A comprehensive dose-volume histogram-based index for radiotherapy treatment plan quality evaluation: application to...

Advances in radiotherapy have increased treatment plan complexity, making manual quality evaluation more subjective and variable. While deep learning approaches offer automation in planning, evaluation remains a manual bottleneck. Existing indices evaluate individual aspects in isolation and lack a unified perspective. To address this, we developed the advanced dose distribution index (ADDI), a comprehensive dose-volume histogram- and biological dose response-based metric for automation-friendly quality evaluation. ADDI summarizes treatment plan quality as a polar vector, ADDI(r,θ), where the magnitude (r) reflects overall quality and the angle (θ) captures the balance between target and organ-at-risk dose. We validated ADDI across four breast cancer groups involving whole-breast irradiation with and without regional nodal irradiation for both lateralities, comprising 778 patients. ADDI demonstrated significant differences between groups, with left-sided and node-inclusive treatments having worse scores (i.e. higher dose exposure) than right-sided and node-exclusive cases. Additionally, ADDI responded to anatomical features such as planning target volume size, cardiothoracic ratio, central lung distance, and maximal heart distance, highlighting its sensitivity to patient-specific anatomical factors. These results indicate that ADDI effectively captures clinically meaningful variations in dose distribution and provides a unified, objective tool that is compatible with both automated and manual treatment planning workflows.