Literature DB >> 31870897

Fluorescence spectral detection of acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML): A novel photodiagnosis strategy.

Vadivel Masilamani1, Sandhanasamy Devanesan2, Mohamad S AlSalhi3, Fatmah S AlQahtany4, Karim H Farhat5.   

Abstract

Acute lymphoblastic leukemia (ALL) is a cancer of the lymphoid line of blood cell, showing a rapid growth of lymphoblastic immature cells. Acute myeloid leukemia (AML) is a cancer of the myeloid line of blood cells. Early diagnosis is crucial for the effective treatment of these patients. The current standard procedure of diagnosis is extensive blood count analysis, microscopic morphological investigations, bone marrow biopsy and flow-cytometer which are all time- consuming and expensive. Here we demonstrate the advantage a new technique for the diagnosis of ALL and AML based on the fluorescence spectra of blood plasma and RBCs samples from the above patients. Based on the 85 patients analyzed the results reveal that our approach could discriminate the two malignancies unambiguously from the normal with 88 % sensitivity and 80 % specificity. The abnormal decrease in the level of amino acid, tryptophan and coenzyme NADH and abnormal increase in the other amino acid, tyrosine and another coenzyme FAD, (both in comparison to the normal control) act as malignancy indicative biomarkers. Since the contrast parameter between the normal and malignant samples is four- fold, the potential for early detection of leukemia is high. The instrumentation and technique are new and simple; hence may have significant supplementary or complementary value with the existing diagnostic methods.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Acute leukemia; Blood plasma; Cancer diagnosis; Fluorescence emission spectra; RBC

Year:  2019        PMID: 31870897     DOI: 10.1016/j.pdpdt.2019.101634

Source DB:  PubMed          Journal:  Photodiagnosis Photodyn Ther        ISSN: 1572-1000            Impact factor:   3.631


  1 in total

1.  A deep learning method and device for bone marrow imaging cell detection.

Authors:  Jie Liu; Ruize Yuan; Yinhao Li; Lin Zhou; Zhiqiang Zhang; Jidong Yang; Li Xiao
Journal:  Ann Transl Med       Date:  2022-02
  1 in total

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