Orthogonal Views Research Articles

A Simple Device and Biplanar Technique to Improve Precision When Templating for Total Joint Arthroplasty

Accurate templating for arthroplasty procedures depends on reliably estimating image magnification. The authors designed a simple device and technique to accomplish this. It is a wedge with four 25-mm balls staggered at different heights, each representing a potential marker. The proper ball to use as the scaling marker is identified on an orthogonal view on the basis of its relationship with the anatomic feature of interest. Reviewing x-rays with known acetabular component diameters, the authors found that the staggered balls technique had a scaling error of 1.48±0.89%. Assuming a constant 20% magnification for all x-rays resulted in an error of 1.65±1.59%. Although similarly accurate, the difference in precision was found to be significant (P=0.012). The constant magnification method resulted in 2 outliers with >4% error, whereas there were no outliers with the novel technique. Staggered marker balls combined with orthogonal imaging is accurate and improves the precision of estimating radiograph magnification.

Bony Hypertrophy in Vascularized Fibular Grafts.

Background: Vascularized fibula graft (VFG) transfer is an established method of repairing large skeletal defects resulting from trauma, tumor resection, or infection. It obviates the process of creeping substitution that conventional bone grafts undergo and therefore exhibits better healing and improved strength. The aim of this study is to evaluate hypertrophy in VFG. Methods: We retrospectively reviewed patients undergoing VFG and studied immediate and late postoperative radiographs. Orthogonal views were measured for width of graft cortex and intramedullary canal, as well as adjacent recipient bone. Changes were measured for total cross sectional area, cortical area, intramedullary area, and graft width. Results: Thirty patients were included in the analysis, with recipient sites including 3 forearm, 4 humerus, 12 tibia, and 11 femur. Mean follow-up was 7.6 years (0.5-24.9 years). Patients' mean age was 31 (16-59 years). Average hypertrophy was 254% in early postoperative period and 340% in the late postoperative period. There was rapid graft hypertrophy in early postoperative period that plateaued with time. The width of the graft increased over time but didn't exceed the width of the adjacent recipient bone. In the later postoperative period, the size of graft intramedullary canal increased. Upper and lower extremity grafts showed similar hypertrophy. Conclusions: Using VFG to treat large skeletal defects is an attractive option in part due to the graft's ability to hypertrophy. We describe an early period of periosteal hypertrophy, followed by endosteal hypertrophy. These processes have relevance to function, mechanical strength, and surgical decision-making.

Triplanar convolution with shared 2D kernels for 3D classification and shape retrieval

Increasing the depth of Convolutional Neural Networks (CNNs) has been recognized to provide better generalization performance. However, in the case of 3D CNNs, stacking layers increases the number of learnable parameters linearly, making it more prone to learn redundant features. In this paper, we propose a novel 3D CNN structure that learns shared 2D triplanar features viewed from the three orthogonal planes, which we term S3PNet. Due to the reduced dimension of the convolutions, the proposed S3PNet is able to learn 3D representations with substantially fewer learnable parameters. Experimental evaluations show that the combination of 2D representations on the different orthogonal views learned through the S3PNet is sufficient and effective for 3D representation, with the results outperforming current methods based on fully 3D CNNs. We support this with extensive evaluations on widely used 3D data sources in computer vision: CAD models, LiDAR point clouds, RGB-D images, and 3D Computed Tomography scans. Experiments further demonstrate that S3PNet has better generalization capability for smaller training sets, and learns more of kernels with less redundancy compared to kernels learned from 3D CNNs.

Fusion of Multi-Size Candidate Regions Enhances Two-Stage Hippocampus Segmentation

The hippocampus plays an important role in the memory and cognition abilities of humans. Precise three-dimensional (3D) segmentation of the hippocampus from magnetic resonance imaging scans is of great importance in the diagnosis of neurological diseases. Conventional automatic segmentation methods poorly achieve satisfactory performance because of the irregular shape and small volume of the hippocampus. We propose a novel two-stage segmentation method, which includes a localization stage and a segmentation stage, to handle the task of the 3D segmentation of the hippocampus. In the localization stage, a novel strategy for localizing multi-size candidate regions was developed to improve the sample balance for the 3D segmentation task. In the segmentation stage, a method which fuses the multi-size candidate regions was proposed to improve the accuracy in predicting the hippocampal boundary, after which we aggregated the segmentation results from three orthogonal views to further improve the performance. Quantitative evaluation was performed on the Alzheimer's Disease Neuroimaging Initiative dataset. The experimental results achieved Dice similarity coefficients of 92.48 ± 0.61% and 92.90 ± 0.51% for the left and right hippocampus, respectively, outperforming state-of-the-art studies in hippocampus segmentation tasks.

