Details

Autor(en) / Beteiligte

• Carretero-Barrio, Irene
• Pijuan, Lara
• Illarramendi, Adrián
• Curto, Daniel
• López-Ríos, Fernando
• Estébanez-Gallo, Ángel
• Castellvi, Josep
• Granados-Aparici, Sofía
• Compañ-Quilis, Desamparados
• Noguera, Rosa
• Esteban-Rodríguez, Isabel
• Sánchez-Güerri, Ignacio
• Ramos-Guerra, Ana Delia
• Ortuño, Juan Enrique
• Garrido, Pilar
• Ledesma-Carbayo, María Jesús
• Benito, Amparo
• Palacios, José

Titel

Concordance in the estimation of tumor percentage in non-small cell lung cancer using digital pathology

Ist Teil von

• Scientific reports, 2024-10, Vol.14 (1), p.24163-11, Article 24163

Ort / Verlag

London: Nature Publishing Group UK

Erscheinungsjahr

2024

Quelle

MEDLINE

Beschreibungen/Notizen

• The incorporation of digital pathology in clinical practice will require the training of pathologists in digital skills. Our study aimed to assess the reliability among pathologists in determining tumor percentage in whole slide images (WSI) of non-small cell lung cancer (NSCLC) using digital image analysis, and study how the results correlate with the molecular findings. Pathologists from nine centers were trained to quantify epithelial tumor cells, tumor-associated stromal cells, and non-neoplastic cells from NSCLC WSI using QuPath. Then, we conducted two consecutive ring trials. In the first trial, analyzing four WSI, reliability between pathologists in the assessment of tumor cell percentage was poor (intraclass correlation coefficient (ICC) 0.09). After performing the first ring trial pathologists received feedback. The second trial, comprising 10 WSI with paired next-generation sequencing results, also showed poor reliability (ICC 0.24). Cases near the recommended 20% visual threshold for molecular techniques exhibited higher values with digital analysis. In the second ring trial reliability slightly improved and human errors were reduced from 5.6% to 1.25%. Most discrepancies arose from subjective tasks, such as the annotation process, suggesting potential improvement with future artificial intelligence solutions.