Volumetric analysis of acute uncomplicated type B aortic dissection using an automated deep learning aortic zone segmentation model.

BACKGROUND: Machine learning techniques have shown excellent performance in three-dimensional medical image analysis, but have not been applied to acute uncomplicated type B aortic dissection (auTBAD) using Society for Vascular Surgery (SVS) and Society of Thoracic Surgeons (STS)-defined aortic zones. The purpose of this study was to establish a trained, automatic machine learning aortic zone segmentation model to facilitate performance of an aortic zone volumetric comparison between patients with auTBAD based on the rate of aortic growth. METHODS: Patients with auTBAD and serial imaging were identified. For each patient, imaging characteristics from two computed tomography (CT) scans were analyzed: (1) the baseline CT angiography (CTA) at the index admission and (2) either the most recent surveillance CTA or the most recent CTA before an aortic intervention. Patients were stratified into two comparative groups based on aortic growth: rapid growth (diameter increase of ≥5 mm/year) and no or slow growth (diameter increase of <5 mm/year). Deidentified images were imported into an open source software package for medical image analysis and images were annotated based on SVS/STS criteria for aortic zones. Our model was trained using four-fold cross-validation. The segmentation output was used to calculate aortic zone volumes from each imaging study. RESULTS: Of 59 patients identified for inclusion, rapid growth was observed in 33 patients (56%) and no or slow growth was observed in 26 patients (44%). There were no differences in baseline demographics, comorbidities, admission mean arterial pressure, number of discharge antihypertensives, or high-risk imaging characteristics between groups (P > .05 for all). Median duration between baseline and interval CT was 1.07 years (interquartile range [IQR], 0.38-2.57). Postdischarge aortic intervention was performed in 13 patients (22%) at a mean of 1.5 ± 1.2 years, with no difference between the groups (P > .05). Among all patients, the largest relative percent increases in zone volumes over time were found in zone 4 (13.9%; IQR, -6.82 to 35.1) and zone 5 (13.4%; IQR, -7.78 to 37.9). There were no differences in baseline zone volumes between groups (P > .05 for all). The average Dice coefficient, a performance measure of the model output, was 0.73. Performance was best in zone 5 (0.84) and zone 9 (0.91). CONCLUSIONS: We describe an automatic deep learning segmentation model incorporating SVS-defined aortic zones. The open source, trained model demonstrates concordance to the manually segmented aortas with the strongest performance in zones 5 and 9, providing a framework for further clinical applications. In our limited sample, there were no differences in baseline aortic zone volumes between patients with rapid growth and patients with no or slow growth.

Outcomes of Patients with Acute Type B Aortic Dissection and High-Risk Features.

BACKGROUND: Recently the Society for Vascular Surgery (SVS) and Society for Thoracic Surgeons (STS) published contemporary guidelines clearly defining complicated versus uncomplicated acute type B aortic dissections (TBADs) with an additional high-risk grouping. Few studies have evaluated outcomes associated with "high-risk" TBADs. The objective of this study was to assess differences in demographics, clinical presentation, symptom onset, and outcomes in high-risk patients that underwent either thoracic endovascular aortic repair (TEVAR) or best medical management for acute TBAD compared to those with complicated and uncomplicated acute TBAD. METHODS: Patients admitted with acute TBADs from a single academic medical center from October 2011 to March 2020 were analyzed. Per the STS/SVS 2020 guidelines, high risk was defined as refractory pain/hypertension, bloody pleural effusion, aortic diameter >4 cm, false lumen diameter >22 mm, radiographic malperfusion, and early readmission, and complicated was defined as ruptured/malperfusion presentation. Uncomplicated patients were those without malperfusion/rupture and without high-risk features. The primary end-point was inpatient mortality. Secondary end-points included complications, reintervention, and survival. RESULTS: Of the 159 patients identified with acute TBAD, 63 (40%) met the high-risk criteria. In the high-risk cohort, 38 (60%) underwent TEVAR (HR-TEVAR), with refractory pain as the most common indication, while 25 (40%) were managed medically (HR-medical). Malperfusion or rupture was present in 63 (40%) patients (complicated TBAD (C-TBAD)), all of whom underwent TEVAR. An additional 33 patients had no high-risk features and were all managed medically (uncomplicated TBAD). There were no differences in age, body mass index, and race between groups. Among the 4 groups, there were variable distributions in sex, insurance status, and incidence of several baseline comorbidities including congestive heart failure, chronic obstructive pulmonary disease, and renal dysfunction (P < 0.05 for all). C-TBAD had increased length of stay (12, interquartile range [IQR] 9-22) compared to HR-TEVAR (11.5, IQR 7-15), HR-medical (6, IQR 5-8), and uncomplicated TBAD (7, IQR 5-10) (P < 0.01). C-TBAD had decreased days from admission to repair (0, IQR 0-2) compared to HR-TEVAR (3.5, IQR 1-8) (P < 0.01). C-TBAD patients had worse 3-year survival compared to other groups (log-rank P < 0.01), although when in-hospital mortality was excluded, survival was similar among groups (P = 0.37). Of patients initially managed medically, outpatient TEVAR was performed in 6 (24%) HR-medical and 4 (12%) uncomplicated patients, with no difference between rate of intervention between groups (P = 0.22). CONCLUSIONS: High-risk features, as defined in updated SVS/STS guidelines, are common in patients presenting with acute TBAD. High-risk patients had acceptable outcomes when managed either surgically or medically. High-risk patients that underwent TEVAR had improved perioperative outcomes and mortality compared to those undergoing TEVAR for C-TBAD, a finding which may help guide preoperative risk stratification and patient counseling.

