CLP-Net: an advanced artificial intelligence technique for localizing standard planes of cleft lip and palate by three-dimensional ultrasound in the first trimester
Abstract Background Early diagnosis of cleft lip and palate (CLP) requires a multiplane examination, demanding high technical proficiency from radiologists. Therefore, this study aims to develop and validate the first artificial intelligence (AI)-based model (CLP-Net) for fully automated multi-plane...
Saved in:
| Main Authors: | , , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-01-01
|
| Series: | BMC Pregnancy and Childbirth |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12884-024-07108-4 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841544207933636608 |
|---|---|
| author | Guangzhi He Zhou Li Zhiyuan Zhu Tong Han Yan Cao Chaoyu Chen Yuhao Huang Haoran Dou Lianying Liang Fangmei Zhang Jin Peng Tao Tan Hongmei Liu Xin Yang Dong Ni |
| author_facet | Guangzhi He Zhou Li Zhiyuan Zhu Tong Han Yan Cao Chaoyu Chen Yuhao Huang Haoran Dou Lianying Liang Fangmei Zhang Jin Peng Tao Tan Hongmei Liu Xin Yang Dong Ni |
| author_sort | Guangzhi He |
| collection | DOAJ |
| description | Abstract Background Early diagnosis of cleft lip and palate (CLP) requires a multiplane examination, demanding high technical proficiency from radiologists. Therefore, this study aims to develop and validate the first artificial intelligence (AI)-based model (CLP-Net) for fully automated multi-plane localization in three-dimensional(3D) ultrasound during the first trimester. Methods This retrospective study included 418 (394 normal, 24 CLP) 3D ultrasound from 288 pregnant woman between July 2022 to October 2024 from Shenzhen Guangming District People’s Hospital during the 11–13+ 6 weeks of pregnancy. 320 normal volumes were used for training and validation, while 74 normal and 24 CLP volumes were used for testing. Two experienced radiologists reviewed three standard lip and palate planes (mid sagittal, retronasal triangle, and maxillary axial planes) as ground truth (GT) and the CLP-Net was developed to locate these planes. Results In normal test set, mean angle(± SD)° and distance(± SD)mm differences were 6.24 ± 4.83, 9.81 ± 5.48, 15.36 ± 18.14 and 0.86 ± 0.72, 1.36 ± 1.15, 1.96 ± 2.35 for MSP ± SD, RTP ± SD and MAP ± SD, NCC and SSIM were 0.931 ± 0.079, 0.819 ± 0.122, 0.781 ± 0.157 and 0.896 ± 0.058, 0.785 ± 0.076, 0.726 ± 0.088 respectively. In the CLP cases, there were 8.61 ± 5.52, 10.67 ± 5.08, 16.91 ± 17.42 and 1.03 ± 1.20, 1.17 ± 1.08, 1.34 ± 0.95 for mean angle and distance in MSP, RTP, and MAP, respectively. NCC and SSIM were 0.876 ± 0.104, 0.803 ± 0.084, 0.793 ± 0.089 and 0.841 ± 0.105, 0.812 ± 0.085, 0.764 ± 0.100, respectively. CLP-Net predictions had a highly visual acceptance rate among radiologists (MSP: 95%, RTP: 70%, MAP: 70%), with improved localization speed 15s(31.3%) for senior radiologists and 63s(38.9%) for junior radiologists. Conclusions CLP-Net accurately locates three planes for CLP screening, aiding radiologists and enhancing the efficiency of ultrasound examinations. |
| format | Article |
| id | doaj-art-a9284c6021804af48f3b22ef58a59a20 |
| institution | Kabale University |
| issn | 1471-2393 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Pregnancy and Childbirth |
