Acquisition scheme of all acquisitions performed in this work.

<p>The regular IR-MAP acquisition consists of one inversion followed by a spoiled gradient-echo data collection (green). The segmented reference is acquired by performing multiple IR-LL acquisitions, each of which is followed by a 15s break for relaxation before the next inversion (orange). Using IR-MAP reconstructions for multiple of the acquired IR-LL datasets, a reproducibility study was carried out (blue).</p

MAPrecon

This package "MAPrecon.rar" is an addition to the package "MAPbox.rar". In case you don't want to do any reconstructions yourself and only want to perform the data analysis using already reconstructed data, additionally download this file and follow the instructions in "readme2.txt"

In vivo images.

<p>IR-MAP reconstruction and the segmented IR-LL reference of volunteers V3 and V7 at exemplary inversion times.</p

Phantom measurement.

<p>a: T₁ maps of the segmented IR reconstruction (left), the IR-MAP reconstruction of the single-inversion IR-LL acquisition (center) and the segmented IR-LL reference (right) and the differences (bottom). b: Reference IR-LL images and IR-MAP reconstructions for exemplary inversion times.</p

T₁ maps of the IR-MAP reconstruction (left) and the segmented IR-LL reference (center) as well as a difference (right) for volunteers V3 and V7.

<p>T₁ maps of the IR-MAP reconstruction (left) and the segmented IR-LL reference (center) as well as a difference (right) for volunteers V3 and V7.</p

MAPbox

This package "MAPbox.rar" contains all raw data and reconstruction code (in MATLAB) that is needed to reconstruct the T1 maps of the phantom & volunteer study of the Manuscript "Model-Based Acceleration of Look-Locker T1 Mapping" which is to be published in PLOS ONE in 2015. If you only need the reconstructed data, please additionally download "MAPrecon.rar"

Reproducibility study.

<p>Shown are the mean T₁ values obtained from IR-MAP reconstructions of ten consecutive IR-LL acquisitions, each of which was followed by a 15 second break for relaxation. While a) shows the results in the seven ROIs of the phantom (A-G), b) depicts the ROIs used for evaluation of T₁ in WM, GM and CSF of volunteer V7.</p

Table2_No-wait inversion—a novel model for T1 mapping from inversion recovery measurements without the waiting times.docx

Introduction: Quantification of longitudinal relaxation time T1 gained interest as an important MR-inducible tissue property for tissue characterization. Standard inversion recovery (IR) measurements for T1 determination take a prohibitively long time, and signal models assume a perfect inversion. Acceleration is possible by using the Look–Locker (LL) technique or other accelerated, model-based algorithms. However, the calculation of real T1 values from LL acquisitions necessitates the knowledge of equilibrium magnetization M0. Thus, usually, a waiting time to allow for free relaxation between global inversion pulses must be implemented. This study aims to introduce a novel model-based fitting approach for T1 mapping without the need for such waiting times.Methods: Single-inversion spiral LL spoiled gradient echo acquisitions were performed in a phantom and eight healthy volunteers using a 1.5T magnetic resonance imaging (MRI) scanner. The measurements comprised two parts, one without magnetization preparation and a second featuring a global inversion pulse preparation before each of the 35 slices. Acquisition was performed without any waiting time in between slices, i.e., before the inversion pulses. T1 maps were calculated based on an iterative model-based reconstruction algorithm which combines the information from these two measurements, with and without inversion.Results: Accurate T1 maps were obtained in phantom and volunteer measurements. ROI-based mean T1 values differ by an average of 1.5% in the phantom and 5% in vivo between reference measurements and the proposed method. The combined fit benefits from both the information obtained in the inversion prepared and the unprepared measurements. The former provides a large dynamic range for accurate model-based fitting of the relaxation process, while the latter provides equilibrium magnetization M0, necessary to obtain accurate T1 values from a LL-like acquisition.Conclusion: The proposed model of a combined fit of an inversion-prepared and an unprepared measurement allows for robust fast T1 mapping, even in cases of imperfect inversion due to skipped waiting times for magnetization recovery. Thus, it can render long waiting times in between inversion pulses redundant.</p