Patch-based generative adversarial neural network models for head and neck MR-only planning.

To evaluate pix2pix and CycleGAN and to assess the effects of multiple combination strategies on accuracy for patch-based synthetic computed tomography (sCT) generation for magnetic resonance (MR)-only treatment planning in head and neck (HN) cancer patients. Twenty-three deformably registered pairs of CT and mDixon FFE MR datasets from HN cancer patients treated at our institution were retrospectively analyzed to evaluate patch-based sCT accuracy via the pix2pix and CycleGAN models. To test effects of overlapping sCT patches on estimations, we (a) trained the models for three orthogonal views to observe the effects of spatial context, (b) we increased effective set size by using per-epoch data augmentation, and (c) we evaluated the performance of three different approaches for combining overlapping Hounsfield unit (HU) estimations for varied patch overlap parameters. Twelve of twenty-three cases corresponded to a curated dataset previously used for atlas-based sCT generation and were used for training with leave-two-out cross-validation. Eight cases were used for independent testing and included previously unseen image features such as fused vertebrae, a small protruding bone, and tumors large enough to deform normal body contours. We analyzed the impact of MR image preprocessing including histogram standardization and intensity clipping on sCT generation accuracy. Effects of mDixon contrast (in-phase vs water) differences were tested with three additional cases. The sCT generation accuracy was evaluated using mean absolute error (MAE) and mean error (ME) in HU between the plan CT and sCT images. Dosimetric accuracy was evaluated for all clinically relevant structures in the independent testing set and digitally reconstructed radiographs (DRRs) were evaluated with respect to the plan CT images. The cross-validated MAEs for the whole-HN region using pix2pix and CycleGAN were 66.9±7.3 vs 82.3±6.4HU, respectively. On the independent testing set with additional artifacts and previously unseen image features, whole-HN region MAEs were 94.0±10.6 and 102.9±14.7HU for pix2pix and CycleGAN, respectively. For patients with different tissue contrast (water mDixon MR images), the MAEs increased to 122.1±6.3 and 132.8±5.5HU for pix2pix and CycleGAN, respectively. Our results suggest that combining overlapping sCT estimations at each voxel reduced both MAE and ME compared to single-view non-overlapping patch results. Absolute percent mean/max dose errors were 2% or less for the PTV and all clinically relevant structures in our independent testing set, including structures with image artifacts. Quantitative DRR comparison between planning CTs and sCTs showed agreement of bony region positions to <1mm. The dosimetric and MAE based accuracy, along with the similarity between DRRs from sCTs, indicate that pix2pix and CycleGAN are promising methods for MR-only treatment planning for HN cancer. Our methods investigated for overlapping patch-based HU estimations also indicate that combining transformation estimations of overlapping patches is a potential method to reduce generation errors while also providing a tool to potentially estimate the MR to CT aleatoric model transformation uncertainty. However, because of small patient sample sizes, further studies are required.

Computer-assisted craniometric evaluation for diagnosis and follow-up of craniofacial asymmetries: SymMetric v. 1.0.

The current assessment of patients with craniofacial asymmetries is accomplished by physical examination, anamnesis and radiological imaging. We propose a semi-automated, computer-assisted craniofacial evaluation (SymMetric v 1.0) based on orthogonal photography of the patient's head in 3 positions. The system is simple, low-cost, no-radiation or special resources needed. Although it does not substitute CT in cases of doubt between craniosynostosis and positional plagiocephaly, multiple numeric evaluations indicate regional deformities and severity of the asymmetry, which can help in the clinical decision of indicating or not the orthosis in positional deformities, determining treatment duration or evaluating surgical outcomes after correction. A Matlab-based tool was developed for digital processing of photographs taken in 3 positions (anterior, superior and lateral). The software guides the user to select visible and reproducible landmarks in each photograph acquisition and calculates multiple indexes and metrics, generating a set of comprehensive plots to offer the user an overview of head and facial symmetry across the orthogonal views. For purposes of demonstration, we evaluated 2 patients (one control and one with non-sinostotic deformity). The results show a clear differentiation of the control and plagiocephalic patient metrics mainly in the superior view, showing potential for diagnosis of the condition, and also detected the clinical improvement during helmet treatment in the follow-up, 3 and 5months after orthosis' use. We presented a proof-of-concept for a low cost, no radiation evaluation system for craniofacial asymmetries, that can be useful in a clinical context for diagnosis and follow-up of patients.

