Geometric contour variation in clinical target volume of axillary lymph nodes in breast cancer radiotherapy: an AIRO multi-institutional study

Abstract

Objectives: To determine interobserver variability in axillary nodal contouring in breast cancer (BC) radiotherapy (RT) by comparing the clinical target volume of participating single centres (SC-CTV) with a gold-standard CTV (GS-CTV). Methods: The GS-CTV of 3 patients (P1, P2, P3) with increasing complexity was created in DICOM format from the median contour of axillary CTVs drawn by BC experts, validated using the simultaneous truth and performance level estimation and peer-reviewed. GS-CTVs were compared with the correspondent SC-CTVs drawn by radiation oncologists, using validated metrics and a total score (TS) integrating all of them. Results: Eighteen RT centres participated in the study. Comparative analyses revealed that, on average, the SC-CTVs were smaller than GS-CTV for P1 and P2 (by −29.25% and −27.83%, respectively) and larger for P3 (by +12.53%). The mean Jaccard index was greater for P1 and P2 compared to P3, but the overlap extent value was around 0.50 or less. Regarding nodal levels, L4 showed the highest concordance with the GS. In the intra patient comparison, L2 and L3 achieved lower TS than L4. Nodal levels showed discrepancy with GS which was not statistically significant for P1, and negligible for P2, while P3 had the worst agreement. DICE Similarity Coefficient did not exceed the minimum threshold for agreement of 0.70 in all the measurements. Conclusions: Substantial differences were observed between SC- and GS-CTV, especially for P3 with altered arm set-up. L2 and L3 were the most critical levels. The study highlighted these key points to address. Advances in knowledge The present study compares, by means of validated geometric indexes, manual segmentationsof axillary lymph nodes in breast cancer from different observers and different institutionsmade on radiotherapy planning computed tomography images. Assessing such variability is ofparamount importance, as geometric uncertainties might lead to incorrect dosimetry andcompromise oncological outcome.

Off‐isocentric VMAT technique for breast cancer: Effective dose reduction to organs at risk and its applicability based on patient anatomy

“…A broad spectrum of breast‐planning studies yields inconsistent conclusions across different publications due to various factors. These include differing clinical goals, planning experience of the physicist, the physician's experience, the use of DIBH, 8,11,29 anatomical diversity from racial groups of patients, 13,30 and the type of guidance employed during the delineation of PTV and OARs 31,32 . By sorting and selecting patients for studies based on clinical parameters (like lymph node involvement), we can inadvertently introduce additional errors and distortions into the results.…”

Impact of inter-observer variability on first axillary level dosimetry in breast cancer radiotherapy: An AIRO multi-institutional study

“…The corresponding gold standard (GS) contours for each axillary level of the three patients were created as shown in a previous paper. 14 The SC-CTV including L2-L4 was replaced by the corresponding GS-CTV and then expanded to form the GS-PTV using the same margins as those used by each RT centre. 15 Likewise, to evaluate the incidental dose to the GS-L1, the SC-L1 contour was replaced with the GS-L1.…”

“…11 In the locoregional RT, L1 is expected to receive a certain amount of the dose from the contribution of the breast/chest wall and the infra/supraclavicular fields, especially when this latter includes the whole or part of the second axillary level (L2). 12 This study aimed to quantify the unintended dose to L1 in the setting of increased anatomical complexity in intensity modulated radiotherapy (IMRT)-based locoregional treatments, using a multicentric platform, which served as basis for three previous investigations, [13][14][15] with the endorsement of the Italian Association of Radiotherapy and Clinical Oncology (AIRO).…”

Comparison of the output of a deep learning segmentation model for locoregional breast cancer radiotherapy trained on 2 different datasets

“…Besides, visual inspection was performed to check for abnormalities and investigate the origin of found differences. In addition, the values for DSC and 95% HD were compared with inter-observer variations (IOV) which are present for manual delineations of these structures, taken from various studies performed after the ESTRO guidelines were published [14] , [17] , [18] , [19] .…”