Quantification Of Wall Thickness Research Articles

Efficient and Accurate 3D Thickness Measurement in Vessel Wall Imaging: Overcoming Limitations of 2D Approaches Using the Laplacian Method.

The clinical significance of measuring vessel wall thickness is widely acknowledged. Recent advancements have enabled high-resolution 3D scans of arteries and precise segmentation of their lumens and outer walls; however, most existing methods for assessing vessel wall thickness are 2D. Despite being valuable, reproducibility and accuracy of 2D techniques depend on the extracted 2D slices. Additionally, these methods fail to fully account for variations in wall thickness in all dimensions. Furthermore, most existing approaches are difficult to be extended into 3D and their measurements lack spatial localization and are primarily confined to lumen boundaries. We advocate for a shift in perspective towards recognizing vessel wall thickness measurement as inherently a 3D challenge and propose adapting the Laplacian method as an outstanding alternative. The Laplacian method is implemented using convolutions, ensuring its efficient and rapid execution on deep learning platforms. Experiments using digital phantoms and vessel wall imaging data are conducted to showcase the accuracy, reproducibility, and localization capabilities of the proposed approach. The proposed method produce consistent outcomes that remain independent of centerlines and 2D slices. Notably, this approach is applicable in both 2D and 3D scenarios. It allows for voxel-wise quantification of wall thickness, enabling precise identification of wall volumes exhibiting abnormal wall thickness. Our research highlights the urgency of transitioning to 3D methodologies for vessel wall thickness measurement. Such a transition not only acknowledges the intricate spatial variations of vessel walls, but also opens doors to more accurate, localized, and insightful diagnostic insights.

A shear horizontal phased array steering excitation technique for remnant wall thickness quantification

Precise wall loss quantification in pipe and plate structures is a critical and challenging task, especially in cases where direct access to the component is limited. Accurate knowledge of the remaining wall thickness allows for timely maintenance or replacement to avoid catastrophic failures. In this work, wall loss quantification is performed utilizing the cut-off frequency of mode SH1. The approach requires the excitation of SH1 across a range of frequencies. For this reason, a novel excitation technique using guided wave phased array steering is developed. Specifically, an array generating shear horizontal waves is employed. The influence of the array’s length, pitch, element width, and mode excitability on excitation is investigated. By appropriately phasing the elements of the array, mode SH1 is targeted and dynamically excited over a wide frequency-wavelength range. The directionality of SH1 is also studied, as in certain conditions, this can be critical for the success of the quantification. Simulation results show the technique can accurately quantify a 65 % wall thinning defect, offering a 15 % increase compared to established techniques. This is critical, as commonly, wall loss defects above 50 % are considered severe. Additionally, using electronic steering, rapid quantification can be achieved. Experiments using an EMAT and synthetic steering on an intact area and an artificially machined corrosion-like defect validate the technique.

PO-04-170 AUTOMATED CT-BASED PREDICTION OF VENTRICULAR ARRHYTHMIA

Robust risk stratification of post-myocardial infarction (MI) ventricular tachycardia (VT) is desirable to overcome the limitations of left ventricular ejection fraction (LVEF), the currently used criterion for implanting cardiac defibrillator devices. We hypothesized, that a fully automated CT-based technology could predict VT in post-MI patients. A fully automated CT image processing pipeline was implemented including AI-based LV wall segmentation followed by joint analysis and quantification of wall thickness (WT), intramural fat, and myocardial calcification (Fig.1A). A cohort of 132 patients with prior MI (66±11 years, 37±10% LVEF) with implanted cardiac devices underwent CT scan, and were subsequently followed by remote monitoring over an average of 6.6 years (80 ± 31 months). We analyzed the relationship between CT markers (WT, fat, calcification) and VT events at follow-up. Analysis of the wall thickness layers showed the optimal WT-derived marker was the ratio between areas of WT < 3mm and WT< 5mm (no VT 0.57±0.45 vs. VT 0.89±0.55; p<0.01). The amount of myocardial calcification was also found higher in patients with VT (no VT 0.10±0.38ml vs. VT 0.47±1.57ml, p=0.039), while the amount of fat did not differ significantly between groups (no VT 1.14±1.38ml vs. VT 1.21±1.01ml, p=0.771). The optimal cut-off for the WT 3/5mm ratio was 0.3. On Kaplan Meier analysis, this WT ratio was a powerful predictor of VT-free survival (Fig.1B, log rank P<0.01). In contrast, a LVEF<35% was not found to significantly relate to VT-free survival (Fig.1C, P=0.77). Automated analysis of post-MI scar is doable from CT images, allowing for improved risk stratification of future VT. The area of severe wall thinning divided by the total area of thinning appears to be the best marker of risk.

