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Rapid intraoperative histology of unprocessed surgical specimens via fibre-laser-based stimulated Raman scattering microscopy.
Orringer, Daniel A; Pandian, Balaji; Niknafs, Yashar S; Hollon, Todd C; Boyle, Julianne; Lewis, Spencer; Garrard, Mia; Hervey-Jumper, Shawn L; Garton, Hugh J L; Maher, Cormac O; Heth, Jason A; Sagher, Oren; Wilkinson, D Andrew; Snuderl, Matija; Venneti, Sriram; Ramkissoon, Shakti H; McFadden, Kathryn A; Fisher-Hubbard, Amanda; Lieberman, Andrew P; Johnson, Timothy D; Xie, X Sunney; Trautman, Jay K; Freudiger, Christian W; Camelo-Piragua, Sandra.
Afiliación
  • Orringer DA; Department of Neurosurgery, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
  • Pandian B; Department of Neurosurgery, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
  • Niknafs YS; Department of Neurosurgery, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
  • Hollon TC; Department of Neurosurgery, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
  • Boyle J; Department of Neurosurgery, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
  • Lewis S; Department of Neurosurgery, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
  • Garrard M; Department of Neurosurgery, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
  • Hervey-Jumper SL; Department of Neurosurgery, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
  • Garton HJL; Department of Neurosurgery, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
  • Maher CO; Department of Neurosurgery, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
  • Heth JA; Department of Neurosurgery, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
  • Sagher O; Department of Neurosurgery, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
  • Wilkinson DA; Department of Neurosurgery, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
  • Snuderl M; Department of Pathology, New York University, New York, NY 10016, USA.
  • Venneti S; Department of Neurology, New York University, New York, NY 10016, USA.
  • Ramkissoon SH; Section of Neuropathology, Department of Pathology, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
  • McFadden KA; Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
  • Fisher-Hubbard A; Department of Medical Oncology, Center for Molecular Oncologic Pathology, Dana Farber Cancer Institute, Boston, MA 02115, USA.
  • Lieberman AP; Section of Neuropathology, Department of Pathology, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
  • Johnson TD; Section of Neuropathology, Department of Pathology, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
  • Xie XS; Section of Neuropathology, Department of Pathology, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
  • Trautman JK; Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA.
  • Freudiger CW; Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA.
  • Camelo-Piragua S; Invenio Imaging Inc, Santa Clara, CA 95051, USA.
Nat Biomed Eng ; 12017.
Article en En | MEDLINE | ID: mdl-28955599
ABSTRACT
Conventional methods for intraoperative histopathologic diagnosis are labour- and time-intensive, and may delay decision-making during brain-tumour surgery. Stimulated Raman scattering (SRS) microscopy, a label-free optical process, has been shown to rapidly detect brain-tumour infiltration in fresh, unprocessed human tissues. Here, we demonstrate the first application of SRS microscopy in the operating room by using a portable fibre-laser-based microscope and unprocessed specimens from 101 neurosurgical patients. We also introduce an image-processing method - stimulated Raman histology (SRH) - which leverages SRS images to create virtual haematoxylin-and-eosin-stained slides, revealing essential diagnostic features. In a simulation of intraoperative pathologic consultation in 30 patients, we found a remarkable concordance of SRH and conventional histology for predicting diagnosis (Cohen's kappa, κ > 0.89), with accuracy exceeding 92%. We also built and validated a multilayer perceptron based on quantified SRH image attributes that predicts brain-tumour subtype with 90% accuracy. Our findings provide insight into how SRH can now be used to improve the surgical care of brain tumour patients.
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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Año: 2017 Tipo del documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Año: 2017 Tipo del documento: Article