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gammaSTAR: A framework for the development of dynamic, real‐time capable MR sequences.

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Title: gammaSTAR: A framework for the development of dynamic, real‐time capable MR sequences.
Authors: Konstandin, Simon1 (AUTHOR) simon.konstandin@mevis.fraunhofer.de, Günther, Matthias1,2,3 (AUTHOR), Hoinkiss, Daniel C.1 (AUTHOR)
Source: Magnetic Resonance in Medicine. Oct2025, Vol. 94 Issue 4, p1485-1499. 15p.
Subjects: Magnetic resonance imaging, Real-time control, Spectrum analysis instruments, Motion compensation (Signal processing), Diagnostic imaging, Real-time computing
Abstract: Purpose: To present the real‐time capability and advanced MR sequence library of the MR sequence development framework gammaSTAR. Methods: The presented platform consists of four different components: (1) a frontend for sequence development combined with a Python backend for sequence generation; (2) a Lua backend for the creation of hardware instructions; (3) a vendor‐specific driver for translation of these instructions into scanner‐specific objects; and (4) an interface for real‐time feedback capability. In vivo measurements of the same volunteer were performed for comparison of imaging and spectroscopy sequences implemented in this framework with those of one main vendor (Siemens Healthineers) at magnetic field strengths of 3 T and 1.5 T. Prospective motion correction was integrated into a spin echo EPI sequence to demonstrate the real‐time feedback capability. Results: The imaging and spectroscopy results of the gammaSTAR sequences show very similar image contrasts and qualities compared to those by the vendor. ADC maps were calculated and show values of (0.80 ± 0.14)10−3 mm2/s in white matter. Results of pseudo‐continuous arterial spin labeling gradient and spin‐echo (pCASL GRASE) and 3D radial UTE imaging demonstrate the ability to run complex sequences without long sequence preparation times. Prospective motion correction is possible by means of real‐time feedback and shows much fewer movement artifacts with mean voxel displacement of 1.63 mm (uncorrected) versus 0.37 mm (corrected). All images were reconstructed using the vendor's reconstruction pipeline. Conclusion: The platform gammaSTAR allows for MR sequence development with real‐time feedback capability demonstrated by a large number of MR sequences and applications. [ABSTRACT FROM AUTHOR]
Copyright of Magnetic Resonance in Medicine is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: gammaSTAR: A framework for the development of dynamic, real‐time capable MR sequences.
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  Data: <searchLink fieldCode="JN" term="%22Magnetic+Resonance+in+Medicine%22">Magnetic Resonance in Medicine</searchLink>. Oct2025, Vol. 94 Issue 4, p1485-1499. 15p.
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  Data: <searchLink fieldCode="DE" term="%22Magnetic+resonance+imaging%22">Magnetic resonance imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Real-time+control%22">Real-time control</searchLink><br /><searchLink fieldCode="DE" term="%22Spectrum+analysis+instruments%22">Spectrum analysis instruments</searchLink><br /><searchLink fieldCode="DE" term="%22Motion+compensation+%28Signal+processing%29%22">Motion compensation (Signal processing)</searchLink><br /><searchLink fieldCode="DE" term="%22Diagnostic+imaging%22">Diagnostic imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Real-time+computing%22">Real-time computing</searchLink>
– Name: Abstract
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  Data: Purpose: To present the real‐time capability and advanced MR sequence library of the MR sequence development framework gammaSTAR. Methods: The presented platform consists of four different components: (1) a frontend for sequence development combined with a Python backend for sequence generation; (2) a Lua backend for the creation of hardware instructions; (3) a vendor‐specific driver for translation of these instructions into scanner‐specific objects; and (4) an interface for real‐time feedback capability. In vivo measurements of the same volunteer were performed for comparison of imaging and spectroscopy sequences implemented in this framework with those of one main vendor (Siemens Healthineers) at magnetic field strengths of 3 T and 1.5 T. Prospective motion correction was integrated into a spin echo EPI sequence to demonstrate the real‐time feedback capability. Results: The imaging and spectroscopy results of the gammaSTAR sequences show very similar image contrasts and qualities compared to those by the vendor. ADC maps were calculated and show values of (0.80 ± 0.14)10−3 mm2/s in white matter. Results of pseudo‐continuous arterial spin labeling gradient and spin‐echo (pCASL GRASE) and 3D radial UTE imaging demonstrate the ability to run complex sequences without long sequence preparation times. Prospective motion correction is possible by means of real‐time feedback and shows much fewer movement artifacts with mean voxel displacement of 1.63 mm (uncorrected) versus 0.37 mm (corrected). All images were reconstructed using the vendor's reconstruction pipeline. Conclusion: The platform gammaSTAR allows for MR sequence development with real‐time feedback capability demonstrated by a large number of MR sequences and applications. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Magnetic Resonance in Medicine is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – SubjectFull: Spectrum analysis instruments
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              Text: Oct2025
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              Y: 2025
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