Imager-4D: New Software for Viewing Dynamic PET Scans and Extracting Radiomic Parameters from PET Data

Abstract

Extensive research is currently being conducted into dynamic positron emission tomography (PET) acquisitions (including dynamic whole-body imaging) as well as extraction of radiomic features from imaging modalities. We describe a new PET viewing software known as Imager-4D that provides a facile means of viewing and analyzing dynamic PET data and obtaining associated quantitative metrics including radiomic parameters. The Imager-4D was programmed in the Java language utilizing the FX extensions. It is executable on any system for which a Java w/FX compliant virtual machine is available. The software incorporates the ability to view and analyze dynamic data acquired with different types of dynamic protocols. For image display, the program maintains a built-in library of 62 different lookup tables with monochromatic and full-color distributions. The Imager-4D provides multiple display layouts and can display fused images. Multiple methods of volume-of-interest (VOI) selection are available. Dynamic analysis features, such as image summation and full Patlak analysis, are also available. The user interface includes window width and level, blending, and zoom functionality. VOI sizes are adjustable and data from VOIs can either be displayed numerically or graphically within the software or exported. An example case of a 50-year-old woman with metastatic colorectal cancer and thyroiditis is included and demonstrates the steps for a user to obtain standard PET parameters, dynamic data, and radiomic features using selected VOIs. The Imager-4D represents a novel PET viewer that allows the user to view dynamic PET data, to derive dynamic and radiomic parameters from that data, and to combine dynamic data with radiomics (“dynomics”). The Imager-4D is available as a free download. This software has the potential to speed the adoption of advanced analysis of dynamic PET data into routine clinical use.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

References

  1. 1.

    Karakatsanis NA, Lodge MA, Tahari AK, Zhou Y, Wahl RL, Rahmim A: Dynamic whole-body PET parametric imaging: I. Concept, acquisition protocol optimization and clinical application. Phys Med Biol 58:7391–7418, 2013

    Article  Google Scholar 

  2. 2.

    Rahmim A, Lodge MA, Karakatsanis NA, Panin VY, Zhou Y, McMillan A, Cho S, Zaidi H, Casey ME, Wahl RL: Dynamic whole-body PET imaging: principles, potentials and applications. Eur J Nucl Med Mol Imaging 46:501–518, 2019

    Article  Google Scholar 

  3. 3.

    Cherry SR, Jones T, Karp JS, Qi J, Moses WW, Badawi RD: Total-body PET: maximizing sensitivity to create new opportunities for clinical research and patient care. J Nucl Med 59:3–12, 2018

    CAS  Article  Google Scholar 

  4. 4.

    Lee JW, Lee SM: Radiomics in oncological PET/CT: clinical applications. Nucl Med Mol Imaging. 52:170–189, 2018

    Article  Google Scholar 

  5. 5.

    Papp L, Rausch I, Grahovac M, Hacker M, Beyer T: Optimized feature extraction for radiomics analysis of 18F-FDG PET imaging. J Nucl Med. 60(6):864–872, 2019.

    Article  Google Scholar 

  6. 6.

    van Helden EJ, Vacher YJL, van Wieringen WN, van Felden FHP, Verheul HMW, Hoekstra OS et al.: Radiomics analysis of pre-treatment [18F]FDG PET/CT for patients with metastatic colorectal cancer undergoing palliative systemic treatment. Eur J Nucl Med Mol Imaging 45:2307–2317, 2018

    Article  Google Scholar 

  7. 7.

    Li K, Sun H, Lu Z, Xin J, Zhang L, Guo Y, Guo Q: Value of [18F]FDG PET radiomic features and VEGF expression in predicting pelvic lymphatic metastasis and their potential relationship in early-stage cervical squamous cell carcinoma. Eur J Radiol 106:160–166, 2018

    Article  Google Scholar 

  8. 8.

    Fahrni G, Karakatsanis NA, Di Domenicantonio G, Garibotto V, Zaidi H: Does whole-body Patlak 18F-FDG PET imaging improve lesion detectability in clinical oncology? Eur Radiol, 2019

  9. 9.

    Constanzo J, Wei L, Tseng HH, El Naqa I: Radiomics in precision medicine for lung cancer. Transl Lung Cancer Res. 6(6):635–647, 2017

    Article  Google Scholar 

  10. 10.

    Hatt M, Tixier F, Pierce L, Kinahan PE, Le Rest CC, Visvikis D: Characterization of PET/CT images using texture analysis: the past, the present… any future? Eur J Nucl Med Mol Imaging. 44(1):151–165, 2016

    Article  Google Scholar 

  11. 11.

