Rapid virtual fractional flow reserve using 3D computational fluid dynamics.

Aims: Over the last ten years, virtual Fractional Flow Reserve (vFFR) has improved the utility of Fractional Flow Reserve (FFR), a globally recommended assessment to guide coronary interventions. Although the speed of vFFR computation has accelerated, techniques utilising full 3D computational fluid dynamics (CFD) solutions rather than simplified analytical solutions still require significant time to compute. Methods and results: This study investigated the speed, accuracy and cost of a novel 3D-CFD software method based upon a graphic processing unit (GPU) computation, compared with the existing fastest central processing unit (CPU)-based 3D-CFD technique, on 40 angiographic cases. The novel GPU simulation was significantly faster than the CPU method (median 31.7 s (Interquartile Range (IQR) 24.0-44.4s) vs. 607.5 s (490-964 s), P < 0.0001). The novel GPU technique was 99.6% (IQR 99.3-99.9) accurate relative to the CPU method. The initial cost of the GPU hardware was greater than the CPU (£4080 vs. £2876), but the median energy consumption per case was significantly less using the GPU method (8.44 (6.80-13.39) Wh vs. 2.60 (2.16-3.12) Wh, P < 0.0001). Conclusion: This study demonstrates that vFFR can be computed using 3D-CFD with up to 28-fold acceleration than previous techniques with no clinically significant sacrifice in accuracy.

The importance of three dimensional coronary artery reconstruction accuracy when computing virtual fractional flow reserve from invasive angiography.

Three dimensional (3D) coronary anatomy, reconstructed from coronary angiography (CA), is now being used as the basis to compute 'virtual' fractional flow reserve (vFFR), and thereby guide treatment decisions in patients with coronary artery disease (CAD). Reconstruction accuracy is therefore important. Yet the methods required remain poorly validated. Furthermore, the magnitude of vFFR error arising from reconstruction is unkown. We aimed to validate a method for 3D CA reconstruction and determine the effect this had upon the accuracy of vFFR. Clinically realistic coronary phantom models were created comprosing seven standard stenoses in aluminium and 15 patient-based 3D-printed, imaged with CA, three times, according to standard clinical protocols, yielding 66 datasets. Each was reconstructed using epipolar line projection and intersection. All reconstructions were compared against the real phantom models in terms of minimal lumen diameter, centreline and surface similarity. 3D-printed reconstructions (n = 45) and the reference files from which they were printed underwent vFFR computation, and the results were compared. The average error in reconstructing minimum lumen diameter (MLD) was 0.05 (± 0.03 mm) which was < 1% (95% CI 0.13-1.61%) compared with caliper measurement. Overall surface similarity was excellent (Hausdorff distance 0.65 mm). Errors in 3D CA reconstruction accounted for an error in vFFR of ± 0.06 (Bland Altman 95% limits of agreement). Errors arising from the epipolar line projection method used to reconstruct 3D coronary anatomy from CA are small but contribute to clinically relevant errors when used to compute vFFR.

Operator-dependent variability of angiography-derived fractional flow reserve and the implications for treatment.

AIMS: To extend the benefits of physiologically guided percutaneous coronary intervention to many more patients, angiography-derived, or 'virtual' fractional flow reserve (vFFR) has been developed, in which FFR is computed, based upon the images, instead of being measured invasively. The effect of operator experience with these methods upon vFFR accuracy remains unknown. We investigated variability in vFFR results based upon operator experience with image-based computational modelling techniques. METHODS AND RESULTS: Virtual fractional flow reserve was computed using a proprietary method (VIRTUheart) from the invasive angiograms of patients with coronary artery disease. Each case was processed by an expert (>100 vFFR cases) and a non-expert (<20 vFFR cases) operator and results were compared. The primary outcome was the variability in vFFR between experts and non-experts and the impact this had upon treatment strategy (PCI vs. conservative management). Two hundred and thirty-one vessels (199 patients) were processed. Mean non-expert and expert vFFRs were similar overall [0.76 (0.13) and 0.77 (0.16)] but there was significant variability between individual results (variability coefficient 12%, intraclass correlation coefficient 0.58), with only moderate agreement (κ = 0.46), and this led to a statistically significant change in management strategy in 27% of cases. Variability was significantly lower, and agreement higher, for expert operators; a change in their recommended management occurred in 10% of repeated expert measurements and 14% of inter-expert measurements. CONCLUSION: Virtual fractional flow reserve results are influenced by operator experience of vFFR processing. This had implications for treatment allocation. These results highlight the importance of training and quality assurance to ensure reliable, repeatable vFFR results.

