Fast rates for estimation error and oracle inequalities for model section

We consider complexity penalization methods for model selection. These methods aim to choose a model to optimally trade off estimation and approximation errors by minimizing the sum of an empirical risk term and a complexity penalty. It is well known that if we use a bound on the maximal deviation between empirical and true risks as a complexity penalty, then the risk of our choice is no more than the approximation error plus twice the complexity penalty. There are many cases, however, where complexity penalties like this give loose upper bounds on the estimation error. In particular, if we choose a function from a suitably simple convex function class with a strictly convex loss function, then the estimation error (the difference between the risk of the empirical risk minimizer and the minimal risk in the class) approaches zero at a faster rate than the maximal deviation between empirical and true risks. In this paper, we address the question of whether it is possible to design a complexity penalized model selection method for these situations. We show that, provided the sequence of models is ordered by inclusion, in these cases we can use tight upper bounds on estimation error as a complexity penalty. Surprisingly, this is the case even in situations when the difference between the empirical risk and true risk (and indeed the error of any estimate of the approximation error) decreases much more slowly than the complexity penalty. We give an oracle inequality showing that the resulting model selection method chooses a function with risk no more than the approximation error plus a constant times the complexity penalty.

Quantification of the accuracy of MRI generated 3D models of long bones compared to CT generated 3D models

Orthopaedic fracture fixation implants are increasingly being designed using accurate 3D models of long bones based on computer tomography (CT). Unlike CT, magnetic resonance imaging (MRI) does not involve ionising radiation and is therefore a desirable alternative to CT. This study aims to quantify the accuracy of MRI-based 3D models compared to CT-based 3D models of long bones. The femora of five intact cadaver ovine limbs were scanned using a 1.5T MRI and a CT scanner. Image segmentation of CT and MRI data was performed using a multi-threshold segmentation method. Reference models were generated by digitising the bone surfaces free of soft tissue with a mechanical contact scanner. The MRI- and CT-derived models were validated against the reference models. The results demonstrated that the CT-based models contained an average error of 0.15mm while the MRI-based models contained an average error of 0.23mm. Statistical validation shows that there are no significant differences between 3D models based on CT and MRI data. These results indicate that the geometric accuracy of MRI based 3D models was comparable to that of CT-based models and therefore MRI is a potential alternative to CT for generation of 3D models with high geometric accuracy.

3D reconstruction of long bones utilising magnetic resonance imaging (MRI)

The design of pre-contoured fracture fixation implants (plates and nails) that correctly fit the anatomy of a patient utilises 3D models of long bones with accurate geometric representation. 3D data is usually available from computed tomography (CT) scans of human cadavers that generally represent the above 60 year old age group. Thus, despite the fact that half of the seriously injured population comes from the 30 year age group and below, virtually no data exists from these younger age groups to inform the design of implants that optimally fit patients from these groups. Hence, relevant bone data from these age groups is required. The current gold standard for acquiring such data–CT–involves ionising radiation and cannot be used to scan healthy human volunteers. Magnetic resonance imaging (MRI) has been shown to be a potential alternative in the previous studies conducted using small bones (tarsal bones) and parts of the long bones. However, in order to use MRI effectively for 3D reconstruction of human long bones, further validations using long bones and appropriate reference standards are required. Accurate reconstruction of 3D models from CT or MRI data sets requires an accurate image segmentation method. Currently available sophisticated segmentation methods involve complex programming and mathematics that researchers are not trained to perform. Therefore, an accurate but relatively simple segmentation method is required for segmentation of CT and MRI data. Furthermore, some of the limitations of 1.5T MRI such as very long scanning times and poor contrast in articular regions can potentially be reduced by using higher field 3T MRI imaging. However, a quantification of the signal to noise ratio (SNR) gain at the bone - soft tissue interface should be performed; this is not reported in the literature. As MRI scanning of long bones has very long scanning times, the acquired images are more prone to motion artefacts due to random movements of the subject‟s limbs. One of the artefacts observed is the step artefact that is believed to occur from the random movements of the volunteer during a scan. This needs to be corrected before the models can be used for implant design. As the first aim, this study investigated two segmentation methods: intensity thresholding and Canny edge detection as accurate but simple segmentation methods for segmentation of MRI and CT data. The second aim was to investigate the usability of MRI as a radiation free imaging alternative to CT for reconstruction of 3D models of long bones. The third aim was to use 3T MRI to improve the poor contrast in articular regions and long scanning times of current MRI. The fourth and final aim was to minimise the step artefact using 3D modelling techniques. The segmentation methods were investigated using CT scans of five ovine femora. The single level thresholding was performed using a visually selected threshold level to segment the complete femur. For multilevel thresholding, multiple threshold levels calculated from the threshold selection method were used for the proximal, diaphyseal and distal regions of the femur. Canny edge detection was used by delineating the outer and inner contour of 2D images and then combining them to generate the 3D model. Models generated from these methods were compared to the reference standard generated using the mechanical contact scans of the denuded bone. The second aim was achieved using CT and MRI scans of five ovine femora and segmenting them using the multilevel threshold method. A surface geometric comparison was conducted between CT based, MRI based and reference models. To quantitatively compare the 1.5T images to the 3T MRI images, the right lower limbs of five healthy volunteers were scanned using scanners from the same manufacturer. The images obtained using the identical protocols were compared by means of SNR and contrast to noise ratio (CNR) of muscle, bone marrow and bone. In order to correct the step artefact in the final 3D models, the step was simulated in five ovine femora scanned with a 3T MRI scanner. The step was corrected using the iterative closest point (ICP) algorithm based aligning method. The present study demonstrated that the multi-threshold approach in combination with the threshold selection method can generate 3D models from long bones with an average deviation of 0.18 mm. The same was 0.24 mm of the single threshold method. There was a significant statistical difference between the accuracy of models generated by the two methods. In comparison, the Canny edge detection method generated average deviation of 0.20 mm. MRI based models exhibited 0.23 mm average deviation in comparison to the 0.18 mm average deviation of CT based models. The differences were not statistically significant. 3T MRI improved the contrast in the bone–muscle interfaces of most anatomical regions of femora and tibiae, potentially improving the inaccuracies conferred by poor contrast of the articular regions. Using the robust ICP algorithm to align the 3D surfaces, the step artefact that occurred by the volunteer moving the leg was corrected, generating errors of 0.32 ± 0.02 mm when compared with the reference standard. The study concludes that magnetic resonance imaging, together with simple multilevel thresholding segmentation, is able to produce 3D models of long bones with accurate geometric representations. The method is, therefore, a potential alternative to the current gold standard CT imaging.

