Disease Progression Modeling in Chronic Obstructive Pulmonary Disease.

Rationale: The decades-long progression of chronic obstructive pulmonary disease (COPD) renders identifying different trajectories of disease progression challenging.Objectives: To identify subtypes of patients with COPD with distinct longitudinal progression patterns using a novel machine-learning tool called "Subtype and Stage Inference" (SuStaIn) and to evaluate the utility of SuStaIn for patient stratification in COPD.Methods: We applied SuStaIn to cross-sectional computed tomography imaging markers in 3,698 Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1-4 patients and 3,479 controls from the COPDGene (COPD Genetic Epidemiology) study to identify subtypes of patients with COPD. We confirmed the identified subtypes and progression patterns using ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) data. We assessed the utility of SuStaIn for patient stratification by comparing SuStaIn subtypes and stages at baseline with longitudinal follow-up data.Measurements and Main Results: We identified two trajectories of disease progression in COPD: a "Tissue→Airway" subtype (n = 2,354, 70.4%), in which small airway dysfunction and emphysema precede large airway wall abnormalities, and an "Airway→Tissue" subtype (n = 988, 29.6%), in which large airway wall abnormalities precede emphysema and small airway dysfunction. Subtypes were reproducible in ECLIPSE. Baseline stage in both subtypes correlated with future FEV1/FVC decline (r = -0.16 [P < 0.001] in the Tissue→Airway group; r = -0.14 [P = 0.011] in the Airway→Tissue group). SuStaIn placed 30% of smokers with normal lung function at elevated stages, suggesting imaging changes consistent with early COPD. Individuals with early changes were 2.5 times more likely to meet COPD diagnostic criteria at follow-up.Conclusions: We demonstrate two distinct patterns of disease progression in COPD using SuStaIn, likely representing different endotypes. One third of healthy smokers have detectable imaging changes, suggesting a new biomarker of "early COPD."

VERDICT-AMICO: Ultrafast fitting algorithm for non-invasive prostate microstructure characterization.

VERDICT (vascular, extracellular and restricted diffusion for cytometry in tumours) estimates and maps microstructural features of cancerous tissue non-invasively using diffusion MRI. The main purpose of this study is to address the high computational time of microstructural model fitting for prostate diagnosis, while retaining utility in terms of tumour conspicuity and repeatability. In this work, we adapt the accelerated microstructure imaging via convex optimization (AMICO) framework to linearize the estimation of VERDICT parameters for the prostate gland. We compare the original non-linear fitting of VERDICT with the linear fitting, quantifying accuracy with synthetic data, and computational time and reliability (performance and precision) in eight patients. We also assess the repeatability (scan-rescan) of the parameters. Comparison of the original VERDICT fitting versus VERDICT-AMICO showed that the linearized fitting (1) is more accurate in simulation for a signal-to-noise ratio of 20 dB; (2) reduces the processing time by three orders of magnitude, from 6.55 seconds/voxel to 1.78 milliseconds/voxel; (3) estimates parameters more precisely; (4) produces similar parametric maps and (5) produces similar estimated parameters with a high Pearson correlation between implementations, r2  > 0.7. The VERDICT-AMICO estimates also show high levels of repeatability. Finally, we demonstrate that VERDICT-AMICO can estimate an extra diffusivity parameter without losing tumour conspicuity and retains the fitting advantages. VERDICT-AMICO provides microstructural maps for prostate cancer characterization in seconds.

VERDICT MRI validation in fresh and fixed prostate specimens using patient-specific moulds for histological and MR alignment.

The VERDICT framework for modelling diffusion MRI data aims to relate parameters from a biophysical model to histological features used for tumour grading in prostate cancer. Validation of the VERDICT model is necessary for clinical use. This study compared VERDICT parameters obtained ex vivo with histology in five specimens from radical prostatectomy. A patient-specific 3D-printed mould was used to investigate the effects of fixation on VERDICT parameters and to aid registration to histology. A rich diffusion data set was acquired in each ex vivo prostate before and after fixation. At both time points, data were best described by a two-compartment model: the model assumes that an anisotropic tensor compartment represents the extracellular space and a restricted sphere compartment models the intracellular space. The effect of fixation on model parameters associated with tissue microstructure was small. The patient-specific mould minimized tissue deformations and co-localized slices, so that rigid registration of MRI to histology images allowed region-based comparison with histology. The VERDICT estimate of the intracellular volume fraction corresponded to histological indicators of cellular fraction, including high values in tumour regions. The average sphere radius from VERDICT, representing the average cell size, was relatively uniform across samples. The primary diffusion direction from the extracellular compartment of the VERDICT model aligned with collagen fibre patterns in the stroma obtained by structure tensor analysis. This confirmed the biophysical relationship between ex vivo VERDICT parameters and tissue microstructure from histology.

