Abstract

Aortic dissection continues to be responsible for significant morbidity and mortality, although recent advances in medical data assimilation and in experimental and in silico models have improved our understanding of the initiation and progression of the accumulation of blood within the aortic wall. Hence, there remains a pressing necessity for innovative and enhanced models to more accurately characterize the associated pathological changes. Early on, experimental models were employed to uncover mechanisms in aortic dissection, such as hemodynamic changes and alterations in wall microstructure, and to assess the efficacy of medical implants. While experimental models were once the only option available, more recently they are also being used to validate in silico models. Based on an improved understanding of the deteriorated microstructure of the aortic wall, numerous multiscale material models have been proposed in recent decades to study the state of stress in dissected aortas, including the changes associated with damage and failure. Furthermore, when integrated with accessible patient-derived medical data, in silico models prove to be an invaluable tool for identifying correlations between hemodynamics, wall stresses, or thrombus formation in the deteriorated aortic wall. They are also advantageous for model-guided design of medical implants with the aim of evaluating the deployment and migration of implants in patients. Nonetheless, the utility of in silico models depends largely on patient-derived medical data, such as chosen boundary conditions or tissue properties. In this review article, our objective is to provide a thorough summary of medical data elucidating the pathological alterations associated with this disease. Concurrently, we aim to assess experimental models, as well as multiscale material and patient data-informed in silico models, that investigate various aspects of aortic dissection. In conclusion, we present a discourse on future perspectives, encompassing aspects of disease modeling, numerical challenges, and clinical applications, with a particular focus on aortic dissection. The aspiration is to inspire future studies, deepen our comprehension of the disease, and ultimately shape clinical care and treatment decisions.

View details for DOI 10.1016/j.pmatsci.2024.101363

View details for PubMedID 39830801

View details for PubMedCentralID PMC11737592

Abstract

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Coronary CT angiography (CTA) is increasingly used for cardiac diagnosis. Dose modulation techniques can reduce radiation dose, but resulting functional images are noisy and challenging for functional analysis. This retrospective study describes and evaluates a deep learning method for denoising functional cardiac imaging, taking advantage of multiphase information in a 3D convolutional neural network. Coronary CT angiograms (n = 566) were used to derive synthetic data for training. Deep learning-based image denoising (DLID) was compared with unprocessed images and a standard noise reduction algorithm (BM3D). Noise and signal-to-noise ratio measurements, as well as expert evaluation of image quality were performed. To validate the use of the denoised images for cardiac quantification, threshold-based segmentation was performed, and results were compared with manual measurements on unprocessed images. Deep learning-based denoised images showed significantly improved noise compared with standard denoising-based images (SD of left ventricular blood pool, 20.3 ± 42.5 HU versus 33.4 ± 39.8 HU for DLID versus BM3D, P < .0001). Expert evaluations of image quality were significantly higher in deep learningbased denoised images compared with standard denoising. Semiautomatic left ventricular size measurements on deep learning-based denoised images showed excellent correlation with expert quantification on unprocessed images (intraclass correlation coefficient, 0.97). Deep learning-based denoising using a 3D approach resulted in excellent denoising performance and facilitated valid automatic processing of cardiac functional imaging. ©RSNA, 2024.

View details for DOI 10.1148/ryai.230153

View details for PubMedID 38416035

Abstract

Understanding the complex interplay between morphologic and hemodynamic features in aortic dissection is critical for risk stratification and for the development of individualized therapy. This work evaluates the effects of entry and exit tear size on the hemodynamics in type B aortic dissection by comparing fluid-structure interaction (FSI) simulations with in vitro 4D-flow magnetic resonance imaging (MRI). A baseline patient-specific 3D-printed model and two variants with modified tear size (smaller entry tear, smaller exit tear) were embedded into a flow- and pressure-controlled setup to perform MRI as well as 12-point catheter-based pressure measurements. The same models defined the wall and fluid domains for FSI simulations, for which boundary conditions were matched with measured data. Results showed exceptionally well matched complex flow patterns between 4D-flow MRI and FSI simulations. Compared to the baseline model, false lumen flow volume decreased with either a smaller entry tear (- 17.8 and - 18.5%, for FSI simulation and 4D-flow MRI, respectively) or smaller exit tear (- 16.0 and - 17.3%). True to false lumen pressure difference (initially 11.0 and 7.9 mmHg, for FSI simulation and catheter-based pressure measurements, respectively) increased with a smaller entry tear (28.9 and 14.6 mmHg), and became negative with a smaller exit tear (- 20.6 and - 13.2 mmHg). This work establishes quantitative and qualitative effects of entry or exit tear size on hemodynamics in aortic dissection, with particularly notable impact observed on FL pressurization. FSI simulations demonstrate acceptable qualitative and quantitative agreement with flow imaging, supporting its deployment in clinical studies.