    Im KC, Choi IS, Ryu JS, Eo GS, Kim JS, Moon DH: PET/CT fusion viewing software for use with picture archiving and communication systems. J Digit Imaging. 23:732–743, 2010

    Article  Google Scholar 

  12. 12.

    Leal J, Turkbey E, Solnes L, Rowe S, Rahmim A, Lodge M: A viewer for dynamic whole body PET/CT studies. J Nucl Med 58(Suppl 1):705, 2017

    Google Scholar 

  13. 13.

    Patlak CS, Blasberg RG, Fenstermacher JD: Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data. J Cereb Blood Flow Metab 3:1–7, 1983

    CAS  Article  Google Scholar 

  14. 14.

    Patlak CS, Blasberg RG: Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data. Generalizations. J Cereb Blood Flow Metab 5:584–590, 1985

    CAS  Article  Google Scholar 

  15. 15.

    Bentourkia M, Zaidi H: Tracer kinetic modeling in PET. PET Clin 2:267–277, 2007

    Article  Google Scholar 

  16. 16.

    Karakatsanis NA, Lodge MA, Zhou Y, Wahl RL, Rahmim A: Dynamic whole-body PET parametric imaging: II. Task-oriented statistical estimation. Phys Med Biol. 58:7419–7445, 2013

    Article  Google Scholar 

  17. 17.

    Hatt M, Vallieres M, Visvikis D, Zwanenburg A: IBSI: an international community radiomics standardization initiative. J Nucl Med. 59(Suppl 1):287, 2018

    Google Scholar 

  18. 18.

    Cherry SR, Badawi RD, Karp JS, Moses WW, Price P, Jones T: Total-body imaging: transforming the role of positron emission tomography. Sci Transl Med. 9:eaaf6169, 2017

    Article  Google Scholar 

  19. 19.

    Zhang X, Zhou J, Cherry SR, Badawi RD, Qi J: Quantitative image reconstruction for total-body PET imaging using the 2-meter long EXPLORER scanner. Phy Med Biol 62:2465–2485, 2017

    CAS  Article  Google Scholar 

  20. 20.

    Karakatsanis NA, Casey ME, Lodge MA, Rahmim A, Zaidi H: Whole-body direct 4D parametric PET imaging employing nested generalized Patlak expectation-maximization reconstruction. Phys Med Biol. 61:5456–5485, 2016

    Article  Google Scholar 

  21. 21.

    Zhuang M, Karakatsanis NA, Dierckx RAJO, Zaidi H: Quantitative analysis of heterogeneous [18F]FDG static (SUV) vs. Patlak (Ki) whole-body PET imaging using different segmentation methods: a simulation study. Mol Imaging Biol. 21:317–327, 2019

    CAS  Article  Google Scholar 

  22. 22.

    Savir-Baruch B, Zanoni L, Schuster DM: Imaging of prostate cancer using fluciclovine. Urol Clin North Am. 45:489–502, 2018

    Article  Google Scholar 

  23. 23.

    Sanli Y, Garg I, Kandathil A, Kendi T, Zanetti MJB, Kuyumcu S, Subramaniam RM: Neuroendocrine tumor diagnosis and management: 68Ga-DOTATATE PET/CT. AJR Am J Roentgenol. 211:267–277, 2018

    Article  Google Scholar 

  24. 24.

    Rowe SP, Gorin MA, Allaf ME, Pienta KJ, Tran PT, Pomper MG et al.: PET imaging of prostate-specific membrane antigen in prostate cancer: current state of the art and future challenges. Prostate Cancer Prostatic Dis 19:223–230, 2016

    CAS  Article  Google Scholar 

Download references

Funding

We gratefully acknowledge funding from the National Institutes of Health EB024495 and the National Cancer Institute P30CA006973.

Author information

Affiliations

Authors

Corresponding authors

Correspondence to Steven P. Rowe or Jeffrey P. Leal.

Ethics declarations

Conflict of Interest

The authors declare that they have no conflicts of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Rowe, S.P., Solnes, L.B., Yin, Y. et al. Imager-4D: New Software for Viewing Dynamic PET Scans and Extracting Radiomic Parameters from PET Data. J Digit Imaging 32, 1071–1080 (2019). https://doi.org/10.1007/s10278-019-00255-7

Download citation

Keywords

  • Dynamic PET
  • FDG PET
  • Radiomics
  • Dynomics