Electromagnetic tracking in image-guided laparoscopic surgery: Comparison with optical tracking and feasibility study of a combined laparoscope and laparoscopic ultrasound system

PURPOSE

In image-guided laparoscopy, optical tracking is commonly employed, but electromagnetic (EM) systems have been proposed in the literature. In this paper, we provide a thorough comparison of EM and optical tracking systems for use in image-guided laparoscopic surgery and a feasibility study of a combined, EM-tracked laparoscope and laparoscopic ultrasound (LUS) image guidance system.

METHODS

We first assess the tracking accuracy of a laparoscope with two optical trackers tracking retroreflective markers mounted on the shaft and an EM tracker with the sensor embedded at the proximal end, using a standard evaluation plate. We then use a stylus to test the precision of position measurement and accuracy of distance measurement of the trackers. Finally, we assess the accuracy of an image guidance system comprised of an EM-tracked laparoscope and an EM-tracked LUS probe.

RESULTS

In the experiment using a standard evaluation plate, the two optical trackers show less jitter in position and orientation measurement than the EM tracker. Also, the optical trackers demonstrate better consistency of orientation measurement within the test volume. However, their accuracy of measuring relative positions decreases significantly with longer distances whereas the EM tracker's performance is stable; at 50 mm distance, the RMS errors for the two optical trackers are 0.210 and 0.233 mm, respectively, and it is 0.214 mm for the EM tracker; at 250 mm distance, the RMS errors for the two optical trackers become 1.031 and 1.178 mm, respectively, while it is 0.367 mm for the EM tracker. In the experiment using the stylus, the two optical trackers have RMS errors of 1.278 and 1.555 mm in localizing the stylus tip, and it is 1.117 mm for the EM tracker. Our prototype of a combined, EM-tracked laparoscope and LUS system using representative calibration methods showed a RMS point localization error of 3.0 mm for the laparoscope and 1.3 mm for the LUS probe, the lager error of the former being predominantly due to the triangulation error when using a narrow-baseline stereo laparoscope.

CONCLUSIONS

The errors incurred by optical trackers, due to the lever-arm effect and variation in tracking accuracy in the depth direction, would make EM-tracked solutions preferable if the EM sensor is placed at the proximal end of the laparoscope.

Automatic Multi-Organ Segmentation on Abdominal CT With Dense V-Networks

Automatic segmentation of abdominal anatomy on computed tomography (CT) images can support diagnosis, treatment planning, and treatment delivery workflows. Segmentation methods using statistical models and multi-atlas label fusion (MALF) require inter-subject image registrations, which are challenging for abdominal images, but alternative methods without registration have not yet achieved higher accuracy for most abdominal organs. We present a registration-free deep-learning-based segmentation algorithm for eight organs that are relevant for navigation in endoscopic pancreatic and biliary procedures, including the pancreas, the gastrointestinal tract (esophagus, stomach, and duodenum) and surrounding organs (liver, spleen, left kidney, and gallbladder). We directly compared the segmentation accuracy of the proposed method to the existing deep learning and MALF methods in a cross-validation on a multi-centre data set with 90 subjects. The proposed method yielded significantly higher Dice scores for all organs and lower mean absolute distances for most organs, including Dice scores of 0.78 versus 0.71, 0.74, and 0.74 for the pancreas, 0.90 versus 0.85, 0.87, and 0.83 for the stomach, and 0.76 versus 0.68, 0.69, and 0.66 for the esophagus. We conclude that the deep-learning-based segmentation represents a registration-free method for multi-organ abdominal CT segmentation whose accuracy can surpass current methods, potentially supporting image-guided navigation in gastrointestinal endoscopy procedures.

A pre-operative planning framework for global registration of laparoscopic ultrasound to CT images

PURPOSE

Laparoscopic ultrasound (LUS) enhances the safety of laparoscopic liver resection by enabling real-time imaging of internal structures such as vessels. However, LUS probes can be difficult to use, and many tumours are iso-echoic and hence are not visible. Registration of LUS to a pre-operative CT or MR scan has been proposed as a method of image guidance. However, the field of view of the probe is very small compared to the whole liver, making the registration task challenging and dependent on a very accurate initialisation.

