Automated osteosclerosis grading of clinical biopsies using infrared spectroscopic imaging

Rupali Mankar, Carlos E. Bueso-Ramos, C. Cameron Yin, Juliana Elisa Hidalgo-Lopez, Sebastian Berisha, Mustafa Kansiz, David Mayerich

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Osteosclerosis and myefibrosis are complications of myeloproliferative neoplasms. These disorders result in excess growth of trabecular bone and collagen fibers that replace hematopoietic cells, resulting in abnormal bone marrow function. Treatments using imatinib and JAK2 pathway inhibitors can be effective on osteosclerosis and fibrosis; therefore, accurate grading is critical for tracking treatment effectiveness. Current grading standards use a four-class system based on analysis of biopsies stained with three histological stains: hematoxylin and eosin (H&E), Masson's trichrome, and reticulin. However, conventional grading can be subjective and imprecise, impacting the effectiveness of treatment. In this Article, we demonstrate that mid-infrared spectroscopic imaging may serve as a quantitative diagnostic tool for quantitatively tracking disease progression and response to treatment. The proposed approach is label-free and provides automated quantitative analysis of osteosclerosis and collagen fibrosis.

Original languageEnglish (US)
Pages (from-to)749-757
Number of pages9
JournalAnalytical Chemistry
Volume92
Issue number1
DOIs
StatePublished - Jan 7 2020

ASJC Scopus subject areas

  • Analytical Chemistry

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