Simultaneous Highly Efficient Contrast-Free Lumen and Vessel Wall MR Imaging for Anatomical Assessment of Aortic Disease.

Bright-blood lumen and black-blood vessel wall imaging are required for the comprehensive assessment of aortic disease. These images are usually acquired separately, resulting in long examinations and potential misregistration between images. To characterize the performance of an accelerated and respiratory motion-compensated three-dimensional (3D) cardiac MRI technique for simultaneous contrast-free aortic lumen and vessel wall imaging with an interleaved T2 and inversion recovery prepared sequence (iT2Prep-BOOST). Prospective. A total of 30 consecutive patients with aortopathy referred for a clinically indicated cardiac MRI examination (9 females, mean age ± standard deviation: 32 ± 12 years). 1.5-T; bright-blood MR angiography (diaphragmatic navigator-gated T2-prepared 3D balanced steady-state free precession [bSSFP], T2Prep-bSSFP), breath-held black-blood two-dimensional (2D) half acquisition single-shot turbo spin echo (HASTE), and 3D bSSFP iT2Prep-BOOST. iT2Prep-BOOST bright-blood images were compared to T2prep-bSSFP images in terms of aortic vessel dimensions, lumen-to-myocardium contrast ratio (CR), and image quality (diagnostic confidence, vessel sharpness and presence of artifacts, assessed by three cardiologists on a 4-point scale, 1: nondiagnostic to 4: excellent). The iT2Prep-BOOST black-blood images were compared to 2D HASTE images for quantification of wall thickness. A visual comparison between computed tomography (CT) and iT2Prep-BOOST was performed in a patient with chronic aortic dissection. Paired t-tests, Wilcoxon signed-rank tests, intraclass correlation coefficient (ICC), Bland-Altman analysis. A P value < 0.05 was considered statistically significant. Bright-blood iT2Prep-BOOST resulted in significantly improved image quality (mean ± standard deviation 3.8 ± 0.5 vs. 3.3 ± 0.8) and CR (2.9 ± 0.8 vs. 1.8 ± 0.5) compared with T2Prep-bSSFP, with a shorter scan time (7.8 ± 1.7minutes vs. 12.9 ± 3.4minutes) while providing a complementary 3D black-blood image. Aortic lumen diameter and vessel wall thickness measurements in bright-blood and black-blood images were in good agreement with T2Prep-bSSFP and HASTE images (<0.02 cm and <0.005 cm bias, respectively) and good intrareader (ICC > 0.96) and interreader (ICC > 0.94) agreement was observed for all measurements. iT2Prep-BOOST might enable time-efficient simultaneous bright- and black-blood aortic imaging, with improved image quality compared to T2Prep-bSSFP and HASTE imaging, and comparable measurements for aortic wall and lumen dimensions. 2. Stage 2.

Accuracy of Nodule Volume and Airway Wall Thickness Measurement Using Low-Dose Chest CT on a Photon-Counting Detector CT Scanner.

