Multidetector Computed Tomography Data Sets Research Articles

Three-Dimensional Segmentation of Equine Paranasal Sinuses in Multidetector Computed Tomography Datasets: Preliminary Morphometric Assessment Assisted with Clustering Analysis.

The paranasal sinuses, a bilaterally symmetrical system of eight air-filled cavities, represent one of the most complex parts of the equine body. This study aimed to extract morphometric measures from computed tomography (CT) images of the equine head and to implement a clustering analysis for the computer-aided identification of age-related variations. Heads of 18 cadaver horses, aged 2-25 years, were CT-imaged and segmented to extract their volume, surface area, and relative density from the frontal sinus (FS), dorsal conchal sinus (DCS), ventral conchal sinus (VCS), rostral maxillary sinus (RMS), caudal maxillary sinus (CMS), sphenoid sinus (SS), palatine sinus (PS), and middle conchal sinus (MCS). Data were grouped into young, middle-aged, and old horse groups and clustered using the K-means clustering algorithm. Morphometric measurements varied according to the sinus position and age of the horses but not the body side. The volume and surface area of the VCS, RMS, and CMS increased with the age of the horses. With accuracy values of 0.72 for RMS, 0.67 for CMS, and 0.31 for VCS, the possibility of the age-related clustering of CT-based 3D images of equine paranasal sinuses was confirmed for RMS and CMS but disproved for VCS.

Three-Dimensional Segmentation Assisted with Clustering Analysis for Surface and Volume Measurements of Equine Incisor in Multidetector Computed Tomography Data Sets.

Dental diagnostic imaging has progressed towards the use of advanced technologies such as 3D image processing. Since multidetector computed tomography (CT) is widely available in equine clinics, CT-based anatomical 3D models, segmentations, and measurements have become clinically applicable. This study aimed to use a 3D segmentation of CT images and volumetric measurements to investigate differences in the surface area and volume of equine incisors. The 3D Slicer was used to segment single incisors of 50 horses' heads and to extract volumetric features. Axial vertical symmetry, but not horizontal, of the incisors was evidenced. The surface area and volume differed significantly between temporary and permanent incisors, allowing for easy eruption-related clustering of the CT-based 3D images with an accuracy of >0.75. The volumetric features differed partially between center, intermediate, and corner incisors, allowing for moderate location-related clustering with an accuracy of >0.69. The volumetric features of mandibular incisors' equine odontoclastic tooth resorption and hypercementosis (EOTRH) degrees were more than those for maxillary incisors; thus, the accuracy of EOTRH degree-related clustering was >0.72 for the mandibula and >0.33 for the maxilla. The CT-based 3D images of equine incisors can be successfully segmented using the routinely achieved multidetector CT data sets and the proposed data-processing approaches.

Quantitative Assessment of the Pharyngeal Recess Morphometry in Anatolian Population Using 3D Models Generated from Multidetector Computed Tomography Images

Aim: It was aimed to analyze the detailed morphometry of the pharyngeal recess (PR) using three-dimensional (3D) models reconstructed from multidetector computed tomography (MDCT) images.
 Material and Methods: This study was a retrospective analysis and performed on MDCT images of 97 patients (43 males, 54 females). 3D models of the PR were reconstructed using 3D Slicer software, enabling morphometric measurements according to established protocols. Measurements included PR depths, distances between the posterior nasal spine and torus levatorius (PNS-TL), distances between right and left TL (RTL-LTL) distances between the PNS and posterior wall of the nasopharynx (PNS-PWN), the angle (α) between the centerline of the PR and the sagittal plane. The morphologies of the PR classified into three types.
 Results: The average measurements for the parameters were as follows: PR depth - 10.42 mm, distance between PNS and TL - 10.40 mm, distance between RTL and LTL - 19.13 mm, distance between PNS and PWN - 19.92 mm, and the angle (α) - 53.65°. The prevalence of PR types was 20.62%, 47.42% and 31.96% for type 1, type 2 and type 3, respectively.
 Conclusion: Variations in reported measurements of the pharyngeal recess can be attributed to imaging techniques, patient positioning, anatomical differences, and sample sizes. The use of 3D models generated from MDCT datasets offers a high-resolution and comprehensive approach to understanding the PR's morphometry and spatial relationships, enabling accurate measurements and advancing our knowledge of this anatomical region.