Lymph node detection in MR Lymphography: false positive reduction using multi-view convolutional neural networks.

PurposeTo investigate whether multi-view convolutional neural networks can improve a fully automated lymph node detection system for pelvic MR Lymphography (MRL) images of patients with prostate cancer.MethodsA fully automated computer-aided detection (CAD) system had been previously developed to detect lymph nodes in MRL studies. The CAD system was extended with three types of 2D multi-view convolutional neural networks (CNN) aiming to reduce false positives (FP). A 2D multi-view CNN is an efficient approximation of a 3D CNN, and three types were evaluated: a 1-view, 3-view, and 9-view 2D CNN. The three deep learning CNN architectures were trained and configured on retrospective data of 240 prostate cancer patients that received MRL images as the standard of care between January 2008 and April 2010. The MRL used ferumoxtran-10 as a contrast agent and comprised at least two imaging sequences: a 3D T1-weighted and a 3D T2*-weighted sequence. A total of 5089 lymph nodes were annotated by two expert readers, reading in consensus. A first experiment compared the performance with and without CNNs and a second experiment compared the individual contribution of the 1-view, 3-view, or 9-view architecture to the performance. The performances were visually compared using free-receiver operating characteristic (FROC) analysis and statistically compared using partial area under the FROC curve analysis. Training and analysis were performed using bootstrapped FROC and 5-fold cross-validation.ResultsAdding multi-view CNNs significantly (p < 0.01) reduced false positive detections. The 3-view and 9-view CNN outperformed (p < 0.01) the 1-view CNN, reducing FP from 20.6 to 7.8/image at 80% sensitivity.ConclusionMulti-view convolutional neural networks significantly reduce false positives in a lymph node detection system for MRL images, and three orthogonal views are sufficient. At the achieved level of performance, CAD for MRL may help speed up finding lymph nodes and assessing them for potential metastatic involvement.

K-Net: Integrate Left Ventricle Segmentation and Direct Quantification of Paired Echo Sequence.

The integration of segmentation and direct quantification on the left ventricle (LV) from the paired apical views(i.e., apical 4-chamber and 2-chamber together) echo sequence clinically achieves the comprehensive cardiac assessment: multiview segmentation for anatomical morphology, and multidimensional quantification for contractile function. Direct quantification of LV, i.e., to automatically quantify multiple LV indices directly from the image via task-aware feature representation and regression, avoids accumulative error from the inter-step target. This integration sequentially makes a stereoscopical reflection of cardiac activity jointly from the paired orthogonal cross views sequences, overcoming limited observation with a single plane. We propose a K-shaped Unified Network (K-Net), the first end-to-end framework to simultaneously segment LV from apical 4-chamber and 2-chamber views, and directly quantify LV from major- and minor-axis dimensions (1D), area (2D), and volume (3D), in sequence. It works via four components: 1) the K-Net architecture with the Attention Junction enables heterogeneous tasks learning of segmentation task of pixel-wise classification, and direct quantification task of image-wise regression, by interactively introducing the information from segmentation to jointly promote spatial attention map to guide quantification focusing on LV-related region, and transferring quantification feedback to make global constraint on segmentation; 2) the Bi-ResLSTMs distributed in K-Net layer-by-layer hierarchically extract spatial-temporal information in echo sequence, with bidirectional recurrent and short-cut connection to model spatial-temporal information among all frames; 3) the Information Valve tailing the Bi-ResLSTMs selectively exchanges information among multiple views, by stimulating complementary information and suppressing redundant information to make the efficient cross-flow for each view; 4) the Evolution Loss comprehensively guides sequential data learning, with static constraint for frame values, and dynamic constraint for inter-frame value changes. The experiments show that our K-Net gains high performance with a Dice coefficient up to 91.44% and a mean absolute error of the major-axis dimension down to 2.74mm, which reveal its clinical potential.

