Literature DB >> 26383027

Comparison study of reconstruction algorithms for prototype digital breast tomosynthesis using various breast phantoms.

Ye-seul Kim1, Hye-suk Park1, Haeng-Hwa Lee1, Young-Wook Choi2, Jae-Gu Choi2, Hak Hee Kim3, Hee-Joung Kim4.   

Abstract

Digital breast tomosynthesis (DBT) is a recently developed system for three-dimensional imaging that offers the potential to reduce the false positives of mammography by preventing tissue overlap. Many qualitative evaluations of digital breast tomosynthesis were previously performed by using a phantom with an unrealistic model and with heterogeneous background and noise, which is not representative of real breasts. The purpose of the present work was to compare reconstruction algorithms for DBT by using various breast phantoms; validation was also performed by using patient images. DBT was performed by using a prototype unit that was optimized for very low exposures and rapid readout. Three algorithms were compared: a back-projection (BP) algorithm, a filtered BP (FBP) algorithm, and an iterative expectation maximization (EM) algorithm. To compare the algorithms, three types of breast phantoms (homogeneous background phantom, heterogeneous background phantom, and anthropomorphic breast phantom) were evaluated, and clinical images were also reconstructed by using the different reconstruction algorithms. The in-plane image quality was evaluated based on the line profile and the contrast-to-noise ratio (CNR), and out-of-plane artifacts were evaluated by means of the artifact spread function (ASF). Parenchymal texture features of contrast and homogeneity were computed based on reconstructed images of an anthropomorphic breast phantom. The clinical images were studied to validate the effect of reconstruction algorithms. The results showed that the CNRs of masses reconstructed by using the EM algorithm were slightly higher than those obtained by using the BP algorithm, whereas the FBP algorithm yielded much lower CNR due to its high fluctuations of background noise. The FBP algorithm provides the best conspicuity for larger calcifications by enhancing their contrast and sharpness more than the other algorithms; however, in the case of small-size and low-contrast microcalcifications, the FBP reduced detectability due to its increased noise. The EM algorithm yielded high conspicuity for both microcalcifications and masses and yielded better ASFs in terms of the full width at half maximum. The higher contrast and lower homogeneity in terms of texture analysis were shown in FBP algorithm than in other algorithms. The patient images using the EM algorithm resulted in high visibility of low-contrast mass with clear border. In this study, we compared three reconstruction algorithms by using various kinds of breast phantoms and patient cases. Future work using these algorithms and considering the type of the breast and the acquisition techniques used (e.g., angular range, dose distribution) should include the use of actual patients or patient-like phantoms to increase the potential for practical applications.

Entities:  

Keywords:  Anthropomorphic breast phantom; Digital breast tomosynthesis; Filtered back-projection; Iterative reconstruction algorithm

Mesh:

Year:  2015        PMID: 26383027     DOI: 10.1007/s11547-015-0583-4

Source DB:  PubMed          Journal:  Radiol Med        ISSN: 0033-8362            Impact factor:   3.469


  15 in total

Review 1.  Digital x-ray tomosynthesis: current state of the art and clinical potential.

Authors:  James T Dobbins; Devon J Godfrey
Journal:  Phys Med Biol       Date:  2003-10-07       Impact factor: 3.609

2.  A comparison of reconstruction algorithms for breast tomosynthesis.

Authors:  Tao Wu; Richard H Moore; Elizabeth A Rafferty; Daniel B Kopans
Journal:  Med Phys       Date:  2004-09       Impact factor: 4.071

3.  A comparative study of limited-angle cone-beam reconstruction methods for breast tomosynthesis.

Authors:  Yiheng Zhang; Heang-Ping Chan; Berkman Sahiner; Jun Wei; Mitchell M Goodsitt; Lubomir M Hadjiiski; Jun Ge; Chuan Zhou
Journal:  Med Phys       Date:  2006-10       Impact factor: 4.071

Review 4.  Breast tomosynthesis: present considerations and future applications.

Authors:  Jeong Mi Park; Edmund A Franken; Megha Garg; Laurie L Fajardo; Loren T Niklason
Journal:  Radiographics       Date:  2007-10       Impact factor: 5.333

5.  Digital breast tomosynthesis: observer performance study.

Authors:  David Gur; Gordon S Abrams; Denise M Chough; Marie A Ganott; Christiane M Hakim; Ronald L Perrin; Grace Y Rathfon; Jules H Sumkin; Margarita L Zuley; Andriy I Bandos
Journal:  AJR Am J Roentgenol       Date:  2009-08       Impact factor: 3.959

6.  X-ray characterization of breast phantom materials.

Authors:  J W Byng; J G Mainprize; M J Yaffe
Journal:  Phys Med Biol       Date:  1998-05       Impact factor: 3.609

7.  Analysis of parenchymal texture with digital breast tomosynthesis: comparison with digital mammography and implications for cancer risk assessment.

Authors:  Despina Kontos; Lynda C Ikejimba; Predrag R Bakic; Andrea B Troxel; Emily F Conant; Andrew D A Maidment
Journal:  Radiology       Date:  2011-07-19       Impact factor: 11.105

Review 8.  A review of breast tomosynthesis. Part II. Image reconstruction, processing and analysis, and advanced applications.

Authors:  Ioannis Sechopoulos
Journal:  Med Phys       Date:  2013-01       Impact factor: 4.071

Review 9.  A review of breast tomosynthesis. Part I. The image acquisition process.

Authors:  Ioannis Sechopoulos
Journal:  Med Phys       Date:  2013-01       Impact factor: 4.071

10.  Parenchymal texture analysis in digital breast tomosynthesis for breast cancer risk estimation: a preliminary study.

Authors:  Despina Kontos; Predrag R Bakic; Ann-Katherine Carton; Andrea B Troxel; Emily F Conant; Andrew D A Maidment
Journal:  Acad Radiol       Date:  2009-03       Impact factor: 3.173

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  1 in total

Review 1.  Artificial Intelligence for Mammography and Digital Breast Tomosynthesis: Current Concepts and Future Perspectives.

Authors:  Krzysztof J Geras; Ritse M Mann; Linda Moy
Journal:  Radiology       Date:  2019-09-24       Impact factor: 11.105

  1 in total

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