Phased-array combination of 2D MRS for lipid composition quantification in patients with breast cancer

Vasiliki Mallikourti* (Corresponding Author), Sai Man Cheung, Tanja Gagliardi, Nicholas Senn, Yazan Masannat, Trevor McGordlrick, Ravi Sharma, Steven D. Heys, Jiabao He

*Corresponding author for this work

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Lipid composition in breast cancer, a central marker of disease progression, can be non-invasively quantified using 2D MRS method of double quantum filtered correlation spectroscopy (DQF-COSY). The low signal to noise ratio (SNR), arising from signal retention of only 25% and depleted lipids within tumour, demands improvement approaches beyond signal averaging for clinically viable applications. We therefore adapted and examined combination algorithms, designed for 1D MRS, for 2D MRS with both internal and external references. Lipid composition spectra were acquired from 17 breast tumour specimens, 15 healthy female volunteers and 25 patients with breast cancer on a clinical 3 T MRI scanner. Whitened singular value decomposition (WSVD) with internal reference yielded maximal SNR with an improvement of 53.3% (40.3–106.9%) in specimens, 84.4 ± 40.6% in volunteers, 96.9 ± 54.2% in peritumoural adipose tissue and 52.4% (25.1–108.0%) in tumours in vivo. Non-uniformity, as variance of improvement across peaks, was low at 21.1% (13.7–28.1%) in specimens, 5.5% (4.2–7.2%) in volunteers, 6.1% (5.0–9.0%) in peritumoural tissue, and 20.7% (17.4–31.7%) in tumours in vivo. The bias (slope) in improvement ranged from − 1.08 to 0.21%/ppm along the diagonal directions. WSVD is therefore the optimal algorithm for lipid composition spectra with highest SNR uniformly across peaks, reducing acquisition time by up to 70% in patients, enabling clinical applications.

Original languageEnglish
Article number20041
Pages (from-to)20041
Number of pages10
JournalScientific Reports
Issue number1
Publication statusPublished - 18 Nov 2020

Bibliographical note

The author would like to thank Dr Matthew Clemence (Philips Healthcare Clinical Science, UK) for clinical scientist support, Ms Bolanle Brikinns, Ms Louisa Pirie, Ms Linda Lett, and Ms Kate Shaw, for patient recruitment support, Ms Dawn Younie for logistic support, Mr Roger Bourne and Ms Mairi Fuller for providing access to the patients as well as Mrs Beverly MacLennan, Mrs Nicola Crouch, Mr Mike Hendry, and Ms Laura Reid for radiographer support.

This project was funded by Friends of Aberdeen and North Centre for Haematology, Oncology and Radiotherapy (ANCHOR), Tenovus Scotland, and NHS Grampian Endowment. Vasiliki Mallikourti’s PhD study is supported by The Princess Royal Tenovus Scotland Medical Research Scholarship.


  • Adult
  • Aged
  • Algorithms
  • Breast Neoplasms/metabolism
  • Case-Control Studies
  • Computer Simulation
  • Female
  • Humans
  • Lipids/analysis
  • Magnetic Resonance Spectroscopy/methods
  • Middle Aged
  • Signal-To-Noise Ratio


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