Growth Trajectories, Breast Size, and Breast-Tissue Composition in a British Prebirth Cohort of Young Women.

Mammographic percent density, the proportion of fibroglandular tissue in the breast, is a strong risk factor for breast cancer, but its determinants in young women are unknown. We examined associations of magnetic resonance imaging (MRI) breast-tissue composition at age 21 years with prospectively collected measurements of body size and composition from birth to early adulthood and markers of puberty (all standardized) in a sample of 500 nulliparous women from a prebirth cohort of children born in Avon, United Kingdom, in 1991-1992 and followed up to 2011-2014. Linear models were fitted to estimate relative change in MRI percent water, which is equivalent to mammographic percent density, associated with a 1-standard-deviation increase in the exposure of interest. In mutually adjusted analyses, MRI percent water was positively associated with birth weight (relative change (RC) = 1.03, 95% confidence interval (CI): 1.00, 1.06) and pubertal height growth (RC = 1.07, 95% CI: 1.02, 1.13) but inversely associated with pubertal weight growth (RC = 0.86, 95% CI: 0.84, 0.89) and changes in dual-energy x-ray absorptiometry percent body fat mass (e.g., for change between ages 11 years and 13.5 years, RC = 0.96, 95% CI: 0.93, 0.99). Ages at thelarche and menarche were positively associated with MRI percent water, but these associations did not persist upon adjustment for height and weight growth. These findings support the hypothesis that growth trajectories influence breast-tissue composition in young women, whereas puberty plays no independent role.

A Validated Multiscale In-Silico Model for Mechano-sensitive Tumour Angiogenesis and Growth.

Vascularisation is a key feature of cancer growth, invasion and metastasis. To better understand the governing biophysical processes and their relative importance, it is instructive to develop physiologically representative mathematical models with which to compare to experimental data. Previous studies have successfully applied this approach to test the effect of various biochemical factors on tumour growth and angiogenesis. However, these models do not account for the experimentally observed dependency of angiogenic network evolution on growth-induced solid stresses. This work introduces two novel features: the effects of hapto- and mechanotaxis on vessel sprouting, and mechano-sensitive dynamic vascular remodelling. The proposed three-dimensional, multiscale, in-silico model of dynamically coupled angiogenic tumour growth is specified to in-vivo and in-vitro data, chosen, where possible, to provide a physiologically consistent description. The model is then validated against in-vivo data from murine mammary carcinomas, with particular focus placed on identifying the influence of mechanical factors. Crucially, we find that it is necessary to include hapto- and mechanotaxis to recapitulate observed time-varying spatial distributions of angiogenic vasculature.

Microstructural models for diffusion MRI in breast cancer and surrounding stroma: an ex vivo study.

The diffusion signal in breast tissue has primarily been modelled using apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) and diffusion tensor (DT) models, which may be too simplistic to describe the underlying tissue microstructure. Formalin-fixed breast cancer samples were scanned using a wide range of gradient strengths, durations, separations and orientations. A variety of one- and two-compartment models were tested to determine which best described the data. Models with restricted diffusion components and anisotropy were selected in most cancerous regions and there were no regions in which conventional ADC or DT models were selected. Maps of ADC generally related to cellularity on histology, but maps of parameters from more complex models suggest that both overall cell volume fraction and individual cell size can contribute to the diffusion signal, affecting the specificity of ADC to the tissue microstructure. The areas of coherence in diffusion anisotropy images were small, approximately 1 mm, but the orientation corresponded to stromal orientation patterns on histology.

Identification of liver metastases with probe-based confocal laser endomicroscopy at two excitation wavelengths.

