Greater Curvature, Centerline or Straightened Centerline Length - Which length is Most Accurate for Preprocedural Planning in Thoracic Endovascular Aortic Repair?

BACKGROUND

Automated centerline (CL) measurements have been conventionally used for stent-graft length estimation during thoracic endovascular aortic repair (TEVAR). The purpose of this study was to assess the accuracy of greater curvature length (GL), semiautomated CL and straightened centerline length (SCL) for preprocedural planning in TEVAR.

METHODS

Immediate postprocedural CT Angiographies of 30 patients (22 males, age-49.2 ± 10.1years) who underwent TEVAR between 2015 and 2017 were retrospectively analyzed. CL, GL, SCL and the straightline length(SL) were measured between proximal and distal ends of the stent-graft and results were compared with the true length of the stent-graft (TL). Tortuosity index (TI = CL/SL) was calculated.

RESULTS

GL (17.92 ± 4.78 cm) was the closest in predicting the TL (17.75 ± 4.29 cm) (P = 0.414) overall, as well as in both dissection and aneurysm subgroups (P= 0.9). There was a significant difference between CL (16.67 ± 4.07 cm) and TL (P< 0.0001) as well as between SCL (16.86 ± 4.16 cm) and TL (P= 0.001). These differences were greater in dissection subgroup than in the aneurysm group (P< 0.0001 and P= 0.03 for TL-CL and TL-SCL, respectively). The extent of mismatch between GL or CL and TL did not correlate with tortuosity, but the difference between TL and SCL had a significant positive correlation with tortuosity (r = 0.375, P= 0.04). TL-GL had a negative linear correlation with the stent-graft length (TL) in the dissection group (r = 0.50, P= 0.03).

CONCLUSIONS

The greater curvature length predicts the actual total length of the deployed stent-graft more accurately than centerline or straightened centerline lengths. Hence, it should be used in planning for the length of stent-graft required for TEVAR.

Automated segmentation and quantification of the healthy and diseased aorta in CT angiographies using a dedicated deep learning approach

OBJECTIVES

To develop and validate a deep learning-based algorithm for segmenting and quantifying the physiological and diseased aorta in computed tomography angiographies.

METHODS

CTA exams of the aorta of 191 patients (68.1 ± 14 years, 128 male), performed between 2015 and 2018, were retrospectively identified from our imaging archive and manually segmented by two investigators. A 3D U-Net model was trained on the data, which was divided into a training, a validation, and a test group at a ratio of 7:1:2. Cases in the test group (n = 41) were evaluated to compare manual and automatic segmentations. Dice similarity coefficient (DSC), mean surface distance (MSD), and Hausdorff surface distance (HSD) were extracted. Maximum diameter, effective diameter, and area were quantified and compared between both segmentations at eight anatomical landmarks, and at the maximum area of an aneurysms if present (n = 14). Statistics included error calculation, intraclass correlation coefficient, and Bland-Altman analysis.

RESULTS

A DSC of 0.95 [0.94; 0.95] and an MSD of 0.76 [0.06; 0.99] indicated close agreement between segmentations. HSD was 8.00 [4.47; 10.00]. The largest absolute errors were found in the ascending aorta with 0.8 ± 1.5 mm for maximum diameter and at the coeliac trunk with - 30.0 ± 81.6 mm² for area. Results for absolute errors in aneurysms were - 0.5 ± 2.3 mm for maximum diameter, 0.3 ± 1.6 mm for effective diameter, and 64.9 ± 114.9 mm² for area. ICC showed excellent agreement (> 0.9; p < 0.05) between quantitative measurements.

CONCLUSIONS

Automated segmentation of the aorta on CTA data using a deep learning algorithm is feasible and allows for accurate quantification of the aortic lumen even if the vascular architecture is altered by disease.

KEY POINTS

• A deep learning-based algorithm can automatically segment the aorta, mostly within acceptable margins of error, even if the vascular architecture is altered by disease. • Quantifications performed in the segmentations were mostly within clinically acceptable limits, even in pathologically altered segments of the aorta.

