L.C. Derikx

Spatial Remapping of Cortico-striatal Connectivity in Parkinson's Disease

Parkinsons disease (PD) is characterized by striatal dopamine depletion, especially in the posterior putamen. The dense connectivity profile of the striatum suggests that these local impairments may propagate throughout the whole cortico-striatal network. Here we test the effect of striatal dopamine depletion on cortico-striatal network properties by comparing the functional connectivity profile of the posterior putamen, the anterior putamen, and the caudate nucleus between 41 PD patients and 36 matched controls. We used multiple regression analyses of resting-state functional magnetic resonance imaging data to quantify functional connectivity across different networks. Each region had a distinct connectivity profile that was similarly expressed in patients and controls: the posterior putamen was uniquely coupled to cortical motor areas, the anterior putamen to the pre-supplementary motor area and anterior cingulate cortex, and the caudate nucleus to the dorsal prefrontal cortex. Differences between groups were specific to the putamen: although PD patients showed decreased coupling between the posterior putamen and the inferior parietal cortex, this region showed increased functional connectivity with the anterior putamen. We conclude that dopamine depletion in PD leads to a remapping of cerebral connectivity that reduces the spatial segregation between different cortico-striatal loops. These alterations of network properties may underlie abnormal sensorimotor integration in PD.

The assessment of the risk of fracture in femora with metastatic lesions: Comparing case-specific finite element analyses with predictions by clinical experts

Previously, we showed that case-specific non-linear finite element (FE) models are better at predicting the load to failure of metastatic femora than experienced clinicians. In this study we improved our FE modelling and increased the number of femora and characteristics of the lesions. We retested the robustness of the FE predictions and assessed why clinicians have difficulty in estimating the load to failure of metastatic femora. A total of 20 femora with and without artificial metastases were mechanically loaded until failure. These experiments were simulated using case-specific FE models. Six clinicians ranked the femora on load to failure and reported their ranking strategies. The experimental load to failure for intact and metastatic femora was well predicted by the FE models (R(2) = 0.90 and R(2) = 0.93, respectively). Ranking metastatic femora on load to failure was well performed by the FE models (τ = 0.87), but not by the clinicians (0.11 < τ < 0.42). Both the FE models and the clinicians allowed for the characteristics of the lesions, but only the FE models incorporated the initial bone strength, which is essential for accurately predicting the risk of fracture. Accurate prediction of the risk of fracture should be made possible for clinicians by further developing FE models.

Finite element analysis and CT-based structural rigidity analysis to assess failure load in bones with simulated lytic defects

There is an urgent need to improve the prediction of fracture risk for cancer patients with bone metastases. Pathological fractures that result from these tumors frequently occur in the femur. It is extremely difficult to determine the fracture risk even for experienced physicians. Although evolving, fracture risk assessment is still based on inaccurate predictors estimated from previous retrospective studies. As a result, many patients are surgically over-treated, whereas other patients may fracture their bones against expectations. We mechanically tested ten pairs of human cadaveric femurs to failure, where one of each pair had an artificial defect simulating typical metastatic lesions. Prior to testing, finite element (FE) models were generated and computed tomography rigidity analysis (CTRA) was performed to obtain axial and bending rigidity measurements. We compared the two techniques on their capacity to assess femoral failure load by using linear regression techniques, Students t-tests, the Bland-Altman methodology and Kendall rank correlation coefficients. The simulated FE failure loads and CTRA predictions showed good correlation with values obtained from the experimental mechanical testing. Kendall rank correlation coefficients between the FE rankings and the CTRA rankings showed moderate to good correlations. No significant differences in prediction accuracy were found between the two methods. Non-invasive fracture risk assessment techniques currently developed both correlated well with actual failure loads in mechanical testing suggesting that both methods could be further developed into a tool that can be used in clinical practice. The results in this study showed slight differences between the methods, yet validation in prospective patient studies should confirm these preliminary findings.

