q-Space Imaging Yields a Higher Effect Gradient to Assess Cellularity than Conventional Diffusion-weighted Imaging Methods at 3.0 T: A Pilot Study with Freshly Excised Whole-Breast Tumors

Nicholas Senn, Yazan Masannat, Ehab Husain, Bernard Siow, Steven D. Heys, Jiabao He (Corresponding Author)

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Abstract

Purpose: Although a reduction in breast tumor cellularity indicates a positive early response to neoadjuvant chemotherapy, existing radiological methods lack the adequate sensitivity required to detect changes in cellularity across whole tumours for use in personalized care. We hypothesized q-space imaging (QSI), an advanced diffusion-weighted MRI method, provides a higher effect gradient to assess tumor cellularity than existing diffusion imaging methods, and fidelity to cellularity from histology.

Materials and Methods: In this prospective study, diffusion-weighted images were acquired from twenty whole breast tumors freshly excised from patients (age range 35–78 years) using a clinical 3T MRI scanner. Median and skewness values were extracted from the histogram distributions obtained from QSI, monoexponential model (MONO), diffusion kurtosis imaging (DKI), and stretched exponential model (SEM). The skewness from QSI and other diffusion models was compared using paired t-tests and relative effect gradient, obtained from correlating skewness values.

Results: The skewness obtained from QSI (1.34±0.77) was significantly higher than the skewness from MONO (1.09±0.67, P = 0.015), SEM (1.07±0.70, P = 0.014), and DKI (0.97±0.63, P = 0.004). QSI yielded a higher effect gradient in skewness (percentage increase) compared to MONO (0.26/0.74, 35.1%), SEM (0.26/0.74, 35.1%), and DKI (0.37/0.63, 58.7%). The skewness and median from QSI were significantly correlated with the skewness (ρ = -0.468, P = 0.038) and median (ρ = -0.513, P = 0.021) of cellularity from histology.

Conclusion: QSI yields a higher effect gradient to assess breast tumor cellularity than existing diffusion methods, and fidelity to underlying histology.
Original languageEnglish
Article numbere190008
JournalRadiology: Imaging Cancer
Volume1
Issue number1
Early online date27 Sep 2019
DOIs
Publication statusPublished - Sep 2019

Keywords

  • q-space imaging (QSI)
  • monoexponential model (MONO)
  • stretched exponential model (SEM)
  • diffusion kurtosis imaging (DKI)
  • tumor heterogeneity

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