Artificial intelligence assisted real-time recognition of intra-abdominal metastasis during laparoscopic gastric cancer surgery
Abstract Laparoscopic exploration (LE) is crucial for diagnosing intra-abdominal metastasis (IAM) in advanced gastric cancer (GC). However, overlooking single, tiny, and occult IAM lesions during LE can severely affect the treatment and prognosis due to surgeons’ visual misinterpretations. To addres...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | npj Digital Medicine |
| Online Access: | https://doi.org/10.1038/s41746-024-01372-6 |
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| _version_ | 1841559044420009984 |
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| author | Hao Chen Longfei Gou Zhiwen Fang Qi Dou Haobin Chen Chang Chen Yuqing Qiu Jinglin Zhang Chenglin Ning Yanfeng Hu Haijun Deng Jiang Yu Guoxin Li |
| author_facet | Hao Chen Longfei Gou Zhiwen Fang Qi Dou Haobin Chen Chang Chen Yuqing Qiu Jinglin Zhang Chenglin Ning Yanfeng Hu Haijun Deng Jiang Yu Guoxin Li |
| author_sort | Hao Chen |
| collection | DOAJ |
| description | Abstract Laparoscopic exploration (LE) is crucial for diagnosing intra-abdominal metastasis (IAM) in advanced gastric cancer (GC). However, overlooking single, tiny, and occult IAM lesions during LE can severely affect the treatment and prognosis due to surgeons’ visual misinterpretations. To address this, we developed the artificial intelligence laparoscopic exploration system (AiLES) to recognize IAM lesions with various metastatic extents and locations. The AiLES was developed based on a dataset consisting of 5111 frames from 100 videos, using 4130 frames for model development and 981 frames for evaluation. The AiLES achieved a Dice score of 0.76 and a recognition speed of 11 frames per second, demonstrating robust performance in different metastatic extents (0.74–0.76) and locations (0.63–0.90). Furthermore, AiLES performed comparably to novice surgeons in IAM recognition and excelled in recognizing tiny and occult lesions. Our results demonstrate that the implementation of AiLES could enhance accurate tumor staging and assist individualized treatment decisions. |
| format | Article |
| id | doaj-art-17208d7fda0f4df39b98d4bb11b0b4b0 |
| institution | Kabale University |
| issn | 2398-6352 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Digital Medicine |
| spelling | doaj-art-17208d7fda0f4df39b98d4bb11b0b4b02025-01-05T12:47:23ZengNature Portfolionpj Digital Medicine2398-63522025-01-018111210.1038/s41746-024-01372-6Artificial intelligence assisted real-time recognition of intra-abdominal metastasis during laparoscopic gastric cancer surgeryHao Chen0Longfei Gou1Zhiwen Fang2Qi Dou3Haobin Chen4Chang Chen5Yuqing Qiu6Jinglin Zhang7Chenglin Ning8Yanfeng Hu9Haijun Deng10Jiang Yu11Guoxin Li12Department of General Surgery & Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, Southern Medical UniversityDepartment of General Surgery & Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, Southern Medical UniversitySchool of Biomedical Engineering, Southern Medical UniversityDepartment of Computer Science and Engineering, The Chinese University of Hong KongNanfang Hospital, Southern Medical UniversityThe First School of Clinical Medicine, Southern Medical UniversitySchool of Biomedical Engineering, Southern Medical UniversitySchool of Biomedical Engineering, Southern Medical UniversitySchool of Biomedical Engineering, Southern Medical UniversityDepartment of General Surgery & Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, Southern Medical UniversityDepartment of General Surgery & Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, Southern Medical UniversityDepartment of General Surgery & Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, Southern Medical UniversityDepartment of General Surgery & Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, Southern Medical UniversityAbstract Laparoscopic exploration (LE) is crucial for diagnosing intra-abdominal metastasis (IAM) in advanced gastric cancer (GC). However, overlooking single, tiny, and occult IAM lesions during LE can severely affect the treatment and prognosis due to surgeons’ visual misinterpretations. To address this, we developed the artificial intelligence laparoscopic exploration system (AiLES) to recognize IAM lesions with various metastatic extents and locations. The AiLES was developed based on a dataset consisting of 5111 frames from 100 videos, using 4130 frames for model development and 981 frames for evaluation. The AiLES achieved a Dice score of 0.76 and a recognition speed of 11 frames per second, demonstrating robust performance in different metastatic extents (0.74–0.76) and locations (0.63–0.90). Furthermore, AiLES performed comparably to novice surgeons in IAM recognition and excelled in recognizing tiny and occult lesions. Our results demonstrate that the implementation of AiLES could enhance accurate tumor staging and assist individualized treatment decisions.https://doi.org/10.1038/s41746-024-01372-6 |
| spellingShingle | Hao Chen Longfei Gou Zhiwen Fang Qi Dou Haobin Chen Chang Chen Yuqing Qiu Jinglin Zhang Chenglin Ning Yanfeng Hu Haijun Deng Jiang Yu Guoxin Li Artificial intelligence assisted real-time recognition of intra-abdominal metastasis during laparoscopic gastric cancer surgery npj Digital Medicine |
| title | Artificial intelligence assisted real-time recognition of intra-abdominal metastasis during laparoscopic gastric cancer surgery |
| title_full | Artificial intelligence assisted real-time recognition of intra-abdominal metastasis during laparoscopic gastric cancer surgery |
| title_fullStr | Artificial intelligence assisted real-time recognition of intra-abdominal metastasis during laparoscopic gastric cancer surgery |
| title_full_unstemmed | Artificial intelligence assisted real-time recognition of intra-abdominal metastasis during laparoscopic gastric cancer surgery |
| title_short | Artificial intelligence assisted real-time recognition of intra-abdominal metastasis during laparoscopic gastric cancer surgery |
| title_sort | artificial intelligence assisted real time recognition of intra abdominal metastasis during laparoscopic gastric cancer surgery |
| url | https://doi.org/10.1038/s41746-024-01372-6 |
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