Regression Analysis of Rectal Cancer and Possible Application of Artificial Intelligence (AI) Utilization in Radiotherapy

被引：2

作者：

Alnowami, Majdi ^{[1
]}

Abolaban, Fouad ^{[1
,2
]}

Hijazi, Hussam ^{[3
]}

Nisbet, Andrew ^{[4
]}

机构：

[1] King Abdulaziz Univ, Fac Engn, Dept Nucl Engn, POB 80204, Jeddah 21589, Saudi Arabia

[2] King Abdulaziz Univ, KA CARE Energy Res & Innovat Ctr, Jeddah 21589, Saudi Arabia

[3] King Abdulaziz Univ, Fac Med, Radiol Dept, Radiat Oncol Unit, POB 80204, Jeddah 21589, Saudi Arabia

[4] UCL, Dept Med Phys & Biomed Engn, Malet Pl Engn Bldg, London WC1E 6BT, England

来源：

APPLIED SCIENCES-BASEL | 2022年 / 12卷 / 02期

关键词：

radiotherapy; treatment planning; Artificial Intelligence; and tumor regression; THERAPY; HEAD;

D O I：

10.3390/app12020725

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

Artificial Intelligence (AI) has been widely employed in the medical field in recent years in such areas as image segmentation, medical image registration, and computer-aided detection. This study explores one application of using AI in adaptive radiation therapy treatment planning by predicting the tumor volume reduction rate (TVRR). Cone beam computed tomography (CBCT) scans of twenty rectal cancer patients were collected to observe the change in tumor volume over the course of a standard five-week radiotherapy treatment. In addition to treatment volume, patient data including patient age, gender, weight, number of treatment fractions, and dose per fraction were also collected. Application of a stepwise regression model showed that age, dose per fraction and weight were the best predictors for tumor volume reduction rate.

引用

页数：11

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