Literature DB >> 26206823

Quantitative Ultrasound Comparison of MAT and 4T1 Mammary Tumors in Mice and Rats Across Multiple Imaging Systems.

Lauren A Wirtzfeld1, Goutam Ghoshal1, Ivan M Rosado-Mendez1, Kibo Nam1, Yeonjoo Park1, Alexander D Pawlicki1, Rita J Miller1, Douglas G Simpson1, James A Zagzebski1, Michael L Oelze1, Timothy J Hall1, William D O'Brien2.   

Abstract

OBJECTIVES: Quantitative ultrasound estimates such as the frequency-dependent backscatter coefficient (BSC) have the potential to enhance noninvasive tissue characterization and to identify tumors better than traditional B-mode imaging. Thus, investigating system independence of BSC estimates from multiple imaging platforms is important for assessing their capabilities to detect tissue differences.
METHODS: Mouse and rat mammary tumor models, 4T1 and MAT, respectively, were used in a comparative experiment using 3 imaging systems (Siemens, Ultrasonix, and VisualSonics) with 5 different transducers covering a range of ultrasonic frequencies.
RESULTS: Functional analysis of variance of the MAT and 4T1 BSC-versus-frequency curves revealed statistically significant differences between the two tumor types. Variations also were found among results from different transducers, attributable to frequency range effects. At 3 to 8 MHz, tumor BSC functions using different systems showed no differences between tumor type, but at 10 to 20 MHz, there were differences between 4T1 and MAT tumors. Fitting an average spline model to the combined BSC estimates (3-22 MHz) demonstrated that the BSC differences between tumors increased with increasing frequency, with the greatest separation above 15 MHz. Confining the analysis to larger tumors resulted in better discrimination over a wider bandwidth.
CONCLUSIONS: Confining the comparison to higher ultrasonic frequencies or larger tumor sizes allowed for separation of BSC-versus-frequency curves from 4T1 and MAT tumors. These constraints ensure that a greater fraction of the backscattered signals originated from within the tumor, thus demonstrating that statistically significant tumor differences were detected.
© 2015 by the American Institute of Ultrasound in Medicine.

Entities:  

Keywords:  backscatter coefficient; mammary tumor models; quantitative ultrasound

Mesh:

Year:  2015        PMID: 26206823      PMCID: PMC4527166          DOI: 10.7863/ultra.34.8.1373

Source DB:  PubMed          Journal:  J Ultrasound Med        ISSN: 0278-4297            Impact factor:   2.153


  21 in total

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Authors:  M C Kolios; G J Czarnota; M Lee; J W Hunt; M D Sherar
Journal:  Ultrasound Med Biol       Date:  2002-05       Impact factor: 2.998

2.  Role of advanced 2 and 3-dimensional ultrasound for detecting prostate cancer.

Authors:  K C Balaji; William R Fair; Ernst J Feleppa; Christopher R Porter; Harold Tsai; Tian Liu; Andrew Kalisz; Stella Urban; John Gillespie
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3.  Relationship of ultrasonic spectral parameters to features of tissue microstructure.

Authors:  F L Lizzi; M Ostromogilsky; E J Feleppa; M C Rorke; M M Yaremko
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  1987       Impact factor: 2.725

4.  Renal ultrasound using parametric imaging techniques to detect changes in microstructure and function.

Authors:  M F Insana; T J Hall; J G Wood; Z Y Yan
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5.  Interlaboratory comparison of backscatter coefficient estimates for tissue-mimicking phantoms.

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6.  Three-dimensional high-frequency characterization of cancerous lymph nodes.

Authors:  Jonathan Mamou; Alain Coron; Masaki Hata; Junji Machi; Eugene Yanagihara; Pascal Laugier; Ernest J Feleppa
Journal:  Ultrasound Med Biol       Date:  2010-02-04       Impact factor: 2.998

7.  Quantitative ultrasonic detection of parenchymal structural change in diffuse renal disease.

Authors:  B S Garra; M F Insana; I A Sesterhenn; T J Hall; R F Wagner; C Rotellar; J Winchester; R K Zeman
Journal:  Invest Radiol       Date:  1994-02       Impact factor: 6.016

8.  Techniques and evaluation from a cross-platform imaging comparison of quantitative ultrasound parameters in an in vivo rodent fibroadenoma model.

Authors:  Lauren A Wirtzfeld; Kibo Nam; Yassin Labyed; Goutam Ghoshal; Alexander Haak; Ellora Sen-Gupta; Zhi He; Nathaniel R Hirtz; Rita J Miller; Sandhya Sarwate; Douglas G Simpson; James A Zagzebski; Timothy A Bigelow; Michael Oelze; Timothy J Hall; William D O'Brien
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2013-07       Impact factor: 2.725

9.  Assessment of high-intensity focused ultrasound treatment of rodent mammary tumors using ultrasound backscatter coefficients.

Authors:  Jeremy P Kemmerer; Goutam Ghoshal; Chandra Karunakaran; Michael L Oelze
Journal:  J Acoust Soc Am       Date:  2013-08       Impact factor: 1.840

10.  Identifying acoustic scattering sources in normal renal parenchyma in vivo by varying arterial and ureteral pressures.

Authors:  M F Insana; J G Wood; T J Hall
Journal:  Ultrasound Med Biol       Date:  1992       Impact factor: 2.998

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Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2018-06       Impact factor: 2.725

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3.  MRI reveals increased tumorigenesis following high fat feeding in a mouse model of triple-negative breast cancer.

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4.  Robust probabilistic classification applicable to irregularly sampled functional data.

Authors:  Yeonjoo Park; Douglas G Simpson
Journal:  Comput Stat Data Anal       Date:  2018-08-11       Impact factor: 1.681

5.  Streamlined variational inference for higher level group-specific curve models.

Authors:  M Menictas; T H Nolan; D G Simpson; M P Wand
Journal:  Stat Modelling       Date:  2020-08-21       Impact factor: 2.039

6.  Structure Function Estimated From Histological Tissue Sections.

Authors:  Aiguo Han; William D O'Brien
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2016-03-25       Impact factor: 2.725

  6 in total

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