MarrowQuant Across Aging and Aplasia: A Digital Pathology Workflow for Quantification of Bone Marrow Compartments in Histological Sections.
MarrowQuant Across Aging and Aplasia: A Digital Pathology Workflow for Quantification of Bone Marrow Compartments in Histological Sections.
复制标题
DOI：
10.3389/fendo.2020.00480
复制
发表时间：
2020
影响因子：
5.2
通讯作者：
Naveiras O
中科院分区：
文献类型：
--
作者：
Tratwal J;Bekri D;Boussema C;Sarkis R;Kunz N;Koliqi T;Rojas-Sutterlin S;Schyrr F;Tavakol DN;Campos V;Scheller EL;Sarro R;Bárcena C;Bisig B;Nardi V;de Leval L;Burri O;Naveiras O
根据骨骼位置、年龄和生理条件，骨髓（BM）以造血细胞/红骨髓或脂肪细胞/黄骨髓的形式异质存在。小鼠模型和接受放疗/化疗或患有急性骨髓衰竭的患者忍受骨髓微环境的快速脂肪细胞转化，即所谓的“红-黄”转变。在造血恢复后，例如在BM移植后，发生“黄-红”转变，并且恢复功能性造血。评估BM细胞组成的金标准是病理学家对苏木精和伊红（H&E）染色的组织切片中造血细胞构成的评估，以及在四氧化锇脂质染色后使用对比增强的微型计算机断层扫描（CE-μCT）对骨髓脂肪的体积测量。由于用户依赖性变量，在纵向研究的再现性是一个挑战，这两种方法。在这里，我们报告了一个半自动化的图像分析插件，MarrowQuant，它采用开源软件QuPath，系统地量化多个骨成分的H&E部分在一个公正的方式。MarrowQuant识别并量化骨、脂肪细胞血影、造血细胞和间质/微血管区室占据的区域。一个单独的功能，AdipoQuant，在髓外脂肪组织的H& E染色切片中将脂肪细胞影片段化，以呈现脂肪细胞面积和大小分布。使用MarrowQuant对BM造血细胞结构的量化在四位独立病理学家的评分范围内，而对全骨切片中总脂肪细胞面积的量化则与体积测量进行比较。使用我们的工具，我们能够在稳态条件下在小鼠C57 BL/6骨的中段中开发BM造血细胞结构和肥胖的标准化图谱，包括在尾侧尾的近端部分和胫骨近端至远端中高度可预测的红色至黄色转变的定量。此外，我们提出了一个比较骨骼地图诱导的致死性照射，纵向量化的“红到黄到红”的过渡超过2个月的C57 BL/6股骨和胫骨。我们发现，骨髓移植后，骨髓肥胖与造血恢复动力学呈负相关，近端到远端的梯度是保守的。通过磁共振成像（MRI）进行的体内恢复分析显示了相当的动力学。在人类环锯活检中，MarrowQuant成功识别了BM隔室，为其在需要标准化人类BM评价的实验或临床环境中的应用开辟了途径。
The bone marrow (BM) exists heterogeneously as hematopoietic/red or adipocytic/yellow marrow depending on skeletal location, age, and physiological condition. Mouse models and patients undergoing radio/chemotherapy or suffering acute BM failure endure rapid adipocytic conversion of the marrow microenvironment, the so-called “red-to-yellow” transition. Following hematopoietic recovery, such as upon BM transplantation, a “yellow-to-red” transition occurs and functional hematopoiesis is restored. Gold Standards to estimate BM cellular composition are pathologists' assessment of hematopoietic cellularity in hematoxylin and eosin (H&E) stained histological sections as well as volumetric measurements of marrow adiposity with contrast-enhanced micro-computerized tomography (CE-μCT) upon osmium-tetroxide lipid staining. Due to user-dependent variables, reproducibility in longitudinal studies is a challenge for both methods. Here we report the development of a semi-automated image analysis plug-in, MarrowQuant, which employs the open-source software QuPath, to systematically quantify multiple bone components in H&E sections in an unbiased manner. MarrowQuant discerns and quantifies the areas occupied by bone, adipocyte ghosts, hematopoietic cells, and the interstitial/microvascular compartment. A separate feature, AdipoQuant, fragments adipocyte ghosts in H&E-stained sections of extramedullary adipose tissue to render adipocyte area and size distribution. Quantification of BM hematopoietic cellularity with MarrowQuant lies within the range of scoring by four independent pathologists, while quantification of the total adipocyte area in whole bone sections compares with volumetric measurements. Employing our tool, we were able to develop a standardized map of BM hematopoietic cellularity and adiposity in mid-sections of murine C57BL/6 bones in homeostatic conditions, including quantification of the highly predictable red-to-yellow transitions in the proximal section of the caudal tail and in the proximal-to-distal tibia. Additionally, we present a comparative skeletal map induced by lethal irradiation, with longitudinal quantification of the “red-to-yellow-to-red” transition over 2 months in C57BL/6 femurs and tibiae. We find that, following BM transplantation, BM adiposity inversely correlates with kinetics of hematopoietic recovery and that a proximal to distal gradient is conserved. Analysis of in vivo recovery through magnetic resonance imaging (MRI) reveals comparable kinetics. On human trephine biopsies MarrowQuant successfully recognizes the BM compartments, opening avenues for its application in experimental, or clinical contexts that require standardized human BM evaluation.
登录
查看更多内容
影响因子：
4.6
作者：
Bankhead P;Loughrey MB;Fernández JA;Dombrowski Y;McArt DG;Dunne PD;McQuaid S;Gray RT;Murray LJ;Coleman HG;James JA;Salto-Tellez M;Hamilton PW
通讯作者：
Hamilton PW
影响因子：
20.3
作者：
Dominietto, A;Lamparelli, T;Bacigalupo, A
通讯作者：
Bacigalupo, A
影响因子：
29
作者：
Cawthorn WP;Scheller EL;Learman BS;Parlee SD;Simon BR;Mori H;Ning X;Bree AJ;Schell B;Broome DT;Soliman SS;DelProposto JL;Lumeng CN;Mitra A;Pandit SV;Gallagher KA;Miller JD;Krishnan V;Hui SK;Bredella MA;Fazeli PK;Klibanski A;Horowitz MC;Rosen CJ;MacDougald OA
通讯作者：
MacDougald OA
影响因子：
6.2
作者：
Devlin, Maureen J.;Cloutier, Alison M.;Thomas, Nishina A.;Panus, David A.;Lotinun, Sutada;Pinz, Ilka;Baron, Roland;Rosen, Clifford J.;Bouxsein, Mary L.
通讯作者：
Bouxsein, Mary L.
影响因子：
4.1
作者：
Le PT;Bishop KA;Maridas DE;Motyl KJ;Brooks DJ;Nagano K;Baron R;Bouxsein ML;Rosen CJ
通讯作者：
Rosen CJ