Patient A.

<p>(A) Non-motion corrected PET image, (B) MAF corrected PET image, (C) LORMC corrected PET image, (D) reference PET image acquired without induced motion, and (E) MP-RAGE image of Patient A. The profiles along the white lines in the images A–D are shown in (F). (G) Subject motion quantified by the mean voxel displacement relative to the initial position is displayed as a black line (see step 2 of the framing algorithm for details). Yellow and white horizontal stripes mark the framing calculated with the framing algorithm consisting of 12 frames. (H) Depicts the residual intra-frame motion for regular 1 minute framing and algorithmic framing. The residual intra-frame motion is quantified for each frame by the average voxel displacement relative to the mean frame position. For regular 1 minute framing (blue) the residual motion inside the frame is larger than for the automated framing algorithm (red). The width of the horizontal line denotes the frame length. The use of the framing algorithm reduces the average voxel distance to the mean frame position from.</p

Iida Brain Phantom.

<p>(A) Non-motion corrected, (B) MAF corrected, (C) LORMC corrected PET images, and (D) MP-RAGE image of the Iida brain phantom filled with ¹⁸F doped water. (E) On the right the profiles along the white lines in the images (A–C) are plotted. (F) Shows the patient motion quantified as the mean voxel displacement relative to the initial position and the 12 frames used in the motion corrected reconstructions. The blurring due to motion is reduced in the motion corrected images.</p

Generic projection data.

<p>(A) Sketch of the 3D data conversion between physical LORs and generic LORs in PRESTO, the physical detector blocks (outer part) define LORs that can be interpolated to the Generic Cylinder (inner part). Intersection points (red dots) pick up unique generic crystal combinations. (B) Generic projection data without considering subject motion. (C) Generic projection data with applied LORMC motion correction. For simple visualisation the projection data are sorted for view angle (vertical) and radial coordinate (horizontal) according to classical sinogram terminology.</p

<i>Superior colliculi</i> and tracer dynamics of Patient A.

<p>(A) Non-motion corrected image. (B) MAF corrected, (C) LORMC corrected PET images of Patient A, and (D) the corresponding MP-RAGE slice. The red arrows mark the <i>superior colliculi</i>. Uptake is visible only in the motion corrected PET images. (E) Dynamic study of the uptake in the <i>basal ganglia</i>. Error bars show the standard deviation of uptake values in the region of interest. The motion corrected (MAF) time activity curve appears more stable than the non motion corrected time activity curve.</p

Motion estimation accuracy.

<p>Phantom study on the influence of parallel imaging on the accuracy of the motion parameters. (A) Mean voxel displacement relative to the initial position calculated from the motion parameters extracted from the MP-RAGE measurements of the Iida Brain phantom. (B) RMS of the mean voxel position error for the four EPI protocols measured with GRAPPA factors of R = 1 to R = 4. The mean of ten measurements is shown. Error bars mark the standard deviation. Please note the error bars being small due to a maximum relative standard deviation of 0.8%. Using GRAPPA increases the accuracy of the measured motion parameters.</p

Mean square difference analysis.

<p>Mean Square Differences as function of the number of iterations for the Iida phantom measurements in 12 different positions reconstructed with the LORMC and MAF methods. As reference image with high statistics the image of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048149#pone-0048149-g004" target="_blank">Figure 4C</a> is used for all evaluated low statistic images (3×12 s).</p

Sequence protocols.

<p>Sequence protocols.</p

Framing algorithm schematic.

<p>A schematic overview of the proposed framing algorithm which consists of four main steps. Step 1: identification of brain voxels from the first acquired EPI volume. (A) The top row shows EPI images and the bottom row shows the resulting binary mask with brain voxels marked in white. Step 2: calculation of the mean voxel displacement of the brain for each time-point of the EPI time series. (B) An example mean voxel displacement trace is shown. Step 3: set initial frame borders where a large change in displacement occurred between two consecutive scans. (C) The top graph shows the absolute volume-to-volume change of the mean voxel displacement. The bottom row shows the resulting frame borders overlaid on the mean voxel displacement. Step 4: Minimise intra-frame motion by setting of additional frame borders such that the intra-frame motion is minimal. (D) The resulting frame borders are shown as red stars overlaid on the mean voxel displacement trace.</p

Patient B.

<p>(A) Non-motion corrected, (B) MAF corrected, and (C) LORMC corrected PET images, (D) reference PET image without induced motion, along with (E) the corresponding MP-RAGE image of Patient B. The profiles (F) along the white lines in the images A–D are shown in the top right corner. (G) Patient motion is shown as mean voxel displacement relative to the initial patient position - the metric calculated in the second step of the framing algorithm.</p

Demographic and clinical characteristics of the hemodialysis patients and healthy control groups.

<p>All data shown as mean (SD), except where noted. Charlson Comorbidity Index (CCI) corrected for dialysis patients and corrected for age in the control group. CV = Cerebrovascular; py = pack years; CKD = Chronic kidney disease. Other causes include progression of CKD due to post-operative infections, reflux diseases, analgesic medication.</p><p>Demographic and clinical characteristics of the hemodialysis patients and healthy control groups.</p