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

NCT03487952 | Unknown

• 1 other identifier: NCLUNG
• Study Type: observational
• Target: 5,000
• Locations: 0 countries
• Sites: N/A

Brief Summary

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.

Conditions

Solitary Pulmonary Nodule; Multiple Pulmonary Nodules

Keywords

Lung nodule; Computed tomography; Artificial intelligence

Outcome Measures

Primary Outcomes (2)

• Detection rate of lung nodule

  Study participants undergo baseline LDCT. Images are reviewed via AI software independently to identify lung nodules with diameters greater than 4mm. The software is developed by our computer technology collaborator. A radiologist then reviews the images, reports lung nodules with diameters greater than 4mm and any other abnormalities. The radiologist's findings will be conveyed to the study participants or their primary care physicians within 3 weeks. The process was conducted via double-blind method and detection rates of AI and radiologist will be recorded respectively. Unit of measurement: Percentage (number of participants with detected lung nodules over the total number of participants).

  3 months

• Profile of detected lung nodule

  All lung nodules detected will be classified as 4 classes by the density and composition of nodule: 1. pure ground-glass nodule (pGGN); 2. part-solid nodule; 3. solid nodule; 4. uncertain nodule. The number and proportion of each class and the diameter and location of each nodule will be recorded. Unit of measurement: Percentage (number of nodules in each class over the total number of nodules); Numerical value (average value±standard deviation of nodules in each class); Percentage (number of nodules in each lobe over the total number of nodules).

  3 months

Secondary Outcomes (5)

• Sensitivity in the detection of clinically actionable lung nodules

  3 months

• Growth of lung nodule

  3 years

• Anxiety and depression level

  3 months

• Life quality and health status

  3 months

• Lung cancer detection rate

  3 months

Study Arms (1)

LDCT screening group

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

Other: Questionnaire Administration

Interventions

Questionnaire Administration 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.

LDCT screening group

Eligibility Criteria

• Age: 40 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

People aged over 40, routinely conducting chest LDCT scan yearly in designated hospital of North China in at least the past 4 years up to December 2017, with acceptable physical conditions are eligible.

You may qualify if:

• 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.

You may not qualify if:

• 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.

Sponsors & Collaborators

• Peking University People's Hospital: lead
• Lu'an Municipal Hospital: collaborator
• North China Petroleum Bureau General Hospital: collaborator

Related Publications (7)

• Field JK, Oudkerk M, Pedersen JH, Duffy SW. Prospects for population screening and diagnosis of lung cancer. Lancet. 2013 Aug 24;382(9893):732-41. doi: 10.1016/S0140-6736(13)61614-1.

  PMID: 23972816 BACKGROUND

• Silva M, Pastorino U, Sverzellati N. Lung cancer screening with low-dose CT in Europe: strength and weakness of diverse independent screening trials. Clin Radiol. 2017 May;72(5):389-400. doi: 10.1016/j.crad.2016.12.021. Epub 2017 Feb 4.

  PMID: 28168954 BACKGROUND

• National Lung Screening Trial Research Team; Aberle DR, Adams AM, Berg CD, Black WC, Clapp JD, Fagerstrom RM, Gareen IF, Gatsonis C, Marcus PM, Sicks JD. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med. 2011 Aug 4;365(5):395-409. doi: 10.1056/NEJMoa1102873. Epub 2011 Jun 29.

  PMID: 21714641 BACKGROUND

• Detterbeck FC, Mazzone PJ, Naidich DP, Bach PB. Screening for lung cancer: Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines. Chest. 2013 May;143(5 Suppl):e78S-e92S. doi: 10.1378/chest.12-2350.

  PMID: 23649455 BACKGROUND

• Baldwin DR, Callister ME; Guideline Development Group. The British Thoracic Society guidelines on the investigation and management of pulmonary nodules. Thorax. 2015 Aug;70(8):794-8. doi: 10.1136/thoraxjnl-2015-207221. Epub 2015 Jul 1.

  PMID: 26135833 BACKGROUND

• Wiener RS, Gould MK, Woloshin S, Schwartz LM, Clark JA. What do you mean, a spot?: A qualitative analysis of patients' reactions to discussions with their physicians about pulmonary nodules. Chest. 2013 Mar;143(3):672-677. doi: 10.1378/chest.12-1095.

  PMID: 22814873 BACKGROUND

• Harris RP, Sheridan SL, Lewis CL, Barclay C, Vu MB, Kistler CE, Golin CE, DeFrank JT, Brewer NT. The harms of screening: a proposed taxonomy and application to lung cancer screening. JAMA Intern Med. 2014 Feb 1;174(2):281-5. doi: 10.1001/jamainternmed.2013.12745.

  PMID: 24322781 BACKGROUND

MeSH Terms

Conditions

Solitary Pulmonary Nodule; Multiple Pulmonary Nodules

Condition Hierarchy (Ancestors)

Lung Diseases; Respiratory Tract Diseases; Lung Neoplasms; Respiratory Tract Neoplasms; Thoracic Neoplasms; Neoplasms by Site; Neoplasms

Study Officials

• Jun J Wang, MM

  Peking University People's Hospital

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Jun J Wang, MM

CONTACT

+8601088326650; xiongwai@263.net

Feng F Yang, MD

CONTACT

yangfeng1007@sina.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator, Clinical Professor

Study Record Dates

• First Submitted: March 21, 2018
• First Posted: April 4, 2018
• Study Start: April 1, 2018
• Primary Completion: December 1, 2021
• Study Completion: December 1, 2021
• Last Updated: April 4, 2018

Record last verified: 2018-03