A comparison of high-resolution photon-counting detector computed tomography (PCD-CT) versus energy-integrating detector (EID) CT via a phantom study using low-dose chest CT to evaluate nodule volume and airway wall thickness quantification. Twelve solid and ground-glass lung nodule phantoms with 3 diameters (5 mm, 8 mm, and 10 mm) and 2 shapes (spherical and star-shaped) and 12 airway tube phantoms (wall thicknesses, 0.27-1.54 mm) were placed in an anthropomorphic chest phantom. The phantom was scanned with EID-CT and PCD-CT at 5 dose levels (CTDI vol = 0.1-0.8 mGy at Sn-100 kV, 7.35 mGy at 120 kV). All images were iteratively reconstructed using matched kernels for EID-CT and medium-sharp kernel (MK) PCD-CT and an ultra-sharp kernel (USK) PCD-CT kernel, and image noise at each dose level was quantified. Nodule volumes were measured using semiautomated segmentation software, and the accuracy was expressed as the percentage error between segmented and reference volumes. Airway wall thicknesses were measured, and the root-mean-square error across all tubes was evaluated. MK PCD-CT images had the lowest noise. At 0.1 mGy, the mean volume accuracy for the solid and ground-glass nodules was improved in USK PCD-CT (3.1% and 3.3% error) compared with MK PCD-CT (9.9% and 10.2% error) and EID-CT images (11.4% and 9.2% error), respectively. At 0.2 mGy and 0.8 mGy, the wall thickness root-mean-square error values were 0.42 mm and 0.41 mm for EID-CT, 0.54 mm and 0.49 mm for MK PCD-CT, and 0.23 mm and 0.16 mm for USK PCD-CT. USK PCD-CT provided more accurate lung nodule volume and airway wall thickness quantification at lower radiation dose compared with MK PCD-CT and EID-CT.

An omnidirectional piezoelectric transducer for selective excitation and reception of high-order shear horizontal waves

Guided wave tomography, as an advanced structural health monitoring (SHM) method, has offered a feasible solution to wall thickness quantification which is essential in petrochemical industries. However, previously used low-frequency Lamb waves (A0 and S0) limit the resolution of tomography. Recently, the first-order shear horizontal guided wave (SH1) was found very promising in tomography for its capability in resolution improvement. However, the SHM-required omnidirectional piezoelectric transducers for selectively generating and receiving the SH1 wave, namely OSH1-PT, are not available yet. In this work, a general method was developed to design an OSH1-PT based on the thickness-poled PZT half-ring configuration. Firstly, the excitation function of the OSH1-PT was explicitly derived and validated through finite element simulations. Secondly, a design formula was obtained and used to determine the size of the OSH1-PT. Then, the designed OSH1-PT was fabricated and tested by using a 2D laser Doppler vibrometer. Significant mode selectivity was observed in all directions (0 ∼ 90°) with the excited SH1 to SH0 ratio higher than 15 dB. Pitch-catch tests were conducted from 400 ∼ 520 kHz and the received SH1 to SH0 ratio was found higher than 19 dB at all frequencies and reached its maxima of 30.7 dB at 490 kHz, which is very close to the designed working frequency of 500 kHz. Finally, an OSH2-PT was theoretically designed and validated by FE simulations. Due to its simplicity and effectiveness in designing the OSHn-PT, the proposed method is expected to pave the road to wide applications of high-order SH wave tomography.

A non-invasive ultrasound imaging method to measure acute radiation-induced bladder wall thickening in rats

