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NCICT: National Cancer Institute Dosimetry System for Computed Tomography

NCICT text on top of brain scans

Over the last three decades, the number of computed tomography (CT) examinations conducted annually has grown exponentially such that CT imaging currently represents about a quarter of the collective effective radiation dose received by the U.S. population. To address this public health concern, it is important to have tools to assess and monitor radiation exposures from CT scans. NCICT, the National Cancer Institute dosimetry system for Computed Tomography,1 is an easy-to-use CT organ dose calculator.

Strong Science

The program provides absorbed dose to major radiosensitive organs and tissues based on the characteristics of patients and CT scan parameters. NCICT combines several cutting-edge technologies including a library of computational human phantoms, the simulation of x-rays from a reference CT scanner, and a user-friendly graphical interface. The simulated dose results have been rigorously validated through comparison with experimental measurement.2-4

Models of the human form that are made of stacked pieces that can be removed

State-of-the-art Phantoms

3d model of person laying flat inside of column made of outlined circles

NCICT uses dose generated from simulations combining a helical x-ray source in CT scanner with state-of-the-art computational human phantoms

The NCICT software incorporates state-of-the-art phantoms with enough variety to represent just about any patient, including the International Commission on Radiological Protection (ICRP) reference pediatric and adult series (NCICT 1.0), the Phantoms library of 370 pediatric and adult males and females of different height and weight (NCICT 2.0), and eight pregnant phantoms containing detailed fetus models at various gestations (NCICT 3.0).5

Hassle-free Installation

NCICT is a standalone software that runs on a personal computer. Users do not need an internet connection to upload sensitive patient data to a central server. NCICT works on multiple platforms including Windows, Mac, and LINUX.

Screenshot of NCICT graphical user interface - two views of a body in the middle, GUI options on either side

Graphical User Interface of NCICT

Versatile Dose Calculation Modes

NCICT features two computation modes: Graphical User Interface (GUI) mode and Batch Calculation mode. The GUI mode allows the user to interactively enter patient and CT scanner data and NCICT rapidly calculates organ doses with simple graphs. The Batch Calculation mode is designed to compute organ doses for a large number of patients by importing a set of parameters from a formatted text file. The Batch Calculation mode also runs by text command, making it easy to connect NCICT with existing databases.

Extensively Tested

NCICT was rigorously tested by more than 100 beta users whose feedback was incorporated into several revisions. The software has been used by hundreds of users worldwide and has resulted in many research publications.6-21

How to Access This Resource

Non-Commercial Research Use

There is no charge to use these resources for non-commercial research purposes. Please submit a Software Transfer Agreement form to Dr. Choonsik Lee.

Commercial Use

Contact Dr. Kevin Chang of the NCI Technology Transfer Center to discuss the licensing process for commercial use.

For answers to questions and other support, join the NCI Hub - Group: NCI Dose Forum.

Selected References
  1. Lee C, Kim KP, Bolch WE, Moroz BE, Les Folio. NCICT: a computational solution to estimate organ doses for pediatric and adult patients undergoing CT scans. J Radiol Prot. 2015.

    [PubMed Abstract]
  2. Long DJ, Lee C, Tien C, et al. Monte Carlo simulations of adult and pediatric computed tomography exams: Validation studies of organ doses with physical phantoms. Med Phys. 2013.

    [PubMed Abstract]
  3. Dabin J, Mencarelli A, McMillan D, Romanyukha A, Struelens L, Lee C. Validation of calculation algorithms for organ doses in CT by measurements on a 5 year old paediatric phantom. Phys Med Biol. 2016.

    [PubMed Abstract]
  4. Giansante L, Martins JC, Nersissian DY, et al. Organ doses evaluation for chest computed tomography procedures with TL dosimeters: Comparison with Monte Carlo simulations. J Appl Clin Med Phys. December 2018.

    [PubMed Abstract]
  5. Maynard MR, Maynard MR, Geyer JW, et al. The UF family of hybrid phantoms of the developing human fetus for computational radiation dosimetry. Phys Med Biol. 2011.

