Search

BACKGROUND: Langerhans cell histiocytosis (LCH) is a neoplastic transformation of myeloid precursors that commonly presents as an osteolytic lesion of the long or flat bones in children. Aneurysmal bone cysts (ABC) are benign neoplasms that frequently affect the metaphysis of long bones and the spine, often revealing a rapidly expansile lesion with fluid-fluid levels. LCH with secondary ABC-like changes is a rare condition that has only been reported five times, with two presentations in the cranium. The aim of this paper is to review the etiology, clinical and radiographic presentations, and treatment of this condition, as well as to present a novel case on the topic. CASE DESCRIPTION: We describe a 5-year-old boy with a rapidly growing head mass and eye pain resulting in a diagnosis of LCH with secondary ABC-like changes. Radiography demonstrated an expansile, lytic lesion of the left parietal bone with fluid-fluid levels. A confirmatory diagnosis was made through histopathology, demonstrating an inflammatory, histiocytic infiltrate staining positive for CD1a, CD68, CD207 (Langerin), and S-100. The lesion was surgically excised, and the patient recovered without any complications. CONCLUSION: We present a novel case of LCH with secondary ABC-like changes managed with surgical excision. While a radiographic workup with multiple imaging modalities is helpful for diagnosis, a thorough immunohistochemical analysis is essential as imaging characteristics are variable and nonspecific. Furthermore, surgical excision should be considered first-line treatment for lesions involving the skull in surgically accessible areas as it is curative, alleviates symptoms, and allows for histopathological diagnosis.

Proton CT (pCT) is a promising new imaging technique that can reconstruct relative stopping power (RSP) more accurately than x-ray CT in each cubic millimeter voxel of the patient. This, in turn, will result in better proton range accuracy and, therefore, smaller planned tumor volumes (PTV). The hardware description and some reconstructed images have previously been reported. In a series of two contributions, we focus on presenting the software algorithms that convert pCT detector data to the final reconstructed pCT images for application in proton treatment planning. There were several options on how to accomplish this, and we will describe our solutions at each stage of the data processing chain. In the first paper of this series, we present the data acquisition with the pCT tracking and energy-range detectors and how the data are preprocessed, including the conversion to the well-formatted track information from tracking data and water-equivalent path length from the data of a calibrated multi-stage energy-range detector. These preprocessed data are then used for the initial image formation with an FDK cone-beam CT algorithm. The output of data acquisition, preprocessing, and FDK reconstruction is presented along with illustrative imaging results for two phantoms, including a pediatric head phantom. The second paper in this series will demonstrate the use of iterative solvers in conjunction with the superiorization methodology to further improve the images resulting from the upfront FDK image reconstruction and the implementation of these algorithms on a hybrid CPU/GPU computer cluster.

The current worldwide energy supply is insufficient to meet the rising demand. As a result, the energy prices are expected to keep soaring despite the recent increases in a variety of renewable energy resources. Although not renewable, shale oil and gas — “unconventional” hydrocarbon resources are relatively clean forms of energy resources, which still hold a vast share of the energy market. For many oil and gas companies, meeting profitable production goals from shale reservoirs is sometimes challenging, due to the loss of fracture conductivity and premature declines in the production. In this paper we investigate the stress-dependent changes in the hydraulic conductivity of proppant-filled fractures and mechanical fracture–proppant interactions in Caney Shale, a calcareous, organic-rich mudrock, through laboratory experiments and numerical modeling. American Petroleum Institute (API) fracture conductivity tests were conducted using 2% KCl on five locations within the Caney Shale that consisted of selecting three brittle (reservoir) zones and two ductile zones. Confining pressures ranged from 1,000 psi to 12,000 psi at 210 °F. Conductivity, permeability as well as embedment were measured during the test. Also, an additional, laboratory in-situ visualization test was conducted to examine the detailed proppant-shale matrix interaction under elevated stress (3,920 psi effective stress) and temperature (252 °F), with a synthetic reservoir fluid. Our experimental results have confirmed that improved fracture conductivity is attributed to proppant size, and that the increase in porosity of the proppant pack, closure pressure changes and the reduction in fracture conductivity are a function of many factors such as fracture closure stress.

