NCT05398887

Brief Summary

The main objective of the study is to evaluate the detection rate of pulmonary conditions, percentage of ionizing radiation dose reduction, and state of image quality of ULDCT coupling with innovative vendor-neutral CT denoising solution based on deep learning technology.

Trial Health

35
At Risk

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
200

participants targeted

Target at P75+ for not_applicable

Timeline
Completed

Started Jun 2022

Shorter than P25 for not_applicable

Status
unknown

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

May 25, 2022

Completed
7 days until next milestone

First Posted

Study publicly available on registry

June 1, 2022

Completed
14 days until next milestone

Study Start

First participant enrolled

June 15, 2022

Completed
3 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

September 1, 2022

Completed
1 month until next milestone

Study Completion

Last participant's last visit for all outcomes

October 1, 2022

Completed
Last Updated

June 1, 2022

Status Verified

May 1, 2022

Enrollment Period

3 months

First QC Date

May 25, 2022

Last Update Submit

May 30, 2022

Conditions

Lung Diseases

Keywords

Computed tomographyArtificial IntelligenceDenoising techniqueUltra-low-dose Computed tomography

Outcome Measures

Primary Outcomes (2)

  • Detection rate of pulmonary conditions

    Pulmonary condition detection rate on low dose chest CT and ultra dose chest CT with artificial intelligence-based CT denoising solution by blinded reviewers

    Within 2 weeks after data collection

  • Contrast media dose

    Administered contrast media dose in each patient

    Within 2 weeks after data collection

Secondary Outcomes (1)

  • Image contrast

    Within 2 weeks after data collection

Study Arms (2)

Low dose Chest CT scan

ACTIVE COMPARATOR

Underwent low dose chest CT with 30% lower radiation dose Interventions: Radiation: Low radiation dose CT Other: Image quality analysis

Radiation: Low radiation dose CT

Ultra low dose CT scan with Artificial Intelligence

EXPERIMENTAL

Interventions: Radiation: Low radiation dose CT Image quality Other: Deep-learning based contrast boosting algorithms

Radiation: Underwent ultra dose chest CTOther: Artificial Intelligence based model

Interventions

Low radiation dose CTRADIATION

Underwent low dose chest CT with 30% lower radiation dose

Low dose Chest CT scan
Underwent ultra dose chest CTRADIATION

Underwent ultra dose chest CT with 90% lower radiation dose

Ultra low dose CT scan with Artificial Intelligence
Artificial Intelligence based modelOTHER

Deep-learning based contrast boosting algorithms

Ultra low dose CT scan with Artificial Intelligence

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • Patients aged over 18-year-old
  • Patients undergoing CT Chest for all purpose

You may not qualify if:

  • Age less than 18 years
  • Any suspicion of pregnancy
  • History of thoracic surgery or placement of the metallic device in the thorax
  • An inability to hold respiration during CT

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Related Publications (19)

  • International Agency for Research on Cancer. Global Cancer Observatory: cancer today. World Health Organization. https://gco.iarc.fr/today (accessed Feb 14, 2022).

    BACKGROUND

  • Health Development Center, WHO. Health Indicators 2019. Mongolian Health Development Center. http://hdc.gov.mn/media/uploads/202108/Eruul_mendiin_uzuulelt_2020.pdf (accessed Feb 14, 2022).

    BACKGROUND

  • WHO global report. WHO global report on mortality attributable to tobacco. 2012