METHODS

We propose the use of a subject-specific planning framework that provides information on which anatomical liver regions it is possible to acquire vascular data that is unique enough for a globally optimal initial registration. Vessel-based rigid registration on different areas of the pre-operative CT vascular tree is used in order to evaluate predicted accuracy and reliability.

RESULTS

The planning framework is tested on one porcine subject where we have taken 5 independent sweeps of LUS data from different sections of the liver. Target registration error of vessel branching points was used to measure accuracy. Global registration based on vessel centrelines is applied to the 5 datasets. In 3 out of 5 cases registration is successful and in agreement with the planning. Further tests with a CT scan under abdominal insufflation show that the framework can provide valuable information in all of the 5 cases.

CONCLUSIONS

We have introduced a planning framework that can guide the surgeon on how much LUS data to collect in order to provide a reliable globally unique registration without the need for an initial manual alignment. This could potentially improve the usability of these methods in clinic.

Global rigid registration of CT to video in laparoscopic liver surgery

PURPOSE

Image-guidance systems have the potential to aid in laparoscopic interventions by providing sub-surface structure information and tumour localisation. The registration of a preoperative 3D image with the intraoperative laparoscopic video feed is an important component of image guidance, which should be fast, robust and cause minimal disruption to the surgical procedure. Most methods for rigid and non-rigid registration require a good initial alignment. However, in most research systems for abdominal surgery, the user has to manually rotate and translate the models, which is usually difficult to perform quickly and intuitively.

METHODS

We propose a fast, global method for the initial rigid alignment between a 3D mesh derived from a preoperative CT of the liver and a surface reconstruction of the intraoperative scene. We formulate the shape matching problem as a quadratic assignment problem which minimises the dissimilarity between feature descriptors while enforcing geometrical consistency between all the feature points. We incorporate a novel constraint based on the liver contours which deals specifically with the challenges introduced by laparoscopic data.

RESULTS

We validate our proposed method on synthetic data, on a liver phantom and on retrospective clinical data acquired during a laparoscopic liver resection. We show robustness over reduced partial size and increasing levels of deformation. Our results on the phantom and on the real data show good initial alignment, which can successfully converge to the correct position using fine alignment techniques. Furthermore, since we can pre-process the CT scan before surgery, the proposed method runs faster than current algorithms.

CONCLUSION

The proposed shape matching method can provide a fast, global initial registration, which can be further refined by fine alignment methods. This approach will lead to a more usable and intuitive image-guidance system for laparoscopic liver surgery.

Determination of optimal ultrasound planes for the initialisation of image registration during endoscopic ultrasound-guided procedures

PURPOSE

Navigation of endoscopic ultrasound (EUS)-guided procedures of the upper gastrointestinal (GI) system can be technically challenging due to the small fields-of-view of ultrasound and optical devices, as well as the anatomical variability and limited number of orienting landmarks during navigation. Co-registration of an EUS device and a pre-procedure 3D image can enhance the ability to navigate. However, the fidelity of this contextual information depends on the accuracy of registration. The purpose of this study was to develop and test the feasibility of a simulation-based planning method for pre-selecting patient-specific EUS-visible anatomical landmark locations to maximise the accuracy and robustness of a feature-based multimodality registration method.

METHODS

A registration approach was adopted in which landmarks are registered to anatomical structures segmented from the pre-procedure volume. The predicted target registration errors (TREs) of EUS-CT registration were estimated using simulated visible anatomical landmarks and a Monte Carlo simulation of landmark localisation error. The optimal planes were selected based on the 90th percentile of TREs, which provide a robust and more accurate EUS-CT registration initialisation. The method was evaluated by comparing the accuracy and robustness of registrations initialised using optimised planes versus non-optimised planes using manually segmented CT images and simulated ([Formula: see text]) or retrospective clinical ([Formula: see text]) EUS landmarks.

RESULTS

The results show a lower 90th percentile TRE when registration is initialised using the optimised planes compared with a non-optimised initialisation approach (p value [Formula: see text]).

CONCLUSIONS

The proposed simulation-based method to find optimised EUS planes and landmarks for EUS-guided procedures may have the potential to improve registration accuracy. Further work will investigate applying the technique in a clinical setting.