Survival in congenital heart disease has steadily improved since 1938, when Dr. Robert Gross successfully ligated for the first time a patent ductus arteriosus in a 7-year-old child. To continue the gains made over the past 80 years, transformative changes with broad impact are needed in management of congenital heart disease. Three-dimensional printing is an emerging technology that is fundamentally affecting patient care, research, trainee education, and interactions among medical teams, patients, and caregivers. This paper first reviews key clinical cases where the technology has affected patient care. It then discusses 3-dimensional printing in trainee education. Thereafter, the role of this technology in communication with multidisciplinary teams, patients, and caregivers is described. Finally, the paper reviews translational technologies on the horizon that promise to take this nascent field even further.

Survival in congenital heart disease has steadily improved since 1938, when Dr. Robert Gross successfully ligated for the first time a patent ductus arteriosus in a 7-year-old child. To continue the gains made over the past 80 years, transformative changes with broad impact are needed in management of congenital heart disease. Three-dimensional printing is an emerging technology that is fundamentally affecting patient care, research, trainee education, and interactions among medical teams, patients, and caregivers. This paper first reviews key clinical cases where the technology has affected patient care. It then discusses 3-dimensional printing in trainee education. Thereafter, the role of this technology in communication with multidisciplinary teams, patients, and caregivers is described. Finally, the paper reviews translational technologies on the horizon that promise to take this nascent field even further.

The images generated during radiation oncology treatments provide a valuable resource to conduct analysis for personalized therapy, outcomes prediction, and treatment margin optimization. Deformable image registration (DIR) is an essential tool in analyzing these images. We are enhancing and examining DIR with the contributions of this paper: 1) implementing and investigating a cloud and graphic processing unit (GPU) accelerated DIR solution and 2) assessing the accuracy and flexibility of that solution on planning computed tomography (CT) with cone-beam CT (CBCT). Registering planning CTs and CBCTs aids in monitoring tumors, tracking body changes, and assuring that the treatment is executed as planned. This provides significant information not only on the level of a single patient, but also for an oncology department. However, traditional methods for DIR are usually time-consuming, and manual intervention is sometimes required even for a single registration. In this paper, we present a cloud-based solution in order to increase the data analysis throughput, so that treatment tracking results may be delivered at the time of care. We assess our solution in terms of accuracy and flexibility compared with a commercial tool registering CT with CBCT. The latency of a previously reported mutual information-based DIR algorithm was improved with GPUs for a single registration. This registration consists of rigid registration followed by volume subdivision-based nonrigid registration. In this paper, the throughput of the system was accelerated on the cloud for hundreds of data analysis pairs. Nine clinical cases of head and neck cancer patients were utilized to quantitatively evaluate the accuracy and throughput. Target registration error (TRE) and structural similarity index were utilized as evaluation metrics for registration accuracy. The total computation time consisting of preprocessing the data, running the registration, and analyzing the results was used to evaluate the system throughput. Evaluation showed that the average TRE for GPU-accelerated DIR for each of the nine patients was from 1.99 to 3.39 mm, which is lower than the voxel dimension. The total processing time for 282 pairs on an Amazon Web Services cloud consisting of 20 GPU enabled nodes took less than an hour. Beyond the original registration, the cloud resources also included automatic registration quality checks with minimal impact to timing. Clinical data were utilized in quantitative evaluations, and the results showed that the presented method holds great potential for many high-impact clinical applications in radiation oncology, including adaptive radio therapy, patient outcomes prediction, and treatment margin optimization.

