Publications by authors named "Anne Catrine T Martinsen"

18 Publications

  • Page 1 of 1

Iterative reconstruction improves image quality and reduces radiation dose in trauma protocols; A human cadaver study.

Acta Radiol Open 2021 Oct 18;10(10):20584601211055389. Epub 2021 Nov 18.

Department of Radiology and Nuclear Medicine, Oslo University Hospital Ullevål, Oslo, Norway.

Background: Radiation-related cancer risk is an object of concern in CT of trauma patients, as these represent a young population. Different radiation reducing methods, including iterative reconstruction (IR), and spilt bolus techniques have been introduced in the recent years in different large scale trauma centers.

Purpose: To compare image quality in human cadaver exposed to thoracoabdominal computed tomography using IR and standard filtered back-projection (FBP) at different dose levels.

Material And Methods: Ten cadavers were scanned at full dose and a dose reduction in CTDIvol of 5 mGy (low dose 1) and 7.5 mGy (low dose 2) on a Siemens Definition Flash 128-slice computed tomography scanner. Low dose images were reconstructed with FBP and Sinogram affirmed iterative reconstruction (SAFIRE) level 2 and 4. Quantitative image quality was analyzed by comparison of contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR). Qualitative image quality was evaluated by use of visual grading regression (VGR) by four radiologists.

Results: Readers preferred SAFIRE reconstructed images over FBP at a dose reduction of 40% (low dose 1) and 56% (low dose 2), with significant difference in overall impression of image quality. CNR and SNR showed significant improvement for images reconstructed with SAFIRE 2 and 4 compared to FBP at both low dose levels.

Conclusions: Iterative image reconstruction, SAFIRE 2 and 4, resulted in equal or improved image quality at a dose reduction of up to 56% compared to full dose FBP and may be used a strong radiation reduction tool in the young trauma population.
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http://dx.doi.org/10.1177/20584601211055389DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8619783PMC
October 2021

Improved image quality in abdominal computed tomography reconstructed with a novel Deep Learning Image Reconstruction technique - initial clinical experience.

Acta Radiol Open 2021 Apr 9;10(4):20584601211008391. Epub 2021 Apr 9.

Department of Diagnostic Physics, Oslo University Hospital, Oslo, Norway.

Background: A novel Deep Learning Image Reconstruction (DLIR) technique for computed tomography has recently received clinical approval.

Purpose: To assess image quality in abdominal computed tomography reconstructed with DLIR, and compare with standardly applied iterative reconstruction.

Material And Methods: Ten abdominal computed tomography scans were reconstructed with iterative reconstruction and DLIR of medium and high strength, with 0.625 mm and 2.5 mm slice thickness. Image quality was assessed using eight visual grading criteria in a side-by-side comparative setting. All series were presented twice to evaluate intraobserver agreement. Reader scores were compared using univariate logistic regression. Image noise and contrast-to-noise ratio were calculated for quantitative analyses.

Results: For 2.5 mm slice thickness, DLIR images were more frequently perceived as equal or better than iterative reconstruction across all visual grading criteria (for both DLIR of medium and high strength, p < 0.001). Correspondingly, DLIR images were more frequently perceived as better (as opposed to equal or in favor of iterative reconstruction) for visual reproduction of liver parenchyma, intrahepatic vascular structures as well as overall impression of image noise and texture (p < 0.001). This improved image quality was also observed for 0.625 mm slice images reconstructed with DLIR of high strength when directly comparing to traditional iterative reconstruction in 2.5 mm slices. Image noise was significantly lower and contrast-to-noise ratio measurements significantly higher for images reconstructed with DLIR compared to iterative reconstruction (p < 0.01).

Conclusions: Abdominal computed tomography images reconstructed using a DLIR technique shows improved image quality when compared to standardly applied iterative reconstruction across a variety of clinical image quality criteria.
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http://dx.doi.org/10.1177/20584601211008391DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8040588PMC
April 2021

BENCHMARKING OF A NEW AUTOMATIC CT RADIATION DOSE CALCULATOR.

Radiat Prot Dosimetry 2020 Dec;191(3):361-368

Department of Diagnostic Physics, Oslo University Hospital, 0424 Oslo, Norway.