View details for DOI 10.1038/s41598-023-49942-0

View details for PubMedID 38110526

View details for PubMedCentralID PMC10728172

Abstract

To describe the design and methodological approach of a multicenter, retrospective study to externally validate a clinical and imaging-based model for predicting the risk of late adverse events in patients with initially uncomplicated type B aortic dissection (uTBAD).The Registry of Aortic Diseases to Model Adverse Events and Progression (ROADMAP) is a collaboration between 10 academic aortic centers in North America and Europe. Two centers have previously developed and internally validated a recently developed risk prediction model. Clinical and imaging data from eight ROADMAP centers will be used for external validation. Patients with uTBAD who survived the initial hospitalization between January 1, 2001, and December 31, 2013, with follow-up until 2020, will be retrospectively identified. Clinical and imaging data from the index hospitalization and all follow-up encounters will be collected at each center and transferred to the coordinating center for analysis. Baseline and follow-up CT scans will be evaluated by cardiovascular imaging experts using a standardized technique.The primary end point is the occurrence of late adverse events, defined as aneurysm formation (≥6 cm), rapid expansion of the aorta (≥1 cm/y), fatal or nonfatal aortic rupture, new refractory pain, uncontrollable hypertension, and organ or limb malperfusion. The previously derived multivariable model will be externally validated by using Cox proportional hazards regression modeling.This study will show whether a recent clinical and imaging-based risk prediction model for patients with uTBAD can be generalized to a larger population, which is an important step toward individualized risk stratification and therapy.Keywords: CT Angiography, Vascular, Aorta, Dissection, Outcomes Analysis, Aortic Dissection, MRI, TEVAR© RSNA, 2022See also the commentary by Rajiah in this issue.

View details for DOI 10.1148/ryct.220039

View details for PubMedID 36601455

View details for PubMedCentralID PMC9806732

Abstract

All patients surviving an acute aortic dissection require continued lifelong surveillance of their diseased aorta. Late complications, driven predominantly by chronic false lumen degeneration and aneurysm formation, often require surgical, endovascular, or hybrid interventions to treat or prevent aortic rupture. Imaging plays a central role in the medical decision-making of patients with chronic aortic dissection. Accurate aortic diameter measurements and rigorous, systematic documentation of diameter changes over time with different imaging equipment and modalities pose a range of practical challenges in these complex patients. Currently, no guidelines or recommendations for imaging surveillance in patients with chronic aortic dissection exist. In this document, we present state-of-the-art imaging and measurement techniques for patients with chronic aortic dissection and clarify the need for standardized measurements and reporting for lifelong surveillance. We also examine the emerging role of imaging and computer simulations to predict aortic false lumen degeneration, remodeling, and biomechanical failure from morphological and hemodynamic features. These insights may improve risk stratification, individualize contemporary treatment options, and potentially aid in the conception of novel treatment strategies in the future.

