Aortic volume as an indicator of disease progression in patients with untreated infrarenal abdominal aneurysm

Type B Aortic Dissection CTA Collection with True and False Lumen Expert Annotations for the Development of AI-based Algorithms

Aortic dissections (ADs) are serious conditions of the main artery of the human body, where a tear in the inner layer of the aortic wall leads to the formation of a new blood flow channel, named false lumen. ADs affecting the aorta distally to the left subclavian artery are classified as a Stanford type B aortic dissection (type B AD). This is linked to substantial morbidity and mortality, however, the course of the disease for the individual case is often unpredictable. Computed tomography angiography (CTA) is the gold standard for the diagnosis of type B AD. To advance the tools available for the analysis of CTA scans, we provide a CTA collection of 40 type B AD cases from clinical routine with corresponding expert segmentations of the true and false lumina. Segmented CTA scans might aid clinicians in decision making, especially if it is possible to fully automate the process. Therefore, the data collection is meant to be used to develop, train and test algorithms.

The Value of Aortic Volume and Intraluminal Thrombus Quantification for Predicting Aortic Events after Endovascular Thoracic Aneurysm Repair

Objectives: To assess the ability of the aortic aneurysm volume (AAV), aneurysmal lumen volume (ALV), and aneurysmal thrombus volume (ATV) to predict the need for aortic reintervention when using the maximal aortic diameter as a reference. Methods: This monocentric retrospective study included 31 consecutive patients who underwent successful thoracic endovascular aortic repair (TEVAR) to treat an atheromatous thoracic aortic aneurysm. All patients underwent clinical and computed tomography angiography (CTA) for 3 years after TEVAR. The patients were categorized into group 0 if no aortic reintervention was required during the follow-up period and categorized into group 1 if they experienced a type I or III endoleak or aneurysm diameter increase requiring intervention. The maximum aneurysm sac diameter and the AAV, ALV, and ATV were calculated using CTA images obtained preoperatively (T0) and at 6-12 months (T1), 24 months (T2), and 36 months (T3) postoperatively, and their changes over time were analyzed. Correlations between diameter and changes in AAV, ALV, and ATV were assessed, and the association between diameter and volume changes and reintervetion was examined. The cutoff values for predicting the need for reintervention was determined using a receiver operating characteristic (ROC) curve. The accuracy of volume change versus diameter change for predicting the need for reintervention was analyzed. Results: There were no significant differences in terms of the mean aneurysm diameter or AAV, ALV or ATV between the groups at preoperative CTA or after one year of follow-up imaging. The mean ATV was higher in group 1 than in group 0 at 2 years (187.6 ± 86.3 mL vs. 114.7 ± 64.7 mL; p = 0.057) and after 3 years (195.0 ± 86.7 mL vs. 82.1 ± 39.9 mL; p = 0.013). The maximal diameter was greater in group 1 than in group 0 at 3 years (67.3 ± 9.5 mm vs. 55.3 ± 12.6 mm; p = 0.044). The rate of AAV change between T0 and T1 was significantly higher in group 1 (7 ± 4.5%) than in group 0 (-6 ± 6.8%; p < 0.001). The rate of ATV change between T1-T3 was significantly higher in group 1 than in group 0 (34 ± 40.9% vs. -13 ± 14.4% (p = 0.041)); similar results were observed for the rate of ATV change between T2 and T3 (27 ± 50.1% for group 1 vs. -8 ± 49.5% in group 0 (p < 0.001)). According to our multivariate analysis, the annual growth rate for AAV between T0 and T1 was the only independent factor that was significantly associated with aortic reintervention (area under the curve (AUC) = 0.84, OR = 1.57, p = 0.025; optimal cutoff +0.4%). An increase in the annual growth rate of the ATV between T0 and T3 was independently associated with the need for aortic reintervention (area under the curve (AUC) = 0.90, OR = 1.11, p = 0.0347; optimal cutoff +10.1%). Conclusions: Aortic volume analysis can predict the need for aortic reintervention more accurately and earlier than maximal aortic diameter.

One-year follow-up after active aortic aneurysm sac treatment with shape memory polymer devices during endovascular aneurysm repair

OBJECTIVE

To determine the safety and efficacy of treating abdominal aortic aneurysm (AAA) sacs with polyurethane shape memory polymer (SMP) devices during endovascular aneurysm repair (EVAR), using a technique to fully treat the target lumen after endograft placement (aortic flow volume minus the endograft volume). SMP devices self-expand in the sac to form a porous scaffold that supports thrombosis throughout its structure.

METHODS

Two identical prospective, multicenter, single-arm studies were conducted in New Zealand and the Netherlands. The study population was adult candidates for elective EVAR of an infrarenal AAA (diameter of ≥55 mm in men and ≥50 mm in women). Key exclusion criteria were an inability to adequately seal a common iliac artery aneurysm, patent sac feeding vessels of >4 mm, and a target lumen volume of <20 mL or >135 mL. Target lumen volumes were estimated by subtracting endograft volumes from preprocedural imaging-based flow lumen volumes. SMP devices were delivered immediately after endograft deployment via a 6F sheath jailed in a bowed position in the sac. The primary efficacy end point was technical success, defined as filling the actual target lumen volume with fully expanded SMP at the completion of the procedure. Secondary efficacy outcome measures during follow-up were the change in sac volume and diameter, rate of type II endoleak and type I or III endoleaks, and the rate of open repair and related reinterventions, with data collection at 30 days, 6 months, and 1 year (to date). Baseline sac volumes and diameters for change in sac size analyses were determined from 30-day imaging studies. Baseline and follow-up volumes were normalized by subtraction of the endograft volume.

