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Ojha V, Ganga KP, Goyal A, Reddy PR, Kumar S, Sharma S. Greater Curvature, Centerline or Straightened Centerline Length - Which length is Most Accurate for Preprocedural Planning in Thoracic Endovascular Aortic Repair? Ann Vasc Surg 2021; 78:123-131. [PMID: 34437962 DOI: 10.1016/j.avsg.2021.05.050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 05/09/2021] [Accepted: 05/13/2021] [Indexed: 11/17/2022]
Abstract
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.
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Affiliation(s)
- Vineeta Ojha
- Department of Cardiovascular Radiology and Endovascular Interventions, All India Institute of Medical Sciences, New Delhi, India
| | - Kartik P Ganga
- Department of Cardiovascular Radiology and Endovascular Interventions, All India Institute of Medical Sciences, New Delhi, India
| | - Aayush Goyal
- Department of Cardiothoracic and Vascular Surgery, All India Institute of Medical Sciences, New Delhi, India
| | - Pradeep Ramakrishnan Reddy
- Department of Cardiothoracic and Vascular Surgery, All India Institute of Medical Sciences, New Delhi, India
| | - Sanjeev Kumar
- Department of Cardiovascular Radiology and Endovascular Interventions, All India Institute of Medical Sciences, New Delhi, India.
| | - Sanjiv Sharma
- Department of Cardiovascular Radiology and Endovascular Interventions, All India Institute of Medical Sciences, New Delhi, India
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Sieren MM, Widmann C, Weiss N, Moltz JH, Link F, Wegner F, Stahlberg E, Horn M, Oecherting TH, Goltz JP, Barkhausen J, Frydrychowicz A. Automated segmentation and quantification of the healthy and diseased aorta in CT angiographies using a dedicated deep learning approach. Eur Radiol 2021; 32:690-701. [PMID: 34170365 DOI: 10.1007/s00330-021-08130-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Accepted: 03/26/2021] [Indexed: 11/29/2022]
Abstract
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.
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Affiliation(s)
- Malte Maria Sieren
- Department of Radiology and Nuclear Medicine, University Hospital Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, 23562, Lübeck, Germany.
| | - Cornelia Widmann
- Department of Radiology and Nuclear Medicine, University Hospital Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, 23562, Lübeck, Germany
| | - Nick Weiss
- Fraunhofer Institute for Digital Medicine MEVIS, Lübeck/Bremen, Germany
| | - Jan Hendrik Moltz
- Fraunhofer Institute for Digital Medicine MEVIS, Lübeck/Bremen, Germany
| | - Florian Link
- Fraunhofer Institute for Digital Medicine MEVIS, Lübeck/Bremen, Germany
| | - Franz Wegner
- Department of Radiology and Nuclear Medicine, University Hospital Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, 23562, Lübeck, Germany
| | - Erik Stahlberg
- Department of Radiology and Nuclear Medicine, University Hospital Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, 23562, Lübeck, Germany
| | - Marco Horn
- Department for Vascular Surgery, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Thekla Helene Oecherting
- Department of Radiology and Nuclear Medicine, University Hospital Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, 23562, Lübeck, Germany
| | - Jan Peter Goltz
- Institute for Diagnostic and Interventional Radiology/Neuroradiology, Sana Clinic, Lübeck, Germany
| | - Joerg Barkhausen
- Department of Radiology and Nuclear Medicine, University Hospital Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, 23562, Lübeck, Germany
| | - Alex Frydrychowicz
- Department of Radiology and Nuclear Medicine, University Hospital Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, 23562, Lübeck, Germany
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3
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Melzig C, Wörz S, Egenlauf B, Partovi S, Rohr K, Grünig E, Kauczor HU, Heussel CP, Rengier F. Combined automated 3D volumetry by pulmonary CT angiography and echocardiography for detection of pulmonary hypertension. Eur Radiol 2019; 29:6059-6068. [PMID: 30963276 DOI: 10.1007/s00330-019-06188-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2018] [Revised: 02/13/2019] [Accepted: 03/20/2019] [Indexed: 01/28/2023]
Abstract
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.
