Data description

We confirm that all methods were carried out in accordance with relevant guidelines and regulations. This study was approved by Taipei Medical University Hospital Joint Institutional Review Board and is not a retrospective study. All of the patients signed the informed consent of identifying information and image publishing. Furthermore, all of the records from patients with pathologically was confirmed and retrospectively reviewed by the final pathological confirmation or clinical diagnosis from 2016 to 2019. CT reports were searched for target patients by initially using the keyword “CT” and “nodule”. After achieving the first round filtered cases, cases with keyword “nodule”, “opacity”, “GGO (ground-glass opacity)”, “adenocarcinoma”, “granuloma”, “metastasis“ and “cancer” in type section and “pleural”, “hilum”, “pulmonary”, “lung”, “RUL”, “RLL”, “EML”, “LLL”, “LUL” in position section would be kept by manually CT report screening. It is noted that the CT reports with “shadow”, “emphysema”, “pneumonia”, “pneumonitis”, “cysts”, “fibrotic foci”, “inflammation”, and “consolidative patchy” were not included. The inclusion criteria for the study were as follow: (1) patients were scanned with routine CT using a slice thickness of 5 mm; (2) diagnosis without distant metastasis was confirmed by surgery and pathology; (3) Only the last CT scan before surgery or biopsy was chosen. (4) The diameter of each nodule was smaller than 30 mm. Under above criteria, a total of 457 cases (220 women, 236 men; average age, 65±13) with 472 lung nodules were enrolled in the study.

The all chest CT images were taken under free-breathing condition with supine position on the scanning bed for all the patients. CT scanners that produced by these manufacturers (GE Medical Systems, Philips Medical Systems, Siemens) were used for the acquisition of those CT images with 110–120 kV and 10–20 mA. The image slice matrix was 512 × 512, with slice thickness of 5 mm and the pixel spacing of 0.168 × 0.168 mm2.

There are two nodule morphologies, segmentation and semantic features in this dataset. All were discussed by three radiological doctors with 10 to 20-year radiological experiences with consensus. These CT images are analyzed mainly on the lung window (the range of HU values from −1400 to 400). There are two steps in nodule segmentation. The first is to use a semi-automatically segmentation way to get the target nodules on commercial software (IntelliSpace Discovery, Netherlands, Philips Healthcare) and then to store into a DICOM format. The second one are the contours which were segmented and would be checked again by another doctor. The nodule contour would be modified by freehand drawn using a self-developed software running on Matlab (r2018b, The MathWorks, USA) if necessary. The data format is DICOM with de-identification. DICOM (Digital Imaging and Communication in Medicine) is a general communication protocol. It can integrate the medical applications from multiple manufacturers such as scanners, servers, workstations, printers, etc. DICOM is widely used in hospital and be used in local clinics and dentist clinics.