Adaptive Importance Learning for Improving Lightweight Image Super-Resolution Network

Deep neural networks have achieved remarkable success in single image super-resolution (SISR). The computing and memory requirements of these methods have hindered their application to broad classes of real devices with limited computing power, however. One approach to this problem has been lightweight network architectures that balance the super-resolution performance and the computation burden. In this study, we revisit this problem from an orthogonal view, and propose a novel learning strategy to maximize the pixel-wise fitting ability of a given lightweight network architecture. Considering that the initial performance of the lightweight network is very limited, we present an adaptive importance learning scheme for SISR that trains the network with an easy-to-complex paradigm by dynamically updating the importance of image pixels on the basis of the training loss. Specifically, we formulate the network training and the importance learning into a joint optimization problem. With a carefully designed importance penalty function, the importance of individual pixels can be gradually increased through solving a convex optimization problem. The training process thus begins with pixels that are easy to reconstruct, and gradually proceeds to more complex pixels as fitting improves. Furthermore, the proposed learning scheme is able to seamlessly assimilate knowledge from a more powerful teacher network in the form of importance initialization, thus obtaining better initial performance for the network. Through learning the network parameters, and updating pixel importance, the proposed learning scheme enables smaller, lightweight, networks to achieve better performance than has previously been possible. Extensive experiments on four benchmark datasets demonstrate the potential benefits of the proposed learning strategy in lightweight SISR network enhancement. In some cases, our learned network with only $$25\%$$ of the parameters and computational complexity can produce comparable or even better results than the corresponding full-parameter network.

Magnetic resonance-guided high intensity focused ultrasound (MR-HIFU) hyperthermia for primary rectal cancer: A virtual feasibility analysis.

77 Background: MR-HIFU Hyperthermia (HT) is a non-invasive treatment modality with real-time thermometry that ensures accurate and precise heating of a target with minimal effect on adjacent tissue. This energy deposition within a tumour can produce local bioeffects resulting in thermal chemo- and radiosensitization. MR-HIFU has been shown to be safe and feasible in a companion phase I study for recurrent rectal cancer. The purpose of this study is to determine the feasibility of MR-HIFU in treating primary rectal tumours. Methods: With ethics approval, the anatomic characteristics and surrounding structures of rectal tumours diagnosed at Sunnybrook from 2014-2019 were retrospectively analyzed. Three orthogonal views of MR images were used to determine the potential ultrasound (US) beam path and organs at risk (OAR). In part 2 of the study, the gross tumour volume was delineated for 30 rectal tumours (10 low, mid &amp;high). Image datasets were imported into the Sonalleve MR-HIFU workstation for virtual treatment simulation and planning to determine tumour targetability, coverage, optimal patient set-up, and transducer positioning. Results: Of the 105 tumours analyzed, 36, 52, and 17 were low, mid, and high, respectively. The average width of the acoustic window (sciatic notch) for the US beam path was 5.8 ± 1.4cm, average tumour length was 5.24 ± 2.0cm, and average beam path (skin to tumour edge) was 7.3 ± 1.9cm. Eighty one percent of tumours were ≤ 0.3cm from an OAR. Of the 24 virtually simulated tumours to date, 6/8 lower, 6/8 mid, and 1/8 upper rectal tumours were targetable by MR-HIFU. Conclusions: This is the first virtual analysis to evaluate MR-HIFU HT targetability in primary rectal cancer. Results from this study will support MR-HIFU HT as an option to enhance the treatment of primary rectal cancer. Acknowledgments: This study has been funded by the Canadian Cancer Society. Patient &amp; tumour characteristics. [Table: see text]

RADIOLOGIC MEASUREMENT AND DETERMINATION OF KIDNEY-TO-VERTEBRA RATIOS AS A METHOD OF ESTIMATING RENAL SIZE IN SERVALS (LEPTAILURUS SERVAL)

