Document Detail

A novel iterative reconstruction algorithm allows reduced dose multidetector-row CT imaging of mechanical prosthetic heart valves.
Jump to Full Text
MedLine Citation:
PMID:  22002686     Owner:  NLM     Status:  MEDLINE    
Multidetector-row CT is promising for prosthetic heart valve (PHV) assessment but retrospectively ECG-gated scanning has a considerable radiation dose. Recently introduced iterative reconstruction (IR) algorithms may enable radiation dose reduction with retained image quality. Furthermore, PHV image quality on the CT scan mainly depends on extent of PHV artifacts. IR may decrease streak artifacts. We compared image noise and artifact volumes in scans of mechanical PHVs reconstructed with conventional filtered back projection (FBP) to lower dose scans reconstructed with IR. Four different PHVs (St. Jude, Carbomedics, ON-X and Medtronic Hall) were scanned in a pulsatile in vitro model. Ten retrospectively ECG-gated CT scans were performed of each PHV at 120 kV, 600 mAs (high-dose CTDI(vol) 35.3 mGy) and 120 kV, 300 mAs (low-dose CTDI(vol) 17.7 mGy) on a 64 detector-row scanner. Diastolic and systolic images were reconstructed with FBP (high and low-dose) and the IR algorithm (low-dose only). Hypo- and hyperdense artifact volumes were determined using two threshold filters. Image noise was measured. Mean hypo- and hyperdense artifact volumes (mm(3)) were 1,235/5,346 (high-dose FBP); 2,405/6,877 (low-dose FBP) and 1,218/5,333 (low-dose IR). Low-dose IR reconstructions had similar image noise compared to high-dose FBP (16.5 ± 1.7 vs. 16.3 ± 1.6, mean ± SD, respectively, P = 1.0). IR allows ECG-gated PHV imaging with similar image noise and PHV artifacts at 50% less dose compared to conventional FBP in an pulsatile in vitro model.
Jesse Habets; Petr Symersky; Bas A J M de Mol; Willem P Th M Mali; Tim Leiner; Ricardo P J Budde
Related Documents :
23182696 - An information hypothesis for the evolution of homeostasis.
6639906 - Lacrimal scintigraphy. iii. physiological aspects of lacrimal drainage.
12515876 - The third circulation: radionuclide lymphoscintigraphy in the evaluation of lymphedema.
9397456 - Mr angiography of the portal venous system: techniques, interpretation, and clinical ap...
23042526 - Quantitative fluorescent speckle microscopy (qfsm) to measure actin dynamics.
18276236 - Line and boundary detection in speckle images.
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2011-10-15
Journal Detail:
Title:  The international journal of cardiovascular imaging     Volume:  28     ISSN:  1875-8312     ISO Abbreviation:  Int J Cardiovasc Imaging     Publication Date:  2012 Aug 
Date Detail:
Created Date:  2012-10-11     Completed Date:  2013-03-22     Revised Date:  2013-06-27    
Medline Journal Info:
Nlm Unique ID:  100969716     Medline TA:  Int J Cardiovasc Imaging     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1567-75     Citation Subset:  IM    
Department of Radiology, University Medical Center Utrecht, PO Box 85500, E01.132, 3508 GA Utrecht, The Netherlands.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Heart Valve Prosthesis*
Models, Cardiovascular
Multidetector Computed Tomography* / instrumentation
Phantoms, Imaging
Prosthesis Design
Pulsatile Flow
Radiation Dosage
Radiographic Image Interpretation, Computer-Assisted / methods*
Signal-To-Noise Ratio

