Breast cancer imaging with glucosamine CEST (chemical exchange saturation transfer) MRI: first human experience.
Objectives: This study aims to evaluate the feasibility of imaging breast cancer with glucosamine (GlcN) chemical exchange saturation transfer (CEST) MRI technique to distinguish between tumor and surrounding tissue, compared to the conventional MRI method.Methods: Twelve patients with newly diagnos...
| Publicado en: | European Radiology Vol. 32; no. 11; pp. 7365 - 7374 |
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| Autores principales: | , , , , , , |
| Formato: | diagnostic images research tables/charts Journal Article |
| Publicado: |
Springer Nature
Nov2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=160256584&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 160256584 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09387994 NPH jtl: European Radiology issn: 09387994 maglogo: N pubinfo: dt: Nov2022 vid: 32 iid: 11 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 160256584 160256584 NLM35420304 160256584 10.1007/s00330-022-08772-w NLM35420304 160256584 ppf: 7365 ppct: 9 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Breast cancer imaging with glucosamine CEST (chemical exchange saturation transfer) MRI: first human experience. aug: au: Rivlin, Michal Anaby, Debbie Nissan, Noam Zaiss, Moritz Deshmane, Anagha Navon, Gil Sklair-Levy, Miri affil: School of Chemistry, Tel-Aviv University, Levanon St., 6997801, Tel Aviv, Israel sug: subj: Breast Neoplasms Pathology Breast Neoplasms Magnetic Resonance Imaging Methods Middle Age Glucosamine Prospective Studies Algorithms Female Scales Arthritis Impact Measurement Scales Middle Aged: 45-64 years Female ab: Objectives: This study aims to evaluate the feasibility of imaging breast cancer with glucosamine (GlcN) chemical exchange saturation transfer (CEST) MRI technique to distinguish between tumor and surrounding tissue, compared to the conventional MRI method.Methods: Twelve patients with newly diagnosed breast tumors (median age, 53 years) were recruited in this prospective IRB-approved study, between August 2019 and March 2020. Informed consent was obtained from all patients. All MRI measurements were performed on a 3-T clinical MRI scanner. For CEST imaging, a fat-suppressed 3D RF-spoiled gradient echo sequence with saturation pulse train was applied. CEST signals were quantified in the tumor and in the surrounding tissue based on magnetization transfer ratio asymmetry (MTRasym) and a multi-Gaussian fitting.Results: GlcN CEST MRI revealed higher signal intensities in the tumor tissue compared to the surrounding breast tissue (MTRasym effect of 8.12 ± 4.09%, N = 12, p = 2.2 E-03) with the incremental increase due to GlcN uptake of 3.41 ± 0.79% (N = 12, p = 2.2 E-03), which is in line with tumor location as demonstrated by T1W and T2W MRI. GlcN CEST spectra comprise distinct peaks corresponding to proton exchange between free water and hydroxyl and amide/amine groups, and relayed nuclear Overhauser enhancement (NOE) from aliphatic groups, all yielded larger CEST integrals in the tumor tissue after GlcN uptake by an averaged factor of 2.2 ± 1.2 (p = 3.38 E-03), 1.4 ± 0.4 (p =9.88 E-03), and 1.6 ± 0.6 (p = 2.09 E-02), respectively.Conclusion: The results of this initial feasibility study indicate the potential of GlcN CEST MRI to diagnose breast cancer in a clinical setup.Key Points: • GlcN CEST MRI method is demonstrated for its the ability to differentiate between breast tumor lesions and the surrounding tissue, based on the differential accumulation of the GlcN in the tumors. • GlcN CEST imaging may be used to identify metabolic active malignant breast tumors without using a Gd contrast agent. • The GlcN CEST MRI method may be considered for use in a clinical setup for breast cancer detection and should be tested as a complementary method to conventional clinical MRI methods. pubtype: Academic Journal doctype: diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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