RESULTS

Of 34 patients treated with SMP devices and followed per protocol, 33 patients were evaluable at 1 year. Preprocedural aneurysm volume was 181.4 mL (95% confidence interval [CI], 150.7-212.1 mL) and preprocedural aneurysm diameter was 60.8 mm (95% CI, 57.8-63.9 mm). The target lumen volume was 56.3 mL (95% CI, 46.9-65.8 mL). Technical success was 100% and the ratio of SMP fully expanded volume to estimated target lumen volume was 1.4 ± 0.3. Baseline normalized sac volume and diameter were 140.7 mL (95% CI, 126.6-154.9 mL) and 61.0 mm (95% CI, 59.7-62.3 mm). The adjusted mean percentage change in normalized volume at 1 year was -28.8% (95% CI, -35.3 to -22.3%; P < .001). The adjusted mean change in sac diameter at 1 year was -5.9 mm (95% CI, -7.5 to -4.4 mm; P < .001). At 1 year, 81.8% of patients (95% CI, 64.5%-93.0%) achieved a ≥10% decrease in normalized volume and 57.6% of patients (95% CI, 39.2%-74.5%) achieved a ≥5 mm decrease in diameter. No device- or study procedure-related major adverse events occurred through 1 year after the procedure.

CONCLUSIONS

Treatment of AAA sacs with SMP devices during EVAR resulted in significant sac volume and diameter regression at 1 year with an acceptable safety profile in this prospective study.

Stress Load and Ascending Aortic Aneurysms: An Observational, Longitudinal, Single-Center Study Using Computational Fluid Dynamics

Ascending aortic aneurysm (AAoA) is a silent disease with high mortality; however, the factors associated with a worse prognosis are not completely understood. The objective of this observational, longitudinal, single-center study was to identify the hemodynamic patterns and their influence on AAoA growth using computational fluid dynamics (CFD), focusing on the effects of geometrical variations on aortic hemodynamics. Personalized anatomic models were obtained from angiotomography scans of 30 patients in two different years (with intervals of one to three years between them), of which 16 (53%) showed aneurysm growth (defined as an increase in the ascending aorta volume by 5% or more). Numerically determined velocity and pressure fields were compared with the outcome of aneurysm growth. Through a statistical analysis, hemodynamic characteristics were found to be associated with aneurysm growth: average and maximum high pressure (superior to 100 Pa); average and maximum high wall shear stress (superior to 7 Pa) combined with high pressure (>100 Pa); and stress load over time (maximum pressure multiplied by the time interval between the exams). This study provides insights into a worse prognosis of this serious disease and may collaborate for the expansion of knowledge about mechanobiology in the progression of AAoA.

Current Imaging Strategies in Patients with Abdominal Aortic Aneurysms

BACKGROUND

 An abdominal aortic aneurysm (AAA) is defined as a localized dilatation of the abdominal aorta of ≥ 3 cm. With a prevalence of 4-8 %, AAA is one of the most common vascular diseases in Western society. Radiological imaging is an elementary component in the diagnosis, monitoring, and treatment planning of AAA patients.

METHOD

 This is a narrative review article on preoperative imaging strategies of AAA, incorporating expert opinions based on the current literature and standard-of-care practices from our own center. Examples are provided to illustrate clinical cases from our institution.

RESULTS AND CONCLUSION

 Radiological imaging plays a pivotal role in the initial diagnosis and monitoring of patients with AAA. Ultrasound is the mainstay imaging modality for AAA screening and surveillance. Contrast-enhanced CT angiography is currently considered the gold standard for preoperative imaging and image-based treatment planning in AAA repair. New non-contrast MR angiography techniques are robustly applicable and allow precise determination of aortic diameters, which is of critical importance, particularly with regard to current diameter-based surgical treatment guidelines. 3D imaging with multiplanar reformation and automatic centerline positioning enables more accurate assessment of the maximum aortic diameter. Modern imaging techniques such as 4D flow MRI have the potential to further improve individualized risk stratification in patients with AAA.

KEY POINTS

  · Ultrasound is the mainstay imaging modality for AAA screening and monitoring. · Contrast-enhanced CT angiography is the gold standard for preoperative imaging in AAA repair. · Non-contrast MR angiography allows for accurate monitoring of aortic diameters in AAA patients. · Measurement of aortic diameters is more accurate with 3D-CT/MRI compared to ultrasound. · Research seeks new quantitative imaging biomarkers for AAA risk stratification, e. g., using 4D flow MRI.

The Role of Aortic Volume in the Natural History of Abdominal Aortic Aneurysms and Post-Endovascular Aortic Aneurysm Repair Surveillance

There has been a debate about whether maximum diameter can be solely used to assess the natural history of abdominal aortic aneurysm. The aim of the present review is to collect all the available evidence on the role of abdominal aortic aneurysm (AAA) volume in the natural history of AAAs, including small untreated AAAs and AAAs treated by EVAR. The current literature appears to reinforce the role of volume as a supplementary measure for evaluating the natural history of AAA, in both intact AAAs and after EVAR. The clinical impact of AAA volume measurements remains unclear. Several studies show that volumetric analysis can assess changes in AAAs and predict successful endoluminal exclusion after EVAR more accurately than diameter. However, most studies lack strict standardized measurement criteria and well-defined outcome definitions. It remains unclear whether volumetry could replace diameter assessment in defining the risk of rupture of AAAs and identifying clinically relevant sac growth.

2022 ACC/AHA guideline for the diagnosis and management of aortic disease: A report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines

AIM

The "2022 ACC/AHA Guideline for the Diagnosis and Management of Aortic Disease" provides recommendations to guide clinicians in the diagnosis, genetic evaluation and family screening, medical therapy, endovascular and surgical treatment, and long-term surveillance of patients with aortic disease across its multiple clinical presentation subsets (ie, asymptomatic, stable symptomatic, and acute aortic syndromes).

METHODS

A comprehensive literature search was conducted from January 2021 to April 2021, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from PubMed, EMBASE, the Cochrane Library, CINHL Complete, and other selected databases relevant to this guideline. Additional relevant studies, published through June 2022 during the guideline writing process, were also considered by the writing committee, where appropriate.