A tissue engineering solution for segmental defect regeneration in load-bearing long bones

The reconstruction of large defects (>10 mm) in humans usually relies on bone graft transplantation. Limiting factors include availability of graft material, comorbidity, and insufficient integration into the damaged bone. We compare the gold standard autograft with biodegradable composite scaffolds consisting of medical-grade polycaprolactone and tricalcium phosphate combined with autologous bone marrow-derived mesenchymal stem cells (MSCs) or recombinant human bone morphogenetic protein 7 (rhBMP-7). Critical-sized defects in sheep - a model closely resembling human bone formation and structure - were treated with autograft, rhBMP-7, or MSCs. Bridging was observed within 3 months for both the autograft and the rhBMP-7 treatment. After 12 months, biomechanical analysis and microcomputed tomography imaging showed significantly greater bone formation and superior strength for the biomaterial scaffolds loaded with rhBMP-7 compared to the autograft. Axial bone distribution was greater at the interfaces. With rhBMP-7, at 3 months, the radial bone distribution within the scaffolds was homogeneous. At 12 months, however, significantly more bone was found in the scaffold architecture, indicating bone remodeling. Scaffolds alone or with MSC inclusion did not induce levels of bone formation comparable to those of the autograft and rhBMP-7 groups. Applied clinically, this approach using rhBMP-7 could overcome autograft-associated limitations.

Correction of step artefact associated with MRI scanning of long bones

3D models of long bones are being utilised for a number of fields including orthopaedic implant design. Accurate reconstruction of 3D models is of utmost importance to design accurate implants to allow achieving a good alignment between two bone fragments. Thus for this purpose, CT scanners are employed to acquire accurate bone data exposing an individual to a high amount of ionising radiation. Magnetic resonance imaging (MRI) has been shown to be a potential alternative to computed tomography (CT) for scanning of volunteers for 3D reconstruction of long bones, essentially avoiding the high radiation dose from CT. In MRI imaging of long bones, the artefacts due to random movements of the skeletal system create challenges for researchers as they generate inaccuracies in the 3D models generated by using data sets containing such artefacts. One of the defects that have been observed during an initial study is the lateral shift artefact occurring in the reconstructed 3D models. This artefact is believed to result from volunteers moving the leg during two successive scanning stages (the lower limb has to be scanned in at least five stages due to the limited scanning length of the scanner). As this artefact creates inaccuracies in the implants designed using these models, it needs to be corrected before the application of 3D models to implant design. Therefore, this study aimed to correct the lateral shift artefact using 3D modelling techniques. The femora of five ovine hind limbs were scanned with a 3T MRI scanner using a 3D vibe based protocol. The scanning was conducted in two halves, while maintaining a good overlap between them. A lateral shift was generated by moving the limb several millimetres between two scanning stages. The 3D models were reconstructed using a multi threshold segmentation method. The correction of the artefact was achieved by aligning the two halves using the robust iterative closest point (ICP) algorithm, with the help of the overlapping region between the two. The models with the corrected artefact were compared with the reference model generated by CT scanning of the same sample. The results indicate that the correction of the artefact was achieved with an average deviation of 0.32 ± 0.02 mm between the corrected model and the reference model. In comparison, the model obtained from a single MRI scan generated an average error of 0.25 ± 0.02 mm when compared with the reference model. An average deviation of 0.34 ± 0.04 mm was seen when the models generated after the table was moved were compared to the reference models; thus, the movement of the table is also a contributing factor to the motion artefacts.