Combined automated 3D volumetry by pulmonary CT angiography and echocardiography for detection of pulmonary hypertension

OBJECTIVES

To assess the diagnostic accuracy of automated 3D volumetry of central pulmonary arteries using computed tomography pulmonary angiography (CTPA) for suspected pulmonary hypertension alone and in combination with echocardiography.

METHODS

This retrospective diagnostic accuracy study included 70 patients (mean age 66.7, 48 female) assessed for pulmonary hypertension by CTPA and transthoracic echocardiography with estimation of the pulmonary arterial systolic pressure (PASP). Gold standard right heart catheterisation with measurement of the invasive mean pulmonary arterial pressure (invasive mPAP) served as the reference. Volumes of the main, right and left pulmonary arteries (MPA, RPA and LPA) were computed using automated 3D segmentation. For comparison, axial dimensions were manually measured. A linear regression model was established for prediction of mPAP (predicted mPAP).

RESULTS

MPA, RPA and LPA volumes were significantly increased in patients with vs. without pulmonary hypertension (all p < 0.001). Of all measures, MPA volume demonstrated the strongest correlation with invasive mPAP (r = 0.76, p < 0.001). Predicted mPAP using MPA volume and echocardiographic PASP as covariates showed excellent correlation with invasive mPAP (r = 0.89, p < 0.001). Area under the curves for predicting pulmonary hypertension were 0.94 for predicted mPAP, compared to 0.90 for MPA volume and 0.92 for echocardiographic PASP alone. A predicted mPAP > 25.8 mmHg identified pulmonary hypertension with sensitivity, specificity, positive and negative predictive values of 86%, 93%, 95% and 81%, respectively.

CONCLUSIONS

Automated 3D volumetry of central pulmonary arteries based on CTPA may be used in conjunction with echocardiographic pressure estimates to noninvasively predict mPAP and pulmonary hypertension as confirmed by gold standard right heart catheterisation with higher diagnostic accuracy than either test alone.

KEY POINTS

• This diagnostic accuracy study derived a regression model for noninvasive prediction of invasively measured mean pulmonary arterial pressure as assessed by gold standard right heart catheterisation. • This regression model using automated 3D volumetry of the central pulmonary arteries based on CT pulmonary angiography in conjunction with the echocardiographic pressure estimate predicted pulmonary arterial pressure and the presence of pulmonary hypertension with good diagnostic accuracy. • The combination of automated 3D volumetry and echocardiographic pressure estimate in the regression model provided superior diagnostic accuracy compared to each parameter alone.

How Precise Are Preinterventional Measurements Using Centerline Analysis Applications? Objective Ground Truth Evaluation Reveals Software-Specific Centerline Characteristics

PURPOSE

To evaluate different centerline analysis applications using objective ground truth from realistic aortic aneurysm phantoms with precisely defined geometry and centerlines to overcome the lack of unknown true dimensions in previously published in vivo validation studies.

METHODS

Three aortic phantoms were created using computer-aided design (CAD) software and a 3-dimensional (3D) printer. Computed tomography angiograms (CTAs) of phantoms and 3 patients were analyzed with 3 clinically approved and 1 research software application. The 3D centerline coordinates, intraluminal diameters, and lengths were validated against CAD ground truth using a dedicated evaluation software platform.

RESULTS

The 3D centerline position mean error ranged from 0.7±0.8 to 2.9±2.5 mm between tested applications. All applications calculated centerlines significantly different from ground truth. Diameter mean errors varied from 0.5±1.2 to 1.1±1.0 mm among 3 applications, but exceeded 8.0±11.0 mm with one application due to an unsteady distortion of luminal dimensions along the centerline. All tested commercially available software tools systematically underestimated centerline total lengths by -4.6±0.9 mm to -10.4±4.3 mm (maximum error -14.6 mm). Applications with the highest 3D centerline accuracy yielded the most precise diameter and length measurements.