Comparison of different software solutions for AVC quantification using contrast enhanced MDCT

Abstract Funding Acknowledgements Type of funding sources: None. Aims Estimating aortic valve calcification (AVC) derived from multi detector computed tomography (MDCT) scans in aortic stenosis (AS) patients has gained increasing interest for diagnostic and prognostic reasons. Little is known about the interchangeability of AVC obtained from different software solutions which, was systematically determined in consecutive patients undergoing contrast enhanced MDCT before TAVR. Methods and results 50 randomly selected patients who underwent contrast enhanced MDCT for TAVR planning were included in the analysis. All MDCT data sets were analysed using three different software vendors (3 Mensio, CVI 42, Snygo.Via). AVC score was expressed as mm³. For analysing intra- and inter-observer variability a subset of 10 patients were analysed twice with at least 2 weeks in between the measurements. Intra- and inter-observer variability was quantified using the ICC reliability method, Bland-Altman analysis and coefficients of variation. AVC scores were successfully obtained using all software solutions (3 Mensio 941 ± 623, CVI42 941 ± 637, Syngo.Via 948 mm³ ± 655) without significant differences (p = 0.455). There was excellent intra- (3 Mensio: ICC 0.999 [0.995 – 1.000], COV 3.86 %, mean difference -19.28 [± 45.07]; CVI 42: ICC 1.000 [0.999 – 1.000], COV 1.6 %, mean difference -10.28 [± 18.6]; Syngo.Via: ICC 0.998 [0.993 – 1.000], COV 4.13 %, mean difference -24.81 [± 48.52]) and inter-observer variability (3 Mensio: ICC 1.000 [0.999 – 1.000], COV 1.38 %, mean difference -7.14 [± 16.20]; CVI 42: ICC 1.000 [1.000 – 1.000], COV 1.01 %, mean difference -1.74 [± 11.83]; Syngo.Via: ICC 0.996 [0.985 – 0.999], COV 6.68 %, mean difference -0.65 [± 79.43]) for all software types. Best inter-vendor agreement was found between CVI 42 and Syngo.Via (ICC 0.997 [CI 0.995-0.998], COV 7.26 %, mean difference -7 [± 68.60]) followed by 3 Mensio / CVI 42 (ICC 0,996 [CI 0,922-0,998], COV 8.95 %, mean difference -0.06 [± 84.16]) and 3 Mensio / Syngo.Via (ICC 0,992 [CI 0,986-0,995], COV 12.19%, mean difference -7.06 [± 115.07]). Conclusion Contrast enhanced MDCT derived AVC scores are interchangeable between and reproducible within different commercially available software solutions. This is important since sufficient reproducibility, inter-changeability and valid results represent prerequisites for accurate TAVR planning and wide spread clinical use.

Automated detection of the contrast phase in MDCT by an artificial neural network improves the accuracy of opportunistic bone mineral density measurements

ObjectivesTo determine the accuracy of an artificial neural network (ANN) for fully automated detection of the presence and phase of iodinated contrast agent in routine abdominal multidetector computed tomography (MDCT) scans and evaluate the effect of contrast correction for osteoporosis screening.MethodsThis HIPPA-compliant study retrospectively included 579 MDCT scans in 193 patients (62.4 ± 14.6 years, 48 women). Three different ANN models (2D DenseNet with random slice selection, 2D DenseNet with anatomy-guided slice selection, 3D DenseNet) were trained in 462 MDCT scans of 154 patients (threefold cross-validation), who underwent triphasic CT. All ANN models were tested in 117 unseen triphasic scans of 39 patients, as well as in a public MDCT dataset containing 311 patients. In the triphasic test scans, trabecular volumetric bone mineral density (BMD) was calculated using a fully automated pipeline. Root-mean-square errors (RMSE) of BMD measurements with and without correction for contrast application were calculated in comparison to nonenhanced (NE) scans.ResultsThe 2D DenseNet with anatomy-guided slice selection outperformed the competing models and achieved an F1 score of 0.98 and an accuracy of 98.3% in the test set (public dataset: F1 score 0.93; accuracy 94.2%). Application of contrast agent resulted in significant BMD biases (all p < .001; portal-venous (PV): RMSE 18.7 mg/ml, mean difference 17.5 mg/ml; arterial (AR): RMSE 6.92 mg/ml, mean difference 5.68 mg/ml). After the fully automated correction, this bias was no longer significant (p > .05; PV: RMSE 9.45 mg/ml, mean difference 1.28 mg/ml; AR: RMSE 3.98 mg/ml, mean difference 0.94 mg/ml).ConclusionAutomatic detection of the contrast phase in multicenter CT data was achieved with high accuracy, minimizing the contrast-induced error in BMD measurements.Key Points• A 2D DenseNet with anatomy-guided slice selection achieved an F1 score of 0.98 and an accuracy of 98.3% in the test set. In a public dataset, an F1 score of 0.93 and an accuracy of 94.2% were obtained.• Automated adjustment for contrast injection improved the accuracy of lumbar bone mineral density measurements (RMSE 18.7 mg/ml vs. 9.45 mg/ml respectively, in the portal-venous phase).• An artificial neural network can reliably reveal the presence and phase of iodinated contrast agent in multidetector CT scans (https://github.com/ferchonavarro/anatomy_guided_contrast_c). This allows minimizing the contrast-induced error in opportunistic bone mineral density measurements.

