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Profile-encoding reconstruction for multiple-acquisition balanced steady-state free precession imaging.

Efe Ilicak1,2, Lutfi Kerem Senel1, Erdem Biyik1

  • 1Department of Electrical and Electronics Engineering, Bilkent University, Ankara, Turkey.

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A new method, profile-encoding reconstruction (PE-SSFP), improves MRI scan efficiency by jointly processing data across phase cycles. This technique enhances image quality and structural information preservation, especially at higher acceleration factors.

Keywords:
SSFPbanding artifactcompressed sensingencodingmagnetization profilereconstruction

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Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Medical Imaging
  • Biomedical Engineering

Background:

  • Maintaining scan-efficiency in multiple-acquisition balanced steady-state free precession (bSSFP) imaging is crucial.
  • Individual reconstruction of phase-cycled acquisitions can neglect valuable correlated structural information.
  • Existing acceleration methods like compressed-sensing and parallel imaging (ESPIRiT) have limitations in preserving image quality.

Purpose of the Study:

  • To propose an improved acceleration framework for multiple-acquisition bSSFP imaging.
  • To develop a method that jointly processes undersampled data across multiple phase cycles.
  • To enhance image quality and preserve structural information at higher acceleration factors.

Main Methods:

  • Phase-cycled imaging was modeled as a profile-encoding problem.
  • A novel profile-encoding reconstruction (PE-SSFP) was developed to recover missing data.
  • PE-SSFP utilized joint sparsity and total-variation penalties across phase cycles and was compared to individual compressed-sensing and ESPIRiT reconstructions.

Main Results:

  • PE-SSFP demonstrated improved image quality in brain and knee imaging compared to individual compressed-sensing and ESPIRiT, particularly for higher N values.
  • On average, PE-SSFP improved peak Signal-to-Noise Ratio (SNR) by 3.8 dB and structural similarity by 1.4% over individual compressed-sensing.
  • PE-SSFP achieved higher improvements over ESPIRiT, with peak SNR increased by 5.6 dB and structural similarity by 7.1%.

Conclusions:

  • PE-SSFP attains superior image quality and preserves high-spatial-frequency information at high acceleration factors compared to conventional methods.
  • The proposed PE-SSFP technique offers improved reliability against field inhomogeneity in scan-efficient bSSFP imaging.
  • PE-SSFP represents a promising advancement for accelerated bSSFP MRI.