BackgroundMethods for the non-invasive quantification of changes in bladder wall thickness as potential predictors of radiation cystitis in pre-clinical research would be desirable. The use of ultrasound for this aim seems promising, but is still relatively unexplored. A method using ultrasound for bladder wall thickness quantification in rats was developed and applied to measure early radiation-induced bladder wall thickness changes.MethodsTwo groups (n = 9 each) of female Fischer rats were treated with a single radiation dose of 25–30 and 35–40 Gy respectively, using an image-guided micro-irradiator; six untreated rats were monitored as a control group. Empty, half-filled and fully-filled bladder volumes were determined for four non-irradiated rats by measuring axes from ultrasound 3D-images and applying the ellipsoid formula. Mean bladder wall thickness was estimated for both ventral and dorsal bladder sides through the measurement of the bladder wall area along a segment of 4 mm in the central sagittal scan, in order to minimize operator-dependence on the measurement position. Ultrasound acquisitions of all fully-filled rat bladders were also acquired immediately before, and 4 and 28 days after irradiation. Mean bladder wall thickness normalized to the baseline value and corrected for filling were then used to evaluate acute bladder wall thickening and to quantify the dose–effect.ResultsThe relationship between mean bladder wall thickness and volume in unirradiated rats showed that for a bladder volume > 1.5 mL the bladder wall thickness is almost constant and equal to 0.30 mm with variations within ± 15%. The average ratios between post and pre irradiation showed a dose–effect relationship. Bladder wall thickening was observed for the 25–30 Gy and 35–40 Gy groups in 2/9 (22%) and 5/9 (56%) cases at day 4 and in 4/9 (44%) and 8/9 (89%) cases at day 28, respectively. The two groups showed significantly different bladder wall thickness both relative to the control group (p < 0.0001) and between them (p = 0.022). The bladder wall thickness increment was on average 1.32 ± 0.41, and was 1.30 ± 0.21 after 25–30 Gy and 1.47 ± 0.29 and 1.90 ± 0.83 after 35–40 Gy at days 4 and 28 respectively.ConclusionsThe feasibility of using ultrasound on a preclinical rat model to detect bladder wall thickness changes after bladder irradiation was demonstrated, and a clear dose–effect relationship was quantified. Although preliminary, these results are promising in addressing the potential role of this non-invasive approach in quantifying radiation cystitis.

Uncertainty quantification of wall thickness of onshore gas transmission pipelines

The present study quantifies probabilistic characteristics of the wall thickness of welded pipe joints in onshore gas transmission pipelines based on about 5900 field-measured wall thicknesses collected from a pipeline system in Canada. The collected data cover a wide range of pipe nominal wall thicknesses, from 3.18 to 16.67 mm. By considering the measurement error involved in the collected wall thickness data, statistical analyses indicate that the actual-over-nominal wall thickness ratio (AONR) follows a normal distribution with a mean of 1.01 and a coefficient of variation (COV) ranging from 1.6% to 2.2% depending on the nominal pipe wall thickness. The implications of the developed AONR statistics for the reliability analysis of corroded pipe joints are investigated. This study provides key input to the reliability-based design and assessment of pipelines with respect to various threats, such as metal-loss corrosion and stress corrosion cracking.

Accuracy and clinical feasibility of 3D-myocardial thickness map measured by cardiac computed tomogram

BackgroundAlthough myocardial thickness is an important variable for therapeutic catheter ablation of cardiac arrhythmias, quantification of wall thickness has been overlooked. We developed a software (AMBER) that measures 3D-myocardial thickness using a cardiac computed tomogram (CT) image, verified its accuracy, and tested its clinical feasibility.MethodsWe generated 3D-thickness maps by calculating wall thickness (WT) from the CT images of 120 patients’ hearts and a 3D-phantom model (PhM). The initial vector field of the Laplace equation was oriented to calculate WT with the field lines derived from the 3D mesh. We demonstrate the robustness of the Laplace WT algorithm by comparing with the real thickness of 3D-PhM, echocardiographically measured left ventricular (LV) WT, and regional left atrial (LA) WT reported from previous studies. We conducted a pilot case of catheter ablation for atrial fibrillation (AF) utilizing real-time LAWT map-guided radiofrequency (RF) energy titration.ResultsAMBER 3D-WT had excellent correlations with the real thickness of the PhM (R = 0.968, p < 0.001) and echocardiographically measured LVWT in 10 patients (R = 0.656, p = 0.007). AMBER 3D-LAWT (n = 120) showed a relatively good match with 12 previously reported regional LAWT. We successfully conducted pilot AF ablation utilizing AMBER 3D-LAWT map-guided real-time RF energy titration.ConclusionWe developed and verified an AMBER 3D-cardiac thickness map measured by cardiac CT images for LAWT and LVWT, and tested its feasibility for RF energy titration during clinical catheter ablation.

