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Development of a Prognostic Model for Rectal Cancer Based on a CT Imaging Deep Learning Algorithm Integrated with Clinical Hematological Features

Development of a Prognostic Model for Rectal Cancer Based on a CT Imaging Deep Learning Algorithm Integrated with Clinical Hematological Features

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500104756
Enrollment
Unknown
Registered
2025-06-23
Start date
2025-07-01
Completion date
Unknown
Last updated
2025-06-30

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Rectal cancer

Interventions

Observation group of rectal cancer resection surgery:None

Sponsors

The First Affiliated Hospital of Shan Tou University Medical College
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1.Pathological diagnosis of rectal cancer confirmed by postoperative tissue examination. ; 2.No prior anticancer treatment, including immunotherapy, targeted therapy, neoadjuvant chemotherapy, or radiotherapy, before CT imaging. 3.Complete preoperative abdominal CT imaging data. 4.Complete imaging, clinical data, and other information, including other information such as genetic testing data, if necessary;

Exclusion criteria

Exclusion criteria: 1.Presence of other severe comorbidities affecting health, such severe heart, brain, liver, lung, or kidney diseases. ; 2.Presence of other primary malignancies. 3.Participants who lack relevant clinical data (such as height, test results, etc.); 4.Patients who have undergone preoperative radiotherapy or chemotherapy. ; 5.Insufficient CT image quality preventing the acquisition of measurable results. ;

Design outcomes

Primary

MeasureTime frame
Preoperative laboratory examination results;Postoperative data;Calibration curve;Presence of lymph node metastasis;Preoperative comorbidities;Image data;Surgical data;Receiver operating characteristic curve(ROC);Area under curve(AUC);Decision Curve Analysis(DCA);C-index;Accuracy rate;Sensitivity;Specificity;

Countries

China

Contacts

Public ContactXinxin Li

the First Affiliated Hospital of Shan Tou University Medical College

13531268157@139.com+86 13531268157

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026