STRUCTURE

Recommendations from previously published AHA/ACC guidelines on thoracic aortic disease, peripheral artery disease, and bicuspid aortic valve disease have been updated with new evidence to guide clinicians. In addition, new recommendations addressing comprehensive care for patients with aortic disease have been developed. There is added emphasis on the role of shared decision making, especially in the management of patients with aortic disease both before and during pregnancy. The is also an increased emphasis on the importance of institutional interventional volume and multidisciplinary aortic team expertise in the care of patients with aortic disease.

Value of aortic volumes assessed by automated segmentation of 3D MRI data in patients with thoracic aortic dilatation: A case-control study

PURPOSE

The purpose of this study was to investigate the benefit of aortic volumes compared to diameters or cross-sectional areas on three-dimensional (3D) magnetic resonance imaging (MRI) in discriminating between patients with dilated aorta and matched controls.

MATERIALS AND METHODS

Sixty-two patients (47 men and 15 women; median age, 66 years; age range: 33-86 years) with tricuspid aortic valve and ascending thoracic aorta aneurysm (TAV-ATAA) and 43 patients (35 men and 8 women; median age, 51 years; age range: 17-76 years) with bicuspid aortic valve and dilated ascending aorta (BAV) were studied. One group of 54 controls matched for age and sex to patients with TAV-ATAA (39 men and 15 women; median age, 68 years; age range: 33-81 years) and one group of 42 controls matched for age and sex to patients with BAV (34 men and 8 women; median age, 50 years; age range: 17-77 years) were identified. All participants underwent 3D MRI, used for 3D-segmentation for measuring aortic length, maximal diameter, maximal cross-sectional area (CSA) and volume for the ascending aorta.

RESULTS

An increase in ascending aorta volume (TAV-ATAA: +107%; BAV: +171% vs. controls; P < 0.001) was found, which was three times greater than the increase in diameter (TAV-ATAA: +29%; BAV: +40% vs. controls; P < 0.001). In differentiating patients with TAV-ATAA from their controls, the indexed ascending aorta volume showed better performances (AUC, 0.935 [95% confidence interval (CI): 0.882-0.989]; accuracy, 88.7% [95% CI: 82.9-94.5]) than indexed ascending aorta length (P < 0.001), indexed ascending aorta maximal diameter (P = 0.003) and indexed ascending aorta maximal CSA (P = 0.03). In differentiating patients with BAV from matched controls, indexed ascending aorta volume showed significantly better performances performance (AUC, 0.908 [95% CI: 0.829-0.987]; accuracy, 88.0% [95% CI: 80.9-95.0]) than indexed ascending aorta length (P = 0.02) and not different from indexed ascending aorta maximal diameter (P = 0.07) or from indexed ascending aorta maximal CSA (P = 0.27) CONCLUSION: Aortic volume measured by 3D-MRI integrates both elongation and luminal dilatation, resulting in greater classification performance than maximal diameter and length in differentiating patients with dilated ascending aorta or aneurysm from controls.

Ascending Aortic Volume: A Feasible Indicator for Ascending Aortic Aneurysm Elective Surgery?

Diameter-based criterion have been widely adopted for preventive surgery of ascending thoracic aortic aneurysm (ATAA). However, recent and growing evidence has shown that diameter-based methods may not be sufficient for identifying patients who are at risk of an ATAA. In this study, fluid-structure interaction (FSI) analysis was performed on one-hundred ATAA geometries reconstructed from clinical data to examine the relationship between hemodynamic conditions, ascending aortic volume (AAV), ascending aortic curvature, and aortic ratios measured from the reconstructed 3D models. The simulated hemodynamic and biomechanical parameters were compared among different groups of ATAA geometries classified based on AAV. The ATAAs with enlarged AAV showed significantly compromised hemodynamic conditions and higher mechanical wall stress. The maximum oscillatory shear index (OSI), particle residence time (PRT) and wall stress (WS) were significantly higher in enlarged ATAAs compared with controls (0.498 [0.497, 0.499] vs 0.499 [0.498, 0.499], p = 0.002, 312.847 [207.445, 519.391] vs 996.047 [640.644, 1573.140], p < 0.001, 769.680 [668.745, 879.795] vs 1072.000 [873.060, 1280.000] kPa, p < 0.001, respectively). Values were reported as median with interquartile range (IQR). AAV was also found to be more strongly correlated with these parameters compared to maximum diameter. The correlation coefficient between AAV and average WS was as high as 0.92 (p < 0.004), suggesting that AAV might be a feasible risk identifier for ATAAs. STATEMENT OF SIGNIFICANCE: Ascending thoracic aortic aneurysm is associated with the risk of dissection or rupture, creating life-threatening conditions. Current surgical intervention guidelines are purely diameter based. Recently, many studies proposed to incorporate other morphological parameters into the current clinical guidelines to better prevent severe adverse aortic events like rupture or dissection. The purpose of this study is to gain a better understanding of the relationship between morphological parameters and hemodynamic parameters in ascending aortic aneurysms using fluid-solid-interaction analysis on patient-specific geometries. Our results suggest that ascending aortic volume may be a better indicator for surgical intervention as it shows a stronger association with pathogenic hemodynamic conditions.

Abdominal Aortic Aneurysm Diameter versus Volume: A Systematic Review

Recently, AAA volume measurement has been proposed as a potentially valuable surveillance method in situations when diameter measurement might fail.

OBJECTIVE

The aim of this systematic review was to analyze the results of previous studies comparing AAA diameter and volume measurements.

METHODS

A systematic search in PubMed, Cochrane, and EMBASE databases was performed to identify studies investigating the use of diameter and volume measurements in AAA diagnosis and prognosis in English, German, and Russian, published until December 2022. The manuscripts were reviewed by three researchers and scored on the quality of the research using MINORS criteria.

RESULTS

After screening 752 manuscripts, 19 studies (n = 1690) were included. The majority (n = 17) of the manuscripts appeared to favor volume. It is, however, important to highlight the heterogeneity of methodologies and lack of standardized protocol for measuring both volume and diameter in the included studies, which hindered the interpretation of the results.

