a, Example slices from cancer ROIs (cyan) determined by bounding boxes (red) detected by the cancer ROI detection model. The final classification model uses the larger additional context as input illustrated by the cyan ROI. b, Sample alignment of prior CT with current CT based on the detected cancer bounding box, which is performed by centering both sub-volumes at the center of their respective detected bounding boxes. When a prior detection is not available, the lung center is used for an approximate alignment. Note that features derived from this large, 90-mm3 context are compared for classification at a late stage in the model after several max-pooling layers that can discard spatial information. Therefore, a precise voxel-to-voxel alignment is not necessary. c, Example cancer-negative case with scarring that was correctly downgraded from a consensus grade of Lung-RADS 4B to LUMAS 1/2 by the model. d, Example cancer-positive case with a nodule (size graded as 7–12 mm, depending on the radiologist) correctly upgraded from grades of Lung-RADS 3 and 4A (depending on the radiologist) to LUMAS 4B/X by the model.