HyperSight CBCT image quality and metal artifact reduction for adaptive head and neck radiotherapy: Results from a prospective clinical trial

HyperSight CBCT图像质量和金属伪影减少在自适应头颈部放射治疗中的应用:一项前瞻性临床试验的结果

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Abstract

BACKGROUND: Accurate Hounsfield units (HU) are critical for dose calculation and anatomical visualization, but are often affected by dental artifacts in head and neck (H&N) cancer patients. The HyperSight cone-beam computed tomography (CBCT) platform provides improved image quality over previous CBCT platforms and offers metal artifact reduction (iCBCT MAR) reconstruction. PURPOSE: This study evaluates the quality of HyperSight CBCT images compared to current clinical standards: TrueBeam CBCT for image guidance and fan-beam CT (FBCT) from a CT simulator for treatment planning, using images captured during H&N cancer treatment. METHODS: Images for 30 H&N cancer patients were acquired on a HyperSight CBCT, conventional TrueBeam and FBCT, with 24 patients exhibiting metal dental artifacts. The HyperSight images were reconstructed using iCBCT MAR and iterative (iCBCT Acuros) algorithms. The four image sets were rigidly registered and compared using the artifact index (AI) measured in the oral cavity and the percentile range (PR) measured in the oral cavity, brain, brainstem and eyes to assess image non-uniformity. The HU accuracy was calculated relative to FBCT (baseline) for soft tissues (oral cavity, brainstem, submandibular and parotid glands), and bone (mandible). The contrast relative to baseline was evaluated between the oral cavity and nearby structures. Image-based metrics were computed relative to FBCT including structural similarity index measure (SSIM), mean-square error (MSE) and peak signal-to-noise ratio (PSNR). RESULTS: The HyperSight iCBCT MAR images showed a significant reduction in AI values compared to the other images (p < 0.0004), but higher PR values indicating decreased HU uniformity compared to HyperSight iCBCT Acuros and FBCT (p < 0.0002). The soft-tissue HU and contrast values were significantly closer to baseline in both HyperSight images compared to TrueBeam (HU: p < 0.001, contrast: p < 0.001). For soft-tissue the HU mean absolute deviation (MAD) from baseline was 16 ± 10 HU for HyperSight iCBCT Acuros, 15 ± 10 HU for HyperSight iCBCT MAR, and 35 ± 22 HU for TrueBeam. For bone, the HU MAD from baseline was 153 ± 233 HU, 185 ± 268 HU, and 214 ± 212 HU, respectively. The HyperSight iCBCT Acuros algorithm achieved significantly superior SSIM, MSE, and PSNR metrics compared to TrueBeam and HyperSight iCBCT MAR in regions with large amounts of bone and air. CONCLUSIONS: HyperSight iCBCT MAR significantly reduced artifacts compared to HyperSight iCBCT Acuros, TrueBeam and FBCT, making it particularly beneficial for patients with metal implants. Both HyperSight reconstructions demonstrated improved soft-tissue HU accuracy and contrast compared to TrueBeam, however the iCBCT Acuros algorithm may be preferred when metal-induced artifacts are not a concern. These results support the suitability of HyperSight images in adaptive treatment workflows requiring accurate image quality, even with severe metal artifacts.

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