CONCLUSIONS

The clinical relevance of abdominal aortic aneurysm volume measurement is still unclear, although studies show favorable and promising results for volumetric changes in AAA, especially in follow-up after EVAR.

2022 ACC/AHA Guideline for the Diagnosis and Management of Aortic Disease: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines

AIM

The "2022 ACC/AHA Guideline for the Diagnosis and Management of Aortic Disease" provides recommendations to guide clinicians in the diagnosis, genetic evaluation and family screening, medical therapy, endovascular and surgical treatment, and long-term surveillance of patients with aortic disease across its multiple clinical presentation subsets (ie, asymptomatic, stable symptomatic, and acute aortic syndromes).

METHODS

A comprehensive literature search was conducted from January 2021 to April 2021, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from PubMed, EMBASE, the Cochrane Library, CINHL Complete, and other selected databases relevant to this guideline. Additional relevant studies, published through June 2022 during the guideline writing process, were also considered by the writing committee, where appropriate. Structure: Recommendations from previously published AHA/ACC guidelines on thoracic aortic disease, peripheral artery disease, and bicuspid aortic valve disease have been updated with new evidence to guide clinicians. In addition, new recommendations addressing comprehensive care for patients with aortic disease have been developed. There is added emphasis on the role of shared decision making, especially in the management of patients with aortic disease both before and during pregnancy. The is also an increased emphasis on the importance of institutional interventional volume and multidisciplinary aortic team expertise in the care of patients with aortic disease.

2022 ACC/AHA Guideline for the Diagnosis and Management of Aortic Disease: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines

AIM

The "2022 ACC/AHA Guideline for the Diagnosis and Management of Aortic Disease" provides recommendations to guide clinicians in the diagnosis, genetic evaluation and family screening, medical therapy, endovascular and surgical treatment, and long-term surveillance of patients with aortic disease across its multiple clinical presentation subsets (ie, asymptomatic, stable symptomatic, and acute aortic syndromes).

METHODS

A comprehensive literature search was conducted from January 2021 to April 2021, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from PubMed, EMBASE, the Cochrane Library, CINHL Complete, and other selected databases relevant to this guideline. Additional relevant studies, published through June 2022 during the guideline writing process, were also considered by the writing committee, where appropriate.

STRUCTURE

Recommendations from previously published AHA/ACC guidelines on thoracic aortic disease, peripheral artery disease, and bicuspid aortic valve disease have been updated with new evidence to guide clinicians. In addition, new recommendations addressing comprehensive care for patients with aortic disease have been developed. There is added emphasis on the role of shared decision making, especially in the management of patients with aortic disease both before and during pregnancy. The is also an increased emphasis on the importance of institutional interventional volume and multidisciplinary aortic team expertise in the care of patients with aortic disease.

AVT: Multicenter aortic vessel tree CTA dataset collection with ground truth segmentation masks

In this article, we present a multicenter aortic vessel tree database collection, containing 56 aortas and their branches. The datasets have been acquired with computed tomography angiography (CTA) scans and each scan covers the ascending aorta, the aortic arch and its branches into the head/neck area, the thoracic aorta, the abdominal aorta and the lower abdominal aorta with the iliac arteries branching into the legs. For each scan, the collection provides a semi-automatically generated segmentation mask of the aortic vessel tree (ground truth). The scans come from three different collections and various hospitals, having various resolutions, which enables studying the geometry/shape variabilities of human aortas and its branches from different geographic locations. Furthermore, creating a robust statistical model of the shape of human aortic vessel trees, which can be used for various tasks such as the development of fully-automatic segmentation algorithms for new, unseen aortic vessel tree cases, e.g. by training deep learning-based approaches. Hence, the collection can serve as an evaluation set for automatic aortic vessel tree segmentation algorithms.

Role of volume in small abdominal aortic aneurysm surveillance

OBJECTIVE

Current management of small abdominal aortic aneurysms (AAAs) primarily involves serial imaging surveillance of maximum transverse diameter (MTD) to estimate rupture risk. Other measurements, such as volume and tortuosity, are less well-studied and may help characterize and predict AAA progression. This study evaluated predictors of AAA volume growth and discusses the role of volume in clinical practice.

METHODS

Subjects from the Non-invasive Treatment of Abdominal Aortic Aneurysm Clinical Trial (baseline AAA MTD, 3.5-5.0 cm) with ≥2 computed tomography scans were included in this study (n = 250). Computed tomography scans were conducted approximately every 6 months over 2 years. MTD, volume, and tortuosity were used to model growth. Univariable and multivariable backwards elimination least squares regressions assessed associations with volume growth.

RESULTS

Baseline MTD accounted for 43% of baseline volume variance (P < .0001). Mean volume growth rate was 10.4 cm³/year (standard deviation, 8.8 cm³/year) (mean volume change +10.4%). Baseline volume accounted for 30% of volume growth variance; MTD accounted for 13% of volume growth variance. More tortuous aneurysms at baseline had significantly larger volume growth rates (difference, 32.8 cm³/year; P < .0001). Univariable analysis identified angiotensin II receptor blocker use (difference, -3.4 cm³/year; P = .02) and history of diabetes mellitus (difference, -2.8 cm³/year; P = .04) to be associated with lower rates of volume growth. Baseline volume, tortuosity index, current tobacco use, and absence of diabetes mellitus remained significantly associated with volume growth in multivariable analysis. AAAs that reached the MTD threshold for repair had a wide range of volumes: 102 cm³ to 142 cm³ in female patients (n = 5) and 105 cm³ to 229 cm³ in male patients (n = 20).

CONCLUSIONS

Baseline AAA volume and MTD were found to be moderately correlated. On average, AAA volume grows about 10% annually. Baseline volume, tortuosity, MTD, current tobacco use, angiotensin II receptor blocker use, and history of diabetes mellitus were predictive of volume growth over time.