Numerous conditions, from acute to chronic renal changes, have the potential to alter the renal size on radiographs. However, current literature does not provide any radiographic reference range for the normal renal size in the serval (Leptailurus serval). This retrospective study includes 13 healthy adult servals, seen between 2004 and 2017 at the UTCVM Veterinary Medical Center, deemed healthy based on physical examination and blood work. Orthogonal radiographs were anonymized, calibrated, and evaluated blindly by three observers of different experience levels. Renal and individual lumbar vertebral body lengths were measured on both orthogonal views, and ratios of kidney length to each lumbar vertebral length were calculated on both views. On the ventro-dorsal projection, the kidney length to L5 vertebra ratio had the lowest standard deviation (SD) with a mean of 1.82, SD of 0.27, and 95% confidence interval (CI) (1.63-2.00). On the lateral view, the kidney length to L3 vertebra ratio had the lowest SD with a mean of 2.03, SD of 0.25, and 95% CI(1.86-2.20). Statistically, all three observers were shown to be in agreement, indicating reproducibility of the measurements among observers with different levels of expertise.

Large-Strain 3-D in Vivo Breast Ultrasound Strain Elastography Using a Multi-compression Strategy and a Whole-Breast Scanning System

Non-linear mechanical properties of breast tissue can be employed to diagnose and differentiate breast tumors. To obtain such non-linear mechanical properties, it is necessary to track tissue motion under large deformation. In this study, a multi-compression strategy was utilized to produce large tissue deformation, and a method to estimate 3-D motion of tissue under large deformation was introduced. Given multiple volumes of ultrasound data, the proposed method first estimates volume-to-volume incremental displacements using a 3-D region-growing motion-tracking method. Then, possible outliers among all incremental displacements are removed to avoid error accumulation. Once large displacement errors have been removed, all incremental displacements are registered together to obtain accumulated displacements under large tissue deformation (e.g., >10%). The proposed method was tested with one set of in vivo tumor-bearing ultrasound data acquired from a human subject. A total of 10 small-strain deformation steps were performed to obtain the final accumulated displacement field, in which the breast lesion and its surrounding were deformed by approximately 6% and 16%, respectively. The contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of the elasticity images obtained with the proposed method were all higher than those obtained with a 2-D tracking method. Furthermore, in three orthogonal views of accumulated axial strain images, the breast lesion was clearly visible with good correspondence between the axial strain and B-mode images.

Transvaginal three-dimensional ultrasound assessment of Sylvian fissures at 18-30 weeks' gestation.

To (1) evaluate the normal development of the Sylvian fissures in the anterior coronal view of the fetal brain at 18-30 weeks' gestation by transvaginal three-dimensional (3D) ultrasound, (2) develop reference ranges of measurements of the right and left Sylvian fissure angles during normal pregnancy at 18-30 weeks' gestation, and (3) examine intra- and interobserver repeatability of measurements of the right and left Sylvian fissure angles. This was a prospective cross-sectional study of 422 women with a singleton pregnancy attending an ultrasound-based research clinic between March and December 2017. The entry criteria for the study were appropriately grown live fetus with no suspected structural and/or chromosomal defects between 18 + 0 and 30 + 6 weeks' gestation. Normal development of the Sylvian fissures was assessed in the anterior coronal plane of the fetal brain using transvaginal 3D volume multiplanar imaging. The coronal view was visualized as a single image from the three orthogonal views. Subsequently, the right and left Sylvian fissure angles were measured between a horizontal reference line (0°) and a line drawn along the upper side of the respective Sylvian fissure. Intra- and interobserver repeatability of the Sylvian fissure angle measurements was assessed by Bland-Altman plots. Reference equations were constructed for right and left Sylvian fissure angles for gestational age (GA) and head circumference (HC) using the Generalized Additive Models for Location Scale and Shape package. In the anterior coronal view of the fetal brain, an inward rotation of the upper portion of the Sylvian fissures was observed during the second and third trimesters of pregnancy. There was a significant negative polynomial association between the Sylvian fissure angles and GA and HC. Both Sylvian fissure angles crossed the reference line (zero), going from positive to negative, at around 25 weeks' gestation or at HC of 22 cm. Z-score difference between the smoothed percentiles of the right and left Sylvian fissure angles indicated that median, 10th and 90th smoothed percentiles were closest and almost the same for the GA-based references between 18 and 28 weeks and for the HC-based references between 14 and 24 cm. The intraclass correlation coefficient of the right and left Sylvian fissure angle measurements between the two sonographers was excellent at 0.993 (95% CI, 0.988-0.996) and 0.991 (95% CI, 0.985-0.995), respectively. On Bland-Altman analysis, the mean difference between the two sonographers in right Sylvian fissure angle measurement was 0.4° (95% CI, -10.2 to 10.1°) and in left Sylvian fissure angle it was 1.0° (95% CI, -9.6 to 11.6°). Assessment of the Sylvian fissure angles is highly reproducible. Sylvian fissure angle reference charts can serve as a screening tool for malformations of cortical development, guiding subsequent follow-up and referral for fetal brain magnetic resonance imaging and/or assessment by an expert neurosonologist. Copyright © 2018 ISUOG. Published by John Wiley & Sons Ltd.

