Literature DB >> 25007048

Digital breast tomosynthesis: observer performance of clustered microcalcification detection on breast phantom images acquired with an experimental system using variable scan angles, angular increments, and number of projection views.

Heang-Ping Chan1, Mitchell M Goodsitt, Mark A Helvie, Scott Zelakiewicz, Andrea Schmitz, Mitra Noroozian, Chintana Paramagul, Marilyn A Roubidoux, Alexis V Nees, Colleen H Neal, Paul Carson, Yao Lu, Lubomir Hadjiiski, Jun Wei.   

Abstract

PURPOSE: To investigate the dependence of microcalcification cluster detectability on tomographic scan angle, angular increment, and number of projection views acquired at digital breast tomosynthesis ( DBT digital breast tomosynthesis ).
MATERIALS AND METHODS: A prototype DBT digital breast tomosynthesis system operated in step-and-shoot mode was used to image breast phantoms. Four 5-cm-thick phantoms embedded with 81 simulated microcalcification clusters of three speck sizes (subtle, medium, and obvious) were imaged by using a rhodium target and rhodium filter with 29 kV, 50 mAs, and seven acquisition protocols. Fixed angular increments were used in four protocols (denoted as scan angle, angular increment, and number of projection views, respectively: 16°, 1°, and 17; 24°, 3°, and nine; 30°, 3°, and 11; and 60°, 3°, and 21), and variable increments were used in three (40°, variable, and 13; 40°, variable, and 15; and 60°, variable, and 21). The reconstructed DBT digital breast tomosynthesis images were interpreted by six radiologists who located the microcalcification clusters and rated their conspicuity.
RESULTS: The mean sensitivity for detection of subtle clusters ranged from 80% (22.5 of 28) to 96% (26.8 of 28) for the seven DBT digital breast tomosynthesis protocols; the highest sensitivity was achieved with the 16°, 1°, and 17 protocol (96%), but the difference was significant only for the 60°, 3°, and 21 protocol (80%, P < .002) and did not reach significance for the other five protocols (P = .01-.15). The mean sensitivity for detection of medium and obvious clusters ranged from 97% (28.2 of 29) to 100% (24 of 24), but the differences fell short of significance (P = .08 to >.99). The conspicuity of subtle and medium clusters with the 16°, 1°, and 17 protocol was rated higher than those with other protocols; the differences were significant for subtle clusters with the 24°, 3°, and nine protocol and for medium clusters with 24°, 3°, and nine; 30°, 3°, and 11; 60°, 3° and 21; and 60°, variable, and 21 protocols (P < .002).
CONCLUSION: With imaging that did not include x-ray source motion or patient motion during acquisition of the projection views, narrow-angle DBT digital breast tomosynthesis provided higher sensitivity and conspicuity than wide-angle DBT digital breast tomosynthesis for subtle microcalcification clusters. © RSNA, 2014.

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Year:  2014        PMID: 25007048      PMCID: PMC4314116          DOI: 10.1148/radiol.14132722

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  35 in total

1.  Resolution at oblique incidence angles of a flat panel imager for breast tomosynthesis.

Authors:  James G Mainprize; Aili K Bloomquist; Michael P Kempston; Martin J Yaffe
Journal:  Med Phys       Date:  2006-09       Impact factor: 4.071

2.  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

3.  Optimization of the acquisition geometry in digital tomosynthesis of the breast.

Authors:  Ioannis Sechopoulos; Caterina Ghetti
Journal:  Med Phys       Date:  2009-04       Impact factor: 4.071

4.  Image artifacts in digital breast tomosynthesis: investigation of the effects of system geometry and reconstruction parameters using a linear system approach.

Authors:  Yue-Houng Hu; Bo Zhao; Wei Zhao
Journal:  Med Phys       Date:  2008-12       Impact factor: 4.071

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.  Automated detection of microcalcification clusters for digital breast tomosynthesis using projection data only: a preliminary study.

Authors:  I Reiser; R M Nishikawa; A V Edwards; D B Kopans; R A Schmidt; J Papaioannou; R H Moore
Journal:  Med Phys       Date:  2008-04       Impact factor: 4.071

7.  Digital tomosynthesis in breast imaging.

Authors:  L T Niklason; B T Christian; L E Niklason; D B Kopans; D E Castleberry; B H Opsahl-Ong; C E Landberg; P J Slanetz; A A Giardino; R Moore; D Albagli; M C DeJule; P F Fitzgerald; D F Fobare; B W Giambattista; R F Kwasnick; J Liu; S J Lubowski; G E Possin; J F Richotte; C Y Wei; R F Wirth
Journal:  Radiology       Date:  1997-11       Impact factor: 11.105

8.  Combination of one-view digital breast tomosynthesis with one-view digital mammography versus standard two-view digital mammography: per lesion analysis.

