Improved human observer performance in digital reconstructed radiograph verification in head and neck cancer radiotherapy

• Published in: International journal for computer assisted radiology and surgery 2015-10, Vol.10 (10), p.1667-1673
• Main Authors: Sturgeon, Jared D., Cox, John A., Mayo, Lauren L., Gunn, G. Brandon, Zhang, Lifei, Balter, Peter A., Dong, Lei, Awan, Musaddiq, Kocak-Uzel, Esengul, Mohamed, Abdallah Sherif Radwan, Rosenthal, David I., Fuller, Clifton David
• Format: Article
• Language: English
• Subjects: Computer Imaging; Computer Science; Head and Neck Neoplasms - diagnostic imaging; Head and Neck Neoplasms - radiotherapy; Health Informatics; Humans; Imaging; Medicine; Medicine & Public Health; Original Article; Pattern Recognition and Graphics; Radiographic Image Interpretation, Computer-Assisted; Radiology; Radiotherapy Planning, Computer-Assisted - methods; Surgery; Tomography, X-Ray Computed; Vision
• ISSN: 1861-6410; 1861-6429
• DOI: 10.1007/s11548-014-1127-4

Purpose    Digitally reconstructed radiographs (DRRs) are routinely used as an a priori reference for setup correction in radiotherapy. The spatial resolution of DRRs may be improved to reduce setup error in fractionated radiotherapy treatment protocols. The influence of finer CT slice thickness reconstruction (STR) and resultant increased resolution DRRs on physician setup accuracy was prospectively evaluated. Methods    Four head and neck patient CT-simulation images were acquired and used to create DRR cohorts by varying STRs at 0.5, 1, 2, 2.5, and 3 mm. DRRs were displaced relative to a fixed isocenter using 0–5 mm random shifts in the three cardinal axes. Physician observers reviewed DRRs of varying STRs and displacements and then aligned reference and test DRRs replicating daily KV imaging workflow. A total of 1,064 images were reviewed by four blinded physicians. Observer errors were analyzed using nonparametric statistics (Friedman’s test) to determine whether STR cohorts had detectably different displacement profiles. Post hoc bootstrap resampling was applied to evaluate potential generalizability. Results    The observer-based trial revealed a statistically significant difference between cohort means for observer displacement vector error ( p = 0.02 ) and for Z -axis ( p < 0.01 ) . Bootstrap analysis suggests a 15 % gain in isocenter translational setup error with reduction of STR from 3 mm to ≤ 2 mm, though interobserver variance was a larger feature than STR-associated measurement variance. Conclusions    Higher resolution DRRs generated using finer CT scan STR resulted in improved observer performance at shift detection and could decrease operator-dependent geometric error. Ideally, CT STRs ≤ 2 mm should be utilized for DRR generation in the head and neck.