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

Full Text
Journal Information
Journal ID (nlm-ta): Int J Cardiovasc Imaging
Journal ID (iso-abbrev): Int J Cardiovasc Imaging
ISSN: 1569-5794
ISSN: 1875-8312
Publisher: Springer Netherlands, Dordrecht
Article Information
Download PDF
© The Author(s) 2011
Received Day: 2 Month: 5 Year: 2011
Accepted Day: 30 Month: 9 Year: 2011
Electronic publication date: Day: 15 Month: 10 Year: 2011
pmc-release publication date: Day: 15 Month: 10 Year: 2011
Print publication date: Month: 8 Year: 2012
Volume: 28 Issue: 6
First Page: 1567 Last Page: 1575
ID: 3463798
PubMed Id: 22002686
Publisher Id: 9954
DOI: 10.1007/s10554-011-9954-7

A novel iterative reconstruction algorithm allows reduced dose multidetector-row CT imaging of mechanical prosthetic heart valves
Jesse Habets1 Address: +31-887556689 +31-302581098
Petr Symersky2
Bas A. J. M. de Mol2
Willem P. Th. M. Mali1
Tim Leiner1
Ricardo P. J. Budde1
1Department of Radiology, University Medical Center Utrecht, P.O. Box 85500, E01.132, 3508 GA Utrecht, The Netherlands
2Department of Cardiothoracic Surgery, Academic Medical Center, Amsterdam, The Netherlands


Multidetector-row CT (MDCT) is a promising imaging technique for prosthetic heart valve (PHV) assessment. It provides complementary information to echocardiography and fluoroscopy in patients with suspected PHV dysfunction [15]. MDCT scanning of PHVs has been mainly performed with retrospective ECG-gated scan protocols which enable dynamic PHV leaflet assessment and imaging of periprosthetic anatomy in both systole and diastole [6]. In an effort to minimize PHV-related artifacts and to improve image quality, some authors have adjusted exposure parameters by increasing either tube voltage (140 kV) [7] or tube current (800–1,000 mAs) [3]. However, these adjustments cause an increase in radiation exposure, which is already substantial with retrospective ECG-gating (up to 20 mSv) [3, 7]. For the use of MDCT in clinical practice, it is important to reduce radiation dose while retaining the ability to assess PHV leaflet motion and anatomy in systole and diastole.

Currently, MDCT uses filtered back projection (FBP) for image reconstruction from raw data [8]. Alternative iterative image reconstruction algorithms have been available for a long time and used in positron emission tomography (PET) and single photon emission computed tomography (SPECT) [9, 10]. Recently, technical developments and increased computational power have allowed the use of novel iterative reconstruction (IR) algorithms for multislice CT image reconstruction [8, 11, 12]. Theoretically these new reconstruction algorithms allow imaging at reduced dose with retained image quality [8]. Furthermore, these new reconstruction algorithms may reduce PHV artifacts as well. At present, it is unknown whether application of these iterative reconstruction algorithms in MDCT scans of PHVs is beneficial for reduction of radiation dose and PHV induced artifacts.

The purpose of the current study was to assess whether IR allows PHV imaging with reduced radiation dose without increased image noise. In addition, we assessed the effect of using IR on the presence and extent of hypo- and hyperdense PHV artifacts in both systolic and diastolic phases.


Four different mechanical PHVs including three bileaflet valves: St Jude (SJ, St Jude Medical Inc., St Paul MN, 27 mm), Carbomedics (CM, Carbomedics Inc., Austin, TX, 21 mm), ON-X (ON-X, ON-X Life Technologies Inc., Austin, TX, 27 mm) and one tilting disc valve: Medtronic Hall (MH, Medtronic Inc., Minneapolis MN, 27 mm) were inserted in a pulsatile in vitro model which was described in detail before [13]. In brief, this model consists of a pump-driven mock loop connected to a custom-made polymethyl methacrylate (PMMA) valve chamber via an inlet and outlet portion. The valve chamber used in this study housed a central mounting ring placed under a 45-degree angle to the CT gantry to simulate the normal in vivo aortic position. The different PHVs were inserted in this mounting ring. The valve chamber was placed in a commercially available anthromorphic thoracic phantom (QRM GmbH, Möhrendorf, Germany) to simulate radiation absorption and scattering from the human thorax. A computer controlled piston-pump produced 60 pulses per minute and emitted an artificial ECG signal, which was read by the CT scanner. Water was used for perfusion in this study. No contrast administration was performed. The valve chamber within the thoracic phantom was positioned in the 64 detector-row CT scanner (Fig. 1).