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Affiliation(s)
- Claudius Melzig
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany.,Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany
| | - Stefan Wörz
- Biomedical Computer Vision Group, BIOQUANT, IPMB and German Cancer Research Center (DKFZ), University of Heidelberg, Heidelberg, Germany
| | - Benjamin Egenlauf
- Centre for Pulmonary Hypertension, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany
| | - Sasan Partovi
- Department of Radiology, Section of Interventional Radiology, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Karl Rohr
- Biomedical Computer Vision Group, BIOQUANT, IPMB and German Cancer Research Center (DKFZ), University of Heidelberg, Heidelberg, Germany
| | - Ekkehard Grünig
- Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany.,Centre for Pulmonary Hypertension, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany
| | - Hans-Ulrich Kauczor
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany.,Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany
| | - Claus Peter Heussel
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany.,Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany.,Department of Radiology, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany
| | - Fabian Rengier
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany. .,Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany. .,Department of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
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Hoegen P, Wörz S, Müller-Eschner M, Geisbüsch P, Liao W, Rohr K, Schmitt M, Rengier F, Kauczor HU, von Tengg-Kobligk H. How Precise Are Preinterventional Measurements Using Centerline Analysis Applications? Objective Ground Truth Evaluation Reveals Software-Specific Centerline Characteristics. J Endovasc Ther 2017; 24:584-594. [PMID: 28587563 DOI: 10.1177/1526602817713737] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
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.
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Affiliation(s)
- Philipp Hoegen
- 1 Diagnostic and Interventional Radiology, University Hospital Heidelberg, Germany.,2 Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Stefan Wörz
- 3 BIOQUANT, IPMB, and DKFZ Heidelberg, Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, Germany
| | - Matthias Müller-Eschner
- 1 Diagnostic and Interventional Radiology, University Hospital Heidelberg, Germany.,4 Nuclear Medicine, University Hospital Frankfurt, Germany
| | - Philipp Geisbüsch
- 5 Vascular and Endovascular Surgery, University Hospital Heidelberg, Germany
| | - Wei Liao
- 3 BIOQUANT, IPMB, and DKFZ Heidelberg, Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, Germany
| | - Karl Rohr
- 3 BIOQUANT, IPMB, and DKFZ Heidelberg, Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, Germany
| | - Matthias Schmitt
- 5 Vascular and Endovascular Surgery, University Hospital Heidelberg, Germany
| | - Fabian Rengier
- 1 Diagnostic and Interventional Radiology, University Hospital Heidelberg, Germany.,2 Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Hans-Ulrich Kauczor
- 1 Diagnostic and Interventional Radiology, University Hospital Heidelberg, Germany
| | - Hendrik von Tengg-Kobligk
- 1 Diagnostic and Interventional Radiology, University Hospital Heidelberg, Germany.,6 Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, University Hospital, University of Bern, Switzerland.,7 Department of Radiology, Wright Center of Innovation in Biomedical Imaging, Ohio State University, Columbus, OH, USA
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5
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van Engelen A, Silva Vieira M, Rafiq I, Cecelja M, Schneider T, de Bliek H, Figueroa CA, Hussain T, Botnar RM, Alastruey J. Aortic length measurements for pulse wave velocity calculation: manual 2D vs automated 3D centreline extraction. J Cardiovasc Magn Reson 2017; 19:32. [PMID: 28270208 PMCID: PMC5341448 DOI: 10.1186/s12968-017-0341-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2016] [Accepted: 02/16/2017] [Indexed: 01/13/2023] Open
Abstract
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.
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Affiliation(s)
- Arna van Engelen
- Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King’s College London, St Thomas’ Hospital, 4th floor Lambeth Wing, Westminster Bridge Road, London, SE17EH UK
| | - Miguel Silva Vieira
- Department of Cardiovascular Imaging, Division of Imaging Sciences and Biomedical Engineering, King’s College London, St Thomas’ Hospital, 4th floor Lambeth Wing, Westminster Bridge Road, London, SE17EH UK
| | - Isma Rafiq
- Department of Cardiovascular Imaging, Division of Imaging Sciences and Biomedical Engineering, King’s College London, St Thomas’ Hospital, 4th floor Lambeth Wing, Westminster Bridge Road, London, SE17EH UK
| | - Marina Cecelja
- Department of Clinical Pharmacology, St Thomas’ Hospital, Westminster Bridge Road, London, SE17EH UK
| | | | | | - C. Alberto Figueroa
- Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King’s College London, St Thomas’ Hospital, 4th floor Lambeth Wing, Westminster Bridge Road, London, SE17EH UK
- Department of Bioengineering and Surgery, University of Michigan, Ann Arbor, MI USA
| | - Tarique Hussain
- Department of Cardiovascular Imaging, Division of Imaging Sciences and Biomedical Engineering, King’s College London, St Thomas’ Hospital, 4th floor Lambeth Wing, Westminster Bridge Road, London, SE17EH UK
- Department of Pediatrics, Pediatric Cardiology, UT Southwestern Medical Center, Dallas, USA
| | - Rene M. Botnar
- Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King’s College London, St Thomas’ Hospital, 4th floor Lambeth Wing, Westminster Bridge Road, London, SE17EH UK
- Pontificia Universidad Católica de Chile, Escuela de Ingeniería, Santiago, Chile
| | - Jordi Alastruey
- Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King’s College London, St Thomas’ Hospital, 4th floor Lambeth Wing, Westminster Bridge Road, London, SE17EH UK
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Szeberin Z, Nemes B, Csobay-Novák C, Mihály Z, Entz L. Proximal scalloped custom-made Relay® stent graft in chronic type B dissection: endovascular repair in a drug abuser patient. Interv Med Appl Sci 2017; 8:37-40. [PMID: 28250982 DOI: 10.1556/1646.8.2016.1.8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
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.