Authors:  Gisella Gennaro; R Edward Hendrick; Alicia Toledano; Jean R Paquelet; Elisabetta Bezzon; Roberta Chersevani; Cosimo di Maggio; Manuela La Grassa; Luigi Pescarini; Ilaria Polico; Alessandro Proietti; Enrica Baldan; Fabio Pomerri; Pier Carlo Muzzio
Journal:  Eur Radiol       Date:  2013-04-26       Impact factor: 5.315

9.  Digital breast tomosynthesis: initial experience in 98 women with abnormal digital screening mammography.

Authors:  Steven P Poplack; Tor D Tosteson; Christine A Kogel; Helene M Nagy
Journal:  AJR Am J Roentgenol       Date:  2007-09       Impact factor: 3.959

10.  Breast tomosynthesis and digital mammography: a comparison of breast cancer visibility and BIRADS classification in a population of cancers with subtle mammographic findings.

Authors:  Ingvar Andersson; Debra M Ikeda; Sophia Zackrisson; Mark Ruschin; Tony Svahn; Pontus Timberg; Anders Tingberg
Journal:  Eur Radiol       Date:  2008-07-19       Impact factor: 5.315

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  10 in total

1.  Digital breast tomosynthesis: computer-aided detection of clustered microcalcifications on planar projection images.

Authors:  Ravi K Samala; Heang-Ping Chan; Yao Lu; Lubomir M Hadjiiski; Jun Wei; Mark A Helvie
Journal:  Phys Med Biol       Date:  2014-11-13       Impact factor: 3.609

2.  Synthesizing mammogram from digital breast tomosynthesis.

Authors:  Jun Wei; Heang-Ping Chan; Mark A Helvie; Marilyn A Roubidoux; Colleen H Neal; Yao Lu; Lubomir M Hadjiiski; Chuan Zhou
Journal:  Phys Med Biol       Date:  2019-02-11       Impact factor: 3.609

3.  Optimization of digital breast tomosynthesis (DBT) acquisition parameters for human observers: effect of reconstruction algorithms.

Authors:  Rongping Zeng; Aldo Badano; Kyle J Myers
Journal:  Phys Med Biol       Date:  2017-02-02       Impact factor: 3.609

4.  Multiscale bilateral filtering for improving image quality in digital breast tomosynthesis.

Authors:  Yao Lu; Heang-Ping Chan; Jun Wei; Lubomir M Hadjiiski; Ravi K Samala
Journal:  Med Phys       Date:  2015-01       Impact factor: 4.071

5.  Computer-aided detection system for clustered microcalcifications in digital breast tomosynthesis using joint information from volumetric and planar projection images.

Authors:  Ravi K Samala; Heang-Ping Chan; Yao Lu; Lubomir M Hadjiiski; Jun Wei; Mark A Helvie
Journal:  Phys Med Biol       Date:  2015-10-14       Impact factor: 3.609

6.  Computational reader design and statistical performance evaluation of an in-silico imaging clinical trial comparing digital breast tomosynthesis with full-field digital mammography.

Authors:  Rongping Zeng; Frank W Samuelson; Diksha Sharma; Andreu Badal; Graff G Christian; Stephen J Glick; Kyle J Myers; Aldo Badano
Journal:  J Med Imaging (Bellingham)       Date:  2020-02-26

7.  Improving image quality for digital breast tomosynthesis: an automated detection and diffusion-based method for metal artifact reduction.

Authors:  Yao Lu; Heang-Ping Chan; Jun Wei; Lubomir M Hadjiiski; Ravi K Samala
Journal:  Phys Med Biol       Date:  2017-09-15       Impact factor: 3.609

8.  Initial clinical evaluation of stationary digital chest tomosynthesis in adult patients with cystic fibrosis.

Authors:  Elias Taylor Gunnell; Dora K Franceschi; Christina R Inscoe; Allison Hartman; Jennifer L Goralski; Agathe Ceppe; Brian Handly; Cassandra Sams; Lynn Ansley Fordham; Jianping Lu; Otto Zhou; Yueh Z Lee
Journal:  Eur Radiol       Date:  2018-09-25       Impact factor: 5.315

9.  Detector Blur and Correlated Noise Modeling for Digital Breast Tomosynthesis Reconstruction.

Authors:  Jiabei Zheng; Jeffrey A Fessler; Heang-Ping Chan
Journal:  IEEE Trans Med Imaging       Date:  2017-07-27       Impact factor: 10.048

10.  Deep Convolutional Neural Network With Adversarial Training for Denoising Digital Breast Tomosynthesis Images.

Authors:  Mingjie Gao; Jeffrey A Fessler; Heang-Ping Chan
Journal:  IEEE Trans Med Imaging       Date:  2021-06-30       Impact factor: 11.037

  10 in total

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