Simultaneous 3D whole-heart bright-blood and black blood imaging for cardiovascular anatomy and wall assessment with interleaved T2 prep-IR.

To develop a motion-corrected 3D flow-insensitive imaging approach interleaved T2 prepared-inversion recovery (iT2 prep-IR) for simultaneous lumen and wall visualization of the great thoracic vessels and cardiac structures. A 3D flow-insensitive approach for simultaneous cardiovascular lumen and wall visualization (iT2 prep) has been previously proposed. This approach requires subject-dependent weighted subtraction to completely null the arterial blood signal in the black-blood volume. Here, we propose an (T2 prep-IR) approach to improve wall visualization and remove need for weighted subtraction. The proposed sequence is based on the acquisition and direct subtraction of 2 interleaved 3D whole-heart data sets acquired with and without T2 prep-IR preparation. Image navigators are acquired before data acquisition to enable 2D translational and 3D non-rigid motion correction allowing 100% respiratory scan efficiency. The proposed approach was evaluated in 10 healthy subjects and compared with the conventional 2D double inversion recovery (DIR) sequence and the 3D iT2 prep sequence. Additionally, 5 patients with congenital heart disease were acquired to test the clinical feasibility of the proposed approach. The proposed iT2 prep-IR sequence showed improved blood nulling compared to both DIR and iT2 prep techniques in terms of SNR (SNRblood = 6.9, 12.2, and 18.2, respectively) and contrast-to-noise-ratio (CNRmyoc-blood = 28.4, 15.4, and 15.3, respectively). No statistical difference was observed between iT2 prep-IR, iT2 prep and DIR atrial and ventricular wall thickness quantification. The proposed interleaved T2 prep-IR sequence enables the simultaneous lumen and wall visualization of cardiac structures and shows promising results in terms of SNR, CNR, and wall thickness measurement.

Automated Measurement of Blood Vessels in Tissues from Microscopy Images.

The quantification of tunica media thickness in histological cross sections is a ubiquitous exercise in cardiopulmonary research, yet the methods for quantifying medial wall thickness have never been rigorously examined with modern image analysis tools. As a result, inaccurate and cumbersome manual measurements of discrete wall regions along the vessel periphery have become common practice for wall thickness quantification. The aim of this study is to introduce, validate, and facilitate the use of an improved method for medial wall thickness quantification. We describe a novel method of wall thickness calculation based on image skeletonization and compare its results to those of common techniques. Using both theoretical and empirical approaches, we demonstrate the accuracy and superiority of the skeleton-based method for measuring wall thickness while discussing its interpretation and limitations. Finally, we present a new freely available software tool, the VMI Calculator, to facilitate wall thickness measurements using our novel method. © 2016 by John Wiley & Sons, Inc.

Local Quantification of Wall Thickness and Intraluminal Thrombus Offer Insight into the Mechanical Properties of the Aneurysmal Aorta.