| spelling | doaj-art-a9284c6021804af48f3b22ef58a59a202025-01-12T12:43:50ZengBMCBMC Pregnancy and Childbirth1471-23932025-01-0125111110.1186/s12884-024-07108-4CLP-Net: an advanced artificial intelligence technique for localizing standard planes of cleft lip and palate by three-dimensional ultrasound in the first trimesterGuangzhi He0Zhou Li1Zhiyuan Zhu2Tong Han3Yan Cao4Chaoyu Chen5Yuhao Huang6Haoran Dou7Lianying Liang8Fangmei Zhang9Jin Peng10Tao Tan11Hongmei Liu12Xin Yang13Dong Ni14Jinan UniversityJinan UniversityNational-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Health Science Center, Shenzhen UniversityNational-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Health Science Center, Shenzhen UniversityShenzhen RayShape Medical Technology Co., LtdNational-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Health Science Center, Shenzhen UniversityNational-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Health Science Center, Shenzhen UniversityDepartment of Computer Science, School of Engineering, University of ManchesterDepartment of Ultrasound, Shenzhen Guangming District People’s HospitalDepartment of Ultrasound, Shenzhen Guangming District People’s HospitalNational-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Health Science Center, Shenzhen UniversityFaculty of Applied Sciences, Macao Polytechnic UniversityDepartment of Ultrasound, Institute of Ultrasound in Musculoskeletal Sports Medicine, The Affiliated Guangdong Second Provincial General Hospital of Jinan UniversityNational-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Health Science Center, Shenzhen UniversityNational-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Health Science Center, Shenzhen UniversityAbstract Background Early diagnosis of cleft lip and palate (CLP) requires a multiplane examination, demanding high technical proficiency from radiologists. Therefore, this study aims to develop and validate the first artificial intelligence (AI)-based model (CLP-Net) for fully automated multi-plane localization in three-dimensional(3D) ultrasound during the first trimester. Methods This retrospective study included 418 (394 normal, 24 CLP) 3D ultrasound from 288 pregnant woman between July 2022 to October 2024 from Shenzhen Guangming District People’s Hospital during the 11–13+ 6 weeks of pregnancy. 320 normal volumes were used for training and validation, while 74 normal and 24 CLP volumes were used for testing. Two experienced radiologists reviewed three standard lip and palate planes (mid sagittal, retronasal triangle, and maxillary axial planes) as ground truth (GT) and the CLP-Net was developed to locate these planes. Results In normal test set, mean angle(± SD)° and distance(± SD)mm differences were 6.24 ± 4.83, 9.81 ± 5.48, 15.36 ± 18.14 and 0.86 ± 0.72, 1.36 ± 1.15, 1.96 ± 2.35 for MSP ± SD, RTP ± SD and MAP ± SD, NCC and SSIM were 0.931 ± 0.079, 0.819 ± 0.122, 0.781 ± 0.157 and 0.896 ± 0.058, 0.785 ± 0.076, 0.726 ± 0.088 respectively. In the CLP cases, there were 8.61 ± 5.52, 10.67 ± 5.08, 16.91 ± 17.42 and 1.03 ± 1.20, 1.17 ± 1.08, 1.34 ± 0.95 for mean angle and distance in MSP, RTP, and MAP, respectively. NCC and SSIM were 0.876 ± 0.104, 0.803 ± 0.084, 0.793 ± 0.089 and 0.841 ± 0.105, 0.812 ± 0.085, 0.764 ± 0.100, respectively. CLP-Net predictions had a highly visual acceptance rate among radiologists (MSP: 95%, RTP: 70%, MAP: 70%), with improved localization speed 15s(31.3%) for senior radiologists and 63s(38.9%) for junior radiologists. Conclusions CLP-Net accurately locates three planes for CLP screening, aiding radiologists and enhancing the efficiency of ultrasound examinations.https://doi.org/10.1186/s12884-024-07108-4Artificial intelligenceCleft lip and palateFirst-trimester3D ultrasoundFetusStandard plane localization |
| spellingShingle | Guangzhi He Zhou Li Zhiyuan Zhu Tong Han Yan Cao Chaoyu Chen Yuhao Huang Haoran Dou Lianying Liang Fangmei Zhang Jin Peng Tao Tan Hongmei Liu Xin Yang Dong Ni CLP-Net: an advanced artificial intelligence technique for localizing standard planes of cleft lip and palate by three-dimensional ultrasound in the first trimester BMC Pregnancy and Childbirth Artificial intelligence Cleft lip and palate First-trimester 3D ultrasound Fetus Standard plane localization |
