Inter-observer and intra-observer reliability for lung cancer target volume delineation in the 4D-CT era

Louie, Alexander V.; Rodrigues, George; Olsthoorn, Jason; Palma, David A.; Yu, Edward; Yaremko, Brian; Ahmad, Belal; Aivas, I.; Gaede, Stewart

doi:10.1016/j.radonc.2009.12.028

Cited by 98 publications

(52 citation statements)

References 27 publications

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“…At least 25% of the high-risk volume at the bladder neck anastomosis and the retro-vesical space was excluded in 11 out of 38 CTVs [13]. Our study found that intra-observer variability was a smaller source of TVD error than inter-observer variability, consistent with the literature [3,17]. Wiltshire et al .…”

Section: Discussionsupporting

confidence: 90%

Technology assessment of automated atlas based segmentation in prostate bed contouring

et al. 2011

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BackgroundProstate bed (PB) contouring is time consuming and associated with inter-observer variability. We evaluated an automated atlas-based segmentation (AABS) engine in its potential to reduce contouring time and inter-observer variability.MethodsAn atlas builder (AB) manually contoured the prostate bed, rectum, left femoral head (LFH), right femoral head (RFH), bladder, and penile bulb of 75 post-prostatectomy cases to create an atlas according to the recent RTOG guidelines. 5 other Radiation Oncologists (RO) and the AABS contoured 5 new cases. A STAPLE contour for each of the 5 patients was generated. All contours were anonymized and sent back to the 5 RO to be edited as clinically necessary. All contouring times were recorded. The dice similarity coefficient (DSC) was used to evaluate the unedited- and edited- AABS and inter-observer variability among the RO. Descriptive statistics, paired t-tests and a Pearson correlation were performed. ANOVA analysis using logit transformations of DSC values was calculated to assess inter-observer variability.ResultsThe mean time for manual contours and AABS was 17.5- and 14.1 minutes respectively (p = 0.003). The DSC results (mean, SD) for the comparison of the unedited-AABS versus STAPLE contours for the PB (0.48, 0.17), bladder (0.67, 0.19), LFH (0.92, 0.01), RFH (0.92, 0.01), penile bulb (0.33, 0.25) and rectum (0.59, 0.11). The DSC results (mean, SD) for the comparison of the edited-AABS versus STAPLE contours for the PB (0.67, 0.19), bladder (0.88, 0.13), LFH (0.93, 0.01), RFH (0.92, 0.01), penile bulb (0.54, 0.21) and rectum (0.78, 0.12). The DSC results (mean, SD) for the comparison of the edited-AABS versus the expert panel for the PB (0.47, 0.16), bladder (0.67, 0.18), LFH (0.83, 0.18), RFH (0.83, 0.17), penile bulb (0.31, 0.23) and rectum (0.58, 0.09). The DSC results (mean, SD) for the comparison of the STAPLE contours and the 5 RO are PB (0.78, 0.15), bladder (0.96, 0.02), left femoral head (0.87, 0.19), right femoral head (0.87, 0.19), penile bulb (0.70, 0.17) and the rectum (0.89, 0.06). The ANOVA analysis suggests inter-observer variability among at least one of the 5 RO (p value = 0.002).ConclusionThe AABS tool results in a time savings, and when used to generate auto-contours for the femoral heads, bladder and rectum had superior to good spatial overlap. However, the generated auto-contours for the prostate bed and penile bulb need improvement.

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Section: Discussionsupporting

confidence: 90%

Technology assessment of automated atlas based segmentation in prostate bed contouring

et al. 2011

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“…It should be noted that intra-observer target volume delineation error might reduce the accuracy of GTVs delineated on the 3DCT and 4DCT images [26], though all the delineation was performed by an observer. Manual delineating on each phase of 4DCT would consume lots of time.…”

Section: Discussionmentioning

confidence: 99%

Geometrical differences in gross target volumes between 3DCT and 4DCT imaging in radiotherapy for non-small-cell lung cancer