Wall stress is a powerful tool to assist clinical decisions in rupture risk assessment of abdominal aortic aneurysms. Key modeling assumptions that influence wall stress magnitude and distribution are the inclusion or exclusion of the intraluminal thrombus in the model and the assumption of a uniform wall thickness. We employed a combined numerical-experimental approach to test the hypothesis that abdominal aortic aneurysm (AAA) wall tissues with different thickness as well as wall tissues covered by different thrombus thickness, exhibit differences in the mechanical behavior. Ultimate tissue strength was measured from in vitro tensile testing of AAA specimens and material properties of the wall were estimated by fitting the results of the tensile tests to a histo-mechanical constitutive model. Results showed a decrease in tissue strength and collagen stiffness with increasing wall thickness, supporting the hypothesis of wall thickening being mediated by accumulation of non load-bearing components. Additionally, an increase in thrombus deposition resulted in a reduction of elastin content, collagen stiffness and tissue strength. Local wall thickness and thrombus coverage may be used as surrogate measures of local mechanical properties of the tissue, and therefore, are possible candidates to improve the specificity of AAA wall stress and rupture risk evaluations.

Effect of Reducing Field of View on Multidetector Quantitative Computed Tomography Parameters of Airway Wall Thickness in Asthma.

We reduced the computed tomography (CT)-reconstructed field of view (FOV), increasing pixel density across airway structures and reducing partial volume effects, to determine whether this would improve accuracy of airway wall thickness quantification. We performed CT imaging on a lung phantom and 29 participants. Images were reconstructed at 30-, 15-, and 10-cm FOV using a medium-smooth kernel. Cross-sectional airway dimensions were compared at each FOV with repeated-measures analysis of variance. Phantom measurements were more accurate when FOV decreased from 30 to 15 cm (P < 0.05). Decreasing FOV further to 10 cm did not significantly improve accuracy. Human airway measurements similarly decreased by decreasing FOV (P < 0.001). Percent changes in all measurements when reducing FOV from 30 to 15 cm were less than 3%. Airway measurements at 30-cm FOV are near the limits of CT resolution using a medium-smooth kernel. Reducing reconstructed FOV would minimally increase sensitivity to detect differences in airway dimensions.

Cardiac magnetic resonance imaging analysis in STEMI: quantitative or still visual?

