Stent grafting of acute hepatic artery bleeding following pancreatic head resection

The purpose of this study was to report the potential of hepatic artery stent grafting in cases of acute hemorrhage of the gastroduodenal artery stump following pancreatic head resection. Five consecutive male patients were treated because of acute, life-threatening massive bleeding. Instead of re-operation, emergency angiography, with the potential of endovascular treatment, was performed. Because of bleeding from the hepatic artery, a stent graft (with the over-the-wire or monorail technique) was implanted to control the hemmorhage by preserving patency of the artery. The outcome was evaluated. In all cases, the hepatic artery stent grafting was successfully performed, and the bleeding was immediately stopped. Clinically, immediately after the procedure, there was an obvious improvement in the general patient condition. There were no immediate procedure-related complications. Completion angiography (n=5) demonstrated control of the hemorrhage and patency of the hepatic artery and the stent graft. Although all patients recovered hemodynamically, three individuals died 2 to 10 days after the procedure. The remaining two patients survived, without the need for re-operation. Transluminal stent graft placement in the hepatic artery is a safe and technically feasible solution to control life-threatening bleeding of the gastroduodenal artery stump.

Comparison of six radiographic projections to assess femoral head/neck asphericity

Early radiographic detection of femoroacetabular impingement might prevent initiation and progression of osteoarthritis. The structural abnormality in femoral-induced femoroacetabular impingement (cam type) is frequently asphericity at the anterosuperior head/neck contour. To determine which of six radiographic projections (anteroposterior, Dunn, Dunn/45 degrees flexion, cross-table/15 degrees internal rotation, cross-table/neutral rotation, and cross-table/15 degrees external rotation) best identifies femoral head/neck asphericity, we studied 21 desiccated femurs; 11 with an aspherical femoral head/neck contour and 10 with a spherical femoral head/neck contour. To radiographically quantify femoral head asphericity, we measured the angle where the femoral head/neck leaves sphericity (angle alpha). The aspherical femoral head/neck contours had a greater maximum angle alpha (70 degrees ) compared with the spherical head/neck contours (50 degrees ). The angle alpha varied depending on the radiographic projection: it was greatest in the Dunn view with 45 degrees hip flexion (71 degrees +/- 10 degrees ) and least in the cross-table view in 15 degrees external rotation (51 degrees +/- 7 degrees ). Diagnosis of a pathologic femoral head/neck contour depends on the radiologic projection. The Dunn view in 45 degrees or 90 degrees flexion or a cross-table projection in internal rotation best show femoral head/neck asphericity, whereas anteroposterior or externally rotated cross-table views are likely to miss asphericity. Level of Evidence: Prognostic study, level II-1 (retrospective study).

Effects of glenoid component version on humeral head displacement and joint reaction forces: an experimental study

The purpose of this study was to determine whether changes in glenoid version are associated with humeral head displacement and changes in the joint reaction forces, as these might contribute to instability or loosening in total shoulder replacement. A total shoulder prosthesis was implanted in neutral version in 6 cadaveric shoulders. Glenoid version was then changed in steps of 4 degrees toward more anteversion and retroversion. An increase in anteversion resulted in anterior translation of the humeral head and in eccentric loading of the anterior part of the glenoid. Retroversion was associated with posterior displacement and posterior loading of the glenoid. A change in rotation of the humeral component did not compensate for altered version of the glenoid component. These results suggest that both instability and glenoid component loosening may be related to the version of the glenoid component. Therefore, assessment of loosening and instability justifies precise assessment of glenoid component version.

Prospective navigator-echo-based real-time triggering of fetal head movement for the reduction of artifacts

The purpose of this study was to evaluate the neuroimaging quality and accuracy of prospective real-time navigator-echo acquisition correction versus untriggered intrauterine magnetic resonance imaging (MRI) techniques. Twenty women in whom fetal motion artifacts compromised the neuroimaging quality of fetal MRI taken during the 28.7 +/- 4 week of pregnancy below diagnostic levels were additionally investigated using a navigator-triggered half-Fourier acquired single-shot turbo-spin echo (HASTE) sequence. Imaging quality was evaluated by two blinded readers applying a rating scale from 1 (not diagnostic) to 5 (excellent). Diagnostic criteria included depiction of the germinal matrix, grey and white matter, CSF, brain stem and cerebellum. Signal-difference-to-noise ratios (SDNRs) in the white matter and germinal zone were quantitatively evaluated. Imaging quality improved in 18/20 patients using the navigator echo technique (2.4 +/- 0.58 vs. 3.65 +/- 0.73 SD, p < 0.01 for all evaluation criteria). In 2/20 patients fetal movement severely impaired image quality in conventional and navigated HASTE. Navigator-echo imaging revealed additional structural brain abnormalities and confirmed diagnosis in 8/20 patients. The accuracy improved from 50% to 90%. Average SDNR increased from 0.7 +/- 7.27 to 19.83 +/- 15.71 (p < 0.01). Navigator-echo-based real-time triggering of fetal head movement is a reliable technique that can deliver diagnostic fetal MR image quality despite vigorous fetal movement.

