# Development and Evaluation of Knowledge-Based Treatment Plans for Chest Wall and Regional Lymph Node Irradiation

**Authors:** Panagiota Galanakou, Nesrin Dogan, Stuart E Samuels, Maria De La Luz De Ornelas, Robert Kaderka

PMC · DOI: 10.7759/cureus.100934 · Cureus · 2026-01-06

## TL;DR

This study develops and evaluates knowledge-based planning models for chest wall and lymph node radiotherapy, showing they can produce plans as good or better than manual ones.

## Contribution

The study introduces laterality-specific and combined KBP models for VMAT chest wall and nodal irradiation, which are validated against clinical plans.

## Key findings

- Left-sided KBP plans reduced doses to the esophagus and thyroid while maintaining target coverage.
- Right-sided KBP plans improved thyroid and heart dose sparing without compromising nodal coverage.
- Physician review showed preference for KBP plans in most cases, with dosimetric improvements observed.

## Abstract

Background

Knowledge-based planning (KBP) improves radiotherapy efficiency and consistency by using machine learning models trained on prior high-quality plans. Most breast KBP studies focus on whole- or partial-breast treatments without nodal coverage, and limited attention has been given to laterality-specific chest wall volumetric modulated arc therapy (VMAT) plans. This study develops left-sided, right-sided, and combined KBP models for chest wall and regional nodal irradiation and compares their performance with clinical plans.

Materials and methods

KBP models were created using 47 left-sided and 44 right-sided chest wall patients involving regional lymph nodes. A combined model incorporating all cases was also developed. Optimization objectives were iteratively refined using model-predicted, manual, and normal tissue objectives (NTOs). Model performance was evaluated using the coefficient of determination (R²), chi-square (χ²), and mean squared error (MSE). For validation, 10 left-sided, 10 right-sided, and 20 combined KBP plans were compared with their corresponding clinical plans using paired t-tests (p < 0.05). Dosimetric endpoints included target coverage, conformity index, homogeneity index, organ-at-risk (OAR) dose-volume metrics, and delivery efficiency factor (intensity modulated radiation therapy factor). KBP plans were generated without planner intervention, with additional optimization using a monitor unit objective when required. All plans underwent blinded physician review for clinical acceptability and preference.

Results

Left-sided KBP plans significantly reduced mean doses to the esophagus (-499 ± 147 cGy, p < 0.05) and thyroid (-296 ± 96 cGy, p < 0.05), with small increases in spinal cord maximum dose (20 ± 82 cGy, p > 0.05) and V15% of the contralateral lung (10.1 ± 1.9, p < 0.05). Right-sided KBP plans reduced mean doses to the thyroid (-220 ± 86 cGy, p < 0.05) and heart (-46.1 ± 9.3 cGy, p < 0.05), with minimal impact on coverage of the planning target volume of the internal mammary nodes (PTV_IMN). The combined model demonstrated similar dosimetric patterns. KBP plans improved conformity in six of 10 cases and homogeneity in 50% of cases, achieving higher dose values corresponding to 98% of the prescription dose (D98%) in 60-65% of cases for laterality-specific and combined KBP models, respectively, while maintaining the maximum dose (Dmax) and the dose received by 105% of the prescription dose (D105%) within constraints. Delivery efficiency remained comparable. A blinded physician review favored KBP in the majority of cases, with equivalence noted in others.

Conclusions

Laterality-specific and combined KBP models for VMAT chest wall and nodal irradiation generate plans that are dosimetrically comparable or superior to manual plans, providing consistent target coverage and improved or maintained OAR sparing. KBP offers a reproducible and efficient strategy for complex breast and chest wall cases, supports workflow standardization, and requires only minimal refinement in selected situations.

## Linked entities

- **Diseases:** breast cancer (MONDO:0004989)

## Full-text entities

- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

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## References

23 references — full list in the complete paper: https://tomesphere.com/paper/PMC12875416/full.md

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Source: https://tomesphere.com/paper/PMC12875416