BACKGROUND: Metastasis of colorectal cancer to the liver is the most common indication for hepatic resection in a western population. Incomplete excision of malignancy due to residual microscopic disease normally results in worse patient outcome. Therefore, a method aiding in the real time discrimination of normal and malignant tissue on a microscopic level would be of benefit. MATERIAL AND METHODS: The ability of fluorescent probe-based confocal laser endomicroscopy (pCLE) to identify normal and malignant liver tissue was evaluated in an orthotopic murine model of colorectal cancer liver metastasis (CRLM). To maximise information yield, two clinical fluorophores, fluorescein and indocyanine green (ICG) were injected and imaged in a dual wavelength approach (488 and 660 nm, respectively). Visual tissue characteristics on pCLE examination were compared with histological features. Fluorescence intensity in both tissues was statistically analysed to elucidate if this can be used to differentiate between normal and malignant tissue. RESULTS: Fluorescein (488 nm) enabled good visualisation of normal and CRLM tissue, whereas ICG (660 nm) visualisation was limited to normal liver tissue only. Fluorescence intensity in areas of CRLM was typically 53-100% lower than normal hepatic parenchyma. Using general linear mixed modelling and receiver operating characteristic analysis, high fluorescence intensity was found to be statistically more likely in normal hepatic tissue. CONCLUSION: Real time discrimination between normal liver parenchyma and metastatic tissue with pCLE examination of fluorescein and ICG is feasible. Employing two (rather than a single) fluorophores allows a combination of qualitative and quantitative characteristics to be used to distinguish between hepatic parenchyma and CRLM. Lasers Surg. Med. 49:280-292, 2017. © 2016 Wiley Periodicals, Inc.

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.

Design, operation, and safety of single-room interventional MRI suites: practical experience from two centers.

The design and operation of a facility in which a magnetic resonance imaging (MRI) scanner is incorporated into a room used for surgical or endovascular cardiac interventions presents several challenges. MR safety must be maintained in the presence of a much wider variety of equipment than is found in a diagnostic unit, and of staff unfamiliar with the MRI environment, without compromising the safety and practicality of the interventional procedure. Both the MR-guided cardiac interventional unit at Kings College London and the intraoperative imaging suite at the National Hospital for Neurology and Neurosurgery are single-room interventional facilities incorporating 1.5 T cylindrical-bore MRI scanners. The two units employ similar strategies to maintain MR safety, both in original design and day-to-day operational workflows, and between them over a decade of incident-free practice has been accumulated. This article outlines these strategies, highlighting both similarities and differences between the units, as well as some lessons learned and resulting procedural changes made in both units since installation.

CT colonography: clinical evaluation of a method for automatic coregistration of polyps at follow-up surveillance studies.

PURPOSE: To evaluate the accuracy of a method of automatic coregistration of the endoluminal surfaces at computed tomographic (CT) colonography performed on separate occasions to facilitate identification of polyps in patients undergoing polyp surveillance. MATERIALS AND METHODS: Institutional review board and HIPAA approval were obtained. A registration algorithm that was designed to coregister the coordinates of endoluminal colonic surfaces on images from prone and supine CT colonographic acquisitions was used to match polyps in sequential studies in patients undergoing polyp surveillance. Initial and follow-up CT colonographic examinations in 26 patients (35 polyps) were selected and the algorithm was tested by means of two methods, the longitudinal method (polyp coordinates from the initial prone and supine acquisitions were used to identify the expected polyp location automatically at follow-up CT colonography) and the consistency method (polyp coordinates from the initial supine acquisition were used to identify polyp location on images from the initial prone acquisition, then on those for follow-up prone and follow-up supine acquisitions). Two observers measured the Euclidean distance between true and expected polyp locations, and mean per-patient registration accuracy was calculated. Segments with and without collapse were compared by using the Kruskal-Wallace test, and the relationship between registration error and temporal separation was investigated by using the Pearson correlation. RESULTS: Coregistration was achieved for all 35 polyps by using both longitudinal and consistency methods. Mean ± standard deviation Euclidean registration error for the longitudinal method was 17.4 mm ± 12.1 and for the consistency method, 26.9 mm ± 20.8. There was no significant difference between these results and the registration error when prone and supine acquisitions in the same study were compared (16.9 mm ± 17.6; P = .451). CONCLUSION: Automatic endoluminal coregistration by using an algorithm at initial CT colonography allowed prediction of endoluminal polyp location at subsequent CT colonography, thereby facilitating detection of known polyps in patients undergoing CT colonographic surveillance.

CT colonography: external clinical validation of an algorithm for computer-assisted prone and supine registration.

