Iron-specific Signal Separation from within Heavy Metal Stained Biological Samples Using X-Ray Microtomography with Polychromatic Source and Energy-Integrating Detectors.
Tsvi KatchalskiTom CaseKeun-Young KimRanjan RamachandraEric A BushongThomas J DeerinckMatthias Georg HaberlMason R MackeySteven PeltierGuillaume A CastillonNobuko FujikawaAlbert R LawrenceMark H EllismanPublished in: Scientific reports (2018)
Biological samples are frequently stained with heavy metals in preparation for examining the macro, micro and ultra-structure using X-ray microtomography and electron microscopy. A single X-ray microtomography scan reveals detailed 3D structure based on staining density, yet it lacks both material composition and functional information. Using a commercially available polychromatic X-ray source, energy integrating detectors and a two-scan configuration labelled by their energy- "High" and "Low", we demonstrate how a specific element, here shown with iron, can be detected from a mixture with other heavy metals. With proper selection of scan configuration, achieving strong overlap of source characteristic emission lines and iron K-edge absorption, iron absorption was enhanced enabling K-edge imaging. Specifically, iron images were obtained by scatter plot material analysis, after selecting specific regions within scatter plots generated from the "High" and "Low" scans. Using this method, we identified iron rich regions associated with an iron staining reaction that marks the nodes of Ranvier along nerve axons within mouse spinal roots, also stained with osmium metal commonly used for electron microscopy.
Keyphrases
- electron microscopy
- heavy metals
- high resolution
- dual energy
- iron deficiency
- computed tomography
- risk assessment
- health risk
- health risk assessment
- healthcare
- radiation therapy
- mass spectrometry
- spinal cord injury
- early stage
- spinal cord
- deep learning
- convolutional neural network
- lymph node
- magnetic resonance imaging
- sewage sludge
- magnetic resonance
- optical coherence tomography
- machine learning
- sentinel lymph node
- tandem mass spectrometry
- simultaneous determination
- peripheral nerve
- anaerobic digestion