Comparison of Outcomes Following EVAR Based on Aneurysm Diameter and Volume and Their Postoperative Variations

PURPOSE

to evaluate the impact of bi- and 3-dimensional preoperative aortic morphological features and their immediate postoperative variations on the outcome of abdominal aortic aneurysms (AAA) treated by endovascular exclusion with standard devices (EVAR).

MATERIALS AND METHODS

Double centre retrospective analysis of prospectively collected registry data of EVAR patients. For all patients, preoperative and 30-day computed tomographic angiography images (CTA) were reviewed. Preoperative maximum AAA diameter >59 mm and volume >159 cm³, and any 30-day postoperative increasing at CTA, were considered as potentially influencing the outcome. The outcome measures were: primary technical success; 30-day, 1-year, and mean follow-up reintervention, all-cause and AAA-related mortality rates, and also endoleak-related reinterventions.

RESULTS

Three hundred and thrity-three patients were enrolled. Mean preoperative and 30-day AAA diameter and volume were 50.4 mm ± 11.8 vs. 49.1 mm ± 12.1, and 112.9 cm3 ± 79.5 vs. 112.1 cm3 ± 80.5, respectively. Primary technical success was achieved in all cases. At 34.9 months follow-up, cumulative reintervention rate was 12.0%, mortality rates 7.2%, without AAA-related deaths. Endoleak-related reintervention rate was 7.5%. At uni- and multi-variate analysis, preoperative AAA diameter >59 mm, and AAA volume >159 cm³ were significantly associated to reintervention (P = 0.012; P = 0.002), and reintervention and death (P = 0.002; P = 0.001) during follow-up. Additionally, any increase in postoperative AAA diameter or volume was significantly associated with reintervention (P = 0.001, P = 0.001) and reintervention and death (P = 0.006, P = 0.001). Endoleak-related reintervention were also significantly associated with all of the analysed morphological parameters (P = 0.019, P = 0.005, P = 0.005, and P = 0.002, respectively).

CONCLUSIONS

Patients with larger baseline AAA size and volume as well as unfavourable early remodelling of the sac are associated to worse long-term EVAR outcome.

CT texture analysis predicts abdominal aortic aneurysm post-endovascular aortic aneurysm repair progression

The aim of this study is to investigate the role of early postoperative CT texture analysis in aneurysm progression. Ninety-nine patients who had undergone post-endovascular aneurysm repair (EVAR) infra-renal abdominal aortic aneurysm CT serial scans were enrolled from July 2014 to December 2019. The clinical and traditional imaging features were obtained. Aneurysm texture analysis was performed using three methods—the grey-level co-occurrence matrix (GLCM), the grey-level run length matrix (GLRLM), and the grey-level difference method (GLDM). A multilayer perceptron neural network was applied as a classifier, and receiver operating characteristic (ROC) curve analysis and area under the curve (AUC) analysis were employed to illustrate the classification performance. No difference was found in the morphological and clinical features between the expansion (+) and (−) groups. GLCM yielded the best performance with an accuracy of 85.17% and an AUC of 0.90, followed by GLRLM with an accuracy of 87.23% and an AUC of 0.8615, and GLDM with an accuracy of 86.09% and an AUC of 0.8313. All three texture analyses showed superior predictive ability over clinical risk factors (accuracy: 69.41%; AUC: 0.6649), conventional imaging features (accuracy: 69.02%; AUC: 0.6747), and combined (accuracy: 75.29%; AUC: 0.7249). Early post-EVAR arterial phase-derived aneurysm texture analysis is a better predictor of later aneurysm expansion than clinical factors and traditional imaging evaluation combined.

Evaluating the diagnostic accuracy of maximal aortic diameter, length and volume for prediction of aortic dissection

OBJECTIVE

Management of thoracic aortic aneurysms (TAAs) comprises regular diameter follow-up until the indication criterion for prophylactic surgery is reached. However, this approach is unable to predict the majority of acute type A aortic dissections (ATAADs). The current study aims to evaluate the diagnostic accuracy of ascending aortic diameter, length and volume for occurrence of ATAAD.

METHODS

This two-centre observational cohort study retrospectively screened 477 consecutive patients who presented with ATAAD between 2009 and 2018. Of those, 25 (5.2%) underwent CT angiography (CTA) within 2 years before dissection onset. Aortic diameter, length and volume of these patients ('pre-ATAAD') were compared with those of TAA controls (n=75). Receiver operating curve analysis was performed to evaluate the predictive accuracy of the three different measurements.

RESULTS

96% of patients with pre-ATAAD did not meet the surgical diameter threshold of 55 mm before dissection onset. Maximal aortic diameters (45 (40-49) mm vs 46 (44-49) mm, p=0.075) and volume (126 (95-157) cm³ vs 124 (102-136) cm³, p=0.909) were comparable between patients with pre-ATAAD and TAA controls. Conversely, ascending aortic length (84±9 mm vs 90±16 mm, p=0.031) was significantly larger in patients with pre-ATAAD. All three parameters had an area under the curve of >0.800. At the 55 mm cut-off point, the maximal diameter yielded a positive predictive value (PPV) of 20%. While maintaining same specificity levels, measurements of aortic volume and length showed superior diagnostic accuracy (PPV 55% and 70%, respectively).

CONCLUSION

Measurements of aortic volume and length have superior diagnostic accuracy compared with the maximal diameter and could improve the timely identification of patients at risk for ATAAD.