Limited short-term effect of palliative radiation therapy on quantitative computed tomography-derived bone mineral density in femora with metastases

Purpose The aim of this study was to determine the effect of single fraction (SF) and multiple fraction (MF) radiation therapy (RT) on bone mineral density (BMD) in patients with cancer and bone metastases in the proximal femur. We studied this effect in the radiation field and within metastatic lesions, and differentiated between lytic, blastic, and mixed lesions. Methods and materials This prospective cohort study comprised 42 patients with painful bone metastases, including 47 irradiated femora with 52 metastatic lesions in the proximal femur. Patients received either 8 Gy SF or 20 to 24 Gy in 5 to 6 fractions (MF). Quantitative computed tomography scans were obtained before RT and 4 and 10 weeks after the initial scan. Patients who received MF additionally underwent quantitative computed tomography on the final day of their treatment. Automated image registration was performed. Mean BMD was determined at each time point for each proximal femur (region of interest [ROI]-PF) and in greater detail for a region of interest that contained the metastatic lesion (ROI-ML). Statistical analysis was performed using linear mixed models. Results No significant differences in mean BMD were found between SF or MF RT over all time points in both ROI-PF and ROI-ML. Mean BMD did not change in ROI-PF with lytic and mixed lesions, but mean BMD in ROI-PF with blastic lesions increased to 109%. Comparably, when focused on ROI-ML, no differences in mean BMD were observed in lytic ROI-ML but mean BMD in mixed and blastic ROI-ML increased up to 105% and 121%, respectively. Conclusions Ten weeks after palliative radiation therapy in patients with femoral metastatic lesions, a limited increase in BMD was seen with no beneficial effect of MF over SF RT. BMD in lytic lesions was unchanged but slightly increased in mixed and blastic lesions.

PATIENT-SPECIFIC FINITE ELEMENT MODELS DIFFERENTIATE BETWEEN PATIENTS WITH AND WITHOUT A PATHOLOGICAL FRACTURE IN METASTATIC BONE DISEASE

Current clinical practice lacks an accurate predictor of the femoral fracture risk in patients suffering metastatic bone disease, which results in large numbers of patients who are overand undertreated with complex surgery [Hipp, 1995; Van der Linden, 2003]. Previously, patient-specific finite element (FE) models have shown to be very promising in the prediction of femoral bone strength in vitro [Bessho, 2007; Keyak, 2005; Tanck, 2009]. The aim of the current in vivo study is to assess whether patient-specific FE models are able to discriminate low-risk patients with a pathological fracture from low-risk patients who did not fracture their femur.

Effect of different CT scanners and settings on femoral failure loads calculated by finite element models: CT SCANNERS AND FAILURE LOADS

In a multi‐center patient study, using different CT scanners, CT‐based finite element (FE) models are utilized to calculate failure loads of femora with metastases. Previous studies showed that using different CT scanners can result in different outcomes. This study aims to quantify the effects of (i) different CT scanners; (ii) different CT protocols with variations in slice thickness, field of view (FOV), and reconstruction kernel; and (iii) air between calibration phantom and patient, on Hounsfield Units (HU), bone mineral density (BMD), and FE failure load. Six cadaveric femora were scanned on four CT scanners. Scans were made with multiple CT protocols and with or without an air gap between the body model and calibration phantom. HU and calibrated BMD were determined in cortical and trabecular regions of interest. Non‐linear isotropic FE models were constructed to calculate failure load. Mean differences between CT scanners varied up to 7% in cortical HU, 6% in trabecular HU, 6% in cortical BMD, 12% in trabecular BMD, and 17% in failure load. Changes in slice thickness and FOV had little effect (≤4%), while reconstruction kernels had a larger effect on HU (16%), BMD (17%), and failure load (9%). Air between the body model and calibration phantom slightly decreased the HU, BMD, and failure loads (≤8%). In conclusion, this study showed that quantitative analysis of CT images acquired with different CT scanners, and particularly reconstruction kernels, can induce relatively large differences in HU, BMD, and failure loads. Additionally, if possible, air artifacts should be avoided.