PURPOSE: To perform external validation of a computer-assisted registration algorithm for prone and supine computed tomographic (CT) colonography and to compare the results with those of an existing centerline method. MATERIALS AND METHODS: All contributing centers had institutional review board approval; participants provided informed consent. A validation sample of CT colonographic examinations of 51 patients with 68 polyps (6-55 mm) was selected from a publicly available, HIPAA compliant, anonymized archive. No patients were excluded because of poor preparation or inadequate distension. Corresponding prone and supine polyp coordinates were recorded, and endoluminal surfaces were registered automatically by using a computer algorithm. Two observers independently scored three-dimensional endoluminal polyp registration success. Results were compared with those obtained by using the normalized distance along the colonic centerline (NDACC) method. Pairwise Wilcoxon signed rank tests were used to compare gross registration error and McNemar tests were used to compare polyp conspicuity. RESULTS: Registration was possible in all 51 patients, and 136 paired polyp coordinates were generated (68 polyps) to test the algorithm. Overall mean three-dimensional polyp registration error (mean ± standard deviation, 19.9 mm ± 20.4) was significantly less than that for the NDACC method (mean, 27.4 mm ± 15.1; P = .001). Accuracy was unaffected by colonic segment (P = .76) or luminal collapse (P = .066). During endoluminal review by two observers (272 matching tasks, 68 polyps, prone to supine and supine to prone coordinates), 223 (82%) polyp matches were visible (120° field of view) compared with just 129 (47%) when the NDACC method was used (P < .001). By using multiplanar visualization, 48 (70%) polyps were visible after scrolling ± 15 mm in any multiplanar axis compared with 16 (24%) for NDACC (P < .001). CONCLUSION: Computer-assisted registration is more accurate than the NDACC method for mapping the endoluminal surface and matching the location of polyps in corresponding prone and supine CT colonographic acquisitions.

The value of Augmented Reality in surgery - A usability study on laparoscopic liver surgery.

Augmented Reality (AR) is considered to be a promising technology for the guidance of laparoscopic liver surgery. By overlaying pre-operative 3D information of the liver and internal blood vessels on the laparoscopic view, surgeons can better understand the location of critical structures. In an effort to enable AR, several authors have focused on the development of methods to obtain an accurate alignment between the laparoscopic video image and the pre-operative 3D data of the liver, without assessing the benefit that the resulting overlay can provide during surgery. In this paper, we present a study that aims to assess quantitatively and qualitatively the value of an AR overlay in laparoscopic surgery during a simulated surgical task on a phantom setup. We design a study where participants are asked to physically localise pre-operative tumours in a liver phantom using three image guidance conditions - a baseline condition without any image guidance, a condition where the 3D surfaces of the liver are aligned to the video and displayed on a black background, and a condition where video see-through AR is displayed on the laparoscopic video. Using data collected from a cohort of 24 participants which include 12 surgeons, we observe that compared to the baseline, AR decreases the median localisation error of surgeons on non-peripheral targets from 25.8 mm to 9.2 mm. Using subjective feedback, we also identify that AR introduces usability improvements in the surgical task and increases the perceived confidence of the users. Between the two tested displays, the majority of participants preferred to use the AR overlay instead of navigated view of the 3D surfaces on a separate screen. We conclude that AR has the potential to improve performance and decision making in laparoscopic surgery, and that improvements in overlay alignment accuracy and depth perception should be pursued in the future.

Delineating COVID-19 subgroups using routine clinical data identifies distinct in-hospital outcomes.

The COVID-19 pandemic has been a great challenge to healthcare systems worldwide. It highlighted the need for robust predictive models which can be readily deployed to uncover heterogeneities in disease course, aid decision-making and prioritise treatment. We adapted an unsupervised data-driven model-SuStaIn, to be utilised for short-term infectious disease like COVID-19, based on 11 commonly recorded clinical measures. We used 1344 patients from the National COVID-19 Chest Imaging Database (NCCID), hospitalised for RT-PCR confirmed COVID-19 disease, splitting them equally into a training and an independent validation cohort. We discovered three COVID-19 subtypes (General Haemodynamic, Renal and Immunological) and introduced disease severity stages, both of which were predictive of distinct risks of in-hospital mortality or escalation of treatment, when analysed using Cox Proportional Hazards models. A low-risk Normal-appearing subtype was also discovered. The model and our full pipeline are available online and can be adapted for future outbreaks of COVID-19 or other infectious disease.

