Measurement of computed tomography modulation transfer function with a novel polymethyl methacrylate phantom

Measurement of computed tomography modulation transfer function with a novel polymethyl methacrylate phantom | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Measurement of computed tomography modulation transfer function with a novel polymethyl methacrylate phantom Jack Svenson, Michael Alan Irvine This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4007337/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Sep, 2024 Read the published version in Physical and Engineering Sciences in Medicine → Version 1 posted 6 You are reading this latest preprint version Abstract A novel phantom for measuring the 10% and 50% values of the modulation transfer function (MTF) for computed tomography scanners (CT) was investigated. The phantom was constructed by drilling rows of holes of different sizes and frequencies into a small block of polymethyl methacrylate (PMMA). The MTF at a given frequency was determined from the ratio of the range of Hounsfield units within the rows of holes at different frequencies, and the difference in Hounsfield units between air and PMMA. A MTF curve was plotted from measurements at different frequencies and the 10% and 50% MTF values were obtained from a cubic spline interpolation. The MTF results obtained with the drilled hole phantom method were compared to a conventional method - using a thin wire and Spice-CT ImageJ Plugin – and with identical acquisition and reconstruction parameters. The drilled hole phantom measured the 50% MTF with reasonable accuracy but underestimated the 10% MTF by 8.2% on average. MTF measurements were reproducible for repeated image acquisitions and with different users analysing the images, and the phantom was able to accurately measure the change in MTF when measured on images using different reconstruction kernels. The tool may find application as a cheap, easy to use method for routine QC testing of CT scanners. Modulation transfer function computed tomography phantom spatial resolution Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 INTRODUCTION The modulation transfer function (MTF) is a metric used to describe the spatial resolution in computed tomography (CT) systems. It’s recommended that the MTF of a CT scanner be measured during acceptance testing, and subsequently during periodic quality control (QC) testing to ensure the expected clinical performance of the scanner continues to be met [ 1 , 2 ]. The MTF describes the ability of an imaging system to transfer contrast from an object to an image at different spatial frequencies and can be described by Eq. ( 1 ), where modulation in (f) is the contrast in the object (e.g. difference in thickness of attenuating material), and modulation out (f) is the contrast in the image (e.g. difference in Hounsfield Units (HU) in acquired CT image) [ 3 ]. $$MTF \left(f\right)=\frac{ {\text{m}\text{o}\text{d}\text{u}\text{l}\text{a}\text{t}\text{i}\text{o}\text{n}}_{out} \left(\text{f}\right)}{{\text{m}\text{o}\text{d}\text{u}\text{l}\text{a}\text{t}\text{i}\text{o}\text{n}}_{in} \left(\text{f}\right)}$$ 1 The MTF can be expressed as a curve showing the transferred-modulation ratio in Eq. ( 1 ) as a function of frequency, or by the specifying the frequencies where the MTF is equal to 0.1 (10% MTF) and 0.5 (50% MTF) for numeric comparison to manufacturer specifications or QC baseline values. Various methods for determining MTF have been described. The point spread function (PSF) resulting from an axial image of a thin wire or bead may be processed to produce a line spread function (LSF), the Fourier Transform (FT) of the LSF produces the MTF [ 4 , 5 ]. Alternatively, an edge spread function acquired from a phantom with a suitable edge [ 6 ] or with a block of Polymethyl methacrylate (PMMA) [ 7 ], the LSF is calculated from the derivative of the ESF and taking the FT of the LSF as above. These are well-established methods performed using phantoms supplied by CT manufacturers or commercially available phantoms used by medical physicists [ 8 , 9 ]. The thin wire and edge methods both require DICOM images to be exported from the scanner console and suitable software for image analysis. An image of a cyclic bar pattern can be used to measure the MTF at pattern frequencies (f) greater than 1/3 the cutoff frequency, where A 0 is the pattern input amplitude and A (f) is the output amplitude for patterns at frequency f. [ 10 ]: \(MTF \left(f\right)=\frac{pi}{4}\frac{\text{A} \left(\text{f}\right)}{{\text{A}}_{0} }\) , where f > f c /3 (2) The terms on the right-hand side of Eq. 2 can be obtained at the scanner console to measure the MTF from an imaged bar pattern at frequency f. The input amplitude A 0 is the difference in Hounsfield Units (HU) of the materials making up the bar pattern. The output amplitude A (f) is the difference between the minimum and maximum HUs within the pattern at frequency f, determined by noting the window level settings when the pattern merges and disappears with the window width set to 1. The MTF curve is formed by plotting the measured MTFs at different bar pattern frequencies. The methods outlined above require the use of specialised CT phantoms and/or exporting images for offline analysis. The aim of this work is to determine whether a small, inexpensive and easily portable phantom can be used to measure the 10% and 50% MTFs of different CT scanners with sufficient accuracy to demonstrate compliance with regulatory standards and consistency with QC baseline MTF measurements and without the need for expensive phantoms or third-party software METHODS The drilled hole phantom (DHP) shown in Fig. 1 as a tool for MTF measurements was investigated. The phantom was constructed by a computer numerical control (CNC) machine with rows of holes drilled into a 50mm x 70mm x 30mm PMMA block. The phantom was 30mm thick, with the indicated diameter of the hole is maintained to a depth of 13mm, with 13mm being the maximum hole depth achievable for the smaller holes. The spacing between the holes was twice the specified hole diameter ± 0.02mm, resulting in the nominal hole frequency shown in Fig. 1 . Axial images were acquired with the drilled face of the DHP in the axial plane and the centre line of the rows of holes positioned vertically. Z-axis position was set to ensure drilled holes were captured in a central slice. Partial volume artefact was confirmed not to be present in the analysed image by ensuring all drilled holes were visible in the two slices adjacent to the slice being analysed. The MTF was measured with the DHP using Eq. 1 , with the input and output modulation terms measured off-site from exported DICOM images of the DHP using Weasis [ 11 ] DICOM Medical Viewer using a similar process to the bar pattern method described above. For all hole frequencies the input modulation (M in ) was set as the difference in HU between air and PMMA in the phantom image, measured from ROIs positioned in a region of air next to the phantom and a uniform region of PMMA in the phantom, away from blurred edges of the phantom or the holes (Fig. 2 ). The output modulation (M out (f)) at frequency f was determined from the difference between the maximum and minimum HUs within the row of circles of frequency f. For analysis, images were zoomed to enhance visualisation and the window width (WW) was set to 1HU. For each row the minimum HU was determined by reducing the window level (WL) until all the holes disappeared (Fig. 3 ), then gradually increasing the WL until at least one pixel in three of the five holes