IntroductionMitral annulus calcification (MAC) is a chronic, non-inflammatory, degenerative mechanism of the fibrous base of the mitral valve. While MAC was originally thought to be an age-related degenerative process, there is evidence that other mechanisms, such as atherosclerosis and abnormal calcium phosphorus metabolism, also contribute to the development of MAC.Areas coveredThis paper summarizes, existing perception of clinically valid definition of MAC and the pathophysiological processes that lead to the development of MAC and the diagnostic implications of this disease entity.Expert opinionMinimal evidence exists on the natural history and progression of MAC. Characterization of MAC progression and identification of predisposing risk factors can help to validate hypotheses. MAC is most commonly asymptomatic and incidental finding. Echocardiography is the primary imaging modality for identification and characterization of MAC and associated mitral valve (MV) disease. For patients with an indication for MV surgery, computed tomography (CT) is a complementary imaging modality for MAC. MAC is generally recognized by its characteristic density, location, and shape on echocardiography and CT, unusual variants are sometimes confused with other lesions.

Purpose: It has been 50 years since computed tomography was introduced to the worldwide neurologic medical and surgical community. In that time, tremendous advances in computer software and hardware, as well as creative changes in computerized tomographic (CT) hardware and tube technology, have dramatically improved the temporal and spatial resolution of CT. In this paper, I address what I feel are some of the most important impacts of CT in the field of clinical neuroscience over the last 50 years, as well as potential applications of CT that are on the horizon. Approach: I have recounted from literature, colleagues, and personal recollection the historical impact of CT on neuroradiology practice and what appear to be near-term future applications. Conclusions: Therapeutic applications beyond diagnosis, such as image-guided procedures, radiation, and surgical planning, and development of the field of theranostics have emerged and further increased the need for faster and more precise CT imaging. The integration of machine learning into the acquisition chain and radiologist tool kit has great implications for standardization, analysis, and diagnosis worldwide.

IntroductionMitral annulus calcification (MAC) is a chronic, non-inflammatory, degenerative mechanism of the fibrous base of the mitral valve. While MAC was originally thought to be an age-related degenerative process, there is evidence that other mechanisms, such as atherosclerosis and abnormal calcium phosphorus metabolism, also contribute to the development of MAC.Areas coveredThis paper summarizes, existing perception of clinically valid definition of MAC and the pathophysiological processes that lead to the development of MAC and the diagnostic implications of this disease entity.Expert opinionMinimal evidence exists on the natural history and progression of MAC. Characterization of MAC progression and identification of predisposing risk factors can help to validate hypotheses. MAC is most commonly asymptomatic and incidental finding. Echocardiography is the primary imaging modality for identification and characterization of MAC and associated mitral valve (MV) disease. For patients with an indication for MV surgery, computed tomography (CT) is a complementary imaging modality for MAC. MAC is generally recognized by its characteristic density, location, and shape on echocardiography and CT, unusual variants are sometimes confused with other lesions.

PurposeDomain knowledge (DK) acquired from prior studies is important for medical diagnosis. This paper leverages the population-level DK using an optimality design criterion to train a deep learning model in an end-to-end manner. In this study, the problem of interest is at the patient level to diagnose a subject with idiopathic pulmonary fibrosis (IPF) among subjects with interstitial lung disease (ILD) using a computed tomography (CT). IPF diagnosis is a complicated process with multidisciplinary discussion with experts and is subject to interobserver variability, even for experienced radiologists. To this end, we propose a new statistical method to construct a time/memory-efficient IPF diagnosis model using axial chest CT and DK, along with an optimality design criterion via a DK-enhanced loss function of deep learning.MethodsFour state-of-the-art two-dimensional convolutional neural network (2D-CNN) architectures (MobileNet, VGG16, ResNet-50, and DenseNet-121) and one baseline 2D-CNN are implemented to automatically diagnose IPF among ILD patients. Axial lung CT images are retrospectively acquired from 389 IPF patients and 700 non-IPF ILD patients in five multicenter clinical trials. To enrich the sample size and boost model performance, we sample 20 three-slice samples (triplets) from each CT scan, where these three slices are randomly selected from the top, middle, and bottom of both lungs respectively. Model performance is evaluated using a fivefold cross-validation, where each fold was stratified using a fixed proportion of IPF vs non-IPF.ResultsUsing DK-enhanced loss function increases the model performance of the baseline CNN model from 0.77 to 0.89 in terms of study-wise accuracy. Four other well-developed models reach satisfactory model performance with an overall accuracy >0.95 but the benefits brought on by the DK-enhanced loss function is not noticeable.ConclusionsWe believe this is the first attempt that (a) uses population-level DK with an optimal design criterion to train deep learning-based diagnostic models in an end-to-end manner and (b) focuses on patient-level IPF diagnosis. Further evaluation of using population-level DK on prospective studies is warranted and is underway.