CT scanner

For each PHV type, twenty scans were performed: ten at 120 kV, 600 mAs (high dose) and ten at 120 kV, 300 mAs (low dose). Scanning was performed on a 64 detector-row CT scanner (Brilliance 64, Philips Medical Systems, Cleveland, Ohio). An additional 15 scans at both scan settings were performed of the St Jude PHV for image noise measurements. Scanning parameters were based on the clinical scanning protocol for retrospectively ECG-gated MDCT coronary angiography: 64 × 0.625 mm collimation, 0.42 s rotation time, pitch of 0.2 and a matrix size of 512 × 512 pixels. Scan length was identical for each scan at 100 mm. Total DLP and CTDIvol for each scan as displayed on the scanner console were recorded.

Image reconstruction

Images of 0.9 mm thickness with 0.45 mm increment were reconstructed using a cardiac B filter at two phases of the ECG interval corresponding to diastolic (closed valve) and systolic (open valve) phases. For the high-dose scans (120 kV, 600 mAs), raw data were reconstructed using standard FBP. The IR (iDose, Philips Healthcare, Best, The Netherlands) applies a maximum likelihood denoising algorithm based on Poisson statistics on the raw projection data. Subsequently, reconstructed images are compared to optimal anatomical structures in image space, allowing noise reduction without altering the characteristics and overall appearance of the initial image. Besides noise reduction, iDose may decrease streak artifacts. iDose allows reconstruction of images at seven different levels with level one having the least influence on image reconstruction and level seven having most influence.

From the raw data of the low-dose scans performed at 120 kV, 300 mAs two different image sets were reconstructed: one image set using standard FBP and one using level 4 IR. Level 4 iDose theoretically leads to image denoising by 29%. A dose reduction from 600 to 300 mAs (factor 2 decrease) would theoretically result in a noise increase by a factor 1.41 (√2) [14]. Applying level 4 iDose would theoretically reduce noise in the low-dose (300 mAs) images to the level of the high-dose scans (noise increase by factor 1.41 due to lower mAs setting, and subsequent reduction by 29% due to IR).

Image analysis and artifact measurement

Images were transferred to a dedicated workstation (Extended Brilliance Workstation, Philips Medical Systems, Philips, Best, The Netherlands) for analysis. On the workstation three-dimensional volume-rendered images were reconstructed from which the thoracic phantom was digitally excised. Subsequently, volumetric threshold filters were used for measurement of hyper- and hypodense artifacts emanating from the PHV (Fig. 2). For hypodense artifacts, the upper limit of the threshold value was established by measuring the Hounsfield Unit (HU) values of the least dense periprosthetic structure (water) and subtracting approximately 3 times the standard deviation (SD) of the CT water density. The threshold for hyperdense artifacts was derived from the CT density of the surrounding PMMA structure and adding approximately 3 times the SD of the HU measurement. According to a method described elsewhere [15], threshold filters were made to include all voxels below the threshold for the hypodense artifacts and above the threshold for the hyperdense artifacts. Thresholds used in this experiment were set at ≤50 and ≥175 HU for hypo- and hyperdense artifacts, respectively. At these settings the ≤50 HU filter measures the volume of hypodense artifacts, and the ≥175 HU filter measures the volume of hyperdense artifacts, including the PHV ring and leaflets.

Image noise (SD of the HU measurement) was measured in the 25 scans of the St Jude PHV using a circular region of interest (ROI, diameter 10 mm) in a homogenous section of the PMMA structure in the valve chamber on identical locations in the different reconstructions (Fig. 3).

