Inter-observer variability of organ contouring for preclinical studies with cone beam Computed Tomography imaging.
Inter-observer variability of organ contouring for preclinical studies with cone beam Computed Tomography imaging.
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DOI:
10.1016/j.phro.2022.01.002
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发表时间:
2022-01
影响因子:
--
通讯作者:
Verhaegen F
中科院分区:
文献类型:
--
作者:
Lappas G;Staut N;Lieuwes NG;Biemans R;Wolfs CJA;van Hoof SJ;Dubois LJ;Verhaegen F
In preclinical radiation studies, there is great interest in quantifying the radiation response of healthy tissues. Manual contouring has significant impact on the treatment-planning because of variation introduced by human interpretation. This results in inconsistencies when assessing normal tissue volumes. Evaluation of these discrepancies can provide a better understanding on the limitations of the current preclinical radiation workflow. In the present work, interobserver variability (IOV) in manual contouring of rodent normal tissues on cone-beam Computed Tomography, in head and thorax regions was evaluated. Two animal technicians performed manually (assisted) contouring of normal tissues located within the thorax and head regions of rodents, 20 cases per body site. Mean surface distance (MSD), displacement of center of mass (ΔCoM), DICE similarity coefficient (DSC) and the 95th percentile Hausdorff distance (HD95) were calculated between the contours of the two observers to evaluate the IOV. For the thorax organs, right lung had the lowest IOV (ΔCoM: 0.08 ± 0.04 mm, DSC: 0.96 ± 0.01, MSD:0.07 ± 0.01 mm, HD95:0.20 ± 0.03 mm) while spinal cord, the highest IOV (ΔCoM:0.5 ± 0.3 mm, DSC:0.81 ± 0.05, MSD:0.14 ± 0.03 mm, HD95:0.8 ± 0.2 mm). Regarding head organs, right eye demonstrated the lowest IOV (ΔCoM:0.12 ± 0.08 mm, DSC: 0.93 ± 0.02, MSD: 0.15 ± 0.04 mm, HD95: 0.29 ± 0.07 mm) while complete brain, the highest IOV (ΔCoM: 0.2 ± 0.1 mm, DSC: 0.94 ± 0.02, MSD: 0.3 ± 0.1 mm, HD95: 0.5 ± 0.1 mm). Our findings reveal small IOV, within the sub-mm range, for thorax and head normal tissues in rodents. The set of contours can serve as a basis for developing an automated delineation method for e.g., treatment planning.
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DOI:
10.1186/s13014-020-01677-2
发表时间:
2021-06-28
期刊:
Radiation oncology (London, England)
影响因子:
--
作者:
van der Veen J;Gulyban A;Willems S;Maes F;Nuyts S
通讯作者:
Nuyts S
影响因子:
--
作者:
Vaassen F;Hazelaar C;Vaniqui A;Gooding M;van der Heyden B;Canters R;van Elmpt W
通讯作者:
van Elmpt W
影响因子:
4.3
作者:
Vande Velde G;Poelmans J;De Langhe E;Hillen A;Vanoirbeek J;Himmelreich U;Lories RJ
通讯作者:
Lories RJ
影响因子:
16.6
作者:
Schoppe O;Pan C;Coronel J;Mai H;Rong Z;Todorov MI;Müskes A;Navarro F;Li H;Ertürk A;Menze BH
通讯作者:
Menze BH
影响因子:
2
作者:
Tillner, Falk;Thute, Prasad;Enghardt, Wolfgang
通讯作者:
Enghardt, Wolfgang