Session Item

Accurate delineation of GTV is crucial for proper dose prescription and treatment implementation. Manual contouring on radiologic imaging is the usual procedure but is time-consuming and suffers from interobserver variability because of the poor quality of acquisitions. Histopathology images from the resection of tumor specimens represent the gold standard for tumor characterization by providing cell-level information on disease invasion. The purpose of this study is two-fold: First, to assess variability in radiology-based GTVs from two expert centers. Second, to extensively compare these GTVs with tumor contours on the histological slides, after AI-based automatic registration of both modalities. The biological insights from histology can help practitioners better understand tumor environment in radiology towards reducing toxicity.

We collected a cohort from 77 patients (joint collaboration Gustave Roussy Institute - Centre Léon Bérard, France) on whom were acquired both pre-operative H&N CT scan and digitalized histopathology after total laryngectomy. For each center, junior and senior radiation oncologists delineated the GTV on CT, while senior pathologists contoured macroscopic tumor on histology. We applied a deep learning model to automatically register both images and deform the tumor masks consequently. We then computed various cross-center statistics to (i) highlight interobserver variability between radiation oncologists, (ii) validate the hypothesis of concordance between pathologists, and (iii) assess systematic errors on GTV delineation compared to histology, whether it be missed area or overestimation of disease extent.

According to GTV interobserver variability, we report a Dice score of 0.63 between juniors and 0.68 between seniors. This highlights the limitations of CT images for precise delineation, even if a higher experience of observers improves agreement with a reduced mean tumor volume (-23%). Conversely, expert pathologists reach an excellent concordance with a Dice score of 0.96, proving the benefit of histological examination for better diagnosis. After co-registration of both modalities and the consensus contours, it appears that GTV is systematically overestimated compared to the histology-based contour, with a mean increased volume of 29% and a low Dice score of 0.59.

A significant deleterious interobserver variability appears for GTV delineations, which can be explained by the intrinsic limitation of CT images, differences in interpretation of the clinical information provided by the endoscopy, level of experience, or working practice proper to each center. The comparison with histology is a powerful tool for understanding systematic errors and improving the training of radiation therapists toward the definition of improved guidelines. Further prospective randomized trials are warranted to assess this approach's practical feasibility and quantify the therapeutic gain in decreased toxicities for an identical tumor cure.