How to Apply 3D3 Prediction? A Novel Mathematical Model to Generate Pareto Optimal Clinical Applicable IMRT Treatment Plan On the Foundation of Dose Prediction and Prescription

TL;DR

This paper introduces a novel mathematical model called QuadLin that converts 3D dose predictions into clinically applicable IMRT treatment plans, significantly improving clinical indicators over previous methods.

Contribution

The study presents the QuadLin model, a new approach integrating prescribed and predicted doses for better IMRT planning, validated on a large patient dataset.

Findings

Clinical indicators improved by over 21% compared to predicted doses.

The model outperformed previous research in dose quality.

570 problems were solved demonstrating the model's effectiveness.

Abstract

In this paper knowledge based planning has been revolutionized via a novel mathematical model which converts three dimensional dose distribution (3D3) prediction to a clinical utilizable IMRT treatment plan. Presented model has benefited from both prescribed dose as well as predicted dose and its objective function includes both quadratic and linear phrases, so it was called QuadLin model. The model has been run on the data of 30 patients with head and neck cancer randomly selected from the Open KBP dataset. For each patient, there are 19 sets of dose prediction data in this database. Therefore, a total of 570 problems have been solved in the CVX framework and the results have been evaluated by two plan quality approaches: 1- DVH points differences, and 2- satisfied clinical criteria. The results of the current study indicate a strong significant improvement in clinical indicators compared to the reference plan of the dataset, 3D3 predictions, as well as the results of previous researches. Accordingly, on average for 570 problems and total ROIs, clinical indicators have improved by more than 21% and 15% compared to the predicted dose and previous research, respectively.