    BACKGROUND

  • Zheng W, McLerran DF, Rolland BA, Fu Z, Boffetta P, He J, Gupta PC, Ramadas K, Tsugane S, Irie F, Tamakoshi A, Gao YT, Koh WP, Shu XO, Ozasa K, Nishino Y, Tsuji I, Tanaka H, Chen CJ, Yuan JM, Ahn YO, Yoo KY, Ahsan H, Pan WH, Qiao YL, Gu D, Pednekar MS, Sauvaget C, Sawada N, Sairenchi T, Yang G, Wang R, Xiang YB, Ohishi W, Kakizaki M, Watanabe T, Oze I, You SL, Sugawara Y, Butler LM, Kim DH, Park SK, Parvez F, Chuang SY, Fan JH, Shen CY, Chen Y, Grant EJ, Lee JE, Sinha R, Matsuo K, Thornquist M, Inoue M, Feng Z, Kang D, Potter JD. Burden of total and cause-specific mortality related to tobacco smoking among adults aged >/= 45 years in Asia: a pooled analysis of 21 cohorts. PLoS Med. 2014 Apr 22;11(4):e1001631. doi: 10.1371/journal.pmed.1001631. eCollection 2014 Apr.

    PMID: 24756146BACKGROUND

  • Fourth national STEPS Survey on the Prevalence of Noncommunicable Disease and Injury Risk Factors-2019. World Health Organization.

    BACKGROUND

  • Smith-Bindman R, Lipson J, Marcus R, Kim KP, Mahesh M, Gould R, Berrington de Gonzalez A, Miglioretti DL. Radiation dose associated with common computed tomography examinations and the associated lifetime attributable risk of cancer. Arch Intern Med. 2009 Dec 14;169(22):2078-86. doi: 10.1001/archinternmed.2009.427.

    PMID: 20008690BACKGROUND

  • 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: 21714641BACKGROUND

  • de Koning HJ, van der Aalst CM, de Jong PA, Scholten ET, Nackaerts K, Heuvelmans MA, Lammers JJ, Weenink C, Yousaf-Khan U, Horeweg N, van 't Westeinde S, Prokop M, Mali WP, Mohamed Hoesein FAA, van Ooijen PMA, Aerts JGJV, den Bakker MA, Thunnissen E, Verschakelen J, Vliegenthart R, Walter JE, Ten Haaf K, Groen HJM, Oudkerk M. Reduced Lung-Cancer Mortality with Volume CT Screening in a Randomized Trial. N Engl J Med. 2020 Feb 6;382(6):503-513. doi: 10.1056/NEJMoa1911793. Epub 2020 Jan 29.

    PMID: 31995683BACKGROUND

  • Boyd MA. U.S. radiation protection: role of national and international recommendations and opportunities for collaboration (harmony, not dissonance). Health Phys. 2015 Feb;108(2):278-82. doi: 10.1097/HP.0000000000000236.

    PMID: 25551510BACKGROUND

  • Katsura M, Matsuda I, Akahane M, Yasaka K, Hanaoka S, Akai H, Sato J, Kunimatsu A, Ohtomo K. Model-based iterative reconstruction technique for ultralow-dose chest CT: comparison of pulmonary nodule detectability with the adaptive statistical iterative reconstruction technique. Invest Radiol. 2013 Apr;48(4):206-12. doi: 10.1097/RLI.0b013e31827efc3a.

    PMID: 23344517BACKGROUND

  • Kim Y, Kim YK, Lee BE, Lee SJ, Ryu YJ, Lee JH, Chang JH. Ultra-Low-Dose CT of the Thorax Using Iterative Reconstruction: Evaluation of Image Quality and Radiation Dose Reduction. AJR Am J Roentgenol. 2015 Jun;204(6):1197-202. doi: 10.2214/AJR.14.13629.

    PMID: 26001228BACKGROUND

  • Lee SW, Kim Y, Shim SS, Lee JK, Lee SJ, Ryu YJ, Chang JH. Image quality assessment of ultra low-dose chest CT using sinogram-affirmed iterative reconstruction. Eur Radiol. 2014 Apr;24(4):817-26. doi: 10.1007/s00330-013-3090-9. Epub 2014 Jan 18.

    PMID: 24442444BACKGROUND

  • Nagatani Y, Takahashi M, Murata K, Ikeda M, Yamashiro T, Miyara T, Koyama H, Koyama M, Sato Y, Moriya H, Noma S, Tomiyama N, Ohno Y, Murayama S; investigators of ACTIve study group. Lung nodule detection performance in five observers on computed tomography (CT) with adaptive iterative dose reduction using three-dimensional processing (AIDR 3D) in a Japanese multicenter study: Comparison between ultra-low-dose CT and low-dose CT by receiver-operating characteristic analysis. Eur J Radiol. 2015 Jul;84(7):1401-12. doi: 10.1016/j.ejrad.2015.03.012. Epub 2015 Apr 2.