Head-to-Head Comparison of Different Software Solutions for AVC Quantification Using Contrast-Enhanced MDCT.

Aortic valve calcification (AVC) in aortic stenosis patients has diagnostic and prognostic implications. Little is known about the interchangeability of AVC obtained from different multidetector computed tomography (MDCT) software solutions. Contrast-enhanced MDCT data sets of 50 randomly selected aortic stenosis patients were analysed using three different software vendors (3Mensio, CVI42, Syngo.Via). A subset of 10 patients were analysed twice for the estimation of intra-observer variability. Intra- and inter-observer variability were determined using the ICC reliability method, Bland-Altman analysis and coefficients of variation. No differences were revealed between the software solutions in the AVC calculations (3Mensio 941 ± 623, Syngo.Via 948 mm3 ± 655, CVI42 941 ± 637; p = 0.455). The best inter-vendor agreement was found between the CVI42 and the Syngo.Via (ICC 0.997 (CI 0.995–0.998)), followed by the 3Mensio and the CVI42 (ICC 0.996 (CI 0.922–0.998)), and the 3Mensio and the Syngo.Via (ICC 0.992 (CI 0.986–0.995)). There was excellent intra- (3Mensio: ICC 0.999 (0.995–1.000); CVI42: ICC 1.000 (0.999–1.000); Syngo.Via: ICC 0.998 (0.993–1.000)) and inter-observer variability (3Mensio: ICC 1.000 (0.999–1.000); CVI42: ICC 1.000 (1.000–1.000); Syngo.Via: ICC 0.996 (0.985–0.999)) for all software types. Contrast-enhanced MDCT-derived AVC scores are interchangeable between and reproducible within different commercially available software solutions. This is important since sufficient reproducibility, interchangeability and valid results represent prerequisites for accurate TAVR planning and its widespread clinical use.

Spontaneous Renal Artery Dissection as a Cause of Acute Renal Infarction: Clinical and MDCT Findings.

The purpose of this study was to assess the incidence of spontaneous renal artery dissection (SRAD) as a cause of acute renal infarction, and to evaluate the clinical and multidetector computed tomography (MDCT) findings of SRAD. From November 2011 to January 2014, 35 patients who were diagnosed with acute renal infarction by MDCT were included. We analyzed the 35 MDCT data sets and medical records retrospectively, and compared clinical and imaging features of SRAD with an embolism, using Fisher's exact test and the Mann-Whitney test. The most common cause of acute renal infarction was an embolism, and SRAD was the second most common cause. SRAD patients had new-onset hypertension more frequently than embolic patients. Embolic patients were found to have increased C-reactive protein (CRP) more often than SRAD patients. Laboratory results, including tests for lactate dehydrogenase (LDH) and blood urea nitrogen (BUN), and the BUN/creatinine ratio (BCR) were significantly higher in embolic patients than SRAD patients. Bilateral renal involvement was detected in embolic patients more often than in SRAD patients. MDCT images of SRAD patients showed the stenosis of the true lumen, due to compression by a thrombosed false lumen. None of SRAD patients progressed to an estimated glomerular filtration rate < 60 mL/min/1.73 m2 or to end-stage renal disease during the follow-up period. SRAD is not a rare cause of acute renal infarction, and it has a benign clinical course. It should be considered in a differential diagnosis of acute renal infarction, particularly in patients with new-onset hypertension, unilateral renal involvement, and normal ranges of CRP, LDH, BUN, and BCR.

Abstract 12227: New Insights Into Calcification and Aortic Stenosis Using 4-dimensional Computed Tomography.

