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Martin CJ, Kortesniemi MK, Sutton DG, Applegate K, Vassileva J. A strategy for achieving optimisation of radiological protection in digital radiology proposed by ICRP. JOURNAL OF RADIOLOGICAL PROTECTION : OFFICIAL JOURNAL OF THE SOCIETY FOR RADIOLOGICAL PROTECTION 2024; 44:041511. [PMID: 39555658 DOI: 10.1088/1361-6498/ad60d1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 07/09/2024] [Indexed: 11/19/2024]
Abstract
Radiology is now predominantly a digital medium and this has extended the flexibility, efficiency and application of medical imaging. Achieving the full benefit of digital radiology requires images to be of sufficient quality to make a reliable diagnosis for each patient, while minimising risks from radiation exposure, and so involves a careful balance between competing objectives. When an optimisation programme is undertaken, a knowledge of patient doses from surveys can be valuable in identifying areas needing attention. However, any dose reduction measures must not degrade image quality to the extent that it is inadequate for the clinical purpose. The move to digital imaging has enabled versatile image acquisition and presentation, including multi-modality display and quantitative assessment, with post-processing options that adjust for optimal viewing. This means that the appearance of an image is unlikely to give any indication when the dose is higher than necessary. Moreover, options to improve performance of imaging equipment add to its complexity, so operators require extensive training to be able to achieve this. Optimisation is a continuous rather than single stage process that requires regular monitoring, review, and analysis of performance feeding into improvement and development of imaging protocols. The ICRP is in the process of publishing two reports about optimisation in digital radiology. The first report sets out components needed to ensure that a radiology service can carry optimisation through. It describes how imaging professionals should work together as a team and explains the benefits of having appropriate methodologies to monitor performance, together with the knowledge and expertise required to use them effectively. It emphasises the need for development of organisational processes that ensure tasks are carried out. The second ICRP report deals with practical requirements for optimisation of different digital radiology modalities, and builds on information provided in earlier modality specific ICRP publications.
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Affiliation(s)
- Colin J Martin
- Department of Clinical Physics and Bio-engineering, University of Glasgow, Glasgow, United Kingdom
| | | | - David G Sutton
- Medical Physics, University of Dundee, Dundee, United Kingdom
| | | | - Jenia Vassileva
- International Atomic Energy Agency, Vienna International Centre, 1400 Vienna, Austria
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2
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Gao M, Fessler JA, Chan HP. Model-based deep CNN-regularized reconstruction for digital breast tomosynthesis with a task-based CNN image assessment approach. Phys Med Biol 2023; 68:245024. [PMID: 37988758 PMCID: PMC10719554 DOI: 10.1088/1361-6560/ad0eb4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 11/02/2023] [Accepted: 11/21/2023] [Indexed: 11/23/2023]
Abstract
Objective. Digital breast tomosynthesis (DBT) is a quasi-three-dimensional breast imaging modality that improves breast cancer screening and diagnosis because it reduces fibroglandular tissue overlap compared with 2D mammography. However, DBT suffers from noise and blur problems that can lower the detectability of subtle signs of cancers such as microcalcifications (MCs). Our goal is to improve the image quality of DBT in terms of image noise and MC conspicuity.Approach. We proposed a model-based deep convolutional neural network (deep CNN or DCNN) regularized reconstruction (MDR) for DBT. It combined a model-based iterative reconstruction (MBIR) method that models the detector blur and correlated noise of the DBT system and the learning-based DCNN denoiser using the regularization-by-denoising framework. To facilitate the task-based image quality assessment, we also proposed two DCNN tools for image evaluation: a noise estimator (CNN-NE) trained to estimate the root-mean-square (RMS) noise of the images, and an MC classifier (CNN-MC) as a DCNN model observer to evaluate the detectability of clustered MCs in human subject DBTs.Main results. We demonstrated the efficacies of CNN-NE and CNN-MC on a set of physical phantom DBTs. The MDR method achieved low RMS noise and the highest detection area under the receiver operating characteristic curve (AUC) rankings evaluated by CNN-NE and CNN-MC among the reconstruction methods studied on an independent test set of human subject DBTs.Significance. The CNN-NE and CNN-MC may serve as a cost-effective surrogate for human observers to provide task-specific metrics for image quality comparisons. The proposed reconstruction method shows the promise of combining physics-based MBIR and learning-based DCNNs for DBT image reconstruction, which may potentially lead to lower dose and higher sensitivity and specificity for MC detection in breast cancer screening and diagnosis.