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Affiliation(s)
- Zoltán Szeberin
- Department of Vascular Surgery, Semmelweis University , Budapest , Hungary
| | - Balázs Nemes
- Department of Vascular Surgery, Semmelweis University , Budapest , Hungary
| | - Csaba Csobay-Novák
- Department of Vascular Surgery, Semmelweis University , Budapest , Hungary
| | - Zsuzsa Mihály
- Department of Vascular Surgery, Semmelweis University , Budapest , Hungary
| | - László Entz
- Department of Vascular Surgery, Semmelweis University , Budapest , Hungary
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7
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Wörz S, Schenk JP, Alrajab A, von Tengg-Kobligk H, Rohr K, Arnold R. 3D Geometric Analysis of the Pediatric Aorta in 3D MRA Follow-Up Images with Application to Aortic Coarctation. Methods Inf Med 2016; 55:455-462. [PMID: 27405687 DOI: 10.3414/me15-01-0104] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2015] [Accepted: 04/18/2016] [Indexed: 11/09/2022]
Abstract
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.
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Affiliation(s)
- Stefan Wörz
- Stefan Wörz, BioQuant Center, BQ 20, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany, E-mail:
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8
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Rengier F, Wörz S, Melzig C, Ley S, Fink C, Benjamin N, Partovi S, von Tengg-Kobligk H, Rohr K, Kauczor HU, Grünig E. Automated 3D Volumetry of the Pulmonary Arteries based on Magnetic Resonance Angiography Has Potential for Predicting Pulmonary Hypertension. PLoS One 2016; 11:e0162516. [PMID: 27626802 PMCID: PMC5023190 DOI: 10.1371/journal.pone.0162516] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2016] [Accepted: 08/24/2016] [Indexed: 11/18/2022] Open
Abstract
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.
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Affiliation(s)
- Fabian Rengier
- Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany
- Translational Lung Research Center (TLRC), Member of the German Center for Lung Research (DZL), University of Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany
- Department of Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
- * E-mail:
| | - Stefan Wörz
- Department of Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, BIOQUANT, IPMB, and German Cancer Research Center (DKFZ), Im Neuenheimer Feld 267, 69120 Heidelberg, Germany
| | - Claudius Melzig
- Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany
- Translational Lung Research Center (TLRC), Member of the German Center for Lung Research (DZL), University of Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany
| | - Sebastian Ley
- Radiology Isar Klinikum, Sonnenstrasse 22-24, 80331 Munich, Germany
- Clinical Radiology, Ludwig Maximilians University Hospital Munich, Marchioninistraße 15, 81377 Munich, Germany
| | - Christian Fink
- Institute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
- Department of Radiology, AKH Celle, Siemensplatz 4, 29223 Celle, Germany
| | - Nicola Benjamin
- Translational Lung Research Center (TLRC), Member of the German Center for Lung Research (DZL), University of Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany
- Centre for Pulmonary Hypertension, Thoraxklinik at the University Hospital Heidelberg, Röntgenstraße 1, 69126 Heidelberg, Germany
| | - Sasan Partovi
- Department of Radiology, University Hospitals Case Medical Center, Case Western Reserve University, 11100 Euclid Ave, Cleveland, Ohio, United States of America
| | - Hendrik von Tengg-Kobligk
- Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany
- Department of Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
- Institute for Diagnostic, Interventional and Paediatric Radiology, University Hospital Bern, Inselspital, Freiburgstr. 10, 3010 Bern, Switzerland
| | - Karl Rohr
- Department of Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, BIOQUANT, IPMB, and German Cancer Research Center (DKFZ), Im Neuenheimer Feld 267, 69120 Heidelberg, Germany
| | - Hans-Ulrich Kauczor
- Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany
- Translational Lung Research Center (TLRC), Member of the German Center for Lung Research (DZL), University of Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany
- Department of Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
| | - Ekkehard Grünig
- Translational Lung Research Center (TLRC), Member of the German Center for Lung Research (DZL), University of Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany
- Centre for Pulmonary Hypertension, Thoraxklinik at the University Hospital Heidelberg, Röntgenstraße 1, 69126 Heidelberg, Germany
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9
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Increasing the feasibility of minimally invasive procedures in type A aortic dissections: a framework for segmentation and quantification. Int J Comput Assist Radiol Surg 2015; 11:243-52. [PMID: 26319128 DOI: 10.1007/s11548-015-1283-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2015] [Accepted: 08/13/2015] [Indexed: 10/23/2022]
Abstract
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.
