Abstract 1441P
Background
The accurate detection of lymph node metastasis (LNM) in early gastric cancer (EGC) remains a challenge, conventional radical gastrectomy may not be warranted for EGC patients with a low LNM risk and a favorable prognosis. This study aims to construct a risk prediction model of lymph node metastasis based on clinicopathologic features, tumor budding, convolutional neural network, and machine learning in early gastric cancer.
Methods
Clinicopathological features and tumor budding (TB) were assessed using the image recognition software Qupath. There was a total of 1523471 patches, 260998 patches, and 166594 patches from three patient cohorts that were retrospectively analyzed. Convolutional neural networks (CNNs) were used for deep transfer learning to classify patches and extract features. LASSO regression and multiple machine learning algorithms were employed to combine CNN features with clinicopathological features. The risk prediction model was also verified in two independent validation cohorts.
Results
Among 200 patients, LNM incidence was 27.14% in the training cohort, 15.15% in the internal validation cohort, and 14.82% in the external validation cohort. Multivariate analysis identified pathological T stage and ITBCC-TB grade as independent LNM risk factors (p < 0.05). The Resnet152 CNN model demonstrated excellent performance with AUC values of 0.995, 0.988, and 0.965 in the training, internal validation, and external validation cohorts, respectively. The CNN-ML model using Gradient Boosting exhibited superior predictive capacity, with AUC values of 0.901 (95% CI 0.844-0.957), 0.871 (95% CI 0.726-0.999), and 0.804 (95% CI 0.555-0.999) in the training and two independent validation cohorts.
Conclusions
Pathological T stage and ITBCC-TB grade were identified as independent risk factors for LNM in EGC. The integration of clinicopathological features, image recognition, and deep transfer learning using CNNs resulted in a highly accurate predictive model for LNM in EGC. This model will provide valuable insights into the development of a more comprehensive and individualized approach to managing EGC, thereby improving the quality of care for affected patients.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
1515P - Surgery versus chemotherapy for pulmonary oligometastasis after pancreatectomy: A multicentre observational study
Presenter: Ryoji Takada
Session: Poster session 18
1516P - Lung-only metastatic PDAC: Another disease?
Presenter: Léa Mercier
Session: Poster session 18
1517P - Isolated LUng Metastases in pancreatic AdenoCArcinoma patients in a multicenter Italian cohort: The LU.M.A.CA study
Presenter: Giulia Orsi
Session: Poster session 18
1518P - Stereotactic radiotherapy and IMM-101 in patients with oligometastatic pancreatic cancer following FOLFIRINOX: The MEPANC trial
Presenter: Leonoor Wismans
Session: Poster session 18
Resources:
Abstract
1519P - Real-world evidence on long-term survivors of metastatic pancreatic ductal adenocarcinoma (mPDAC) previously treated with liposomal irinotecan: NALLONG study
Presenter: Makoto Ueno
Session: Poster session 18
1520P - Real-world assessment of NALIRIFOX for advanced pancreatic ductal adenocarcinoma: An exploratory analysis
Presenter: Andreas Reichinger
Session: Poster session 18
Resources:
Abstract
1521P - Efficacy and safety of liposomal irinotecan plus S-1 in patients with metastatic pancreatic cancer after failure of first-line gemcitabine-based chemotherapy: Result of a phase I/II study
Presenter: Hiroshi Imaoka
Session: Poster session 18
1522P - S-1 monotherapy versus nanoliposomal irinotecan plus 5-fluorouracil/leucovorin regimen for second-line therapy of recurrent or metastatic pancreatic cancer (JON 2109-P)
Presenter: Yuichiro Tozuka
Session: Poster session 18
1523P - Efficacy of gemcitabine plus nab-paclitaxel in second-line treatment of metastatic pancreatic cancer
Presenter: Yasin Sezgin
Session: Poster session 18