| title | CLP-Net: an advanced artificial intelligence technique for localizing standard planes of cleft lip and palate by three-dimensional ultrasound in the first trimester |
| title_full | CLP-Net: an advanced artificial intelligence technique for localizing standard planes of cleft lip and palate by three-dimensional ultrasound in the first trimester |
| title_fullStr | CLP-Net: an advanced artificial intelligence technique for localizing standard planes of cleft lip and palate by three-dimensional ultrasound in the first trimester |
| title_full_unstemmed | CLP-Net: an advanced artificial intelligence technique for localizing standard planes of cleft lip and palate by three-dimensional ultrasound in the first trimester |
| title_short | CLP-Net: an advanced artificial intelligence technique for localizing standard planes of cleft lip and palate by three-dimensional ultrasound in the first trimester |
| title_sort | clp net an advanced artificial intelligence technique for localizing standard planes of cleft lip and palate by three dimensional ultrasound in the first trimester |
| topic | Artificial intelligence Cleft lip and palate First-trimester 3D ultrasound Fetus Standard plane localization |
| url | https://doi.org/10.1186/s12884-024-07108-4 |
| work_keys_str_mv | AT guangzhihe clpnetanadvancedartificialintelligencetechniqueforlocalizingstandardplanesofcleftlipandpalatebythreedimensionalultrasoundinthefirsttrimester AT zhouli clpnetanadvancedartificialintelligencetechniqueforlocalizingstandardplanesofcleftlipandpalatebythreedimensionalultrasoundinthefirsttrimester AT zhiyuanzhu clpnetanadvancedartificialintelligencetechniqueforlocalizingstandardplanesofcleftlipandpalatebythreedimensionalultrasoundinthefirsttrimester AT tonghan clpnetanadvancedartificialintelligencetechniqueforlocalizingstandardplanesofcleftlipandpalatebythreedimensionalultrasoundinthefirsttrimester AT yancao clpnetanadvancedartificialintelligencetechniqueforlocalizingstandardplanesofcleftlipandpalatebythreedimensionalultrasoundinthefirsttrimester AT chaoyuchen clpnetanadvancedartificialintelligencetechniqueforlocalizingstandardplanesofcleftlipandpalatebythreedimensionalultrasoundinthefirsttrimester AT yuhaohuang clpnetanadvancedartificialintelligencetechniqueforlocalizingstandardplanesofcleftlipandpalatebythreedimensionalultrasoundinthefirsttrimester AT haorandou clpnetanadvancedartificialintelligencetechniqueforlocalizingstandardplanesofcleftlipandpalatebythreedimensionalultrasoundinthefirsttrimester AT lianyingliang clpnetanadvancedartificialintelligencetechniqueforlocalizingstandardplanesofcleftlipandpalatebythreedimensionalultrasoundinthefirsttrimester AT fangmeizhang clpnetanadvancedartificialintelligencetechniqueforlocalizingstandardplanesofcleftlipandpalatebythreedimensionalultrasoundinthefirsttrimester AT jinpeng clpnetanadvancedartificialintelligencetechniqueforlocalizingstandardplanesofcleftlipandpalatebythreedimensionalultrasoundinthefirsttrimester AT taotan clpnetanadvancedartificialintelligencetechniqueforlocalizingstandardplanesofcleftlipandpalatebythreedimensionalultrasoundinthefirsttrimester AT hongmeiliu clpnetanadvancedartificialintelligencetechniqueforlocalizingstandardplanesofcleftlipandpalatebythreedimensionalultrasoundinthefirsttrimester AT xinyang clpnetanadvancedartificialintelligencetechniqueforlocalizingstandardplanesofcleftlipandpalatebythreedimensionalultrasoundinthefirsttrimester AT dongni clpnetanadvancedartificialintelligencetechniqueforlocalizingstandardplanesofcleftlipandpalatebythreedimensionalultrasoundinthefirsttrimester |