MR-based attenuation correction and scatter correction in neurological PET/MR imaging with 18F-FDG

The aim was to investigate the effects of MR-based attenuation correction (MRAC) and scatter correction to positron emission tomography (PET) image quantification in neurological PET/MR with 18F-FDG. A multi-center phantom study was conducted to investigate the effect of MRAC between PET/MR and PET/CT systems (I). An MRAC method to derive bone from T1-weighted MR images was developed (II, III). Finally, scatter correction accuracy with MRAC was investigated (IV). The results show that the quantitative accuracy in PET is well-comparable be-tween PET/MR and PET/CT systems when an attenuation correction method resembling CT-based attenuation correction (CTAC) is implemented. This al-lows achieving of a PET bias within standard uptake value (SUV) quantification repeatability (< 10 % error) and is within the repeatability of PET in most sys-tems and brain regions (< 5 % error). In addition, MRAC considering soft tissue, air and bone can be derived using T1-weighted images alone. The improved version of the MRAC method allows achieving a quantitative accuracy feasible for advanced applications (< 5 % error). MRAC has a minor effect on the scatter correction accuracy (< 3 % error), even when using MRAC without bone. In conclusion, MRAC can be considered the largest contributing factor to PET quantification bias in 18F-FDG neurological PET/MR. This finding is not explicitly limited only to 18F-FDG imaging. Once an MRAC method that performs close to CTAC is implemented, there is no reason why a PET/MR system would perform differently from a PET/CT system. Such an MRAC method has been developed and is freely available (http://bit.ly/2fx6Jjz). Scatter correction can be considered a non-issue in neurological PET/MR imaging when using 18F-FD

Complete head cerebral sensitivity mapping for diffuse correlation spectroscopy using subject-specific magnetic resonance imaging models

We characterize cerebral sensitivity across the entire adult human head for diffuse correlation spectroscopy, an optical technique increasingly used for bedside cerebral perfusion monitoring. Sixteen subject-specific magnetic resonance imaging-derived head models were used to identify high sensitivity regions by running Monte Carlo light propagation simulations at over eight hundred uniformly distributed locations on the head. Significant spatial variations in cerebral sensitivity, consistent across subjects, were found. We also identified correlates of such differences suitable for real-time assessment. These variations can be largely attributed to changes in extracerebral thickness and should be taken into account to optimize probe placement in experimental settings

Identifying Visible Tissue in Intraoperative Ultrasound Images during Brain Surgery: A Method and Application

Intraoperative ultrasound scanning is a demanding visuotactile task. It requires operators to simultaneously localise the ultrasound perspective and manually perform slight adjustments to the pose of the probe, making sure not to apply excessive force or breaking contact with the tissue, whilst also characterising the visible tissue. In this paper, we propose a method for the identification of the visible tissue, which enables the analysis of ultrasound probe and tissue contact via the detection of acoustic shadow and construction of confidence maps of the perceptual salience. Detailed validation with both in vivo and phantom data is performed. First, we show that our technique is capable of achieving state of the art acoustic shadow scan line classification - with an average binary classification accuracy on unseen data of 0.87. Second, we show that our framework for constructing confidence maps is able to produce an ideal response to a probe's pose that is being oriented in and out of optimality - achieving an average RMSE across five scans of 0.174. The performance evaluation justifies the potential clinical value of the method which can be used both to assist clinical training and optimise robot-assisted ultrasound tissue scanning

The effect of meninges on the electric fields in TES and TMS: Numerical modeling with adaptive mesh refinement

Background When modeling transcranial electrical stimulation (TES) and transcranial magnetic stimulation (TMS) in the brain, the meninges – dura, arachnoid, and pia mater – are often neglected due to high computational costs. Objective We investigate the impact of the meningeal layers on the cortical electric field in TES and TMS while considering the headreco segmentation as the base model. Method We use T1/T2 MRI data from 16 subjects and apply the boundary element fast multipole method with adaptive mesh refinement, which enables us to accurately solve this problem and establish method convergence at reasonable computational cost. We compare electric fields in the presence and absence of various meninges for two brain areas ( and ) and for several distinct TES and TMS setups. Results Maximum electric fields in the cortex for focal TES consistently increase by approximately 30% on average when the meninges are present in the CSF volume. Their effect on the maximum field can be emulated by reducing the CSF conductivity from 1.65 S/m to approximately 0.85 S/m. In stark contrast to that, the TMS electric fields in the cortex are only weakly affected by the meningeal layers and slightly (∼6%) decrease on average when the meninges are included. Conclusion Our results quantify the influence of the meninges on the cortical TES and TMS electric fields. Both focal TES and TMS results are very consistent. The focal TES results are also in a good agreement with a prior relevant study. The solver and the mesh generator for the meningeal layers (compatible with SimNIBS) are available online

