4D Flow with Compressed Sensing for the Evaluation of Intracranial Aneurysmal Flow Patterns

Background: 4D flow (4DF) magnetic resonance imaging (MRI) offers a promising way to evaluate blood flow patterns in intracranial aneurysms, although long scan times present a major limitation to broad clinical implementation. Compressed sensing (CS), an accelerated imaging technique using strategically undersampled data for data reconstruction, offers a possible solution to reduce scan times. The aim of this study was to understand the effects and limitations of varying compressed sensing acceleration factors, R, at different resolutions in in vitro 4D flow acquisitions.Methods: This study employed a phantom depicting a saccular aneurysm. Experiment 1 evaluated the reliability of 4D flow with varying levels of compressed sensing acceleration factors (R=7.6, 12.8, and 16.6). Experiment 2 assessed the effects of varying resolutions (0.5, 1.0, 1.5, and 2.0 mm) with a compressed sensing R=12.8. Qualitative analysis included a visual assessment of velocity vectors and streamlines. Quantitative analysis compared the velocity components, peak velocity, flow rate, and wall shear stress in each experiment. All studies were post-processed using a clinically-geared software as well as with an In-House engineering pipeline, with the purpose of understanding the advantages and disadvantages of each approach and validating any results.Results: The addition of compressed sensing reduced scan times to approximately 4-7 minutes. The In-House processing pipeline is superior to the clinical software in visualizing of velocity; visual analysis showed velocity overestimations in the R=16.8 streamlines, indicating the limits of compressed sensing to be 7.6 < R < 12.8. As expected, comparison of velocity components reflects a decrease in linear regression slopes and correlations as acceleration factors increased (m > 0.90 for all acceleration factors except R=16.6, and all r > 0.9). Experiment 2 highlights partial voluming effect at R=12.8: as resolutions decrease, velocities along the wall are less reliable than velocities furthest from the wall, which retain high slope and correlation values (both above 0.9 at 1.0 mm and 1.5 mm resolutions). High variability peak velocity, flow rate, and wall shear stress in both pipelines point to the need for a reliable way to post-process 4D flow.Conclusion: This study showed reliable velocity data can be obtained from 4D flow studies acquired with compressed sensing lower to moderate acceleration factors at higher resolutions. With clinically-acceptable scan times, the focus now shifts towards establishing a robust and validated workflow for 4D flow studies before clinical implementation can truly be feasible

Inter-observer Variability of Expert-derived Morphologic Risk Predictors in Aortic Dissection

OBJECTIVES: Establishing the reproducibility of expert-derived measurements on CTA exams of aortic dissection is clinically important and paramount for ground-truth determination for machine learning. METHODS: Four independent observers retrospectively evaluated CTA exams of 72 patients with uncomplicated Stanford type B aortic dissection and assessed the reproducibility of a recently proposed combination of four morphologic risk predictors (maximum aortic diameter, false lumen circumferential angle, false lumen outflow, and intercostal arteries). For the first inter-observer variability assessment, 47 CTA scans from one aortic center were evaluated by expert-observer 1 in an unconstrained clinical assessment without a standardized workflow and compared to a composite of three expert-observers (observers 2-4) using a standardized workflow. A second inter-observer variability assessment on 30 out of the 47 CTA scans compared observers 3 and 4 with a constrained, standardized workflow. A third inter-observer variability assessment was done after specialized training and tested between observers 3 and 4 in an external population of 25 CTA scans. Inter-observer agreement was assessed with intraclass correlation coefficients (ICCs) and Bland-Altman plots. RESULTS: Pre-training ICCs of the four morphologic features ranged from 0.04 (-0.05 to 0.13) to 0.68 (0.49-0.81) between observer 1 and observers 2-4 and from 0.50 (0.32-0.69) to 0.89 (0.78-0.95) between observers 3 and 4. ICCs improved after training ranging from 0.69 (0.52-0.87) to 0.97 (0.94-0.99), and Bland-Altman analysis showed decreased bias and limits of agreement. CONCLUSIONS: Manual morphologic feature measurements on CTA images can be optimized resulting in improved inter-observer reliability. This is essential for robust ground-truth determination for machine learning models. KEY POINTS: • Clinical fashion manual measurements of aortic CTA imaging features showed poor inter-observer reproducibility. • A standardized workflow with standardized training resulted in substantial improvements with excellent inter-observer reproducibility. • Robust ground truth labels obtained manually with excellent inter-observer reproducibility are key to develop reliable machine learning models