Zhang

et al. 2013

Journal of Radiation Research

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The aim of this study was to explore the characteristic of 3DCT scanning phases and estimate the comparative amount of respiration motion information included in 3DCT and 4DCT by comparing the volumetric and positional difference between the volumes from 3DCT and 4DCT for the radiotherapy of non-small-cell lung cancer (NSCLC). A total of 28 patients with NSCLC sequentially underwent 3DCT and 4DCT simulation scans of the thorax during free breathing. The 4DCT images with respiratory signal data were reconstructed and sorted into 10 phases throughout a respiratory cycle. GTV-3D from 3DCT, GTV-0%, GTV-20%, GTV-50% and GTV-70% from end-inspiration, mid-expiration, end-expiration and mid-inspiration of 4DCT, and the internal GTV (IGTV-10) from the fused phase of 4DCT were delineated based on the 50% phase image, respectively. The differences in the position, size, matching index (MI) and degree of inclusion (DI) for different volumes were evaluated. The variation in the centroid shifts of GTV-0% and GTV-3D, GTV-20% and GTV-3D, GTV-50% and GTV-3D, and GTV-90% and GTV-3D in the 3D direction was not significant (P = 0.990). The size ratios of GTV-0%, GTV-20%, GTV-50%, GTV-70% and IGTV-10 to GTV-3D were 0.94 ± 0.18, 0.95 ± 0.18, 0.98 ± 0.15, 1.00 ± 0.18 and 1.60 ± 0.55, respectively. DIs of GTV-3D in IGTV-10, and IGTV-10 in GTV-3D were 0.88 ± 0.14 and 0.59 ± 0.16 (P < 0.001). The 3DCT scanning phases are irregular. The CTV-to-ITV expansion should be isotropic when defining the ITV on the 3DCT. The internal GTV derived from 4DCT cannot completely include the GTV from 3DCT. An additional margin may be required when defining the ITV-based 4DCT.

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“…The process of target and normal tissue delineation, known as segmentation or contouring, is subject to significant levels of inter- and intra-observer variability in both the accuracy and reproducibility of structures [2-8]. Accurate delineation of target volumes is critical to ensure adequate coverage and reduce the risk of local recurrence[4].…”

Section: Introductionmentioning

confidence: 99%

Creation of RTOG compliant patient CT-atlases for automated atlas based contouring of local regional breast and high-risk prostate cancers

et al. 2013

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BackgroundIncreasing use of IMRT to treat breast and prostate cancers at high risk of regional nodal spread relies on accurate contouring of targets and organs at risk, which is subject to significant inter- and intra-observer variability. This study sought to evaluate the performance of an atlas based deformable registration algorithm to create multi-patient CT based atlases for automated contouring.MethodsBreast and prostate multi-patient CT atlases (n = 50 and 14 respectively) were constructed to be consistent with RTOG consensus contouring guidelines. A commercially available software algorithm was evaluated by comparison of atlas-predicted contours against manual contours using Dice Similarity coefficients.ResultsHigh levels of agreement were demonstrated for prediction of OAR contours of lungs, heart, femurs, and minor editing required for the CTV breast/chest wall. CTVs generated for axillary nodes, supraclavicular nodes, prostate, and pelvic nodes demonstrated modest agreement. Small and highly variable structures, such as internal mammary nodes, lumpectomy cavity, rectum, penile bulb, and seminal vesicles had poor agreement.ConclusionsA method to construct and validate performance of CT-based multi-patient atlases for automated atlas based auto-contouring has been demonstrated, and can be adopted for clinical use in planning of local regional breast and high-risk prostate radiotherapy.

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Inter-observer and intra-observer reliability for lung cancer target volume delineation in the 4D-CT era

Cited by 98 publications

References 27 publications

Technology assessment of automated atlas based segmentation in prostate bed contouring

Technology assessment of automated atlas based segmentation in prostate bed contouring

Geometrical differences in gross target volumes between 3DCT and 4DCT imaging in radiotherapy for non-small-cell lung cancer

Creation of RTOG compliant patient CT-atlases for automated atlas based contouring of local regional breast and high-risk prostate cancers

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