Evidence map›Paper›PMID 32333575›Full record

ArticleJournal of X-ray science and technology2020

Dedicated cone-beam breast CT using laterally-shifted detector geometry: Quantitative analysis of feasibility for clinical translation.

Srinivasan Vedantham, Hsin-Wu Tseng, Souleymane Konate, Linxi Shi, Andrew Karellas

Abstract read
In one paragraph

Article in Journal of X-ray science and technology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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0cells of the map it votes in
6citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Srinivasan VedanthamDepartment of Medical Imaging, University of Arizona, Tucson, AZ, USA.
Hsin-Wu TsengDepartment of Medical Imaging, University of Arizona, Tucson, AZ, USA.
Souleymane KonateHarvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA.
Linxi ShiDepartment of Radiology, Stanford University, Stanford, CA, USA.
Andrew KarellasDepartment of Medical Imaging, University of Arizona, Tucson, AZ, USA.

Funding

Towards screening with high-resolution, low-dose, dedicated breast CTR01CA199044 · NCI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI SRINIVASAN VEDANTHAM · 2016 to 2026
$6.1M
Role of 3D Tomography in Breast CancerR21CA134128 · NCI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI GLICK, STEPHEN J, KARELLAS, ANDREW · 2009 to 2010
$723k
NCI NIH HHS R01 CA199044NCI NIH HHS R21 CA134128
6 · The paper itself

Abstract

backgroundHigh-resolution, low-noise detectors with minimal dead-space at chest-wall could improve posterior coverage and microcalcification visibility in the dedicated cone-beam breast CT (CBBCT). However, the smaller field-of-view necessitates laterally-shifted detector geometry to enable optimizing the air-gap for x-ray scatter rejection.

objectiveTo evaluate laterally-shifted detector geometry for CBBCT with clinical projection datasets that provide for anatomical structures and lesions.

methodsCBBCT projection datasets (n = 17 breasts) acquired with a 40×30 cm detector (1024×768-pixels, 0.388-mm pixels) were truncated along the fan-angle to emulate 20.3×30 cm, 22.2×30 cm and 24.1×30 cm detector formats and correspond to 20, 120, 220 pixels overlap in conjugate views, respectively. Feldkamp-Davis-Kress (FDK) algorithm with 3 different weighting schemes were used for reconstruction. Visual analysis for artifacts and quantitative analysis of root-mean-squared-error (RMSE), absolute difference between truncated and 40×30 cm reconstructions (Diff), and its power spectrum (PSDiff) were performed.

resultsArtifacts were observed for 20.3×30 cm, but not for other formats. The 24.1×30 cm provided the best quantitative results with RMSE and Diff (both in units of μ, cm-1) of 4.39×10-3±1.98×10-3 and 4.95×10-4±1.34×10-4, respectively. The PSDiff (>0.3 cycles/mm) was in the order of 10-14μ2mm3 and was spatial-frequency independent.

conclusionsLaterally-shifted detector CBBCT with at least 220 pixels overlap in conjugate views (24.1×30 cm detector format) provides quantitatively accurate and artifact-free image reconstruction.

Indexed as

AlgorithmsBreastBreast NeoplasmsCone-Beam Computed TomographyFeasibility StudiesFemaleHumansImage Interpretation, Computer-AssistedMammographyRetrospective StudiesBreastbreast CTcone-beam CTmammographyX-Ray computed tomography (CT)

Identifiers

PMID32333575
PMCPMC7347391

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.