Information on patient radiation dose is essential to meet the radiation protection regulations and the demands of dose optimization. Vendors have developed different tools for patient dose assessment for radiological purposes. In this study, estimated effective doses derived from a new image-based software tool (DoseWatch, GE Healthcare) was benchmarked against the corresponding doses from a dose calculator (CT-Expo, SASCRAD) and a conversion coefficient method. Dose data from 150 adult patients (66 male and 84 female), who underwent CT head, abdominopelvic or chest examinations, were retrospectively collected using DoseWatch. Effective dose estimated by DoseWatch was significantly lower than that of CT-Expo and DLP-E (k) (p ≤ 0.001). For the organ doses, DoseWatch resulted in lower dose than CT-Expo for all the organs with the exception of testis (p ≤ 001) and eye lenses (p ≤ 0.026).
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http://dx.doi.org/10.1093/rpd/ncaa167DOI Listing
December 2020

Image Quality Measured From Ultra-Low Dose Chest Computed Tomography Examination Protocols Using 6 Different Iterative Reconstructions From 4 Vendors, a Phantom Study.

J Comput Assist Tomogr 2020 Jan/Feb;44(1):95-101

From the Departments of Diagnostic Physics.

Purpose: This study aimed to evaluate image quality of ultra-low dose chest computed tomography using 6 iterative reconstruction (IR) algorithms.

Method: A lung phantom was scanned on 4 computed tomography scanners using fixed tube voltages and the lowest mAs available on each scanner, resulting in dose levels of 0.1 to 0.2 mGy (80 kVp) and 0.3 to 1 mGy (140 kVp) volume CT dose index (CTDIvol). Images were reconstructed with IR available on the scanners. Image noise, signal-to-noise ratios, contrast-to-noise ratios, uniformity, and noise power spectrum (NPS) were assessed for evaluation of image quality.

Results: Image quality parameters increased with increasing dose for all algorithms. At constant dose levels, model-based techniques improved the contrast-to-noise ratio of lesions more than the statistical algorithms. All algorithms tested at 0.1 mGy showed lower NPS peak frequencies compared with 0.39 mGy. In contrast to the statistical techniques, model-based algorithms showed lower NPS peak frequencies at the lowest doses, indicating a coarser and blotchier noise texture.

Conclusion: This study shows the importance of evaluating IR when introduced clinically.
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http://dx.doi.org/10.1097/RCT.0000000000000947DOI Listing
January 2020

Digital Mammography versus Breast Tomosynthesis: Impact of Breast Density on Diagnostic Performance in Population-based Screening.

Radiology 2019 10 13;293(1):60-68. Epub 2019 Aug 13.

From the Department of Diagnostic Physics (B.H.Ø., A.C.T.M.) and Division of Radiology and Nuclear Medicine (R.G., P.S.), Oslo University Hospital, Building 20, Gaustad, PO Box 4959, Nydalen, 0424 Oslo, Norway; and Institute of Clinical Medicine (B.H.Ø., P.S.) and Department of Physics (A.C.T.M.), University of Oslo, Oslo, Norway.

