Probing lipids relaxation times in breast cancer using magnetic resonance spectroscopic fingerprinting

ObjectivesTo investigate the clinical relevance of the relaxation times of lipids within breast cancer and normal fibroglandular tissue in vivo, using magnetic resonance spectroscopic fingerprinting (MRSF).MethodsTwelve patients with biopsy-confirmed breast cancer and 14 healthy controls were prospectively scanned at 3 T using a protocol consisting of diffusion tensor imaging (DTI), MRSF, and dynamic contrast-enhanced (DCE) MRI. Single-voxel MRSF data was recorded from the tumor (patients) - identified using DTI - or normal fibroglandular tissue (controls), in under 20 s. MRSF data was analyzed using in-house software. Linear mixed model analysis was used to compare the relaxation times of lipids in breast cancer VOIs vs. normal fibroglandular tissue.ResultsSeven distinguished lipid metabolite peaks were identified and their relaxation times were recorded. Of them, several exhibited statistically significant changes between controls and patients, with strong significance (p < 10(-3)) recorded for several of the lipid resonances at 1.3 ppm (T-1 = 355 +/- 17 ms vs. 389 +/- 27 ms), 4.1 ppm (T-1 = 255 +/- 86 ms vs. 127 +/- 33 ms), 5.22 ppm (T-1 = 724 +/- 81 ms vs. 516 +/- 62 ms), and 5.31 ppm (T-2 = 56 +/- 5 ms vs. 44 +/- 3.5 ms, respectively).ConclusionsThe application of MRSF to breast cancer imaging is feasible and achievable in clinically relevant scan time. Further studies are required to verify and comprehend the underling biological mechanism behind the differences in lipid relaxation times in cancer and normal fibroglandular tissue.

Automated summary

This study investigated the clinical relevance of the relaxation times of lipids within breast cancer and normal fibroglandular tissue using magnetic resonance spectroscopic fingerprinting (MRSF). The results showed significant differences in the relaxation times of certain lipids between breast cancer patients and healthy controls. The study demonstrates the feasibility and clinical applicability of using MRSF for breast cancer imaging.