Image synthesis for the attenuation correction and analysis of PET/MR data

While magnetic resonance imaging (MRI) provides high-resolution anatomical information, positron emission tomography (PET) provides functional information. Combined PET/MR scanners are expected to offer a new range of clinical applications but efforts are still necessary to mitigate some limitations of this promising technology. One of the factors limiting the use of PET/MR scanners, especially in the case of neurology studies, is the imperfect attenuation correction, leading to a strong bias of the PET activity. Exploiting the simultaneous acquisition of both modalities, I explored a new family of methods to synthesise X-ray computed tomography (CT) images from MR images. The synthetic images are generated through a multi-atlas information propagation scheme, locally matching the MRI-derived patient's morphology to a database of MR/CT image pairs, using a local image similarity measure. The proposed algorithm provides a significant improvement in PET reconstruction accuracy when compared with the current correction, allowing an unbiased analysis of the PET images. A similar image synthesis scheme was then used to better identify abnormalities in cerebral glucose metabolism measured by [18]F-fluorodeoxyglucose (FDG) PET. This framework consists of creating a subject-specific healthy PET model based on the propagation of morphologically-matched PET images, and comparing the subject's PET image to the model via a Z-score. By accounting for inter-subject morphological differences, the proposed method reduces the variance of the normal population used for comparison in the Z-score, thus increasing the sensitivity. To demonstrate that the applicability of the proposed CT synthesis method is not limited to PET/MR attenuation correction, I redesigned the synthesis process to derive tissue attenuation properties from MR images in the head & neck and pelvic regions to facilitate MR-based radiotherapy treatment planning

Improving Attenuation Correction in Hybrid Positron Emission Tomography

Hybrid positron emission tomography imaging techniques such as PET/CT and PET/MR have undergone significant developments over the last two decades and have played increasingly more important roles both in research and in the clinic. A unique advantage PET has over other clinical imaging modalities is its capability of accurate quantification. However, as the most critical component of PET quantification, attenuation correction in hybrid PET systems is challenged in several different aspects, including the spatial- temporal mismatch between the PET emission images and the associated attenuation images provided by the complementary modality, and the difficulty in bone identification in the MR-based attenuation correction approaches. These problems, if left unaddressed, can limit the potential of the hybrid PET systems. This research developed solutions to overcome the spatial-temporal mismatch in PET/CT and PET/MR, and established the requirements for bone identification in PET/MR. An automatic registration algorithm based on a modified fuzzy c-means clustering method and gradient correlation was developed and validated to perform automatic registration in cardiac PET/CT data of different breathing protocols. A free- breathing MR protocol and post-process algorithm were developed to provide MR-based attenuation images that also match the temporal resolution of PET and were evaluated in a feasibility study. The relationship between the sensitivity of bone identification in attenuation images and PET quantification of bone lesions uptake was evaluated in a simulated study using data from 18F-sodium fluoride PET/CT exams

Deep learning-based post-processing of real-time MRI to assess and quantify dynamic wrist movement in health and disease

While morphologic magnetic resonance imaging (MRI) is the imaging modality of choice for the evaluation of ligamentous wrist injuries, it is merely static and incapable of diagnosing dynamic wrist instability. Based on real-time MRI and algorithm-based image post-processing in terms of convolutional neural networks (CNNs), this study aims to develop and validate an automatic technique to quantify wrist movement. A total of 56 bilateral wrists (28 healthy volunteers) were imaged during continuous and alternating maximum ulnar and radial abduction. Following CNN-based automatic segmentations of carpal bone contours, scapholunate and lunotriquetral gap widths were quantified based on dedicated algorithms and as a function of wrist position. Automatic segmentations were in excellent agreement with manual reference segmentations performed by two radiologists as indicated by Dice similarity coefficients of 0.96 ± 0.02 and consistent and unskewed Bland–Altman plots. Clinical applicability of the framework was assessed in a patient with diagnosed scapholunate ligament injury. Considerable increases in scapholunate gap widths across the range-of-motion were found. In conclusion, the combination of real-time wrist MRI and the present framework provides a powerful diagnostic tool for dynamic assessment of wrist function and, if confirmed in clinical trials, dynamic carpal instability that may elude static assessment using clinical-standard imaging modalities

Investigation of 3DP technology for fabrication of surgical simulation phantoms

The demand for affordable and realistic phantoms for training, in particular for functional endoscopic sinus surgery (FESS), has continuously increased in recent years. Conventional training methods, such as current physical models, virtual simulators and cadavers may have restrictions, including fidelity, accessibility, cost and ethics. In this investigation, the potential of three-dimensional printing for the manufacture of biologically representative simulation materials for surgery training phantoms has been investigated. A characterisation of sinus anatomical elements was performed through CT and micro-CT scanning of a cadaveric sinus portion. In particular, the relevant constituent tissues of each sinus region have been determined. Secondly, feedback force values experienced during surgical cutting have been quantified with an actual surgical instrument, specifically modified for this purpose. Force values from multiple post-mortem subjects and different areas of the paranasal sinuses have been gathered and used as a benchmark for the optimisation of 3D-printing materials. The research has explored the wide range of properties achievable in 3DP through post-processing methods and variation of printing parameters. For this latter element, a machine-vision system has been developed to monitor the 3DP in real time. The combination of different infiltrants allowed the reproduction of force values comparable to those registered from cadaveric human tissue. The internal characteristics of 3D printed samples were shown to influence their fracture behaviour under resection. Realistic appearance under endoscopic conditions has also been confirmed. The utilisation of some of the research has also been demonstrated in another medical (non-surgical) training application. This investigation highlights a number of capabilities, and also limitations, of 3DP for the manufacturing of representative materials for application in surgical training phantoms