Virtual 3D reconstruction of complex congenital cardiac anatomy from 3D rotational angiography
Abstract Background Despite advancements in imaging technologies, including CT scans and MRI, these modalities may still fail to capture intricate details of congenital heart defects accurately. Virtual 3D models have revolutionized the field of pediatric interventional cardiology by providing clini...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-01-01
|
| Series: | 3D Printing in Medicine |
| Online Access: | https://doi.org/10.1186/s41205-024-00247-6 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832571977566519296 |
|---|---|
| author | Ernesto Mejia Shannon Sweeney Jenny E. Zablah |
| author_facet | Ernesto Mejia Shannon Sweeney Jenny E. Zablah |
| author_sort | Ernesto Mejia |
| collection | DOAJ |
| description | Abstract Background Despite advancements in imaging technologies, including CT scans and MRI, these modalities may still fail to capture intricate details of congenital heart defects accurately. Virtual 3D models have revolutionized the field of pediatric interventional cardiology by providing clinicians with tangible representations of complex anatomical structures. We examined the feasibility and accuracy of utilizing an automated, Artificial Intelligence (AI) driven, cloud-based platform for virtual 3D visualization of complex congenital heart disease obtained from 3D rotational angiography DICOM images. Methods Five patients selected at random with 3DRA performed in the pediatric cardiac catheterization suite were selected. 3DRA’s were performed following published institutional protocols and segmentations performed by primary operators. The 3DRA DICOM images were anonymized as per protocol and exported. Images when then processed by Axial3D Artificial Intelligence (AI) driven cloud-based platform for virtual segmentation. Two separate expert operators were selected to subjectively analyze the segmentations and compare them to the operator reconstructions for anatomic accuracy. Results Comparing results with local reconstructions by expert operators, five different patient anatomies were analyzed, showcasing Axial3D’s ability to produce highly detailed reconstructions with improved visual appeal, including color-coded segments for implanted materials like stents. The reconstructions exhibited superior segmentation of different intrathoracic structures when compared to local models, offering valuable insights for medical professionals and patients. Conclusions The use of the AI driven, cloud-based platform for 3D visualization of complex congenital heart lesions presents a promising advancement in pediatric interventional cardiology, facilitating enhanced patient care, procedural planning, and educational opportunities for trainees and patients alike. |
| format | Article |
| id | doaj-art-0bf78573fa5941dea44e91df898d05a3 |
| institution | Kabale University |
| issn | 2365-6271 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | 3D Printing in Medicine |
| spelling | doaj-art-0bf78573fa5941dea44e91df898d05a32025-02-02T12:09:24ZengBMC3D Printing in Medicine2365-62712025-01-011111510.1186/s41205-024-00247-6Virtual 3D reconstruction of complex congenital cardiac anatomy from 3D rotational angiographyErnesto Mejia0Shannon Sweeney1Jenny E. Zablah2Department of Pediatric Cardiology, The Heart Institute, University of Colorado, Children’s Hospital ColoradoDepartment of Pediatric Cardiology, The Heart Institute, University of Colorado, Children’s Hospital ColoradoDepartment of Pediatric Cardiology, The Heart Institute, University of Colorado, Children’s Hospital ColoradoAbstract Background Despite advancements in imaging technologies, including CT scans and MRI, these modalities may still fail to capture intricate details of congenital heart defects accurately. Virtual 3D models have revolutionized the field of pediatric interventional cardiology by providing clinicians with tangible representations of complex anatomical structures. We examined the feasibility and accuracy of utilizing an automated, Artificial Intelligence (AI) driven, cloud-based platform for virtual 3D visualization of complex congenital heart disease obtained from 3D rotational angiography DICOM images. Methods Five patients selected at random with 3DRA performed in the pediatric cardiac catheterization suite were selected. 3DRA’s were performed following published institutional protocols and segmentations performed by primary operators. The 3DRA DICOM images were anonymized as per protocol and exported. Images when then processed by Axial3D Artificial Intelligence (AI) driven cloud-based platform for virtual segmentation. Two separate expert operators were selected to subjectively analyze the segmentations and compare them to the operator reconstructions for anatomic accuracy. Results Comparing results with local reconstructions by expert operators, five different patient anatomies were analyzed, showcasing Axial3D’s ability to produce highly detailed reconstructions with improved visual appeal, including color-coded segments for implanted materials like stents. The reconstructions exhibited superior segmentation of different intrathoracic structures when compared to local models, offering valuable insights for medical professionals and patients. Conclusions The use of the AI driven, cloud-based platform for 3D visualization of complex congenital heart lesions presents a promising advancement in pediatric interventional cardiology, facilitating enhanced patient care, procedural planning, and educational opportunities for trainees and patients alike.https://doi.org/10.1186/s41205-024-00247-6 |
| spellingShingle | Ernesto Mejia Shannon Sweeney Jenny E. Zablah Virtual 3D reconstruction of complex congenital cardiac anatomy from 3D rotational angiography 3D Printing in Medicine |
| title | Virtual 3D reconstruction of complex congenital cardiac anatomy from 3D rotational angiography |
| title_full | Virtual 3D reconstruction of complex congenital cardiac anatomy from 3D rotational angiography |
| title_fullStr | Virtual 3D reconstruction of complex congenital cardiac anatomy from 3D rotational angiography |
| title_full_unstemmed | Virtual 3D reconstruction of complex congenital cardiac anatomy from 3D rotational angiography |
| title_short | Virtual 3D reconstruction of complex congenital cardiac anatomy from 3D rotational angiography |
| title_sort | virtual 3d reconstruction of complex congenital cardiac anatomy from 3d rotational angiography |
| url | https://doi.org/10.1186/s41205-024-00247-6 |
| work_keys_str_mv | AT ernestomejia virtual3dreconstructionofcomplexcongenitalcardiacanatomyfrom3drotationalangiography AT shannonsweeney virtual3dreconstructionofcomplexcongenitalcardiacanatomyfrom3drotationalangiography AT jennyezablah virtual3dreconstructionofcomplexcongenitalcardiacanatomyfrom3drotationalangiography |