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Volonghi P, Tresoldi D, Cadioli M, Usuelli AM, Ponzini R, Morbiducci U, Esposito A, Rizzo G. Automatic extraction of three-dimensional thoracic aorta geometric model from phase contrast MRI for morphometric and hemodynamic characterization. Magn Reson Med 2015; 75:873-82. [PMID: 25754538 DOI: 10.1002/mrm.25630] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2014] [Revised: 12/19/2014] [Accepted: 01/05/2015] [Indexed: 11/11/2022]
Abstract
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.
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Affiliation(s)
- Paola Volonghi
- Institute of Molecular Bioimaging and Physiology, CNR, Segrate (MI), Italy
| | - Daniele Tresoldi
- Institute of Molecular Bioimaging and Physiology, CNR, Segrate (MI), Italy
| | | | - Antonio M Usuelli
- Institute of Molecular Bioimaging and Physiology, CNR, Segrate (MI), Italy
| | | | - Umberto Morbiducci
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy
| | - Antonio Esposito
- Department of Radiology, Scientific Institute H.S. Raffaele, Milan, Italy
| | - Giovanna Rizzo
- Institute of Molecular Bioimaging and Physiology, CNR, Segrate (MI), Italy
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11
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Kotelis D, Brenke C, Wörz S, Rengier F, Rohr K, Kauczor HU, Böckler D, von Tengg-Kobligk H. Aortic morphometry at endograft position as assessed by 3D image analysis affects risk of type I endoleak formation after TEVAR. Langenbecks Arch Surg 2015; 400:523-9. [PMID: 25702140 DOI: 10.1007/s00423-015-1291-1] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2014] [Accepted: 02/12/2015] [Indexed: 10/24/2022]
Abstract
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.
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Affiliation(s)
- Drosos Kotelis
- Department of Vascular and Endovascular Surgery, Heidelberg University Hospital, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany,
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12
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Müller-Eschner M, Müller T, Biesdorf A, Wörz S, Rengier F, Böckler D, Kauczor HU, Rohr K, von Tengg-Kobligk H. 3D morphometry using automated aortic segmentation in native MR angiography: an alternative to contrast enhanced MRA? Cardiovasc Diagn Ther 2014; 4:80-7. [PMID: 24834406 DOI: 10.3978/j.issn.2223-3652.2013.10.06] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2013] [Accepted: 10/28/2013] [Indexed: 11/14/2022]
Abstract
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.
