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• W2011972406 abstract "To compare lung automatic delineation (AD) of the software X version X and AD manually corrected for major deviations known as Semi-Automatic Delineation (SAD) with the gold standard “slice-to-slice” Manual Delineation (MD) per RTOG recommendations. To assess time spent, CT chest images of 20 lung cancer patients were used. Each lung was contoured using AD, SAD and MD strategies. Total contouring time was recorded according to strategy and compared using the non-parametric Wilcoxon test with Holm-Bonferroni correction. To describe the quality of design, the following parameters were used: 1) Volumetric Variation (VV); 2) Similarity Coefficient (SC); 3) Sensitivity (S); 4) Inclusion Index (II). To assess the impact of delineation variation on the dose-volume histogram (DVH) of various thoracic tumors, CT chest images of 3D-conformal plans of 40 patients were used (lung cancer [20], breast cancer [10], esophageal cancer [10]). We analyzed the following pulmonary DVH parameters: Mean Lung Dose (MLD), V5, V10, V20, V30 and V40. Prescribed dose was the same among all tumors for each site (breast: 50 Gy; esophagus: 50.4 Gy; lung: 60 Gy) We used the intraclass correlation coefficient to demonstrate the reproducibility of the methods. The mean values for AD, SAD and MD spending time were 62.85 (SD = 10.48), 168.45 (SD = 63.28) and 706.00 (SD = 126.77) seconds (p < 0.001), respectively. The mean VV was 0.0874% for AD (SD = 0.8903) and -1.0657% for SAD (SD = 0.6265) in comparison to MD. The mean SC was 0.9895 for AD (SD = 0.0045) and 0.9948 for SAD (SD = 0.0042). The mean S was 0.9891 (SD = 0.0063) for AD and 0.9895 (SD = 0.0071) for SAD. The mean II was 0.9900 (SD = 0.0063) for AD and 1 (SD = 0.0022) for SAD. For organ volumes, the intraclass correlation coefficient was 0.999; CI 95% = 0.999 to 1, p < 0.0001). DVH differences are expressed in the table below:Scientific Abstract 2949; TableMean DVH parameters deviation (%) in relation to MD according to primaryBreast tumorLung tumorEsophageal tumorADSADADSADADSADMLD1.28 ±1.430.53 ±0.381.04 ±0.890.44 ±0.291.22 ±0.650.29 ±0.26V51.13 ±0.951.13 ±0.950.65 ±0.470.83 ±0.570.67 ±0.430.57 ±0.37V101.09 ±0.741.09 ±0.740.90 ±0.720.73 ±0.480.66 ±0.500.67 ±0.47V201.32 ±0.901.31 ±0.911.22 ±0.950.98 ±1.040.88 ±0.530.87 ±0.57 Open table in a new tab Our data demonstrate that lung AD or SAD using software X version X is accurate, precise, and efficient compared to MD. The mean deviation in DVH parameters is relatively small for the aforementioned thoracic tumors. In a busy clinic with approximately 10 new cases per day requiring lung contours, ten minutes per case can be saved in each one, which amounts to almost two hours of workload." @default.
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• W2011972406 date "2014-09-01" @default.
• W2011972406 modified "2023-09-26" @default.
• W2011972406 title "The Reliability of Automatic Segmentation for Lung Volumes in Breast, Lung, and Esophageal Cancers" @default.
• W2011972406 doi "https://doi.org/10.1016/j.ijrobp.2014.05.1757" @default.
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