ESTRO 2023

Session Item

Monday

May 15

11:40 - 12:40

Plenary Hall

Highlights of Proffered Papers - Latest clinical trials

Chair: , United Kingdom;

Chair: , Switzerland

Session Type: Proffered Papers

Track: Interdisciplinary

Journey:

11:40 - 11:50

Benefit of AI-assisted organ-at-risk contouring in head-and-neck cancer: A global randomized study

Mathis Ersted Rasmussen, Denmark

Presentation Number: OC-0828

Abstract

Abstract Title:

Benefit of AI-assisted organ-at-risk contouring in head-and-neck cancer: A global randomized study

Authors:

Mathis Ersted Rasmussen¹, Kamal Akbarov², Egor Titowich², Katherine Wakeham², Jasper Albertus Nijkamp³, Wouter Van Elmpt⁴, A.F.M. Kamal Uddin, Ahmed Mohamed⁵, Ben Prajogi, Brohet Kartika Erida⁵, Catherine Nyongesa, Darejan Lomidze⁵, Gisupnikha Prasiko, Gustavo Ferraris⁵, Humera Mahmood, Igor Stojkovski⁵, Isa Isayev, Issa Mohamad⁵, Leivon Shirley, Lotfi Kochbati⁵, Ludmila Eftodiev, Maksim Piatkevich⁵, Maria Matilde Bonilla Jara, Orges Spahiu⁵, Rakhat Aralbayev, Raushan Zakirova⁶, Sandya Subramaniam, Solomon Kibudde, Uranchimeg Tsegmed⁵, Stine Sofia Korreman⁷, Jesper Grau Eriksen⁷

¹Principal Investigator, The ELAISA Consortium, Aarhus, Denmark; ²International Atomic Energy Agency, The ELAISA Consortium, Vienna, Austria; ³Consultant, The ELAISA Consortium, Aarhus, Denmark; ⁴Consultant, The ELAISA Consortium, Maastricht, The Netherlands; ⁵Chief Scientific Investigators, The ELAISA Consortium, Vienna, Austria; ⁶Chief Scientific Investigators, The ELAISA Consortium , Vienna, Austria; ⁷Principal Investigator and shared last author, The ELAISA Consortium, Aarhus, Denmark

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Purpose or Objective

Global roll-out of artificial intelligence-assisted (AI-assisted) contouring has immense potential for the access and quality of care in radiotherapy. However, the current evidence is primarily from high-income countries.

The purpose of this study was to compare inter-observer variation (IOV) between radiation oncologists (ROs) in low- and middle-income countries (LMICs) using either AI-assisted or manual contouring of organs-at-risk in head-and-neck cancer.

Material and Methods

97 ROs from 23 institutions in 22 nations across 5 continents were invited to the study. The institutions were randomized to either manual contouring (control) or AI-assisted contouring (intervention) of 8 common organs-at-risk of head-neck cancer. Randomization was balanced on (1) the annual number of head-neck cases treated at institutions and (2) the availability of auto-contouring at institutions.

Four head-neck cases were randomly assigned to ROs institution-wise resulting in 2-3 institutions (8-15 ROs) per case in each group. Deep learning-based auto-contours were made with MVision AI Oy, Helsinki, Finland. Contouring was performed online in EduCase™ (RadOnc eLearning Center, Inc).

ROs were informed about the contouring guidelines used in the study and that their task was to “generate clinically acceptable contours”. ROs were also asked to complete in a short survey on their professional backgrounds.

IOV was quantified as medians of Dice coefficients and Hausdorff distances 95th percentile (HD95) between contours of the ROs and a median contour within groups. Median contours were made by summing structures and thresholding where the median number of ROs or more had included a given voxel. High Dice and low HD95 indicate low IOV.

Confidence intervals were estimated with bootstrap and groups were compared with the Mann-Whitney U test.

Results

89 ROs handed in the contours and 74 completed the survey. The four cases were contoured respectively by 18 (7/11), 24 (12/12), 23 (11/12) and 24 (12/12) ROs (Manual/AI-assisted) (See Table 1 for details).

Table 1

AI-assisted contouring as compared to manual contouring significantly reduced IOV across all organs-at-risk [Figure 1]. Below is an overview of the differences in medians for Dice and HD95 with manual contouring as reference value.

Absolute (relative) differences. Control as reference	Dice (%)	HD95 [mm] (%)
BrainStem	0.07 (8.0)	-0.82 (-29.2)
SpinalCord	0.11 (13.5)	-0.93 (-39.7)
Parotid	0.10 (11.5)	-1.47 (-42.5)
Submandibular	0.06 (6.2)	-0.60 (-26.7)
Thyroid	0.08 (9.6)	-0.53 (-23.9)
OralCavity	0.09 (10.2)	-5.60 (-59.2)
OpticNerve	0.16 (21.7)	-1.41 (-47.1)
Mandible	0.06 (7.0)	-0.66 (-35.9)

Figure 1:

Conclusion

AI-assisted contouring significantly reduced IOV across multiple institutions located in LMICs globally. The results add a significant piece of evidence favoring further adoption of AI-assisted contouring worldwide. To the best of our knowledge, this is the largest study ever performed on inter-observer variation and auto-contouring, and it is the first time LMICs has been the primary focus.