Intraoperative fabrication of patient-specific moulded implants for skull reconstruction: single-centre experience of 28 cases

BACKGROUND Intraoperatively fabricated polymethylmethacrylate (PMMA) implants based on computer-designed moulds were used to improve cosmetic results after hard tissue replacement. To assess the implant's cosmetic and functional results we performed both subjective and objective assessments. METHODS This retrospective analysis was performed using a cohort of 28 patients who received PMMA implants between February 2009 and March 2012. The cosmetic and functional results were assessed using a patient questionnaire. Furthermore an objective volumetric subtraction score (0-100) was applied and implant thickness, as well as gaps and tiers, were measured. RESULTS Patients mainly judged their cosmetic result as "good". Two of the 28 patients found their cosmetic result unfavourable. The functional result and stability was mainly judged to be good. Measurements of implant thickness showed a very high correlation with the thickness of the contralateral bone. Volumetric subtraction led to a median quality of 80 on a scale from 0 to 100. Median gaps around the margins of the implant were 1.5 mm parietally, 1.7 mm frontally and 3.5 mm fronto-orbitally, and median tiers were 1.2 mm, 0 mm and 0 mm respectively. The overall rate of surgical revisions was 10.7 % (three patients). Two patients suffered from wound healing disturbances (7.1 %). The overall complication rate was comparable to other reports in the literature. CONCLUSIONS Implantation of intraoperatively fabricated patient-specific moulded implants is a cost-effective and safe technique leading to good clinical results with a low complication rate.

Patient-Specific Semi-Supervised Learning for Postoperative Brain Tumor Segmentation

In contrast to preoperative brain tumor segmentation, the problem of postoperative brain tumor segmentation has been rarely approached so far. We present a fully-automatic segmentation method using multimodal magnetic resonance image data and patient-specific semi-supervised learning. The idea behind our semi-supervised approach is to effectively fuse information from both pre- and postoperative image data of the same patient to improve segmentation of the postoperative image. We pose image segmentation as a classification problem and solve it by adopting a semi-supervised decision forest. The method is evaluated on a cohort of 10 high-grade glioma patients, with segmentation performance and computation time comparable or superior to a state-of-the-art brain tumor segmentation method. Moreover, our results confirm that the inclusion of preoperative MR images lead to a better performance regarding postoperative brain tumor segmentation.

AN EVALUATION OF THE CONSISTENCY OF IMRT PATIENT-SPECIFIC QA TECHNIQUES

To ensure the integrity of an intensity modulated radiation therapy (IMRT) treatment, each plan must be validated through a measurement-based quality assurance (QA) procedure, known as patient specific IMRT QA. Many methods of measurement and analysis have evolved for this QA. There is not a standard among clinical institutions, and many devices and action levels are used. Since the acceptance criteria determines if the dosimetric tools’ output passes the patient plan, it is important to see how these parameters influence the performance of the QA device. While analyzing the results of IMRT QA, it is important to understand the variability in the measurements. Due to the different form factors of the many QA methods, this reproducibility can be device dependent. These questions of patient-specific IMRT QA reproducibility and performance were investigated across five dosimeter systems: a helical diode array, radiographic film, ion chamber, diode array (AP field-by-field, AP composite, and rotational composite), and an in-house designed multiple ion chamber phantom. The reproducibility was gauged for each device by comparing the coefficients of variation (CV) across six patient plans. The performance of each device was determined by comparing each one’s ability to accurately label a plan as acceptable or unacceptable compared to a gold standard. All methods demonstrated a CV of less than 4%. Film proved to have the highest variability in QA measurement, likely due to the high level of user involvement in the readout and analysis. This is further shown by how the setup contributed more variation than the readout and analysis for all of the methods, except film. When evaluated for ability to correctly label acceptable and unacceptable plans, two distinct performance groups emerged with the helical diode array, AP composite diode array, film, and ion chamber in the better group; and the rotational composite and AP field-by-field diode array in the poorer group. Additionally, optimal threshold cutoffs were determined for each of the dosimetry systems. These findings, combined with practical considerations for factors such as labor and cost, can aid a clinic in its choice of an effective and safe patient-specific IMRT QA implementation.

Quantitative evaluation of patient-specific conforming hexahedral meshes of abdominal aortic aneurysms and intraluminal thrombus generated from MRI

A novel method for generating patient-specific high quality conforming hexahedral meshes is presented. The meshes are directly obtained from the segmentation of patient magnetic resonance (MR) images of abdominal aortic aneu-rysms (AAA). The MRI permits distinguishing between struc-tures of interest in soft tissue. Being so, the contours of the lumen, the aortic wall and the intraluminal thrombus (ILT) are available and thus the meshes represent the actual anato-my of the patient?s aneurysm, including the layered morpholo-gies of these structures. Most AAAs are located in the lower part of the aorta and the upper section of the iliac arteries, where the inherent tortuosity of the anatomy and the presence of the ILT makes the generation of high-quality elements at the bifurcation is a challenging task. In this work we propose a novel approach for building quadrilateral meshes for each surface of the sectioned geometry, and generating conforming hexahedral meshes by combining the quadrilateral meshes. Conforming hexahedral meshes are created for the wall and the ILT. The resulting elements are evaluated on four patients? datasets using the Scaled Jacobian metric. Hexahedral meshes of 25,000 elements with 94.8% of elements well-suited for FE analysis are generated.

High-quality conforming hexahedral meshes of patient-specific abdominal aortic aneurysms including their intraluminal thrombi

In order to perform finite element (FE) analyses of patient-specific abdominal aortic aneurysms, geometries derived from medical images must be meshed with suitable elements. We propose a semi-automatic method for generating conforming hexahedral meshes directly from contours segmented from medical images. Magnetic resonance images are generated using a protocol developed to give the abdominal aorta high contrast against the surrounding soft tissue. These data allow us to distinguish between the different structures of interest. We build novel quadrilateral meshes for each surface of the sectioned geometry and generate conforming hexahedral meshes by combining the quadrilateral meshes. The three-layered morphology of both the arterial wall and thrombus is incorporated using parameters determined from experiments. We demonstrate the quality of our patient-specific meshes using the element Scaled Jacobian. The method efficiently generates high-quality elements suitable for FE analysis, even in the bifurcation region of the aorta into the iliac arteries. For example, hexahedral meshes of up to 125,000 elements are generated in less than 130 s, with 94.8 % of elements well suited for FE analysis. We provide novel input for simulations by independently meshing both the arterial wall and intraluminal thrombus of the aneurysm, and their respective layered morphologies.

Insights from Native American Veterans on Developing a Patient-Centered, Integrative Model for Mental Health Services

Thesis (Master's)--University of Washington, 2016-06

A study of patient-specific prognosis of ovarian cancer

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