Data analysis

Data were analyzed using SPSS software (SPSS Statistics Version 15.0, SPSS Inc, Chicago, IL) and presented as means ± SD. For each PHV type, a two-way repeated measures analysis was performed with reconstruction algorithm (120 kV, 600 mAs FBP; and 120 kV, 300 mAs FBP and 120 kV, 300 mAs iDose level 4) and reconstruction phase (systolic or diastolic) defined as within-subject factors. Post-hoc pairwise testing with Bonferroni correction was performed to compare different reconstruction algorithms and reconstruction phases. Mean image noise was compared for the different reconstruction algorithms in a repeated measures analysis. Statistical significance was defined as a P value <0.05.

Dose reduction

For all low-dose scans, CTDIvol and DLP were equal (17.7 and 236.5 mGy, respectively). For the high-dose scans, CTDIvol and DLP were 35.3 and 473.4 mGy respectively and equal for all scans. Radiation dose for low-dose scans was 50% of high-dose scans.

Image noise

Mean image noise in the high-dose (120 kV, 600 mAs) scans (16.3 ± 1.6 HU) was 29.7% lower compared to the low-dose (120 kV, 300 mAs) scans (23.2 ± 2.3 HU) reconstructed with FBP. The difference was statistically significantly (P < 0.001). Low-dose scans reconstructed with iDose level 4 demonstrated similar image noise compared to high-dose scans reconstructed with FBP (16.5 ± 1.7 HU vs. 16.3 ± 1.6 HU, respectively, P = 1.0). Low-dose scans reconstructed with iDose level 4 had lower image noise compared to low-dose scans reconstructed with FBP (P < 0.001) (Table 1, Fig. 4).

PHV artifact volumes

Mean hypo- and hyperdense artifact volumes for different reconstruction algorithms are shown in Table 2 and classified per PHV type and reconstruction phase in Table 3. Boxplots of mean hypodense and hyperdense PHV artifact volumes are shown in Fig. 5a and b. Repeated measures analyses were performed for each PHV type. For all PHV types, hypo- and hyperdense artifact volumes were significantly higher at low-dose scans compared to high dose scans reconstructed with FBP (P < 0.001).

For all PHV types, hypodense artifact volumes were similar (ON-X PHVs P = 0.55 and other PHVs P = 1.0, respectively) for the high-dose scans reconstructed with FBP when compared to low-dose scans reconstructed with IR. Hyperdense artifacts were similar for the high-dose scans reconstructed with FBP when compared to low-dose scans reconstructed with IR (St Jude P = 0.95, all other valves P = 1.0).

Hypodense artifact volumes were significantly smaller in the diastolic (closed valve) phase compared to the systolic (opened valve) phase for St Jude PHVs (P = 0.003); Medtronic Hall PHVs (P < 0.001); Carbomedics PHVs (P < 0.001) and ON-X PHVs (P < 0.001) (Table 3). Hyperdense artifact volumes were also significant smaller in the diastolic phase as opposed to the systolic phase for Medtronic Hall PHVs (P < 0.001), Carbomedics PHVs (P = 0.002), and ON-X PHVs (P < 0.001). The St Jude PHV demonstrated similar hyperdense artifacts (P = 0.074).


The principal finding of this study is that iterative reconstruction allows different PHVs in a pulsatile in vitro model to be visualized with similar image noise and artifacts at a considerably reduced radiation dose (50% CTDIvol and DLP) compared to conventional acquisitions reconstructed with FBP.

In a recent editorial [8] Fleischman and Boas provided an insightful summary of the history and principles underlying iterative reconstruction. They explain that reconstruction of raw CT data is currently performed using the FBP algorithm on virtually all commercially available CT systems [8]. The principle of FBP relies on the exact mathematical relationship between the measured X-ray attenuation in the projection data and the pixel values in the corresponding image. FPB assumes exact data. In reality, however, projection data from the CT scanner are noisy. The filter used in FBP increases image noise [8]. Iterative reconstruction utilizes statistical models to improve signal to noise with each iteration. The main advantage of iterative reconstruction compared to FBP is the reduced image noise. Furthermore, iterative reconstruction reduces metal streak artifacts [8, 16].

