Quantifying multiple stain distributions in bioimaging by hyperspectral X-ray tomography

被引:4
|
作者
Warr, Ryan [1 ]
Handschuh, Stephan [2 ]
Gloesmann, Martin [2 ]
Cernik, Robert J. [1 ]
Withers, Philip J. [1 ]
机构
[1] Univ Manchester, Dept Mat, Henry Royce Inst, Manchester M13 9PL, Lancs, England
[2] Univ Vet Med Vienna, VetCore Facil Res, Vienna, Austria
来源
SCIENTIFIC REPORTS | 2022年 / 12卷 / 01期
基金
英国工程与自然科学研究理事会; 欧洲研究理事会;
关键词
COMPUTED-TOMOGRAPHY; CONTRAST AGENTS; HIGH-RESOLUTION; TOOL; RECOMMENDATIONS; FLUORESCENCE; REMOVAL; MICROCT; IODINE;
D O I
10.1038/s41598-022-23592-0
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Chemical staining of biological specimens is commonly utilised to boost contrast in soft tissue structures, but unambiguous identification of staining location and distribution is difficult without confirmation of the elemental signature, especially for chemicals of similar density contrast. Hyperspectral X-ray computed tomography (XCT) enables the non-destructive identification, segmentation and mapping of elemental composition within a sample. With the availability of hundreds of narrow, high resolution (similar to 1 keV) energy channels, the technique allows the simultaneous detection of multiple contrast agents across different tissue structures. Here we describe a hyperspectral imaging routine for distinguishing multiple chemical agents, regardless of contrast similarity. Using a set of elemental calibration phantoms, we perform a first instance of direct stain concentration measurement using spectral absorption edge markers. Applied to a set of double- and triple-stained biological specimens, the study analyses the extent of stain overlap and uptake regions for commonly used contrast markers. An improved understanding of stain concentration as a function of position, and the interaction between multiple stains, would help inform future studies on multi-staining procedures, as well as enable future exploration of heavy metal uptake across medical, agricultural and ecological fields.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] Quantifying multiple stain distributions in bioimaging by hyperspectral X-ray tomography
    Ryan Warr
    Stephan Handschuh
    Martin Glösmann
    Robert J. Cernik
    Philip J. Withers
    Scientific Reports, 12 (1)
  • [2] Hyperspectral image reconstruction for x-ray fluorescence tomography
    Guersoy, Doga
    Bicer, Tekin
    Lanzirotti, Antonio
    Newville, Matthew G.
    De Carlo, Francesco
    OPTICS EXPRESS, 2015, 23 (07): : 9014 - 9023
  • [3] Quantifying mineral grain size distributions for process modelling using X-ray micro-tomography
    Evans, C. L.
    Wightman, E. M.
    Yuan, X.
    MINERALS ENGINEERING, 2015, 82 : 78 - 83
  • [4] Quantifying neutron scintillator screens with X-ray computed tomography
    Chuirazzi, William
    Cool, Steven
    Craft, Aaron
    NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT, 2024, 1063
  • [5] Quantifying neutron scintillator screens with X-ray computed tomography
    Chuirazzi, William
    Cool, Steven
    Craft, Aaron
    Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2024, 1063
  • [6] Dynamic X-ray tomography with multiple sources
    Niemi, Esa
    Lassas, Matti
    Siltanen, Samuli
    2013 8TH INTERNATIONAL SYMPOSIUM ON IMAGE AND SIGNAL PROCESSING AND ANALYSIS (ISPA), 2013, : 618 - 621
  • [7] A Library of Potential Nanoparticle Contrast Agents for X-Ray Fluorescence Tomography Bioimaging
    Li, Yuyang
    Shaker, Kian
    Larsson, Jakob C.
    Vogt, Carmen
    Hertz, Hans M.
    Toprak, Muhammet S.
    CONTRAST MEDIA & MOLECULAR IMAGING, 2018,
  • [8] X-ray Stain Localization with Near-Field Ptychographic Computed Tomography
    Taphorn, Kirsten
    Busse, Madleen
    Brantl, Johannes
    Guenther, Benedikt
    Diaz, Ana
    Holler, Mirko
    Dierolf, Martin
    Mayr, Doris
    Pfeiffer, Franz
    Herzen, Julia
    ADVANCED SCIENCE, 2022, 9 (24)
  • [9] A hyperspectral X-ray computed tomography system for enhanced material identification
    Wu, Xiaomei
    Wang, Qian
    Ma, Jinlei
    Zhang, Wei
    Li, Po
    Fang, Zheng
    REVIEW OF SCIENTIFIC INSTRUMENTS, 2017, 88 (08):
  • [10] Visualizing and quantifying cell phenotype using soft X-ray tomography
    McDermott, Gerry
    Fox, Douglas M.
    Epperly, Lindsay
    Wetzler, Modi
    Barron, Annelise E.
    Le Gros, Mark A.
    Larabell, Carolyn A.
    BIOESSAYS, 2012, 34 (04) : 320 - 327