Enhanced Extraction of Blood and Tissue Time-Activity Curves in Cardiac Mouse FDG PET Imaging by Means of Constrained Nonnegative Matrix Factorization
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Bibliographic record
Abstract
We propose an enhanced method to accurately retrieve time-activity curves (TACs) of blood and tissue from dynamic 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography (PET) cardiac images of mice. The method is noninvasive and consists of using a constrained nonnegative matrix factorization algorithm (CNMF) applied to the matrix ( <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mi>A</a:mi> </a:math> ) containing the intensity values of the voxels of the left ventricle (LV) PET image. CNMF factorizes <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" id="M2"> <c:mi>A</c:mi> </c:math> into nonnegative matrices <e:math xmlns:e="http://www.w3.org/1998/Math/MathML" id="M3"> <e:mi>H</e:mi> </e:math> and <g:math xmlns:g="http://www.w3.org/1998/Math/MathML" id="M4"> <g:mi>W</g:mi> </g:math> , respectively, representing the physiological factors (blood and tissue) and their associated weights, by minimizing an extended cost function. We verified our method on 32 C57BL/6 mice, 14 of them with acute myocardial infarction (AMI). With CNMF, we could break down the mouse LV into myocardial and blood pool images. Their corresponding TACs were used in kinetic modeling to readily determine the [18F]FDG influx constant ( <i:math xmlns:i="http://www.w3.org/1998/Math/MathML" id="M5"> <i:msub> <i:mrow> <i:mi>K</i:mi> </i:mrow> <i:mrow> <i:mi>i</i:mi> </i:mrow> </i:msub> </i:math> ) required to compute the myocardial metabolic rate of glucose. The calculated <k:math xmlns:k="http://www.w3.org/1998/Math/MathML" id="M6"> <k:msub> <k:mrow> <k:mi>K</k:mi> </k:mrow> <k:mrow> <k:mi>i</k:mi> </k:mrow> </k:msub> </k:math> values using CNMF for the heart of control mice were in good agreement with those published in the literature. Significant differences in <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" id="M7"> <m:msub> <m:mrow> <m:mi>K</m:mi> </m:mrow> <m:mrow> <m:mi>i</m:mi> </m:mrow> </m:msub> </m:math> values for the heart of control and AMI mice were found using CNMF. The values of the elements of <o:math xmlns:o="http://www.w3.org/1998/Math/MathML" id="M8"> <o:mi>W</o:mi> </o:math> agreed well with the LV structural changes induced by ligation of the left coronary artery. CNMF was compared with the recently published method based on robust unmixing of dynamic sequences using regions of interest (RUDUR). A clear improvement of signal separation was observed with CNMF compared to the RUDUR method.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it