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Affiliation(s)
- Mingjie Gao
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109, United States of America
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Jeffrey A Fessler
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109, United States of America
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Heang-Ping Chan
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109, United States of America
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Salomon E, Unger E, Homolka P, Cockmartin L, Petrov D, Semturs F, Songsaeng C, Panagiotis K, Vancoillie L, Figl M, Sommer A, Bosmans H, Hummel J. Technical note: Realization and uncertainty analysis for an adjustable 3D structured breast phantom in digital breast tomosynthesis. Med Phys 2023; 50:4816-4824. [PMID: 37438921 DOI: 10.1002/mp.16600] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 04/09/2023] [Accepted: 06/07/2023] [Indexed: 07/14/2023] Open
Abstract
BACKGROUND Projection imaging phantoms are often optimized for 2-dimensional image characteristics in homogeneous backgrounds. Therefore, evaluation of image quality in tomosynthesis (DBT) lacks accepted and established phantoms. PURPOSE We describe a 3D breast phantom with a structured, variable background. The phantom is an adaptable and advanced version of the L1 phantom by Cockmartin et al. Phantom design and its use for quality assurance measurements for DBT devices are described. Four phantoms were compared to assess the objectivity. METHODS The container size was increased to a diameter of 24 cm and a total height of 53.5 mm. Spiculated masses were replaced by five additional non-spiculated masses for higher granularity in threshold diameter resolution. These patterns are adjustable to the imaging device. The masses were printed in one session with a base layer using two-component 3D printing. New materials compared to the L1 phantom improved the attenuation difference between the lesion models and the background. Four phantoms were built and intra-human observer, inter-human observer and inter-phantom variations were determined. The latter assess the reproducibility of the phantom production. Coefficients of variance (V) were calculated for all three variations. RESULTS The difference of the attenuation coefficients between the lesion models and the background was 0.20 cm-1 (with W/Al at 32 kV, equivalent to 19-20 keV effective energy) compared to 0.21 cm-1 for 50/50 glandular/adipose breast tissue and cancerous lesions. PMMA equivalent thickness of the phantom was 47.0 mm for the Siemens Mammomat Revelation. For the masses, theV i n t r a $V_{intra}$ for the intra-observer variation was 0.248, the averaged inter-observer variation,V ¯ i n t e r $\overline{V}_{inter}$ was 0.383.V p h a n t o m $V_{phantom}$ for phantom variance was 0.321. For the micro-calcifications,V i n t r a $V_{intra}$ was 0.0429,V ¯ i n t e r = $\overline{V}_{inter}=$ 0.0731 andV p h a n t o m = $V_{phantom}=$ 0.0759. CONCLUSIONS Position, orientation and shape of the masses are reproducible and attenuation differences appropriate. The phantom presented proved to be a candidate test object for quality control.
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Affiliation(s)
- Elisabeth Salomon
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Spitalgasse, Vienna, Austria
| | - Ewald Unger
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Spitalgasse, Vienna, Austria
| | - Peter Homolka
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Spitalgasse, Vienna, Austria
| | | | - Dimitar Petrov
- Department of Radiology, UZ Gasthuisberg, Leuven, Belgium
| | - Friedrich Semturs
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Spitalgasse, Vienna, Austria
| | - Chatsuda Songsaeng
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Spitalgasse, Vienna, Austria
- Christian Doppler Laboratory for Mathematical Modelling and Simulation of Next-Generation Medical Ultrasound Devices, Vienna, Austria
| | - Kapetas Panagiotis
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna and General Hospital, Spitalgasse, Vienna, Austria
| | | | - Michael Figl
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Spitalgasse, Vienna, Austria
- Christian Doppler Laboratory for Mathematical Modelling and Simulation of Next-Generation Medical Ultrasound Devices, Vienna, Austria
| | - Alexander Sommer
- Clinic for Radiology and Reference Center for Mammography Münster, University of Münster and University Hospital Münster, Münster, Germany
| | - Hilde Bosmans
- Department of Radiology, UZ Gasthuisberg, Leuven, Belgium
| | - Johann Hummel
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Spitalgasse, Vienna, Austria
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Marshall NW, Bosmans H. Performance evaluation of digital breast tomosynthesis systems: physical methods and experimental data. Phys Med Biol 2022; 67. [DOI: 10.1088/1361-6560/ac9a35] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 10/13/2022] [Indexed: 11/17/2022]
Abstract
Abstract
Digital breast tomosynthesis (DBT) has become a well-established breast imaging technique, whose performance has been investigated in many clinical studies, including a number of prospective clinical trials. Results from these studies generally point to non-inferiority in terms of microcalcification detection and superior mass-lesion detection for DBT imaging compared to digital mammography (DM). This modality has become an essential tool in the clinic for assessment and ad-hoc screening but is not yet implemented in most breast screening programmes at a state or national level. While evidence on the clinical utility of DBT has been accumulating, there has also been progress in the development of methods for technical performance assessment and quality control of these imaging systems. DBT is a relatively complicated ‘pseudo-3D’ modality whose technical assessment poses a number of difficulties. This paper reviews methods for the technical performance assessment of DBT devices, starting at the component level in part one and leading up to discussion of system evaluation with physical test objects in part two. We provide some historical and basic theoretical perspective, often starting from methods developed for DM imaging. Data from a multi-vendor comparison are also included, acquired under the medical physics quality control protocol developed by EUREF and currently being consolidated by a European Federation of Organisations for Medical Physics working group. These data and associated methods can serve as a reference for the development of reference data and provide some context for clinical studies.
