Details

Autor(en) / Beteiligte

• Tang, Chunbo
• Yuan, Jun
• Guo, Hailiang
• Dai, Zhongyang
• Liu, Biaoshui
• Xi, Haiyan
• He, Ji
• Niu, Shanzhou

Titel

Quantify the Effect of Air Gap Errors on Skin Dose for Breast Cancer Radiotherapy

Ist Teil von

• Technology in cancer research & treatment, 2024-01, Vol.23, p.15330338241258566-15330338241258566

Ort / Verlag

United States: SAGE Publications

Erscheinungsjahr

2024

Quelle

MEDLINE

Beschreibungen/Notizen

• Determining the impact of air gap errors on the skin dose in postoperative breast cancer radiotherapy under dynamic intensity-modulated radiation therapy (IMRT) techniques. This was a retrospective study that involved 55 patients who underwent postoperative radiotherapy following modified radical mastectomy. All plans employed tangential IMRT, with a prescription dose of 50 Gy, and bolus added solely to the chest wall. Simulated air gap depth errors of 2 mm, 3 mm, and 5 mm were introduced at depression or inframammary fold areas on the skin, resulting in the creation of air gaps named Air2, Air3, and Air5. Utilizing a multivariable GEE, the average dose ( ) of the local skin was determined to evaluate its relationship with air gap volume and the lateral beam's average angle (AALB). Additionally, an analysis was conducted on the impact of gaps on local skin. When simulating an air gap depth error of 2 mm, the average in plan2 increased by 0.46 Gy compared to the initial plan (planO) (  < .001). For the 3-mm air gap, the average of plan3 was 0.51 Gy higher than that of planO (  < .001). When simulating the air gap as 5 mm, the average of plan5 significantly increased by 0.59 Gy compared to planO (  < .001). The TCP results showed a similar trend to those of . As the depth of air gap error increases, NTCP values also gradually rise. The linear regression of the multivariable GEE equation indicates that the volume of air gaps and the AALB are strong predictors of . With small irregular air gap errors simulated in 55 patients, the values of skin's , TCP, and NTCP increased. A multivariable linear GEE regression model may effectively explain the impact of air gap volume and AALB on the local skin.