Photon-counting detector computing tomography in treatment planning of head-and-neck cancer

<h2>Abstract</h2><h3>Background and purpose</h3> Photon-counting detector computed tomography (PCD-CT) offers several image reconstruction options, e.g. virtual monoenergetic images (VMIs) and relative electron density (RED) images. This study investigated these PCD-CT reconstructions for dose calculation in head-and-neck cancer (HNC) patients. <h3>Materials and methods</h3> 10 HNC patients referred to radiotherapy were scanned with PCD-CT. The same contouring and therapy strategy was followed as in the patients' clinical treatment, optimized on an energy-integrated-detector CT (EID-CT). 18 volumetric arc therapy treatment plans (6 MV photons) were optimized on RED images and recalculated on 70 keV VMI (VMI70), using the same amount of monitor units. While RED images did not require scanner-specific calibration, the conversion from CT number to RED for VMI70 was calibrated using a phantom with tissue-equivalent inserts with known RED. To assess the clinical impact of using RED maps with vendor-provided calibration, one plan per patient was recalculated using bulk material overrides. Plan quality was evaluated by evaluating dose-volume metrics, such as the dose to 98% of planning target volume, and compared between RED, VMI70, and EID-CT. <h3>Results</h3> All plans optimized on RED images fulfilled the clinical goals. Dose-volume metrics differed by <3% between RED and VMI70 and <5% between RED and EID-CT. RED differed by differed by <4% from bulk density override (<1% when the target did not overlap with air volumes). <h3>Conclusions</h3> Treatment planning can be accurately performed on PCD-CT images of HNC cases, using either VMI (after CT-number-to-RED conversion) or RED images (without scanner-specific calibration)