Registry of Aortic Diseases to Model Adverse Events and Progression (ROADMAP) in Uncomplicated Type B Aortic Dissection: Study Design and Rationale

PURPOSE To describe the design and methodological approach of a multicenter, retrospective study to externally validate a clinical and imaging-based model for predicting the risk of late adverse events in patients with initially uncomplicated type B aortic dissection (uTBAD). MATERIALS AND METHODS The Registry of Aortic Diseases to Model Adverse Events and Progression (ROADMAP) is a collaboration between 10 academic aortic centers in North America and Europe. Two centers have previously developed and internally validated a recently developed risk prediction model. Clinical and imaging data from eight ROADMAP centers will be used for external validation. Patients with uTBAD who survived the initial hospitalization between January 1, 2001, and December 31, 2013, with follow-up until 2020, will be retrospectively identified. Clinical and imaging data from the index hospitalization and all follow-up encounters will be collected at each center and transferred to the coordinating center for analysis. Baseline and follow-up CT scans will be evaluated by cardiovascular imaging experts using a standardized technique. RESULTS The primary end point is the occurrence of late adverse events, defined as aneurysm formation (≥6 cm), rapid expansion of the aorta (≥1 cm/y), fatal or nonfatal aortic rupture, new refractory pain, uncontrollable hypertension, and organ or limb malperfusion. The previously derived multivariable model will be externally validated by using Cox proportional hazards regression modeling. CONCLUSION This study will show whether a recent clinical and imaging-based risk prediction model for patients with uTBAD can be generalized to a larger population, which is an important step toward individualized risk stratification and therapy.Keywords: CT Angiography, Vascular, Aorta, Dissection, Outcomes Analysis, Aortic Dissection, MRI, TEVAR© RSNA, 2022See also the commentary by Rajiah in this issue

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

4D Flow with Compressed Sensing for the Evaluation of Intracranial Aneurysmal Flow Patterns

Background: 4D flow (4DF) magnetic resonance imaging (MRI) offers a promising way to evaluate blood flow patterns in intracranial aneurysms, although long scan times present a major limitation to broad clinical implementation. Compressed sensing (CS), an accelerated imaging technique using strategically undersampled data for data reconstruction, offers a possible solution to reduce scan times. The aim of this study was to understand the effects and limitations of varying compressed sensing acceleration factors, R, at different resolutions in in vitro 4D flow acquisitions.Methods: This study employed a phantom depicting a saccular aneurysm. Experiment 1 evaluated the reliability of 4D flow with varying levels of compressed sensing acceleration factors (R=7.6, 12.8, and 16.6). Experiment 2 assessed the effects of varying resolutions (0.5, 1.0, 1.5, and 2.0 mm) with a compressed sensing R=12.8. Qualitative analysis included a visual assessment of velocity vectors and streamlines. Quantitative analysis compared the velocity components, peak velocity, flow rate, and wall shear stress in each experiment. All studies were post-processed using a clinically-geared software as well as with an In-House engineering pipeline, with the purpose of understanding the advantages and disadvantages of each approach and validating any results.Results: The addition of compressed sensing reduced scan times to approximately 4-7 minutes. The In-House processing pipeline is superior to the clinical software in visualizing of velocity; visual analysis showed velocity overestimations in the R=16.8 streamlines, indicating the limits of compressed sensing to be 7.6 &lt; R &lt; 12.8. As expected, comparison of velocity components reflects a decrease in linear regression slopes and correlations as acceleration factors increased (m &gt; 0.90 for all acceleration factors except R=16.6, and all r &gt; 0.9). Experiment 2 highlights partial voluming effect at R=12.8: as resolutions decrease, velocities along the wall are less reliable than velocities furthest from the wall, which retain high slope and correlation values (both above 0.9 at 1.0 mm and 1.5 mm resolutions). High variability peak velocity, flow rate, and wall shear stress in both pipelines point to the need for a reliable way to post-process 4D flow.Conclusion: This study showed reliable velocity data can be obtained from 4D flow studies acquired with compressed sensing lower to moderate acceleration factors at higher resolutions. With clinically-acceptable scan times, the focus now shifts towards establishing a robust and validated workflow for 4D flow studies before clinical implementation can truly be feasible

Inter-observer variability of expert-derived morphologic risk predictors in aortic dissection.

