Hofer, Jan

Introduction: In seniors, the prevalence of abdominal aortic aneurysms (AAA) is high (9-10%). We aim to characterize AAA growth rates (slow vs. rapid) to help inform management strategies, including individualized imaging surveillance frequency. Hypothesis: Modeling thrombosis may improve the characterization of AAAs' growth status. Methods: 3D geometrical AAA models with and without thrombosis (vessel lumen only) were generated for 70 human subjects using available contrast-enhanced CTA data. AAA growth rates were categorized as slow (< 5 mm/year) or rapid (≥ 5 mm/year) based on serial imaging. Python scripts were used to calculate geometrical parameters (83) with and without thrombosis. Patient-specific relevant health information was retrieved through a review of medical records. Support vector machine (SVM), a well-established machine learning method, was run with 10-fold cross-validation (100 iterations) to assess the predictive accuracy. Results: Among 70 AAAs studied, the ratio between rapidly-growing and slowly-growing was nearly 1:2. The combination of antihypertensive medication, coronary artery disease, juxta-aneurysm aortic size, and five geometrical parameters quantifying the extent of thrombosis provided the best accuracy for AAA's growth status. The area under receiving operating curve (AUROC) was 0.85, and total accuracy was 0.81, with 57% and 93% of rapidly- and slowly-growing AAAs correctly identified, respectively. Excluding patients with aneurysm thrombus, the AUROC and accuracy in predicting rapidly-growing AAAs decreased to 0.82 and 48%, respectively. Conclusions: machine-learning-based predictive modeling appears feasible for characterizing AAA's growth rate status. Manual aortic image segmentation, required for data analytics, is labor-intensive (on average, 1 hour). Leveraging artificial intelligence-based segmentation methodology may provide an automated solution to improve workflow and feasibility.

Objective: The aim of this study was to investigate the midterm outcomes of fenestrated and branched endovascular aortic repair (FB-EVAR) of pararenal (PRA) and thoracoabdominal aortic aneurysms (TAAAs). Summary Background Data: FB-EVAR has been associated with decreased morbidity compared to open repair, but there is limited midterm data. Methods: A total of 430 patients (302 males, mean age 74 ± 8 years) treated by FB-EVAR were enrolled in a prospective, nonrandomized investigational device exemption study. Endpoints included 30-day mortality and major adverse events (MAEs), freedom from all cause and aortic-related mortality, target vessel patency, and freedom from secondary intervention and target vessel instability. Results: There were 133 PRAs and 297 TAAAs with 1673 renal-mesenteric arteries incorporated by fenestrations or directional branches (3.9 ± 0.5 vessels/patient). At 30 days or within the hospital stay if longer than 30 days, there were 4 (0.9%) deaths. MAEs included new-onset dialysis in 8 patients (2%), permanent paraplegia or stroke in 10 patients each (2%), and respiratory failure requiring tracheostomy in 2 patients (0.5%). After a mean follow-up of 26 ± 20 months, there were 3 (0.7%) aortic-related deaths from SMA stent occlusion, gastrointestinal hemorrhage, or complications of open arch repair. At 5 years, freedom from all-cause and aortic-related mortality were 57% ± 5% and 98% ± 1%, respectively. Freedom from secondary intervention was 64% ± 4%, primary target vessel patency was 94% ± 1%, and freedom from target vessel instability was 89% ± 2% at same interval. One patient (0.2%) had nonfatal aneurysm treated using endovascular repair. Conclusion: FB-EVAR is safe and effective for treatment of PRA and TAAAs with low rate of aortic-related mortality and aneurysm rupture on midterm follow-up.

Purpose: To review outcomes of continuous motor/somatosensory-evoked potential (MEP/SSEP) monitoring, cerebrospinal fluid drainage, and selective use of iliofemoral conduits in patients undergoing endovascular repair of descending thoracic aneurysm (DTA) and thoracoabdominal aortic aneurysms (TAAAs). Methods: The clinical data of 49 patients (mean age 75±8 years; 38 men) who underwent endovascular repair of DTA and TAAAs (2011–2014) were reviewed. All patients had cerebrospinal fluid drainage, permissive hypertension (mean arterial pressure ≥80 mm Hg), and MEP/SSEP monitoring. There were 44 (90%) patients with TAAAs and 5 (10%) with DTA. Types I and II TAAAs were repaired in staged procedures. Iliofemoral conduits were used for small iliac arteries and to minimize time of lower extremity ischemia in patients with difficult anatomy. In patients with changes in MEP/SSEPs, a standardized protocol was employed to optimize spinal cord perfusion and restore lower extremity blood flow. Endpoints were mortality, spinal cord injury (SCI), and lower extremity ischemic complications. Results: Sixteen (33%) patients had staged TAAA repair. A total of 163 visceral arteries were targeted by fenestrations and branches (mean 3.7±1.0 vessels/patient). Temporary iliofemoral conduits were used in 16 limbs/14 patients. A stable MEP/SSEP was achieved in all patients. Thirty-one (63%) patients had a ≥75% decrease in MEP/SSEP amplitude in 50 limbs starting on average 75±28 minutes after obtaining vascular access. MEP/SSEP amplitude improved with maneuvers in 12 (39%) patients and returned to baseline with restoration of lower extremity flow in all except 1 patient who developed immediate SCI. Thirty-day mortality was 4%. Three (6%) patients had SCI, 2 permanent and 1 temporary at 14 days. There were no lower extremity ischemic complications. Conclusion: Neuromonitoring predicted immediate SCI and allowed use of a protocol to optimize spinal cord and lower extremity perfusion during complex endovascular aortic repair. Larger clinical experience is needed to evaluate the efficacy of neuromonitoring to prevent SCI.