View details for DOI 10.1161/HCI.0000000000000075

View details for PubMedID 35172599

Abstract

Credible computational fluid dynamic (CFD) simulations of aortic dissection are challenging, because the defining parallel flow channels-the true and the false lumen-are separated from each other by a more or less mobile dissection membrane, which is made up of a delaminated portion of the elastic aortic wall. We present a comprehensive numerical framework for CFD simulations of aortic dissection, which captures the complex interplay between physiologic deformation, flow, pressures, and time-averaged wall shear stress (TAWSS) in a patient-specific model. Our numerical model includes (1) two-way fluid-structure interaction (FSI) to describe the dynamic deformation of the vessel wall and dissection flap; (2) prestress and (3) external tissue support of the structural domain to avoid unphysiologic dilation of the aortic wall and stretching of the dissection flap; (4) tethering of the aorta by intercostal and lumbar arteries to restrict translatory motion of the aorta; and a (5) independently defined elastic modulus for the dissection flap and the outer vessel wall to account for their different material properties. The patient-specific aortic geometry is derived from computed tomography angiography (CTA). Three-dimensional phase contrast magnetic resonance imaging (4D flow MRI) and the patient's blood pressure are used to inform physiologically realistic, patient-specific boundary conditions. Our simulations closely capture the cyclical deformation of the dissection membrane, with flow simulations in good agreement with 4D flow MRI. We demonstrate that decreasing flap stiffness from [Formula: see text] to [Formula: see text] kPa (a) increases the displacement of the dissection flap from 1.4 to 13.4 mm, (b) decreases the surface area of TAWSS by a factor of 2.3, (c) decreases the mean pressure difference between true lumen and false lumen by a factor of 0.63, and (d) decreases the true lumen flow rate by up to 20% in the abdominal aorta. We conclude that the mobility of the dissection flap substantially influences local hemodynamics and therefore needs to be accounted for in patient-specific simulations of aortic dissection. Further research to accurately measure flap stiffness and its local variations could help advance future CFD applications.

View details for DOI 10.1007/s10237-020-01294-8

View details for PubMedID 31993829

Abstract

Patients with medically treated type B aortic dissection (TBAD) remain at significant risk for late adverse events (LAEs). We hypothesize that not only initial morphological features, but also their change over time at follow-up are associated with LAEs.Baseline and 188 follow-up computed tomography (CT) scans with a median follow-up time of 4 years (range, 10 days to 12.7 years) of 47 patients with acute uncomplicated TBAD were retrospectively reviewed. Morphological features (n = 8) were quantified at baseline and each follow-up. Medical records were reviewed for LAEs, which were defined according to current guidelines. To assess the effects of changes of morphological features over time, the linear mixed effects models were combined with Cox proportional hazards regression for the time-to-event outcome using a joint modeling approach.LAEs occurred in 21 of 47 patients at a median of 6.6 years (95% confidence interval [CI], 5.1-11.2 years). Among the 8 investigated morphological features, the following 3 features showed strong association with LAEs: increase in partial false lumen thrombosis area (hazard ratio [HR], 1.39; 95% CI, 1.18-1.66 per cm2 increase; P < .001), increase of major aortic diameter (HR, 1.24; 95% CI, 1.13-1.37 per mm increase; P < .001), and increase in the circumferential extent of false lumen (HR, 1.05; 95% CI, 1.01-1.10 per degree increase; P < .001).In medically treated TBAD, increases in aortic diameter, new or increased partial false lumen thrombosis area, and increases of circumferential extent of the false lumen are strongly associated with LAEs.

View details for DOI 10.1016/j.jtcvs.2019.10.074

View details for PubMedID 31839226

Abstract

Limited intimal tears (LITs) of the aorta (Class 3 dissection variant) are the least common form of aortic pathology in patients presenting with acute aortic syndrome (AAS). LITs are difficult to detect on imaging and may be underappreciated.This study sought to describe the frequency, pathology, treatment, and outcome of LITs compared with other AAS, and to demonstrate that LITs can be detected pre-operatively by contemporary imaging.The authors retrospectively reviewed 497 patients admitted for 513 AAS events at a single academic aortic center between 2003 and 2012. AAS were classified into classic dissection (AD), intramural hematoma, LIT, penetrating atherosclerotic ulcer, and rupturing thoracic aortic aneurysm. The prevalence, pertinent risk factors, and detailed imaging findings with surgical and pathological correlation of LITs are described. Management, early outcomes, and late mortality are reported.Among 497 patients with AAS, the authors identified 24 LITs (4.8% of AAS) in 16 men and 8 women (17 type A, 7 type B). Patients with LITs were older than those with AD, and type A LITs had similarly dilated ascending aortas as type A AD. Three patients presented with rupture. Eleven patients underwent urgent surgical aortic replacement, and 2 patients underwent endovascular repair. Medial degeneration was present in all surgical specimens. In-hospital mortality was 4% (1 of 24), and in total, 5 patients with LIT died subsequently at 1.5 years (interquartile range [IQR]: 0.3 to 2.5 years). Computed tomography imaging detected all but 1 LIT, best visualized on volume-rendered images.LITs are rare acute aortic lesions within the dissection spectrum, with similar presentation, complications, and outcomes compared with AD and intramural hematoma. Awareness of this lesion allows pre-operative diagnosis using high-quality computed tomography angiography.