Background: Aortic Valve Calcification (AVC) is intrinsic to aortic stenosis (AS). While established concepts assume homogeneous calcification causing AS, wide variability in hemodynamic severity at any given AVC burden suggests other operative mechanisms. Multidetector computed tomography (MDCT) now accurately measures global AVC, but AVC spatial distribution remains elusive due to imaging orientation. Methods and Results: We developed ‘en-face’ imaging by re-registration of 4D-MDCT to quantify AVC spatial distribution and analyzed global AVC load and AVC distribution in 418 patients with AS (76±9 years; mean gradient 35±17 mmHg). 4D-volume-rendered MDCT datasets were re-oriented to en-face view of aortic valve for AVC spatial scoring with individual cusp calcification load, cusp-edge calcification and AVC asymmetry. Despite high total AVC load (450 [250-666] AU/cm 2 ), asymmetry was frequent (50%), with a difference between most- and least-calcified cusp of 112 [66-182] AU/cm 2 . Maximum AVC was in the non-coronary cusp in 61% (p&lt;0.001). Cusp edge calcification was none-mild in 26%, moderate in 62% and severe in 12%. Adjusting for total AVC, severe AS (mean gradient &gt;40 mmHg) was more likely with symmetrical AVC (odds ratio [OR] 2.36, p&lt;0.001) and with edge calcification moderate (OR 4.16, p=0.001 vs none-mild) to severe (OR 10.7, p=0.001). Inclusion of AVC distribution improved models predicting AS severity over total AVC (p&lt;0.001). Conclusions: Four-dimensional MDCT en-face re-registration and AVC quantitation provides new insight into AS pathophysiology. Contrary to classical concepts, AVC is frequently inhomogeneous and asymmetric. Hemodynamic AS severity is independently affected not only by global AVC but also by variations in AVC distribution and location within cusps, emphasizing the importance of 4D AVC assessment in AS. Impact of quantified AVC asymmetry and location on outcome of transcutaneous aortic valve replacement should be evaluated.

Automatic 3D modelling of human diaphragm from lung MDCT images.

The thoracic diaphragm separates the thorax and abdomen cavity and also performs an important function in respiration. An automatic algorithm to model the human full diaphragm from multi-detector computed tomography (MDCT) images has been developed and tested. The modelling algorithm comprises these steps: (i) diaphragm top boundary estimation (ii) diaphragm side boundary estimation and (iii) full diaphragm modelling in 3D. Diaphragm top boundary is estimated based on lungs' diaphragmatic surfaces with three different methods including: linear interpolation and fitting fourth and fifth degree polynomial surfaces. Diaphragm side boundary is assumed as the inner surfaces of the lower ribs, spinal column and costal cartilages, estimated via interpolation. As the last step, the full diaphragm is modelled by employing 3D active contours that are initiated from a predefined mesh and expand towards the estimated boundaries of the diaphragm. The proposed algorithm was tested on MDCT datasets from 15 patients, and the result were compared to reference masks provided by an experienced radiologist. Based on quantitative evaluations, the accuracy of the algorithm highly depends on the diaphragm top surface estimation, e.g., the proposed algorithm failed on two datasets, both with enlarged pericardial fat pad that cuts off the left lung from the diaphragm. The proposed algorithm was tested on the remaining 13 datasets in which lungs' lower surfaces have normal contact with the diaphragm. To perform quantitative evaluations, four slices per dataset including an axial, mid-coronal and one-fourth of the sagittal planes from left and right, were compared to the ground truth. Hausdorff distance and mean distance to the closest point were measured to be 11.61 and 3.46mm respectively, when the diaphragm top surface is modelled by a fourth degree polynomial surface. Human full diaphragm can be automatically modelled with 3D active contours bounded by the lower surfaces of the lungs and inner surfaces of the lower ribs, spinal column and costal cartilages.

Automatic patient-customised 3D reconstruction of human costal cartilage from lung MDCT dataset.

The costal cartilage is a prominent feature of the anterior chest wall that is subject to developmental and acquired abnormalities. A fully automatic algorithm to reconstruct the human costal cartilage from multidetector computed tomography (MDCT) images was developed and tested. The reconstruction algorithm includes three steps: (1) estimation of length, curvature and end points for each costal cartilage centre-line, (2) costal cartilage cross-section area approximation, and (3) transformation of the estimated cross-section to the centre-line into a cylindrical coordinate system. Four different models were as follows: circle, vertical ellipse, horizontal ellipse and a non-geometric shape have been assumed for the cross-section. Shape estimates were based on each patient's dataset, so the algorithm is patient-specific and anatomically faithful. MDCT datasets from 15 patients were evaluated with the automated algorithm and the results compared with reference masks provided by an experienced radiologist. The costal cartilage reconstruction result and the reference mask were visually consistent. Based on evaluation results, the circular model cross-section with area of twice M (mean area of all rib cross-sections in the mid-coronal plane) had the highest Dice similarity coefficient (DSC = 77.5%) with only 2.12 mm registration distance. Costal cartilage 3D morphology can be extracted from MDCT scans with an automated method, using a circular cross-section with area equal to twice M.