Initial clinical results with iterative reconstruction are encouraging. Iterative reconstruction algorithms have been shown to decrease image noise and improve image quality of coronary segments in patients that underwent cardiac CTA for clinical indications at lower radiation dose [11, 12]. Nevertheless, little is known about the application of iterative reconstruction algorithms in MDCT imaging of PHVs. We evaluated the effect of a novel IR algorithm (iDose, Philips Medical Systems, Best, The Netherlands) that performs iterative processing in both the projection and image domains on the image noise at a considerable lower radiation dose. Additionally, the effect of IR on the artifacts typically associated with MDCT imaging of PHV was evaluated.

The amount of noise in CT images depends on several factors: section collimation, acquisition time, and tube current [14]. Theoretically a decrease in tube current by a factor 2 leads to an increase in image noise by the square root of 2 (1.41), given that all other scanning parameters are kept constant [14]. By reconstructing images acquired with half the tube current using iDose level 4 IR, we expected, and found, noise to be reduced to the level of the initial tube current setting (Table 1). When low dose scans were reconstructed with iDose level 4, mean image noise was again similar to the high-dose scans (Table 1). The 50% radiation dose reduction (CTDIvol/DLP 35.3/473.4 mGy vs. 17.7/236.5 mGy) is mainly compensated for by the improvement of spatial resolution due to the denoising properties of the iterative reconstruction algorithm (Fig. 6). Hypo- and hyperdense artifacts were comparable between high dose scans with FBP and low dose scans reconstructed with iDose level 4 IR (Fig. 7). IR performed similar in the systolic and diastolic phase for the reduction of PHV artifacts (Table 3).


This study has limitations. First, the study was performed in an in-vitro model. In this model, the normal annular motion present in the human heart, which may induce additional artifacts, is absent. However, strictly standardized conditions are essential for the comparison between different reconstruction algorithms. Second, no contrast medium was administered. The usage of diluted contrast would have represented a more realistic situation. However, in patients contrast timing, amount and enhancement may differ widely between centers. We used water as perfusate to standardize the experimental set-up. Furthermore we do not expect the artifacts generated by the PHV itself to be influenced by contrast material. Third, no PHV pathology was imaged in this in vitro model. Therefore, diagnostic accuracy cannot be verified. Artifacts are the main reasons for non-assessable PHVs. These artifacts were similar for the iterative reconstructions compared to the high-dose scans. Therefore, our assumption is that pathology can be equally well detected. Fourth, because hypodense artifact volumes (≤50 HU filter) did not only include hypodense PHV artifacts but also image noise, we cannot rule out an influence on the results. However, the appearance of hypodense artifacts was similar for high dose scans reconstructed with FBP and low dose scans reconstructed with IR (Fig. 7). Fifth, we scanned only with one tube voltage setting (120 kV). In our institution, 120 kV is commonly used for PHV CT imaging. Experiments with different kV settings (100, 140 kV) would be interesting to optimize PHV CT scan protocols. Sixth, image quality was not assessed. Continuous outcome measures (3D artifact volumes and image noise) were preferred to quantify the effect of iterative reconstruction algorithms on image quality because of the more objective nature of these outcome measures. Further clinical evaluation in patients with PHVs is required to determine if PHV imaging with IR can replace standard FBP at a lower radiation dose. In prospective clinical studies, other patient related factors (e.g. body mass index) which can influence CT image quality have to be taken into account. Besides the novel IR algorithms other dose reducing techniques (e.g. prospective ECG triggering) have to be evaluated for PHV imaging. At present, retrospectively ECG-gated scanning remains essential to obtain dynamic information in both systolic and diastolic phases which is required for adequate leaflet motion assessment. Sixth, only one heart rate (60 bpm) was explored. Higher heart rates and arrhythmia may influence PHV CT image quality. Wide area detector CT scanners (256 slice or higher) enable prospective data acquisition in one or only several heart beats [17, 18]. The more efficient radiation use in prospective scanning compared to retrospective scanning and the lower or 0 pitch may influence PHV generated artifacts. On the other hand this may improve image quality compared to 64 slice CT scanning. High-pitch spiral scanning is an interesting alternative for image acquisition because of the decreased radiation exposure [19, 20]. Low heart rates (<60 bpm) are required to allow high-pitch spiral scanning. However, most patients with suspected PHV dysfunction have high heart rates or rhythm disorders and contraindications for β-blockers which preclude high-pitch spiral scanning. In further prospective studies, a multivariate approach including different heart rates and different scanner types would be an interesting research topic. Finally, we investigated just one level of iterative reconstruction. It is possible that lower or higher levels of IR could have led to different results.