Anatomical MR imaging of long bones : comparative performance of MRI at 1.5 T and 3 T

The current gold standard for the design of orthopaedic implants is 3D models of long bones obtained using computed tomography (CT). However, high-resolution CT imaging involves high radiation exposure, which limits its use in healthy human volunteers. Magnetic resonance imaging (MRI) is an attractive alternative for the scanning of healthy human volunteers for research purposes. Current limitations of MRI include difficulties of tissue segmentation within joints and long scanning times. In this work, we explore the possibility of overcoming these limitations through the use of MRI scanners operating at a higher field strength. We quantitatively compare the quality of anatomical MR images of long bones obtained at 1.5 T and 3 T and optimise the scanning protocol of 3 T MRI. FLASH images of the right leg of five human volunteers acquired at 1.5 T and 3 T were compared in terms of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). The comparison showed a relatively high CNR and SNR at 3 T for most regions of the femur and tibia, with the exception of the distal diaphyseal region of the femur and the mid diaphyseal region of the tibia. This was accompanied by an ~65% increase in the longitudinal spin relaxation time (T1) of the muscle at 3 T compared to 1.5 T. The results suggest that MRI at 3 T may be able to enhance the segmentability and potentially improve the accuracy of 3D anatomical models of long bones, compared to 1.5 T. We discuss how the total imaging times at 3 T can be kept short while maximising the CNR and SNR of the images obtained.

Gene silencing: Fleshing out the bones

Genetic studies are revealing the pathway for RNA-mediated gene silencing. Short RNA molecules are the key, giving sequence specificity for RNA degradation and mediating communication within and between cells; these short RNAs are common to transcriptional and post-transcriptional silencing pathways. The expression of transgenes in plants varies between independent transformants and there are many examples where the transgenic trait is not expressed, or disappears in subsequent generations, despite the presence of the transgene. This loss of a trait, but not of the transgene, has become known as gene silencing and can take two forms, transcriptional or post-transcriptional. As their names imply, transcriptional gene silencing occurs when a transgene is not transcribed, whereas in post-transcriptional gene silencing, the transgene mRNA is produced but degraded before it is translated (reviewed in [1]). Both forms of silencing seem to be the result of inherent mechanisms for protecting plants against mobile or invading DNA — for example, transposable elements or the T-DNA of Agrobacterium — or RNA viruses. Plants are not alone in their capacity for transgene silencing; both forms of silencing occur in flies and fungi, where it is known as RIP or quelling, while nematodes exhibit post-transcriptional silencing, generally referred to as RNA interference (RNAi). A clearer picture of the mechanisms and relationships of the different types of transgene silencing is beginning to emerge from a number of recent studies [2], [3], [4], [5], [6], [7] and [8]. Some of these studies [2], [3], [4] and [5] have enhanced our understanding of the steps within the post-transcriptional silencing pathway, and others [6], [7] and [8] have demonstrated that the two forms of silencing may be mechanistically linked.

Myeloma-induced alloreactive T cells arising in myeloma-infiltrated bones include double-positive CD8+CD4+ T cells : evidence from myeloma-bearing mouse model

The graft-versus-myeloma (GVM) effect represents a powerful form of immune attack exerted by alloreactive T cells against multiple myeloma cells, which leads to clinical responses in multiple myeloma transplant recipients. Whether myeloma cells are themselves able to induce alloreactive T cells capable of the GVM effect is not defined. Using adoptive transfer of T naive cells into myeloma-bearing mice (established by transplantation of human RPMI8226-TGL myeloma cells into CD122(+) cell-depleted NOD/SCID hosts), we found that myeloma cells induced alloreactive T cells that suppressed myeloma growth and prolonged survival of T cell recipients. Myeloma-induced alloreactive T cells arising in the myeloma-infiltrated bones exerted cytotoxic activity against resident myeloma cells, but limited activity against control myeloma cells obtained from myeloma-bearing mice that did not receive T naive cells. These myeloma-induced alloreactive T cells were derived through multiple CD8(+) T cell divisions and enriched in double-positive (DP) T cells coexpressing the CD8alphaalpha and CD4 coreceptors. MHC class I expression on myeloma cells and contact with T cells were required for CD8(+) T cell divisions and DP-T cell development. DP-T cells present in myeloma-infiltrated bones contained a higher proportion of cells expressing cytotoxic mediators IFN-gamma and/or perforin compared with single-positive CD8(+) T cells, acquired the capacity to degranulate as measured by CD107 expression, and contributed to an elevated perforin level seen in the myeloma-infiltrated bones. These observations suggest that myeloma-induced alloreactive T cells arising in myeloma-infiltrated bones are enriched with DP-T cells equipped with cytotoxic effector functions that are likely to be involved in the GVM effect.