Using VR to Investigate the Relationship between Visual Acuity and Severity of Simulated Oscillopsia.

PURPOSE: Oscillopsia is a debilitating symptom resulting from involuntary eye movement most commonly associated with acquired nystagmus. Investigating and documenting the effects of oscillopsia severity on visual acuity (VA) is challenging. This paper aims to further understanding of the effects of oscillopsia using a virtual reality simulation. METHODS: Fifteen right-beat horizontal nystagmus waveforms, with different amplitude (1°, 3°, 5°, 8° and 11°) and frequency (1.25 Hz, 2.5 Hz and 5 Hz) combinations, were produced and imported into virtual reality to simulate different severities of oscillopsia. Fifty participants without ocular pathology were recruited to read logMAR charts in virtual reality under stationary conditions (no oscillopsia) and subsequently while experiencing simulated oscillopsia. The change in VA (logMAR) was calculated for each oscillopsia simulation (logMAR VA with oscillopsia - logMAR VA with no oscillopsia), removing the influence of different baseline VAs between participants. A one-tailed paired t-test was used to assess statistical significance in the worsening in VA caused by the oscillopsia simulations. RESULTS: VA worsened with each incremental increase in simulated oscillopsia intensity (frequency x amplitude), either by increasing frequency or amplitude, with the exception of statistically insignificant changes at lower intensity simulations. Theoretical understanding predicted a linear relationship between increasing oscillopsia intensity and worsening VA. This was supported by observations at lower intensity simulations but not at higher intensities, with incremental changes in VA gradually levelling off. A potential reason for the difference at higher intensities is the influence of frame rate when using digital simulations in virtual reality. CONCLUSIONS: The frequency and amplitude were found to equally affect VA, as predicted. These results not only consolidate the assumption that VA degrades with oscillopsia but also provide quantitative information that relates these changes to amplitude and frequency of oscillopsia.

Measurement of in vitro cardiac deformation by means of 3D digital image correlation and ultrasound 2D speckle-tracking echocardiography.

Ultrasound-based 2D speckle-tracking echocardiography (US-2D-STE) is increasingly used to assess the functionality of the heart. In particular, the analysis of cardiac strain plays an important role in the identification of several cardiovascular diseases. However, this imaging technique presents some limitations associated with its operating principle that result in low accuracy and reproducibility of the measurement. In this study, an experimental framework for multimodal strain imaging in an in vitro porcine heart was developed. Specifically, the aim of this work was to analyse displacement and strain in the heart by means of 3D digital image correlation (3D-DIC) and US-2D-STE. Over a single cardiac cycle, displacement values obtained from the two techniques were in strong correlation, although systematically larger displacements were observed with 3D-DIC. Notwithstanding an absolute comparison of the strain measurements was not possible to achieve between the two methods, maximum principal strain directions computed with 3D-DIC were consistent with the longitudinal and circumferential strain distribution measured with US-2D-STE. 3D-DIC confirmed its high repeatability in quantifying displacement and strain over multiple cardiac cycles, unlike US-2D-STE which is affected by accumulated errors over time (i.e. drift). To conclude, this study demonstrates the potential of 3D-DIC to perform dynamic measurement of displacement and strain during heart deformations and supports future applications of this method in ex vivo beating heart platforms, which replicate more fully the complex contraction of the heart.

A complex flow phantom for medical imaging: ring vortex phantom design and technical specification.