CONCLUSION

One clinically approved application did not provide reproducible centerline-based analysis results, while another approved application showed length errors that might influence stent-graft choice and procedure success. The variety and specific characteristics of endovascular aneurysm repair planning software tools require scientific evaluation and user awareness.

Aortic length measurements for pulse wave velocity calculation: manual 2D vs automated 3D centreline extraction

BACKGROUND

Pulse wave velocity (PWV) is a biomarker for the intrinsic stiffness of the aortic wall, and has been shown to be predictive for cardiovascular events. It can be assessed using cardiovascular magnetic resonance (CMR) from the delay between phase-contrast flow waveforms at two or more locations in the aorta, and the distance on CMR images between those locations. This study aimed to investigate the impact of different distance measurement methods on PWV. We present and evaluate an algorithm for automated centreline tracking in 3D images, and compare PWV calculations using distances derived from 3D images to those obtained from a conventional 2D oblique-sagittal image of the aorta.

METHODS

We included 35 patients from a twin cohort, and 20 post-coarctation repair patients. Phase-contrast flow was acquired in the ascending, descending and diaphragmatic aorta. A 3D centreline tracking algorithm is presented and evaluated on a subset of 30 subjects, on three CMR sequences: balanced steady-state free precession (SSFP), black-blood double inversion recovery turbo spin echo, and contrast-enhanced CMR angiography. Aortic lengths are subsequently compared between measurements from a 2D oblique-sagittal plane, and a 3D geometry.

RESULTS

The error in length of automated 3D centreline tracking compared with manual annotations ranged from 2.4 [1.8-4.3] mm (mean [IQR], black-blood) to 6.4 [4.7-8.9] mm (SSFP). The impact on PWV was below 0.5m/s (<5%). Differences between 2D and 3D centreline length were significant for the majority of our experiments (p < 0.05). Individual differences in PWV were larger than 0.5m/s in 15% of all cases (thoracic aorta) and 37% when studying the aortic arch only. Finally, the difference between end-diastolic and end-systolic 2D centreline lengths was statistically significant (p < 0.01), but resulted in small differences in PWV (0.08 [0.04 - 0.10]m/s).

CONCLUSIONS

Automatic aortic centreline tracking in three commonly used CMR sequences is possible with good accuracy. The 3D length obtained from such sequences can differ considerably from lengths obtained from a 2D oblique-sagittal plane, depending on aortic curvature, adequate planning of the oblique-sagittal plane, and patient motion between acquisitions. For accurate PWV measurements we recommend using 3D centrelines.

Proximal scalloped custom-made Relay® stent graft in chronic type B dissection: endovascular repair in a drug abuser patient

The best solution for enlarging chronic type B aortic dissection is not known. Hybrid surgical and endovascular procedures offer a reliable solution in such circumstances, but technically complex stent-graft designs are sometimes needed when the treatment segment of the aorta presents anatomical challenges. We report a case of a proximally scalloped custom-made stent-graft implantation following left subclavian artery transposition in a formerly cocaine-abuser patient. The one-month follow-up computed tomography angiography showed a proximal endoleak (type Ia) which was successfully solved by coil embolization. Proximally scalloped stent grafts offer a reliable solution in complex aortic dissections involving the supra-aortic branches.

3D Geometric Analysis of the Pediatric Aorta in 3D MRA Follow-Up Images with Application to Aortic Coarctation

BACKGROUND

Coarctation of the aorta is one of the most common congenital heart diseases. Despite different treatment opportunities, long-term outcome after surgical or interventional therapy is diverse. Serial morphologic follow-up of vessel growth is necessary, because vessel growth cannot be predicted by primer morphology or a therapeutic option.

OBJECTIVES

For the analysis of the long-term outcome after therapy of congenital diseases such as aortic coarctation, accurate 3D geometric analysis of the aorta from follow-up 3D medical image data such as magnetic resonance angiography (MRA) is important. However, for an objective, fast, and accurate 3D geometric analysis, an automatic approach for 3D segmentation and quantification of the aorta from pediatric images is required.

