European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery · 2022
Artificial intelligence analysis of three-dimensional imaging data derives factors associated with postoperative recurrence in patients with radiologically solid-predominant small-sized lung cancers.
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Kudo Yujin, Shimada Yoshihisa, Matsubayashi Jun, Kitamura Yoshiro, Makino Yojiro, Maehara Sachio, Hagiwara Masaru, Park Jinho, Yamada Takafumi, Takeuchi Susumu, Kakihana Masatoshi, Nagao Toshitaka, Ohira Tatsuo, Masumoto Jun, Ikeda Norihiko
Аннотация
OBJECTIVES: Indications of limited resection, such as segmentectomy, have recently been reported for patients with solid-predominant lung cancers ≤2 cm. This study aims to identify unfavourable prognostic factors using three-dimensional imaging analysis with artificial intelligence (AI) technology.
METHODS: A total of 157 patients who had clinical N0 non-small cell lung cancer with a radiological size ≤2 cm, and a consolidation tumour ratio > 0.5, who underwent anatomical lung resection between 2011 and 2017 were enrolled. To evaluate the three-dimensional structure, the ground-glass nodule/Solid Automatic Identification AI software Beta Version (AI software; Fujifilm Corporation, Japan) was used.
RESULTS: Maximum standardized uptake value (SUVmax) and solid-part volume measured by AI software (AI-SV) showed significant differences between the 139 patients with adenocarcinoma and the 18 patients with non-adenocarcinoma. Among the adenocarcinoma patients, 42 patients (30.2%) were found to be pathological upstaging. Multivariable analysis demonstrated that high SUVmax, high carcinoembryonic antigen level and high AI-SV were significant prognostic factors for recurrence-free survival (RFS; P < 0.05). The 5-year RFS was compared between patients with tumours showing high SUVmax and those showing low SUVmax (67.7% vs 95.4%, respectively, P < 0.001). The 5-year RFS was 91.0% in patients with small AI-SV and 68.1% in those with high AI-SV (P = 0.001).
CONCLUSIONS: High AI-SV, high SUVmax and abnormal carcinoembryonic antigen level were unfavourable prognostic factors of patients with solid-predominant lung adenocarcinoma with a radiological size ≤2 cm. Our results suggest that lobectomy should be preferred to segmentectomy for patients with these prognostic factors.
METHODS: A total of 157 patients who had clinical N0 non-small cell lung cancer with a radiological size ≤2 cm, and a consolidation tumour ratio > 0.5, who underwent anatomical lung resection between 2011 and 2017 were enrolled. To evaluate the three-dimensional structure, the ground-glass nodule/Solid Automatic Identification AI software Beta Version (AI software; Fujifilm Corporation, Japan) was used.
RESULTS: Maximum standardized uptake value (SUVmax) and solid-part volume measured by AI software (AI-SV) showed significant differences between the 139 patients with adenocarcinoma and the 18 patients with non-adenocarcinoma. Among the adenocarcinoma patients, 42 patients (30.2%) were found to be pathological upstaging. Multivariable analysis demonstrated that high SUVmax, high carcinoembryonic antigen level and high AI-SV were significant prognostic factors for recurrence-free survival (RFS; P < 0.05). The 5-year RFS was compared between patients with tumours showing high SUVmax and those showing low SUVmax (67.7% vs 95.4%, respectively, P < 0.001). The 5-year RFS was 91.0% in patients with small AI-SV and 68.1% in those with high AI-SV (P = 0.001).
CONCLUSIONS: High AI-SV, high SUVmax and abnormal carcinoembryonic antigen level were unfavourable prognostic factors of patients with solid-predominant lung adenocarcinoma with a radiological size ≤2 cm. Our results suggest that lobectomy should be preferred to segmentectomy for patients with these prognostic factors.