Evaluation of Left Ventricular Flow Kinetic Energy by Four‐Dimensional Blood Flow <scp>MRI</scp> in Nondialysis Chronic Kidney Disease Patients
Bibliographic record
Abstract
BACKGROUND: Chronic kidney disease (CKD) is associated with increased, and early cardiovascular disease risk. Changes in hemodynamics within the left ventricle (LV) respond to cardiac remodeling. The LV hemodynamics in nondialysis CKD patients are not clearly understood. PURPOSE: To use four-dimensional blood flow MRI (4D flow MRI) to explore changes in LV kinetic energy (KE) and the relationship between LV KE and LV remodeling in CKD patients. STUDY TYPE: Retrospective. POPULATION: 98 predialysis CKD patients (Stage 3: n = 21, stage 4: n = 21, and stage 5: n = 56) and 16 age- and sex-matched healthy controls. FIELD STRENGTH/SEQUENCE: 3.0 T/balanced steady-state free precession (SSFP) cine sequence, 4D flow MRI with a fast field echo sequence, T1 mapping with a modified Look-Locker SSFP sequence, and T2 mapping with a gradient recalled and spin echo sequence. ASSESSMENT: Demographic characteristics (age, sex, height, weight, blood pressure, heart rate, aortic regurgitation, and mitral regurgitation) and laboratory data (eGFR, Creatinine, hemoglobin, ferritin, transferrin saturation, potassium, and carbon dioxide bonding capacity) were extracted from patient records. Myocardial T1, T2, LV ejection fraction, end diastolic volume (EDV), end systolic volume, LV flow components (direct flow, delayed ejection, retained inflow, and residual volume) and KE parameters (peak systolic, systolic, diastolic, peak E-wave, peak A-wave, E/A ratio, and global) were assessed. The KE parameters were normalized to EDV (KEiEDV). Parameters were compared between disease stage in CKD patients, and between CKD patients and healthy controls. STATISTICAL TESTS: Differences in clinical and imaging parameters between groups were compared using one-way ANOVA, Kruskal Walls and Mann-Whitney U tests, chi-square test, and Fisher's exact test. Pearson or Spearman's correlation coefficients and multiple linear regression analysis were used to compare the correlation between LV KE and other clinical and functional parameters. A P-value of <0.05 was considered significant. RESULTS: Compared with healthy controls, peak systolic (24.76 ± 5.40 μJ/mL vs. 31.86 ± 13.18 μJ/mL), systolic (11.62 ± 2.29 μJ/mL vs. 15.27 ± 5.10 μJ/mL), diastolic (7.95 ± 1.92 μJ/mL vs. 13.33 ± 5.15 μJ/mL), peak A-wave (15.95 ± 4.86 μJ/mL vs. 31.98 ± 14.51 μJ/mL), and global KEiEDV (9.40 ± 1.64 μJ/mL vs. 14.02 ± 4.14 μJ/mL) were significantly increased and the KEiEDV E/A ratio (1.16 ± 0.67 vs. 0.69 ± 0.53) was significantly decreased in CKD patients. As the CKD stage progressed, both diastolic KEiEDV (10.45 ± 4.30 μJ/mL vs. 12.28 ± 4.85 μJ/mL vs. 14.80 ± 5.06 μJ/mL) and peak E-wave KEiEDV (15.30 ± 7.06 μJ/mL vs. 14.69 ± 8.20 μJ/mL vs. 19.33 ± 8.29 μJ/mL) increased significantly. In multiple regression analysis, global KEiEDV (β* = 0.505; β* = 0.328), and proportion of direct flow (β* = -0.376; β* = -0.410) demonstrated an independent association with T1 and T2 times. DATA CONCLUSION: 4D flow MRI-derived LV KE parameters show altered LV adaptations in CKD patients and correlate independently with T1 and T2 mapping that may represent myocardial fibrosis and edema. TECHNICAL EFFICACY: Stage 3.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".