Sarcopenia is a Poor Predictor of Outcomes in Elective Colectomy for Diverticulitis.

BACKGROUND: Sarcopenia is associated with adverse perioperative outcomes in patients undergoing operations for malignancy, but its influence on patients undergoing elective colectomy for diverticulitis is unknown. We hypothesized that sarcopenia is associated with adverse perioperative events in patients undergoing elective colectomy for diverticulitis. METHODS: Comorbidities, operative characteristics, and postoperative complications were extrapolated from our institutional EMR in patients undergoing elective colectomy for diverticulitis from 2016 to 2020. Sarcopenia was calculated using perioperative imaging and defined by standard skeletal muscle index (SMI) and psoas muscle index (PMI) thresholds. Univariate analysis was used to compare sarcopenic and non-sarcopenic patients. RESULTS: 148 patients met inclusion criteria. Using SMI thresholds, 95 patients (64%) were sarcopenic. With SMI criteria, sarcopenic patients were older (67 vs 52 years old; P < .01) and had lower BMIs (26.2 vs 34.0, respectively; P < .001) than non-sarcopenic patients. There were no differences in baseline characteristics, postoperative complications, and non-home discharge between groups (P > .05 for all). Postoperative length of stay was greater in sarcopenic patients (3 IQR 2-5 vs 2 IQR 2-3 days; P < .01). Using PMI thresholds, 68 (46%) met criteria for sarcopenia. Using PMI thresholds, sarcopenic patients were older (68 vs 57.5 years old; P < .01) and had lower BMIs (25.8 vs 32.8; P < .01). There were no differences in comorbidities or measured operative outcomes between groups (P > .05 for all), other than postoperative length of stay which was longer in the sarcopenic group (3.5 IQR 3-5 vs 2 IQR 2-3; P < .01). CONCLUSIONS: Incidence of sarcopenia was high in patients undergoing elective colectomy for diverticulitis in our practice, but sarcopenia was not associated with adverse perioperative outcomes. In select patients, elective colectomy for diverticulitis can be safely performed in the presence of sarcopenia.

Resolvin D2/GPR18 signaling enhances monocytic myeloid-derived suppressor cell function to mitigate abdominal aortic aneurysm formation.

Abdominal aortic aneurysm (AAA) formation is a chronic vascular pathology characterized by inflammation, leukocyte infiltration and vascular remodeling. The aim of this study was to delineate the protective role of Resolvin D2 (RvD2), a bioactive isoform of specialized proresolving lipid mediators, via G-protein coupled receptor 18 (GPR18) receptor signaling in attenuating AAAs. Importantly, RvD2 and GPR18 levels were significantly decreased in aortic tissue of AAA patients compared with controls. Furthermore, using an established murine model of AAA in C57BL/6 (WT) mice, we observed that treatment with RvD2 significantly attenuated aortic diameter, pro-inflammatory cytokine production, immune cell infiltration (neutrophils and macrophages), elastic fiber disruption and increased smooth muscle cell α-actin expression as well as increased TGF-ß2 and IL-10 expressions compared to untreated mice. Moreover, the RvD2-mediated protection from vascular remodeling and AAA formation was blocked when mice were previously treated with siRNA for GPR18 signifying the importance of RvD2/GPR18 signaling in vascular inflammation. Mechanistically, RvD2-mediated protection significantly enhanced infiltration and activation of monocytic myeloid-derived suppressor cells (M-MDSCs) by increasing TGF-ß2 and IL-10 secretions that mitigated smooth muscle cell activation in a GPR18-dependent manner to attenuate aortic inflammation and vascular remodeling via this intercellular crosstalk. Collectively, this study demonstrates RvD2 treatment induces an expansion of myeloid-lineage committed progenitors, such as M-MDSCs, and activates GPR18-dependent signaling to enhance TGF-ß2 and IL-10 secretion that contributes to resolution of aortic inflammation and remodeling during AAA formation.

Pharmacologic Inhibition of Ferroptosis Attenuates Experimental Abdominal Aortic Aneurysm Formation.

The pathogenesis of abdominal aortic aneurysm (AAA) formation involves vascular inflammation, thrombosis formation and programmed cell death leading to aortic remodeling. Recent studies have suggested that ferroptosis, an excessive iron-mediated cell death, can regulate cardiovascular diseases, including AAAs. However, the role of ferroptosis in immune cells, like macrophages, and ferroptosis-related genes in AAA formation remains to be deciphered. Single cell-RNA sequencing of human aortic tissue from AAA patients demonstrates significant differences in ferroptosis-related genes compared to control aortic tissue. Using two established murine models of AAA and aortic rupture in C57BL/6 (WT) mice, we observed that treatment with liproxstatin-1, a specific ferroptosis inhibitor, significantly attenuated aortic diameter, pro-inflammatory cytokine production, immune cell infiltration (neutrophils and macrophages), increased smooth muscle cell α-actin expression and elastic fiber disruption compared to mice treated with inactivated elastase in both pre-treatment and treatment after a small AAA had already formed. Lipidomic analysis using mass spectrometry shows a significant increase in ceramides and a decrease in intact lipid species levels in murine tissue compared to controls in the chronic AAA model on day 28. Mechanistically, in vitro studies demonstrate that liproxstatin-1 treatment of macrophages mitigated the crosstalk with aortic smooth muscle cells (SMCs) by downregulating MMP2 secretion. Taken together, this study demonstrates that pharmacological inhibition by liproxstatin-1 mitigates macrophage-dependent ferroptosis contributing to inhibition of aortic inflammation and remodeling during AAA formation.