View details for PubMedID 29903350

Abstract

Medical treatment of initially uncomplicated acute Stanford type-B aortic dissection is associated with a high rate of late adverse events. Identification of individuals who potentially benefit from preventive endografting is highly desirable.The association of computed tomography imaging features with late adverse events was retrospectively assessed in 83 patients with acute uncomplicated Stanford type-B aortic dissection, followed over a median of 850 (interquartile range 247-1824) days. Adverse events were defined as fatal or nonfatal aortic rupture, rapid aortic growth (>10 mm/y), aneurysm formation (≥6 cm), organ or limb ischemia, or new uncontrollable hypertension or pain. Five significant predictors were identified using multivariable Cox regression analysis: connective tissue disease (hazard ratio [HR] 2.94, 95% confidence interval [CI]: 1.29-6.72; P=0.01), circumferential extent of false lumen in angular degrees (HR 1.03 per degree, 95% CI: 1.01-1.04, P=0.003), maximum aortic diameter (HR 1.10 per mm, 95% CI: 1.02-1.18, P=0.015), false lumen outflow (HR 0.999 per mL/min, 95% CI: 0.998-1.000; P=0.055), and number of intercostal arteries (HR 0.89 per n, 95% CI: 0.80-0.98; P=0.024). A prediction model was constructed to calculate patient specific risk at 1, 2, and 5 years and to stratify patients into high-, intermediate-, and low-risk groups. The model was internally validated by bootstrapping and showed good discriminatory ability with an optimism-corrected C statistic of 70.1%.Computed tomography imaging-based morphological features combined into a prediction model may be able to identify patients at high risk for late adverse events after an initially uncomplicated type-B aortic dissection.

View details for DOI 10.1161/CIRCIMAGING.116.005709

View details for PubMedID 28360261

Abstract

Patients with Stanford type B aortic dissections (ADs) are at risk of long-term disease progression and late complications. The aim of this study was to evaluate the natural course and evolution of acute type B AD and intramural hematomas (IMHs) in patients who presented without complications during their initial hospital admission and who were treated with optimal medical management (MM).Databases from 2 aortic centers in Europe and the United States were used to identify 136 patients with acute type B AD (n = 92) and acute type B IMH (n = 44) who presented without complications during their index admission and were treated with MM. Computed tomography angiography scans were available at onset (≤14 days) and during follow-up for those patients. Relevant data, including evidence of adverse events during follow-up (AE; defined according to current guidelines), were retrieved from medical records and by reviewing computed tomography scan images. Aortic diameters were measured with dedicated 3-dimensional software.The 1-, 2-, and 5-year event-free survival rates of patients with type B AD were 84.3% (95% confidence interval [CI], 74.4-90.6), 75.4% (95% CI, 64.0-83.7), and 62.6% (95% CI, 68.9-73.6), respectively. Corresponding estimates for IMH were 76.5% (95% CI, 57.8-87.8), 76.5% (95% CI, 57.8-87.8), and 68.9% (95% CI, 45.2-83.9), respectively. In patients with type B AD, risk of an AE increased with aortic growth within the first 6 months after onset. A diameter increase of 5 mm in the first half year was associated with a relative risk for AE of 2.29 (95% CI, 1.70-3.09) compared with the median 6 months' growth of 2.4 mm. In approximately 60% of patients with IMH, the abnormality resolved within 12 months and in the patients with nonresolving IMH, risk of an adverse event was greatest in the first year after onset and remained stable thereafter.More than one third of patients with initially uncomplicated type B AD suffer an AE under MM within 5 years of initial diagnosis. In patients with nonresolving IMH, most adverse events are observed in the first year after onset. In patients with type B AD an early aortic growth is associated with a greater risk of AE.