was visible. The maximum pixel value was determined by setting the WW to 1HU, decreasing the WL until all five holes were distinct, and increasing the WL until at least two of the four gaps between the holes were connected by adjacent or diagonally connected dark pixels (Fig. 3 ). The minimum and maximum HUs in the row were the respective WLs when the above criteria were met. M out (f) was calculated as the difference between these measurements at the hole frequency f. The M out (f)/ M in ratio was determined for each hole frequency to produce a plot of the MTF curve. The frequencies where the modulation ratio M(f)/M 0 = 0.5 and 0.1 were measured from a cubic spline interpolation of the plotted curve to give the 50% and 10% MTF values for the DHP. For each MTF determination using the DHP method, an image with identical acquisition and reconstruction parameters was acquired of a Siemens Definition AS + QA phantom containing a 0.2mm tungsten wire for a point-source MTF determination. The 10% and 50% MTFs were determined from these images using the SPICE-CT ImageJ plugin [ 12 ] and compared to the corresponding DHP MTF method results. MTFs were obtained on four different scanners using the scan and reconstruction parameters shown in Table 1 . Selection of these parameters was guided by the typical scan conditions specified in vendor documentation. High resolution kernels were not investigated. Each series was acquired with a sequential scan. Table 1 CT scan parameters for MTF assessment Make Model Recon. Kernel Focal Spot (mm) Recon. FOV (cm) kVp mAs per slice Reconstructed Slice Thickness (mm) Pixel Size (mm) Canon Aquilion Prime FC70 0.9/0.8 240 120 300 2 0.468 Siemens Definition Somatom AS+ Hr38s 0.9 250 120 300 5 0.488 Siemens Somatom Perspective H31s 0.95 250 130 220 5 0.488 Siemens Somatom Perspective B41s 0.95 380 130 125 5 0.742 Siemens Definition Open H30s 0.95 250 130 220 5 0.488 Siemens Definition Open B30f 0.95 300 130 .350 4.8 0.586 The reproducibility of the DHP MTF method was investigated by acquiring six sets of head images on the Siemens Definition AS+. Between each scan both the DHP and thin wire phantoms were slightly shifted by around 2mm in the vertical and horizontal directions with an intent to randomly shift the centrelines of the drilled holes with respect to the image matrix. To investigate the sensitivity of the DHP method at detecting modified scan conditions, the process was repeated with the Somatom Perspective head series using all the HXXs series of kernels between H10s and H50s, with no other factors changed. This resulted in an additional twelve sets of images with both increased and decreased MTFs, enabling comparison of the relative change in MTF between the DHP and thin wire methods. The image analysis of the Siemens Definition AS + and Canon Prime scans in Table 1 was repeated by two other medical physicists (each with 10 + years of experience) to investigate the reproducibility between different users. One physicist used ImageJ instead of Weasis for the analysis and both physicists were provided with the instructions to analyse the images, as outlined above, and conducted the analysis independently. RESULTS A comparison of 50% and 10% MTF values determined from the DHP and the wire/Spice-CT methods are shown in Table 2 . The results showed reasonable agreement between the 50% MTF values for both methods, with an average difference of 1.9% and a range of differences between − 2.2% and 4.7%. The 10% MTF values for the DHP method were consistently below the wire/Spice-CT method, with an average difference of -7.3% and a range of differences between − 5.1% and − 9.7%. Table 2 Comparison of 10% and 50% MTFs results for the Spice-CT method and the DHP Make Model Kernel 50% MTF 10% MTF Spice-CT DHP Difference (%) Spice-CT DHP Difference (%) Canon Aquilion Prime FC70 3.93 3.99 1.5% 7.46 6.82 -8.6% Siemens Definition AS+ Hr38s 3.2 3.24 1.3% 5.86 5.56 -5.1% Siemens Somatom Perspective H31s 3.19 3.12 -2.2% 6.08 5.49 -9.7% Siemens Somatom Perspective B41s 3.2 3.35 4.7% 5.95 5.47 -8.1% Siemens Definition Open B30f 3.01 3.09 2.7% 5.23 4.87 -6.9% Siemens Definition Open H30s 3.17 3.27 3.2% 5.77 5.46 -5.4% Average difference 1.9% -7.3% An example of the output modulation in the phantom with the fitted cubic-spline curve and the corresponding Spice-CT MTF results for the Definition AS + is shown in Fig. 4 . Results from the reproducibility assessment from six different acquisitions are shown in Table 3 . The DHP and thin wire methods were both reproducible with coefficients of variation ≤ 0.01 for both the 10% and 50% MTF measurements. Table 3 10% and 50% MTFs results for the Spice-CT and DHP reproducibility assessment 50% MTF 10% MTF Spice-CT DHP Spice-CT DHP Scan 1 3.2 3.24 5.86 5.46 Scan 2 3.2 3.24 5.86 5.46 Scan 3 3.23 3.2 5.89 5.45 Scan 4 3.23 3.25 5.89 5.42 Scan 5 3.2 3.22 5.83 5.32 Scan 6 3.14 3.23 5.74 5.43 CoV (HU) 0.01 0.006 0.01 0.01 To investigate how well the DHP detected change in the MTF, both methods were compared on thirteen different images acquired using different reconstruction kernels. MTF results were normalised to the H31s kernel results, and the percentage change from the baseline result for each kernel was calculated using both methods. The change in MTF with respect to the H31s baseline was up to ± 25% for the different kernels. Figure 5 shows a plot of the percentage change from the baseline MTFs using the DHP method (y-axis) compared to the corresponding change for the Spice-CT result (x-axis) for each kernel. Perfect agreement between results would be the line y = x, shown in Fig. 5 for reference. Agreement between the methods was strong, indicating that the DHP correctly measured the change in MTF for modified image reconstructions. The comparison between results obtained by three different medical physicists interpreting the same images is shown in Table 4 . The results showed good agreement between different physicists, the largest difference was a 2% difference between two of the medical physicists for the 10% MTF measurement on the Canon Aquilion Prime system. Table 4 Comparison of MTF results from the DHP phantom when images were assessed by three different medical physicists Siemens Definition AS+ Canon Aquilion Prime 50% MTF 10% MTF 50% MTF 10% MTF Medical physicist 1 3.24 5.46 4.1 7.37 Medical physicist 2 3.25 5.48 4.13 7.24 Medical physicist 3 3.24 5.43 4.1 7.36 CoV 0.002 0.005 0.004 0.01 DISCUSSION Routine QC testing of spatial resolution of CT scanners as part of a quality assurance program and/or to meet regulatory compliance testing standards typically includes ensuring the MTF is consistent with manufacturer tolerances or baseline values. The MTF results from the DHP method were reproducible between different users and for measurements using repeated image acquisitions, and were able to accurately detect changes in the 10% and 50% MTFs induced by using different reconstruction kernels. Using the wire/Spice-CT method as a reference the DHP measured the 50% MTF for CT scans using standard resolution reconstruction kernels with reasonable accuracy, but consistently underestimated the 10% MTF by an average of 8.2%. Given the ability of the DHP to accurately measure a change in the MTF with respect to a baseline result, an appropriate application of this phantom would be to confirm MTF performance with respect to manufacturer specifications during acceptance testing using an established method, and simultaneously setting MTF baselines using the DHP for subsequent testing. Direct comparison of the 10% MTF to the corresponding manufacturer specifications may be