Prediction of invasion depth and lymph node metastasis in early gastric cancer by artificial intelligence and Gene expression profiling
| Project/Area Number |
19K16825
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 50020:Tumor diagnostics and therapeutics-related
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| Research Institution | The University of Tokyo |
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Principal Investigator |
Kataoka Yosuke 東京大学, 医学部附属病院, 届出研究員 (80800896)
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| Project Period (FY) |
2019-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2020: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2019: ¥3,120,000 (Direct Cost: ¥2,400,000、Indirect Cost: ¥720,000)
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| Keywords | 早期胃癌 / 深達度 / リンパ節転移リスク / AI / 網羅的遺伝子解析 / 深達度診断 / リンパ節転移 / 遺伝子 / ESD / 非治癒切除 |
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| Outline of Research at the Start |
本研究の目的は早期胃癌ESD非治癒切除症例で追加外科手術が施行された症例を対象に、リンパ節転移陽性群およびリンパ節転移陰性群の患者背景、ESD病理所見、網羅的遺伝子発現データの比較から早期胃癌リンパ節転移リスク因子を特定することである。さらに得られた成果を根拠にリンパ節転移リスクの層別化を行い、追加外科手術適応の判断の際に、より有用な基準を確立することは、早期胃癌診療の発展に大きく寄与することが期待される。
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| Outline of Final Research Achievements |
As for the diagnosis of gastric cancer invasion depth by AI, 1207 endoscopic images of intramucosal cancer, 1048 images of submucosal slight invasive cancer (<500 μm), 1260 images of submucosal massive invasive cancer (>500 μm), and 716 images of advanced cancer were annotated. 75% of the dataset was used for training and 25% for evaluation. AI showed that the positive detection rate was 67% with the AUC value of 0.76.
For the gene expression profiling, RNA from 8 cases of intramucosal cancer and 8 cases of submucosal massive invasive cancer were extracted for microarray analysis. We focused on gene A with large variation among the two groups. Through the immunohistological examination, the mean number of positive cells in a 400-fold field of view for gene A was 3.8 for intramucosal cancer and 0.4 for submucosal massive invasive cancer with a significant difference (p < 0.001). The ROC curve for the diagnosis of invasion depth using gene A showed that the AUC value was 0.71.
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| Academic Significance and Societal Importance of the Research Achievements |
早期胃癌の深達度及びリンパ節転移リスクに関する術前診断は内視鏡的粘膜下層剥離術の適応判定および追加外科切除を減らす上で重要である。これまで胃癌深達度診断は、内視鏡医が肉眼所見をもとに主観的評価よって行われてきたが、本研究ではAIおよび網羅的遺伝子発現解析による新たな予測法の可能性を示した。
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Report
(3 results)
Research Products
(2 results)