METHODS

We introduce a new model-based approach for the segmentation of the thoracic aorta and its main branches from follow-up pediatric 3D MRA image data. For robust segmentation of vessels even in difficult cases (e.g., neighboring structures), we propose a new extended parametric cylinder model that requires only relatively few model parameters. Moreover, we include a novel adaptive background-masking scheme used for least-squares model fitting, we use a spatial normalization scheme to align the segmentation results from follow-up examinations, and we determine relevant 3D geometric parameters of the aortic arch.

RESULTS

We have evaluated our proposed approach using different 3D synthetic images. Moreover, we have successfully applied the approach to follow-up pediatric 3D MRA image data, we have normalized the 3D segmentation results of follow-up images of individual patients, and we have combined the results of all patients. We also present a quantitative evaluation of our approach for four follow-up 3D MRA images of a patient, which confirms that our approach yields accurate 3D segmentation results. An experimental comparison with two previous approaches demonstrates that our approach yields superior results.

CONCLUSIONS

From the results, we found that our approach is well suited for the quantification of the 3D geometry of the aortic arch from follow-up pediatric 3D MRA image data. In future work, this will enable to investigate the long-term outcome of different surgical and interventional therapies for aortic coarctation.

Automated 3D Volumetry of the Pulmonary Arteries based on Magnetic Resonance Angiography Has Potential for Predicting Pulmonary Hypertension

PURPOSE

To demonstrate feasibility of automated 3D volumetry of central pulmonary arteries based on magnetic resonance angiography (MRA), to assess pulmonary artery volumes in patients with pulmonary hypertension compared to healthy controls, and to investigate the potential of the technique for predicting pulmonary hypertension.

METHODS

MRA of pulmonary arteries was acquired at 1.5T in 20 patients with pulmonary arterial hypertension and 21 healthy normotensive controls. 3D model-based image analysis software was used for automated segmentation of main, right and left pulmonary arteries (MPA, RPA and LPA). Volumes indexed to vessel length and mean, minimum and maximum diameters along the entire vessel course were assessed and corrected for body surface area (BSA). For comparison, diameters were also manually measured on axial reconstructions and double oblique multiplanar reformations. Analyses were performed by two cardiovascular radiologists, and by one radiologist again after 6 months.

RESULTS

Mean volumes of MPA, RPA and LPA for patients/controls were 5508 ± 1236/3438 ± 749, 3522 ± 934/1664 ± 468 and 3093 ± 692/1812 ± 474 μl/(cm length x m2 BSA) (all p<0.001). Mean, minimum and maximum diameters along the entire vessel course were also significantly increased in patients compared to controls (all p<0.001). Intra- and interobserver agreement were excellent for both volume and diameter measurements using 3D segmentation (intraclass correlation coefficients 0.971-0.999, p<0.001). Area under the curve for predicting pulmonary hypertension using volume was 0.998 (95% confidence interval 0.990-1.0, p<0.001), compared to 0.967 using manually measured MPA diameter (95% confidence interval 0.910-1.0, p<0.001).

CONCLUSIONS

Automated MRA-based 3D volumetry of central pulmonary arteries is feasible and demonstrated significantly increased volumes and diameters in patients with pulmonary arterial hypertension compared to healthy controls. Pulmonary artery volume may serve as a superior predictor for pulmonary hypertension compared to manual measurements on axial images but verification in a larger study population is warranted.

Increasing the feasibility of minimally invasive procedures in type A aortic dissections: a framework for segmentation and quantification

PURPOSE

Our goal is to provide precise measurements of the aortic dimensions in case of dissection pathologies. Quantification of surface lengths and aortic radii/diameters together with the visualization of the dissection membrane represents crucial prerequisites for enabling minimally invasive treatment of type A dissections, which always also imply the ascending aorta.

METHODS

We seek a measure invariant to luminance and contrast for aortic outer wall segmentation. Therefore, we propose a 2D graph-based approach using phase congruency combined with additional features. Phase congruency is extended to 3D by designing a novel conic directional filter and adding a lowpass component to the 3D Log-Gabor filterbank for extracting the fine dissection membrane, which separates the true lumen from the false one within the aorta.

