An Automated Liver Vasculature Segmentation from CT Scans for Hepatic Surgical Planning

Liver vasculature segmentation is a crucial step for liver surgical planning. Segmentation of liver vasculature is an important part of the 3D visualisation of the liver anatomy. The spatial relationship between vessels and other liver structures, like tumors and liver anatomic segments, helps in reducing the surgical treatment risks. However, liver vessels segmentation is a challenging task, that is due to low contrast with neighboring parenchyma, the complex anatomy, the very thin branches and very small vessels. This paper introduces a fully automated framework consist of four steps to segment the vessels inside the liver organ. Firstly, in the preprocessing step, a combination of two filtering techniques are used to extract and enhance vessels inside the liver region, first the vesselness filter is used to extract the vessels structure, and then the anisotropic coherence enhancing diffusion (CED) filter is used to enhance the intensity within the tubular vessels structure. This step is followed by a smart multiple thresholding to extract the initial vasculature segmentation. The liver vasculature structures, including hepatic veins connected to the inferior vena cava and the portal veins, are extracted. Finally, the inferior vena cava is segmented and excluded from the vessels segmentation, as it is not considered as part of the liver vasculature structure. The liver vessel segmentation method is validated on the publically available 3DIRCAD datasets. Dice coefficient (DSC) is used to evaluate the method, the average DSC score achieved a score 68.5%. The proposed approach succeeded to segment liver vasculature from the liver envelope accurately, which makes it as potential tool for clinical preoperative planning

Development of a 4D digital phantom for Cone-Beam CT (CBCT) imaging on the Varian On-Board Imager (OBI)

Mitigating effects of respiratory motion during image guided radiotherapy (IGRT) is important especially during thoracic and abdomen scanning protocols such as cone-beam CT (CBCT) imaging. However, the lack of ‘ground-truth’ in validating new algorithms has always been a challenge. The objective of this study is to outline the development of a novel 4D digital phantom for simulation of respiratory motion effects during CBCT image reconstruction based on Varian On-Board Imager (OBI): Half-Fan (HF) operating mode geometry. A set of actual 4D Magnetic Resonance (MR) data was used to develop the digital phantom. Firstly, the MR data sequencewasextendedto mimic a standard CBCT imaging acquisition protocol. Then, the images were segmented into several organs of interest and assigned with respective CT attenuation values. Subsequently, 2D projections of the developed digital phantom were simulated using the Varian OBI geometry. A Poisson noise model was also incorporated to the projection data to realistically simulate quantum noise that is present in an actual clinical environment. Three types of projections were then reconstructed using the standard 3D Feldkamp-Davis-Kress (FDK) algorithm, projections: without noise, with noise, and with noise and reconstructed with an additional Hann filter. As validation, the reconstructed images were compared against a single-frame of the developed phantom; quantitatively, using normalized root mean squared error (NRMSE) and qualitatively, using difference images. The results indicated that the phantom managed to display a consistent trend in modeling the effects of respiratory motion on the reconstructed images. On average, the NRMSE values for all three reconstructed images within the entire field-of-view (FOV) were evaluated to be approximately 29.07±0.22%. Nonetheless, the difference images indicated a large error in areas largely affected by respiratory motion. The NRMSE of a region-of-interest (ROI) near the affected area was evaluated as 51.26% that constitute to a significant +22.19% difference

Lupus Anticoagulunt Associated with Transient Severe Factor X Deficiency: A Report of Two Patients Presenting with Major Bleeding Complications

Abstract Acquired factor X (FX) deficiency is rare, but has been reported in diverse disease states, including systemic amyloidosis and respiratory infections. FX deficiency associated with lupus anticoagulant (LA) and a bleeding diathesis has not been previously reported. We report two patients both of whom presented with a severe bleeding diathesis after a preceding respiratory infection due to isolated FX deficiency associated with a LA. The FX deficiency and LA were transient. We conclude that patients with LA may rarely present with severe acquired FX deficiency. This may be another mechanism whereby patients with antiphospholipid antibodies present with bleeding complications

AUTOMATIC LIVER SEGMENTATION FROM CT SCANS USING INTENSITY ANALYSIS AND LEVEL-SET ACTIVE CONTOURS

Liver segmentation from CT scans is still a challenging task due to the liver characteristics in terms of shape and intensity variability. In this work, we propose an automatic segmentation method of the liver from CT data sets. The framework consists of three main steps: liver shape model localization, liver intensity range estimation and localized active contouring. We proposed an adaptive multiple thresholding technique to estimate the range of the liver intensities. First, multiple thresholding is used to extract the dense tissue from the whole CT scan. A localization step is then used to find the approximate location of the liver in the CT scan, to localize a constructed mean liver shape model. A liver intensity-range estimation step is then applied within the localized shape model ROI. The localized shape model and the estimated liver intensity range are used to build the initial mask. A level set based active contour algorithm is used to deform the initial mask to the liver boundaries in the CT scan. The proposed method was evaluated on two public data sets: SLIVER07 and 3D-IRCAD. The experiments showed that the proposed method is able to segment to liver in all CT scans in the two data sets accurately