Online correlation of spontaneous arterial and intracranial pressure fluctuations in patients with diffuse severe head injury

Determination of relevant clinical monitoring parameters for helping guide the intensive care therapy in patients with severe head injury, is one of the most demanding issues in neurotrauma research. New insights into cerebral autoregulation and metabolism have revealed that a rigid cerebral perfusion pressure (CPP) regimen might not be suitable for all severe head injured patients. We thus developed an online analysis technique to monitor the correlation (AI rho) between the spontaneous fluctuations of the mean arterial blood pressure (MABP) and the intracranial pressure (ICP). In addition, brain tissue oxygen (PtiO2) and metabolic microdialysate measures including glucose and lactate were registered. We found that in patients with good outcome, the AI rho values were significantly lower as compared with patients with poor outcome. Accordingly, microdialysate glucose and lactate were significantly higher in the good outcome group. We conclude that online determination of AI rho offers a valuable additional and technically easily performable tool for guidance of therapy in patients with severe head injury.

Automatic extraction of femur contours from calibrated fluoroscopic images

Automatic identification and extraction of bone contours from X-ray images is an essential first step task for further medical image analysis. In this paper we propose a 3D statistical model based framework for the proximal femur contour extraction from calibrated X-ray images. The automatic initialization is solved by an estimation of Bayesian network algorithm to fit a multiple component geometrical model to the X-ray data. The contour extraction is accomplished by a non-rigid 2D/3D registration between a 3D statistical model and the X-ray images, in which bone contours are extracted by a graphical model based Bayesian inference. Preliminary experiments on clinical data sets verified its validity

Accurate and robust reconstruction of proximal femur from sparse intraoperative data and dense point distribution model for surgical navigation

Constructing a 3D surface model from sparse-point data is a nontrivial task. Here, we report an accurate and robust approach for reconstructing a surface model of the proximal femur from sparse-point data and a dense-point distribution model (DPDM). The problem is formulated as a three-stage optimal estimation process. The first stage, affine registration, is to iteratively estimate a scale and a rigid transformation between the mean surface model of the DPDM and the sparse input points. The estimation results of the first stage are used to establish point correspondences for the second stage, statistical instantiation, which stably instantiates a surface model from the DPDM using a statistical approach. This surface model is then fed to the third stage, kernel-based deformation, which further refines the surface model. Handling outliers is achieved by consistently employing the least trimmed squares (LTS) approach with a roughly estimated outlier rate in all three stages. If an optimal value of the outlier rate is preferred, we propose a hypothesis testing procedure to automatically estimate it. We present here our validations using four experiments, which include 1 leave-one-out experiment, 2 experiment on evaluating the present approach for handling pathology, 3 experiment on evaluating the present approach for handling outliers, and 4 experiment on reconstructing surface models of seven dry cadaver femurs using clinically relevant data without noise and with noise added. Our validation results demonstrate the robust performance of the present approach in handling outliers, pathology, and noise. An average 95-percentile error of 1.7-2.3 mm was found when the present approach was used to reconstruct surface models of the cadaver femurs from sparse-point data with noise added.

An integrated approach for reconstructing surface models of the proximal femur from sparse input data for surgical navigation

A patient-specific surface model of the proximal femur plays an important role in planning and supporting various computer-assisted surgical procedures including total hip replacement, hip resurfacing, and osteotomy of the proximal femur. The common approach to derive 3D models of the proximal femur is to use imaging techniques such as computed tomography (CT) or magnetic resonance imaging (MRI). However, the high logistic effort, the extra radiation (CT-imaging), and the large quantity of data to be acquired and processed make them less functional. In this paper, we present an integrated approach using a multi-level point distribution model (ML-PDM) to reconstruct a patient-specific model of the proximal femur from intra-operatively available sparse data. Results of experiments performed on dry cadaveric bones using dozens of 3D points are presented, as well as experiments using a limited number of 2D X-ray images, which demonstrate promising accuracy of the present approach.