BackgroundPrevious studies comparing digital breast tomosynthesis (DBT) to digital mammography (DM) have shown conflicting results regarding breast density and diagnostic performance.PurposeTo compare true-positive and false-positive interpretations in DM versus DBT according to volumetric density, age, and mammographic findings.Materials and MethodsFrom November 2010 to December 2012, 24 301 women aged 50-69 years (mean age, 59.1 years ± 5.7) were prospectively included in the Oslo Tomosynthesis Screening Trial. Participants received same-compression DM and DBT with independent double reading for both DM and DM plus DBT reading modes. Eight experienced radiologists rated the images by using a five-point scale for probability of malignancy. Participants were followed up for 2 years to assess for interval cancers. Breast density was assessed by using automatic volumetric software (scale, 1-4). Differences in true-positive rates, false-positive rates, and mammographic findings were assessed by using confidence intervals (Newcombe paired method) and values (McNemar and χ tests).ResultsThe true-positive rate of DBT was higher than that of DM for density groups (range, 12%-24%; < .001 for density scores of 2 and 3, and > .05 for density scores of 1 and 4) and age groups (range, 15%-35%; < .05 for all age groups), mainly due to the higher number of spiculated masses and architectural distortions found at DBT ( < .001 for density scores of 2 and 3; < .05 for women aged 55-69 years). The false-positive rate was lower for DBT than for DM in all age groups (range, -0.6% to -1.2%; < .01) and density groups (range, -0.7 to -1.0%; < .005) owing to fewer asymmetric densities ( ≤ .001), except for extremely dense breasts (0.1%, = .82).ConclusionDigital breast tomosynthesis enabled the detection of more cancers in all density and age groups compared with digital mammography, especially cancers classified as spiculated masses and architectural distortions. The improvement in cancer detection rate showed a positive correlation with age. With use of digital breast tomosynthesis, false-positive findings were lower due to fewer asymmetric densities, except in extremely dense breasts.© RSNA, 2019See also the editorial by Fuchsjäger and Adelsmayr in this issue.
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http://dx.doi.org/10.1148/radiol.2019190425DOI Listing
October 2019

Ultra-low dose chest computed tomography: Effect of iterative reconstruction levels on image quality.

Eur J Radiol 2019 May 18;114:62-68. Epub 2019 Feb 18.

Department of Diagnostic Physics, Oslo University Hospital, Oslo, Norway; The Department of Physics, University of Oslo, Oslo, Norway.

Purpose: To optimize image quality and radiation dose of chest CT with respect to various iterative reconstruction levels, detector collimations and body sizes.

Method: A Kyoto Kagaku Lungman with and without extensions was scanned using fixed ultra-low doses of 0.25, 0.49 and 0.74 mGy CTDI, and collimations of 40 and 80 mm. Images were reconstructed with the lung kernel, filtered back projection (FBP) and different ASIR-V levels (10-100%). Contrast-to-noise ratios (CNR) were calculated for 12 mm simulated lesions of different densities in the lung. Image noise, signal-to-noise ratios (SNR), variations in Hounsfield units (HU), noise power spectrum (NPS) and noise texture deviations (NTD) were evaluated for all reconstructions. NTD was calculated as percentage of pixels outside 3 standard deviations to evaluate IR-specific artefacts.

Results: Compared to the FBP, image noise reduced (5-55%) with ASIR-V levels irrespective of dose or collimation. SNR correlated positively (r ≥ 0.925, p ≤ 0.001) with ASIR-V levels at all doses, collimations, and phantom sizes. ASIR-V enhanced the CNR of the lesion with the lowest contrast from 12.7-42.1 (0-100% ASIR-V) at 0.74 mGy with 40 mm collimation. As expected, higher SNR and CNR were measured in the smaller phantom than the bigger phantom. Uniform HU were observed between FBP and ASIR-V levels at all doses, collimations, and phantom sizes. NPS curves left-shifted towards lower frequencies at increasing levels of ASIR-V irrespective of collimation. A positive correlation (r ≥ 0.946, p ≥ 0.001) was observed between NTD and ASIR-V levels. NTD of the FBP was not significantly (p ≤ 0.087) different from NTD of ASIR-V ≤ 20%. The data from the NPS and NTD indicates a blotchier and coarser noise texture at higher levels of ASIR-V, especially at 100% ASIR-V.

Conclusion: In comparison with the FBP technique, ASIR-V enhanced quantitative image quality parameters at all ultra-low doses tested. Moreover, the use of ASIR-V showed consistency with body size and collimation. Hence, ASIR-V may be useful for improving image quality of chest CT at ultra-low doses.
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http://dx.doi.org/10.1016/j.ejrad.2019.02.021DOI Listing
May 2019

EVALUATION OF OCCUPATIONAL RADIATION DOSE IN TRANSCATHETER AORTIC VALVE IMPLANTATION.

Radiat Prot Dosimetry 2018 Apr;179(1):9-17

Department of Diagnostic Physics, Oslo University Hospital, Oslo, Norway.

