Literature DB >> 16177415

Thickness of molybdenum filter and squared contrast-to-noise ratio per dose for digital mammography.

Thomas K Nishino1, Xizeng Wu, Raleigh F Johnson.   

Abstract

OBJECTIVE: The objective of our study was to test whether the lesion-tissue contrast-to-noise ratio (CNR) at a given dose level can be improved by increasing the thickness of the molybdenum (Mo) filter currently used in digital mammography.
MATERIALS AND METHODS: We studied how the CNR between breast and a 5-mm simulated infiltrating ductal carcinoma (IDC) embedded in a 5-cm-thick breast changes with Mo filter thickness. We performed phantom imaging experiments by modifying the filter wheel of a Senographe 2000D unit with Mo filters that ranged from 15 to 90 microm in thickness. A 5-cm-thick 50% glandular-50% adipose breast phantom with a 5-mm insert simulating IDC was used as the phantom for all the cases. The CNRs between the breast phantom and the IDC insert were measured, and average glandular doses were calculated using a filtration-dependent X-ray spectra model and a breast dosimetry model based on a validated Monte Carlo simulation.
RESULTS: The lesion-tissue CNR at a given dose level increases with increasing Mo filter thickness from 15 to 90 microm. The measured squared CNR per dose increased by 8%, 14%, 17%, and 17% for 45-, 60-, 75-, and 90-microm Mo filters, respectively, compared with the standard 30-microm Mo filter. Meanwhile, the exposure times were increased by 35% (45 microm), 71% (60 microm), 177% (75 microm), and 229% (90 microm).
CONCLUSION: Increasing Mo filter thickness from 30 to 60 microm can increase lesion-tissue squared CNR per dose by 14% with a tolerable increase in the duration of exposure.

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Year:  2005        PMID: 16177415     DOI: 10.2214/AJR.04.1489

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  3 in total

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Authors:  Sang Min Lee; Whal Lee; Jin Wook Chung; Eun-Ah Park; Jae Hyung Park
Journal:  Int J Cardiovasc Imaging       Date:  2013-11-02       Impact factor: 2.357

2.  Optimization of Image Quality and Dose in Digital Mammography.

Authors:  Agnes M F Fausto; M C Lopes; M C de Sousa; Tânia A C Furquim; Anderson W Mol; Fermin G Velasco
Journal:  J Digit Imaging       Date:  2017-04       Impact factor: 4.056

3.  A novel method for contrast-to-noise ratio (CNR) evaluation of digital mammography detectors.

Authors:  P Baldelli; N Phelan; G Egan
Journal:  Eur Radiol       Date:  2009-05-08       Impact factor: 5.315

  3 in total

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