inappropriate given the consistent underestimation of this result with the DHP, particularly if the 10% measured with the DHP was below manufacturer specifications. An assumption of this work is that Spice-CT/wire method is a suitable method for MTF measurements. Checking the MTF using an additional method would allow confirmation of agreement between the acceptance test method and the DHP. The method used to assess the MTF with the DHP is similar to an approach that can be employed with a bar pattern phantom, where the modulation ratio in a bar a set of bars at frequency f is scaled by pi/4 to give the MTF at frequency f (Eq. 2). The relationship between the MTF and the modulation ratio as is not so simple for the DHP phantom, as shown by the systematic underestimation of the 10% MTF. Spice-CT only provides the 50% and 10% MTF results, so whilst out of scope for this work it would be interesting to compare a full MTF curve acquired with an established method to the curve produced by the DHP method. Figure 3 shows the minimum HU occurs in the centre of the holes, and the maximum HU occurs in the region between the holes where the edges of the holes are closest together. When the WL is increased beyond the maximum HU, the band of dark pixels between the holes spreads out from the centre line, indicating that modulation results are measured from the single column of pixels best aligned with the centre line of the holes. The visual criteria for determining minimum and maximum HUs were chosen to be both unambiguous for the assessor, and to return the median minimum and maximum values in the respective troughs (holes) and peaks (space between the holes) in the regions between the holes. With a single line of pixels being sampled for each set of holes, and random alignment of the line of pixels with respect to the centre line of the holes, some variation in the measured MTF would be expected. In practice the variation was minimal when assessing the DHP on multiple images with the phantom randomly shifted vertically and horizontally between each image acquisition. For this set of images, the 10% MTF measured on Spice CT occurred around 5.9 lp/cm. The closest frequency hole set for the DHP is 6.25 lp/cm, which has 0.8mm diameter holes and a 0.8mm gap between the holes, compared to the 0.488mm pixel size. The two body modes investigated had pixel sizes of 0.742mm and 0.586mm. The discrepancy between the Spice-CT and DHP 10% MTFs for these modes was less than the average discrepancy across all the modes, suggesting that reduction in modulation due to the increased pixel size is comparable for both methods. Figure 7 shows the pixel values from the centre line of pixels through three different sets of drilled holes. An image of a bar pattern will also produce a decreasing range of pixel values as the frequency of the bar set increases, with the pixel values converging to the average HU of the pattern materials as the frequency increases. For the DHP images in this work the HU converged to values between − 40HU and − 110HU at high frequencies for the images assessed. The bulk of the observed modulation in the DHP therefore was due to an increase in the minimum HU, opposed to a modest decrease in the maximum HU. The asymmetric changes to the minimum and maximum HU are due to the difference in material surrounding the area in the phantom where the minimum and maximum HUs are observed. The air holes are surrounded by PMMA, and the air-PMMA edge is blurred by the imaging system and thus increasing the HU in the hole. The increase in HU becomes larger at higher frequencies as the holes become smaller with respect to the extent of introduced blurring. The gaps between the holes are surrounded by both air and PMMA, and the reduction in pixel values in the region by blurring from the air holes is watered down by blurring from PMMA adjacent to the gap, resulting in less decrease to the maximum HU in the gap compared to the increased HU in the hole. The DHP was not investigated for higher resolution kernels which may have 10% and 50% MTFs greater than 10 lp/cm, beyond the highest frequency (10 lp/cm) holes used in the DHP. The manufacturing uncertainty in the hole placement was 0.02mm. This introduces an uncertainty up to 4% for the 10 lp/cm hole set. The uncertainty would increase to 8% for a 20 lp/cm hole if constructed with the same tolerance. CONCLUSION Using the thin wire/Spice-CT as a reference method, the DHP method was able to provide a reasonably accurate measurement of the 50% MTF, but systematically underestimated the 10% MTF by 5–10%. The DHP results were reproducible between different image acquisitions and different users interpreting the images. The DHP method accurately measured changes to 10% and 50% MTFs results for images using different reconstruction kernels when compared to baseline results with standard settings, indicating the phantom could be used for QC purposes. The advantage of the DHP is that it is cheap, easily portable, and image analysis can be readily performed by the user on scanner console or PACS workstation without the need for exporting images or software for analysis. Declarations STATEMENTS & DECLARATIONS Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Conflict of Interest The authors have no competing interests to declare that are relevant to the content of this article. Ethical Approval This is a phantom study and ethical approval is not required References International Atomic Energy Agency (2012) Quality assurance programme for computed tomography: diagnostic and therapy applications. IAEA Human Health Series No. 19, IAEA, Vienna Standards Australia & Standards New Zealand (2022) Evaluation and Routine Testing in Medical Imaging Departments, Part 3.5: Acceptance and constancy tests – Imaging performance of computed tomography X-ray equipment, AS/NZS IEC 61223.3.5:2022 Ahmed SN (2007) Physics and Engineering of Radiation Detection, First Edition. Elsevier Inc.), p 435 Kayugawa A, Ohkubo M, Wada S (2013) Accurate determination of CT point-spread-function with high precision. J Appl Clin Med Phys 14(4):216–226 Mie´ville F, Beaumont S, Torfeh T, Gudinchet F, Verdun FR (2010) Computed tomography commissioning programmes: How to obtain a reliable MTF with an automatic approach? Radiat. Prot Dosim 139(1 –3):443–448 Friedman SN, Fung GSK, Siewerdsen JH, Tsui BMW (2013) A simple approach to measure computed tomography (CT) modulation transfer function (MTF) and noise-power spectrum (NPS) using the American College of Radiology (ACR) accreditation phantom. Med Phys 40:051907 Zabilal E et al (2020) An improvement in automatic MTF measurement in CT images using an edge of the PMMA phantom. J Phys : Conf Ser 1505:012039 Husby E, Svendsen ED, Andersen HK, Martinsen ACT (2017) 100 days with scans of the same Catphan phantom on the same CT scanner. J Appl Clin Med Phys 18(6):224–231 Friedman SN, Fung GSK, Siewerdsen JH, Tsui BMW (2013) A simple approach to measure computed tomography (CT) modulation transfer function (MTF) and noise-power spectrum (NPS) using the American College of Radiology (ACR) accreditation phantom. Med Phys 40:051907 Droege R, Morin R (1982) A practical method to measure the MTF of CT scanners. Med Phys 9(5):758–760 Weasis DICOM Medical Viewer version 4.0 [computer software] Loveland J (2011) SPICE-CT [computer software]. Edinburgh Cite Share Download PDF Status: Published Journal Publication published 09 Sep, 2024 Read the published version in Physical and Engineering Sciences in Medicine → Version 1 posted Editorial decision: Minor revisions 08 Apr, 2024 Reviewers agreed at journal 10 