Fully Convolutional Mandible Segmentation on a valid Ground- Truth Dataset

This contribution presents the automatic segmentation of the lower jawbone (mandible) in humans' computed tomography (CT) images with the support of trained deep learning networks. CT acquisitions from the mandible frequently include radiological artifacts e.g., from metal dental restorations, ostheosynthesis materials or include trauma related free pieces of bones with missing bone contour anatomy. As a result, manual outlining these slices to generate the ground truth for evaluating segmentation algorithms lead to massive uncertainties and results in significant interphysician disagreement. Simply excluding these slices is also not the option of choice, regarding the treatment outcome. Hence, we defined strict inclusion and exclusion criteria for our datasets to avoid subjectivity or occurring bias in the groundtruth creation. Amongst others, datasets must display a complete physiological mandible without teeth. According to these data selection criteria such images are difficult to find since they originate from the clinical routine and therefore need a medical indication (such as trauma or pathologic lesions) to be provided as CT data. Furthermore, to prove the adequateness of our ground-truth, clinical experts segmented all cases twice manually, showing the great qualitative and quantitative agreement between them. Our dataset collection and the corresponding ground truth is an absolute novelty and the first serious evaluation of segmentation algorithms for the mandible.

Predictive imaging for thoracic aortic dissection and rupture: moving beyond diameters

Abstract

Acute aortic syndromes comprise a group of potentially fatal conditions that result from weakening of the aortic vessel wall. Pre-emptive surgical intervention is currently reserved for patients with severe aortic dilatation, although abundant evidence describes the occurrence of dissection and rupture in aortas with diameters below surgical thresholds. Modern imaging techniques (such as hybrid PET-CT and 4D flow MRI) afford the non-invasive assessment of anatomic, hemodynamic, and molecular features of the aorta, and may provide for a more accurate selection of patients who will benefit from preventative surgical intervention. In the current review, we summarize evidence and considerations regarding predictive aortic imaging and highlight evolving imaging modalities that have shown promise to improve risk assessment for the occurrence of dissection and rupture.

Key Points

• Guidelines for the preventative management of aortic disease depend on maximal vessel diameters, while these have shown to be poor predictors for the occurrence of catastrophic acute aortic events.

• Evolving imaging modalities (such as 4D flow MRI and hybrid PET-CT) afford a more comprehensive insight into anatomic, hemodynamic, and molecular features of the aorta and have shown promise to detect vessel wall instability at an early stage.

Vascular Deformation Mapping (VDM) of Thoracic Aortic Enlargement in Aneurysmal Disease and Dissection

Thoracic aortic aneurysm is a common and lethal disease that requires regular imaging surveillance to determine timing of surgical repair and prevent major complications such as rupture. Current cross-sectional imaging surveillance techniques, largely based on computed tomography angiography, are focused on measurement of maximal aortic diameter, although this approach is limited to fixed anatomic positions and is prone to significant measurement error. Here we present preliminary results showing the feasibility of a novel technique for assessing change in aortic dimensions, termed vascular deformation mapping (VDM). This technique allows quantification of 3-dimensional changes in the aortic wall geometry through nonrigid coregistration of computed tomography angiography images and spatial Jacobian analysis of aortic deformation. Through several illustrative cases we demonstrate that this method can be used to measure changes in the aortic wall geometry among patients with stable and enlarging thoracic aortic aneurysm and dissection. Furthermore, VDM results yield observations about the presence, distribution, and rate of aortic wall deformation that are not apparent by routine clinical evaluation. Finally, we show the feasibility of superposing patient-specific VDM results on a 3-dimensional aortic model using color 3D printing and discuss future directions and potential applications for the VDM technique.

Computer-aided planning and reconstruction of cranial 3D implants

In this contribution, a prototype for semiautomatic computer-aided planning and reconstruction of cranial 3D Implants is presented. The software prototype guides the user through the workflow, beginning with loading and mirroring the patient's head to obtain an initial curvature of the cranial implant. However, naïve mirroring is not sufficient for an implant, because human heads are in general too asymmetric. Thus, the user can perform Laplacian smoothing, followed by Delaunay triangulation, for generating an aesthetic looking and well-fitting implant. Finally, our software prototype allows to save the designed 3D model of the implant as a STL-file for 3D printing. The 3D printed implant can be used for further pre-interventional planning or even as the final implant for the patient. In summary, our findings show that a customized MeVisLab prototype can be an alternative to complex commercial planning software, which may not be available in a clinic.

Aortic Volumetry at Contrast-Enhanced Magnetic Resonance Angiography: Feasibility as a Sensitive Method for Monitoring Bicuspid Aortic Valve Aortopathy

OBJECTIVES

Bicuspid aortic valve patients can develop thoracic aortic aneurysms and therefore require serial imaging to monitor aortic growth. This study investigates the reliability of contrast-enhanced magnetic resonance angiography (CEMRA) volumetry compared with 2-dimensional diameter measurements to identify thoracic aortic aneurysm growth.

MATERIALS AND METHODS

A retrospective, institutional review board-approved, and Health Insurance Portability and Accountability Act-compliant study was conducted on 20 bicuspid aortic valve patients (45 ± 8.9 years, 20% women) who underwent serial CEMRA with a minimum imaging follow-up of 11 months. Magnetic resonance imaging was performed at 1.5 T with electrocardiogram-gated, time-resolved CEMRA. Independent observers measured the diameter at the sinuses of Valsalva (SOVs) and mid ascending aorta (MAA) as well as ascending aorta volume between the aortic valve annulus and innominate branch. Intraobserver/interobserver coefficient of variation (COV) and intraclass correlation coefficient (ICC) were computed to assess reliability. Growth rates were calculated and assessed by Student t test (P < 0.05, significant). The diameter of maximal growth (DMG), defined as the diameter at SOV or MAA with the faster growth rate, was recorded.

RESULTS

The mean time of follow-up was 2.6 ± 0.82 years. The intraobserver COV was 0.01 for SOV, 0.02 for MAA, and 0.02 for volume (interobserver COV: 0.02, 0.03, 0.04, respectively). The ICC was 0.83 for SOV, 0.86 for MAA, 0.90 for DMG, and 0.95 for volume. Average aortic measurements at baseline and (follow-up) were 42 ± 3 mm (42 ± 3 mm, P = 0.11) at SOV, 46 ± 4 mm (47 ± 4 mm, P < 0.05) at MAA, and 130 ± 23 mL (144 ± 24 mL, P < 0.05). Average size changes were 0.2 ± 0.6 mm/y (1% ± 2%) at SOV, 0.5 ± 0.8 mm/y (1% ± 2%) at MAA, 0.7 ± 0.7 mm/y (2% ± 2%) at DMG, and 6 ± 3 mL/y (4% ± 3%) with volumetry.