While deep learning methods have demonstrated performance comparable to human readers in tasks such as computer-aided diagnosis, these models are difficult to interpret, do not incorporate prior domain knowledge, and are often considered as a "black-box." The lack of model interpretability hinders them from being fully understood by end users such as radiologists. In this paper, we present a novel interpretable deep hierarchical semantic convolutional neural network (HSCNN) to predict whether a given pulmonary nodule observed on a computed tomography (CT) scan is malignant. Our network provides two levels of output: 1) low-level semantic features; and 2) a high-level prediction of nodule malignancy. The low-level outputs reflect diagnostic features often reported by radiologists and serve to explain how the model interprets the images in an expert-interpretable manner. The information from these low-level outputs, along with the representations learned by the convolutional layers, are then combined and used to infer the high-level output. This unified architecture is trained by optimizing a global loss function including both low- and high-level tasks, thereby learning all the parameters within a joint framework. Our experimental results using the Lung Image Database Consortium (LIDC) show that the proposed method not only produces interpretable lung cancer predictions but also achieves significantly better results compared to using a 3D CNN alone.

PurposeIntertrochanteric (IT) hip fractures can be treated with sliding hip screws (SHS) or cephalomedullary nails (CMN) based on the stability of the fracture. This stability is affected by the initial impaction of the fracture which can be difficult to assess. The aim of this paper is to develop specific pre-operative computed tomography (CT) measurements of IT fractures which are predictive of post-operative shortening.MethodsA retrospective review was performed of 141 patients with AO/OTA 31A1 or 31A2 fracture patterns, who had pre-operative radiographs and CT scans, and who were treated with a SHS or a CMN. Pre-operative and post-operative imaging of IT fractures were analyzed for those fractures that shortened ≥15 mm post-fixation.Results11 fractures shortened ≥15 mm with CMN being protective of shortening (6/36 SHS versus 5/105 CMN, p = 0.0268). A novel measurement made on the pre-operative CT scan called the cortical thin point (CTP) detected differences between patients with

BackgroundSubarachnoid hemorrhage (SAH) is frequently caused by the rupture of an intracranial aneurysmal vessel or arteriovenous malformation, leading to a cascade of events that can result in severe disability or death. When evaluating for this diagnosis, emergency physicians have classically performed a noncontrast computed tomography (NCCT) scan, followed by a lumbar puncture (LP). Recently, however, as CT technology has advanced, many studies have questioned the necessity of the LP in the SAH diagnostic algorithm and have instead advocated for noninvasive techniques, such as NCCT alone or NCCT with CT angiogram (CTA).ObjectiveThe primary goal of this literature search was to determine the appropriate emergency department (ED) management of patients with suspected SAH.MethodsA MEDLINE literature search from October 2008 to June 2015 was performed using the keywords computed tomography AND subarachnoid hemorrhage AND lumbar puncture, while limiting the search to human studies written in the English language. General review articles and single case reports were omitted. Each of the selected articles then underwent a structured review.ResultsNinety-one articles were identified, with 31 papers being considered appropriate for analysis. These studies then underwent a rigorous review from which recommendations were developed.ConclusionsThe literature search supports that NCCT followed by CTA is a reasonable approach in the evaluation of ED patients with possible SAH.