Increased Sylvian fissure angle as early sonographic sign of malformation of cortical development.

ABSTRACTObjectiveTo evaluate Sylvian fissure development by assessing Sylvian fissure angles in fetuses with malformation of cortical development (MCD).MethodsThis was a retrospective study of 22 fetuses with MCD. Cases with a stored three‐dimensional (3D) brain volume acquired at 18 + 0 to 30 + 6 weeks of gestation at an ultrasound‐based research clinic between January 2010 and December 2017 were identified through a database. Of the 22 fetuses, seven had an extracranial abnormality, such as cardiac, renal, gastrointestinal and/or digital anomalies, and five had a minor abnormality such as micrognathia, low‐set ears and/or single umbilical artery. To confirm the final clinical diagnosis of brain abnormality, postmortem histological findings or prenatal or postnatal magnetic resonance images were used. For measurement of Sylvian fissure angle, an anterior coronal plane of the fetal brain on transvaginal 3D volume multiplanar imaging was visualized as a single image from the three orthogonal views. The right and left Sylvian fissure angles were measured between a horizontal reference line (0°) and a line drawn along the upper side of the respective Sylvian fissure. The Sylvian fissure angle on both sides was plotted on the graphs of the reference ranges for gestational age in weeks.ResultsIn 21 (95.5%; 95% CI, 86.8–100.0%) of 22 fetuses with MCD, the Sylvian fissure angle on one or both sides was larger than the 90th percentile of the normal reference. There was one case with apparent focal MCD in the parietal lobe, but the Sylvian fissure angles were normal. A case with apparent unilateral cortical dysplasia and one with apparent unilateral schizencephaly had conspicuous discrepancies between the left and right Sylvian fissure angles. Abnormal genetic test results were obtained in six cases, including four cases with a mutation in a single gene.ConclusionsThis study has shown that the Sylvian fissures, as defined by the Sylvian fissure angle, have delayed development in most MCD cases prior to the diagnosis of the condition. The Sylvian fissure angle may potentially be a strong indicator for the subsequent development of cortical malformation, before the time point at which the gyri and sulci become obvious on the fetal brain surface. Further research is required to validate these findings. © 2018 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.

Third Place Award: Characterization and incidence of occult posterior malleolar fractures

Background: Occult fractures of the posterior malleolus are often missed by primary care providers and radiologists. Delayed treatment of posterior malleolar fractures can be problematic because of the potential for malunion, arthritis, or instability. The incidence and characterization of missed posterior malleolar fractures has not been reported in the literature. Methods: A retrospective review was performed of all ankle fractures with CT scans from 2005 to 2015 at a single institution. Inclusion criteria included age older than 18 yr and posterior malleolar fracture as seen on CT scan. Exclusion criteria included distal tibial shaft fractures and pilon fractures. Forty-six patients were identified with the above criteria. Data collected included whether a fracture was missed on initial radiographs by a board-certified radiologist, and the size and angle of the posterior malleolar fragment. Results: Of the 46 patients with posterior malleolar fractures, nine (19.5%) were missed on the radiology report. Seven of 46 (15.2%) were not described on all plain films prior to the CT scan. Two of seven (28.6%) radiographically occult fractures underwent open reduction and internal fixation of the posterior malleolar fragment. The average angle of occult posterior malleolar fractures relative to the transmalleolar axis was quite variable, with an average of 17 degrees (SD 11 degrees, range −20 degrees to 50 degrees). Conclusions: With a 15% incidence of occult posterior malleolar fractures, a CT scan or multiple orthogonal views can be helpful to avoid missed fractures. Given the wide variability of fracture angle, a single external rotation view is unlikely to prevent all missed fractures on initial radiographic interpretations. Level of Evidence: Level III, retrospective cohort study.