The subpubic angle in sex determination: Anthropometric measurements and analyses on Anatolian Caucasians using multidetector computed tomography datasets

Introduction and aimThe investigation of new anatomical criteria and revalidation of existing ones in sex determination for different populations are among main research foci of forensic anthropometry. In that context, the pelvis is the most extensively studied bone. A number of qualitative classifications, dimensional measurements and indices have been proposed for investigative anthropometry and forensic studies. Independent use of these parameters generally provided an accuracy rate of 70–75%. In this study, the accuracy rate of the subpubic angle in sex determination was investigated in living Anatolian Caucasians. Material and methodThe subpubic angle was identified and measured on three-dimensional computed tomographic images of pelves. Data were obtained using 64-detector computed tomography (MDCT) with an isotrophic resolution of 500 μm. The sample included 66 males (41.6 ± 14.9 years of age) and 43 females (41.1 ± 14.2 years of age). Measurements were taken on a dedicated three-dimensional image analysis workstation. The subpubic angle was electronically measured. The technique and methodology was validated on a standard skeletal model. Intraobserver agreement was analyzed with intraclass correlation coefficient, and intraobserver variability was evaluated with technical error of measurement (inter- and intra-observer TEM), relative technical error of measurement (rTEM) and coefficient of reliability (R) measures. The subpubic angle for the study group and for both sexes was reported as minimum–maximum (mean ± SD). Independent-Samples T Test for equality of means was used to determine the difference between the two sexes regarding the subpubic angle. The correlation between the subpubic angle and the age of subjects were using Pearson Correlation Coefficients in males and in females. Logistic regression model was used to classify subjects according to their sex. Receiver operating characteristic curve analysis was performed to determine a cut-off value for further studies and to test the performance of the binary classification test. ResultsIntraclass correlation for the subpubic angle (0.990), TEM (1082), rTEM (1.492), and R (0.990) represented almost complete reliability and accuracy of the measurement method. The subpubic angle was between 48° and 81° (65.9° ± 7.2°) in males and was between 64° and 100° (82.6° ± 7.7°) in females. Statistically significant difference was found between males and females regarding the subpubic angle (p < 0.0001). The subpubic angle was not significantly correlated with age in males (p = 0.953), or in females (r = 0.975). The accuracy of the subpubic angle in sex determination was 90.8%. With a cut-off value of 74°, sensitivity of subpubic angle to detect female phenotype was 88% and its specificity was 95%. ConclusionThe subpubic angle is an accurate parameter in sex determination with high sensitivity and specificity.

Visualization of Thrombotic Deposits in Extracorporeal Membrane Oxygenation Devices Using Multidetector Computed Tomography

Despite heparin coating and systemic anticoagulation, thrombotic clot formation is a serious complication in extracorporeal membrane oxygenation (ECMO). We describe our first results of visualization of thrombotic deposits in ECMO devices using advanced multidetector computed tomography (MDCT). A bioline-coated polymethylpentene membrane oxygenator (MO) after 8 days of ECMO treatment (device 1) and a factory-sealed MO serving as an internal quality control (device 2) were analyzed with three-dimensional (3D) visualization volume rendering technique (VRT) using a 0.6 mm3 voxel isotropic MDCT dataset. After the computed tomography (CT) scan, device 1 was anatomically dissected for direct visualization of potential deposits and further analyzed by scanning electron microscopy (SEM). The VRT 3D model based on the MDCT dataset of device 1 showed red-coded areas within the gas exchange surface of the device consistent with fibrous and cellular deposits. These deposits could be confirmed by anatomical dissection of the device and by SEM. Device 2 showed no signs of clot formation in MDCT using the same VRT settings. It was demonstrated that MDCT with VRT is able to detect thrombotic deposits in ECMO devices under ex vivo conditions. MDCT allows direct visualization of the actual thrombus load of a used ECMO device as well as the quantification of the thrombus volume and could, therefore, play a significant role in better understanding the oxygenator thrombosis in modern ECMO treatment.

