English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Multiparametric magnetic resonance imaging (MRI) can be used to characterize many cancer subtypes including ovarian cancer. Quantitative mapping of MRI relaxation values, such as T  1 and T  2 mapping, is promising for improving tumor assessment beyond conventional qualitative T  1 - and T  2 -weighted images. However, quantitative MRI relaxation mapping methods often involve long scan times due to sequentially measuring many parameters. Magnetic resonance fingerprinting (MRF) is a new method that enables fast quantitative MRI by exploiting the transient signals caused by the variation of pseudorandom sequence parameters. These transient signals are then matched to a simulated dictionary of T  1 and T  2 values to create quantitative maps. The ability of MRF to simultaneously measure multiple parameters, could represent a new approach to characterizing cancer and assessing treatment response. This feasibility study investigates MRF for simultaneous T  1 , T  2 , and relative proton density (rPD) mapping using ovarian cancer as a model system.

Feasibility of Quantitative Magnetic Resonance Fingerprinting in Ovarian Tumors for T1 and T2 Mapping in a PET/MR Setting

Feasibility of Quantitative Magnetic Resonance Fingerprinting in Ovarian Tumors for T₁ and T₂ Mapping in a PET/MR Setting