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Simulation-free spine palliative radiotherapy enabled by AI-adapted diagnostic CT.

Yiding Han1, Alexander Nicola Hanania1, Zaid Ali Siddiqui1

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An AI method transforms diagnostic CT scans into simulation-equivalent planning CTs, enabling faster spinal palliative radiotherapy without extra scans. This AI-pCT approach reduces errors and improves treatment access.

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Area of Science:

  • Medical Imaging
  • Artificial Intelligence in Radiation Oncology
  • Radiotherapy Planning

Background:

  • Traditional radiotherapy planning requires a simulation CT (sCT), causing treatment delays.
  • Diagnostic CT (dCT) is often available earlier but has geometric and dosimetric inaccuracies for planning.
  • Timely treatment is crucial in spinal palliative care to manage symptoms and prevent neurological decline.

Purpose of the Study:

  • To develop and validate an AI-based method (AI-pCT) for transforming dCT into sCT-equivalent images.
  • To enable a clinically feasible simulation-free workflow for spinal palliative radiotherapy.

Main Methods:

  • Two neural networks were trained on paired dCT-sCT images to correct spine position and body contour.
  • The AI-pCT method was evaluated on internal test and external academic medical center cohorts.
  • Dosimetric accuracy was assessed by comparing dose-volume histogram (DVH) endpoints and RMS error between dCT, AI-pCT, and sCT plans.

Main Results:

  • AI-pCT significantly reduced geometric and dosimetric errors compared to dCT in the safety net cohort (e.g., Dmean error reduced from 2.0% to 0.57%).
  • Physician plan-quality ratings improved from "Acceptable" to "Good-Perfect," and clinical goal achievement increased from 37.5% to 100%.
  • Statistically significant gains were also observed in the external academic medical center cohort.

Conclusions:

  • AI-pCT achieves sCT-level fidelity, enabling simulation-free planning for spinal palliative radiotherapy.
  • This AI-driven approach can potentially reduce treatment delays and improve access to care, especially in resource-limited settings.