Literature DB >> 26035107

Magnetic relaxometry as applied to sensitive cancer detection and localization.

Leyma P De Haro, Todor Karaulanov, Erika C Vreeland, Bill Anderson, Helen J Hathaway, Dale L Huber, Andrei N Matlashov, Christopher P Nettles, Andrew D Price, Todd C Monson, Edward R Flynn.   

Abstract

BACKGROUND: Here we describe superparamagnetic relaxometry (SPMR), a technology that utilizes highly sensitive magnetic sensors and superparamagnetic nanoparticles for cancer detection. Using SPMR, we sensitively and specifically detect nanoparticles conjugated to biomarkers for various types of cancer. SPMR offers high contrast in vivo, as there is no superparamagnetic background, and bones and tissue are transparent to the magnetic fields.
METHODS: In SPMR measurements, a brief magnetizing pulse is used to align superparamagnetic nanoparticles of a discrete size. Following the pulse, an array of superconducting quantum interference detectors (SQUID) sensors detect the decaying magnetization field. NP size is chosen so that, when bound, the induced field decays in seconds. They are functionalized with specific biomarkers and incubated with cancer cells in vitro to determine specificity and cell binding. For in vivo experiments, functionalized NPs are injected into mice with xenograft tumors, and field maps are generated to localize tumor sites.
RESULTS: Superparamagnetic NPs developed here have small size dispersion. Cell incubation studies measure specificity for different cell lines and antibodies with very high contrast. In vivo animal measurements verify SPMR localization of tumors. Our results indicate that SPMR possesses sensitivity more than 2 orders of magnitude better than previously reported.

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Year:  2015        PMID: 26035107     DOI: 10.1515/bmt-2015-0053

Source DB:  PubMed          Journal:  Biomed Tech (Berl)        ISSN: 0013-5585            Impact factor:   1.411


  8 in total

1.  Screening for ovarian cancer: imaging challenges and opportunities for improvement.

Authors:  K B Mathieu; D G Bedi; S L Thrower; A Qayyum; R C Bast
Journal:  Ultrasound Obstet Gynecol       Date:  2018-03       Impact factor: 7.299

2.  Development of advanced signal processing and source imaging methods for superparamagnetic relaxometry.

Authors:  Ming-Xiong Huang; Bill Anderson; Charles W Huang; Gerd J Kunde; Erika C Vreeland; Jeffrey W Huang; Andrei N Matlashov; Todor Karaulanov; Christopher P Nettles; Andrew Gomez; Kayla Minser; Caroline Weldon; Giulio Paciotti; Michael Harsh; Roland R Lee; Edward R Flynn
Journal:  Phys Med Biol       Date:  2017-01-10       Impact factor: 3.609

Review 3.  Current and Emerging Methods for Ovarian Cancer Screening and Diagnostics: A Comprehensive Review.

Authors:  Juliane M Liberto; Sheng-Yin Chen; Ie-Ming Shih; Tza-Huei Wang; Tian-Li Wang; Thomas R Pisanic
Journal:  Cancers (Basel)       Date:  2022-06-11       Impact factor: 6.575

Review 4.  Rapid MR relaxometry using deep learning: An overview of current techniques and emerging trends.

Authors:  Li Feng; Dan Ma; Fang Liu
Journal:  NMR Biomed       Date:  2020-10-15       Impact factor: 4.478

5.  Simultaneous Coercivity and Size Determination of Magnetic Nanoparticles.

Authors:  Annelies Coene; Jonathan Leliaert
Journal:  Sensors (Basel)       Date:  2020-07-12       Impact factor: 3.576

Review 6.  Self-Assembly of Magnetic Nanoparticles in Ferrofluids on Different Templates Investigated by Neutron Reflectometry.

Authors:  Katharina Theis-Bröhl; Apurve Saini; Max Wolff; Joseph A Dura; Brian B Maranville; Julie A Borchers
Journal:  Nanomaterials (Basel)       Date:  2020-06-24       Impact factor: 5.076

7.  Biomarkers and Strategies for Early Detection of Ovarian Cancer.

Authors:  Robert C Bast; Zhen Lu; Chae Young Han; Karen H Lu; Karen S Anderson; Charles W Drescher; Steven J Skates
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2020-10-13       Impact factor: 4.254

8.  High-sensitivity in vivo contrast for ultra-low field magnetic resonance imaging using superparamagnetic iron oxide nanoparticles.

Authors:  David E J Waddington; Thomas Boele; Richard Maschmeyer; Zdenka Kuncic; Matthew S Rosen
Journal:  Sci Adv       Date:  2020-07-17       Impact factor: 14.136

  8 in total

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