A biopsy simulation study to assess the accuracy of several transrectal ultrasonography (TRUS)-biopsy strategies compared with template prostate mapping biopsies in patients who have undergone radical prostatectomy.

UNLABELLED: What's known on the subject? and What does the study add? Transrectal ultrasonography (TRUS)-guided biopsies can miss prostate cancer and misclassify risk in a diagnostic setting; the exact extent to which it does so in a repeat biopsy strategy in men with low-intermediate risk prostate cancer is unknown. A simulation study of different biopsy strategies showed that repeat 12-core TRUS biopsy performs poorly. Adding anterior sampling improves on this but the highest accuracy is achieved using transperineal template prostate mapping using a 5 mm sampling frame. OBJECTIVE: To determine the effectiveness of two sampling strategies; repeat transrectal ultrasonography (TRUS)-biopsy and transperineal template prostate mapping (TPM) to detect and exclude lesions of ≥0.2 mL or ≥0.5 mL using computer simulation on reconstructed three-dimensional (3-D) computer models of radical whole-mount specimens. PATIENTS AND METHODS: Computer simulation on reconstructed 3-D computer models of radical whole-mount specimens was used to evaluate the performance characteristics of repeat TRUS-biopsy and TPM to detect and exclude lesions of ≥0.2 mL or ≥0.5 mL. In all, 107 consecutive cases were analysed (1999-2001) with simulations repeated 500 times for each biopsy strategy. TPM and five different TRUS-biopsy strategies were simulated; the latter involved a standard 12-core sampling and incorporated variable amounts of error, as well as the addition of anterior cores. Sensitivity, specificity, negative and positive predictive values for detection of lesions with a volume of ≥0.2 mL or ≥0.5 mL were calculated. RESULTS: The mean (SD) age and PSA concentration were 61 (6.4) years and 8.5 (5.9) ng/mL, respectively.In all, 53% (57/107) had low-intermediate risk disease. In all, 665 foci were reconstructed; there were 149 foci ≥0.2 mL and 97 ≥ 0.5 mL in the full cohort and 68 ≥ 0.2 mL and 43 ≥ 0.5 mL in the low-intermediate risk group. Overall, TPM accuracy (area under the receiver operating curve, AUC) was ≈0.90 compared with AUC 0.70-0.80 for TRUS-biopsy. In addition, at best, TRUS-biopsy missed 30-40% of lesions of ≥0.2 mL and ≥0.5 mL whilst TPM missed 5% of such lesions. CONCLUSION: TPM under simulation conditions appears the most effective re-classification strategy, although augmented TRUS-biopsy techniques are better than standard TRUS-biopsy.

Magnetic resonance virtual histology for embryos: 3D atlases for automated high-throughput phenotyping.

Ambitious international efforts are underway to produce gene-knockout mice for each of the 25,000 mouse genes, providing a new platform to study mammalian development and disease. Robust, large-scale methods for morphological assessment of prenatal mice will be essential to this work. Embryo phenotyping currently relies on histological techniques but these are not well suited to large volume screening. The qualitative nature of these approaches also limits the potential for detailed group analysis. Advances in non-invasive imaging techniques such as magnetic resonance imaging (MRI) may surmount these barriers. We present a high-throughput approach to generate detailed virtual histology of the whole embryo, combined with the novel use of a whole-embryo atlas for automated phenotypic assessment. Using individual 3D embryo MRI histology, we identified new pituitary phenotypes in Hesx1 mutant mice. Subsequently, we used advanced computational techniques to produce a whole-body embryo atlas from 6 CD-1 embryos, creating an average image with greatly enhanced anatomical detail, particularly in CNS structures. This methodology enabled unsupervised assessment of morphological differences between CD-1 embryos and Chd7 knockout mice (n=5 Chd7(+/+) and n=8 Chd7(+/-), C57BL/6 background). Using a new atlas generated from these three groups, quantitative organ volumes were automatically measured. We demonstrated a difference in mean brain volumes between Chd7(+/+) and Chd7(+/-) mice (42.0 vs. 39.1mm(3), p<0.05). Differences in whole-body, olfactory and normalised pituitary gland volumes were also found between CD-1 and Chd7(+/+) mice (C57BL/6 background). Our work demonstrates the feasibility of combining high-throughput embryo MRI with automated analysis techniques to distinguish novel mouse phenotypes.

