Artificial image appearance was slightly increased on vContrast images (score 1 [5% percentile: 1; 95% percentile: 1] vs score 1 [5% percentile: 1; 95% percentile: 2], P > 0.05, respectively). A total of 15 CT slices imaging PE in different regions of the pulmonary artery tree (central, segmental, subsegmental) were included in the subjective image analysis. By taking all radiologists together, 87.5% of PEs were detected on standard images, whereas 91.7% of emboli were found when employing vContrast. The inter-reader agreement of the subjective image analysis was good for all three observers with 0.656, 0.717, and 0.680. DISCUSSION In our study, we evaluated the post-processing algorithm vContrast to enhance the contrast in CT acquisitions of the 3

Academic Radiology, Vol ■, No ■■, 2016

MUENZEL ET AL

TABLE 1. Mean CT Values, SNR, and CNR of the Different Segments of the Pulmonary Artery Tree on Standard and vContrast Images CT Value (HU)

Main PA Left PA Right PA Right upper lobe PA Left lower lobe PA

SNR

CNR

Standard

vContrast

P Value

Standard

vContrast

P Value

Standard

vContrast

P Value

165.90 ±38.95 160.02 ±35.73 157.24 ±34.60 183.73 ±129.61 170.39 ±41.89

284.51 ±42.58 279.05 ±44.83 276.76 ±46.09 274.51 ±45.28 287.17 44.09

<0.01

11.46 ±6.11 10.99 ±5.48 10.86 ±5.73 12.89 6.61 11.72 ±6.02

17.42 ±6.03 17.13 ±6.15 17.03 ±6.31 16.77 ±5.33 17.74 ±6.80

<0.01

8.36 ±4.98 7.89 ±4.35 7.76 ±4.58 9.79 ±5.33 8.62 ±4.89

14.66 ±5.24 14.37 ±5.36 14.27 ±5.50 14.01 ±4.51 14.97 ±5.96

<0.01

<0.01 <0.01 <0.01 <0.01

<0.01 <0.01 <0.05 <0.01

<0.01 <0.01 <0.05 <0.01

CNR, contrast-to-noise ratio; CT, computed tomography; HU, Hounsfield units; PA, pulmonary artery; SNR, signal-to-noise ratio.

Figure 3. Computed tomography values of the embolus and the vessel lumen on standard and vContrast images of the patients with pulmonary embolism. The mean difference in Hounsfield units between the contrast-filled vessel lumen and the embolus was increased using vContrast, resulting in an increased contrast-to-embolus ratio of 5.7 in vContrast versus 3.7 in standard images. Figure 2. Computed tomography (CT) values of the main pulmonary arteries (PA) and the different tissues of the chest on standard and vContrast images. Contrast opacification was significantly increased in the main PA. However, CT values of the muscle, fat, and bone showed no significant changes using vContrast. * Statistically significant difference, P > 0.05.

pulmonary arteries in a clinical setting. In all patients with suspected PE, the examination was planned as a contrast enhancement CT angiogram of the pulmonary arteries, but sufficient contrast filling of the pulmonary arteries failed. We could show that vContrast is a feasible post-processing tool to improve image quality and diagnostic value in misarranged CT angiograms of the pulmonary arteries. The SNR and CNR were improved, whereas image noise and the incidence of artifacts remained unaffected. Subjective image assessment demonstrated improved diagnostic confidence with regard to PE. Because in radiology departments around the world CT examinations of the pulmonary arteries are a common imaging protocol, it is of special importance to establish a robust tech4

nique for this diagnostic imaging task. During the last decade, CTA has replaced interventional angiography as the reference standard for detecting or ruling out PE (4,5,13–15). Nowadays, CTA is a well-established tool and an integral part of the diagnostic pathway for patients with suspected PE (6,7). However, it is of special importance to achieve optimal contrast enhancement of the pulmonary arteries. There are several studies dealing with different techniques for improved coordination of intravenous contrast administration and image acquisition. Kerl et al. considered test bolus and bolus tracking techniques as equivalent to homogenous opacification of the pulmonary arteries (16). Saade et al. presented a patientspecific approach to administration of contrast agent for improved visualization of the pulmonary vasculature (17). In addition, specific protocols for contrast opacification in dualenergy CTA were established (8,18,19). Nevertheless, there are several factors that may cause misdiagnosis of PE, eg, patient-related, technical, anatomic, or pathologic (20). In several patients, vessel opacification is

Academic Radiology, Vol ■, No ■■, 2016

IMPROVED CONTRAST ENHANCEMENT IN PE CTA

Figure 4. Pulmonary embolism of a segmental artery of the right lower lobe (patient 1, [a] and [b]) and at the bifurcation of the pulmonary artery of the left upper lobe (patient 2, [c] and [d]). The images on the left show suboptimal contrast opacification of computed tomography angiography. Using vContrast (b and d), there is a significant improvement in the visualization of pulmonary embolism, and the embolus can be depicted more clearly within the contrast-filled vessel lumen.