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Avramova-Cholakova S, Kulama E, Daskalov S, Loveland J. PERFORMANCE COMPARISON OF SYSTEMS WITH FULL-FIELD DIGITAL MAMMOGRAPHY, DIGITAL BREAST TOMOSYNTHESIS AND CONTRAST-ENHANCED SPECTRAL MAMMOGRAPHY. RADIATION PROTECTION DOSIMETRY 2021; 197:212-229. [PMID: 34977945 DOI: 10.1093/rpd/ncab172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 07/12/2021] [Accepted: 11/16/2021] [Indexed: 06/14/2023]
Abstract
The purpose is to compare full-field digital mammography (FFDM), digital breast tomosynthesis (DBT) and contrast-enhanced spectral mammography (CESM) technologies on three mammography systems in terms of image quality and patient dose. Two Senographe Essential with DBT and CESM (denoted S1 and S2) and one Selenia Dimensions (S3) with FFDM and DBT were considered. Dosimetry methods recommended in the European protocol were used. Image quality was tested with CDMAM in FFDM and DBT and with ideal observer method in FFDM. Mean values of mean glandular dose (MGD) from whole patient samples on S1, S2 and S3 were as follows: FFDM 1.65, 1.84 and 2.23 mGy; DBT 2.03, 1.96 and 2.87 mGy; CESM 2.65 and 3.16 mGy, respectively. S3 exhibited better low-contrast detectability for the smallest sized discs of CDMAM and ideal observer in FFDM, and for the largest sized discs in DBT, at similar dose levels.
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Anton M, Reginatto M, Elster C, Mäder U, Schopphoven S, Sechopoulos I, van Engen R. The regression detectability index RDI for mammography images of breast phantoms with calcification-like objects and anatomical background. Phys Med Biol 2021; 66. [PMID: 34706354 DOI: 10.1088/1361-6560/ac33ea] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 10/27/2021] [Indexed: 11/11/2022]
Abstract
Currently, quality assurance measurements in mammography are performed on unprocessed images. For diagnosis, however, radiologists are provided with processed images. This image processing is optimised for images of human anatomy and therefore does not always perform satisfactorily with technical phantoms. To overcome this problem, it may be possible to use anthropomorphic phantoms reflecting the anatomic structure of the human breast in place of technical phantoms when carrying out task-specific quality assessment using model observers. However, the use of model observers is hampered by the fact that a large number of images needs to be acquired. A recently published novel observer called the regression detectability index (RDI) needs significantly fewer images, but requires the background of the images to be flat. Therefore, to be able to apply the RDI to images of anthropomorphic phantoms, the anatomic background needs to be removed. For this, a procedure in which the anatomical structures are fitted by thin plate spline (TPS) interpolation has been developed. When the object to be detected is small, such as a calcification-like lesion, it is shown that the anatomic background can be removed successfully by subtracting the TPS interpolation, which makes the background-free image accessible to the RDI. We have compared the detectability obtained by the RDI with TPS background subtraction to results of the channelized Hotelling observer (CHO) and human observers. With the RDI, results for the detectabilityd'can be obtained using 75% fewer images compared to the CHO, while the same uncertainty ofd'is achieved. Furthermore, the correlation ofd'(RDI) with the results of human observers is at least as good as that ofd'(CHO) with human observers.
