Comparative study of left atrium epicardial fat tissue pattern using persistent homology approach
Abstract Objective Atrial Fibrillation (A-fib) is an abnormal heartbeat condition in which the heart races and beats in an uncontrollable way. It is observed that the presence of increased epicardial fat/fatty tissue in the atrium can lead to A-fib. Persistent homology using topological features can...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-09-01
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| Series: | BMC Research Notes |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13104-022-06173-2 |
| _version_ | 1818022025190440960 |
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| author | Deepa Deepa Yashbir Singh Wathiq Mansoor Weichih Hu Rahul Paul Gunnar E. Carlsson |
| author_facet | Deepa Deepa Yashbir Singh Wathiq Mansoor Weichih Hu Rahul Paul Gunnar E. Carlsson |
| author_sort | Deepa Deepa |
| collection | DOAJ |
| description | Abstract Objective Atrial Fibrillation (A-fib) is an abnormal heartbeat condition in which the heart races and beats in an uncontrollable way. It is observed that the presence of increased epicardial fat/fatty tissue in the atrium can lead to A-fib. Persistent homology using topological features can be used to recapitulate enormous amounts of spatially complicated medical data into a visual code to identify a specific pattern of epicardial fat tissue with non-fat tissue. Our aim is to evaluate the topological pattern of left atrium epicardial fat tissue with non-fat tissue. Results A topological data analysis approach was acquired to study the imaging pattern between the left atrium epicardial fat tissue and non-fat tissue patches. The patches of eight patients from CT images of the left atrium heart were used and categorized into “left atrium epicardial fat tissue” and “non-fat tissue” groups. The features that distinguish the “epicardial fat tissue” and “non-fat tissue” groups are extracted using persistent homology (PH). Our result reveals that our proposed research can discriminate between left atrium epicardial fat tissue and non-fat tissue. Specifically, the range of Betti numbers in the epicardial tissue is smaller (0–30) than the non-fat tissue (0–100), indicating that non-fat tissue has good topology. |
| first_indexed | 2024-04-14T08:25:55Z |
| format | Article |
| id | doaj.art-3c7eb820fa7943a699ec2ba00e54013b |
| institution | Directory Open Access Journal |
| issn | 1756-0500 |
| language | English |
| last_indexed | 2024-04-14T08:25:55Z |
| publishDate | 2022-09-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Research Notes |
| spelling | doaj.art-3c7eb820fa7943a699ec2ba00e54013b2022-12-22T02:04:03ZengBMCBMC Research Notes1756-05002022-09-011511510.1186/s13104-022-06173-2Comparative study of left atrium epicardial fat tissue pattern using persistent homology approachDeepa Deepa0Yashbir Singh1Wathiq Mansoor2Weichih Hu3Rahul Paul4Gunnar E. Carlsson5Biomedical Engineering, Chung Yuan Christian UniversityBiomedical Engineering, Chung Yuan Christian UniversityEngineering & Information Technology, University of DubaiBiomedical Engineering, Chung Yuan Christian UniversityDepartment of Radiation Oncology, Massachusetts General HospitalDepartment of Mathmetics, Stanford UniversityAbstract Objective Atrial Fibrillation (A-fib) is an abnormal heartbeat condition in which the heart races and beats in an uncontrollable way. It is observed that the presence of increased epicardial fat/fatty tissue in the atrium can lead to A-fib. Persistent homology using topological features can be used to recapitulate enormous amounts of spatially complicated medical data into a visual code to identify a specific pattern of epicardial fat tissue with non-fat tissue. Our aim is to evaluate the topological pattern of left atrium epicardial fat tissue with non-fat tissue. Results A topological data analysis approach was acquired to study the imaging pattern between the left atrium epicardial fat tissue and non-fat tissue patches. The patches of eight patients from CT images of the left atrium heart were used and categorized into “left atrium epicardial fat tissue” and “non-fat tissue” groups. The features that distinguish the “epicardial fat tissue” and “non-fat tissue” groups are extracted using persistent homology (PH). Our result reveals that our proposed research can discriminate between left atrium epicardial fat tissue and non-fat tissue. Specifically, the range of Betti numbers in the epicardial tissue is smaller (0–30) than the non-fat tissue (0–100), indicating that non-fat tissue has good topology.https://doi.org/10.1186/s13104-022-06173-2Atrial fibrillationBarcodePersistent homologyPixel value maskingTopology |
| spellingShingle | Deepa Deepa Yashbir Singh Wathiq Mansoor Weichih Hu Rahul Paul Gunnar E. Carlsson Comparative study of left atrium epicardial fat tissue pattern using persistent homology approach BMC Research Notes Atrial fibrillation Barcode Persistent homology Pixel value masking Topology |
| title | Comparative study of left atrium epicardial fat tissue pattern using persistent homology approach |
| title_full | Comparative study of left atrium epicardial fat tissue pattern using persistent homology approach |
| title_fullStr | Comparative study of left atrium epicardial fat tissue pattern using persistent homology approach |
| title_full_unstemmed | Comparative study of left atrium epicardial fat tissue pattern using persistent homology approach |
| title_short | Comparative study of left atrium epicardial fat tissue pattern using persistent homology approach |
| title_sort | comparative study of left atrium epicardial fat tissue pattern using persistent homology approach |
| topic | Atrial fibrillation Barcode Persistent homology Pixel value masking Topology |
| url | https://doi.org/10.1186/s13104-022-06173-2 |
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