    PMID: 25892051BACKGROUND

  • Wang R, Sui X, Schoepf UJ, Song W, Xue H, Jin Z, Schmidt B, Flohr TG, Canstein C, Spearman JV, Chen J, Meinel FG. Ultralow-radiation-dose chest CT: accuracy for lung densitometry and emphysema detection. AJR Am J Roentgenol. 2015 Apr;204(4):743-9. doi: 10.2214/AJR.14.13101.

    PMID: 25794063BACKGROUND

  • Yanagawa M, Gyobu T, Leung AN, Kawai M, Kawata Y, Sumikawa H, Honda O, Tomiyama N. Ultra-low-dose CT of the lung: effect of iterative reconstruction techniques on image quality. Acad Radiol. 2014 Jun;21(6):695-703. doi: 10.1016/j.acra.2014.01.023. Epub 2014 Apr 6.

    PMID: 24713541BACKGROUND

  • Tsushima E. Intraclass correlation coefficient as a reliability index [Japanese]. http://www.hs.hirosaki-u.ac.jp/~pteiki/research/stat/icc.pdf. Accessed 9 Feb 2017.

    BACKGROUND

  • Svahn TM, Sjoberg T, Ast JC. Dose estimation of ultra-low-dose chest CT to different sized adult patients. Eur Radiol. 2019 Aug;29(8):4315-4323. doi: 10.1007/s00330-018-5849-5. Epub 2018 Dec 17.

    PMID: 30560356BACKGROUND

  • Afadzi M, Fossa K, Andersen HK, Aalokken TM, Martinsen ACT. Image Quality Measured From Ultra-Low Dose Chest Computed Tomography Examination Protocols Using 6 Different Iterative Reconstructions From 4 Vendors, a Phantom Study. J Comput Assist Tomogr. 2020 Jan/Feb;44(1):95-101. doi: 10.1097/RCT.0000000000000947.

    PMID: 31939889BACKGROUND

  • Zhang M, Qi W, Sun Y, Jiang Y, Liu X, Hong N. Screening for lung cancer using sub-millisievert chest CT with iterative reconstruction algorithm: image quality and nodule detectability. Br J Radiol. 2018 Oct;91(1090):20170658. doi: 10.1259/bjr.20170658. Epub 2017 Dec 5.

    PMID: 29120665BACKGROUND

MeSH Terms

Conditions

Lung Diseases

Condition Hierarchy (Ancestors)

Respiratory Tract Diseases

Study Officials

  • Khulan Khurelsukh, M.D, MSc

    Intermed Hospital

    STUDY CHAIR

  • Delgerekh Sainjargal, M.D, MSc

    Intermed Hospital

    PRINCIPAL INVESTIGATOR

  • Bayarbaatar Bold, M.D

    Intermed Hospital

    PRINCIPAL INVESTIGATOR

Central Study Contacts

Bayarbaatar Bold, M.D

CONTACT

976-99063486bayarbaatar99@gmail.com

Khulan Khurelsukh, M.D, MSc

CONTACT

976-88010440khulan.kh@intermed.mn

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
QUADRUPLE
Who Masked
PARTICIPANT, CARE PROVIDER, INVESTIGATOR, OUTCOMES ASSESSOR
Purpose
DIAGNOSTIC
Intervention Model
PARALLEL
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Principal Investigator, Bayarbaatar Bold, Diagnostic Radiologist, M.D, Intermed Hospital

Study Record Dates

First Submitted

May 25, 2022

First Posted

June 1, 2022

Study Start

June 15, 2022

Primary Completion

September 1, 2022

Study Completion

October 1, 2022

Last Updated

June 1, 2022

Record last verified: 2022-05

Data Sharing

IPD Sharing
Will not share