In conclusion, MDCT imaging using iterative reconstruction enables in vitro imaging of different PHV types at 50% lower radiation dose with similar image noise and hypo- and hyperdense PHV artifacts.

We would like to thank Karin Rijnbach, Multimedia specialist, Department of Digital Photography, University Medical Center Utrecht for her help with edition of the figures. The present study was supported by a grant of The Netherlands Heart Foundation [Grant number 2009B014].

Conflict of interest


Open Access

This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

1.. Tsai IC,Lin YK,Chang Y,et al. Correctness of multi-detector-row computed tomography for diagnosing mechanical prosthetic heart valve disorders using operative findings as a gold standardEur RadiolYear: 20091985786710.1007/s00330-008-1232-219037643
2.. Symersky P,Budde RP,Mol BA,et al. Comparison of multidetector-row computed tomography to echocardiography and fluoroscopy for evaluation of patients with mechanical prosthetic valve obstructionAm J CardiolYear: 20091041128113410.1016/j.amjcard.2009.05.06119801036
3.. Konen E,Goitein O,Feinberg MS,et al. The role of ECG-gated MDCT in the evaluation of aortic and mitral mechanical valves: initial experienceAm J RoentgenolYear: 2008191263110.2214/AJR.07.295118562720
4.. Feuchtner GM,Stolzmann P,Dichtl W,et al. Multislice computed tomography in infective endocarditis: comparison with transesophageal echocardiography and intraoperative findingsJ Am Coll CardiolYear: 20095343644410.1016/j.jacc.2008.01.07719179202
5.. Habets J,Budde RP,Symersky P,et al. Diagnostic evaluation of left-sided prosthetic heart valve dysfunctionNat Rev CardiolYear: 2011846647810.1038/nrcardio.2011.7121587215
6.. Habets J,Symersky P,Herwerden LA,et al. Prosthetic heart valve assessment with multidetector-row CT: imaging characteristics of 91 valves in 83 patientsEur RadiolYear: 2011211390139610.1007/s00330-011-2068-821279515
7.. Chenot F,Montant P,Goffinet C,et al. Evaluation of anatomic valve opening and leaflet morphology in aortic valve bioprosthesis by using multidetector CT: comparison with transthoracic echocardiographyRadiologyYear: 201025537738510.1148/radiol.000008229420019133
8.. Fleischmann D,Boas FE. Computed tomography—old ideas and new technologyEur RadiolYear: 20112151051710.1007/s00330-011-2056-z21249371
9.. Lange K,Carson R. EM reconstruction algorithms for emission and transmission tomographyJ Comput Assist TomogrYear: 198483063166608535
10.. Shepp LA,Vardi Y. Maximum likelihood reconstruction for emission tomographyIEEE Trans Med ImagingYear: 1982111312210.1109/TMI.1982.430755818238264
11.. Leipsic J,LaBounty TM,Heilbron B,et al. Estimated radiation dose reduction using adaptive statistical iterative reconstruction in coronary CT angiography: the ERASIR studyAm J RoentgenolYear: 201019565566010.2214/AJR.10.428820729443
12.. Leipsic J,LaBounty TM,Heilbron B,et al. Adaptive statistical iterative reconstruction: assessment of image noise and image quality in coronary CT angiographyAm J RoentgenolYear: 201019564965410.2214/AJR.10.428520729442
13.. Symersky P,Budde RPJ,Prokop M,et al. Multidetector-row computed tomography imaging characteristics of mechanical prosthetic valvesJ Heart Valve DisYear: 20112021622221560825
14.. Prokop M. Prokop M,Galanski MRadiation dose and image qualitySpiral and multislide computed tomography of the bodyYear: 2003StuttgartThieme143144
15.. Schaaf I,Leeuwen M,Vlassenbroek A,et al. Minimizing clip artifacts in multi CT angiography of clipped patientsAm J NeuroradiolYear: 200627606616418357
16.. Boas FE,Fleischmann D. Evaluation of two iterative techniques for reducing metal artifacts in computed tomographyRadiologyYear: 201125989490210.1148/radiol.1110178221357521
17.. Rybicki FJ,Otero HJ,Steigner ML,et al. Initial evaluation of coronary images from 320-detector row computed tomographyInt J Cardiovasc ImagingYear: 20082453554610.1007/s10554-008-9308-218368512
18.. Weigold WG,Olsezewski ME,Walker MJ. Low-dose prospectively gated 256-slice coronary computed tomographic angiographyInt J Cardiovasc ImagingYear: 20092521723010.1007/s10554-009-9439-0
19.. Achenbach S,Marwan M,Ropers D,et al. Coronary computed tomography angiography with a consistent dose below 1 mSv using prospectively electrocardiogram-triggered high-pitch spiral acquisitionEur HeartYear: 20103134034610.1093/eurheartj/ehp470
20.. Achenbach S,Marwan M,Schepis T,et al. High-pitch spiral acquisition: a new scan mode for coronary CT angiographyJ Cardiovasc Comput TomogrYear: 2009311712110.1016/j.jcct.2009.02.00819332343