Automatic segmentation of stereoelectroencephalography (SEEG) electrodes post-implantation considering bending

Purpose

The accurate and automatic localisation of SEEG electrodes is crucial for determining the location of epileptic seizure onset. We propose an algorithm for the automatic segmentation of electrode bolts and contacts that accounts for electrode bending in relation to regional brain anatomy.

Methods

Co-registered post-implantation CT, pre-implantation MRI, and brain parcellation images are used to create regions of interest to automatically segment bolts and contacts. Contact search strategy is based on the direction of the bolt with distance and angle constraints, in addition to post-processing steps that assign remaining contacts and predict contact position. We measured the accuracy of contact position, bolt angle, and anatomical region at the tip of the electrode in 23 post-SEEG cases comprising two different surgical approaches when placing a guiding stylet close to and far from target point. Local and global bending are computed when modelling electrodes as elastic rods.

Results

Our approach executed on average in 36.17 s with a sensitivity of 98.81% and a positive predictive value (PPV) of 95.01%. Compared to manual segmentation, the position of contacts had a mean absolute error of 0.38 mm and the mean bolt angle difference of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.59^{\circ }$$\end{document}0.59∘ resulted in a mean displacement error of 0.68 mm at the tip of the electrode. Anatomical regions at the tip of the electrode were in strong concordance with those selected manually by neurosurgeons, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ICC(3,k)=0.76$$\end{document}ICC(3,k)=0.76, with average distance between regions of 0.82 mm when in disagreement. Our approach performed equally in two surgical approaches regardless of the amount of electrode bending.

Conclusion

We present a method robust to electrode bending that can accurately segment contact positions and bolt orientation. The techniques presented in this paper will allow further characterisation of bending within different brain regions.

Electronic supplementary material

The online version of this article (10.1007/s11548-018-1740-8) contains supplementary material, which is available to authorized users.

Efficacy of blood flow restriction exercise during dialysis for end stage kidney disease patients: protocol of a randomised controlled trial

BACKGROUND

Exercise during haemodialysis improves strength and physical function. However, both patients and clinicians are time poor, and current exercise recommendations add an excessive time burden making exercise a rare addition to standard care. Hypothetically, blood flow restriction exercise performed during haemodialysis can provide greater value for time spent exercising, reducing this time burden while producing similar or greater outcomes. This study will explore the efficacy of blood flow restriction exercise for enhancing strength and physical function among haemodialysis patients.

METHODS

This is a randomised controlled trial design. A total of 75 participants will be recruited from haemodialysis clinics. Participants will be allocated to a blood flow restriction cycling group, traditional cycling group or usual care control group. Both exercising groups will complete 3 months of cycling exercise, performed intradialytically, three times per week. The blood flow restriction cycling group will complete two 10-min cycling bouts separated by a 20-min rest at a subjective effort of 15 on a 6 to 20 rating scale. This will be done with pressurised cuffs fitted proximally on the active limbs during exercise at 50% of a pre-determined limb occlusion pressure. The traditional cycling group will perform a continuous 20-min bout of exercise at a subjective effort of 12 on the same subjective effort scale. These workloads and volumes are equivalent and allow for comparison of a common blood flow restriction aerobic exercise prescription and a traditional aerobic exercise prescription. The primary outcome measures are lower limb strength, assessed by a three repetition maximum leg extension test, as well as objective measures of physical function: six-minute walk test, 30-s sit to stand, and timed up and go. Secondary outcome measures include thigh muscle cross sectional area, body composition, routine pathology, quality of life, and physical activity engagement.

DISCUSSION

This study will determine the efficacy of blood flow restriction exercise among dialysis patients for improving key physiological outcomes that impact independence and quality of life, with reduced burden on patients. This may have broader implications for other clinical populations with similarly declining muscle health and physical function, and those contraindicated to higher intensities of exercise.

TRIAL REGISTRATION

Australian and New Zealand Clinical Trial Register: ACTRN12616000121460.