View details for PubMedID 28668458

Abstract

To evaluate two methods for reducing metal artifacts in computed tomography (CT)--the metal deletion technique (MDT) and the selective algebraic reconstruction technique (SART)--and compare these methods with filtered back projection (FBP) and linear interpolation (LI).The institutional review board approved this retrospective HIPAA-compliant study; informed patient consent was waived. Simulated projection data were calculated for a phantom that contained water, soft tissue, bone, and iron. Clinical projection data were obtained retrospectively from 11 consecutively identified CT scans with metal streak artifacts, with a total of 178 sections containing metal. Each scan was reconstructed using FBP, LI, SART, and MDT. The simulated scans were evaluated quantitatively by calculating the average error in Hounsfield units for each pixel compared with the original phantom. Two radiologists who were blinded to the reconstruction algorithms used qualitatively evaluated the clinical scans, ranking the overall severity of artifacts for each algorithm. P values for comparisons of the image quality ranks were calculated from the binomial distribution.The simulations showed that MDT reduces artifacts due to photon starvation, beam hardening, and motion and does not introduce new streaks between metal and bone. MDT had the lowest average error (76% less than FBP, 42% less than LI, 17% less than SART). Blinded comparison of the clinical scans revealed that MDT had the best image quality 100% of the time (95% confidence interval: 72%, 100%). LI had the second best image quality, and SART and FBP had the worst image quality. On images from two CT scans, as compared with images generated by the scanner, MDT revealed information of potential clinical importance.For a wide range of scans, MDT yields reduced metal streak artifacts and better-quality images than does FBP, LI, or SART.http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.11101782/-/DC1.

View details for DOI 10.1148/radiol.11101782

View details for Web of Science ID 000290898100030

View details for PubMedID 21357521

Abstract

Several recently introduced 'new' techniques in computed tomography--iterative reconstruction, gated cardiac CT, multiple-source, and dual-energy CT--actually date back to the early days of CT. We review the historic origins and evolution of these techniques, which may provide some insight into the latest innovations in commercial CT systems.

View details for DOI 10.1007/s00330-011-2056-z

View details for Web of Science ID 000286943600013

View details for PubMedID 21249371

Abstract

The purpose of this work was to measure the accuracy of dual-energy computed tomography for identifying iodine and calcium and to determine the effects of calcium suppression in phantoms and lower-extremity computed tomographic (CT) angiographic data sets.Using a three-material basis decomposition method for 80- and 140-kVp data, the accuracy of correctly identified contrast medium and calcium voxels and the mean attenuation before and after calcium suppression were computed. Experiments were first performed on a phantom of homogenous contrast medium and hydroxyapatite samples with mean attenuation of 57.2, 126, and 274 Hounsfield units (HU) and 50.0, 122, and 265 HU, respectively. Experiments were repeated in corresponding attenuation groups of voxels from manually segmented bones and contrast medium-enhanced arteries in a lower-extremity CT angiographic data set with mean attenuation of 293 and 434 HU, respectively. Calcium suppression in atherosclerotic plaques of a cadaveric specimen was also studied, using micro-computed tomography as a reference, and in a lower-extremity CT angiographic data set with substantial below-knee calcified plaques.Higher concentrations showed increased accuracy of iodine and hydroxyapatite identification of 87.4%, 99.7%, and 99.9% and 88.0%, 95.0%, and 99.9%, respectively. Calcium suppression was also more accurate with higher concentrations of iodine and hydroxyapatite, with mean attenuation after suppression of 47.1, 122, and 263 HU and 7.14, 11.6, and 12.6 HU, respectively. Similar patterns were seen in the corresponding attenuation groups of the contrast medium-enhanced arteries and bone in the clinical data set, which had overall accuracy of 81.3% and 78.9%, respectively, and mean attenuation after calcium suppression of 254 and 73.7 HU, respectively. The suppression of calcified atherosclerotic plaque was accurate compared with the micro-CT reference; however, the suppression in the clinical data set showed probable inappropriate suppression of the small vessels.Dual-energy computed tomography can detect and differentiate between contrast medium and calcified tissues, but its accuracy is dependent on the CT density of tissues and limited when CT attenuation is low.