CONCLUSIONS

Three-dimensional CEMRA volumetry exhibited a larger effect when examining percentage growth, a better ICC, and a marginally lower COV. Volumetry may be more sensitive to growth and possibly less affected by error than diameter measurements.

HTC Vive MeVisLab integration via OpenVR for medical applications

Virtual Reality, an immersive technology that replicates an environment via computer-simulated reality, gets a lot of attention in the entertainment industry. However, VR has also great potential in other areas, like the medical domain, Examples are intervention planning, training and simulation. This is especially of use in medical operations, where an aesthetic outcome is important, like for facial surgeries. Alas, importing medical data into Virtual Reality devices is not necessarily trivial, in particular, when a direct connection to a proprietary application is desired. Moreover, most researcher do not build their medical applications from scratch, but rather leverage platforms like MeVisLab, MITK, OsiriX or 3D Slicer. These platforms have in common that they use libraries like ITK and VTK, and provide a convenient graphical interface. However, ITK and VTK do not support Virtual Reality directly. In this study, the usage of a Virtual Reality device for medical data under the MeVisLab platform is presented. The OpenVR library is integrated into the MeVisLab platform, allowing a direct and uncomplicated usage of the head mounted display HTC Vive inside the MeVisLab platform. Medical data coming from other MeVisLab modules can directly be connected per drag-and-drop to the Virtual Reality module, rendering the data inside the HTC Vive for immersive virtual reality inspection.

Iterative-cuts: longitudinal and scale-invariant segmentation via user-defined templates for rectosigmoid colon in gynecological brachytherapy

Among all types of cancer, gynecological malignancies belong to the fourth most frequent type of cancer among women. In addition to chemotherapy and external beam radiation, brachytherapy is the standard procedure for the treatment of these malignancies. In the progress of treatment planning, localization of the tumor as the target volume and adjacent organs of risks by segmentation is crucial to accomplish an optimal radiation distribution to the tumor while simultaneously preserving healthy tissue. Segmentation is performed manually and represents a time-consuming task in clinical daily routine. This study focuses on the segmentation of the rectum/sigmoid colon as an organ-at-risk in gynecological brachytherapy. The proposed segmentation method uses an interactive, graph-based segmentation scheme with a user-defined template. The scheme creates a directed two-dimensional graph, followed by the minimal cost closed set computation on the graph, resulting in an outlining of the rectum. The graph's outline is dynamically adapted to the last calculated cut. Evaluation was performed by comparing manual segmentations of the rectum/sigmoid colon to results achieved with the proposed method. The comparison of the algorithmic to manual result yielded a dice similarity coefficient value of [Formula: see text], in comparison to [Formula: see text] for the comparison of two manual segmentations by the same physician. Utilizing the proposed methodology resulted in a median time of [Formula: see text], compared to 300 s needed for pure manual segmentation.

Correlation between coronary artery calcium score and aortic diameter in a high-risk population of elderly male hypertensive patients

BACKGROUND

Studies on the relationship between coronary artery calcium and aortic diameter are scarce. The aim of the current study was to evaluate the correlation between coronary artery calcium score (CACS) and maximal thoracic and abdominal aortic diameters in a population of elderly (>65 years) male hypertensive patients at high risk for coronary artery disease.

PATIENTS AND METHODS

From June 2012 to April 2013, we prospectively enrolled 393 male hypertensive patients older than 65 years of age who had no history of aortic aneurysm. Coronary artery calcium and maximal diameters of the ascending thoracic aorta (ATAmax), descending thoracic aorta (DTAmax), and abdominal aorta (AAmax) were measured using noncontrast computed tomography imaging. Aortic diameters are indexed to body surface area (BSA). Participants were divided into five groups according to CACS (0, 1-10, 10-100, 100-400, and >400).

RESULTS

The mean ATAmax/BSA, DTAmax/BSA, and AAmax/BSA were 22.0±2.7, 16.3±1.9, and 13.0±2.9 mm, respectively. On multivariate analysis, ATAmax/BSA was associated independently with age, diabetes, and history of aortic valve replacement (all P<0.001). DTAmax/BSA was associated independently with age (P<0.001). However, there were no significant correlations between thoracic aorta diameter and CACS. In contrast, AAmax/BSA was associated independently with CACS as well as age and history of smoking (P=0.014, 0.003, and 0.019, respectively). Abdominal aortic aneurysm (>30 mm) was more prevalent in patients with a CACS of 400 or more compared with the others (14 vs. 3%, P<0.001).

CONCLUSION

CACS was associated with increased abdominal aorta diameter, but not with thoracic aorta diameter. Therefore, screening for an abdominal aortic aneurysm is warranted in patients with a high risk of coronary artery disease and a high CACS. However, the necessity for thoracic aortic aneurysm screening is not clear in these patients.

Interactive Volumetry Of Liver Ablation Zones

Percutaneous radiofrequency ablation (RFA) is a minimally invasive technique that destroys cancer cells by heat. The heat results from focusing energy in the radiofrequency spectrum through a needle. Amongst others, this can enable the treatment of patients who are not eligible for an open surgery. However, the possibility of recurrent liver cancer due to incomplete ablation of the tumor makes post-interventional monitoring via regular follow-up scans mandatory. These scans have to be carefully inspected for any conspicuousness. Within this study, the RF ablation zones from twelve post-interventional CT acquisitions have been segmented semi-automatically to support the visual inspection. An interactive, graph-based contouring approach, which prefers spherically shaped regions, has been applied. For the quantitative and qualitative analysis of the algorithm's results, manual slice-by-slice segmentations produced by clinical experts have been used as the gold standard (which have also been compared among each other). As evaluation metric for the statistical validation, the Dice Similarity Coefficient (DSC) has been calculated. The results show that the proposed tool provides lesion segmentation with sufficient accuracy much faster than manual segmentation. The visual feedback and interactivity make the proposed tool well suitable for the clinical workflow.

