Intra-fraction setup variability: IR optical localization vs. X-ray imaging in a hypofractionated patient population

<p>Abstract</p> <p>Background</p> <p>The purpose of this study is to investigate intra-fraction setup variability in hypo-fractionated cranial and body radiotherapy; this is achieved by means of integrated infrared optical localization and stereoscopic kV X-ray imaging.</p> <p>Method and Materials</p> <p>We analyzed data coming from 87 patients treated with hypo-fractionated radiotherapy at cranial and extra-cranial sites. Patient setup was realized through the ExacTrac X-ray 6D system (BrainLAB, Germany), consisting of 2 infrared TV cameras for external fiducial localization and X-ray imaging in double projection for image registration. Before irradiation, patients were pre-aligned relying on optical marker localization. Patient position was refined through the automatic matching of X-ray images to digitally reconstructed radiographs, providing 6 corrective parameters that were automatically applied using a robotic couch. Infrared patient localization and X-ray imaging were performed at the end of treatment, thus providing independent measures of intra-fraction motion.</p> <p>Results</p> <p>According to optical measurements, the size of intra-fraction motion was (<it>median ± quartile</it>) 0.3 ± 0.3 mm, 0.6 ± 0.6 mm, 0.7 ± 0.6 mm for cranial, abdominal and lung patients, respectively. X-ray image registration estimated larger intra-fraction motion, equal to 0.9 ± 0.8 mm, 1.3 ± 1.2 mm, 1.8 ± 2.2 mm, correspondingly.</p> <p>Conclusion</p> <p>Optical tracking highlighted negligible intra-fraction motion at both cranial and extra-cranial sites. The larger motion detected by X-ray image registration showed significant inter-patient variability, in contrast to infrared optical tracking measurement. Infrared localization is put forward as the optimal strategy to monitor intra-fraction motion, featuring robustness, flexibility and less invasivity with respect to X-ray based techniques.</p

Role of quantitative computed tomography texture analysis in the prediction of adherent perinephric fat

International audienceObjective - To assess the performance of computed tomography (CT) texture analysis to predict the presence of adherent perinephric fat (APF). Materials and methods - Seventy patients with small renal tumors treated with robot-assisted partial nephrectomy were included. Patients were divided into two groups according to the presence of APF. We extracted 15 image features from unenhanced CT and contrast-enhanced CT corresponding to first-order and second-order Haralick textural features. Predictors of APF were evaluated by univariable and multivariable analysis. Receiver operating characteristic (ROC) analysis was performed and the area under the ROC curve (AUC) to predict APF was calculated for the independent predictors. Results - APF was observed in 26 patients (37%). We identified entropy (p = 0.01), sum entropy (p = 0.02) and difference entropy (p = 0.05) as significant independent predictors of APF. In the portal phase, we identified correlation (p = 0.03), inverse difference moment (p = 0.01), sum entropy (p = 0.02), entropy (p = 0.01), difference variance (p = 0.04) and difference entropy (p = 0.02) as significant independent predictors of APF. Combining these parameters yielded to an ROC-AUC of 0.82 (95% CI 0.65-0.86). Conclusion - Results from this preliminary study suggest that CT texture analysis might be a promising quantitative imaging tool that helps urologist to identify APF