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Affiliation(s)
- Matthias Müller-Eschner
- 1 Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Germany ; 2 Department of Radiology, German Cancer Research Center, Heidelberg, Germany ; 3 Dept. Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, BIOQUANT, IPMB, and DKFZ Heidelberg; 4 Department of Vascular and Endovascular Surgery, University Hospital Heidelberg, Germany ; 5 Institute of Diagnostic, Interventional and Pediatric Radiology, University Hospital Bern, Inselspital, Bern, Switzerland
| | - Tobias Müller
- 1 Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Germany ; 2 Department of Radiology, German Cancer Research Center, Heidelberg, Germany ; 3 Dept. Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, BIOQUANT, IPMB, and DKFZ Heidelberg; 4 Department of Vascular and Endovascular Surgery, University Hospital Heidelberg, Germany ; 5 Institute of Diagnostic, Interventional and Pediatric Radiology, University Hospital Bern, Inselspital, Bern, Switzerland
| | - Andreas Biesdorf
- 1 Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Germany ; 2 Department of Radiology, German Cancer Research Center, Heidelberg, Germany ; 3 Dept. Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, BIOQUANT, IPMB, and DKFZ Heidelberg; 4 Department of Vascular and Endovascular Surgery, University Hospital Heidelberg, Germany ; 5 Institute of Diagnostic, Interventional and Pediatric Radiology, University Hospital Bern, Inselspital, Bern, Switzerland
| | - Stefan Wörz
- 1 Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Germany ; 2 Department of Radiology, German Cancer Research Center, Heidelberg, Germany ; 3 Dept. Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, BIOQUANT, IPMB, and DKFZ Heidelberg; 4 Department of Vascular and Endovascular Surgery, University Hospital Heidelberg, Germany ; 5 Institute of Diagnostic, Interventional and Pediatric Radiology, University Hospital Bern, Inselspital, Bern, Switzerland
| | - Fabian Rengier
- 1 Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Germany ; 2 Department of Radiology, German Cancer Research Center, Heidelberg, Germany ; 3 Dept. Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, BIOQUANT, IPMB, and DKFZ Heidelberg; 4 Department of Vascular and Endovascular Surgery, University Hospital Heidelberg, Germany ; 5 Institute of Diagnostic, Interventional and Pediatric Radiology, University Hospital Bern, Inselspital, Bern, Switzerland
| | - Dittmar Böckler
- 1 Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Germany ; 2 Department of Radiology, German Cancer Research Center, Heidelberg, Germany ; 3 Dept. Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, BIOQUANT, IPMB, and DKFZ Heidelberg; 4 Department of Vascular and Endovascular Surgery, University Hospital Heidelberg, Germany ; 5 Institute of Diagnostic, Interventional and Pediatric Radiology, University Hospital Bern, Inselspital, Bern, Switzerland
| | - Hans-Ulrich Kauczor
- 1 Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Germany ; 2 Department of Radiology, German Cancer Research Center, Heidelberg, Germany ; 3 Dept. Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, BIOQUANT, IPMB, and DKFZ Heidelberg; 4 Department of Vascular and Endovascular Surgery, University Hospital Heidelberg, Germany ; 5 Institute of Diagnostic, Interventional and Pediatric Radiology, University Hospital Bern, Inselspital, Bern, Switzerland
| | - Karl Rohr
- 1 Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Germany ; 2 Department of Radiology, German Cancer Research Center, Heidelberg, Germany ; 3 Dept. Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, BIOQUANT, IPMB, and DKFZ Heidelberg; 4 Department of Vascular and Endovascular Surgery, University Hospital Heidelberg, Germany ; 5 Institute of Diagnostic, Interventional and Pediatric Radiology, University Hospital Bern, Inselspital, Bern, Switzerland
| | - Hendrik von Tengg-Kobligk
- 1 Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Germany ; 2 Department of Radiology, German Cancer Research Center, Heidelberg, Germany ; 3 Dept. Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, BIOQUANT, IPMB, and DKFZ Heidelberg; 4 Department of Vascular and Endovascular Surgery, University Hospital Heidelberg, Germany ; 5 Institute of Diagnostic, Interventional and Pediatric Radiology, University Hospital Bern, Inselspital, Bern, Switzerland
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True four-dimensional analysis of thoracic aortic displacement and distension using model-based segmentation of computed tomography angiography. Int J Cardiovasc Imaging 2013; 30:185-94. [DOI: 10.1007/s10554-013-0307-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2013] [Accepted: 10/05/2013] [Indexed: 10/26/2022]
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14
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Craiem D, Casciaro ME, Graf S, Chironi G, Simon A, Armentano RL. Effects of aging on thoracic aorta size and shape: a non-contrast CT study. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2013; 2012:4986-9. [PMID: 23367047 DOI: 10.1109/embc.2012.6347112] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
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.
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Affiliation(s)
- Damian Craiem
- Favaloro University, Facultad de Ciencias Exactas y Naturales, Buenos Aires, Argentina.