View details for DOI 10.1016/j.acra.2008.09.004

View details for Web of Science ID 000262536500007

View details for PubMedID 19124101

Abstract

Accurate arterial centerline extraction is essential for comprehensive visualization in CT Angiography. Time consuming manual tracking is needed when automated methods fail to track centerlines through severely diseased and occluded vessels. A previously described algorithm, Partial Vector Space Projection (PVSP), which uses vessel shape information from a database to bridge occlusions of the femoropopliteal artery, has a limited accuracy in long (>100 mm) occlusions. In this article we introduce a new algorithm, Intermediate Point Detection (IPD), which uses calcifications in the occluded artery to provide additional information about the location of the centerline to facilitate improvement in PVSP performance. It identifies calcified plaque in image space to find the most useful point within the occlusion to improve the estimate from PVSP. In this algorithm candidates for calcified plaque are automatically identified on axial CT slices in a restricted region around the estimate obtained from PVSP. A modified Canny edge detector identifies the edge of the calcified plaque and a convex polygon fit is used to find the edge of the calcification bordering the wall of the vessel. The Hough transform for circles estimates the center of the vessel on the slice, which serves as a candidate intermediate point. Each candidate is characterized by two scores based on radius and relative position within the occluded segment, and a polynomial function is constructed to define a net score representing the potential benefit of using this candidate for improving the centerline. We tested our approach in 44 femoropopliteal artery occlusions of lengths up to 398 mm in 30 patients with peripheral arterial occlusive disease. Centerlines were tracked manually by four-experts, twice each, with their mean serving as the reference standard. All occlusions were first interpolated with PVSP using a database of femoropopliteal arterial shapes obtained from a total of 60 subjects. Occlusions longer than 80 mm (N = 20) were then processed with the IPD algorithm, provided calcifications were found (N = 14). We used the maximum point-wise distance of an interpolated curve from the reference standard as our error metric. The IPD algorithm significantly reduced the average error of the initial PVSP from 2.76 to 1.86 mm (p < 0.01). The error was less than the clinically desirable 3 mm (smallest radius of the femoropopliteal artery) in 13 of 14 occlusions. The IPD algorithm achieved results within the range of the human readers in 11 of 14 cases. We conclude that the additional use of sparse but specific image space information, such as calcified atherosclerotic plaque, can be used to substantially improve the performance of a previously described knowledge-based method to restore the centerlines of femoropopliteal arterial occlusions.

View details for DOI 10.1118/1.2940194

View details for Web of Science ID 000257231700039

View details for PubMedID 18697561

View details for PubMedCentralID PMC2673553

Abstract

Curved planar reformation allows comprehensive visualization of arterial flow channels, providing information about calcified and noncalcified plaques and degrees of stenoses. Existing semiautomated centerline-extraction algorithms for curved planar reformation generation fail in severely diseased and occluded arteries. We explored whether contralateral shape information could be used to reconstruct centerlines through femoropopliteal occlusions. We obtained CT angiography data sets of 29 subjects (16m/13f, 19-86yo) without peripheral arterial occlusive disease and five consecutive subjects (1m/4f, 54-85yo) with unilateral femoropopliteal arterial occlusions. A gradient-based method was used to extract the femoropopliteal centerlines in nondiseased segments. Centerlines of the five occluded segments were manually determined by four experts, two times each. We interpolated missing centerlines in 2475 simulated occlusions of various occlusion lengths in nondiseased subjects. We used different curve registration methods (reflection, similarity, affine, and global polynomial) to align the nonoccluded segments, matched the end points of the occluded segments to the corresponding patent end points, and recorded maximum Euclidean distances to the known centerlines. We also compared our algorithm to an existing knowledge-based PCA interpolation algorithm using the nondiseased subjects. In the five subjects with real femoropopliteal occlusions, we measured the maximum Euclidean distance and the percentage of the interpolation that remained within a typical 3 mm radius vessel. In the nondiseased subjects, we found that the rigid registration methods were not significantly (p<0.750) different among themselves but were more accurate than the nonrigid methods (p<0.001). In simulations using nondiseased subjects, our method produced centerlines that stayed within 3 mm of a semiautomatically tracked centerline in occlusions up to 100 mm in length; however, the PCA method was significantly more accurate for all occlusions lengths. In the actual clinical cases, we found the following [occlusion length (mm):error (mm)]: 16.5:0.775, 42.0:1.54, 79.9:1.82, 145:3.23, and 292:6.13, which were almost always more accurate than the PCA algorithm. We conclude that the use of contralateral shape information, when available, is a promising method for the interpolation of centerlines through arterial occlusions.

View details for DOI 10.1118/1.2759603

View details for Web of Science ID 000249547200003

View details for PubMedID 17926944

Abstract

The study was approved by the institutional review board, and informed consent was obtained. The purpose of the study was to prospectively quantify the angular visibility range, determine the existence of orthogonal viewing pairs, and characterize the conditions that cause artifacts in multipath curved planar reformations (MPCPRs) of the peripheral arterial tree in 10 patients (eight men and two women; mean age, 69 years; range, 54-80 years) with peripheral arterial occlusive disease. Percentage of segments with the maximal possible visibility score of 1 was significantly greater (odds ratio, 1.42; P<.001) for MPCPRs than for maximum intensity projections. One or more orthogonal viewing pairs were identified for all above-knee arterial segments, and artifactual vessel distortion was observed when the vessel axis approached a horizontal course in MPCPRs.