OBJECTIVES: Establishing the reproducibility of expert-derived measurements on CTA exams of aortic dissection is clinically important and paramount for ground-truth determination for machine learning. METHODS: Four independent observers retrospectively evaluated CTA exams of 72 patients with uncomplicated Stanford type B aortic dissection and assessed the reproducibility of a recently proposed combination of four morphologic risk predictors (maximum aortic diameter, false lumen circumferential angle, false lumen outflow, and intercostal arteries). For the first inter-observer variability assessment, 47 CTA scans from one aortic center were evaluated by expert-observer 1 in an unconstrained clinical assessment without a standardized workflow and compared to a composite of three expert-observers (observers 2-4) using a standardized workflow. A second inter-observer variability assessment on 30 out of the 47 CTA scans compared observers 3 and 4 with a constrained, standardized workflow. A third inter-observer variability assessment was done after specialized training and tested between observers 3 and 4 in an external population of 25 CTA scans. Inter-observer agreement was assessed with intraclass correlation coefficients (ICCs) and Bland-Altman plots. RESULTS: Pre-training ICCs of the four morphologic features ranged from 0.04 (-0.05 to 0.13) to 0.68 (0.49-0.81) between observer 1 and observers 2-4 and from 0.50 (0.32-0.69) to 0.89 (0.78-0.95) between observers 3 and 4. ICCs improved after training ranging from 0.69 (0.52-0.87) to 0.97 (0.94-0.99), and Bland-Altman analysis showed decreased bias and limits of agreement. CONCLUSIONS: Manual morphologic feature measurements on CTA images can be optimized resulting in improved inter-observer reliability. This is essential for robust ground-truth determination for machine learning models. KEY POINTS: • Clinical fashion manual measurements of aortic CTA imaging features showed poor inter-observer reproducibility. • A standardized workflow with standardized training resulted in substantial improvements with excellent inter-observer reproducibility. • Robust ground truth labels obtained manually with excellent inter-observer reproducibility are key to develop reliable machine learning models

Registry of Aortic Diseases to Model Adverse Events and Progression (ROADMAP) in Uncomplicated Type B Aortic Dissection:Study Design and Rationale

PURPOSE: To describe the design and methodological approach of a multicenter, retrospective study to externally validate a clinical and imaging-based model for predicting the risk of late adverse events in patients with initially uncomplicated type B aortic dissection (uTBAD). MATERIALS AND METHODS: The Registry of Aortic Diseases to Model Adverse Events and Progression (ROADMAP) is a collaboration between 10 academic aortic centers in North America and Europe. Two centers have previously developed and internally validated a recently developed risk prediction model. Clinical and imaging data from eight ROADMAP centers will be used for external validation. Patients with uTBAD who survived the initial hospitalization between January 1, 2001, and December 31, 2013, with follow-up until 2020, will be retrospectively identified. Clinical and imaging data from the index hospitalization and all follow-up encounters will be collected at each center and transferred to the coordinating center for analysis. Baseline and follow-up CT scans will be evaluated by cardiovascular imaging experts using a standardized technique. RESULTS: The primary end point is the occurrence of late adverse events, defined as aneurysm formation (≥6 cm), rapid expansion of the aorta (≥1 cm/y), fatal or nonfatal aortic rupture, new refractory pain, uncontrollable hypertension, and organ or limb malperfusion. The previously derived multivariable model will be externally validated by using Cox proportional hazards regression modeling. CONCLUSION: This study will show whether a recent clinical and imaging-based risk prediction model for patients with uTBAD can be generalized to a larger population, which is an important step toward individualized risk stratification and therapy.Keywords: CT Angiography, Vascular, Aorta, Dissection, Outcomes Analysis, Aortic Dissection, MRI, TEVAR© RSNA, 2022See also the commentary by Rajiah in this issue