Occupational doses during fluoroscopy in interventional procedures vary largely (Kim et al. (Occupational radiation doses to operators performing cardiac catheterization procedures. Health Phys. 2008;94:211-227)). In transcatheter aortic valve implantation, the operators' positions and use of radiation shielding are particularly related to the entry choice on the patient's heart. This study evaluates how occupational doses depend on operator positioning during transfemoral and transaortal access. Occupational dosimetric readings were collected with electronic dosemeters on two cardiothoracic surgeons and one cardiologist during 31 procedures. The findings were significantly higher body doses and eye lens doses to the surgeons during transaortal access compared to transfemoral access. The median equivalent eye lens dose per procedure received by the cardiologists was 0.05-0.06 mSv; hence, the cardiologists should wear protective eye wear to prevent reaching the proposed annual dose limit of 20 mSv to the eye lens. Surgeons ought to use protective eye wear as well, and should only perform a restricted number of transcatheter aortic valve implantations with transaortal access annually.
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http://dx.doi.org/10.1093/rpd/ncx184DOI Listing
April 2018

100 days with scans of the same Catphan phantom on the same CT scanner.

J Appl Clin Med Phys 2017 Nov 18;18(6):224-231. Epub 2017 Sep 18.

Department of Diagnostic Physics, Oslo University Hospital, Oslo, Norway.

Quality control (QC) of CT scanners is important to evaluate image quality and radiation dose. Different QC phantoms for testing image quality parameters on CT are commercially available, and Catphan phantoms are widely used for this purpose. More data from measured image quality parameters on CT are necessary to assess test methods, tolerance levels, and test frequencies. The aim of this study was to evaluate the stability of essential image quality parameters for axial and helical scans on one CT scanner over time. A Catphan 600 phantom was scanned on a Philips Ingenuity CT scanner for 100 days over a period of 6 months. At each day of testing, one helical scan covering the entire phantom and four axial scans covering four different modules in the phantom were performed. All images were uploaded into Image Owl for automatic analysis of CT numbers, modular transfer function (MTF), low-contrast resolution, noise, and uniformity. In general, the different image quality parameters for both scan techniques were stable over time compared to given tolerance levels. Average measured CT numbers differed between axial and helical scans, while MTF was almost identical for helical and axial scans. Axial scans had better low-contrast resolution and less noise than helical scans. The uniformity was relatively similar for axial and helical scans. Most standard deviations of measured values were larger for helical scans compared to axial scans. Test results in this study were stable over time for both scan techniques, but further studies on different CT scanners are required to confirm that this also holds true for other systems.
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http://dx.doi.org/10.1002/acm2.12186DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5689914PMC
November 2017

[Radiation-induced cataracts].

Tidsskr Nor Laegeforen 2016 Nov 22;136(21):1809-1812. Epub 2016 Nov 22.

Intervensjonssenteret Oslo universitetssykehus, Rikshospitalet og Fysisk institutt Universitetet i Oslo.

The dose limit for the lens of the eye for occupationally exposed workers that is stipulated in the Norwegian Regulation on radiation protection is based on outdated threshold doses for radiation-induced cataracts. Recent studies have shown that injuries may occur at significantly lower radiation doses than previously assumed. The results from the new studies will impact upon future legislation and recommendations regarding radiation hygiene for personnel in x-ray laboratories and operating theatres who may be exposed to significant radiation doses in the course of their work.
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http://dx.doi.org/10.4045/tidsskr.16.0307DOI Listing
November 2016

Can use of adaptive statistical iterative reconstruction reduce radiation dose in unenhanced head CT? An analysis of qualitative and quantitative image quality.

Acta Radiol Open 2016 Aug 17;5(8):2058460116645831. Epub 2016 Aug 17.

The Intervention Centre, Oslo University Hospital, Postbox 4950, Nydalen, 0424 Oslo, Norway; Institute of Physics, University of Oslo, 0027 Oslo, Norway.

Background: Iterative reconstruction can reduce image noise and thereby facilitate dose reduction.

Purpose: To evaluate qualitative and quantitative image quality for full dose and dose reduced head computed tomography (CT) protocols reconstructed using filtered back projection (FBP) and adaptive statistical iterative reconstruction (ASIR).