RFA-cut: Semi-automatic segmentation of radiofrequency ablation zones with and without needles via optimal s-t-cuts

In this contribution, we present a semi-automatic segmentation algorithm for radiofrequency ablation (RFA) zones via optimal s-t-cuts. Our interactive graph-based approach builds upon a polyhedron to construct the graph and was specifically designed for computed tomography (CT) acquisitions from patients that had RFA treatments of Hepatocellular Carcinomas (HCC). For evaluation, we used twelve post-interventional CT datasets from the clinical routine and as evaluation metric we utilized the Dice Similarity Coefficient (DSC), which is commonly accepted for judging computer aided medical segmentation tasks. Compared with pure manual slice-by-slice expert segmentations from interventional radiologists, we were able to achieve a DSC of about eighty percent, which is sufficient for our clinical needs. Moreover, our approach was able to handle images containing (DSC=75.9%) and not containing (78.1%) the RFA needles still in place. Additionally, we found no statistically significant difference (p<;0.423) between the segmentation results of the subgroups for a Mann-Whitney test. Finally, to the best of our knowledge, this is the first time a segmentation approach for CT scans including the RFA needles is reported and we show why another state-of-the-art segmentation method fails for these cases. Intraoperative scans including an RFA probe are very critical in the clinical practice and need a very careful segmentation and inspection to avoid under-treatment, which may result in tumor recurrence (up to 40%). If the decision can be made during the intervention, an additional ablation can be performed without removing the entire needle. This decreases the patient stress and associated risks and costs of a separate intervention at a later date. Ultimately, the segmented ablation zone containing the RFA needle can be used for a precise ablation simulation as the real needle position is known.

Refinement-cut: user-guided segmentation algorithm for translational science

In this contribution, a semi-automatic segmentation algorithm for (medical) image analysis is presented. More precise, the approach belongs to the category of interactive contouring algorithms, which provide real-time feedback of the segmentation result. However, even with interactive real-time contouring approaches there are always cases where the user cannot find a satisfying segmentation, e.g. due to homogeneous appearances between the object and the background, or noise inside the object. For these difficult cases the algorithm still needs additional user support. However, this additional user support should be intuitive and rapid integrated into the segmentation process, without breaking the interactive real-time segmentation feedback. I propose a solution where the user can support the algorithm by an easy and fast placement of one or more seed points to guide the algorithm to a satisfying segmentation result also in difficult cases. These additional seed(s) restrict(s) the calculation of the segmentation for the algorithm, but at the same time, still enable to continue with the interactive real-time feedback segmentation. For a practical and genuine application in translational science, the approach has been tested on medical data from the clinical routine in 2D and 3D.

Abdominal aortic aneurysm imaging with 3-D ultrasound: 3-D-based maximum diameter measurement and volume quantification

The clinical reliability of 3-D ultrasound imaging (3-DUS) in quantification of abdominal aortic aneurysm (AAA) was evaluated. B-mode and 3-DUS images of AAAs were acquired for 42 patients. AAAs were segmented. A 3-D-based maximum diameter (Max3-D) and partial volume (Vol30) were defined and quantified. Comparisons between 2-D (Max2-D) and 3-D diameters and between orthogonal acquisitions were performed. Intra- and inter-observer reproducibility was evaluated. Intra- and inter-observer coefficients of repeatability (CRs) were less than 5.18 mm for Max3-D. Intra-observer and inter-observer CRs were respectively less than 6.16 and 8.71 mL for Vol30. The mean of normalized errors of Vol30 was around 7%. Correlation between Max2-D and Max3-D was 0.988 (p < 0.0001). Max3-D and Vol30 were not influenced by a probe rotation of 90°. Use of 3-DUS to quantify AAA is a new approach in clinical practice. The present study proposed and evaluated dedicated parameters. Their reproducibility makes the technique clinically reliable.

Standardization of outcome measures in clinical trials of pharmacological treatment for abdominal aortic aneurysm

An abdominal aortic aneurysm (AAA) is a common aortic wall disease with an increased prevalence in the elderly population (4-8% for those aged >65 years). Many AAAs are slow growing and remain insidious. Current standard of care for patients with small AAAs (<49 mm) is surveillance, with interventional therapy (open surgical repair or endovascular aneurysm repair) recommended for large (>50-55 mm), rapidly growing (>10 mm/year) or symptomatic AAAs. Although open surgical repair or endovascular aneurysm repair are effective, significant short- and long-term postoperative morbidity and mortality occurs. Currently, there is no pharmacological treatment specific for AAA; the need for the development of targeted pharmacological therapies based on clinically relevant and feasible outcomes acceptable to the medical community, regulatory agencies and third-party payers is high. A consensus on such end points will be critical to accelerating the development of pharmacological agents to prevent formation, arrest the expansion and reduce the rupture risk of AAA.

Manual refinement system for graph-based segmentation results in the medical domain

The basic principle of graph-based approaches for image segmentation is to interpret an image as a graph, where the nodes of the graph represent 2D pixels or 3D voxels of the image. The weighted edges of the graph are obtained by intensity differences in the image. Once the graph is constructed, the minimal cost closed set on the graph can be computed via a polynomial time s-t cut, dividing the graph into two parts: the object and the background. However, no segmentation method provides perfect results, so additional manual editing is required, especially in the sensitive field of medical image processing. In this study, we present a manual refinement method that takes advantage of the basic design of graph-based image segmentation algorithms. Our approach restricts a graph-cut by using additional user-defined seed points to set up fixed nodes in the graph. The advantage is that manual edits can be integrated intuitively and quickly into the segmentation result of a graph-based approach. The method can be applied to both 2D and 3D objects that have to be segmented. Experimental results for synthetic and real images are presented to demonstrate the feasibility of our approach.