Dataset Information

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

ABSTRACT: 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.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.The observer-based trial revealed a statistically significant difference between cohort means for observer displacement vector error ([Formula: see text]) and for [Formula: see text]-axis [Formula: see text]. Bootstrap analysis suggests a 15% gain in isocenter translational setup error with reduction of STR from 3 mm to [Formula: see text]2 mm, though interobserver variance was a larger feature than STR-associated measurement variance.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 [Formula: see text]2 mm should be utilized for DRR generation in the head and neck.

SUBMITTER: Sturgeon JD

PROVIDER: S-EPMC4801514 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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

Sturgeon Jared D JD Cox John A JA Mayo Lauren L LL Gunn G Brandon GB Zhang Lifei L Balter Peter A PA Dong Lei L Awan Musaddiq M Kocak-Uzel Esengul E Mohamed Abdallah Sherif Radwan AS Rosenthal David I DI Fuller Clifton David CD

International journal of computer assisted radiology and surgery 20141205 10

<h4>Purpose</h4>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.<h4>Methods</h4>Four head and neck patient CT-simulation images were acquired and ...[more]

PMID: 25477277

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Project description:No clear criteria have yet been established to guide decision-making for patient selection and the optimal timing of adaptive radiotherapy (ART) based on image-guided radiotherapy (IGRT). We have developed a novel protocol-the Best for Adaptive Radiotherapy (B-ART) protocol-to guide patient selection for ART. The aim of the present study is to describe this protocol, to evaluate its validity in patients with head and neck (HN) cancer, and to identify the anatomical and clinical predictors of the need for replanning. We retrospectively evaluated 82 patients with HN cancer who underwent helical tomotherapy (HT) and subsequently required replanning due to soft tissue changes upon daily MVCT. Under the proposed criteria, patients with anatomical changes >3 mm on three to four consecutive scans are candidates for ART. We compared the volumes on the initial CT scan (iCT) and the replanning CT (rCT) scan for the clinical target volumes (CTV1, referring to primary tumor or tumor bed and CTV2, metastatic lymph nodes) and for the parotid glands (PG) and body contour (B-body). The patients were stratified by primary tumor localization, clinical stage, and treatment scheme. The main reasons for replanning were: (1) a planning target volume (PTV) outside the body contour (n = 70; 85.4%), (2) PG shrinkage (n = 69; 84.1%), (3) B-body deviations (n = 69; 84.1%), and (4) setup deviations (n = 40; 48.8%). The replanning decision was made, on average, during the fourth week of treatment (n = 47; 57.3%). The mean reductions in the size of the right and left PG volumes were 6.31 cc (20.9%) and 5.98 cc (20.5%), respectively (p < 0.001). The reduction in PG volume was ≥30% in 30 patients (36.6%). The volume reduction in all of the anatomical structures was statistically significant. Four variables-advanced stage disease (T3-T4), chemoradiation, increased weight loss, and oropharyngeal localization-were significantly associated with the need for ART. The B-ART protocol provides clear criteria to eliminate random errors, and to allow for an early response to relevant changes in target volumes.

Project description:To develop an algorithm for computing realistic digitally reconstructed radiographs (DRRs) that match real cone-beam CT (CBCT) projections with no artificial adjustments.The authors used measured attenuation data from cone-beam CT projection radiographs of different materials to obtain a function to convert CT number to linear attenuation coefficient (LAC). The effects of scatter, beam hardening, and veiling glare were first removed from the attenuation data. Using this conversion function the authors calculated the line integral of LAC through a CT along rays connecting the radiation source and detector pixels with a ray-tracing algorithm, producing raw DRRs. The effects of scatter, beam hardening, and veiling glare were then included in the DRRs through postprocessing.The authors compared actual CBCT projections to DRRs produced with all corrections (scatter, beam hardening, and veiling glare) and to uncorrected DRRs. Algorithm accuracy was assessed through visual comparison of projections and DRRs, pixel intensity comparisons, intensity histogram comparisons, and correlation plots of DRR-to-projection pixel intensities. In general, the fully corrected algorithm provided a small but nontrivial improvement in accuracy over the uncorrected algorithm. The authors also investigated both measurement- and computation-based methods for determining the beam hardening correction, and found the computation-based method to be superior, as it accounted for nonuniform bowtie filter thickness. The authors benchmarked the algorithm for speed and found that it produced DRRs in about 0.35 s for full detector and CT resolution at a ray step-size of 0.5 mm.The authors have demonstrated a DRR algorithm calculated from first principles that accounts for scatter, beam hardening, and veiling glare in order to produce accurate DRRs. The algorithm is computationally efficient, making it a good candidate for iterative CT reconstruction techniques that require a data fidelity term based on the matching of DRRs and projections.

Dataset Information

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

Publications

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

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