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Simulation of time–intensity curve based on k-space filling in breast dynamic contrast-enhanced three-dimensional magnetic resonance imaging

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Abstract

This study elucidated the effects of a three-dimensional k-space trajectory incorporating the partial Fourier (PF) technique on a time–intensity curve (TIC) in a dynamic contrast-enhanced magnetic resonance imaging of a typical malignant breast tumor using a digital phantom. Images were obtained from the Cancer Imaging Archive Open Data for Breast Cancer, and 1-min scans with high temporal resolution were analyzed. The order of the k-space trajectory was set as Linear (sequential), Low–High (centric), PF (62.5%; Z-, Y-, and both directions), and Low–High Radial. k0 (center of the k-space) timing and TIC shape were affected by the chosen k-space trajectory and implementation of the PF technique. A small TIC gradient was obtained using a Low–High Radial order. If the k-space filling method (particularly the radial method) produces a gentle TIC gradient, misinterpretation could arise during the assessment of tumor malignancy status.

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References

  1. American College of Radiology. Breast imaging reporting and data system (BI-RADS). 5th edn. Reston, VA: American College of Radiology; 2013.

  2. Kuhl CK, Mielcareck P, Klaschik S, Leutner C, Wardelmann E, Gieseke J, Schilid HH. Dynamic breast MR imaging: are signal intensity time course data useful for differential diagnosis of enhancing lesion? Radiology. 1999;211:101–10.

    Article  CAS  PubMed  Google Scholar 

  3. Moate PJ, Dougherty L, Schnall MD, Landis RJ, Boston RC. A modified logistic model to describe gadolinium kinetics in breast tumors. Magn Reson Imaging. 2004;22:467–73.

    Article  CAS  PubMed  Google Scholar 

  4. Mann RM, Kuhl CK, Kinkel K, Boetes C. Breast MRI: guidelines from the European Society of Breast Imaging. Eur Radiol. 2008;18:1307–18.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Kuhl C. The current status of breast MR imaging. Part I. Choice of technique, image interpretation, diagnostic accuracy, and transfer to clinical practice. Radiology. 2007;244: 356–78.

  6. King KF. Chapter 11.2, k-space, chapter 11.3, keyhole, BRISK, and TRICKS. In: Bernstein MA, King KF, Zhou XJ, editors. Handbook of MRI pulse sequences. London: Elsevier Academic Press; 2004. p. 378–93.

  7. Zhou XJ. Chapter 11.5, two-dimensional acquisition. In: Bernstein MA, King KF, Zhou XJ, editors. Handbook of MRI pulse sequences. London: Elsevier Academic Press; 2004. p. 405–23.

  8. King KF. Chapter 17.5, projection acquition. In: Bernstein MA, King KF, Zhou XJ, editors. Handbook of MRI pulse sequences. London: Elsevier Academic Press; 2004. p. 897–927.

  9. Sekine T, Amano Y, Takagi R, Matsumura Y, Murai Y, Kumita S. Feasibility of 4D flow MR imaging of brain with either Cartesian y-z radial sampling or k-t SENSE: comparison with 4D flow MR imaging using SENSE. Magn Reason Med Sci. 2014;13:15–24.

    Article  Google Scholar 

  10. Feng L, Grimm R, Block KT, Chandarana H, Kim S, Xu J, Axel L, Sodickson DK, Otazo R. Golden-angle radial sparse parallel MRI: combination of compressed sensing, parallel imaging, and golden-angle radial sampling for fast and flexible dynamic volumetric MRI. Magn Reson Med. 2014;72:707–17.

    Article  PubMed  Google Scholar 

  11. Takatsu Y, Ueyama T, Iwasaki T, Asahara M, Honda M, Miyati T. Effects of k-space orders on the time-intensity curves in dynamic contrast-enhanced magnetic resonance imaging of the breast based on simulation study. Magn Reson Imaging. 2021;79:85–96.

    Article  PubMed  Google Scholar 

  12. Takatsu Y, Ueyama T, Miyati T, Yamamura K. Simulation of the modulation transfer function dependent on the partial Fourier fraction in dynamic contrast enhancement magnetic resonance imaging. Australas Phys Eng Sci Med. 2016;39:825–31.

    Article  PubMed  Google Scholar 

  13. King KF, Chap 13.4, partial Fourier reconstruction. In: Bernstein MA, King KF, Zhou XJ, editors. Handbook of MRI pulse sequences. London: Elsevier Academic Press; 2004. p. 546–58.

  14. Kazerooni AF, Nabil M, Khah HH, Parviz S, Gity M, Rad HS. A one-step biomarker quantification methodology for DCE-MRI of adnexal masses: capturing kinetic pattern from early to late enhancement. Magn Reson Med. 2018;79:1165–71.

    Article  Google Scholar 

  15. King KF. Chapter 13.2, k-space, gridding reconstruction. In: Bernstein MA, King KF, Zhou XJ, editors. Handbook of MRI pulse sequences. London: Elsevier Academic Press; 2004. p. 506–21.

  16. Mann RM, Cho N, Moy L. Breast MRI: state of the art. Radiology. 2019;292:520–36.

    Article  PubMed  Google Scholar 

  17. MathWorks Help Center. In: Evaluating goodness of fit. The MathWorks, Inc. 1994–2023. Accessed 25 Dec 2023.

  18. King KF, Chap 13.1, Fourier reconstruction. In: Bernstein MA, King KF, Zhou XJ, editors. Handbook of MRI pulse sequences. London: Elsevier Academic Press; 2004. p. 491–505.

  19. Dang Y, Guo L, Lv D, Wang X, Zhang J. Classification of breast lesions based on a dual S-shaped logistic model in dynamic contrast enhanced magnetic resonance imaging. Sci China Life Sci. 2011;54:889–96.

    Article  PubMed  Google Scholar 

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Acknowledgements

The authors would like to thank Dr. Kenichiro Yamamura of Tokushima Bunri University for his valuable advice and technical support during the measurements.

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No funds, grants, or other support was received. The authors declare they have no financial interests.

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Correspondence to Yasuo Takatsu.

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The authors have no competing interests to declare relevant to the content of this article.

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A digital phantom study was conducted using online images. Therefore, approval from the Institutional Review Board was not required.

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Takatsu, Y., Ueyama, T., Iwasaki, T. et al. Simulation of time–intensity curve based on k-space filling in breast dynamic contrast-enhanced three-dimensional magnetic resonance imaging. Radiol Phys Technol (2024). https://doi.org/10.1007/s12194-024-00793-y

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  • DOI: https://doi.org/10.1007/s12194-024-00793-y

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