Cardiovascular fluid dynamics exhibit complex flow patterns, such as recirculation and vortices. Quantitative analysis of these complexities supports diagnosis, leading to early prediction of pathologies. Quality assurance of technologies that image such flows is challenging but essential, and to this end, a novel, cost-effective, portable, complex flow phantom is proposed and the design specifications are provided. The vortex ring is the flow of choice because it offers patterns comparable to physiological flows and is stable, predictable, reproducible and controllable. This design employs a piston/cylinder system for vortex ring generation, coupled to an imaging tank full of fluid, for vortex propagation. The phantom is motor-driven and by varying piston speed, piston displacement and orifice size, vortex rings with different characteristics can be produced. Two measurement methods, namely Laser-PIV and an optical/video technique, were used to test the phantom under a combination of configurations. Vortex rings with a range of travelling velocities (approximately 1-80 cm/s) and different output-orifice diameters (10-25 mm) were produced with reproducibility typically better than ±10%. Although ultrasound compatibility has been demonstrated, longer-term ambitions include adapting the design to support comparative studies with different modalities, such as MRA and X-ray-CTA.

Full-field analysis of epicardial strain in an in vitro porcine heart platform.

The quantitative assessment of cardiac strain is increasingly performed to provide valuable insights on heart function. Currently, the most frequently used technique in the clinic is ultrasound-based speckle tracking echocardiography (STE). However, verification and validation of this modality are still under investigation and further reference measurements are required to support this activity. The aim of this work was to enable these reference measurements using a dynamic beating heart simulator to ensure reproducible, controlled, and realistic haemodynamic conditions and to validate the reliability of optical-based three-dimensional digital image correlation (3D-DIC) for a dynamic full-field analysis of epicardial strain. Specifically, performance assessment of 3D-DIC was carried out by evaluating the accuracy and repeatability of the strain measurements across multiple cardiac cycles in a single heart and between five hearts. Moreover, the ability of this optical method to differentiate strain variations when different haemodynamic conditions were imposed in the same heart was examined. Strain measurements were successfully accomplished in a region of the lateral left ventricle surface. Results were highly repeatable over heartbeats and across hearts (intraclass correlation coefficient = 0.99), whilst strain magnitude was significantly different between hearts, due to change in anatomy and wall thickness. Within an individual heart, strain variations between different haemodynamic scenarios were greater than the estimated error of the measurement technique. This study demonstrated the feasibility of applying 3D-DIC in a dynamic passive heart simulator. Most importantly, non-contact measurements were obtained at a high spatial resolution (~ 1.5 mm) allowing resolution of local variation of strain on the epicardial surface during ventricular filling. The experimental framework developed in this paper provides detailed measurement of cardiac strains under controlled conditions, as a reference for validation of clinical cardiac strain imaging modalities.

The challenge of clinical adoption-the insurmountable obstacle that will stop machine learning?

Machine learning promises much in the field of radiology, both in terms of software that can directly analyse patient data and algorithms that can automatically perform other processes in the reporting pipeline. However, clinical practice remains largely untouched by such technology. This article highlights what we consider to be the major obstacles to widespread clinical adoption of machine learning software, namely: representative data and evidence, regulations, health economics, heterogeneity of the clinical environment and support and promotion. We argue that these issues are currently so substantial that machine learning will struggle to find acceptance beyond the narrow group of applications where the potential benefits are readily evident. In order that machine learning can fulfil its potential in radiology, a radical new approach is needed, where significant resources are directed at reducing impediments to translation rather than always being focused solely on development of the technology itself.

Computer-aided diagnosis for (123I)FP-CIT imaging: impact on clinical reporting.

BACKGROUND: For (123I)FP-CIT imaging, a number of algorithms have shown high performance in distinguishing normal patient images from those with disease, but none have yet been tested as part of reporting workflows. This study aims to evaluate the impact on reporters' performance of a computer-aided diagnosis (CADx) tool developed from established machine learning technology. Three experienced (123I)FP-CIT reporters (two radiologists and one clinical scientist) were asked to visually score 155 reconstructed clinical and research images on a 5-point diagnostic confidence scale (read 1). Once completed, the process was then repeated (read 2). Immediately after submitting each image score for a second time, the CADx system output was displayed to reporters alongside the image data. With this information available, the reporters submitted a score for the third time (read 3). Comparisons between reads 1 and 2 provided evidence of intra-operator reliability, and differences between reads 2 and 3 showed the impact of the CADx. RESULTS: The performance of all reporters demonstrated a degree of variability when analysing images through visual analysis alone. However, inclusion of CADx improved consistency between reporters, for both clinical and research data. The introduction of CADx increased the accuracy of the radiologists when reporting (unfamiliar) research images but had less impact on the clinical scientist and caused no significant change in accuracy for the clinical data. CONCLUSIONS: The outcomes for this study indicate the value of CADx as a diagnostic aid in the clinic and encourage future development for more refined incorporation into clinical practice.