Improved Vinegar & Wellington calibration for estimation of fluid saturation and porosity from CT images for a core flooding test under geologic carbon storage conditions

X-ray computed tomography (CT) of fluid flow in formation rocks is an important characterization technique in geologic carbon sequestration research to provide insight into the migration and capillary trapping of CO2 under reservoir conditions. An improved calibration method adapted from traditional Vinegar & Wellington calibration is proposed to map the 3D pore and fluid distributions from the CT images of CO2/brine displacement flooding. Similar to Vinegar & Wellington calibration, the proposed method adopts the linear scaling law of CT number transformation to mass density. However, different from Vinegar & Wellington calibration that uses a 100% brine-saturated core image and a 100% CO2-saturated core image as references to calculate CO2 and brine saturations at all time steps, the proposed method uses the CT numbers of CO2 and brine to calculate the incremental of CO2 and brine saturations from time step i to time step i +1. The method is intended for cases in which the two 100% brine saturation and 100% CO2 saturation images can not be successfully obtained. Overall, the improved calibration proposed by this study presents more reasonable results of CO2 and brine distribution in a Berea sandstone core, as compared to traditional Vinegar & Wellington calibration. The reconstructed porosity image agrees with the laminated structure of the Berea sandstone core, and the average porosity evaluated over the entire core (0.176) is comparable to the physical porosity (0.165). Furthermore, the reconstructed saturation images using the improved calibration reveal a flat piston-like flooding front from a homogeneous longitudinal-section of the 3D orthogonal view and preferential fingerings from another non-homogeneous longitudinal-section, which are not present in the reconstructed saturation images using traditional Vinegar & Wellington calibration. Concerns and causes with respect to the uncertainty of linear CT number calibration are also explained, and approaches to alleviate the uncertainty are suggested.

Imaging characteristics of acute type A aortic dissection and candidacy for repair with ascending aortic endografts

BackgroundAcute type A aortic dissection (ATAD) remains associated with substantial short-term mortality, and despite increasing rates of surgical repair, as many as 10% to 20% of patients do not undergo surgery because of comorbidities and dissection-related complications. For patients unable to undergo open repair, previous attempts at endovascular treatment of ATAD used devices originally designed for deployment in the descending thoracic aorta. Industry has begun to support early investigational devices meant specifically for placement within the ascending aorta. We evaluated relevant aortic parameters to examine which patients may be candidates for repair with an ascending aortic endograft. MethodsWe reviewed 100 consecutive patients in our institutional ATAD database with contrast-enhanced computed tomography imaging on an Aquarius iNtuition workstation (TeraRecon, San Mateo, Calif), using curved planar reformatting (vessel tracking) and orthogonal views for measurements. We compared relevant aortic measurements against proposed criteria for future ascending endografts, including various landing zone diameters and intimal tear distances from the distal coronary ostium. ResultsOf the 100 patients examined, 39% had proximal intimal tears located outside the tubular ascending aorta. In all, 30% were excluded on the basis of either the presence of a prosthetic aortic valve or significant aortic insufficiency, and 6% were excluded on the basis of the presence of patent coronary artery bypass grafts from the ascending aorta. Many patients had multiple exclusion criteria, and based on various proposed criteria, overall candidacy ranged from 2% to 23%. If a maximum landing zone diameter of 42 mm and intimal tears as little as 20 mm distal to the distalmost coronary were considered treatable, only 8% of patients would have been candidates compared with 20% candidacy if aortic diameters up to 46 mm and intimal tears as little as 10 mm distal to the distalmost coronary were considered treatable. The most frequent single cause for exclusion was inadequacy of the proximal landing zone. Iliofemoral vascular access was also assessed and deemed adequate in >90% of cases. ConclusionsA minority of patients suffering ATAD would currently qualify for ascending aortic endografting on the basis of anatomic criteria alone. Future device designs should take into account these common anatomic exclusion criteria so that more versatile devices may be developed and commercially available to treat a larger number of patients.