Cardiac magnetic resonance imaging (CMR) has long been recognized as an accurate and reliable means of evaluating cardiac anatomy and ventricular function. Considerable progress has been made in the field of CMR, providing accurate evaluation of left ventricular function parameters in coronary artery disease, heart failure, hypertrophic cardiomyopathy, and many other cardiac diseases [1–12]. Stress first-pass contrast-enhanced myocardial perfusion CMR can be used to detect subendocardial ischemia and recent studies have demonstrated the high diagnostic accuracy of stress myocardial perfusion CMR for detecting significant coronary artery disease [13–16]. Magnetic resonance angiography has been introduced as a method that can provide visualization of all three major coronary arteries, coronary anomalies, coronary bypasses and the aorta within a single three-dimensional acquisition [17–19]. CMR has become the first choice imaging modality in complex congenital heart disease [20–26], imaging great vessels, and evaluation of therapy such as cardiac resynchronization therapy [27–38]. Over the past years, contrast-enhanced CMR has been used to visualize the transmural extent of myocardial infarction with high spatial resolution [39–45]. Infarcted myocardium appears hyperenhanced compared with normal myocardium when imaged by a late enhancement MRI technique with the use of T1-weighted sequence after injection of gadolinium chelates. Late gadolinium-enhanced CMR can clearly delineate subendocardial infarction and the transmural extent of delayed enhancement potentially predicts functional outcome after revascularization in acute myocardial infarction and chronic ischemic heart disease [46–49]. In the current issue of the International Journal of Cardiovascular Imaging, Husser et al. [50] compared quantitative assessment of contrast CMR with visual analysis in patients with ST-segment elevation myocardial infarction (STEMI) for predicting reduced ejection fraction and major adverse cardiac events such as death, re-infarction, and re-admission for heart failure. The authors studied 192 patients who underwent CMR at 1 week and 6 months after a sustained STEMI. Three quantitative indices (initial slope, maximal signal intensity and contrast delay in first-pass imaging) and two visual perfusion indices (hypo-enhancement in first-pass and microvascular obstruction in late enhancement imaging) were evaluated. Quantification of infarct mass and visual assessment of the extent of transmural necrosis was also performed on the basis of the standard 17-segment model. At 6 months, 69 patients showed reduced ejection fraction; during follow-up of mean 655 days, 20 major adverse cardiac events occurred. Quantification of the perfusion images was very time-consuming and proved not superior to visual perfusion analysis to predict reduced ejection fraction and/or major adverse cardiac events. Similarly, quantification of infarct size was not superior to visual assessment of the extent of transmural necrosis. In multivariate analysis, only visual assessment of extent of transmural necrosis predicted reduced ejection fraction and major adverse cardiac events. The authors concluded that visual analysis of CMR in patients with STEMI is not time-consuming and predicts reduced ejection fraction and major adverse cardiac events comparable to quantitative analysis. The extent of transmural necrosis turned out to be the strongest parameter. The present study is the first to investigate whether a complete quantitative analysis of a post-infarct-CMR study would be more accurate than a complete visual analysis of microvascular perfusion and myocardial necrosis to predict late ejection fraction and major adverse cardiac events in a large group of patients with STEMI. The data confirm previous findings from the same group showing that neither qualitative nor quantitative myocardial perfusion nor time-consuming quantification of infarct mass provides incremental predictive value over visual assessment of transmural necrosis [51–53]. Despite these interesting findings, it should be realized that quantification of perfusion and infarct size offers the potential advantages of being less operator-dependent, more objective, and more accurate. At present, CMR offers several acquisition techniques for precise and highly reproducible assessment of global and regional ventricular function, flow, and perfusion at rest and under pharmacological or physical stress conditions [54–56]. Moreover, CMR allows quantification of blood flow over the valves, and automatic vessel wall contour detection and quantification of wall thickness of in-vivo MR images of the human aorta [57–59]. Recent advances in hardware and software have resulted in strong improvement of image quality and in a significant decrease in the required imaging time for each of these acquisitions. However, quantitative image analysis often still relies on manual tracing of contours in the images, being indeed time-consuming thereby limiting the clinical applicability of CMR for routine analysis. Methods for automated and robust assessment of the parameters of cardiac function, blood flow and morphology, are still being developed to overcome the limitations associated with manual image processing [60]. Until these issues are fully solved, the present study clearly indicates that, for prediction of late cardiac events in patients with STEMI, a comprehensive visual approach may suffice in routine clinical practice.

Semiautomatic vessel wall detection and quantification of wall thickness in computed tomography images of human abdominal aortic aneurysms

Quantitative measurements of wall thickness in human abdominal aortic aneurysms (AAAs) may lead to more accurate methods for the evaluation of their biomechanical environment. The authors describe an algorithm for estimating wall thickness in AAAs based on intensity histograms and neural networks involving segmentation of contrast enhanced abdominal computed tomography images. The algorithm was applied to ten ruptured and ten unruptured AAA image data sets. Two vascular surgeons manually segmented the lumen, inner wall, and outer wall of each data set and a reference standard was defined as the average of their segmentations. Reproducibility was determined by comparing the reference standard to lumen contours generated automatically by the algorithm and a commercially available software package. Repeatability was assessed by comparing the lumen, outer wall, and inner wall contours, as well as wall thickness, made by the two surgeons using the algorithm. There was high correspondence between automatic and manual measurements for the lumen area (r = 0.978 and r = 0.996 for ruptured and unruptured aneurysms, respectively) and between vascular surgeons (r = 0.987 and r = 0.992 for ruptured and unruptured aneurysms, respectively). The authors' automatic algorithm showed better results when compared to the reference with an average lumen error of 3.69%, which is less than half the error between the commercially available application Simpleware and the reference (7.53%). Wall thickness measurements also showed good agreement between vascular surgeons with average coefficients of variation of 10.59% (ruptured aneurysms) and 13.02% (unruptured aneurysms). Ruptured aneurysms exhibit significantly thicker walls (1.78 +/- 0.39 mm) than unruptured ones (1.48 +/- 0.22 mm), p = 0.044. While further refinement is needed to fully automate the outer wall segmentation algorithm, these preliminary results demonstrate the method's adequate reproducibility and low interobserver variability.

