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Evaluation of the INCISIVE Services in Cancer Imaging: A Feasibility Study

Seminars in Oncology NursingResearch Authors: Lithin Zacharias, Iman Hesso, Reem Kayyali, Andreas Charalambous, Elizabeth Katherine Anna Triumbari, Ioanna Chouvarda, Tatjana Loncar-Turukalo, Stavros Sykiotis, Chrysostomos Symvoulidis, Alberto Gutierrez-Torre, Dimitrios K Nasikas, Magdalena Kogut-Czarkowska, Yiannis Roussakis, Christodoulou Maria, Liontou Maria, Susanna Ausso Trias, Didier Domínguez Herrera, Olga Tsave, Antonio Alcaraz, Dimitris Fotopoulos, Kristis Vevis, Lourdes Mengual, Nikolaos Doulamis, Nikša Jakovljević, Papagiannis George, Papalla Diana, Stefanos Finitsis, Tarek Ajami, Vasilakou Evanthia, Vladan Zdravkovic, Shereen Nabhani-GebaraAIIM Authors: Junhyeok Hong, Madison SchanzApproved by President Reda RiffiPublication Date: 1/7/2026

Comprehensive Summary

Zacharias et al. evaluated the practicality of INCISIVE, a tool made to assist cancer imaging for breast, lung, colorectal, and prostate cancers. The toolbox was tested by 24 clinicians from five European countries, and they used INCISIVE to review 1,205 real patient imaging cases. The evaluation was composed of standardized usability and trust questionnaires in addition to in-depth interviews to record user experience. Overall, clinicians reported moderate usability and satisfaction, and many felt the tool assisted with reducing workload and improving diagnostic confidence for clinical decision making. The system was particularly helpful as a supplemental tool providing a second opinion and for streamlining image interpretation. Regardless, users also noted challenges, including unclear outputs and explanations in some cases, as well as moderate trust levels.

Outcomes and Implications

As cancer care increasingly relies on advanced imaging across multiple specialties, tools that can help clinicians manage growing diagnostic complexity are becoming more important. The paper strongly conveyed that AI tools like INCISIVE can support cancer imaging in real clinical settings, especially by saving time and assisting clinicians with complex image interpretation. The important keynote was that the AI was seen as most useful when used alongside human judgment. The findings also highlight that clarity and ease of use are just as important as technical performance for successful integration. Since this was a study based on a relatively small group and limited cancer types per site, further testing in various clinical cases and settings will be required before wider clinical implementation.

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