4.5 Article

Magnetic resonance imaging of mean cell size in human breast tumors

期刊

MAGNETIC RESONANCE IN MEDICINE
卷 83, 期 6, 页码 2002-2014

出版社

WILEY
DOI: 10.1002/mrm.28056

关键词

cell size; density; diameter; diffusion; IMPULSED; MRI; OGSE; oscillating gradient

资金

  1. NIH [K25CA168936, R01CA109106, R01CA173593, UL1TR002243, S10OD021771, U01CA142565, F32CA216942, UL1TR000445, P30 CA068485]
  2. American Cancer Society [58-009-56]

向作者/读者索取更多资源

Purpose Cell size is a fundamental characteristic of all tissues, and changes in cell size in cancer reflect tumor status and response to treatments, such as apoptosis and cell-cycle arrest. Unfortunately, cell size can currently be obtained only by pathological evaluation of tumor tissue samples obtained invasively. Previous imaging approaches are limited to preclinical MRI scanners or require relatively long acquisition times that are impractical for clinical imaging. There is a need to develop cell-size imaging for clinical applications. Methods We propose a clinically feasible IMPULSED (imaging microstructural parameters using limited spectrally edited diffusion) approach that can characterize mean cell sizes in solid tumors. We report the use of a combination of pulse sequences, using different gradient waveforms implemented on clinical MRI scanners and analytical equations based on these waveforms to analyze diffusion-weighted MRI signals and derive specific microstructural parameters such as cell size. We also describe comprehensive validations of this approach using computer simulations, cell experiments in vitro, and animal experiments in vivo and demonstrate applications in preoperative breast cancer patients. Results With fast acquisitions (7 minutes), IMPULSED can provide high-resolution (1.3 mm in-plane) mapping of mean cell size of human tumors in vivo on clinical 3T MRI scanners. All validations suggest that IMPULSED provides accurate and reliable measurements of mean cell size. Conclusion The proposed IMPULSED method can assess cell-size variations in tumors of breast cancer patients, which may have the potential to assess early response to neoadjuvant therapy.

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