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Affiliation(s)
- M Anton
- Physikalisch-Technische Bundesanstalt Braunschweig and Berlin, Germany
| | - M Reginatto
- Physikalisch-Technische Bundesanstalt Braunschweig and Berlin, Germany
| | - C Elster
- Physikalisch-Technische Bundesanstalt Braunschweig and Berlin, Germany
| | - U Mäder
- Institute of Medical Physics and Radiation Protection, University of Applied Sciences, Giessen, Germany
| | - S Schopphoven
- Reference Centre for Mammography Screening Southwest Germany, Marburg, Germany
| | - I Sechopoulos
- Radboud University Medical Center, Nijmegen, The Netherlands.,LRCB Dutch Expert Centre for Screening, Nijmegen, The Netherlands
| | - R van Engen
- LRCB Dutch Expert Centre for Screening, Nijmegen, The Netherlands
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Wigati KT, Marshall NW, Lemmens K, Binst J, Jacobs A, Cockmartin L, Zhang G, Vancoillie L, Petrov D, Vandenbroucke DAN, Soejoko DS, Bosmans H. On the relevance of modulation transfer function measurements in digital mammography quality control. J Med Imaging (Bellingham) 2021; 8:023505. [PMID: 33937435 DOI: 10.1117/1.jmi.8.2.023505] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 03/31/2021] [Indexed: 11/14/2022] Open
Abstract
Purpose: The relevance of presampling modulation transfer function (MTF) measurements in digital mammography (DM) quality control (QC) is examined. Two studies are presented: a case study on the impact of a reduction in MTF on the technical image quality score and analysis of the robustness of routine QC MTF measurements. Approach: In the first study, two needle computed radiography (CR) plates with identical sensitivities were used with differences in the 50% point of the MTF ( f MTF 0.5 ) larger than the limiting value in the European guidelines ( > 10 % change between successive measurements). Technical image quality was assessed via threshold gold thickness of the CDMAM phantom and threshold microcalcification diameter of the L1 structured phantom. For the second study, presampling MTF results from 595 half-yearly QC tests of 55 DM systems (16 types, six manufacturers) were analyzed for changes from the baseline value and changes in f MTF 0.5 between successive tests. Results: A reduction of 20% in f MTF 0.5 of the two CR plates was observed. There was a tendency to a lower score for task-based metrics, but none were significant. Averaging over 55 systems, the absolute relative change in f MTF 0.5 between consecutive tests (with 95% confidence interval) was 3% (2.5% to 3.4%). Analysis of the maximum relative change from baseline revealed changes of up to - 10 % for one a-Se based system and - 15 % for a group of CsI-based systems. Conclusions: A limit of 10% is a relevant action level for investigation. If exceeded, then the impact on performance has to be verified with extra metrics.
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Affiliation(s)
- Kristina T Wigati
- KU Leuven, Department of Imaging and Pathology, Leuven, Belgium.,Universitas Indonesia, Department of Physics, Depok, Indonesia
| | - Nicholas W Marshall
- KU Leuven, Department of Imaging and Pathology, Leuven, Belgium.,UZ Leuven, Department of Radiology, Leuven, Belgium
| | - Kim Lemmens
- UZ Leuven, Department of Radiology, Leuven, Belgium
| | - Joke Binst
- UZ Leuven, Department of Radiology, Leuven, Belgium
| | | | - Lesley Cockmartin
- KU Leuven, Department of Imaging and Pathology, Leuven, Belgium.,UZ Leuven, Department of Radiology, Leuven, Belgium
| | - Guozhi Zhang
- UZ Leuven, Department of Radiology, Leuven, Belgium
| | - Liesbeth Vancoillie
- KU Leuven, Department of Imaging and Pathology, Leuven, Belgium.,UZ Leuven, Department of Radiology, Leuven, Belgium
| | - Dimitar Petrov
- KU Leuven, Department of Imaging and Pathology, Leuven, Belgium.,UZ Leuven, Department of Radiology, Leuven, Belgium
| | | | | | - Hilde Bosmans
- KU Leuven, Department of Imaging and Pathology, Leuven, Belgium.,UZ Leuven, Department of Radiology, Leuven, Belgium
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Ricciardi R, Mettivier G, Staffa M, Sarno A, Acampora G, Minelli S, Santoro A, Antignani E, Orientale A, Pilotti I, Santangelo V, D'Andria P, Russo P. A deep learning classifier for digital breast tomosynthesis. Phys Med 2021; 83:184-193. [DOI: 10.1016/j.ejmp.2021.03.021] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 02/04/2021] [Accepted: 03/13/2021] [Indexed: 10/21/2022] Open
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Bliznakova K. The advent of anthropomorphic three-dimensional breast phantoms for X-ray imaging. Phys Med 2020; 79:145-161. [DOI: 10.1016/j.ejmp.2020.11.025] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2020] [Revised: 11/16/2020] [Accepted: 11/19/2020] [Indexed: 10/22/2022] Open