Mar, 2024 Reviewers invited by journal 05 Mar, 2024 Editor invited by journal 03 Mar, 2024 Editor assigned by journal 03 Mar, 2024 First submitted to journal 02 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4007337","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":276624672,"identity":"8d557e2e-7bee-447e-a5ed-22606d8d8db8","order_by":0,"name":"Jack Svenson","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+klEQVRIiWNgGAWjYBACxgYGZoYPUM4HvEqRtTDOgLJnMCQQZxEzMw9JWpjbDz82tm27J29w/vDDho8/DjPwt3cnMPxsw+OwnjTj5JwzxYYbbqQZNs5IOMwgcebsBsZefFoacpgP51QkMG64wWD+mAeoxUAidwMDLz4t/W+YD1sYJNhvOH/8Y/MfqBbGv/i0zMhhTmaoSEjccCDHsJkBqoUZry0znhkb9pxJSJ55I6ewsSctnQfkl8My53BrMexPfizxsy3Btu/88Y0NP2ys5fjbezc+fFOGR0sDlKFwAEw1g+PoAG4NDAzycAZEbx0+xaNgFIyCUTBCAQC1WVhakDzW1gAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0007-1613-8003","institution":"X-ray Safety Australia","correspondingAuthor":true,"prefix":"","firstName":"Jack","middleName":"","lastName":"Svenson","suffix":""},{"id":276624673,"identity":"375c402f-33c5-4001-9571-00bb5ae80a1e","order_by":1,"name":"Michael Alan Irvine","email":"","orcid":"","institution":"X-ray Safety Australia","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"Alan","lastName":"Irvine","suffix":""}],"badges":[],"createdAt":"2024-03-03 02:36:44","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4007337/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4007337/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s13246-024-01468-z","type":"published","date":"2024-09-09T15:58:29+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":52448858,"identity":"172bfcb7-cd89-4292-994f-148d6971987d","added_by":"auto","created_at":"2024-03-11 18:45:15","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":294904,"visible":true,"origin":"","legend":"\u003cp\u003eFront face of the drilled hole phantom (DHP) constructed by drilling sets of holes of different diameters and spacings into a PMMA block\u003c/p\u003e","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4007337/v1/33b8c4fbd70a5dc6677a6be0.jpg"},{"id":52448857,"identity":"b7cb82dd-be1d-4493-b5ec-d9375890e28e","added_by":"auto","created_at":"2024-03-11 18:45:15","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":196766,"visible":true,"origin":"","legend":"\u003cp\u003eROI locations used to measure the mean pixel value in air and in the DHP (PMMA). The difference between these values was the input modulation\u003c/p\u003e","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4007337/v1/737c2561779facab56b21c1a.jpg"},{"id":52449315,"identity":"83b3d932-a939-4aae-9bfa-e4021cb71a59","added_by":"auto","created_at":"2024-03-11 18:53:15","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":225725,"visible":true,"origin":"","legend":"\u003cp\u003eWith the window width set to 1, the window level was increased until at least two of the four gaps between the holes were connected by black pixels as shown in the middle set of holes in a, the window level when this occurred was the maximum Hounsfield Unit (HU) for that set of holes. The minimum HU was determined by increasing the window width until at least one pixel was visible in three of the five holes (b).\u003c/p\u003e","description":"","filename":"Fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4007337/v1/351e770c65b9da06cbe686ff.jpg"},{"id":52448860,"identity":"e3ae8d6a-dc7a-4b15-8783-6cab81d3e06b","added_by":"auto","created_at":"2024-03-11 18:45:15","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":159461,"visible":true,"origin":"","legend":"\u003cp\u003eExample of the DHP MTF data points (crosses), fitted cubic-spline curve (dashed line) and Spice-CT 10% and 50% results (squares) from the Definition AS+\u003c/p\u003e","description":"","filename":"Fig5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4007337/v1/687cfd4d3fc4a2d1811651c0.jpg"},{"id":52448862,"identity":"4d39977a-9fdf-4dc4-aee6-c6ac43906204","added_by":"auto","created_at":"2024-03-11 18:45:16","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":242555,"visible":true,"origin":"","legend":"\u003cp\u003eRelative change in MTF for both methods for modified reconstructions, the percentage change in the DHP 10% and 50% MTFs is compared to the H31s values is plotted against the corresponding change for the Spice-CT values. Perfect agreement between the methods would have all points on the ideal line y=x\u003c/p\u003e","description":"","filename":"Fig6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4007337/v1/94108bc67abe2a8879888f52.jpg"},{"id":52448861,"identity":"853ee6d8-0573-432b-9b8f-902a04be79d6","added_by":"auto","created_at":"2024-03-11 18:45:15","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":256574,"visible":true,"origin":"","legend":"\u003cp\u003eLine profiles taken through the centreline of three rows of holes in the DHP. The x-axis represents the pixel location in the line and have been scaled to improve visualisation. The dashed line shows the average HU of Air and PMMA measured in the image\u003c/p\u003e","description":"","filename":"Fig7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4007337/v1/5d36e490cc730f04eb4c1ceb.jpg"},{"id":64619327,"identity":"a5e60434-a555-40a2-a4be-3f7a733e02fa","added_by":"auto","created_at":"2024-09-16 16:14:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1821446,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4007337/v1/97d55b7e-89e2-4451-8dbb-7a4f65d6e206.pdf"}],"financialInterests":"","formattedTitle":"Measurement of computed tomography modulation transfer function with a novel polymethyl methacrylate phantom","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe modulation transfer function (MTF) is a metric used to describe the spatial resolution in computed tomography (CT) systems. It\u0026rsquo;s recommended that the MTF of a CT scanner be measured during acceptance testing, and subsequently during periodic quality control (QC) testing to ensure the expected clinical performance of the scanner continues to be met [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe MTF describes the ability of an imaging system to transfer contrast from an object to an image at different spatial frequencies and can be described by Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), where modulation\u003csub\u003ein\u003c/sub\u003e (f) is the contrast in the object (e.g. difference in thickness of attenuating material), and modulation\u003csub\u003eout\u003c/sub\u003e (f) is the contrast in the image (e.g. difference in Hounsfield Units (HU) in acquired CT image) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$MTF \\left(f\\right)=\\frac{ {\\text{m}\\text{o}\\text{d}\\text{u}\\text{l}\\text{a}\\text{t}\\text{i}\\text{o}\\text{n}}_{out} \\left(\\text{f}\\right)}{{\\text{m}\\text{o}\\text{d}\\text{u}\\text{l}\\text{a}\\text{t}\\text{i}\\text{o}\\text{n}}_{in} \\left(\\text{f}\\right)}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe MTF can be expressed as a curve showing the transferred-modulation ratio in Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) as a function of frequency, or by the specifying the frequencies where the MTF is equal to 0.1 (10% MTF) and 0.5 (50% MTF) for numeric comparison to manufacturer specifications or QC baseline values.