Intelligent viewpoint selection for efficient CT to video registration in laparoscopic liver surgery

PURPOSE

Minimally invasive surgery offers advantages over open surgery due to a shorter recovery time, less pain and trauma for the patient. However, inherent challenges such as lack of tactile feedback and difficulty in controlling bleeding lower the percentage of suitable cases. Augmented reality can show a better visualisation of sub-surface structures and tumour locations by fusing pre-operative CT data with real-time laparoscopic video. Such augmented reality visualisation requires a fast and robust video to CT registration that minimises interruption to the surgical procedure.

METHODS

We propose to use view planning for efficient rigid registration. Given the trocar position, a set of camera positions are sampled and scored based on the corresponding liver surface properties. We implement a simulation framework to validate the proof of concept using a segmented CT model from a human patient. Furthermore, we apply the proposed method on clinical data acquired during a human liver resection.

RESULTS

The first experiment motivates the viewpoint scoring strategy and investigates reliable liver regions for accurate registrations in an intuitive visualisation. The second experiment shows wider basins of convergence for higher scoring viewpoints. The third experiment shows that a comparable registration performance can be achieved by at least two merged high scoring views and four low scoring views. Hence, the focus could change from the acquisition of a large liver surface to a small number of distinctive patches, thereby giving a more explicit protocol for surface reconstruction. We discuss the application of the proposed method on clinical data and show initial results.

CONCLUSION

The proposed simulation framework shows promising results to motivate more research into a comprehensive view planning method for efficient registration in laparoscopic liver surgery.

Development and Phantom Validation of a 3-D-Ultrasound-Guided System for Targeting MRI-Visible Lesions During Transrectal Prostate Biopsy

OBJECTIVE

Three- and four-dimensional transrectal ultrasound transducers are now available from most major ultrasound equipment manufacturers, but currently are incorporated into only one commercial prostate biopsy guidance system. Such transducers offer the benefits of rapid volumetric imaging, but can cause substantial measurement distortion in electromagnetic tracking sensors, which are commonly used to enable 3-D navigation. In this paper, we describe the design, development, and validation of a 3-D-ultrasound-guided transrectal prostate biopsy system that employs high-accuracy optical tracking to localize the ultrasound probe and prostate targets in 3-D physical space.

METHODS

The accuracy of the system was validated by evaluating the targeted needle placement error after inserting a biopsy needle to sample planned targets in a phantom using standard 2-D ultrasound guidance versus real-time 3-D guidance provided by the new system.

RESULTS

The overall mean needle-segment-to-target distance error was 3.6 ± 4.0 mm and mean needle-to-target distance was 3.2 ± 2.4 mm.

CONCLUSION

A significant increase in needle placement accuracy was observed when using the 3-D guidance system compared with visual targeting of invisible (virtual) lesions using a standard B-mode ultrasound-guided biopsy technique.

Identification and removal of laser-induced noise in photoacoustic imaging using singular value decomposition

Singular value decomposition (SVD) was used to identify and remove laser-induced noise in photoacoustic images acquired with a clinical ultrasound scanner. This noise, which was prominent in the radiofrequency data acquired in parallel from multiple transducer elements, was induced by the excitation light source. It was modelled by truncating the SVD matrices so that only the first few largest singular value components were retained, and subtracted prior to image reconstruction. The dependency of the signal amplitude and the number of the largest singular value components used for noise modeling was investigated for different photoacoustic source geometries. Validation was performed with simulated data and measured noise, and with photoacoustic images acquired from the human forearm and finger in vivo using L14-5/38 and L40-8/12 linear array clinical imaging probes. The use of only one singular value component was found to be sufficient to achieve near-complete removal of laser-induced noise from reconstructed images. This method has strong potential to increase image quality for a wide range of photoacoustic imaging systems with parallel data acquisition.

Hand-eye calibration for rigid laparoscopes using an invariant point

PURPOSE

Laparoscopic liver resection has significant advantages over open surgery due to less patient trauma and faster recovery times, yet it can be difficult due to the restricted field of view and lack of haptic feedback. Image guidance provides a potential solution but one current challenge is in accurate "hand-eye" calibration, which determines the position and orientation of the laparoscope camera relative to the tracking markers.