Material And Methods: Fourteen patients undergoing follow-up head CT were included. All patients underwent full dose (FD) exam and subsequent 15% dose reduced (DR) exam, reconstructed using FBP and 30% ASIR. Qualitative image quality was assessed using visual grading characteristics. Quantitative image quality was assessed using ROI measurements in cerebrospinal fluid (CSF), white matter, peripheral and central gray matter. Additionally, quantitative image quality was measured in Catphan and vendor's water phantom.

Results: There was no significant difference in qualitative image quality between FD FBP and DR ASIR. Comparing same scan FBP versus ASIR, a noise reduction of 28.6% in CSF and between -3.7 and 3.5% in brain parenchyma was observed. Comparing FD FBP versus DR ASIR, a noise reduction of 25.7% in CSF, and -7.5 and 6.3% in brain parenchyma was observed. Image contrast increased in ASIR reconstructions. Contrast-to-noise ratio was improved in DR ASIR compared to FD FBP. In phantoms, noise reduction was in the range of 3 to 28% with image content.

Conclusion: There was no significant difference in qualitative image quality between full dose FBP and dose reduced ASIR. CNR improved in DR ASIR compared to FD FBP mostly due to increased contrast, not reduced noise. Therefore, we recommend using caution if reducing dose and applying ASIR to maintain image quality.
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http://dx.doi.org/10.1177/2058460116645831DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4994404PMC
August 2016

Image Quality in Oncologic Chest Computerized Tomography With Iterative Reconstruction: A Phantom Study.

J Comput Assist Tomogr 2016 May-Jun;40(3):351-6

From the *Intervention Centre, Rikshospitalet, Nydalen; †Institute of Physics, University of Oslo; ‡Department of Radiology and Nuclear Medicine, Rikshospitalet, Nydalen, Oslo, Norway; §Department of Medical Radiation Physics, Lund University, Skåne University Hospital, Malmö, Sweden; and ∥Institute of Clinical Medicine, University of Oslo, Oslo, Norway.

Objective: The purpose of this study was to validate iterative reconstruction technique in oncologic chest computed tomography (CT).

Methods: An anthropomorphic thorax phantom with 4 simulated tumors was scanned on a 64-slice CT scanner with 2 different iterative reconstruction techniques: one model based (MBIR) and one hybrid (ASiR). Dose levels of 14.9, 11.1, 6.7, and 0.6 mGy were used, and all images were reconstructed with filtered back projection (FBP) and both iterative reconstruction algorithms. Hounsfield units (HU) and absolute noise were measured in the tumors, lung, heart, diaphragm, and muscle. Contrast-to-noise ratios (CNRs) and signal-to-noise ratios (SNRs) were calculated.

Results: Model-based iterative reconstruction (MBIR) increased CNRs of the tumors (21.1-192.2) and SNRs in the lung (-49.0-165.6) and heart (3.1-8.5) at all dose levels compared with FBP (CNR, 1.1-23.0; SNR, -7.5-31.6 and 0.2-1.1) and with adaptive statistical iterative reconstruction (CNR, 1.2-33.2; SNR, -7.3-37.7 and 0.2-1.5). At the lowest dose level (0.6 mGy), MBIR reduced the cupping artifact (HU range: 17.0 HU compared with 31.4-32.2). An HU shift in the negative direction was seen with MBIR.

Conclusions: Quantitative image quality parameters in oncologic chest CT are improved with MBIR compared with FBP and simpler iterative reconstruction algorithms. Artifacts at low doses are reduced. A shift in HU values was shown; thus, absolute HU values should be used with care.
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http://dx.doi.org/10.1097/RCT.0000000000000364DOI Listing
January 2017

BI-RADS Density Classification From Areometric and Volumetric Automatic Breast Density Measurements.

Acad Radiol 2016 Apr 1;23(4):468-78. Epub 2016 Feb 1.

Institute of Clinical Medicine, University of Oslo, Postbox 1171, Blindern, 1318, Oslo, Norway; Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway.

