Can computed tomography differentiate adenocarcinoma in situ from minimally invasive adenocarcinoma?. Issue 7 (17th February 2021) - Yoshida, Mitsuteru; Yuasa, Masao; Ogawa, Hirohisa; Miyamoto, Naoki; Kawakami, Yukikiyo; Kondo, Kazuya; Tangoku, Akira
Abstract: Background: Given the subtle pathological signs of adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA), effective differentiation between the two entities is crucial. However, it is difficult to predict these conditions using preoperative computed tomography (CT) imaging. In this study, we investigated whether histological diagnosis of AIS and MIA using quantitative three‐dimensional CT imaging analysis could be predicted. Methods: We retrospectively analyzed the images and histopathological findings of patients with lung cancer who were diagnosed with AIS or MIA between January 2017 and June 2018. We used Synapse Vincent (v. 4.3) (Fujifilm) software to analyze the CT attenuation values and performed a histogram analysis. Results: There were 22 patients with AIS and 22 with MIA. The ground‐glass nodule (GGN) rate was significantly higher in patients with AIS ( p < 0.001), whereas the solid volume ( p < 0.001) and solid rate ( p = 0.001) were significantly higher in those with MIA. The mean ( p = 0.002) and maximum ( p = 0.025) CT values were significantly higher in patients with MIA. The 25th, 50th, 75th, and 97.5th percentiles (all p < 0.05) for the CT values were significantly higher in patients with MIA. Conclusions: We demonstrated that quantitative analysis of 3D‐CT imaging data using software can help distinguish AIS from MIA. These analyses are useful for guiding decision‐making in the surgical management of early lung cancer, as well as subsequent follow‐up. Abstract : Given the subtle pathological signs of adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA), effective differentiation between the two entities is crucial. However, it is difficult to predict these conditions using preoperative computed tomography (CT) imaging.