Computer-aided detection of lung nodules on multidetector CT in concurrent-reader and second-reader modes: A comparative study

PurposeTo compare the reading times and detection performances of radiologists in concurrent-reader and second-reader modes of computer-aided detection (CAD) for lung nodules on multidetector computed tomography (CT). Materials and MethodsFifty clinical multidetector CT datasets containing nodules up to 20mm in diameter were retrospectively collected. For the detection and rating of non-calcified nodules larger than 4mm in diameter, 6 radiologists (3 experienced radiologists and 3 resident radiologists) independently interpreted these datasets twice, once with concurrent-reader CAD and once with second-reader CAD. The reference standard of nodules in the datasets was determined by the consensus of two experienced chest radiologists. The reading times and detection performances in the two modes of CAD were statistically compared, where jackknife free-response receiver operating characteristic (JAFROC) analysis was used for the comparison of detection performances. ResultsTwo hundreds and seven nodules constituted the reference standard. Reading time was significantly shorter in the concurrent-reader mode than in the second-reader mode, with the mean reading time for the 6 radiologists being 132s with concurrent-reader CAD and 210s with second-reader CAD (p<0.01). JAFROC analysis revealed no significant difference between the detection performances in the two modes, with the average figure-of-merit value for the 6 radiologists being 0.70 with concurrent-reader CAD and 0.72 with second-reader CAD (p=0.35). ConclusionIn CAD for lung nodules on multidetector CT, the concurrent-reader mode is more time-efficient than the second-reader mode, and there can be no significant difference between the two modes in terms of detection performance of radiologists.

A systematic approach towards the objective evaluation of low-contrast performance in MDCT: Combination of a full-reference image fidelity metric and a software phantom

ObjectivesTo assess the feasibility of an objective approach for the evaluation of low-contrast detectability in multidetector computed-tomography (MDCT) by combining a virtual phantom containing simulated lesions with an image quality metric. Materials and methodsA low-contrast phantom containing hypodense spheric lesions (−20HU) was scanned on a 64-slice MDCT scanner at 4 different dose levels (25, 50, 100, 200mAs). In addition, virtual round hypodense low-contrast lesions (20HU object contrast) based on real CT data were inserted into the lesion-free section of the datasets. The sliding-thin-slab algorithm was applied to the image data with an increasing slice-thickness from 1 to 15 slices. For each dataset containing simulated lesions a lesion-free counterpart was reconstructed and post-processed in the same manner. The low-contrast performance of all datasets containing virtual lesions was determined using a full-reference image quality metric (modified multiscale structural similarity index, MS-SSIM*). The results were validated against a reader-study of the real lesions. ResultsFor all dose levels and lesion sizes there was no statistically significant difference between the low-contrast performance as determined by the image quality metric when compared to the reader study (p<0.05). The intraclass correlation coefficient was 0.72, 0.82, 0.90 and 0.84 for lesion diameters of 4mm, 5mm, 8mm and 10mm, respectively. The use of the sliding-thin-slab algorithm improves lesion detectability by a factor ranging from 1.15 to 2.69 when compared with the original axial slice (0.625mm). ConclusionThe combination of a virtual phantom and a full-reference image quality metric enables a systematic, automated and objective evaluation of low-contrast detectability in MDCT datasets and correlates well with the judgment of human readers.

Assessment of atherosclerotic plaques at coronary bifurcations with multidetector computed tomography angiography and intravascular ultrasound-virtual histology

We evaluated the distribution and composition of atherosclerotic plaques at bifurcations with intravascular ultrasound-virtual histology (IVUS-VH) and multidetector computed tomography (MDCT) in relation to the bifurcation angle (BA). In 33 patients (age 63±11 years, 79% male) imaged with IVUS-VH and MDCT, 33 bifurcations were matched and studied. The analysed main vessel was divided into a 5 mm proximal segment, the in-bifurcation segment, and a 5 mm distal segment. Plaque contours were manually traced on MDCT and IVUS-VH. Plaques with >10% confluent necrotic core and <10% dense calcium on IVUS-VH were considered high risk, whereas plaque composition by MDCT was graded as non-calcified, calcified, or mixed. The maximum BA between the main vessel and the side branch was measured on diastolic MDCT data sets. Overall the mean plaque area decreased from the proximal to the distal segment [8.5±2.8 vs. 6.0±3.0 mm2 (P<0.001) by IVUS-VH and 9.0±2.6 vs. 6.5±2.5 mm2 (P<0.001) by MDCT]. Similarly, the necrotic core area was higher in the proximal compared with the distal segment (1.12±0.7 vs. 0.71±0.7 mm2, P=0.001). The proximal segment had the higher percentage of high-risk plaques (13/25, 52%), followed by the in-bifurcation (6/25, 24%), and the distal segment (6/25, 24%); these plaques were characterized by MDCT as non-calcified (72%) or mixed (28%). The presence of high-risk and non-calcified plaques in the proximal segment was associated with higher BA values (71±19° vs. 55±19°, P=0.028 and 74±20° vs. 50±14°, P=0.001, respectively). The proximal segment of bifurcations is more likely to contain high-risk plaques, especially when the branching angle is wide.