Large breast compressions: observations and evaluation of simulations.

PURPOSE: Several methods have been proposed to simulate large breast compressions such as those occurring during x-ray mammography. However, the evaluation of these methods against real data is rare. The aim of this study is to learn more about the deformation behavior of breasts and to assess a simulation method. METHODS: Magnetic resonance (MR) images of 11 breasts before and after applying a relatively large in vivo compression in the medial direction were acquired. Nonrigid registration was employed to study the deformation behavior. Optimal material properties for finite element modeling were determined and their prediction performance was assessed. The realism of simulated compressions was evaluated by comparing the breast shapes on simulated and real mammograms. RESULTS: Following image registration, 19 breast compressions from 8 women were studied. An anisotropic deformation behavior, with a reduced elongation in the anterior-posterior direction and an increased stretch in the inferior-superior direction was observed. Using finite element simulations, the performance of isotropic and transverse isotropic material models to predict the displacement of internal landmarks was compared. Isotropic materials reduced the mean displacement error of the landmarks from 23.3 to 4.7 mm, on average, after optimizing material properties with respect to breast surface alignment and image similarity. Statistically significantly smaller errors were achieved with transverse isotropic materials (4.1 mm, P=0.0045). Homogeneous material models performed substantially worse (transverse isotropic: 5.5 mm; isotropic: 6.7 mm). Of the parameters varied, the amount of anisotropy had the greatest influence on the results. Optimal material properties varied less when grouped by patient rather than by compression magnitude (mean: 0.72 vs. 1.44). Employing these optimal materials for simulating mammograms from ten MR breast images of a different cohort resulted in more realistic breast shapes than when using established material models. CONCLUSIONS: Breasts in the prone position exhibited an anisotropic compression behavior. Transverse isotropic materials with an increased stiffness in the anterior-posterior direction improved the prediction of these deformations and produced more realistic mammogram simulations from MR images.

Registration of the endoluminal surfaces of the colon derived from prone and supine CT colonography.

PURPOSE: Computed tomographic (CT) colonography is a relatively new technique for detecting bowel cancer or potentially precancerous polyps. CT scanning is combined with three-dimensional (3D) image reconstruction to produce a virtual endoluminal representation similar to optical colonoscopy. Because retained fluid and stool can mimic pathology, CT data are acquired with the bowel cleansed and insufflated with gas and patient in both prone and supine positions. Radiologists then match visually endoluminal locations between the two acquisitions in order to determine whether apparent pathology is real or not. This process is hindered by the fact that the colon, essentially a long tube, can undergo considerable deformation between acquisitions. The authors present a novel approach to automatically establish spatial correspondence between prone and supine endoluminal colonic surfaces after surface parameterization, even in the case of local colon collapse. METHODS: The complexity of the registration task was reduced from a 3D to a 2D problem by mapping the surfaces extracted from prone and supine CT colonography onto a cylindrical parameterization. A nonrigid cylindrical registration was then performed to align the full colonic surfaces. The curvature information from the original 3D surfaces was used to determine correspondence. The method can also be applied to cases with regions of local colonic collapse by ignoring the collapsed regions during the registration. RESULTS: Using a development set, suitable parameters were found to constrain the cylindrical registration method. Then, the same registration parameters were applied to a different set of 13 validation cases, consisting of 8 fully distended cases and 5 cases exhibiting multiple colonic collapses. All polyps present were well aligned, with a mean (+/- std. dev.) registration error of 5.7 (+/- 3.4) mm. An additional set of 1175 reference points on haustral folds spread over the full endoluminal colon surfaces resulted in an error of 7.7 (+/- 7.4) mm. Here, 82% of folds were aligned correctly after registration with a further 15% misregistered by just onefold. CONCLUSIONS: The proposed method reduces the 3D registration task to a cylindrical registration representing the endoluminal surface of the colon. Our algorithm uses surface curvature information as a similarity measure to drive registration to compensate for the large colorectal deformations that occur between prone and supine data acquisitions. The method has the potential to both enhance polyp detection and decrease the radiologist's interpretation time.

The A-rich RNA sequences of HIV-1 pol are important for the synthesis of viral cDNA.