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15
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Centerline is Not as Accurate as Outer Curvature Length to Estimate Thoracic Endograft Length. Eur J Vasc Endovasc Surg 2013; 46:82-6. [DOI: 10.1016/j.ejvs.2013.04.012] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2012] [Accepted: 04/04/2013] [Indexed: 11/17/2022]
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16
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Akhtar NJ, Oderich GS, Vrtiska TJ, Williamson EE, Araoz PA. Computed tomography angiography of hybrid thoracic endovascular aortic repair of the aortic arch. Expert Rev Cardiovasc Ther 2013; 11:589-606. [PMID: 23621141 DOI: 10.1586/erc.13.47] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
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.
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Affiliation(s)
- Nila J Akhtar
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
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17
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Chiu P, Lee HP, Venkatesh SK, Ho P. Anatomical characteristics of the thoracic aortic arch in an Asian population. Asian Cardiovasc Thorac Ann 2013; 21:151-9. [PMID: 24532612 DOI: 10.1177/0218492312449637] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
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.
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Affiliation(s)
- Peixuan Chiu
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Heow Pueh Lee
- Department of Mechanical Engineering, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Sudhakar K Venkatesh
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Pei Ho
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
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18
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Midulla M, Moreno R, Negre-Salvayre A, Nicoud F, Pruvo JP, Haulon S, Rousseau H. Impact of endografting on the thoracic aortic anatomy: comparative analysis of the aortic geometry before and after the endograft implantation. Cardiovasc Intervent Radiol 2013; 37:69-76. [PMID: 23483287 DOI: 10.1007/s00270-013-0601-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2012] [Accepted: 01/30/2013] [Indexed: 11/30/2022]
Abstract
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.
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Affiliation(s)
- Marco Midulla
- Cardiovascular and Interventional Radiology, University Hospital of Lille, Lille, France,
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19
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Müller-Eschner M, Rengier F, Partovi S, Weber TF, Kopp-Schneider A, Geisbüsch P, Kauczor HU, von Tengg-Kobligk H. Accuracy and variability of semiautomatic centerline analysis versus manual aortic measurement techniques for TEVAR. Eur J Vasc Endovasc Surg 2013; 45:241-7. [PMID: 23318135 DOI: 10.1016/j.ejvs.2012.12.003] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2012] [Accepted: 12/06/2012] [Indexed: 10/27/2022]
Abstract
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.
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Affiliation(s)
- M Müller-Eschner
- Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany
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Beller C, von Tengg-Kobligk H. Computermodellierung und multimodale 4D-Bildgebung für Risikostratifizierung und Operationsplanung bei Erkrankungen der thorakalen Aorta. ZEITSCHRIFT FUR HERZ THORAX UND GEFASSCHIRURGIE 2012. [DOI: 10.1007/s00398-012-0922-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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21
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Biesdorf A, Rohr K, Feng D, von Tengg-Kobligk H, Rengier F, Böckler D, Kauczor HU, Wörz S. Segmentation and quantification of the aortic arch using joint 3D model-based segmentation and elastic image registration. Med Image Anal 2012; 16:1187-201. [DOI: 10.1016/j.media.2012.05.010] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2011] [Revised: 05/13/2012] [Accepted: 05/31/2012] [Indexed: 11/25/2022]
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22
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Craiem D, Chironi G, Redheuil A, Casciaro M, Mousseaux E, Simon A, Armentano RL. Aging impact on thoracic aorta 3D morphometry in intermediate-risk subjects: looking beyond coronary arteries with non-contrast cardiac CT. Ann Biomed Eng 2011; 40:1028-38. [PMID: 22173558 DOI: 10.1007/s10439-011-0487-y] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2011] [Accepted: 12/05/2011] [Indexed: 11/30/2022]
Abstract
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.
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Affiliation(s)
- Damian Craiem
- Favaloro University, Av. Belgrano 1723, CP 1093 Buenos Aires, Argentina.
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23
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Abstract
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.
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Reliability of Semiautomatic Centerline Analysis versus Manual Aortic Measurement Techniques for TEVAR among Non-experts. Eur J Vasc Endovasc Surg 2011; 42:324-31. [DOI: 10.1016/j.ejvs.2011.04.019] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2011] [Accepted: 04/08/2011] [Indexed: 11/21/2022]
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Development of in vivo quantitative geometric mapping of the aortic arch for advanced endovascular aortic repair: feasibility and preliminary results. J Vasc Interv Radiol 2011; 22:980-6. [PMID: 21459612 DOI: 10.1016/j.jvir.2011.01.434] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2010] [Revised: 12/19/2010] [Accepted: 01/11/2011] [Indexed: 11/23/2022] Open
Abstract
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.
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