Rationale And Objectives: The aim of our study was to classify breast density using areometric and volumetric automatic measurements to best match Breast Imaging-Reporting and Data System (BI-RADS) density scores, and determine which technique best agrees with BI-RADS. Second, this study aimed to provide a set of threshold values for areometric and volumetric density to estimate BI-RADS categories.

Materials And Methods: We randomly selected 537 full-field digital mammography examinations from a population-based screening program. Five radiologists assessed breast density using BI-RADS with all views available. A commercial program calculated areometric and volumetric breast density automatically. We compared automatically calculated density to all BI-RADS density thresholds using area under the receiver operating characteristic curve, and used Youden's index to estimate thresholds in automatic densities, with matching sensitivity and specificity. The 95% confidence intervals were estimated by bootstrapping.

Results: Areometric density correlated well with volumetric density (r(2) = 0.76, excluding outliers, n = 2). For the BI-RADS threshold between II and III, areometric and volumetric assessment showed about equal area under the curve (0.94 vs. 0.93). For the threshold between I and II, areometric assessment was better than volumetric assessment (0.91 vs. 0.86). For the threshold between III and IV, volumetric assessment was better than areometric assessment (0.97 vs. 0.92).

Conclusions: Volumetric assessment is equal to or better than areometric assessment for the most clinically relevant thresholds (ie, between scattered fibroglandular and heterogeneously dense, and between heterogeneously dense and extremely dense breasts). Thresholds found in this study can be applied in daily practice to automatic measurements of density to estimate BI-RADS classification.
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http://dx.doi.org/10.1016/j.acra.2015.12.016DOI Listing
April 2016

Classification of fatty and dense breast parenchyma: comparison of automatic volumetric density measurement and radiologists' classification and their inter-observer variation.

Acta Radiol 2016 Oct 20;57(10):1178-85. Epub 2016 Jan 20.

Institute of Clinical Medicine, University of Oslo, Oslo, Norway Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway.

Background: Automatically calculated breast density is a promising alternative to subjective BI-RADS density assessment. However, such software needs a cutoff value for density classification.

Purpose: To determine the volumetric density threshold which classifies fatty and dense breasts with highest accuracy compared to average BI-RADS density assessment, and to analyze radiologists' inter-observer variation.

Material And Methods: A total of 537 full field digital mammography examinations were randomly selected from a population based screening program. Five radiologists assessed density using the BI-RADS density scale, where BI-RADS I-II were classified as fatty and III-IV as dense. A commercially available software (Quantra) calculated volumetric breast density. We calculated the cutoff (threshold) values in volumetric density that yielded highest accuracy compared to median and individual radiologists' classification. Inter-observer variation was analyzed using the kappa statistic.

Results: The threshold that best matched the median radiologists' classification was 10%, which resulted in 87% accuracy. Thresholds that best matched individual radiologist's classification had a range of 8-15%. A total of 191 (35.6 %) cases were scored both dense and fatty by at least one radiologist. Fourteen (2.6 %) cases were unanimously scored by the radiologists, yet differently using automatic assessment. The agreement (kappa) between reader's median classification and individual radiologists was 0.624 to 0.902, and agreement between median classification and Quantra was 0.731.

Conclusion: The optimal volumetric threshold of 10% using automatic assessment would classify breast parenchyma as fatty or dense with substantial accuracy and consistency compared to radiologists' BI-RADS categorization, which suffers from high inter-observer variation.
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http://dx.doi.org/10.1177/0284185115626469DOI Listing
October 2016

Improved Liver Lesion Conspicuity With Iterative Reconstruction in Computed Tomography Imaging.

Curr Probl Diagn Radiol 2016 Sep-Oct;45(5):291-6. Epub 2015 Dec 15.

The Intervention Centre, Rikshospitalet, Oslo, Norway; Institute of Physics, University of Oslo, Oslo, Norway.

