Reconstruction of difference in sequential CT studies using penalized likelihood estimation

Characterization of anatomical change and other differences is important in sequential computed tomography (CT) imaging, where a high-fidelity patient-specific prior image is typically present, but is not used, in the reconstruction of subsequent anatomical states. Here, we introduce a penalized likelihood (PL) method called reconstruction of difference (RoD) to directly reconstruct a difference image volume using both the current projection data and the (unregistered) prior image integrated into the forward model for the measurement data. The algorithm utilizes an alternating minimization to find both the registration and reconstruction estimates. This formulation allows direct control over the image properties of the difference image, permitting regularization strategies that inhibit noise and structural differences due to inconsistencies between the prior image and the current data. Additionally, if the change is known to be local, RoD allows local acquisition and reconstruction, as opposed to traditional model-based approaches that require a full support field of view (or other modifications). We compared the performance of RoD to a standard PL algorithm, in simulation studies and using test-bench cone-beam CT data. The performances of local and global RoD approaches were similar, with local RoD providing a significant computational speedup. In comparison across a range of data with differing fidelity, the local RoD approach consistently showed lower error (with respect to a truth image) than PL in both noisy data and sparsely sampled projection scenarios. In a study of the prior image registration performance of RoD, a clinically reasonable capture ranges were demonstrated. Lastly, the registration algorithm had a broad capture range and the error for reconstruction of CT data was 35% and 20% less than filtered back-projection for RoD and PL, respectively. The RoD has potential for delivering high-quality difference images in a range of sequential clinical scenarios including image-guided surgeries and treatments where accurate and quantitative assessments of anatomical change is desired.

Statistical reconstruction for cone-beam CT with a post-artifact-correction noise model: application to high-quality head imaging

Non-contrast CT reliably detects fresh blood in the brain and is the current front-line imaging modality for intracranial hemorrhage such as that occurring in acute traumatic brain injury (contrast ~40-80 HU, size  >  1 mm). We are developing flat-panel detector (FPD) cone-beam CT (CBCT) to facilitate such diagnosis in a low-cost, mobile platform suitable for point-of-care deployment. Such a system may offer benefits in the ICU, urgent care/concussion clinic, ambulance, and sports and military theatres. However, current FPD-CBCT systems face significant challenges that confound low-contrast, soft-tissue imaging. Artifact correction can overcome major sources of bias in FPD-CBCT but imparts noise amplification in filtered backprojection (FBP). Model-based reconstruction improves soft-tissue image quality compared to FBP by leveraging a high-fidelity forward model and image regularization. In this work, we develop a novel penalized weighted least-squares (PWLS) image reconstruction method with a noise model that includes accurate modeling of the noise characteristics associated with the two dominant artifact corrections (scatter and beam-hardening) in CBCT and utilizes modified weights to compensate for noise amplification imparted by each correction. Experiments included real data acquired on a FPD-CBCT test-bench and an anthropomorphic head phantom emulating intra-parenchymal hemorrhage. The proposed PWLS method demonstrated superior noise-resolution tradeoffs in comparison to FBP and PWLS with conventional weights (viz. at matched 0.50 mm spatial resolution, CNR = 11.9 compared to CNR = 5.6 and CNR = 9.9, respectively) and substantially reduced image noise especially in challenging regions such as skull base. The results support the hypothesis that with high-fidelity artifact correction and statistical reconstruction using an accurate post-artifact-correction noise model, FPD-CBCT can achieve image quality allowing reliable detection of intracranial hemorrhage.

Cone-Beam CT of Traumatic Brain Injury Using Statistical Reconstruction with a Post-Artifact-Correction Noise Model

Traumatic brain injury (TBI) is a major cause of death and disability. The current front-line imaging modality for TBI detection is CT, which reliably detects intracranial hemorrhage (fresh blood contrast 30-50 HU, size down to 1 mm) in non-contrast-enhanced exams. Compared to CT, flat-panel detector (FPD) cone-beam CT (CBCT) systems offer lower cost, greater portability, and smaller footprint suitable for point-of-care deployment. We are developing FPD-CBCT to facilitate TBI detection at the point-of-care such as in emergent, ambulance, sports, and military applications. However, current FPD-CBCT systems generally face challenges in low-contrast, soft-tissue imaging. Model-based reconstruction can improve image quality in soft-tissue imaging compared to conventional filtered backprojection (FBP) by leveraging high-fidelity forward model and sophisticated regularization. In FPD-CBCT TBI imaging, measurement noise characteristics undergo substantial change following artifact correction, resulting in non-negligible noise amplification. In this work, we extend the penalized weighted least-squares (PWLS) image reconstruction to include the two dominant artifact corrections (scatter and beam hardening) in FPD-CBCT TBI imaging by correctly modeling the variance change following each correction. Experiments were performed on a CBCT test-bench using an anthropomorphic phantom emulating intra-parenchymal hemorrhage in acute TBI, and the proposed method demonstrated an improvement in blood-brain contrast-to-noise ratio (CNR = 14.2) compared to FBP (CNR = 9.6) and PWLS using conventional weights (CNR = 11.6) at fixed spatial resolution (1 mm edge-spread width at the target contrast). The results support the hypothesis that FPD-CBCT can fulfill the image quality requirements for reliable TBI detection, using high-fidelity artifact correction and statistical reconstruction with accurate post-artifact-correction noise models.