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Lee C, Han M, Baek J. Human observer performance on in-plane digital breast tomosynthesis images: Effects of reconstruction filters and data acquisition angles on signal detection. PLoS One 2020; 15:e0229915. [PMID: 32163472 PMCID: PMC7067468 DOI: 10.1371/journal.pone.0229915] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Accepted: 02/17/2020] [Indexed: 11/29/2022] Open
Abstract
For digital breast tomosynthesis (DBT) systems, we investigate the effects of the reconstruction filters for different data acquisition angles on signal detection. We simulated a breast phantom with a 30% volume glandular fraction (VGF) of breast anatomy using the power law spectrum and modeled the breast mass as a spherical object with a 1 mm diameter. Projection data were acquired using two different data acquisition angles and numbers of projection view pairs, and in-plane breast images were reconstructed using the Feldkamp-Davis-Kress (FDK) algorithm with three different reconstruction filter schemes. To measure the ability to detect a signal, we conducted the human observer study with a binary detection task and compared the signal detectability of human to that of channelized Hotelling observer (CHO) with Laguerre-Gauss (LG) channels and dense difference-of-Gaussian (D-DOG) channels. We also measured the contrast-to-noise ratio (CNR), signal power spectrum (SPS), and β values of the anatomical noise power spectrum (NPS) to show the association between human observer performance and these traditional metrics. Our results show that using a slice thickness (ST) filter degraded the signal detection performance of human observers at the same data acquisition angle. This could be predicted by D-DOG CHO with internal noise, but the correlation between the traditional metrics and signal detectability was not observed in this work.
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Affiliation(s)
- Changwoo Lee
- Center for Medical Convergence Metrology, Korea Research Institute of Standards and Science (KRISS), Daejeon, South Korea
| | - Minah Han
- School of Integrated Technology and Yonsei Institute of Convergence Technology, Yonsei University, Incheon, South Korea
| | - Jongduk Baek
- School of Integrated Technology and Yonsei Institute of Convergence Technology, Yonsei University, Incheon, South Korea
- * E-mail:
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Petrov D, Marshall N, Young K, Zhang G, Bosmans H. Model and human observer reproducibility for detection of microcalcification clusters in digital breast tomosynthesis images of three-dimensionally structured test object. J Med Imaging (Bellingham) 2019; 6:015503. [PMID: 30915383 DOI: 10.1117/1.jmi.6.1.015503] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2018] [Accepted: 03/05/2019] [Indexed: 11/14/2022] Open
Abstract
We compare the reproducibility of the human observers and a channelized Hotelling observer (CHO), when reading digital breast tomosynthesis (DBT) images of a physical phantom containing a breast simulating structured background and calcification clusters at three dose levels. The phantom is scanned 217 times on a Siemens Inspiration DBT system. Volumes of interest, with and without the calcification targets, are extracted and the human observers' percentage of correct (PC) scores is evaluated using a four-alternative forced choice method. A two-layer CHO is developed using the human observer results. The first layer consists of a localizing CHO that identifies the most conspicuous calcifications using two Laguerre-Gauss channels. Then a CHO with eight Gabor channels estimates the PC score for the calcification cluster. Observer reproducibility is estimated by bootstrapping, and the standard deviation (SD) is used as a figure of merit. The CHO closely approximated the human observer results for all the three dose levels with a correlation of > 0.97 . For the larger calcification cluster sizes, both observers have similar reproducibility, whereas the CHO is more reproducible for the smaller calcifications, with a maximum of 5.5 SD against 13.1 SD for the human observers. The developed CHO is a good candidate for automated reading of the calcification clusters of the structured phantom, with better reproducibility than the human readers for small calcifications.
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Affiliation(s)
- Dimitar Petrov
- KU Leuven, Department of Medical Physics and Quality Assessment, Leuven, Belgium
| | - Nicholas Marshall
- KU Leuven, Department of Medical Physics and Quality Assessment, Leuven, Belgium.,UZ Leuven, Department of Radiology, Leuven, Belgium
| | - Kenneth Young
- Royal Surrey County Hospital, NCCPM, Guildford, United Kingdom
| | - Guozhi Zhang
- UZ Leuven, Department of Radiology, Leuven, Belgium
| | - Hilde Bosmans
- KU Leuven, Department of Medical Physics and Quality Assessment, Leuven, Belgium.,UZ Leuven, Department of Radiology, Leuven, Belgium
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