suboptimal for diagnostic evaluation of the pulmonary arteries. For example, deep breathing may result in a Valsalva maneuver, and non-contrasted blood from the inferior vena cava will fill the right atrium and right ventricle and consecutively the pulmonary arteries. Insufficient bolus tracking, delayed image acquisition, and heart failure are further possible causes of impaired contrast opacification. CT angiograms with insufficient contrast filling of the pulmonary arteries may require a repetition of the CT scan. This translates to a double radiation exposure for the patient, as well as a double amount of contrast agent. This is particularly crucial in patients with renal failure, young patients, or patients with a low probability of PE (rule-out diagnostics). Niemann et al. assumed a low absolute organ-specific risk of cancer incidence and cancer mortality for a single chest CTA for PE, but substantial risks in relative cumulative analysis for young patients (21). In these patients, vContrast may help improve image quality of suboptimal CT datasets, allowing for a diagnostic interpretation. Bendik et al. showed a significant improvement of detectability of hepatocellular carcinoma (HCC) liver lesions using vContrast (22). In PE examinations, an increase of the ratio of HUs of the (low-)contrast-filled vessel lumen and the embolus will amend the diagnostic value of those CT examinations. Lowering radiation dose in CT examinations is a hot topic in the CT community (23–26). However, lowering the amount of contrast media is of special importance as well, but is usually neglected in scientific discussions. Contrast media load on individual patients can result in significant side effects, notably renal complications especially in elderly patients or patients with preexisting renal dysfunction (27–30). The use of a high contrast dose is associated with an increased risk of contrastinduced nephropathy (25,26). As CT use increases, so will contrast load effects in the population. Further, with a body

weight-dependent contrast load and a growing number of obese individuals (currently represent more than one-third of US adults), a growing number of patients with side effects can be expected in the near future, causing a further increase in cost for the public health sector. Thus, it seems important if not imperative that efforts be made to reduce contrast load in CT studies. In this context, vContrast will help in a significant reduction of contrast material while maintaining the diagnostic quality for evaluation of pulmonary arteries. Therefore, further studies will be necessary to determine the minimum amount of injected contrast material for CT examinations using vContrast. In our study, the CT values of the lumen of the main pulmonary artery were significantly increased by vContrast, whereas no significant changes in CT attenuation of the emboli were seen. In addition, there was no increase of artifacts, and the CT values of unenhanced tissue like subcutaneous fat, muscle, and bone showed no changes between unprocessed and vContrast datasets. However, anatomic structures with CT values within the thresholds of vContrast may be enhanced too, and this may lead to misinterpretation. Therefore, we are of the opinion that vContrast should not be used as a standalone technique, but offers an additional diagnostic value for the assessment of the vessel structures. In addition, great potential can be foreseen in the reduction of the amount of contrast agent, especially in patients with renal insufficiency. Hence, it might be possible to considerably decrease the injection dose of iodine contrast agent while maintaining diagnostic quality in the CTA of the pulmonary artery, and also CT angiograms of the aorta, coronary arteries, or abdominal vessels. In future clinical studies, the diagnostic performance of low-dose CTA combined with the application of vContrast needs to be evaluated for specific clinical indications. There are several studies that evaluated the image quality of CTA examinations of the pulmonary 5

MUENZEL ET AL

arteries with reduced amount of iodine contrast agent. They proved diagnostic quality in high pitch pulmonary CTA even for ultra low-dose examinations with application of 40 mL or even 20 mL of contrast agent (31,32). In conclusion, we believe that the main goal of CT imaging of the pulmonary vessels remains an optimized time management for excellent contrast opacification of the pulmonary arteries. However, vContrast is intended to be a complement to the original examination dataset for improved detectability of PE. So we recommend vContrast as a feasible additive tool for diagnostic evaluation of suboptimal contrastenhanced pulmonary arteries.

REFERENCES 1. Kakkar N, Vasishta RK. Pulmonary embolism in medical patients: an autopsy-based study. Clin Appl Thromb Hemost 2008; 14:159– 167. 2. Tsai J, Grosse SD, Grant AM, et al. Correlates of in-hospital deaths among hospitalizations with pulmonary embolism: findings from the 2001– 2008 National Hospital Discharge Survey. PLoS ONE 2012; 7:e34048. 3. Schoepf UJ, Goldhaber SZ, Costello P. Spiral computed tomography for acute pulmonary embolism. Circulation 2004; 109:2160–2167. 4. Schoepf UJ, Costello P. CT angiography for diagnosis of pulmonary embolism: state of the art. Radiology 2004; 230:329–337. 5. Blanke P, Apfaltrer P, Ebersberger U, et al. CT detection of pulmonary embolism and aortic dissection. Cardiol Clin 2012; 30:103–116. 6. Stein PD, Woodard PK, Weg JG, et al. Diagnostic pathways in acute pulmonary embolism: recommendations of the PIOPED II investigators. Radiology 2007; 242:15–21. 7. Zhang LJ, Lu GM, Meinel FG, et al. Computed tomography of acute pulmonary embolism: state-of-the-art. Eur Radiol 2015; 25:2547–2557. 8. Hansmann J, Fink C, Jost G, et al. Impact of iodine delivery rate with varying flow rates on image quality in dual-energy CT of patients with suspected pulmonary embolism. Acad Radiol 2013; 20:962–971. 9. Wong GT, Irwin MG. Contrast-induced nephropathy. Br J Anaesth 2007; 99:474–483. 10. Wong PCY, Li Z, Guo J, et al. Pathophysiology of contrast-induced nephropathy. Int J Cardiol 2012; 158:186–192. 11. Nash K, Hafeez A, Hou S. Hospital-acquired renal insufficiency. Am J Kidney Dis 2002; 39:930–936. 12. Noël PB, Bendik E, Münzel D, et al. A method for improving iodine contrast enhancement in abdominal computed tomography: experimental study in a pig model. Eur Radiol 2013; 4:985–990. 13. Estrada-Y-Martin RM, Oldham SA. CTPA as the gold standard for the diagnosis of pulmonary embolism. Int J Comput Assist Radiol Surg 2011; 6:557–563. 14. Sadigh G, Kelly AM, Cronin P. Challenges, controversies, and hot topics in pulmonary embolism imaging. AJR Am J Roentgenol 2011; 196:497– 515.