View details for DOI 10.1148/radiol.2441060976

View details for Web of Science ID 000247436500032

View details for PubMedID 17495179

Abstract

We present a novel algorithm, Partial Vector Space Projection (PVSP), for estimation of missing data given a database of similar datasets, and demonstrate its use in restoring the centerlines through simulated occlusions of femoropopliteal arteries, derived from CT angiography data. The algorithm performs Principal Component Analysis (PCA) on a database of centerlines to obtain a set of orthonormal basis functions defined in a scaled and oriented frame of reference, and assumes that any curve not in the database can be represented as a linear combination of these basis functions. Using a database of centerlines derived from 30 normal femoropopliteal arteries, we evaluated the algorithm, and compared it to a correlation-based linear Minimum Mean Squared Error (MMSE) method, by deleting portions of a centerline for several occlusion lengths (OL: 10 mm, 25 mm, 50 mm, 75 mm, 100 mm, 125 mm, 150 mm, 175 mm and 200 mm). For each simulated occlusion, we projected the partially known dataset on the set of basis functions derived from the remaining 29 curves to restore the missing segment. We calculated the maximum point-wise distance (Maximum Departure or MD) between the actual and estimated centerline as the error metric. Mean (standard deviation) of MD increased from 0.18 (0.14) to 4.35 (2.23) as OL increased. The results were fairly accurate even for large occlusion lengths and are clinically useful. The results were consistently better than those using the MMSE method. Multivariate regression analysis found that OL and the root-mean-square error in the 2 cm proximal and distal to the occlusion accounted for most of the error.

View details for DOI 10.1016/j.media.2006.11.005

View details for Web of Science ID 000245596200005

View details for PubMedID 17218147

View details for PubMedCentralID PMC1989127

Abstract

To prospectively determine the range of aortopopliteal bolus transit times in patients with moderate-to-severe peripheral arterial occlusive disease (PAOD) as a guideline for developing injection strategies for computed tomographic (CT) angiography of peripheral arteries.The study protocol was approved by the local ethics board, and informed consent was obtained. Twenty patients with PAOD referred for CT angiography of the lower extremities were categorized into two groups, Fontaine stage IIb (group 1) and stage III or IV (group 2), and demographic information was collected. In all patients, a 16-mL test bolus was injected intravenously, and single-level dynamic acquisitions were obtained at the level of the abdominal aorta. After injection of a second 16-mL test bolus, dynamic acquisitions were obtained at the level of the knee (popliteal arteries). Aortopopliteal bolus transit times were calculated by subtracting the time to peak enhancement in the popliteal arteries from that in the aorta. Aortopopliteal transit speeds also were derived. Transit times and speeds were compared graphically between clinical stage groups. The time required for the contrast medium to enhance the entire peripheral arterial tree in patients with PAOD was estimated by using linear extrapolation.Sixteen men and four women with a mean age of 69 years (range, 49-86 years) were included. Twelve patients were included in group 1, and eight patients, in group 2. Aortopopliteal bolus transit times ranged from 4 to 24 seconds (median, 8 seconds) in all subjects, which corresponded to bolus transit speeds of 177 and 29 mm/sec, respectively. Wide overlap of transit times and transit speeds was observed between clinical stage groups. The estimated time needed for the bolus to enhance the entire peripheral arterial tree was 6-39 seconds.Aortopopliteal bolus transit times differ widely among patients and may be substantially delayed in all patients with PAOD. Empirical injection protocols should include an injection duration of 35 seconds or more, as well as an increased scanning delay, with table speeds of more than 30 mm/sec.