\u003c/p\u003e \u003cp\u003eVarious methods for determining MTF have been described. The point spread function (PSF) resulting from an axial image of a thin wire or bead may be processed to produce a line spread function (LSF), the Fourier Transform (FT) of the LSF produces the MTF [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Alternatively, an edge spread function acquired from a phantom with a suitable edge [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] or with a block of Polymethyl methacrylate (PMMA) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], the LSF is calculated from the derivative of the ESF and taking the FT of the LSF as above. These are well-established methods performed using phantoms supplied by CT manufacturers or commercially available phantoms used by medical physicists [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The thin wire and edge methods both require DICOM images to be exported from the scanner console and suitable software for image analysis.\u003c/p\u003e \u003cp\u003eAn image of a cyclic bar pattern can be used to measure the MTF at pattern frequencies (f) greater than 1/3 the cutoff frequency, where A\u003csub\u003e0\u003c/sub\u003e is the pattern input amplitude and A (f) is the output amplitude for patterns at frequency f. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]:\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(MTF \\left(f\\right)=\\frac{pi}{4}\\frac{\\text{A} \\left(\\text{f}\\right)}{{\\text{A}}_{0} }\\)\u003c/span\u003e \u003c/span\u003e, where f\u0026thinsp;\u0026gt;\u0026thinsp;f\u003csub\u003ec\u003c/sub\u003e/3 (2)\u003c/p\u003e \u003cp\u003eThe terms on the right-hand side of Eq.\u0026nbsp;2 can be obtained at the scanner console to measure the MTF from an imaged bar pattern at frequency f. The input amplitude A\u003csub\u003e0\u003c/sub\u003e is the difference in Hounsfield Units (HU) of the materials making up the bar pattern. The output amplitude A (f) is the difference between the minimum and maximum HUs within the pattern at frequency f, determined by noting the window level settings when the pattern merges and disappears with the window width set to 1. The MTF curve is formed by plotting the measured MTFs at different bar pattern frequencies.\u003c/p\u003e \u003cp\u003eThe methods outlined above require the use of specialised CT phantoms and/or exporting images for offline analysis. The aim of this work is to determine whether a small, inexpensive and easily portable phantom can be used to measure the 10% and 50% MTFs of different CT scanners with sufficient accuracy to demonstrate compliance with regulatory standards and consistency with QC baseline MTF measurements and without the need for expensive phantoms or third-party software\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eThe drilled hole phantom (DHP) shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e as a tool for MTF measurements was investigated. The phantom was constructed by a computer numerical control (CNC) machine with rows of holes drilled into a 50mm x 70mm x 30mm PMMA block. The phantom was 30mm thick, with the indicated diameter of the hole is maintained to a depth of 13mm, with 13mm being the maximum hole depth achievable for the smaller holes. The spacing between the holes was twice the specified hole diameter\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02mm, resulting in the nominal hole frequency shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eAxial images were acquired with the drilled face of the DHP in the axial plane and the centre line of the rows of holes positioned vertically. Z-axis position was set to ensure drilled holes were captured in a central slice. Partial volume artefact was confirmed not to be present in the analysed image by ensuring all drilled holes were visible in the two slices adjacent to the slice being analysed.\u003c/p\u003e \u003cp\u003eThe MTF was measured with the DHP using Eq.\u0026nbsp;\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, with the input and output modulation terms measured off-site from exported DICOM images of the DHP using Weasis [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] DICOM Medical Viewer using a similar process to the bar pattern method described above.\u003c/p\u003e \u003cp\u003eFor all hole frequencies the input modulation (M\u003csub\u003ein\u003c/sub\u003e) was set as the difference in HU between air and PMMA in the phantom image, measured from ROIs positioned in a region of air next to the phantom and a uniform region of PMMA in the phantom, away from blurred edges of the phantom or the holes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe output modulation (M\u003csub\u003eout\u003c/sub\u003e(f)) at frequency f was determined from the difference between the maximum and minimum HUs within the row of circles of frequency f. For analysis, images were zoomed to enhance visualisation and the window width (WW) was set to 1HU. For each row the minimum HU was determined by reducing the window level (WL) until all the holes disappeared (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), then gradually increasing the WL until at least one pixel in three of the five holes was visible.\u003c/p\u003e \u003cp\u003eThe maximum pixel value was determined by setting the WW to 1HU, decreasing the WL until all five holes were distinct, and increasing the WL until at least two of the four gaps between the holes were connected by adjacent or diagonally connected dark pixels (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The minimum and maximum HUs in the row were the respective WLs when the above criteria were met.\u003c/p\u003e \u003cp\u003eM\u003csub\u003eout\u003c/sub\u003e(f) was calculated as the difference between these measurements at the hole frequency f. The M\u003csub\u003eout\u003c/sub\u003e(f)/ M\u003csub\u003ein\u003c/sub\u003e ratio was determined for each hole frequency to produce a plot of the MTF curve. The frequencies where the modulation ratio M(f)/M\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.5 and 0.1 were measured from a cubic spline interpolation of the plotted curve to give the 50% and 10% MTF values for the DHP.\u003c/p\u003e \u003cp\u003eFor each MTF determination using the DHP method, an image with identical acquisition and reconstruction parameters was acquired of a Siemens Definition AS\u0026thinsp;+\u0026thinsp;QA phantom containing a 0.2mm tungsten wire for a point-source MTF determination. The 10% and 50% MTFs were determined from these images using the SPICE-CT ImageJ plugin [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and compared to the corresponding DHP MTF method results.\u003c/p\u003e \u003cp\u003eMTFs were obtained on four different scanners using the scan and reconstruction parameters shown in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Selection of these parameters was guided by the typical scan conditions specified in vendor documentation. High resolution kernels were not investigated. Each series was acquired with a sequential scan.