An in-silico quality assurance study of contouring target volumes in thoracic tumors within a cooperative group setting

Assessing Interobserver Variability in the Delineation of Structures in Radiation Oncology: A Systematic Review

PURPOSE

The delineation of target volumes and organs at risk is the main source of uncertainty in radiation therapy. Numerous interobserver variability (IOV) studies have been conducted, often with unclear methodology and nonstandardized reporting. We aimed to identify the parameters chosen in conducting delineation IOV studies and assess their performances and limits.

METHODS AND MATERIALS

We conducted a systematic literature review to highlight major points of heterogeneity and missing data in IOV studies published between 2018 and 2021. For the main used metrics, we did in silico analyses to assess their limits in specific clinical situations.

RESULTS

All disease sites were represented in the 66 studies examined. Organs at risk were studied independently of tumor site in 29% of reviewed IOV studies. In 65% of studies, statistical analyses were performed. No gold standard (GS; ie, reference) was defined in 36% of studies. A single expert was considered as the GS in 21% of studies, without testing intraobserver variability. All studies reported both absolute and relative indices, including the Dice similarity coefficient (DSC) in 68% and the Hausdorff distance (HD) in 42%. Limitations were shown in silico for small structures when using the DSC and dependence on irregular shapes when using the HD. Variations in DSC values were large between studies, and their thresholds were inconsistent. Most studies (51%) included 1 to 10 cases. The median number of observers or experts was 7 (range, 2-35). The intraclass correlation coefficient was reported in only 9% of cases. Investigating the feasibility of studying IOV in delineation, a minimum of 8 observers with 3 cases, or 11 observers with 2 cases, was required to demonstrate moderate reproducibility.

CONCLUSIONS

Implementation of future IOV studies would benefit from a more standardized methodology: clear definitions of the gold standard and metrics and a justification of the tradeoffs made in the choice of the number of observers and number of delineated cases should be provided.

ProCaLung - Peer review in stage III, mediastinal node-positive, non-small-cell lung cancer: How to benchmark clinical practice of nodal target volume definition and delineation in Belgium☆

BACKGROUND AND PURPOSE

The Quality Assurance project for stage III non-small cell lung cancer radiotherapy ProCaLung performed a multicentric two-step exercise evaluating mediastinal nodal Target Volume Definition and Delineation (TVD) variability and the opportunity for standardization. The TVD variability before and after providing detailed guidelines and the value of qualitative contour reviewing before applying quantitative measures were investigated.

MATERIALS AND METHODS

The case of a patient with stage III NSCLC and involved mediastinal lymph nodes was used as a basis for this study. Twenty-two radiation oncologists from nineteen centers in Belgium and Luxembourg participated in at least one of two phases of the project (before and after introduction of ProCaLung contouring guidelines). The resulting thirty-three mediastinal nodal GTV and CTV contours were then evaluated using a qualitative-before-quantitative (QBQ) approach. First, a qualitative analysis was performed, evaluating adherence to most recent guidelines. From this, a list of observed deviations was created and these were used to evaluate contour conformity. The second analysis was quantitative, using overlap and surface distance measures to compare contours within qualitative groups and between phases. A 'most robust' reference volume for these analyses was created using the STAPLE-algorithm and an averaging method.

RESULTS

Five GTV and seven CTV qualitative groups were identified. Second step contours were more often in higher-conformity groups (p = 0.012 for GTV and p = 0.024 for CTV). Median Residual Mean Square Distances improved from 2.34 mm to 1.36 mm for GTV (p = 0.01) and from 4.53 mm to 1.58 mm for CTV (p < 0.0001). Median Dice coefficients increased from 0.81 to 0.84 for GTV (p = 0.07) and from 0.82 to 0.89 for CTV (p ≤ 0.001). Using HC-contours only to generate references translated in more robust quantitative evaluations.

CONCLUSION

Variability of mediastinal nodal TVD was reduced after providing the ProCaLung consensus guidelines. A qualitative review was essential for providing meaningful quantitative measures.

Optimizing HR-pQCT workflow: a comparison of bias and precision error for quantitative bone analysis

Manual correction of automatically generated contours for high-resolution peripheral quantitative computed tomography can be time consuming and introduces precision error. However, bias related to the automated protocol is unknown. This study provides insight into error bias that is present when using uncorrected contours and inter-operator precision error based on operator training.

INTRODUCTION

High-resolution peripheral quantitative computed tomography workflow includes manually correcting contours generated by the manufacturer's automated protocol. There is interest in minimizing corrections to save time and reduce precision error; however, bias related to the automated protocol is unknown. This study quantifies error bias when contours are uncorrected and identifies the impact of operator training on bias and precision error.

METHODS

Forty-five radii and tibiae scans across a representative range of bone density were analyzed using the automated and manually corrected contours of three operators, with training ranging from beginner to expert, and compared with a "ground truth" to estimate bias. Inter-operator precision was measured across operators.

RESULTS

The tibia had greater error bias than the radius when contours were uncorrected, with compartmental bone mineral densities and cortical microarchitecture having greatest biases, which could have significant implications for interpretation of studies using this skeletal site. Bias and precision error were greatest when contours were corrected by the beginner operator; however, when this operator was removed, bias was no longer present and inter-operator precision was between 0.01 and 3.74% for all parameters except cortical porosity.

CONCLUSION

These findings establish the need for manual correction and provide guidance on operator training needed to maximize workflow efficiency.