MarrowQuant 2.0: A Digital Pathology Workflow Assisting Bone Marrow Evaluation in Experimental and Clinical Hematology

被引:6
作者
Sarkis, Rita [1 ,2 ,3 ,4 ]
Burri, Olivier [5 ]
Royer-Chardon, Claire [6 ,7 ]
Schyrr, Frederica [1 ,2 ]
Blum, Sophie [1 ,2 ]
Costanza, Mariangela [8 ,9 ,10 ]
Cherix, Stephane [11 ,12 ]
Piazzon, Nathalie [6 ,7 ]
Barcena, Carmen [6 ,7 ,13 ]
Bisig, Bettina [6 ,7 ]
Nardi, Valentina [14 ]
Sarro, Rossella [6 ,7 ,15 ]
Ambrosini, Giovanna [16 ]
Weigert, Martin [17 ]
Spertini, Olivier [8 ,9 ,10 ]
Blum, Sabine [8 ,9 ,10 ]
Deplancke, Bart [4 ,18 ]
Seitz, Arne [5 ]
de Leval, Laurence [6 ,7 ]
Naveiras, Olaia [1 ,2 ,8 ,9 ,10 ]
机构
[1] Ecole Polytech Fed Lausanne EPFL, Inst Bioengn, Lab Regenerat Hematopoiesis, Lausanne, Switzerland
[2] Ecole Polytech Fed Lausanne EPFL, ISREC, Lausanne, Switzerland
[3] Univ Lausanne UNIL, Dept Biomed Sci, Lausanne, Switzerland
[4] Ecole Polytech Fed Lausanne EPFL, Sch Life Sci, Inst Bioengn, Lab Syst Biol & Genet, Lausanne, Switzerland
[5] Ecole Polytech Fed Lausanne, Sch Life Sci, BioImaging & Opt Core Facil, Lausanne, Switzerland
[6] Lausanne Univ Hosp, Inst Pathol, Dept Lab Med & Pathol, Lausanne, Switzerland
[7] Lausanne Univ, Lausanne, Switzerland
[8] Lausanne Univ Hosp CHUV, Dept Oncol, Hematol Serv, Lausanne, Switzerland
[9] Lausanne Univ Hosp CHUV, Dept Lab Med, Hematol Serv, Lausanne, Switzerland
[10] Univ Lausanne UNIL, Lausanne, Switzerland
[11] Lausanne Univ Hosp, Dept Orthopaed & Traumatol, Lausanne, Switzerland
[12] Univ Lausanne, Lausanne, Switzerland
[13] Hosp 12 Octubre, Dept Pathol, Madrid, Spain
[14] Massachusetts Gen Hosp, Dept Pathol, Boston, MA USA
[15] Ente Osped Cantonale EOC, Inst Pathol, Locarno, Switzerland
[16] UNIL EPFL Lausanne, Bioinformat Competence Ctr BICC, Lausanne, Switzerland
[17] Ecole Polytech Fed Lausanne EPFL, Sch Life Sci, Inst Bioengn, Lausanne, Switzerland
[18] Swiss Inst Bioinformat, Lausanne, Switzerland
基金
瑞士国家科学基金会;
关键词
adiposity; bone marrow; cellularity; digital pathology; hematopathology; open-source; stroma; ACUTE MYELOID-LEUKEMIA; APLASTIC-ANEMIA; CELLULARITY; BIOPSY; IMAGE; DIAGNOSIS; ASPIRATE; AGE; HISTOPATHOLOGY; CLASSIFICATION;
D O I
10.1016/j.modpat.2022.100088
中图分类号
R36 [病理学];
学科分类号
100104 ;
摘要
Bone marrow (BM) cellularity assessment is a crucial step in the evaluation of BM trephine biopsies for hematologic and nonhematologic disorders. Clinical assessment is based on a semiquantitative visual estimation of the hematopoietic and adipocytic components by hematopathologists, which does not provide quantitative information on other stromal compartments. In this study, we developed and validated MarrowQuant 2.0, an efficient, user-friendly digital hematopathology workflow integrated within QuPath software, which serves as BM quantifier for 5 mutually exclusive compartments (bone, hematopoietic, adipocytic, and interstitial/microvasculature areas and other) and derives the cellularity of human BM trephine biopsies. Instance segmentation of individual adipocytes is realized through the adaptation of the machine-learning-based algorithm StarDist. We calculated BM compartments and adipocyte size distributions of hematoxylin and eosin images obtained from 250 bone specimens, from control subjects and