METHODS

In this paper, we propose a simple and clinically feasible calibration method based on a single invariant point. The method requires no additional hardware, can be constructed by theatre staff during surgical setup, requires minimal image processing and can be visualised in real time. Real-time visualisation allows the surgical team to assess the calibration accuracy before use in surgery. In addition, in the laboratory, we have developed a laparoscope with an electromagnetic tracking sensor attached to the camera end and an optical tracking marker attached to the distal end. This enables a comparison of tracking performance.

RESULTS

We have evaluated our method in the laboratory and compared it to two widely used methods, "Tsai's method" and "direct" calibration. The new method is of comparable accuracy to existing methods, and we show RMS projected error due to calibration of 1.95 mm for optical tracking and 0.85 mm for EM tracking, versus 4.13 and 1.00 mm respectively, using existing methods. The new method has also been shown to be workable under sterile conditions in the operating room.

CONCLUSION

We have proposed a new method of hand-eye calibration, based on a single invariant point. Initial experience has shown that the method provides visual feedback, satisfactory accuracy and can be performed during surgery. We also show that an EM sensor placed near the camera would provide significantly improved image overlay accuracy.

Utilizing confocal laser endomicroscopy for evaluating the adequacy of laparoscopic liver ablation

Background

Laparoscopic liver ablation therapy can be used for the treatment of primary and secondary liver malignancy. The increased incidence of cancer recurrence associated with this approach, has been attributed to the inability of monitoring the extent of ablated liver tissue.

Methods

The feasibility of assessing liver ablation with probe‐based confocal laser endomicroscopy (CLE) was studied in a porcine model of laparoscopic microwave liver ablation. Following the intravenous injection of the fluorophores fluorescein and indocyanine green, CLE images were recorded at 488 nm and 660 nm wavelength and compared to liver histology. Statistical analysis was performed to assess if fluorescence intensity change can predict the presence of ablated liver tissue.

Results

CLE imaging of fluorescein at 488 nm provided good visualization of the hepatic microvasculature; whereas, CLE imaging of indocyanine green at 660 nm enabled detailed visualization of hepatic sinusoid architecture and interlobular septations. Fluorescence intensity as measured in relative fluorescence units was found to be 75–100% lower in ablated compared to healthy liver regions. General linear mixed modeling and ROC analysis found the decrease in fluorescence to be statistically significant.

Conclusion

Laparoscopic, dual wavelength CLE imaging using two different fluorophores enables clinically useful visualization of multiple liver tissue compartments, in greater detail than is possible at a single wavelength. CLE imaging may provide valuable intraoperative information on the extent of laparoscopic liver ablation. Lasers Surg. Med. 48:299–310, 2016. © 2015 The Authors. Lasers in Surgery and Medicine Published by Wiley Periodicals, Inc.

Locally rigid, vessel-based registration for laparoscopic liver surgery

PURPOSE

Laparoscopic liver resection has significant advantages over open surgery due to less patient trauma and faster recovery times, yet is difficult for most lesions due to the restricted field of view and lack of haptic feedback. Image guidance provides a potential solution but is challenging in a soft deforming organ such as the liver. In this paper, we therefore propose a laparoscopic ultrasound (LUS) image guidance system and study the feasibility of a locally rigid registration for laparoscopic liver surgery.

METHODS

We developed a real-time segmentation method to extract vessel centre points from calibrated, freehand, electromagnetically tracked, 2D LUS images. Using landmark-based initial registration and an optional iterative closest point (ICP) point-to-line registration, a vessel centre-line model extracted from preoperative computed tomography (CT) is registered to the ultrasound data during surgery.

RESULTS

Using the locally rigid ICP method, the RMS residual error when registering to a phantom was 0.7 mm, and the mean target registration error (TRE) for two in vivo porcine studies was 3.58 and 2.99 mm, respectively. Using the locally rigid landmark-based registration method gave a mean TRE of 4.23 mm using vessel centre lines derived from CT scans taken with pneumoperitoneum and 6.57 mm without pneumoperitoneum.

CONCLUSION

In this paper we propose a practical image-guided surgery system based on locally rigid registration of a CT-derived model to vascular structures located with LUS. In a physical phantom and during porcine laparoscopic liver resection, we demonstrate accuracy of target location commensurate with surgical requirements. We conclude that locally rigid registration could be sufficient for practically useful image guidance in the near future.

