Rosette Cardiac MR Fingerprinting for Simultaneous T<sub>1</sub>, T<sub>2</sub>, <math xmlns="http://www.w3.org/1998/Math/MathML"> <semantics> <mrow><msubsup><mi>T</mi> <mn>2</mn> <mo>*</mo></msubsup> </mrow> <annotation>$$ {\mathrm{T}}_2^{\ast } $$</annotation></semantics> </math> , and Fat Fraction Mapping Using a Multi-Echo Deep Image Prior Reconstruction.
Authors
Affiliations (2)
Affiliations (2)
- Radiology, University of Michigan, Ann Arbor, Michigan, USA.
- Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA.
Abstract
Quantitative mapping of cardiac tissue properties is used clinically in diagnosis and monitoring of a wide variety of cardiac pathologies. Cardiac Magnetic Resonance Fingerprinting (cMRF) enables rapid and simultaneous quantification of multiple parameters in the myocardium from a single scan. In this work, a multi-echo cMRF acquisition is combined with a deep image prior framework to reconstruct cardiac T<sub>1</sub>, T<sub>2</sub>, <math xmlns="http://www.w3.org/1998/Math/MathML"> <semantics> <mrow><msubsup><mi>T</mi> <mn>2</mn> <mo>*</mo></msubsup> </mrow> <annotation>$$ {\mathrm{T}}_2^{\ast } $$</annotation></semantics> </math> , and fat fraction maps. A 2D, single-breathhold, ECG-gated rosette trajectory cMRF sequence was deployed to sensitize the signal to T<sub>1</sub>, T<sub>2</sub>, <math xmlns="http://www.w3.org/1998/Math/MathML"> <semantics> <mrow><msubsup><mi>T</mi> <mn>2</mn> <mo>*</mo></msubsup> </mrow> <annotation>$$ {\mathrm{T}}_2^{\ast } $$</annotation></semantics> </math> , and fat off-resonance effects. Data were processed using a deep image prior reconstruction trained with the cMRF encoding model to generate images consistent with the acquired k-space data. These images were used in curve fitting and pattern matching algorithms to generate T<sub>1</sub>, T<sub>2</sub>, <math xmlns="http://www.w3.org/1998/Math/MathML"> <semantics> <mrow><msubsup><mi>T</mi> <mn>2</mn> <mo>*</mo></msubsup> </mrow> <annotation>$$ {\mathrm{T}}_2^{\ast } $$</annotation></semantics> </math> and fat fraction maps. The technique was validated using numerical simulations, standard phantoms, and 28 healthy subjects. In phantoms, good agreement was observed between the proposed technique and gold-standard reference measurements. In healthy subjects, measurements made with the deep image prior (DIP) reconstruction agreed with clinical cardiac measurements and demonstrated smaller voxel-level variance in a healthy population compared to iterative low-rank and direct matching reconstructions. The multi-echo cMRF acquisition coupled with a DIP reconstruction enables the simultaneous quantification of T<sub>1</sub>, T<sub>2</sub>, <math xmlns="http://www.w3.org/1998/Math/MathML"> <semantics> <mrow><msubsup><mi>T</mi> <mn>2</mn> <mo>*</mo></msubsup> </mrow> <annotation>$$ {\mathrm{T}}_2^{\ast } $$</annotation></semantics> </math> , and fat in the heart and demonstrates good agreement with conventional mapping approaches in phantom and in vivo experiments. Additionally, the DIP reconstruction provides accurate measurements with a lower voxel-level variance compared with direct gridding and iterative low-rank reconstruction methods.