Image2_No-wait inversion—a novel model for T1 mapping from inversion recovery measurements without the waiting times.TIF

Introduction: Quantification of longitudinal relaxation time T1 gained interest as an important MR-inducible tissue property for tissue characterization. Standard inversion recovery (IR) measurements for T1 determination take a prohibitively long time, and signal models assume a perfect inversion. Acceleration is possible by using the Look–Locker (LL) technique or other accelerated, model-based algorithms. However, the calculation of real T1 values from LL acquisitions necessitates the knowledge of equilibrium magnetization M0. Thus, usually, a waiting time to allow for free relaxation between global inversion pulses must be implemented. This study aims to introduce a novel model-based fitting approach for T1 mapping without the need for such waiting times.Methods: Single-inversion spiral LL spoiled gradient echo acquisitions were performed in a phantom and eight healthy volunteers using a 1.5T magnetic resonance imaging (MRI) scanner. The measurements comprised two parts, one without magnetization preparation and a second featuring a global inversion pulse preparation before each of the 35 slices. Acquisition was performed without any waiting time in between slices, i.e., before the inversion pulses. T1 maps were calculated based on an iterative model-based reconstruction algorithm which combines the information from these two measurements, with and without inversion.Results: Accurate T1 maps were obtained in phantom and volunteer measurements. ROI-based mean T1 values differ by an average of 1.5% in the phantom and 5% in vivo between reference measurements and the proposed method. The combined fit benefits from both the information obtained in the inversion prepared and the unprepared measurements. The former provides a large dynamic range for accurate model-based fitting of the relaxation process, while the latter provides equilibrium magnetization M0, necessary to obtain accurate T1 values from a LL-like acquisition.Conclusion: The proposed model of a combined fit of an inversion-prepared and an unprepared measurement allows for robust fast T1 mapping, even in cases of imperfect inversion due to skipped waiting times for magnetization recovery. Thus, it can render long waiting times in between inversion pulses redundant.</p

Table1_No-wait inversion—a novel model for T1 mapping from inversion recovery measurements without the waiting times.docx

Introduction: Quantification of longitudinal relaxation time T1 gained interest as an important MR-inducible tissue property for tissue characterization. Standard inversion recovery (IR) measurements for T1 determination take a prohibitively long time, and signal models assume a perfect inversion. Acceleration is possible by using the Look–Locker (LL) technique or other accelerated, model-based algorithms. However, the calculation of real T1 values from LL acquisitions necessitates the knowledge of equilibrium magnetization M0. Thus, usually, a waiting time to allow for free relaxation between global inversion pulses must be implemented. This study aims to introduce a novel model-based fitting approach for T1 mapping without the need for such waiting times.Methods: Single-inversion spiral LL spoiled gradient echo acquisitions were performed in a phantom and eight healthy volunteers using a 1.5T magnetic resonance imaging (MRI) scanner. The measurements comprised two parts, one without magnetization preparation and a second featuring a global inversion pulse preparation before each of the 35 slices. Acquisition was performed without any waiting time in between slices, i.e., before the inversion pulses. T1 maps were calculated based on an iterative model-based reconstruction algorithm which combines the information from these two measurements, with and without inversion.Results: Accurate T1 maps were obtained in phantom and volunteer measurements. ROI-based mean T1 values differ by an average of 1.5% in the phantom and 5% in vivo between reference measurements and the proposed method. The combined fit benefits from both the information obtained in the inversion prepared and the unprepared measurements. The former provides a large dynamic range for accurate model-based fitting of the relaxation process, while the latter provides equilibrium magnetization M0, necessary to obtain accurate T1 values from a LL-like acquisition.Conclusion: The proposed model of a combined fit of an inversion-prepared and an unprepared measurement allows for robust fast T1 mapping, even in cases of imperfect inversion due to skipped waiting times for magnetization recovery. Thus, it can render long waiting times in between inversion pulses redundant.</p