Self-supervised 3D deep learning on preoperative contrast-enhanced computed tomography for predicting high pathologic nodal burden in esophageal squamous cell carcinoma: temporal and external multicohort validation - Scorecard - MDSpire

Self-supervised 3D deep learning on preoperative contrast-enhanced computed tomography for predicting high pathologic nodal burden in esophageal squamous cell carcinoma: temporal and external multicohort validation

  • By

  • Qian Li

  • Yongxin Li

  • Jing Bai

  • Jinze Zhang

  • Zhenkai Nie

  • Yanxin Ren

  • Zhantao Li

  • Jin Guo

  • Meng Li

  • Tingting Zhang

  • Xinbo Liu

  • June 11, 2026

  • 0 min

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Clinical Scorecard: Utilizing Self-Supervised 3D Deep Learning on Preoperative Contrast-Enhanced CT to Forecast High Pathologic Nodal Burden in Esophageal Squamous Cell Carcinoma: Validation Across Temporal and External Multicohorts

At a Glance

CategoryDetail
Condition
Key Mechanisms
Target PopulationPatients with histopathologically confirmed esophageal squamous cell carcinoma undergoing curative-intent esophagectomy within 30 days of preoperative imaging.
Care Setting

Key Highlights

  • additional_context

Guideline-Based Recommendations

Diagnosis

    Management

      Monitoring & Follow-up

      • Consider routine follow-up imaging such as CT or PET/CT to assess nodal status post-surgery.

      Risks

        Patient & Prescribing Data

        1,060 patients with esophageal squamous cell carcinoma.

        Curative-intent esophagectomy with lymphadenectomy performed within 30 days of preoperative CECT.

        Clinical Best Practices

        • additional_recommendation

        Related Resources & Content

        Original Source(s)

        Self-supervised 3D deep learning on preoperative contrast-enhanced computed tomography for predicting high pathologic nodal burden in esophageal squamous cell carcinoma: temporal and external multicohort validation

        • by Qian Li, Yongxin Li, Jing Bai, Jinze Zhang, Zhenkai Nie, Yanxin Ren, Zhantao Li, Jin Guo, Meng Li, Tingting Zhang, Xinbo Liu

        • June 11, 2026

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