Automatic vessel wall contour detection and quantification of wall thickness in in‐vivo MR images of the human aorta

To develop an automated technique to trace the contours of the lumen and outer boundary of the aortic wall, and measure aortic wall thickness in axial MR images. The algorithm uses prior knowledge of vessel wall morphology. A geometrical model (ellipse) is deformed, translated and rotated to obtain a rough approximation of the contours. Model-matching is based on image gradient measurements. To enhance edges, the images were preprocessed using gray-level stretching. Refinement is performed by means of dynamic programming. Wall thickness is computed by measuring the distance between inner and outer contour of the aortic wall. The algorithm has been tested on high-resolution axial MR images from 28 human subjects of the descending thoracic aorta. The results demonstrate: High correspondence between automatic and manual area measurements: lumen (r = 0.99), outer (r = 0.96), and wall thickness (r = 0.85). Though further optimization is required, our algorithm is a powerful tool to automatically draw the boundaries of the aortic wall and measure aortic wall thickness in aortic wall devoid of major lesions. J. Magn. Reson. Imaging 2006. (c) 2006 Wiley-Liss, Inc.

Three-dimensional echocardiographic measurement of left ventricular wall thickness: In vitro and in vivo validation

Introduction: Three-dimensional (3D) echocardiography has been shown to accurately measure left ventricular (LV) volume and mass. This study evaluated the accuracy of 3D echocardiography and the CenterSurface method for measuring LV wall thickness in vitro and in vivo. Method: Three-dimensional echocardiography scans, obtained from 7 LV phantoms and subjects having healthy (n = 5) or diseased (n = 8) hearts, were digitized. Endocardial and epicardial borders were outlined and used in 3D LV reconstruction. In vitro wall thickness was compared with true micrometer measurements. Three-dimensional in vivo wall thickness was compared with 2-dimensional (2D) thickness measured by the centerline method. Results: The in vitro 3D echocardiography measurements agreed closely with true wall thickness (P <.0001), as did in vivo measurements (P <.0001). Conclusion: Three-dimensional echocardiography reconstruction has previously been shown to provide accurate representation of LV shape in addition to volume and mass. This study demonstrates that the CenterSurface method provides accurate quantification of wall thickness. (J Am Soc Echocardiogr 2002;15:129-35.)

Regression of Left Ventricular Hypertrophy Under Ramipril Treatment Investigated by Nuclear Magnetic Resonance Imaging

Thirty-two hypertensive subjects with diastolic blood pressure greater than 95 mm Hg were treated with ramipril over a period of 3 months. To determine the effective decrease of blood pressure and for reliable and reproducible demonstration of regression of myocardial hypertrophy during ramipril treatment, we performed parallel measurements with magnetic resonance imaging (MRI) and echocardiography. Measurements were carried out before treatment, 4 h after the first dose, and after 14 days and 3 months of treatment. MRI slices showed a significant decrease of interventricular septal thickness from 19.57 to 15.20 mm, whereas echocardiography demonstrated an equivalent decrease from 18.78 to 14.57 mm. At each measuring point, quantification of wall thickness was performed three times and the means were calculated. The septum and the posterior wall of the left ventricle were also measured at three different points. The values were obtained with negligible scatter and the changes with ramipril treatment were highly significant (p less than 0.001). A concomitant decrease of blood pressure was also observed. The therapeutic aim to reduce diastolic blood pressures below 90 mm Hg was achieved in all patients. In addition to the significant reduction in blood pressure, the angiotensin converting enzyme (ACE) inhibitor ramipril caused a significant regression of pathologic left ventricular hypertrophy demonstrated by magnetic resonance imaging and echocardiography.