[Figure ID: Fig1]
Fig. 1 

Photograph of in vitro pulsatile model in the 64 slice CT-scanner (Brilliance 64, Philips Medical Systems, Cleveland, Ohio)

[Figure ID: Fig2]
Fig. 2 

MDCT image of ON-X Bileaflet PHV. a MDCT image with measured artifacts (blue color), b Frontal plane with 3D volume PHV hypodense artifacts including PHV artifact measurement

[Figure ID: Fig3]
Fig. 3 

MDCT image of St Jude bileaflet PHV. Image noise (SD) is measured with a circular region of interest in a homogenous part of the polymethyl methacrylate (PMMA) structure. Av (average image signal), HU Hounsfield Units, ED external diameter (mm)

[Figure ID: Fig4]
Fig. 4 

Boxplots of image noise for different reconstruction algorithms. 1 120 kV, 600 mAs FBP reconstruction 2 120 kV, 300 mAs FBP reconstruction 3 120 kV, 300 mAs iDose level 4

[Figure ID: Fig5]
Fig. 5 

Boxplots of hypodense (a) and hyperdense (b) PHV artifacts for different reconstruction algorithms. 1 120 kV, 600 mAs FBP reconstruction, 2 120 kV, 300 mAs FBP reconstruction, 3 120 kV, 300 mAs iDose level 4

[Figure ID: Fig6]
Fig. 6 

MDCT image of ON-X Bileaflet PHV. a Frontal plane 120 kV, 600 mAs reconstructed with FBP, b Frontal plane 120 kV 300 mAs reconstructed with FBP, c Frontal plane 120 kV 300 mAs reconstructed with iDose level 4