6

Academic Radiology, Vol ■, No ■■, 2016

15. Mayo J, Thakur Y. Pulmonary CT angiography as first-line imaging for PE: image quality and radiation dose considerations. AJR Am J Roentgenol 2013; 200:522–528. 16. Kerl JM, Lehnert T, Schell B, et al. Intravenous contrast material administration at high-pitch dual-source CT pulmonary angiography: test bolus versus bolus-tracking technique. Eur J Radiol 2012; 81:2887–2891. 17. Saade C, Bourne R, El-Merhi F, et al. An optimised patient-specific approach to administration of contrast agent for CT pulmonary angiography. Eur Radiol 2013; 23:3205–3212. 18. Yuan R, Shuman WP, Earls JP, et al. Reduced iodine load at CT pulmonary angiography with dual-energy monochromatic imaging: comparison with standard CT pulmonary angiography–a prospective randomized trial. Radiology 2012; 262:290–297. 19. Nance JW, Jr, Henzler T, Meyer M, et al. Optimization of contrast material delivery for dual-energy computed tomography pulmonary angiography in patients with suspected pulmonary embolism. Invest Radiol 2012; 47:78–84. 20. Wittram C, Maher MM, Yoo AJ, et al. CT angiography of pulmonary embolism: diagnostic criteria and causes of misdiagnosis. Radiographics 2004; 24:1219–1238. 21. Niemann T, Zbinden I, Roser H, et al. Computed tomography for pulmonary embolism: assessment of a 1-year cohort and estimated cancer risk associated with diagnostic irradiation. Acta Radiol 2013; 54:778– 784. 22. Bendik E, Noël PB, Münzel D, et al. Evaluation of a method for improving the detection of hepatocellular carcinoma. Eur Radiol 2014; 24:250– 255. 23. Noël PB, Renger B, Fiebich M, et al. Does iterative reconstruction lower CT radiation dose: evaluation of 15,000 examinations. PLoS ONE 2013; 26:e81141. 24. Noël PB, Fingerle AA, Renger B, et al. Initial performance characterization of a clinical noise-suppressing reconstruction algorithm for MDCT. AJR Am J Roentgenol 2011; 197:1404–1409. 25. Marin D, Nelson RC, Schindera ST, et al. Low-tube-voltage, high-tubecurrent multidetector abdominal CT: improved image quality and decreased radiation dose with adaptive statistical iterative reconstruction algorithm– initial clinical experience. Radiology 2010; 254:145–153. 26. Hara AK, Paden RG, Silva AC, et al. Iterative reconstruction technique for reducing body radiation dose at CT: feasibility study. AJR Am J Roentgenol 2009; 193:764–771. 27. Aly O, Vakil E, Kousha M, et al. Frequency of contrast induced nephropathy in patients who undergo computed tomography pulmonary angiography for pulmonary embolism. Chest 2014; 145:524A. 28. Solomon R, Barrett B. Follow-up of patients with contrast- induced nephropathy. Kidney Int Suppl 2006; 100:S46–S50. 29. Kooiman J, Seth M, Share D, et al. The association between contrast dose and renal complications post PCI across the continuum of procedural estimated risk. PLoS ONE 2014; 13:e90233. 30. Barrett BJ, Parfrey PS. Clinical practice. Preventing nephropathy induced by contrast medium. N Engl J Med 2006; 354:379–386. 31. Lu GM, Luo S, Meinel FG, et al. High-pitch computed tomography pulmonary angiography with iterative reconstruction at 80 kVp and 20 mL contrast agent volume. Eur Radiol 2014; 24:3260–3268. 32. Li X, Ni QQ, Schoepf UJ, et al. 70-kVp high-pitch computed tomography pulmonary angiography with 40 mL contrast agent: initial experience. Acad Radiol 2015; 22:1562–1570.