Literature DB >> 3884539

A model for acoustic characterization of intraocular tumors.

D J Coleman, F L Lizzi, R H Silverman, L Helson, J H Torpey, M J Rondeau.   

Abstract

Human intraocular tumors and tumors derived from human tumor cell lines grown subcutaneously in the athymic nude mouse were scanned by diagnostic ultrasound. Radiofrequency scan data were converted to digital form and analyzed in the frequency domain. Characteristics of normalized power spectra were found to be significantly different among human spindle cell malignant melanomas, mixed/epithelioid malignant melanomas, metastatic carcinomas, and hemangiomas. Significant differences, as well, were found between implanted primary skin malignant melanomas and adenocarcinomas of the lung, colon, and stomach. Comparison of spectral properties of human intraocular and implanted tumors revealed that human spindle cell malignant melanomas and implanted melanomas exhibit similar characteristics. Human intraocular metastatic tumors from the lung were found to exhibit characteristics similar to those of implanted lung tumors. These results indicate that the implantation of human tumor cell lines in the nude mouse may provide a very useful model for application of diagnostic and therapeutic ultrasound modalities to human intraocular tumors.

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Mesh:

Year:  1985        PMID: 3884539

Source DB:  PubMed          Journal:  Invest Ophthalmol Vis Sci        ISSN: 0146-0404            Impact factor:   4.799


  5 in total

1.  Algorithms and results of eye tissues differentiation based on RF ultrasound.

Authors:  R Jurkonis; A Janušauskas; V Marozas; D Jegelevičius; S Daukantas; M Patašius; A Paunksnis; A Lukoševičius
Journal:  ScientificWorldJournal       Date:  2012-05-02

2.  Noninvasive characterization of locally advanced breast cancer using textural analysis of quantitative ultrasound parametric images.

Authors:  Hadi Tadayyon; Ali Sadeghi-Naini; Gregory J Czarnota
Journal:  Transl Oncol       Date:  2014-12       Impact factor: 4.243

3.  A priori Prediction of Neoadjuvant Chemotherapy Response and Survival in Breast Cancer Patients using Quantitative Ultrasound.

Authors:  Hadi Tadayyon; Lakshmanan Sannachi; Mehrdad J Gangeh; Christina Kim; Sonal Ghandi; Maureen Trudeau; Kathleen Pritchard; William T Tran; Elzbieta Slodkowska; Ali Sadeghi-Naini; Gregory J Czarnota
Journal:  Sci Rep       Date:  2017-04-12       Impact factor: 4.379

4.  Deep learning of quantitative ultrasound multi-parametric images at pre-treatment to predict breast cancer response to chemotherapy.

Authors:  Hamidreza Taleghamar; Seyed Ali Jalalifar; Gregory J Czarnota; Ali Sadeghi-Naini
Journal:  Sci Rep       Date:  2022-02-10       Impact factor: 4.379

5.  Characterizing intra-tumor regions on quantitative ultrasound parametric images to predict breast cancer response to chemotherapy at pre-treatment.

Authors:  Hamidreza Taleghamar; Hadi Moghadas-Dastjerdi; Gregory J Czarnota; Ali Sadeghi-Naini
Journal:  Sci Rep       Date:  2021-07-21       Impact factor: 4.379

  5 in total

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