The subresolution DaTSCAN phantom: a cost-effective, flexible alternative to traditional phantom technology.

The Alderson striatal phantom is frequently used to assess I-FP-CIT (Ioflupane) image quality and to test semi-quantification software. However, its design is associated with a number of limitations, in particular: unrealistic image appearances and inflexibility. A new physical phantom approach is proposed on the basis of subresolution phantom technology. The design incorporates thin slabs of attenuating material generated through additive manufacturing, and paper sheets with radioactive ink patterns printed on their surface, created with a conventional inkjet printer. The paper sheets and attenuating slabs are interleaved before scanning. Use of thin layers ensures that they cannot be individually resolved on reconstructed images. An investigation was carried out to demonstrate the performance of such a phantom in producing simplified I-FP-CIT uptake patterns. Single photon emission computed tomography imaging was carried out on an assembled phantom designed to mimic a healthy patient. Striatal binding ratio results and linear striatal dimensions were calculated from the reconstructed data and compared with that of 22 clinical patients without evidence of Parkinsonian syndrome, determined from clinical follow-up. Striatal binding ratio results for the fully assembled phantom were: 3.1, 3.3, 2.9 and 2.6 for the right caudate, left caudate, right putamen and right caudate, respectively. All were within two SDs of results derived from a cohort of clinical patients. Medial-lateral and anterior-posterior dimensions of the simulated striata were also within the range of values seen in clinical data. This work provides the foundation for the generation of a range of more clinically realistic, physical phantoms.

Simulation of Oscillopsia in Virtual Reality.

PURPOSE: Nystagmus is characterised by involuntary eye movement. A proportion of those with nystagmus experience the world constantly in motion as their eyes move: a symptom known as oscillopsia. Individuals with oscillopsia can be incapacitated and often feel neglected due to limited treatment options. Effective communication of the condition is challenging and no tools to aid communication exist. This paper describes a virtual reality (VR) application that recreates the effects of oscillopsia, enabling others to appreciate the condition. METHODS: Eye tracking data was incorporated into a VR oscillopsia simulator and released as a smartphone app - "Nystagmus Oscillopsia Sim VR". When a smartphone is used in conjunction with a Google Cardboard headset, it presents an erratic image consistent with oscillopsia. The oscillopsia simulation was appraised by six participants for its representativeness. These individuals have nystagmus and had previously experienced oscillopsia but were not currently symptomatic; they were therefore uniquely placed to judge the app. The participants filled in a questionnaire to record impressions and the usefulness of the app. RESULTS: The published app has been downloaded ~3700 times (28/02/2018) and received positive feedback from the nystagmus community. The validation study questionnaire scored the accuracy of the simulation an average of 7.8/10 while its ability to aid communication received 9.2/10. CONCLUSION: The evidence indicates that the simulation can effectively recreate the sensation of oscillopsia and facilitate effective communication of the symptoms associated with the condition. This has implications for communication of other visual conditions.

Comparison of machine learning and semi-quantification algorithms for (I123)FP-CIT classification: the beginning of the end for semi-quantification?