NiftySim: A GPU-based nonlinear finite element package for simulation of soft tissue biomechanics

PURPOSE

NiftySim, an open-source finite element toolkit, has been designed to allow incorporation of high-performance soft tissue simulation capabilities into biomedical applications. The toolkit provides the option of execution on fast graphics processing unit (GPU) hardware, numerous constitutive models and solid-element options, membrane and shell elements, and contact modelling facilities, in a simple to use library.

METHODS

The toolkit is founded on the total Lagrangian explicit dynamics (TLEDs) algorithm, which has been shown to be efficient and accurate for simulation of soft tissues. The base code is written in C[Formula: see text], and GPU execution is achieved using the nVidia CUDA framework. In most cases, interaction with the underlying solvers can be achieved through a single Simulator class, which may be embedded directly in third-party applications such as, surgical guidance systems. Advanced capabilities such as contact modelling and nonlinear constitutive models are also provided, as are more experimental technologies like reduced order modelling. A consistent description of the underlying solution algorithm, its implementation with a focus on GPU execution, and examples of the toolkit's usage in biomedical applications are provided.

RESULTS

Efficient mapping of the TLED algorithm to parallel hardware results in very high computational performance, far exceeding that available in commercial packages.

CONCLUSION

The NiftySim toolkit provides high-performance soft tissue simulation capabilities using GPU technology for biomechanical simulation research applications in medical image computing, surgical simulation, and surgical guidance applications.

The NifTK software platform for image-guided interventions: platform overview and NiftyLink messaging

PURPOSE

To perform research in image-guided interventions, researchers need a wide variety of software components, and assembling these components into a flexible and reliable system can be a challenging task. In this paper, the NifTK software platform is presented. A key focus has been high-performance streaming of stereo laparoscopic video data, ultrasound data and tracking data simultaneously.

METHODS

A new messaging library called NiftyLink is introduced that uses the OpenIGTLink protocol and provides the user with easy-to-use asynchronous two-way messaging, high reliability and comprehensive error reporting. A small suite of applications called NiftyGuide has been developed, containing lightweight applications for grabbing data, currently from position trackers and ultrasound scanners. These applications use NiftyLink to stream data into NiftyIGI, which is a workstation-based application, built on top of MITK, for visualisation and user interaction. Design decisions, performance characteristics and initial applications are described in detail. NiftyLink was tested for latency when transmitting images, tracking data, and interleaved imaging and tracking data.

RESULTS

NiftyLink can transmit tracking data at 1,024 frames per second (fps) with latency of 0.31 milliseconds, and 512 KB images with latency of 6.06 milliseconds at 32 fps. NiftyIGI was tested, receiving stereo high-definition laparoscopic video at 30 fps, tracking data from 4 rigid bodies at 20-30 fps and ultrasound data at 20 fps with rendering refresh rates between 2 and 20 Hz with no loss of user interaction.

CONCLUSION

These packages form part of the NifTK platform and have proven to be successful in a variety of image-guided surgery projects. Code and documentation for the NifTK platform are available from http://www.niftk.org . NiftyLink is provided open-source under a BSD license and available from http://github.com/NifTK/NiftyLink . The code for this paper is tagged IJCARS-2014.

Genetic influences on atrophy patterns in familial Alzheimer's disease: a comparison of APP and PSEN1 mutations

Mutations in the presenilin1 (PSEN1) and amyloid β-protein precursor (APP) genes account for the majority of cases of autosomal dominantly inherited Alzheimer's disease (AD). We wished to assess and compare the patterns of cerebral loss produced by these two groups of mutations. Volumetric magnetic resonance imaging and neuropsychological assessments were performed in individuals with clinical AD carrying mutations in the APP (n = 10) and PSEN1 (n = 18) genes and in healthy controls (n = 18). Voxel-based morphometry (VBM), cortical thickness, and region of interest analyses were performed. Mini-Mental State Examination scores were similar in the two disease groups suggesting similar levels of disease severity. There was evidence that APP subjects have smaller hippocampal volume compared with PSEN1 subjects (p = 0.007), and weak evidence that they have larger whole-brain and grey matter volumes (both p = 0.07). Although there was no evidence of statistically significant differences between APP and PSEN1 in VBM or cortical thickness analyses, effect-maps were suggestive of APP subjects having more medial temporal lobe atrophy and conversely PSEN1 subjects showing more neocortical loss. Neuropsychological data were consistent with these regional differences and suggested greater memory deficits in the APP patients and greater impairment in non-memory domains in the PSEN1 group, although these differences were not statistically significant. We conclude that the mechanisms by which APP and PSEN1 mutations cause neuronal loss may differ which furthers our understanding of the neuropathology underlying AD and may inform future therapeutic strategies and trial designs.

