Table 3: Performance of the SVM-based classifier with the proposed quantitative features. Acinar structures are graded as nonmalignant as trained from the 10A and AT samples, noninvasive carcinoma as trained from the KCL and DCIS samples, and invasive carcinoma as trained from the CA1H and CA1A samples using all of the proposed features as well as the five most discriminative features: continuity of integrin 𝛼 6 along the basal membrane, colocalization of integrin 𝛼 3 with integrin 𝛼 6, integrin 𝛼 3 density, ratio between hollow lumen and acinar structure areas, and integrin 𝛼 6 density. The data set includes 400 acinar structures: 99 10A, 49 10AT, 81 KCL, 80 DCIS, 29 CA1H, and 62 CA1A.

Grading results utilizing overall feature setGrading categories (%)
NonmalignantNoninvasive CarcinomaInvasive Carcinoma

Nonmalignant10A97.02.01.0
AT73.524.52.0
Noninvasive CarcinomaKCL11.172.114.8
DCIS0.095.05.0
Invasive CarcinomaCA1H0.06.993.1
CA1A0.06.593.5

Grading results utilizing the five most discriminative featuresGrading categories (%)
NonmalignantNoninvasive CarcinomaInvasive Carcinoma

Nonmalignant10A93.03.04.0
AT85.710.24.1
Noninvasive CarcinomaKCL18.553.128.4
DCIS0.093.86.2
Invasive CarcinomaCA1H0.027.672.4
CA1A0.08.191.9