RESULTS

The result of the outer wall segmentation is compared with manually annotated axial slices belonging to 11 CTA datasets. Quantitative assessment of our novel 2D/3D membrane extraction algorithms has been obtained for 10 datasets and reveals subvoxel accuracy in all cases. Aortic inner and outer surface lengths, determined within 2 cadaveric CT datasets, are validated against manual measurements performed by a vascular surgeon on excised aortas of the body donors.

CONCLUSIONS

This contribution proposes a complete pipeline for segmentation and quantification of aortic dissections. Validation against ground truth of the 3D contour lengths quantification represents a significant step toward custom-designed stent-grafts.

Automatic extraction of three-dimensional thoracic aorta geometric model from phase contrast MRI for morphometric and hemodynamic characterization

PURPOSE

To propose and assess a new method that automatically extracts a three-dimensional (3D) geometric model of the thoracic aorta (TA) from 3D cine phase contrast MRI (PCMRI) acquisitions.

METHODS

The proposed method is composed of two steps: segmentation of the TA and creation of the 3D geometric model. The segmentation algorithm, based on Level Set, was set and applied to healthy subjects acquired in three different modalities (with and without SENSE reduction factors). Accuracy was evaluated using standard quality indices. The 3D model is characterized by the vessel surface mesh and its centerline; the comparison of models obtained from the three different datasets was also carried out in terms of radius of curvature (RC) and average tortuosity (AT).

RESULTS

In all datasets, the segmentation quality indices confirmed very good agreement between manual and automatic contours (average symmetric distance < 1.44 mm, DICE Similarity Coefficient > 0.88). The 3D models extracted from the three datasets were found to be comparable, with differences of less than 10% for RC and 11% for AT.

CONCLUSION

Our method was found effective on PCMRI data to provide a 3D geometric model of the TA, to support morphometric and hemodynamic characterization of the aorta.

Aortic morphometry at endograft position as assessed by 3D image analysis affects risk of type I endoleak formation after TEVAR

PURPOSE

The purpose of this study was to identify morphologic factors affecting type I endoleak formation and bird-beak configuration after thoracic endovascular aortic repair (TEVAR).

METHODS

Computed tomography (CT) data of 57 patients (40 males; median age, 66 years) undergoing TEVAR for thoracic aortic aneurysm (34 TAA, 19 TAAA) or penetrating aortic ulcer (n = 4) between 2001 and 2010 were retrospectively reviewed. In 28 patients, the Gore TAG® stent-graft was used, followed by the Medtronic Valiant® in 16 cases, the Medtronic Talent® in 8, and the Cook Zenith® in 5 cases. Proximal landing zone (PLZ) was in zone 1 in 13, zone 2 in 13, zone 3 in 23, and zone 4 in 8 patients. In 14 patients (25%), the procedure was urgent or emergent. In each case, pre- and postoperative CT angiography was analyzed using a dedicated image processing workstation and complimentary in-house developed software based on a 3D cylindrical intensity model to calculate aortic arch angulation and conicity of the landing zones (LZ).

RESULTS

Primary type Ia endoleak rate was 12% (7/57) and subsequent re-intervention rate was 86% (6/7). Left subclavian artery (LSA) coverage (p = 0.036) and conicity of the PLZ (5.9 vs. 2.6 mm; p = 0.016) were significantly associated with an increased type Ia endoleak rate. Bird-beak configuration was observed in 16 patients (28%) and was associated with a smaller radius of the aortic arch curvature (42 vs. 65 mm; p = 0.049). Type Ia endoleak was not associated with a bird-beak configuration (p = 0.388). Primary type Ib endoleak rate was 7% (4/57) and subsequent re-intervention rate was 100%. Conicity of the distal LZ was associated with an increased type Ib endoleak rate (8.3 vs. 2.6 mm; p = 0.038).

