Virtual Library
Start Your Search
Fumitsugu Kojima
Author of
-
+
P1.11 - Screening and Early Detection (Not CME Accredited Session) (ID 943)
- Event: WCLC 2018
- Type: Poster Viewing in the Exhibit Hall
- Track:
- Presentations: 1
- Moderators:
- Coordinates: 9/24/2018, 16:45 - 18:00, Exhibit Hall
-
+
P1.11-17 - Discriminating Less Invasive Lesions of Early-Stage Lung Adenocarcinoma by Three-Dimensional Computed Tomography Analysis (ID 11151)
16:45 - 18:00 | Author(s): Fumitsugu Kojima
- Abstract
Background
In the revised TNM classification for non-small cell lung cancer, the clinical T factor is specified by the maximum diameter and by the diameter of the solid component for subsolid nodules. However, as radiological measurement of the solid part is sometimes difficult, errors can occur among observers. If less invasive lesions can be truly predicted using computed tomography (CT) images, it will be very useful for determining treatment strategies. Hence, we investigated the ability to detect less invasive lesions in pathologically early-stage adenocarcinomas by evaluating the whole tumor based on three dimensional (3D) images from high-resolution CT (HRCT).
a9ded1e5ce5d75814730bb4caaf49419 Method
Among patients who underwent lung resections for primary lung cancer between February 2014 and December 2016 in our institution, we retrospectively reviewed 127 patients with pathological stage 0 or IA adenocarcinoma. All the lesions were divided into two groups: the less invasive group comprised adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA), and the invasive group comprised invasive adenocarcinoma. Radiological occupied lesion volumes (cm3) were semi-automatically calculated using 3D-CT volumetry, which included the data of CT values and voxels. The following six factors were also evaluated using voxel-based histogram analysis (VHA): % solid (the ratio of the volume with CT values above -300 Hounsfield units to the whole CT value), mean CT values, variance, kurtosis, skewness, and entropy. Using multivariate logistic regression analysis, the relationship between these seven variables and pathological less invasive lesions were analyzed to prepare an optimal model for detecting the less invasive group.
4c3880bb027f159e801041b1021e88e8 Result
Among 131 lesions, there were 39 lesions in the less invasive group (AIS/MIA = 16/23) and 94 in the invasive group. In univariate analysis, all the seven variables were significantly different between the two groups. Multivariate analysis using three variables revealed an odds ratio of 0.52 (95% confidence interval [CI]: 0.34-0.79, p = 0.002) for radiological lesion volume (cm3), 0.94 (95% CI: 0.89-0.99, p = 0.016) for % solid, and 1.58 (95% CI: 1.11-2.23, p = 0.01) for kurtosis. The optimal cut-off values were less than 8.2% for % solid, less than 5.8 cm3 for lesion volume, and greater than 3.6 for kurtosis. The area under the receiver operating characteristic curve was 0.92 (95% CI: 0.88-0.97) with the model, which achieved a 90% sensitivity and 84% specificity.
8eea62084ca7e541d918e823422bd82e Conclusion
Semi-automated objective discrimination of less-invasive lung adenocarcinomas can be achieved with high accuracy using VHA based on 3D-HRCT.
6f8b794f3246b0c1e1780bb4d4d5dc53
-
+
P2.04 - Immunooncology (Not CME Accredited Session) (ID 953)
- Event: WCLC 2018
- Type: Poster Viewing in the Exhibit Hall
- Track:
- Presentations: 1
- Moderators:
- Coordinates: 9/25/2018, 16:45 - 18:00, Exhibit Hall
-
+
P2.04-16 - Correlation Between Programmed Death Ligand 1(PD-L1) Expression and Solid Component on HRCT in Stage I Lung Cancer Patients (ID 13113)
16:45 - 18:00 | Author(s): Fumitsugu Kojima
- Abstract
Background
Programmed death ligand 1(PD-L1) expression on lung cancer cell is one of the predictors of treatment response to immune checkpoint inhibitors. However, little has been reported about PD-L1 expression in patients with early stage lung cancer because previous clinical trials were mostly focused on advanced stage, and little has been also reported about association PD-L1 expression with high-resolution computed tomography (HRCT) findings. The purposes of this study were to describe PD-L1 expression in early stage lung cancer and to evaluate correlation with solid component on HRCT.
a9ded1e5ce5d75814730bb4caaf49419 Method
We evaluated patients with non-small cell lung carcinoma (NSCLC) who had been performed surgical resection between March 2017 and 2018, and resulted in pathological stage were stage I. Adenocarcinoma in situ was excluded. PD-L1 expression was assessed by means of the PD-L1 immunohistochemistry(IHC) 22C3 pharmDx assay (Agilent). PD-L1 expression was classified into three categories, negative group (PD-L1 expression less than 1%), low expression group (over 1% and less than 50%) and high expression group (over 50%). We also described HRCT findings of the tumor by solid/ground glass nodule (GGN)-ratio, calculating by the ratio of the solid component and GGN component area. The ratio was defined 0% in pure GGN cases and 100% in solid nodule cases.
4c3880bb027f159e801041b1021e88e8 Result
During study period, 60 patients were evaluated. The mean age (±SD) was 67 (±10) years old, 28 patients (46.7%) were female. 47 patients (78.3%) were adenocarcinoma and, of these, 10 patients were minimally invasive adenocarcinoma. In radiological classification, 8 patients (13.3%) were pure GGN, 24 (40.0%) were part solid nodules and 28 (46.7%) were solid nodules. In PD-L1 expression, 33 (55.0％) patients were negative group, 23 (38.3％) were low expression group and 4 (6.7%) were high expression group. The mean PD-L1 expression (±SD) was 7.82 (±18.6)% and the mean solid/GGN-ratio (±SD) was 58.8 (±40.9)%. A Spearman’s correlation test showed significant correlation between PD-L1 expression and solid/GGN-ratio. (rho=0.43, p<0.001)
8eea62084ca7e541d918e823422bd82e Conclusion
There was a positive correlation between PD-L1 expression and solid component on HRCT in stage I NSCLC patients.
6f8b794f3246b0c1e1780bb4d4d5dc53
