Predictive value of Excel forms based on an automatic calculation of dose equivalent in 2 Gy per fraction in adaptive brachytherapy for cervical cancer.

Purpose: External beam radiotherapy (EBRT) combined with brachytherapy (BT) is the standard mode of radical radiotherapy for locally advanced cervical cancer. The cumulative equivalent doses in 2 Gy per fraction (EQD) is an important basis for estimating the probability of local control of tumors and monitoring the occurrence of side effects in normal tissues. The purpose of this study was to explore the predictive value of Excel forms based on an automatic calculation in radical adaptive BT for cervical cancer.

Material And Methods: A retrospective analysis of 119 patients suffering from cervical cancer, treated with radical radiotherapy. All patients were treated with EBRT and adaptive BT. EBRT prescribed dose was 42.0-50.4 Gy in 21-28 fractions. BT nominal prescribed dose was 28 Gy in 4 fractions, separated by one week. Total EQD prediction at nth ( = 1-3) BT (TEPB) or actual cumulative EQD (ACEQD) can be calculated automatically by inputting the physical dose based on an in-house designed application. The relationship between TEPB and ACEQD was evaluated, and the predictive value of Excel forms based on the automatic calculation was analyzed.

Results: For the volume of high-risk clinical target, there was a significant decrease between BT1 and BT2. Similarly, for the volume of intermediate-risk clinical target, there was a significant decrease between BT2 and BT3. The sensitivity ranges of TEPB, TEPB, and TEPB prediction were 74.5-91.3%, 83.7-95.7%, and 92.9-99.1%, respectively, and the specificity ranges were 46.7-80.0%, 53.3-90.5%, and 66.7-90.5%, respectively.

Conclusions: The in-house designed application has the function of quickly reading dose-volume histogram (DVH) parameters from the treatment planning system, which allows for balance between the total dose to target volumes and organs at risk (OARs). Excel forms based on EQD automatic calculation presents high predictive accuracy.