Segmentation procedure for the generation of a 3D model and solid replica of a human skull

The present study describes a strategy to produce patient-specific skull base replica with realistic shapes, starting from radiological images. Several papers aim to highlight the clinical value of patient-specific three-dimensional (3D) models, obtained segmenting multidetector computed tomography (MDCT) images, for preoperative planning in general surgery, for physician training and for didactics targets. In this study, segmentation and 3D model generation were performed using a semiautomatic tool developed in the EndoCAS centre. The segmentation procedure is based on the neighbourhood connected region-growing algorithm that, appropriately parameterized for the anatomy of interest and combined with the optimal segmentation sequence, generates good-quality 3D images coupled with facility of use. Using a touch screen monitor, manual refining has been added to segment structures unsuitable for automatic reconstruction. The goal of the present work consists in providing and visualizing quantitative geometrical and topological information on the anatomy of a cranium, starting from a MDCT dataset, and to develop a detailed solid replica that allow to improve the comprehension of anatomy and the dimensions of deep structures of a skull base. Anatomical structures of little size - e.g. foramen rotundum, foramen spinosum, lamina cribriformis, hypoglossal canal - were replicated in detail. Furthermore our 3D virtual model permits to well distinguish pneumatized bones; in particular nasal cavities and paranasal sinuses were minutely computer-generated. We consider that our methodological approach to reproduce virtual and solid anatomical models can represent an useful didactic tool, both for undergraduate and postgraduate students.

Detection and quantification of coronary atherosclerotic plaque by 64-slice multidetector CT: A systematic head-to-head comparison with intravascular ultrasound

ObjectiveWe evaluated the ability of 64-slice multidetector computed tomography (MDCT)-derived plaque parameters to detect and quantify coronary atherosclerosis, using intravascular ultrasound (IVUS) as the reference standard. MethodsIn 32 patients, IVUS and 64-MDCT was performed. The MDCT and IVUS datasets of 44 coronary arteries were co-registered using a newly developed fusion technique and quantitative parameters were derived from both imaging modalities. The threshold of >0.5mm of maximum wall thickness was used to establish plaque presence on MDCT and IVUS. ResultsWe analyzed 1364 coregistered 1-mm coronary cross-sections and 255 segments of 5-mm length. Compared with IVUS, 64-MDCT enabled correct detection in 957 of 1109 cross-sections containing plaque (sensitivity 86%). In 180 of 255 cross-sections atherosclerosis was correctly excluded (specificity 71%). On the segmental level, MDCT detected 213 of 220 segments with any atherosclerotic plaque (sensitivity 96%), whereas the presence of any plaque was correctly ruled out in 28 of 32 segments (specificity 88%). Interobserver agreement for the detection of atherosclerotic cross-sections was moderate (Cohen's kappa coefficient K=0.51), but excellent for the atherosclerotic segments (K=1.0). Pearson's correlation coefficient for vessel plaque volumes measured by MDCT and IVUS was r=0.91 (p<0.001). Bland–Altman analysis showed a slight non-significant underestimation of any plaque volume by MDCT (p=0.5), with a trend to underestimate noncalcified and overestimate mixed/calcified plaque volumes (p=0.22 and p=0.87 respectively). ConclusionMDCT is able to detect and quantify atherosclerotic plaque. Further improvement in CT resolution is necessary for more reliable assessment of very small and distal coronary plaques.