Studies on iterative reconstruction techniques on computed tomographic (CT) scanners show reduced noise and changed image texture. The purpose of this study was to address the possibility of dose reduction and improved conspicuity of lesions in a liver phantom for different iterative reconstruction algorithms. An anthropomorphic upper abdomen phantom, specially designed for receiver operating characteristic analysis was scanned with 2 different CT models from the same vendor, GE CT750 HD and GE Lightspeed VCT. Images were obtained at 3 dose levels, 5, 10, and 15mGy, and reconstructed with filtered back projection (FBP), and 2 different iterative reconstruction algorithms; adaptive statistical iterative reconstruction and Veo. Overall, 5 interpreters evaluated the images and receiver operating characteristic analysis was performed. Standard deviation and the contrast to noise ratio were measured. Veo image reconstruction resulted in larger area under curves compared with those adaptive statistical iterative reconstruction and FBP image reconstruction for given dose levels. For the CT750 HD, iterative reconstruction at the 10mGy dose level resulted in larger or similar area under curves compared with FBP at the 15mGy dose level (0.88-0.95 vs 0.90). This was not shown for the Lightspeed VCT (0.83-0.85 vs 0.92). The results in this study indicate that the possibility for radiation dose reduction using iterative reconstruction techniques depends on both reconstruction technique and the CT scanner model used.
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http://dx.doi.org/10.1067/j.cpradiol.2015.11.004DOI Listing
April 2017

CT image quality over time: comparison of image quality for six different CT scanners over a six-year period.

J Appl Clin Med Phys 2015 Mar 8;16(2):4972. Epub 2015 Mar 8.

The Intervention Centre Oslo University Hospital.

UNSCEAR concluded that increased use of CT scanning caused dramatic changes in population dose. Therefore, international radiation protection authorities demand: 1) periodical quality assurance tests with respect to image quality and radiation dose, and 2) optimization of all examination protocols with respect to image quality and radiation dose. This study aimed to evaluate and analyze multiple image quality parameters and variability measured throughout time for six different CT scanners from four different vendors, in order to evaluate the current methodology for QA controls of CT systems. The results from this study indicate that there is minor drifting in the image noise and uniformity and in the spatial resolution over time for CT scanners, independent of vendors. The HU for different object densities vary between different CT scanner models from different vendors, and over time for one specific CT scanner. Future tests of interphantom and intraphantom variations, along with inclusion of more CT scanners, are necessary to establish robust baselines and recommendations of methodology for QA controls of CT systems, independent of model and vendor.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5690105PMC
http://dx.doi.org/10.1120/jacmp.v16i2.4972DOI Listing
March 2015

Comparing five different iterative reconstruction algorithms for computed tomography in an ROC study.

Eur Radiol 2014 Dec 22;24(12):2989-3002. Epub 2014 Jul 22.

The Intervention Centre, Rikshospitalet, Postboks 4950, Nydalen, 0424, Oslo, Norway,

Objectives: The purpose of this study was to evaluate lesion conspicuity achieved with five different iterative reconstruction techniques from four CT vendors at three different dose levels. Comparisons were made of iterative algorithm and filtered back projection (FBP) among and within systems.

Methods: An anthropomorphic liver phantom was examined with four CT systems, each from a different vendor. CTDIvol levels of 5 mGy, 10 mGy and 15 mGy were chosen. Images were reconstructed with FBP and the iterative algorithm on the system. Images were interpreted independently by four observers, and the areas under the ROC curve (AUCs) were calculated. Noise and contrast-to-noise ratios (CNR) were measured.

Results: One iterative algorithm increased AUC (0.79, 0.95, and 0.97) compared to FBP (0.70, 0.86, and 0.93) at all dose levels (p < 0.001 and p = 0.047). Another algorithm increased AUC from 0.78 with FBP to 0.84 (p = 0.007) at 5 mGy. Differences at 10 and 15 mGy were not significant (p-values: 0.084-0.883). Three algorithms showed no difference in AUC compared to FBP (p-values: 0.008-1.000). All of the algorithms decreased noise (10-71%) and improved CNR.

Conclusions: Only two algorithms improved lesion detection, even though noise reduction was shown with all algorithms.

Key Points: Iterative reconstruction algorithms affected lesion detection differently at different dose levels. One iterative algorithm improved lesion detectability compared to filtered back projection. Three algorithms did not significantly improve lesion detectability. One algorithm improved lesion detectability at the lowest dose level.
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http://dx.doi.org/10.1007/s00330-014-3333-4DOI Listing
December 2014
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