Rates of hemispheric and lobar atrophy in the language variants of frontotemporal lobar degeneration

Frontotemporal lobar degeneration (FTLD) is a neurodegenerative disorder which presents with either behavioral or language impairment. The two language syndromes are known as progressive nonfluent aphasia (PNFA) and semantic dementia (SEMD). While cross-sectional imaging patterns of brain atrophy are well-described in FTLD, fewer studies have investigated longitudinal imaging changes. We measured longitudinal hemispheric and lobar atrophy rates using serial MRI in a cohort of 18 patients with PNFA and 17 patients with SEMD as well as 14 cognitively-normal control subjects. We subsequently calculated sample size estimates for clinical trials. Rates of left hemisphere atrophy were greater than rates of right hemisphere atrophy in both PNFA and SEMD with no significant differences between the groups. The disease groups showed asymmetrical atrophy (more severe on the left) at baseline with significantly increasing asymmetry over time. Within a hemisphere, the fastest rate of atrophy varied between lobes: in SEMD temporal > frontal > parietal > occipital, while in PNFA frontal > temporal/parietal > occipital. In SEMD, using temporal lobe measures of atrophy in clinical trials would provide the lowest sample sizes necessary, while in PNFA left hemisphere atrophy measures provided the lowest sample size. These patterns provide information about disease evolution in the FTLD language variants that is of both clinical and neurobiological relevance.

Longitudinal cortical thickness estimation using Khalimsky's cubic complex

Longitudinal measurements of cortical thickness is a current hot topic in medical imaging research. Measuring the thickness of the cortex through time is normally hindered by the presence of noise, partial volume (PV) effects and topological defects, but mainly by the lack of a common directionality in the measurement to ensure consistency. In this paper, we propose a 4D pipeline (3D + time) using the Khalimsky cubic complex for the extraction of a topologically correct Laplacian field in an unbiased temporal group-wise space. The thickness at each time point is then obtained by integrating the probabilistic segmentation (transformed to the group-wise space) modulated by the Jacobian determinant of its deformation field through the group-wise Laplacian field. Experiments performed on digital phantoms show that the proposed method improves the time consistency of the thickness measurements with a statistically significant increase in accuracy when compared to two well established 3D techniques and a 3D version of the same method. Furthermore, quantitative analysis on brain MRI data showed that the proposed algorithm is able to retrieve increasingly significant time consistent consistent group differences between the cortical thickness of AD patients and controls.

Clinical and neuroanatomical signatures of tissue pathology in frontotemporal lobar degeneration

