Evaluation of Lung Nodule Detection With Artificial Intelligence Assisted Computed Tomography in North China

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Total Enrollment

5000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2018-04-30

Study Completion Date

2021-12-31

Brief Summary

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Lung cancer is one of the leading cause of cancer related death in China. Lung cancer screening with low-dose computed tomography was considered as a better approach than radiography. However, the role of Lung cancer screening with Low-dose CT (LDCT) among Chinese people remains unclear. With rapid development of artificial intelligence (AI),the application of AI in detection and diagnosis of diseases has become research focus. Moreover, patients' psychological status also plays an important role in diagnosis and treatment.

This study focuses on detection and natural history management of lung nodule and lung cancer with AI assisted chest CT among people living in North China, and aims to investigate epidemiological results, patients' medical records and social psychological status.

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Detailed Description

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Lu'an Municipal Hospital and North China Petroleum Bureau General Hospital initialed the lung cancer screening by LDCT a few years ago. People living in North China who are administrated by these hospitals routinely took a chest CT every year. This study is to the best of our knowledge the first one designed to combine lung nodule and lung cancer screening with the application of artificial intelligence in China.

Methods: Firstly, the study acquires epidemiological, medical information and psychological status of people recruited, and investigates the data acquired from past several years of CT scans using AI to develop a model for lung nodule detection. Secondly, evaluating the performance of models and apply it to analyse the CT scans from the North China population recruited. Thirdly, improving the model and adding function for lung nodule prediction of natural history and probability of malignancy.

Aims: To depict the epidemiological results about the incidence of lung nodules and lung cancer in North China population; To evaluate association between people 's epidemiological, medical and psychological profiles and incidence, diagnosis and treatment of lung nodule; To develop an artificial intelligence assisted lung nodule diagnosis and management software to assist strategies of CT screening.

Conditions

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Solitary Pulmonary Nodule Multiple Pulmonary Nodules

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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LDCT screening group

People receive questionnaire administration at baseline, then subsequent yearly chest LDCT scan and follow up.

Questionnaire Administration

Intervention Type OTHER

Subjects will be asked to complete an additional detailed questionnaire regarding personal information, smoking history, medical history, their diet and lifestyle habits, family history of malignant neoplasm, any past or current environmental exposures and psychological status.

Interventions

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Questionnaire Administration

Subjects will be asked to complete an additional detailed questionnaire regarding personal information, smoking history, medical history, their diet and lifestyle habits, family history of malignant neoplasm, any past or current environmental exposures and psychological status.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* Aged 40 years or older
* Routinely conducting chest CT scan at a low-dose setting (120kVp, 40-80mA, slice thickness of 1.25 mm or less) yearly in Lu'an Municipal Hospital and North China Petroleum Bureau General Hospital in at least the past 4 years up to December 2017, willing to continue routine yearly LDCT scan.
* Chest CT data are available for DICOM format.
* Signed Informed Consent Form.

Exclusion Criteria

* Pregnant woman and the disabled
* Past thoracic surgery history, except for diagnostic thoracoscopy
* Poor physical status without sufficient respiratory reserve to undergo lobectomy if necessary
* Shortened life expectancy less than 10 years
* Malignant tumor history within the past 5 years, except for the following conditions: cured skin basal cell carcinoma, superficial bladder carcinoma. and uterine cervix cancer in situ.
* Past history of interstitial lung disease, pulmonary bulla and lung tuberculosis.
* Other circumstances which is deemed inappropriate for enrollment by the researchers.

Minimum Eligible Age

40 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No