BackgroundSubarachnoid hemorrhage (SAH) is frequently caused by the rupture of an intracranial aneurysmal vessel or arteriovenous malformation, leading to a cascade of events that can result in severe disability or death. When evaluating for this diagnosis, emergency physicians have classically performed a noncontrast computed tomography (NCCT) scan, followed by a lumbar puncture (LP). Recently, however, as CT technology has advanced, many studies have questioned the necessity of the LP in the SAH diagnostic algorithm and have instead advocated for noninvasive techniques, such as NCCT alone or NCCT with CT angiogram (CTA).ObjectiveThe primary goal of this literature search was to determine the appropriate emergency department (ED) management of patients with suspected SAH.MethodsA MEDLINE literature search from October 2008 to June 2015 was performed using the keywords computed tomography AND subarachnoid hemorrhage AND lumbar puncture, while limiting the search to human studies written in the English language. General review articles and single case reports were omitted. Each of the selected articles then underwent a structured review.ResultsNinety-one articles were identified, with 31 papers being considered appropriate for analysis. These studies then underwent a rigorous review from which recommendations were developed.ConclusionsThe literature search supports that NCCT followed by CTA is a reasonable approach in the evaluation of ED patients with possible SAH.

A significant proportion (estimates range from 16 to 74%) of patients with spinal cord injury (SCI) have concomitant traumatic brain injury (TBI), and the combination often produces difficulties in planning and implementing rehabilitation strategies and drug therapies. For example, many of the drugs used to treat SCI may interfere with cognitive rehabilitation, and conversely drugs that are used to control seizures in TBI patients may undermine locomotor recovery after SCI. The current paper presents an experimental animal model for combined SCI and TBI to help drive mechanistic studies of dual diagnosis. Rats received a unilateral SCI (75 kdyn) at C5 vertebral level, a unilateral TBI (2.0 mm depth, 4.0 m/s velocity impact on the forelimb sensori-motor cortex), or both SCI+TBI. TBI was placed either contralateral or ipsilateral to the SCI. Behavioral recovery was examined using paw placement in a cylinder, grooming, open field locomotion, and the IBB cereal eating test. Over 6weeks, in the paw placement test, SCI+contralateral TBI produced a profound deficit that failed to recover, but SCI+ipsilateral TBI increased the relative use of the paw on the SCI side. In the grooming test, SCI+contralateral TBI produced worse recovery than either lesion alone even though contralateral TBI alone produced no observable deficit. In the IBB forelimb test, SCI+contralateral TBI revealed a severe deficit that recovered in 3 weeks. For open field locomotion, SCI alone or in combination with TBI resulted in an initial deficit that recovered in 2 weeks. Thus, TBI and SCI affected forelimb function differently depending upon the test, reflecting different neural substrates underlying, for example, exploratory paw placement and stereotyped grooming. Concurrent SCI and TBI had significantly different effects on outcomes and recovery, depending upon laterality of the two lesions. Recovery of function after cervical SCI was retarded by the addition of a moderate TBI in the contralateral hemisphere in all tests, but forepaw placements were relatively increased by an ipsilateral TBI relative to SCI alone, perhaps due to the dual competing injuries influencing the use of both forelimbs. These findings emphasize the complexity of recovery from combined CNS injuries, and the possible role of plasticity and laterality in rehabilitation, and provide a start towards a useful preclinical model for evaluating effective therapies for combine SCI and TBI.

This paper describes a set of techniques developed for the visualization of high-resolution volume data generated from industrial computed tomography for nondestructive testing (NDT) applications. Because the data are typically noisy and contain one features, direct volume rendering methods do not always give us satisfactory results. We have coupled region growing techniques and a 2D histogram interface to facilitate volumetric feature extraction. The new interface allows the user to conveniently identify, separate or compos- ite, and compare features in the data. To lower the cost of segmentation, we show how partial region growing re- sults can suggest a reasonably good classification function for the rendering of the whole volume. The NDT applications that we work on demand visualization tasks including not only feature extraction and visual inspection, but also modeling and measurement of concealed structures in volumetric objects. An efficient filtering and modeling process for generating surface representation of extracted features is also introduced. Four CT data sets for preliminary NDT are used to demonstrate the e�ectiveness of the new visualization strategy that we have developed.