    [PubMed Abstract]
  6. Pokora R, Krille L, Dreger S, et al. Computed Tomography in Germany. Dtsch Arzteblatt Int. 2016.

    [PubMed Abstract]
  7. Olerud HM, Toft B, Flatabø S, Jahnen A, Lee C, Thierry-Chef I. Reconstruction of paediatric organ doses from axial CT scans performed in the 1990s – range of doses as input to uncertainty estimates. Eur Radiol. January 2016.

    [PubMed Abstract]
  8. Meulepas JM, Ronckers C e cile M, Smets AMJB, et al. Leukemia and brain tumors among children after radiation exposure from CT scans: design and methodological opportunities of the Dutch Pediatric CT Study. Eur J Epidemiol. 2014.

    [PubMed Abstract]
  9. de Basea MB, Pearce MS, Kesminiene A, et al. EPI-CT: design, challenges and epidemiological methods of an international study on cancer risk after paediatric and young adult CT. J Radiol Prot. 2015.

    [PubMed Abstract]
  10. Thierry-Chef I, Dabin J, Friberg E, et al. Assessing Organ Doses from Paediatric CT Scans: A Novel Approach for an Epidemiology Study (the EPI-CT Study). Int J Environ Res Public Health. 2013.

    [PubMed Abstract]
  11. Pearce MS, Salotti JA, Little MP, et al. Radiation exposure from CT scans in childhood and subsequent risk of leukaemia and brain tumours: a retrospective cohort study. Lancet. 2012.

    [PubMed Abstract]
  12. Berrington de González A, Journy N, Lee C, et al. No association between radiation dose from pediatric CT scans and risk of subsequent Hodgkin lymphoma. Cancer Epidemiol Biomarkers Prev. January 2017.

    [PubMed Abstract]
  13. Journy NMY, Lee C, Harbron RW, McHugh K, Pearce MS, de Gonza acute lez AB. Projected cancer risks potentially related to past, current, and future practices in paediatric CT in the United Kingdom, 1990–2020. Br J Cancer. 2016.

    [PubMed Abstract]
  14. Journy NMY, Dreuil S, Boddaert N, et al. Individual radiation exposure from computed tomography: a survey of paediatric practice in French university hospitals, 2010–2013. Eur Radiol. August 2017.

    [PubMed Abstract]
  15. Romanyukha A, Les Folio, Lamart S, Simon SL, Lee C. Body size-specific effective dose conversion coefficients for CT scans. Radiat Prot Dosimetry. 2016.

    [PubMed Abstract]
  16. Bahadori A, Miglioretti D, Kruger R, et al. Calculation of Organ Doses for a Large Number of Patients Undergoing CT Examinations. Am J Roentgenol. 2015.

    [PubMed Abstract]
  17. Lodwick DL, Cooper JN, Adler B, et al. How to identify high radiation burden from computed tomography: an example in obese children. J Surg Res. 2017.

    [PubMed Abstract]
  18. Cooper JN, Lodwick DL, Adler B, Lee C, Minneci PC, Deans KJ. Patient characteristics associated with differences in radiation exposure from pediatric abdomen-pelvis CT scans: a quantile regression analysis. Comput Biol Med. 2017.

    [PubMed Abstract]
  19. Krille L, Dreger S, Schindel R, et al. Risk of cancer incidence before the age of 15 years after exposure to ionising radiation from computed tomography: results from a German cohort study. Radiat Environ Biophys. 2015.

    [PubMed Abstract]
  20. Lee C, Flynn MJ, Judy PF, Cody DD, Bolch WE, Kruger RL. Body Size–Specific Organ and Effective Doses of Chest CT Screening Examinations of the National Lung Screening Trial. Am J Roentgenol. 2017.

    [PubMed Abstract]
  21. Chang LA, Miller DL, Lee C, et al. Thyroid Radiation Dose to Patients from Diagnostic Radiology Procedures over Eight Decades: 1930–2010. Health Phys. 2017.

    [PubMed Abstract]
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