A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä

Multicentre evaluation of deep learning CT autosegmentation of the head and neck region for radiotherapy




TekijätPang, Eric Pei Ping; Tan, Hong Qi; Wang, Fuqiang; Niemelä, Jarkko; Bolard, Gregory; Ramadan, Susan; Kiljunen, Timo; Capala, Marta; Petit, Steven; Seppala, Jan; Vuolukka, Kristiina; Kiitam, Ingrid; Zolotuhhin, Danil; Gershkevitsh, Eduard; Lehtiö, Kaisa; Nikkinen, Juha; Keyriläinen, Jani; Mokka, Miia; Chua, Melvin Lee Kiang

KustantajaNATURE PORTFOLIO

KustannuspaikkaBERLIN

Julkaisuvuosi2025

Lehti:npj Digital Medicine

Tietokannassa oleva lehden nimiNPJ DIGITAL MEDICINE

Lehden akronyymiNPJ DIGIT MED

Artikkelin numero312

Vuosikerta8

Numero1

Sivujen määrä11

eISSN2398-6352

DOIhttps://doi.org/10.1038/s41746-025-01624-z

Verkko-osoitehttps://www.nature.com/articles/s41746-025-01624-z

Rinnakkaistallenteen osoitehttps://research.utu.fi/converis/portal/detail/Publication/498728007


Tiivistelmä
This is a multi-institutional study to evaluate a head-and-neck CT auto-segmentation software across seven institutions globally. 11 lymph node levels and 7 organs-at-risk contours were evaluated in a two-phase study design. Time savings were measured in both phases, and the inter-observer variability across the seven institutions was quantified in phase two. Overall time savings were found to be 42% in phase one and 49% in phase two. Lymph node levels IA, IB, III, IVA, and IVB showed no significant time savings, with some centers reporting longer editing times than manual delineation. All the edited ROIs showed reduced inter-observer variability compared to manual segmentation. Our study shows that auto-segmentation plays a crucial role in harmonizing contouring practices globally. However, the clinical benefits of auto-segmentation software vary significantly across ROIs and between clinics. To maximize its potential, institution-specific commissioning is required to optimize the clinical benefits.

Ladattava julkaisu

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Last updated on 2025-21-08 at 09:00