CONCLUSIONS

CT-based 3D aortic morphometry helps to identify risk factors of type I endoleak formation and bird-beak configuration during TEVAR. These factors were LSA coverage and conicity within the landing zones for type I endoleak formation and steep aortic angulation for bird-beak configuration.

3D morphometry using automated aortic segmentation in native MR angiography: an alternative to contrast enhanced MRA?

INTRODUCTION

Native-MR angiography (N-MRA) is considered an imaging alternative to contrast enhanced MR angiography (CE-MRA) for patients with renal insufficiency. Lower intraluminal contrast in N-MRA often leads to failure of the segmentation process in commercial algorithms. This study introduces an in-house 3D model-based segmentation approach used to compare both sequences by automatic 3D lumen segmentation, allowing for evaluation of differences of aortic lumen diameters as well as differences in length comparing both acquisition techniques at every possible location.

METHODS AND MATERIALS

Sixteen healthy volunteers underwent 1.5-T-MR Angiography (MRA). For each volunteer, two different MR sequences were performed, CE-MRA: gradient echo Turbo FLASH sequence and N-MRA: respiratory-and-cardiac-gated, T2-weighted 3D SSFP. Datasets were segmented using a 3D model-based ellipse-fitting approach with a single seed point placed manually above the celiac trunk. The segmented volumes were manually cropped from left subclavian artery to celiac trunk to avoid error due to side branches. Diameters, volumes and centerline length were computed for intraindividual comparison. For statistical analysis the Wilcoxon-Signed-Ranked-Test was used.

RESULTS

Average centerline length obtained based on N-MRA was 239.0±23.4 mm compared to 238.6±23.5 mm for CE-MRA without significant difference (P=0.877). Average maximum diameter obtained based on N-MRA was 25.7±3.3 mm compared to 24.1±3.2 mm for CE-MRA (P<0.001). In agreement with the difference in diameters, volumes obtained based on N-MRA (100.1±35.4 cm(3)) were consistently and significantly larger compared to CE-MRA (89.2±30.0 cm(3)) (P<0.001).

CONCLUSIONS

3D morphometry shows highly similar centerline lengths for N-MRA and CE-MRA, but systematically higher diameters and volumes for N-MRA.

Effects of aging on thoracic aorta size and shape: a non-contrast CT study

Measures of atherosclerosis burden like coronary artery calcification are performed using non-contrast heart CT. However, additional information can be derived from these studies, looking beyond the coronary arteries without exposing the patients to further radiation. We present a semi-automated method to assess ascending, arch and descending aorta geometry from non-contrast CT datasets in 250 normotensive patients. We investigated the effect of aging on thoracic aorta morphometry. The algorithm identifies the aortic centerline coordinates following a toroidal path for the curvilinear portion and axial planes for descending aorta. Then it reconstructs oblique planes orthogonal to the centerline direction and a circle fitting process estimates the vessel cross-section. Finally, global thoracic aorta dimensions (diameter, volume and length) and shape (vessel curvature and tortuosity, aortic arch width and height) are calculated. From a multivariate analysis, adjusted for gender and body-size area, aortic volume and arch width were the descriptors that better represented the aortic size and shape alterations with aging. The thoracic aorta suffers an expanding and unfolding process with aging that deserves further attention to prevent aortic aneurisms.

Computed tomography angiography of hybrid thoracic endovascular aortic repair of the aortic arch

Endovascular repair of the aorta has traditionally been limited to the abdominal aorta and, more recently, the descending thoracic aorta. However, recently hybrid repairs (a combination of open surgical and endovascular repair) have made endovascular repair of the aortic arch possible. Hybrid repair of the aortic arch typically involves an open surgical debranching procedure that allows for revascularization of the aortic arch vessels and subsequent endovascular stent placement. These approaches avoid the deep hypothermic circulatory arrest required for full, open surgical repair of the aortic arch. In hybrid repairs, the stent landing zone determines which branch vessels will be covered and therefore need revascularization. This article will review the preprocedure assessment with computed tomography angiography, techniques for revascularization and postprocedure complications.