Relating clinical symptoms to neuroanatomical profiles of brain damage and ultimately to tissue pathology is a key challenge in the field of neurodegenerative disease and particularly relevant to the heterogeneous disorders that comprise the frontotemporal lobar degeneration spectrum. Here we present a retrospective analysis of clinical, neuropsychological and neuroimaging (volumetric and voxel-based morphometric) features in a pathologically ascertained cohort of 95 cases of frontotemporal lobar degeneration classified according to contemporary neuropathological criteria. Forty-eight cases (51%) had TDP-43 pathology, 42 (44%) had tau pathology and five (5%) had fused-in-sarcoma pathology. Certain relatively specific clinicopathological associations were identified. Semantic dementia was predominantly associated with TDP-43 type C pathology; frontotemporal dementia and motoneuron disease with TDP-43 type B pathology; young-onset behavioural variant frontotemporal dementia with FUS pathology; and the progressive supranuclear palsy syndrome with progressive supranuclear palsy pathology. Progressive non-fluent aphasia was most commonly associated with tau pathology. However, the most common clinical syndrome (behavioural variant frontotemporal dementia) was pathologically heterogeneous; while pathologically proven Pick's disease and corticobasal degeneration were clinically heterogeneous, and TDP-43 type A pathology was associated with similar clinical features in cases with and without progranulin mutations. Volumetric magnetic resonance imaging, voxel-based morphometry and cluster analyses of the pathological groups here suggested a neuroanatomical framework underpinning this clinical and pathological diversity. Frontotemporal lobar degeneration-associated pathologies segregated based on their cerebral atrophy profiles, according to the following scheme: asymmetric, relatively localized (predominantly temporal lobe) atrophy (TDP-43 type C); relatively symmetric, relatively localized (predominantly temporal lobe) atrophy (microtubule-associated protein tau mutations); strongly asymmetric, distributed atrophy (Pick's disease); relatively symmetric, predominantly extratemporal atrophy (corticobasal degeneration, fused-in-sarcoma pathology). TDP-43 type A pathology was associated with substantial individual variation; however, within this group progranulin mutations were associated with strongly asymmetric, distributed hemispheric atrophy. We interpret the findings in terms of emerging network models of neurodegenerative disease: the neuroanatomical specificity of particular frontotemporal lobar degeneration pathologies may depend on an interaction of disease-specific and network-specific factors.

A comparison of voxel and surface based cortical thickness estimation methods

Cortical thickness estimation performed in-vivo via magnetic resonance imaging is an important technique for the diagnosis and understanding of the progression of neurodegenerative diseases. Currently, two different computational paradigms exist, with methods generally classified as either surface or voxel-based. This paper provides a much needed comparison of the surface-based method FreeSurfer and two voxel-based methods using clinical data. We test the effects of computing regional statistics using two different atlases and demonstrate that this makes a significant difference to the cortical thickness results. We assess reproducibility, and show that FreeSurfer has a regional standard deviation of thickness difference on same day scans that is significantly lower than either a Laplacian or Registration based method and discuss the trade off between reproducibility and segmentation accuracy caused by bending energy constraints. We demonstrate that voxel-based methods can detect similar patterns of group-wise differences as well as FreeSurfer in typical applications such as producing group-wise maps of statistically significant thickness change, but that regional statistics can vary between methods. We use a Support Vector Machine to classify patients against controls and did not find statistically significantly different results with voxel based methods compared to FreeSurfer. Finally we assessed longitudinal performance and concluded that currently FreeSurfer provides the most plausible measure of change over time, with further work required for voxel based methods.

LoAd: a locally adaptive cortical segmentation algorithm

Thickness measurements of the cerebral cortex can aid diagnosis and provide valuable information about the temporal evolution of diseases such as Alzheimer's, Huntington's, and schizophrenia. Methods that measure the thickness of the cerebral cortex from in-vivo magnetic resonance (MR) images rely on an accurate segmentation of the MR data. However, segmenting the cortex in a robust and accurate way still poses a challenge due to the presence of noise, intensity non-uniformity, partial volume effects, the limited resolution of MRI and the highly convoluted shape of the cortical folds. Beginning with a well-established probabilistic segmentation model with anatomical tissue priors, we propose three post-processing refinements: a novel modification of the prior information to reduce segmentation bias; introduction of explicit partial volume classes; and a locally varying MRF-based model for enhancement of sulci and gyri. Experiments performed on a new digital phantom, on BrainWeb data and on data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) show statistically significant improvements in Dice scores and PV estimation (p<10(-3)) and also increased thickness estimation accuracy when compared to three well established techniques.

A framework for using diffusion weighted imaging to improve cortical parcellation

Cortical parcellation refers to anatomical labelling of every point in the cortex. An accurate parcellation is useful in many analysis techniques including the study of regional changes in cortical thickness or volume in ageing and neurodegeneration. Parcellation is also key to anatomic apportioning of functional imaging changes. We present preliminary work on a novel algorithm that takes an entire cortical parcellation and iteratively updates it to better match connectivity information derived from diffusion weighted imaging. We demonstrate the algorithm on a cohort of 17 healthy controls. Initial results show the algorithm recovering artificially induced mis-registrations of the parcellation and also converging to a group-wise average. This work introduces a framework to investigate the relationship between structure and function, with no a-priori knowledge of specific regions of interest.