The Application of Morphogo in the Detection of Megakaryocytes from Bone Marrow Digital Images with Convolutional Neural Networks
The evaluation of megakaryocytes is an important part of the work up on bone marrow smear examination. It has significance in the differential diagnosis, therapeutic efficacy assessment, and predication of prognosis of many hematologic diseases. The process of manual identification of megakaryocytes...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2023-01-01
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| Series: | Technology in Cancer Research & Treatment |
| Online Access: | https://doi.org/10.1177/15330338221150069 |
| _version_ | 1797858934666559488 |
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| author | Xiaofen Wang MM Ying Wang BS Chao Qi MM Sai Qiao MD, PhD Suwen Yang MM Rongrong Wang MM Hong Jin BM Jun Zhang MD, PhD |
| author_facet | Xiaofen Wang MM Ying Wang BS Chao Qi MM Sai Qiao MD, PhD Suwen Yang MM Rongrong Wang MM Hong Jin BM Jun Zhang MD, PhD |
| author_sort | Xiaofen Wang MM |
| collection | DOAJ |
| description | The evaluation of megakaryocytes is an important part of the work up on bone marrow smear examination. It has significance in the differential diagnosis, therapeutic efficacy assessment, and predication of prognosis of many hematologic diseases. The process of manual identification of megakaryocytes are tedious and lack of reproducibility; therefore, a reliable method of automated megakaryocytic identification is urgently needed. Three hundred and thirty-three bone marrow aspirate smears were digitized by Morphogo system. Pathologists annotated megakaryocytes on the digital images of marrow smears are applied to construct a large dataset for testing the system's predictive performance. Subsequently, we obtained megakaryocyte count and classification for each sample by different methods (system-automated analysis, system-assisted analysis, and microscopic examination) to study the correlation between different counting and classification methods. Morphogo system localized cells likely to be megakaryocytes on digital smears, which were later annotated by pathologists and the system, respectively. The system showed outstanding performance in identifying megakaryocytes in bone marrow smears with high sensitivity (96.57%) and specificity (89.71%). The overall correlation between the different methods was confirmed the high consistency ( r ≥ 0.7218, R 2 ≥ 0.5211) with microscopic examination in classifying megakaryocytes. Morphogo system was proved as a reliable screen tool for analyzing megakaryocytes. The application of Morphogo system shows promises to advance the automation and standardization of bone marrow smear examination. |
| first_indexed | 2024-04-09T21:21:23Z |
| format | Article |
| id | doaj.art-2aea392466324e5694661af7ebd73fe3 |
| institution | Directory Open Access Journal |
| issn | 1533-0338 |
| language | English |
| last_indexed | 2024-04-09T21:21:23Z |
| publishDate | 2023-01-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Technology in Cancer Research & Treatment |
| spelling | doaj.art-2aea392466324e5694661af7ebd73fe32023-03-28T05:03:48ZengSAGE PublishingTechnology in Cancer Research & Treatment1533-03382023-01-012210.1177/15330338221150069The Application of Morphogo in the Detection of Megakaryocytes from Bone Marrow Digital Images with Convolutional Neural NetworksXiaofen Wang MM0Ying Wang BS1Chao Qi MM2Sai Qiao MD, PhD3Suwen Yang MM4Rongrong Wang MM5Hong Jin BM6Jun Zhang MD, PhD7 Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, China Department of Medical Development, Hangzhou Zhiwei Information&Technology Ltd., Hangzhou, China Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, China Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, China Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, China Department of Clinical Pharmacy, the First Affiliated Hospital, Zhejiang University, Hangzhou, Zhejiang, China Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, China Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, ChinaThe evaluation of megakaryocytes is an important part of the work up on bone marrow smear examination. It has significance in the differential diagnosis, therapeutic efficacy assessment, and predication of prognosis of many hematologic diseases. The process of manual identification of megakaryocytes are tedious and lack of reproducibility; therefore, a reliable method of automated megakaryocytic identification is urgently needed. Three hundred and thirty-three bone marrow aspirate smears were digitized by Morphogo system. Pathologists annotated megakaryocytes on the digital images of marrow smears are applied to construct a large dataset for testing the system's predictive performance. Subsequently, we obtained megakaryocyte count and classification for each sample by different methods (system-automated analysis, system-assisted analysis, and microscopic examination) to study the correlation between different counting and classification methods. Morphogo system localized cells likely to be megakaryocytes on digital smears, which were later annotated by pathologists and the system, respectively. The system showed outstanding performance in identifying megakaryocytes in bone marrow smears with high sensitivity (96.57%) and specificity (89.71%). The overall correlation between the different methods was confirmed the high consistency ( r ≥ 0.7218, R 2 ≥ 0.5211) with microscopic examination in classifying megakaryocytes. Morphogo system was proved as a reliable screen tool for analyzing megakaryocytes. The application of Morphogo system shows promises to advance the automation and standardization of bone marrow smear examination.https://doi.org/10.1177/15330338221150069 |
| spellingShingle | Xiaofen Wang MM Ying Wang BS Chao Qi MM Sai Qiao MD, PhD Suwen Yang MM Rongrong Wang MM Hong Jin BM Jun Zhang MD, PhD The Application of Morphogo in the Detection of Megakaryocytes from Bone Marrow Digital Images with Convolutional Neural Networks Technology in Cancer Research & Treatment |
| title | The Application of Morphogo in the Detection of Megakaryocytes from Bone Marrow Digital Images with Convolutional Neural Networks |
| title_full | The Application of Morphogo in the Detection of Megakaryocytes from Bone Marrow Digital Images with Convolutional Neural Networks |
| title_fullStr | The Application of Morphogo in the Detection of Megakaryocytes from Bone Marrow Digital Images with Convolutional Neural Networks |
| title_full_unstemmed | The Application of Morphogo in the Detection of Megakaryocytes from Bone Marrow Digital Images with Convolutional Neural Networks |
| title_short | The Application of Morphogo in the Detection of Megakaryocytes from Bone Marrow Digital Images with Convolutional Neural Networks |
| title_sort | application of morphogo in the detection of megakaryocytes from bone marrow digital images with convolutional neural networks |
| url | https://doi.org/10.1177/15330338221150069 |
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