BACKGROUND: Semi-quantification methods are well established in the clinic for assisted reporting of (I123) Ioflupane images. Arguably, these are limited diagnostic tools. Recent research has demonstrated the potential for improved classification performance offered by machine learning algorithms. A direct comparison between methods is required to establish whether a move towards widespread clinical adoption of machine learning algorithms is justified. This study compared three machine learning algorithms with that of a range of semi-quantification methods, using the Parkinson's Progression Markers Initiative (PPMI) research database and a locally derived clinical database for validation. Machine learning algorithms were based on support vector machine classifiers with three different sets of features: Voxel intensities Principal components of image voxel intensities Striatal binding radios from the putamen and caudate. Semi-quantification methods were based on striatal binding ratios (SBRs) from both putamina, with and without consideration of the caudates. Normal limits for the SBRs were defined through four different methods: Minimum of age-matched controls Mean minus 1/1.5/2 standard deviations from age-matched controls Linear regression of normal patient data against age (minus 1/1.5/2 standard errors) Selection of the optimum operating point on the receiver operator characteristic curve from normal and abnormal training data Each machine learning and semi-quantification technique was evaluated with stratified, nested 10-fold cross-validation, repeated 10 times. RESULTS: The mean accuracy of the semi-quantitative methods for classification of local data into Parkinsonian and non-Parkinsonian groups varied from 0.78 to 0.87, contrasting with 0.89 to 0.95 for classifying PPMI data into healthy controls and Parkinson's disease groups. The machine learning algorithms gave mean accuracies between 0.88 to 0.92 and 0.95 to 0.97 for local and PPMI data respectively. CONCLUSIONS: Classification performance was lower for the local database than the research database for both semi-quantitative and machine learning algorithms. However, for both databases, the machine learning methods generated equal or higher mean accuracies (with lower variance) than any of the semi-quantification approaches. The gain in performance from using machine learning algorithms as compared to semi-quantification was relatively small and may be insufficient, when considered in isolation, to offer significant advantages in the clinical context.

Computer model for the cardiovascular system: development of an e-learning tool for teaching of medical students.

BACKGROUND: This study combined themes in cardiovascular modelling, clinical cardiology and e-learning to create an on-line environment that would assist undergraduate medical students in understanding key physiological and pathophysiological processes in the cardiovascular system. METHODS: An interactive on-line environment was developed incorporating a lumped-parameter mathematical model of the human cardiovascular system. The model outputs were used to characterise the progression of key disease processes and allowed students to classify disease severity with the aim of improving their understanding of abnormal physiology in a clinical context. Access to the on-line environment was offered to students at all stages of undergraduate training as an adjunct to routine lectures and tutorials in cardiac pathophysiology. Student feedback was collected on this novel on-line material in the course of routine audits of teaching delivery. RESULTS: Medical students, irrespective of their stage of undergraduate training, reported that they found the models and the environment interesting and a positive experience. After exposure to the environment, there was a statistically significant improvement in student performance on a series of 6 questions based on cardiovascular medicine, with a 33% and 22% increase in the number of questions answered correctly, p < 0.0001 and p < 0.001 respectively. CONCLUSIONS: Considerable improvement was found in students' knowledge and understanding during assessment after exposure to the e-learning environment. Opportunities exist for development of similar environments in other fields of medicine, refinement of the existing environment and further engagement with student cohorts. This work combines some exciting and developing fields in medical education, but routine adoption of these types of tool will be possible only with the engagement of all stake-holders, from educationalists, clinicians, modellers to, most importantly, medical students.

A novel diagnostic aid for intra-abdominal adhesion detection in cine-MRI: pilot study and initial diagnostic impressions.

OBJECTIVE: A non-invasive diagnostic technique for abdominal adhesions is not currently available. Capture of abdominal motion due to respiration in cine-MRI has shown promise, but is difficult to interpret. This article explores the value of a complimentary diagnostic aid to facilitate the non-invasive detection of abdominal adhesions using cine-MRI. METHOD: An image processing technique was developed to quantify the amount of sliding that occurs between the organs of the abdomen and the abdominal wall in sagittal cine-MRI slices. The technique produces a "sheargram" which depicts the amount of sliding which has occurred over 1-3 respiratory cycles. A retrospective cohort of 52 patients, scanned for suspected adhesions, made 281 cine-MRI sagittal slices available for processing. The resulting sheargrams were reported by two operators and compared with expert clinical judgment of the cine-MRI scans. RESULTS: The sheargram matched clinical judgment in 84% of all sagittal slices and 93-96% of positive adhesions were identified on the sheargram. The sheargram displayed a slight skew towards sensitivity over specificity, with a high positive adhesion detection rate but at the expense of false positives. CONCLUSION: Good correlation between sheargram and absence/presence of inferred adhesions indicates quantification of sliding motion has potential to aid adhesion detection in cine-MRI. ADVANCES IN KNOWLEDGE: This is the first attempt to clinically evaluate a novel image processing technique quantifying the sliding motion of the abdominal contents against the abdominal wall. The results of this pilot study reveal its potential as a diagnostic aid for detection of abdominal adhesions.

