Real‐world efficacy of radiomics versus clinical predictors for microvascular invasion in patients with hepatocellular carcinoma: Large cohort study
A clinical model is as effective as a CT radiomics model for predicting MVI status in patients with HCC based on real-world scanning data, and integration of both models does not improve the predictive performance compared with a clinical model alone.
Authors
- Hirokazu Noshirο (ORCID: https://orcid.org/0000-0003-3227-7816)
- Takao Ide (ORCID: https://orcid.org/0000-0003-2441-4438)
- Susumu Eguchi (ORCID: https://orcid.org/0000-0002-7876-0152)
- Mitsuhisa Takatsuki (ORCID: https://orcid.org/0000-0002-0819-3156)
- Tomoharu Yoshizumi (ORCID: https://orcid.org/0000-0002-4497-1816)
- Kohji Okamoto (ORCID: https://orcid.org/0000-0002-9170-717X)
- Toru Beppu (ORCID: https://orcid.org/0000-0001-9046-0454)
- Shinji Itoh (ORCID: https://orcid.org/0000-0003-0382-2520)
- Hideo A. Baba (ORCID: https://orcid.org/0000-0002-1750-5318)
- Takeshi Nakaura (ORCID: https://orcid.org/0000-0002-9010-0341)
- Masatoshi Kajiwara (ORCID: https://orcid.org/0000-0002-3479-0616)
- Tomoaki Noritomi
- Atsushi Miyoshi (ORCID: https://orcid.org/0000-0001-7500-7459)
- Atsushi Nanashima (ORCID: https://orcid.org/0000-0002-3246-557X)
- Takashi Hamada (ORCID: https://orcid.org/0000-0002-8438-750X)
- Yuko Takami (ORCID: https://orcid.org/0000-0002-9331-6658)
- Yuichi Endo (ORCID: https://orcid.org/0000-0002-8792-4067)
- Masahiko Sakoda
- Tamotsu Kuroki
- Tohru Utsunomiya
- Shunsuke Kinoshita (ORCID: https://orcid.org/0000-0002-6690-4702)
Institutions
- University of Miyazaki (JP)
- Kyushu University (JP)
- Yamaguchi University (JP)
- Saga University (JP)
- Oita University (JP)
- National Kyushu Medical Center (JP)
- Fukuoka University (JP)
- University of the Ryukyus (JP)
- Fukuoka Tokushukai Hospital (JP)
- Saga-Ken Medical Centre Koseikan (JP)
- Oita Prefectural Hospital (JP)
- Nagasaki Medical Center (JP)
- Kagoshima City Hospital (JP)
- Sunagawa City Medical Center (JP)
- Kitakyushu City Hospital Organization (JP)
- Nagasaki University (JP)
- Kumamoto University (JP)
Publication Details
- Journal
- Hepatology Research
- Published
- 2024-12-12
- DOI
- https://doi.org/10.1111/hepr.14149
- Citations
- 2
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.81