Anatomical characteristics of the thoracic aortic arch in an Asian population

Background: Endovascular repair of the aortic arch is often unsatisfactory due to poor stent-vessel conformity and inadequate landing zones.

Objective: To study the anatomical characteristics of the aortic arch and provide basic information for the development of arch-specific endovascular devices.

Materials and methods: Three-dimensional models were reconstructed in Mimics (image segmentation software) from computed tomography aortograms of 120 elderly Asian patients, by manual segmentation. The centerline of each Three-dimensional aortic model was calculated using a repulsive force field method. Measurements of the aorta and supra-aortic branches were analyzed using Patran (finite-element software). A three-dimensional statistical aortic arch model was built using principal component analysis.

Results: The mean diameters of the ascending and descending aorta, and the origins of the innominate, left common carotid, and left subclavian artery were 39.4 ± 6.7, 34.5 ± 7.9, 18.0 ± 3.8, 12.6 ± 2.7, and 14.1 ± 2.5 mm, respectively. The length of the ascending aorta, innominate to left common carotid artery, and left common carotid to left subclavian artery were 62.6 ± 11.4, 12.0 ± 5.6, and 18.7 ± 5.6 mm along the centerline. The mean angle of curvature was 103.8 ± 25 degrees. Principal component analysis of the three-dimensional centerlines derived 3 main modes of variation, which account for 61% of the overall shape range.

Conclusion: Aortic arch anatomical information from an elderly Asian population can be useful for the development of future endovascular devices.

Impact of endografting on the thoracic aortic anatomy: comparative analysis of the aortic geometry before and after the endograft implantation

PURPOSE

Although the widespread acceptance of thoracic endovascular aortic repair (TEVAR) as a first-line treatment option for a multitude of thoracic aortic diseases, little is known about the consequences of the device implantation on the native aortic anatomy. We propose a comparative analysis of the pre- and postoperative geometry on a clinical series of patients and discuss the potential clinical implications

METHODS

CT pre- and postoperative acquisitions of 30 consecutive patients treated by TEVAR for different pathologies (20 thoracic aortic aneurysms, 6 false aneurysms, 3 penetrating ulcers, 1 traumatic rupture) were used to model the vascular geometry. Pre- and postoperative geometries were compared for each patient by pairing and matching the 3D models. An implantation site was identified, and focal differences were detected and described.

RESULTS

Segmentation of the data sets was successfully performed for all 30 subjects. Geometry differences between the pre- and postoperative meshes were depicted in 23 patients (76 %). Modifications at the upper implantation site were detected in 14 patients (47 %), and among them, the implantation site involved the arch (Z0-3) in 11 (78 %).

CONCLUSION

Modeling the vascular geometry on the basis of imaging data offers an effective tool to perform patient-specific analysis of the vascular geometry before and after the treatment. Future studies will evaluate the consequences of these changes on the aortic function.

Accuracy and variability of semiautomatic centerline analysis versus manual aortic measurement techniques for TEVAR

OBJECTIVES

This study aims to test whether inter-observer variability and time of diameter measurements for thoracic endovascular aortic repair (TEVAR) are improved by semiautomatic centerline analysis compared to manual assessment.

METHODS

Preoperative computed tomography (CT) angiographies of 30 patients with thoracic aortic disease (mean age 66.8 ± 11.6 years, 23 males) were retrospectively analysed by two blinded experts in vascular radiology. Maximum aortic diameters at three positions relevant to TEVAR were assessed (P1, distal to left common carotid artery; P2, distal to left subclavian artery; and P3, proximal to coeliac trunk) using three measurement techniques: manual axial slices (axial), manual double-oblique multiplanar reformations (MPRs) and semiautomatic centerline analysis.

RESULTS

Diameter measurements by both centerline analysis and the axial technique did not significantly differ from MPR (p = 0.17 and p = 0.37). Total deviation index for 0.9 was for P1 2.7 mm (axial), 3.7 mm (MPR), 1.8 mm (centerline); for P2 2.0 mm (axial), 3.6 mm (MPR), 1.8 mm (centerline); and for P3 3.0 mm (axial), 3.5 mm (MPR), 2.5 mm (centerline). Measurement time using centerline analysis was significantly shorter than for assessment by MPR.

