@misc{9244060,
  abstract     = {{Four-dimensional flow magnetic resonance imaging (4D flow MRI) enables time-resolved assessment of intracardiac blood transport, but quantitative analysis requires workflows that convert complex velocity data into consistent and interpretable measures. This thesis aimed to develop and evaluate a semi-automated workflow in Segment for quantitative left-ventricular (LV) flow-component analysis. The workflow combines cine MRI-derived LV geometry with 4D flow MRI velocity data. An LV seed region is generated from cine short-axis segmentation and transferred to the 4D flow analysis space. From matched seed positions, pathlines are traced forward and backward in time using fourth-order Runge–Kutta (RK4) integration. Crossings of mitral and aortic analysis planes are used to classify particles into the four established LV flow components: Direct Flow, Retained Inflow, Delayed Ejection Flow, and Residual Volume. The implementation also provides visual output for quality control and calculates time-resolved LV kinetic energy as a complementary measure. Technical evaluation was performed using two controlled phantoms. In a circular-flow phantom, RK4 reproduced the analytic particle trajectory with near-perfect agreement and performed better than forward Euler. In a three-cylinder vessel phantom, the implemented plane-crossing and classification logic exactly reproduced the predefined component assignments. The workflow was then applied to 60 retrospective human datasets, including healthy adults, patients with heart failure, and healthy children. In the heart-failure datasets, the group with reduced ejection fraction showed markedly lower Direct Flow and higher Residual Volume than groups with higher ejection fraction, consistent with previously reported changes in LV flow-component distributions in heart failure. Automatic and manual plane-placement analyses produced similar group-level internal-consistency measures, while dataset-specific failures showed that visual review and manual adjustment are still needed. A proof-of-concept analysis further demonstrated the technical feasibility of applying the general framework to right-ventricular data. In conclusion, this thesis presents a practical Segment-based research workflow for quantitative LV flow-component analysis from 4D flow MRI. The method integrates particle tracing, rule-based classification, visualization, and kinetic-energy output within one analysis environment. Further development should focus on improving robustness, reducing user dependence, and strengthening the workflow for reproducible research use.}},
  author       = {{Hasselberg, Fredrik and Jensen, Axel}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Quantitative Flow Components in 4D Flow MRI}},
  year         = {{2026}},
}