Effectiveness of Ultra-low-dose Chest CT With AI Based Denoising Solution
Utilization and Effectiveness of Ultra-low-dose Chest Computed Tomography Using Innovative CT Denoising Solution Based on Deep Learning Technology
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Anticipated)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Contact
Study Contact
- Name: Bayarbaatar Bold, M.D
- Phone Number: 976-99063486
- Email: bayarbaatar99@gmail.com
Study Contact Backup
- Name: Khulan Khurelsukh, M.D, MSc
- Phone Number: 976-88010440
- Email: khulan.kh@intermed.mn
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Description
Inclusion Criteria:
- Patients aged over 18-year-old
- Patients undergoing CT Chest for all purpose
Exclusion Criteria:
- 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
Study Plan
How is the study designed?
Design Details
- Primary Purpose: DIAGNOSTIC
- Allocation: RANDOMIZED
- Interventional Model: PARALLEL
- Masking: QUADRUPLE
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
ACTIVE_COMPARATOR: Low dose Chest CT scan
Underwent low dose chest CT with 30% lower radiation dose Interventions: Radiation: Low radiation dose CT Other: Image quality analysis |
Underwent low dose chest CT with 30% lower radiation dose
|
|
EXPERIMENTAL: Ultra low dose CT scan with Artificial Intelligence
Interventions: Radiation: Low radiation dose CT Image quality Other: Deep-learning based contrast boosting algorithms |
Underwent ultra dose chest CT with 90% lower radiation dose
Deep-learning based contrast boosting algorithms
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Detection rate of pulmonary conditions
Time Frame: Within 2 weeks after data collection
|
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
Time Frame: Within 2 weeks after data collection
|
Administered contrast media dose in each patient
|
Within 2 weeks after data collection
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Image contrast
Time Frame: Within 2 weeks after data collection
|
Signal to Noise, Noise and Edge-rise-distance on a five-point scale (1-5) with a higher score indicates better conspicuity.
|
Within 2 weeks after data collection
|
Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Study Chair: Khulan Khurelsukh, M.D, MSc, Intermed Hospital
- Principal Investigator: Delgerekh Sainjargal, M.D, MSc, Intermed Hospital
- Principal Investigator: Bayarbaatar Bold, M.D, Intermed Hospital
Publications and helpful links
General Publications
- 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.
- International Agency for Research on Cancer. Global Cancer Observatory: cancer today. World Health Organization. https://gco.iarc.fr/today (accessed Feb 14, 2022).
- 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).
- WHO global report. WHO global report on mortality attributable to tobacco. 2012
- 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.
- Fourth national STEPS Survey on the Prevalence of Noncommunicable Disease and Injury Risk Factors-2019. World Health Organization.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
Study record dates
Study Major Dates
Study Start (ANTICIPATED)
Study Start
Primary Completion (ANTICIPATED)
Primary Completion
Study Completion (ANTICIPATED)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (ACTUAL)
First Posted
Study Record Updates
Last Update Posted (ACTUAL)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- IMC20220515-01
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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