[Figure ID: Fig7]
Fig. 7 

MDCT image of ON-X Bileaflet PHV. a Frontal plane 120 kV, 600 mAs reconstructed with FBP, b Frontal plane 120 kV, 300 mAs reconstructed with iDose level 4, c Frontal plane with 3D volume PHV hypodense artifacts (120 kV, 600 mAs, BFP), d Frontal plane with 3D volume PHV hypodense artifacts (120kV, 300mAs, iDose level 4)

[TableWrap ID: Tab1] Table 1 

Mean image noise measured in the plexiglass (PMMA) of the perfusion chamber for different reconstruction algorithms

Reconstruction algorithm Image noise PMMA
Mean ± SD
120 kV 600 mAs FBP 16.3 ± 1.6
120 kV 300 mAs FBP 23.2 ± 2.3
120 kV 300 mAs IR level 4 16.5 ± 1.7

FBP filtered back projection, IR iterative reconstruction algorithm

[TableWrap ID: Tab2] Table 2 

Mean artifact volumes (mm3) for hypo- and hyperdense PHV artifacts for different reconstruction algorithms (all PHVs combined diastolic and systolic phases)

Reconstruction algorithm Hypodense artifacts
Mean ± SD
Hyperdense artifacts
Mean ± SD
120 kV 600 mAs FBP 1,235 ± 731 5,346 ± 1,677
120 kV 300 mAs FBP 2,405 ± 1,051 6,877 ± 1,849
120 kV 300 mAs (IR level 4) 1,218 ± 683 5,333 ± 1,663

FBP filtered back projection, IR iterative reconstruction algorithm

[TableWrap ID: Tab3] Table 3 

Hypodense and hyperdense artifacts in systolic and diastolic phase for each PHV type and reconstruction algorithm

Reconstruction algorithm Reconstruction algorithm Hypodense artifacts
Mean ± SD
Hyperdense artifacts
Mean ± SD
Systolic Diastolic Systolic Diastolic
St Jude Bileaflet PHV 120 kV, 600 mAs FBP 1,829 ± 488 1,572 ± 341 7,170 ± 352 7,180 ± 492
120 kV, 300 mAs FBP 2,994 ± 275 2,436 ± 299 8,770 ± 254 8,580 ± 355
120 kV, 300 mAs IR level 4 1,890 ± 208 1,484 ± 208 7,120 ± 253 6,920 ± 294
Carbomedics Bileaflet PHV 120 kV, 600 mAs FBP 630 ± 137 342 ± 43 3,010 ± 175 2,836 ± 125
120 kV, 300 mAs FBP 1,582 ± 232 1,062 ± 147 4,281 ± 318 3,992 ± 153
120 kV, 300 mAs IR level 4 683 ± 167 322 ± 56 3,051 ± 264 2,746 ± 120
ON-X Bileaflet PHV 120 kV, 600 mAs FBP 1,237 ± 216 790 ± 73 5,292 ± 178 5,052 ± 57
120 kV, 300 mAs FBP 2,265 ± 267 1,637 ± 127 6,752 ± 179 6,582 ± 107
120 kV, 300 mAs IR level 4 1,198 ± 138 716 ± 45 5,282 ± 171 5,032 ± 57
Medtronic Hall tilting disc PHV 120 kV, 600 mAs FBP 2,575 ± 433 905 ± 116 6,880 ± 1,001 5,350 ± 196
120 kV, 300 mAs FBP 4,534 ± 564 2,729 ± 283 8,910 ± 928 7,150 ± 268
120 kV, 300 mAs IR level 4 2,385 ± 489 1,068 ± 325 7,010 ± 936 5,500 ± 542

Article Categories:
  • Original Paper

Keywords: Keywords Prosthetic heart valve, Computed tomography, Iterative reconstruction, Artifacts, Image noise, Reconstruction algorithm.

Previous Document:  Supplementing endophyte-infected tall fescue or reed canarygrass with alfalfa or birdsfoot trefoil i...
Next Document:  The usefulness of delayed contrast-enhanced cardiovascular magnetic resonance imaging in differentia...