AI-based imaging diagnostic systems for rectal cancer

JRCT ID: jRCT1040210050

Registered date:06/08/2021

Basic Information

• Recruitment status: Recruiting
• Health condition(s) or Problem(s) studied: rectal cancer
• Date of first enrollment: 06/08/2021
• Target sample size: 200
• Study type: Observational

Outcome(s)

• Primary Outcome: Construction of imaging diagnostic systems based on AI for rectal cancer
• Secondary Outcome: Validation of AI-based imaging diagnostic systems: false-positive rate, false-negative rate, positive predicting value, sensitivity, specificity, negative predicting value

Key inclusion & exclusion criteria

• Age minimum: Not applicable
• Age maximum: Not applicable
• Gender: Both

Include criteria

1) Pathologically diagnosed as adenocarcinoma (including mucinous, signet-cell, and medullary carcinoma) based on the Japanese Classification of Colorectal, Appendiceal, and Anal Carcinoma (JCCAAC), 3rd English Edition on the resected specimen for rectal cancer
2) Performed abdominal and pelvic contrast-enhanced CT (aortic bifurcation to pelvis) or abdominal and pelvic contrast-enhanced MRI (aortic bifurcation to pelvis) before surgery.
3) Inversion depth was suspected cT2 or deeper on JCCAAC 3rd English Edition, mainly located at the low rectum or anal canal.
4) No preoperative chemotherapy or radiotherapy, and performed bilateral lateral pelvic lymph node dissection and primary rectal cancer resection.
5) No treatment history of surgery, chemotherapy, or radiotherapy for pelvic malignancies (including rectal, gynecologic, and urologic cancers).
6) No distant organ metastasis, distant lymph node metastasis, or peritoneal dissemination (not cStage IV) on preoperative images.

• Exclude criteria: none

Related Information

• Primary Sponsor: Ouchi Akira