Evaluation Methodology for Respiratory Signal Extraction from Clinical Cone-Beam CT (CBCT) using Data-Driven Methods

The absence of a ground truth for internal motion in clinical studies has always been a challenge to evaluate developed methods to extract respiratory motion especially during a 60-second cone-beam CT (CBCT) scan in Image-Guided Radiotherapy Treatment (IGRT). The unavailability of a gold standard has led this study to present a methodology to manually track respiratory motion on a clinically acquired CBCT projection data set over a 360° view angle. The tracked signal is then used as a reference to assess the performance of four data-driven methods in respiratory motion extraction, namely: the Amsterdam Shroud (AS), Local Principal Component Analysis (LPCA), Intensity Analysis (IA), and Fourier Transform (FT)-based methods that do not require additional equipment nor protocol to the existing treatment delivery. The assessment using this reference signal includes both quantitative and qualitative analysis. It is found out quantitatively that all four methods managed to extract respiratory signals that are highly correlated with the reference signal, with the LPCA method displaying the highest correlation coefficient value at 0.9108. Furthermore, the normalized root-mean-squared amplitude error of detected peaks and troughs within the signal from the LPCA method is also lowest at 1.6529 % compared to the other methods. This result is further supported by qualitative analysis via visual inspection of each extracted signal plotted with the reference signal on the same axes

Strengthening programming skills among engineering students through experiential learning based robotics project

This study examined the educational effects in strengthening programming skills among university’s undergraduate engineering students via integration of a robotics project and an experiential learning approach. In this study, a robotics project was conducted to close the gap of students’ difficulty in relating the theoretical concepts of programming and real-world problems. Hence, an experiential learning approach using the Kolb model was proposed to investigate the problem. In this project, students were split into groups whereby they were asked to develop codes for controlling the navigation of a wheeled mobile robot. They were responsible for managing their group’s activities, conducting laboratory tests, producing technical reports and preparing a video presentation. The statistical analysis performed on the students’ summative assessments of a programming course revealed a remarkable improvement in their problem-solving skills and ability to provide programming solutions to a real-world problem

Femoral Neuropathy due to Iliacus Muscle Hematoma in a Patient on Warfarin Therapy

Spontaneous hematomas of the iliacus muscle are rare lesions and these are seen in individuals receiving anticoagulation therapy or patients with blood dyscrasias such as hemophilia. It can cause femoral neuropathy and resultant pain and paralysis. Although there is no clear consensus for the treatment of femoral neuropathy from iliacus muscle hematomas, delays in the surgical evacuation of hematoma for decompression of the femoral nerve can lead to a prolonged or permanent disability. We report here on a rare case of a spontaneous iliacus muscle hematoma that caused femoral neuropathy in a patient who was taking warfarin for occlusive vascular disease and we discuss the treatment

Case Report Monoclonal Gammopathy of Undetermined Significance (MGUS) in a Man with Fragile X-associated Tremor/Ataxia Syndrome

We report the clinical presentation and laboratory findings of a 69-year-old man with fragile X-associated tremor ataxia syndrome (FXTAS), a progressive neurodegenerative disorder, who was noted to have monoclonal gammopathy of undetermined significance (MGUS), a plasma cell proliferative disorder and a precursor disease of multiple myeloma. Both MGUS and FXTAS are associated with microRNA (miRNA) dysregulation. We speculate that individuals with FXTAS may be predisposed to MGUS and further studies are warranted regarding this association

Septic arthritis in males with haemophilia

We used data collected as part of the Universal Data Collection (UDC) surveillance project in haemophilia treatment centers (HTC) to study the incidence, risk factors, and impact of septic arthritis among males with haemophilia. Patients participating in UDC on 2 or more occasions were included. Cases were defined as patients with documented joint infection. Characteristics of the cases were compared with those of haemophilia patients without infection. Among the 8026 eligible patients with 36,015 person-years of follow-up, 30 (0.37%) had a documented joint infection (incidence rate 83 per 100,000 person-years). In a logistic regression model, only increasing age (OR = 6.1 for age ≥30), race/ethnicity other than white (OR = 3.9), presence of inhibitor (OR = 3.9), invasive procedure in the past year (OR = 2.7) and presence of one or more target joints (OR = 3.2) remained statistically significant. CVAD use and HCV and HIV infection were not associated with septic arthritis risk after adjusting for potential confounders. Study limitations include possible underestimation of septic arthritis rate in this population and its retrospective design. We conclude that septic arthritis is an uncommon complication of haemophilia occurring primarily in joints most affected by bleeding and reparative surgical interventions