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCT scan parameters for MTF assessment\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMake\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRecon. Kernel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFocal Spot (mm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRecon. FOV (cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ekVp\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003emAs per slice\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eReconstructed Slice Thickness (mm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePixel Size (mm)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCanon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAquilion Prime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFC70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9/0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.468\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSiemens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDefinition Somatom AS+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHr38s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.488\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSiemens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSomatom Perspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eH31s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.488\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSiemens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSomatom Perspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB41s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.742\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSiemens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDefinition Open\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eH30s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.488\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSiemens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDefinition Open\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB30f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.586\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe reproducibility of the DHP MTF method was investigated by acquiring six sets of head images on the Siemens Definition AS+. Between each scan both the DHP and thin wire phantoms were slightly shifted by around 2mm in the vertical and horizontal directions with an intent to randomly shift the centrelines of the drilled holes with respect to the image matrix.\u003c/p\u003e \u003cp\u003eTo investigate the sensitivity of the DHP method at detecting modified scan conditions, the process was repeated with the Somatom Perspective head series using all the HXXs series of kernels between H10s and H50s, with no other factors changed. This resulted in an additional twelve sets of images with both increased and decreased MTFs, enabling comparison of the relative change in MTF between the DHP and thin wire methods.\u003c/p\u003e \u003cp\u003eThe image analysis of the Siemens Definition AS\u0026thinsp;+\u0026thinsp;and Canon Prime scans in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e was repeated by two other medical physicists (each with 10\u0026thinsp;+\u0026thinsp;years of experience) to investigate the reproducibility between different users. One physicist used ImageJ instead of Weasis for the analysis and both physicists were provided with the instructions to analyse the images, as outlined above, and conducted the analysis independently.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA comparison of 50% and 10% MTF values determined from the DHP and the wire/Spice-CT methods are shown in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The results showed reasonable agreement between the 50% MTF values for both methods, with an average difference of 1.9% and a range of differences between \u0026minus;\u0026thinsp;2.2% and 4.7%. The 10% MTF values for the DHP method were consistently below the wire/Spice-CT method, with an average difference of -7.3% and a range of differences between \u0026minus;\u0026thinsp;5.1% and \u0026minus;\u0026thinsp;9.7%.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of 10% and 50% MTFs results for the Spice-CT method and the DHP\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMake\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eKernel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e50% MTF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003e10% MTF\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpice-CT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDHP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDifference (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSpice-CT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDHP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eDifference (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCanon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAquilion Prime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFC70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-8.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSiemens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDefinition AS+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHr38s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-5.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSiemens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSomatom Perspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eH31s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-9.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSiemens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSomatom Perspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB41s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-8.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSiemens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDefinition Open\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB30f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-6.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSiemens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDefinition Open\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eH30s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-5.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eAverage difference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-7.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAn example of the output modulation in the phantom with the fitted cubic-spline curve and the corresponding Spice-CT MTF results for the Definition AS\u0026thinsp;+\u0026thinsp;is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eResults from the reproducibility assessment from six different acquisitions are shown in Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The DHP and thin wire methods were both reproducible with coefficients of variation\u0026thinsp;\u0026le;\u0026thinsp;0.01 for both the 10% and 50% MTF measurements.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e10% and 50% MTFs results for the Spice-CT and DHP reproducibility assessment\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e50% MTF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e10% MTF\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpice-CT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDHP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpice-CT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDHP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScan 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScan 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScan 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScan 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScan 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScan 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoV (HU)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo investigate how well the DHP detected change in the MTF, both methods were compared on thirteen different images acquired using different reconstruction kernels. MTF results were normalised to the H31s kernel results, and the percentage change from the baseline result for each kernel was calculated using both methods. The change in MTF with respect to the H31s baseline was up to \u0026plusmn;\u0026thinsp;25% for the different kernels. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows a plot of the percentage change from the baseline MTFs using the DHP method (y-axis) compared to the corresponding change for the Spice-CT result (x-axis) for each kernel. Perfect agreement between results would be the line y\u0026thinsp;=\u0026thinsp;x, shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e for reference. Agreement between the methods was strong, indicating that the DHP correctly measured the change in MTF for modified image reconstructions.\u003c/p\u003e \u003cp\u003eThe comparison between results obtained by three different medical physicists interpreting the same images is shown in Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The results showed good agreement between different physicists, the largest difference was a 2% difference between two of the medical physicists for the 10% MTF measurement on the Canon Aquilion Prime system.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of MTF results from the DHP phantom when images were assessed by three different medical physicists\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eSiemens Definition AS+\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eCanon Aquilion Prime\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50% MTF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10% MTF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50% MTF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10% MTF\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical physicist 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical physicist 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical physicist 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eRoutine QC testing of spatial resolution of CT scanners as part of a quality assurance program and/or to meet regulatory compliance testing standards typically includes ensuring the MTF is consistent with manufacturer tolerances or baseline values. The MTF results from the DHP method were reproducible between different users and for measurements using repeated image acquisitions, and were able to accurately detect changes in the 10% and 50% MTFs induced by using different reconstruction kernels. Using the wire/Spice-CT method as a reference the DHP measured the 50% MTF for CT scans using standard resolution reconstruction kernels with reasonable accuracy, but consistently underestimated the 10% MTF by an average of 8.2%. Given the ability of the DHP to accurately measure a change in the MTF with respect to a baseline result, an appropriate application of this phantom would be to confirm MTF performance with respect to manufacturer specifications during acceptance testing using an established method, and simultaneously setting MTF baselines using the DHP for subsequent testing. Direct comparison of the 10% MTF to the corresponding manufacturer specifications may be inappropriate given the consistent underestimation of this result with the DHP, particularly if the 10% measured with the DHP was below manufacturer specifications.\u003c/p\u003e \u003cp\u003eAn assumption of this work is that Spice-CT/wire method is a suitable method for MTF measurements. Checking the MTF using an additional method would allow confirmation of agreement between the acceptance test method and the DHP.\u003c/p\u003e \u003cp\u003eThe method used to assess the MTF with the DHP is similar to an approach that can be employed with a bar pattern phantom, where the modulation ratio in a bar a set of bars at frequency f is scaled by pi/4 to give the MTF at frequency f (Eq.\u0026nbsp;2). The relationship between the MTF and the modulation ratio as is not so simple for the DHP phantom, as shown by the systematic underestimation of the 10% MTF. Spice-CT only provides the 50% and 10% MTF results, so whilst out of scope for this work it would be interesting to compare a full MTF curve acquired with an established method to the curve produced by the DHP method.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the minimum HU occurs in the centre of the holes, and the maximum HU occurs in the region between the holes where the edges of the holes are closest together. When the WL is increased beyond the maximum HU, the band of dark pixels between the holes spreads out from the centre line, indicating that modulation results are measured from the single column of pixels best aligned with the centre line of the holes. The visual criteria for determining minimum and maximum HUs were chosen to be both unambiguous for the assessor, and to return the median minimum and maximum values in the respective troughs (holes) and peaks (space between the holes) in the regions between the holes.\u003c/p\u003e \u003cp\u003eWith a single line of pixels being sampled for each set of holes, and random alignment of the line of pixels with respect to the centre line of the holes, some variation in the measured MTF would be expected. In practice the variation was minimal when assessing the DHP on multiple images with the phantom randomly shifted vertically and horizontally between each image acquisition. For this set of images, the 10% MTF measured on Spice CT occurred around 5.9 lp/cm. The closest frequency hole set for the DHP is 6.25 lp/cm, which has 0.8mm diameter holes and a 0.8mm gap between the holes, compared to the 0.488mm pixel size. The two body modes investigated had pixel sizes of 0.742mm and 0.586mm. The discrepancy between the Spice-CT and DHP 10% MTFs for these modes was less than the average discrepancy across all the modes, suggesting that reduction in modulation due to the increased pixel size is comparable for both methods.\u003c/p\u003e \u003cp\u003eFigure 7 shows the pixel values from the centre line of pixels through three different sets of drilled holes. An image of a bar pattern will also produce a decreasing range of pixel values as the frequency of the bar set increases, with the pixel values converging to the average HU of the pattern materials as the frequency increases. For the DHP images in this work the HU converged to values between \u0026minus;\u0026thinsp;40HU and \u0026minus;\u0026thinsp;110HU at high frequencies for the images assessed. The bulk of the observed modulation in the DHP therefore was due to an increase in the minimum HU, opposed to a modest decrease in the maximum HU. The asymmetric changes to the minimum and maximum HU are due to the difference in material surrounding the area in the phantom where the minimum and maximum HUs are observed. The air holes are surrounded by PMMA, and the air-PMMA edge is blurred by the imaging system and thus increasing the HU in the hole. The increase in HU becomes larger at higher frequencies as the holes become smaller with respect to the extent of introduced blurring. The gaps between the holes are surrounded by both air and PMMA, and the reduction in pixel values in the region by blurring from the air holes is watered down by blurring from PMMA adjacent to the gap, resulting in less decrease to the maximum HU in the gap compared to the increased HU in the hole.\u003c/p\u003e \u003cp\u003eThe DHP was not investigated for higher resolution kernels which may have 10% and 50% MTFs greater than 10 lp/cm, beyond the highest frequency (10 lp/cm) holes used in the DHP. The manufacturing uncertainty in the hole placement was 0.02mm. This introduces an uncertainty up to 4% for the 10 lp/cm hole set. The uncertainty would increase to 8% for a 20 lp/cm hole if constructed with the same tolerance.