patients with acute myeloid leukemia or myelodysplastic syndrome, at diagnosis and follow-up, and measured the agreement of cellularity estimates by MarrowQuant 2.0 against visual scores from 4 hematopathologists. The algorithm was capable of robust BM compartment segmentation with an average mask accuracy of 86%, maximal for bone (99%), hematopoietic (92%), and adipocyte (98%) areas. MarrowQuant 2.0 cellularity score and hematopathologist estimations were highly correlated (R2 = 0.92-0.98, intraclass correlation coefficient [ICC] = 0.98; interobserver ICC = 0.96). BM compartment segmentation quantitatively confirmed the reciprocity of the hematopoietic and adipocytic compartments. MarrowQuant 2.0 performance was additionally tested for cellularity assessment of specimens prospectively collected from clinical routine diagnosis. After special consideration for the choice of the cellularity equation in specimens with expanded stroma, performance was similar in this setting (R2 = 0.86, n = 42). Thus, we conclude that these validation experiments establish MarrowQuant 2.0 as a reliable tool for BM cellularity assessment. We expect this workflow will serve as a clinical research tool to explore novel biomarkers related to BM stromal components and may contribute to further validation of future digitalized diagnostic hematopathology workstreams.(c) 2022 THE AUTHORS. Published by Elsevier Inc. on behalf of the United States & Canadian Academy of Pathology. This is an open access article under the CC BY license (http://creativecommons.org/ licenses/by/4.0/).
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页数:17
相关论文
共 67 条
  • [31] Open-Source Clinical Machine Learning Models: Critical Appraisal of Feasibility, Advantages, and Challenges
    Harish, Keerthi B.
    Price, W. Nicholson
    Aphinyanaphongs, Yindalon
    [J]. JMIR FORMATIVE RESEARCH, 2022, 6 (04)
  • [32] HARTSOCK RJ, 1965, AM J CLIN PATHOL, V43, P326
  • [33] BONE-MARROW CELLULARITY ASSESSED BY POINT-COUNTING
    HOYEN, DO
    SLIDDERS, W
    [J]. JOURNAL OF CLINICAL PATHOLOGY, 1978, 31 (08) : 753 - 756
  • [34] JAMSHIDI K, 1971, SCAND J HAEMATOL, V8, P69
  • [35] Towards a national strategy for digital pathology in Switzerland
    Janowczyk, Andrew
    Baumhoer, Daniel
    Dirnhofer, Stefan
    Grobholz, Rainer
    Kipar, Anja
    de Leval, Laurence
    Merkler, Doron
    Michielin, Olivier
    Moch, Holger
    Perren, Aurel
    Rottenberg, Sven
    Rubbia-Brandt, Laura
    Rubin, Mark A.
    Sempoux, Christine
    Tolnay, Markus
    Zlobec, Inti
    Koelzer, Viktor Hendrik
    [J]. VIRCHOWS ARCHIV, 2022, 481 (04) : 647 - 652
  • [36] KERNDRUP G, 1980, SCAND J HAEMATOL, V24, P110
  • [37] Kidd PG, 1997, MED PEDIATR ONCOL, V29, P541, DOI 10.1002/(SICI)1096-911X(199712)29:6<541::AID-MPO4>3.0.CO
  • [38] 2-K
  • [39] Estimation of bone marrow cellularity using digital image nucleated cell counts in patients receiving chemotherapy
    Kim, Y.
    Kim, M.
    Kim, Y.
    Han, J. H.
    Han, K.
    [J]. INTERNATIONAL JOURNAL OF LABORATORY HEMATOLOGY, 2014, 36 (05) : 548 - 554
  • [40] A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research
    Koo, Terry K.
    Li, Mae Y.
    [J]. JOURNAL OF CHIROPRACTIC MEDICINE, 2016, 15 (02) : 155 - 163