View details for DOI 10.1148/radiol.2363041392

View details for Web of Science ID 000231412600046

View details for PubMedID 16000649

Abstract

The purpose of this work was to determine the accuracy of predicting arterial enhancement from peripheral versus central venous test bolus injections at CT angiography (CTA).In 40 patients with abdominal aortic aneurysms, aortoiliac enhancement profiles were predicted by mathematical deconvolution of the time-attenuation response to a 16 ml test bolus injection. Injection sites were either a cubital vein (n = 20) or a central venous injection site (n = 20). The accuracy of predicting enhancement was quantified as the "off-predicted deviation" (calculated as mean squared differences between observed minus predicted enhancement values) in all patients.Off-predicted deviation was significantly smaller in the central venous injection group (17 +/- 6 HU) than the peripheral injection group (33 +/- 18 HU) (p < 0.001).Arterial enhancement at CTA can be mathematically predicted and controlled more accurately if a central venous injection site is used. Automated saline flushing of the veins might improve the accuracy of the mathematical model for peripheral injections.

View details for Web of Science ID 000167521000024

View details for PubMedID 11242230

Abstract

We conducted a novel quantitative three-dimensional analysis of computed tomography (CT) angiograms to establish the relationship between aortic geometry and age, sex, and body surface area in healthy subjects.Abdominal helical CT angiograms from 77 healthy potential renal donors (33 men/44 women; mean age, 44 years; age range, 19-67 years) were selected. In each dataset, orthonormal cross-sectional area and diameter measurements were obtained at 1-mm intervals along the automatically calculated central axis of the abdominal aorta. The aorta was subdivided into six consecutive anatomic segments (supraceliac, supramesenteric, suprarenal, inter-renal, proximal infrarenal, and distal infrarenal). The interrelated effects of anatomic segment, age, sex, and body surface area on cross-sectional dimensions were analyzed with linear mixed-effects and varying-coefficient statistical models.We found that significant effects of sex and of body surface area on aortic diameters were similar at all anatomic levels. The effect of age, however, was interrelated with anatomic position, and gradually decreasing slopes of significant diameter-versus-age relationships along the aorta, which ranged from 0.14 mm/y (P <.0001) proximally to 0.03 mm/y (P =.013) distally in the abdominal aorta, were shown.The abdominal aorta undergoes considerable geometric changes when a patient is between 19 and 67 years of age, leading to an increase of aortic taper with time. The hemodynamic consequences of this geometric evolution for the development of aortic disease still need to be established.

View details for Web of Science ID 000166576900022

View details for PubMedID 11137929

Abstract

To compare the uniformity of aortoiliac opacification obtained from uniphasic contrast medium injections versus individualized biphasic injections at computed tomographic (CT) angiography.Thirty-two patients with an abdominal aortic aneurysm underwent CT angiography. In 16 patients (group 1), 120 mL of contrast material was administered at a flow rate of 4 mL/sec. In the other 16 patients (group 2), biphasic injection protocols were computed by using mathematic deconvolution of each patient's time-attenuation response to a standardized test injection. Attenuation uniformity was quantified as the "plateau deviation" of enhancement values, which were calculated as the SD of the time-contiguous attenuation values observed during the 30-second scanning period.Group 2 patients received between 77 and 165 mL (mean, 115 mL) of contrast medium. Initial flow rates ranged from 4.1 to 10.0 mL/sec (mean, 6.8 mL/sec) for the first 4-6 seconds; continuing flow rates ranged from 2.0 to 4.8 mL/sec (mean, 3.1 mL/sec) for the remaining 24-26 seconds. The plateau deviation was significantly smaller in group 2 patients (19 HU) versus group 1 patients (38 HU, P <.001).At CT angiography, tailored biphasic injections led to more uniform aortoiliac enhancement, compared with standard uniphasic injections of contrast medium.

View details for Web of Science ID 000085023400009

View details for PubMedID 10671582

Abstract

The goal of this work was to develop a clinically applicable mathematical algorithm to analyze and optimize individual arterial enhancement in CT angiography (CTA).Assuming a time-invariant linear system, the discrete Fourier transform was used to calculate the transfer function of the system ("patient function") from the arterial time-attenuation response to a test bolus. The patient function was subsequently used to predict aortic enhancement in five select patients and to calculate optimized biphasic injection protocols in two of these patients undergoing CTA of the abdominal aorta.Arterial time-attenuation curves were accurately predicted in all patients. Optimized biphasic contrast agent injection protocols resulted in uniform aortic enhancement at the predefined level over the entire scanning period in both subjects despite markedly different contrast agent volumes and injection rates used.Fourier analysis of the time-attenuation response to a test bolus is a simple and feasible approach to optimize arterial enhancement in CTA.

View details for Web of Science ID 000080366000026

View details for PubMedID 10348458