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eUsing the thin wire/Spice-CT as a reference method, the DHP method was able to provide a reasonably accurate measurement of the 50% MTF, but systematically underestimated the 10% MTF by 5\u0026ndash;10%. The DHP results were reproducible between different image acquisitions and different users interpreting the images. The DHP method accurately measured changes to 10% and 50% MTFs results for images using different reconstruction kernels when compared to baseline results with standard settings, indicating the phantom could be used for QC purposes.\u003c/p\u003e \u003cp\u003eThe advantage of the DHP is that it is cheap, easily portable, and image analysis can be readily performed by the user on scanner console or PACS workstation without the need for exporting images or software for analysis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eSTATEMENTS \u0026amp; DECLARATIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests to declare that are relevant to the content of this article.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis is a phantom study and ethical approval is not required\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eInternational Atomic Energy Agency (2012) Quality assurance programme for computed tomography: diagnostic and therapy applications. IAEA Human Health Series No. 19, IAEA, Vienna\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStandards Australia \u0026amp; Standards New Zealand (2022) Evaluation and Routine Testing in Medical Imaging Departments, Part 3.5: Acceptance and constancy tests \u0026ndash; Imaging performance of computed tomography X-ray equipment, AS/NZS IEC 61223.3.5:2022\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAhmed SN (2007) Physics and Engineering of Radiation Detection, First Edition. Elsevier Inc.), p 435\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKayugawa A, Ohkubo M, Wada S (2013) Accurate determination of CT point-spread-function with high precision. J Appl Clin Med Phys 14(4):216\u0026ndash;226\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMie\u0026acute;ville F, Beaumont S, Torfeh T, Gudinchet F, Verdun FR (2010) Computed tomography commissioning programmes: How to obtain a reliable MTF with an automatic approach? Radiat. Prot Dosim 139(1 \u0026ndash;3):443\u0026ndash;448\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFriedman SN, Fung GSK, Siewerdsen JH, Tsui BMW (2013) A simple approach to measure computed tomography (CT) modulation transfer function (MTF) and noise-power spectrum (NPS) using the American College of Radiology (ACR) accreditation phantom. Med Phys 40:051907\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZabilal E et al (2020) An improvement in automatic MTF measurement in CT images using an edge of the PMMA phantom. J Phys : Conf Ser 1505:012039\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHusby E, Svendsen ED, Andersen HK, Martinsen ACT (2017) 100 days with scans of the same Catphan phantom on the same CT scanner. J Appl Clin Med Phys 18(6):224\u0026ndash;231\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFriedman SN, Fung GSK, Siewerdsen JH, Tsui BMW (2013) A simple approach to measure computed tomography (CT) modulation transfer function (MTF) and noise-power spectrum (NPS) using the American College of Radiology (ACR) accreditation phantom. Med Phys 40:051907\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDroege R, Morin R (1982) A practical method to measure the MTF of CT scanners. Med Phys 9(5):758\u0026ndash;760\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeasis DICOM Medical Viewer version 4.0 [computer software]\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLoveland J (2011) SPICE-CT [computer software]. Edinburgh\u003c/span\u003e\u003c/li\u003e \u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"physical-and-engineering-sciences-in-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"apes","sideBox":"Learn more about [Physical and Engineering Sciences in Medicine](http://link.springer.com/journal/13246)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/apes/default.aspx","title":"Physical and Engineering Sciences in Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Modulation transfer function, computed tomography, phantom, spatial resolution","lastPublishedDoi":"10.21203/rs.3.rs-4007337/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4007337/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eA novel phantom for measuring the 10% and 50% values of the modulation transfer function (MTF) for computed tomography scanners (CT) was investigated. The phantom was constructed by drilling rows of holes of different sizes and frequencies into a small block of polymethyl methacrylate (PMMA). The MTF at a given frequency was determined from the ratio of the range of Hounsfield units within the rows of holes at different frequencies, and the difference in Hounsfield units between air and PMMA. A MTF curve was plotted from measurements at different frequencies and the 10% and 50% MTF values were obtained from a cubic spline interpolation. The MTF results obtained with the drilled hole phantom method were compared to a conventional method - using a thin wire and Spice-CT ImageJ Plugin \u0026ndash; and with identical acquisition and reconstruction parameters. The drilled hole phantom measured the 50% MTF with reasonable accuracy but underestimated the 10% MTF by 8.2% on average. MTF measurements were reproducible for repeated image acquisitions and with different users analysing the images, and the phantom was able to accurately measure the change in MTF when measured on images using different reconstruction kernels. The tool may find application as a cheap, easy to use method for routine QC testing of CT scanners.\u003c/p\u003e","manuscriptTitle":"Measurement of computed tomography modulation transfer function with a novel polymethyl methacrylate phantom","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-11 18:45:11","doi":"10.21203/rs.3.rs-4007337/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor revisions","date":"2024-04-09T00:32:11+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-03-11T00:57:52+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-06T01:28:38+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Physical and Engineering Sciences in Medicine","date":"2024-03-04T04:09:11+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-04T04:02:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"Physical and Engineering Sciences in Medicine","date":"2024-03-02T21:36:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"physical-and-engineering-sciences-in-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"apes","sideBox":"Learn more about [Physical and Engineering Sciences in Medicine](http://link.springer.com/journal/13246)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/apes/default.aspx","title":"Physical and Engineering Sciences in Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"96dc86a8-26e0-48e3-a11e-a336fcf61df7","owner":[],"postedDate":"March 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-09-16T16:06:28+00:00","versionOfRecord":{"articleIdentity":"rs-4007337","link":"https://doi.org/10.1007/s13246-024-01468-z","journal":{"identity":"physical-and-engineering-sciences-in-medicine","isVorOnly":false,"title":"Physical and Engineering Sciences in Medicine"},"publishedOn":"2024-09-09 15:58:29","publishedOnDateReadable":"September 9th, 2024"},"versionCreatedAt":"2024-03-11 18:45:11","video":"","vorDoi":"10.1007/s13246-024-01468-z","vorDoiUrl":"https://doi.org/10.1007/s13246-024-01468-z","workflowStages":[]},"version":"v1","identity":"rs-4007337","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4007337","identity":"rs-4007337","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}