A Novel Diagnostic Aid for Detection of Intra-Abdominal Adhesions to the Anterior Abdominal Wall Using Dynamic Magnetic Resonance Imaging.

Introduction. Abdominal adhesions can cause serious morbidity and complicate subsequent operations. Their diagnosis is often one of exclusion due to a lack of a reliable, non-invasive diagnostic technique. Development and testing of a candidate technique are described below. Method. During respiration, smooth visceral sliding motion occurs between the abdominal contents and the walls of the abdominal cavity. We describe a technique involving image segmentation and registration to calculate shear as an analogue for visceral slide based on the tracking of structures throughout the respiratory cycle. The presence of an adhesion is attributed to a resistance to visceral slide resulting in a discernible reduction in shear. The abdominal movement due to respiration is captured in sagittal dynamic MR images. Results. Clinical images were selected for analysis, including a patient with a surgically confirmed adhesion. Discernible reduction in shear was observed at the location of the adhesion while a consistent, gradually changing shear was observed in the healthy volunteers. Conclusion. The technique and its validation show encouraging results for adhesion detection but a larger study is now required to confirm its potential.

A study to quantify the effect of patient motion and develop methods to detect and correct for motion during myocardial perfusion imaging on a CZT solid-state dedicated cardiac camera.

BACKGROUND: Due to differences in the design and acquisition parameters on the solid-state CZT cardiac camera the effect of patient motion may vary compared to Anger cameras. This study evaluates the effect of motion, two new methods of three-dimensional (3D) motion detection and a method of motion correction. METHOD: Phantom acquisitions were offset in the X, Y, and Z directions and combined to simulate different types of motion. Motion artifacts were identified using the total perfusion defect and blinded visual interpretation. Motion was detected by registering planar and reconstructed 30 second images, and corrected by summing the aligned reconstructed images. Validation was performed on phantom data. These techniques were then applied to 40 patient studies. RESULTS: Motion ≥10 mm and ≥60 seconds in duration introduced significant artifacts. There was no significant difference (P = .258) between the two methods of motion detection. Motion correction removed artifacts from 9/10 phantom simulations. Superior-inferior motion ≥8 mm was measured on 10% of patient studies, and 5% were affected by motion. Motion in the lateral and anterior-posterior directions was <8 mm. CONCLUSION: Superior-inferior patient motion artifacts have been identified on myocardial perfusion images acquired on a CZT camera. Routine QC to identify studies with significant motion is recommended.

Measurement of in vitro and in vivo stent geometry and deformation by means of 3D imaging and stereo-photogrammetry.

PURPOSE: To quantify variability of in vitro and in vivo measurement of 3D device geometry using 3D and biplanar imaging. METHODS: Comparison of stent reconstruction is reported for in vitro coronary stent deployment (using micro-CT and optical stereo-photogrammetry) and in vivo pulmonary valve stent deformation (using 4DCT and biplanar fluoroscopy). Coronary stent strut length and inter-strut angle were compared in the fully deployed configuration. Local (inter-strut angle) and global (dog-boning ratio) measures of stent deformation were reported during stent deployment. Pulmonary valve stent geometry was assessed throughout the cardiac cycle by reconstruction of stent geometry and measurement of stent diameter. RESULTS: Good agreement was obtained between methods for assessment of coronary stent geometry with maximum disagreement of +/- 0.03 mm (length) and +/- 3 degrees (angle). The stent underwent large, non-uniform, local deformations during balloon inflation, which did not always correlate with changes in stent diameter. Three-dimensional reconstruction of the pulmonary valve stent was feasible for all frames of the fluoroscopy and for 4DCT images, with good correlation between the diameters calculated from the two methods. The largest compression of the stent during the cardiac cycle was 6.98% measured from fluoroscopy and 7.92% from 4DCT, both in the most distal ring. CONCLUSIONS: Quantitative assessment of stent geometry reconstructed from biplanar imaging methods in vitro and in vivo has shown good agreement with geometry reconstructed from 3D techniques. As a result of their short image acquisition time, biplanar methods may have significant advantages in the measurement of dynamic 3D stent deformation.