The bias of A-rich codons in HIV-1 pol is thought to be a record of hypermutations in viral genomes that lack biological functions. Bioinformatic analysis predicted that A-rich sequences are generally associated with minimal local RNA structures. Using codon modifications to reduce the amount of A-rich sequences within HIV-1 genomes, we have reduced the flexibility of RNA sequences in pol to analyze the functional significance of these A-rich 'structurally poor' RNA elements in HIV-1 pol. Our data showed that codon modification of HIV-1 sequences led to a suppression of virus infectivity by 5-100-fold, and this defect does not correlate with, viral entry, viral protein expression levels, viral protein profiles or virion packaging of genomic RNA. Codon modification of HIV-1 pol correlated with an enhanced dimer stability of the viral RNA genome, which was associated with a reduction of viral cDNA synthesis both during HIV-1 infection and in a cell free reverse transcription assay. Our data provided direct evidence that the HIV-1 A-rich pol sequence is not merely an evolutionary artifact of enzyme-induced hypermutations, and that HIV-1 has adapted to rely on A-rich RNA sequences to support the synthesis of viral cDNA during reverse transcription, highlighting the utility of using 'structurally poor' RNA domains in regulating biological process.

Registration of Untracked 2D Laparoscopic Ultrasound to CT Images of the Liver Using Multi-Labelled Content-Based Image Retrieval.

Laparoscopic Ultrasound (LUS) is recommended as a standard-of-care when performing laparoscopic liver resections as it images sub-surface structures such as tumours and major vessels. Given that LUS probes are difficult to handle and some tumours are iso-echoic, registration of LUS images to a pre-operative CT has been proposed as an image-guidance method. This registration problem is particularly challenging due to the small field of view of LUS, and usually depends on both a manual initialisation and tracking to compose a volume, hindering clinical translation. In this paper, we extend a proposed registration approach using Content-Based Image Retrieval (CBIR), removing the requirement for tracking or manual initialisation. Pre-operatively, a set of possible LUS planes is simulated from CT and a descriptor generated for each image. Then, a Bayesian framework is employed to estimate the most likely sequence of CT simulations that matches a series of LUS images. We extend our CBIR formulation to use multiple labelled objects and constrain the registration by separating liver vessels into portal vein and hepatic vein branches. The value of this new labeled approach is demonstrated in retrospective data from 5 patients. Results show that, by including a series of 5 untracked images in time, a single LUS image can be registered with accuracies ranging from 5.7 to 16.4 mm with a success rate of 78%. Initialisation of the LUS to CT registration with the proposed framework could potentially enable the clinical translation of these image fusion techniques.

Automated registration of diagnostic to prediagnostic x-ray mammograms: evaluation and comparison to radiologists' accuracy.

PURPOSE: To compare and evaluate intensity-based registration methods for computation of serial x-ray mammogram correspondence. METHODS: X-ray mammograms were simulated from MRIs of 20 women using finite element methods for modeling breast compressions and employing a MRI/x-ray appearance change model. The parameter configurations of three registration methods, affine, fluid, and free-form deformation (FFD), were optimized for registering x-ray mammograms on these simulated images. Five mammography film readers independently identified landmarks (tumor, nipple, and usually two other normal features) on pairs of diagnostic and corresponding prediagnostic digitized images from 52 breast cancer cases. Landmarks were independently reidentified by each reader. Target registration errors were calculated to compare the three registration methods using the reader landmarks as a gold standard. Data were analyzed using multilevel methods. RESULTS: Between-reader variability varied with landmark (p < 0.01) and screen (p = 0.03), with between-reader mean distance (mm) in point location on the diagnostic/prediagnostic images of 2.50 (95% CI 1.95, 3.15)/2.84 (2.24, 3.55) for nipples and 4.26 (3.43, 5.24)/4.76 (3.85, 5.84) for tumors. Registration accuracy was sensitive to the type of landmark and the amount of breast density. For dense breasts (> or = 40%), the affine and fluid methods outperformed FFD. For breasts with lower density, the affine registration surpassed both fluid and FFD. Mean accuracy (mm) of the affine registration varied between 3.16 (95% CI 2.56, 3.90) for nipple points in breasts with density 20%-39% and 5.73 (4.80, 6.84) for tumor points in breasts with density < 20%. CONCLUSIONS: Affine registration accuracy was comparable to that between independent film readers. More advanced two-dimensional nonrigid registration algorithms were incapable of increasing the accuracy of image alignment when compared to affine registration.