CONCLUSIONS

Centerline analysis provides the least variable and fast diameter measurements in TEVAR patients with the same accuracy as the current reference standard MPR.

Aging impact on thoracic aorta 3D morphometry in intermediate-risk subjects: looking beyond coronary arteries with non-contrast cardiac CT

An increasing number of intermediate risk asymptomatic subjects benefit from measures of atherosclerosis burden like coronary artery calcification studies with non-contrast heart computed tomography (CT). However, additional information can be derived from these studies, looking beyond the coronary arteries and without exposing the patients to further radiation. We report a semi-automatic method that objectively assesses ascending, arch and descending aorta dimension and shape from non-contrast CT datasets to investigate the effect of aging on thoracic aorta geometry. First, the segmentation process identifies the vessel centerline coordinates following a toroidal path for the curvilinear portion and axial planes for descending aorta. Then, reconstructing oblique planes orthogonal to the centerline direction, it iteratively fits circles inside the vessel cross-section. Finally, regional thoracic aorta dimensions (diameter, volume and length) and shape (vessel curvature and tortuosity) are calculated. A population of 200 normotensive men was recruited. Length, mean diameter and volume differed by 1.2 cm, 0.13 cm and 21 cm(3) per decade of life, respectively. Aortic shape uncoiled with aging, reducing its tortuosity and increasing its radius of curvature. The arch was the most affected segment. In conclusion, non-contrast cardiac CT imaging can be successfully employed to assess thoracic aorta 3D morphometry.

Model-based segmentation and motion analysis of the thoracic aorta from 4D ECG-gated CTA images

Pathologies of the thoracic aorta can alter the shape and motion pattern of the aorta throughout the cardiac cycle. For diagnosis and therapy planning, determination of the aortic shape and motion is important. We introduce a new approach for segmentation and motion analysis of the thoracic aorta from 4D ECG-CTA images, which combines spatial and temporal tracking, motion determination by intensity-based matching, and 3D fitting of vessel models. The approach has been successfully applied to 30 clinically relevant 4D CTA image sequences. We have also performed a quantitative evaluation of the segmentation accuracy.

Development of in vivo quantitative geometric mapping of the aortic arch for advanced endovascular aortic repair: feasibility and preliminary results

PURPOSE

To evaluate whether quantitative characterization of aortic arch geometry including its branches is feasible based on in vivo computed tomography (CT) angiography and magnetic resonance (MR) angiography data in healthy and diseased aortic arches.

MATERIALS AND METHODS

Ten healthy volunteers, 10 patients with abdominal aortic disease, and 10 patients with aortic arch disease underwent MR angiography (10 volunteers) or CT angiography (20 patients). Commercial software was used for individual segmentation of supraaortic arteries. In-house software was developed for segmentation of aortic arch landmarks based on standardized multiplanar reformations (MPRs) and for subsequent aortic arch mapping.

RESULTS

Supraaortic arteries and aortic arch landmarks were successfully segmented in all 30 subjects for CT angiography and MR angiography data. Significant tapering within the first centimeter was observed in all supraaortic arteries (P < .001). The three supraaortic arteries showed significantly different vessel diameters and areas (P < .001). The software developed in-house allowed detailed aortic arch mapping with quantitative definitions of the positional relationships between each supraaortic artery and the aorta. Distances between supraaortic arteries were less than 5 mm in 77.6% (mean 4.1 mm ± 3.8). The brachiocephalic trunk tended to be positioned on the right side of the aortic arch, and the left subclavian and left common carotid arteries tended to be positioned on the left side of the aortic arch.

CONCLUSIONS

The feasibility and application of a postprocessing method allowing quantification of geometry of supraaortic arteries and aortic arch mapping were successfully demonstrated. Validation and evaluation of clinical implications are warranted.