Uncertainty assessment of imaging techniques for the 3D reconstruction of stent geometry.

This paper presents a quantitative assessment of uncertainty for the 3D reconstruction of stents. This study investigates a CP stent (Numed, USA) used in congenital heart disease applications with a focus on the variance in measurements of stent geometry. The stent was mounted on a model of patient implantation site geometry, reconstructed from magnetic resonance images, and imaged using micro-computed tomography (CT), conventional CT, biplane fluoroscopy and optical stereo-photogrammetry. Image data were post-processed to retrieve the 3D stent geometry. Stent strut length, separation angle and cell asymmetry were derived and repeatability was assessed for each technique along with variation in relation to µCT data, assumed to represent the gold standard. The results demonstrate the performance of biplanar reconstruction methods is comparable with volumetric CT scans in evaluating 3D stent geometry. Uncertainty on the evaluation of strut length, separation angle and cell asymmetry using biplanar fluoroscopy is of the order ±0.2mm, 3° and 0.03, respectively. These results support the use of biplanar fluoroscopy for in vivo measurement of 3D stent geometry and provide quantitative assessment of uncertainty in the measurement of geometric parameters.

Towards radiological diagnosis of abdominal adhesions based on motion signatures derived from sequences of cine-MRI images.

This paper reports novel development and preliminary application of an image registration technique for diagnosis of abdominal adhesions imaged with cine-MRI (cMRI). Adhesions can severely compromise the movement and physiological function of the abdominal contents, and their presence is difficult to detect. The image registration approach presented here is designed to expose anomalies in movement of the abdominal organs, providing a movement signature that is indicative of underlying structural abnormalities. Validation of the technique was performed using structurally based in vitro and in silico models, supported with Receiver Operating Characteristic (ROC) methods. For the more challenging cases presented to the small cohort of 4 observers, the AUC (area under curve) improved from a mean value of 0.67 ± 0.02 (without image registration assistance) to a value of 0.87 ± 0.02 when image registration support was included. Also, in these cases, a reduction in time to diagnosis was observed, decreasing by between 20% and 50%. These results provided sufficient confidence to apply the image registration diagnostic protocol to sample magnetic resonance imaging data from healthy volunteers as well as a patient suffering from encapsulating peritoneal sclerosis (an extreme form of adhesions) where immobilization of the gut by cocooning of the small bowel is observed. The results as a whole support the hypothesis that movement analysis using image registration offers a possible method for detecting underlying structural anomalies and encourages further investigation.

A vision and strategy for the virtual physiological human: 2012 update.

European funding under Framework 7 (FP7) for the virtual physiological human (VPH) project has been in place now for 5 years. The VPH Network of Excellence (NoE) has been set up to help develop common standards, open source software, freely accessible data and model repositories, and various training and dissemination activities for the project. It is also working to coordinate the many clinically targeted projects that have been funded under the FP7 calls. An initial vision for the VPH was defined by the FP6 STEP project in 2006. In 2010, we wrote an assessment of the accomplishments of the first two years of the VPH in which we considered the biomedical science, healthcare and information and communications technology challenges facing the project (Hunter et al. 2010 Phil. Trans. R. Soc. A 368, 2595-2614 (doi:10.1098/rsta.2010.0048)). We proposed that a not-for-profit professional umbrella organization, the VPH Institute, should be established as a means of sustaining the VPH vision beyond the time-frame of the NoE. Here, we update and extend this assessment and in particular address the following issues raised in response to Hunter et al.: (i) a vision for the VPH updated in the light of progress made so far, (ii) biomedical science and healthcare challenges that the VPH initiative can address while also providing innovation opportunities for the European industry, and (iii) external changes needed in regulatory policy and business models to realize the full potential that the VPH has to offer to industry, clinics and society generally.