MOSAICING FIDELITY GEOMETRICAL ASSESSMENT BASED ON SURF POINT CLASSIFICATION

Abstract. The recent development of automated UAV imaging applications for geomatics is leading to an unprecedented rapid growth in mosaic and DEM images. Newer, more advanced algorithms are being extensively studied to fulfill constantly increasing requirements. Sequences of georeferenced images that cannot be shot at once are merged with ideally no geometrical distortion to allow for 3D reconstruction and orthophotography generation. If newer robust mosaicing algorithms are being developed to withstand UAV tighter real-time constraints, very little attention has been given to objectively assess their capacity to coherently combine different image geometries. Changes in FOV and illumination, oblique scenes and dynamic sequences featuring movement and object occlusion are not yet fully handled by state-of-the-art algorithms. Despite the large panel of existing applications featuring different quality constraints, our work focuses on the geomatics context, where the main requirement is the respect of geometrical proportions among images. Geometrically coherent mosaics and 3D reconstructions can only result from fully static, high-altitude orthogonal views. GCPs or well known geographical landmarks are employed with RTK-GPS for scene georeferencing. The overall fidelity is computed as the global variance of the distances between SGPs. However, very few ways seem to exist to measure the content coherence of large geographical scenes, interiors or unreferenced scenes. Distances are mostly expressed in a local coordinate system and GCPs are often unavailable. The main contribution of this paper consists in the definition of a formal metric for measuring local coordinate geometrical fidelity of mosaics issued of UAV image sequences, in real operating conditions. A Mosaicing Fidelity Assessment (MSF) index is therefore computed for every couple of consecutive images of a sequence. The metric generates an index based on the distances of SURF feature points extracted in the images and compares them to estimate geometrical changes transferred to the mosaic. The solution can detect perspective inaccuracies caused by residual registration errors. It can fulfill the requirements of most of imaging and geomatics applications and can be executed as nearly real-time due to its low computational complexity.

Accuracy of imaging fusion between echocardiography and fluoroscopy in percutaneous atrial septal defect closure in children

Imaging fusion between echocardiography and fluoroscopy is now available in the catheterization laboratory. We aim to test the feasibility and accuracy of imaging fusion in a pediatric population. Thirty-one patients (26 kgs [21–37]) underwent percutaneous atrial septal defect (ASD) closure were prospectively included. Occluder device's screw, visualized on both echocardiography and fluoroscopy images was used as a reference tool. Bias was measured between a marker positioned on the device screw visualized on echocardiography and the fluoroscopic screw image on the fusion screen (distance 1). Another bias was measured between the screw on 3D echocardiographic image and the screw on fluoroscopic image (distance 2). The 2 distances were measured on 4 orthogonal views in end-systolic and end-diastolic frames. Fusion and marker positioning were feasible in real-time in all cases. In 5 cases (16.1%), there was a transient loss of the automatic tracking of the probe during the procedure. Quality of imaging fusion was rated good in all cases. On the fusion screen, systolic and diastolic first distances were 0.5 [0.3–1] and 2 mm [1.5–2.5] ( P < 0.0001). The marker positioned from echocardiography screen was fixed on fusion screen and did not follow the systole-diastolic translation of the screw. Systolic and diastolic second distances were 0.5 [0–0.5] and 2 mm [1.5–2.5] ( P < 0.0001). Echocardiographic-fluoroscopic imaging fusion is feasible, safe and accurate in children above 20 kgs. This innovate technic offers a new real-time imaging guiding modality in the catheterization laboratory with potential interest in complex procedures as well as for fellow training.

Lesion Localization Using Digital Breast Tomosynthesis: Where Did I Go Wrong?

The scroll bar on digital breast tomosynthesis has become an imperative tool that breast imaging radiologists rely on for help in identify lesions on the orthogonal view, targeting breast ultrasound, and performing challenging biopsies for one-view findings. The ability to predict the lesion location using the scroll bar not only saves time in the diagnostic setting but also reduces screening recalls when a finding can be confirmed as dermal. It is important, however, to recognize settings in which the location prediction can be misleading, such as for lesions in thin breast tissue or the anterior portion of the breast or if the breast is not appropriately positioned. In these situations, radiologists can use other diagnostic tools for problem solving.