Potential contribution of multiplanar reconstruction (MPR) to computer-aided detection of lung nodules on MDCT

To evaluate potential benefits of using multiplanar reconstruction (MPR) in computer-aided detection (CAD) of lung nodules on multidetector computed tomography (MDCT). MDCT datasets of 60 patients with suspected lung nodules were retrospectively collected. Using "second-read" CAD, two radiologists (Readers 1 and 2) independently interpreted these datasets for the detection of non-calcified nodules (≥ 4 mm) with concomitant confidence rating. They did this task twice, first without MPR (using only axial images), and then 4 weeks later with MPR (using also coronal and sagittal MPR images), where the total reading time per dataset, including the time taken to assess the detection results of CAD software (CAD assessment time), was recorded. The total reading time and CAD assessment time without MPR and those with MPR were statistically compared for each reader. The radiologists' performance for detecting nodules without MPR and the performance with MPR were compared using jackknife free-response receiver operating characteristic (JAFROC) analysis. Compared to the CAD assessment time without MPR (mean, 69s and 57s for Readers 1 and 2), the CAD assessment time with MPR (mean, 46s and 45s for Readers 1 and 2) was significantly reduced (P<0.001). For Reader 1, the total reading time was also significantly shorter in the case with MPR. There was no significant difference between the detection performances without MPR and with MPR. The use of MPR has the potential to improve the workflow in CAD of lung nodules on MDCT.

Semiautomated Segmentation of Pleural Effusions in MDCT Datasets

To develop and evaluate a novel algorithm for semiautomated segmentation and volumetry of pleural effusions in multidetector computed tomography (MDCT) datasets. A seven-step algorithm for semiautomated segmentation of pleural effusions in MDCT datasets was developed, mainly using algorithms from the ITK image processing library. Semiautomated segmentation of pleural effusions was performed in 40 MDCT datasets of the chest (males = 22, females = 18, mean age: 56.7 +/- 19.3 years). The accuracy of the semiautomated segmentation as compared with a manual segmentation approach was quantified based on the differences of the segmented volumes, the degree of over-/undersegmentation, and the Hausdorff distance. The time needed for the semiautomated and the manual segmentation process were recorded and compared. The mean volume of the pleural effusions was 557.30 mL (+/- 477.27 mL) for the semiautomated and 553.19 (+/- 473.49 mL) for the manual segmentation. The difference was not statistically significant (Student t-test, P = .133). Regression analysis confirmed a strong relationship between the semiautomated algorithm and the gold standard (r(2) = 0.998). Mean overlap of the segmented areas was 79% (+/- 9.3%) over all datasets with moderate oversegmentation (22% +/- 9.3%) and undersegmentation (21% +/- 9.7%). The mean Hausdorff distance was 17.2 mm (+/- 8.35 mm). The mean duration of the semiautomated segmentation process with user interaction was 8.4 minutes (+/- 2.6 minutes) as compared to 32.9 minutes (+/- 17.4 minutes) for manual segmentation. The semiautomated algorithm for segmentation and volumetry of pleural effusions in MDCT datasets shows a high diagnostic accuracy when compared with manual segmentation.

Volumetric quantification of myocardial perfusion using analysis of multi-detector computed tomography 3D datasets: comparison with nuclear perfusion imaging

Although the ability of multi-detector computed tomography (MDCT) to detect perfusion abnormalities associated with acute and chronic myocardial infarction (MI) has been demonstrated, this methodology is based on visual interpretation of selected 2D slices. We sought to develop a new technique for quantitative volumetric analysis of myocardial perfusion from 3D datasets and test it against resting nuclear myocardial perfusion imaging (NMPI) reference. We studied 44 patients undergoing CTCA: a control group of 15 patients and a study group of 29 patients. MDCT datasets acquired for CTCA were analyzed using custom software designed to: (1) generate bull's eye display of myocardial perfusion and (2) calculate a quantitative index of extent and severity of perfusion abnormality, Q(H), for 16 volumetric myocardial segments. Visual interpretation of MDCT-derived bull's eyes was compared with rest NMPI scores using kappa statistics of agreement on a coronary territory and patient basis. Quantitative MDCT perfusion data were correlated with rest NMPI summed scores and used for objective detection of perfusion defects. Visual analysis of MDCT-derived bull's eyes accurately detected perfusion defects in agreement with NMPI (kappa = 0.70 by territory; 0.79 by patient). Quantitative data were in good agreement with NMPI, as reflected by: (1) correlation of 0.87 (territory) and 0.84 (patient) between summed Q(H) and NMPI scores, (2) area under ROC curve 0.87 with sensitivity of 0.79-0.92, specificity 0.83-0.91, and accuracy 0.83-0.89 for objective detection of abnormalities. Our new technique for volumetric analysis of 3D MDCT images allows accurate objective detection of perfusion defects. This perfusion information can be obtained without additional radiation or contrast load, and may aid in elucidating the significance of coronary lesions.