Early gene expression in salivary gland after isoproterenol treatment

Isoproterenol, a β-adrenergic agonist, has been shown to induce salivary gland hyperplasia. However, the mechanism involved in this pharmacological phenomenon is not well understood. To gain a better understanding of the underlying changes, including genes, networks and pathways altered by isoproterenol, microarray-based gene expression analysis was conducted on rat parotid glands at 10, 30, and 60 min after isoproterenol injection. After isoproterenol treatment, the number of differentially expressed genes was increased in a time-dependent manner. Pathway analysis showed that cell hyperplasia, p38(MAPK), and IGF-1 were the most altered function, network and pathway, respectively. The balanced regulation of up- and down-expression of genes related to cell proliferation/survival may provide a better understanding of the mechanism of isoproterenol-induced parotid gland enlargement without tumor transformation.

dPIRPLE: a joint estimation framework for deformable registration and penalized-likelihood CT image reconstruction using prior images

Sequential imaging studies are conducted in many clinical scenarios. Prior images from previous studies contain a great deal of patient-specific anatomical information and can be used in conjunction with subsequent imaging acquisitions to maintain image quality while enabling radiation dose reduction (e.g., through sparse angular sampling, reduction in fluence, etc). However, patient motion between images in such sequences results in misregistration between the prior image and current anatomy. Existing prior-image-based approaches often include only a simple rigid registration step that can be insufficient for capturing complex anatomical motion, introducing detrimental effects in subsequent image reconstruction. In this work, we propose a joint framework that estimates the 3D deformation between an unregistered prior image and the current anatomy (based on a subsequent data acquisition) and reconstructs the current anatomical image using a model-based reconstruction approach that includes regularization based on the deformed prior image. This framework is referred to as deformable prior image registration, penalized-likelihood estimation (dPIRPLE). Central to this framework is the inclusion of a 3D B-spline-based free-form-deformation model into the joint registration-reconstruction objective function. The proposed framework is solved using a maximization strategy whereby alternating updates to the registration parameters and image estimates are applied allowing for improvements in both the registration and reconstruction throughout the optimization process. Cadaver experiments were conducted on a cone-beam CT testbench emulating a lung nodule surveillance scenario. Superior reconstruction accuracy and image quality were demonstrated using the dPIRPLE algorithm as compared to more traditional reconstruction methods including filtered backprojection, penalized-likelihood estimation (PLE), prior image penalized-likelihood estimation (PIPLE) without registration, and prior image penalized-likelihood estimation with rigid registration of a prior image (PIRPLE) over a wide range of sampling sparsity and exposure levels.

The healing of dental extraction sockets in patients with Type 2 diabetes on oral hypoglycaemics: a prospective cohort

BACKGROUND

The aim of this study was to determine whether there is a difference in delayed healing following dental extractions for Type 2 diabetics on oral hypoglycaemics and non-diabetic patients.

METHODS

Prospective patients referred for dental extractions were recruited into two groups: known diabetics and non-diabetics with no conditions associated with poor healing. All had a random blood glucose level (BGL). Extractions were performed using local anaesthesia. Delayed healing cases were identified and statistical evaluation performed to identify risk factors.

RESULTS

There were 224 Type 2 diabetics on oral hypoglycaemics (BGL 7.51, range 4.1-17.4) and 232 non-diabetics. The diabetic group were older, more males and less smokers than the control group. Twenty-eight patients, 12 (5%) diabetic and 16 (7%) control group, had socket healing delayed for more than one week but all healed in four weeks. There were no statistical differences between delayed healing and age, gender, diabetic state, BGL or smoking. The younger control group had more healing problems.

CONCLUSIONS

The traditional view that diabetics have increased delayed healing was not supported. Type 2 diabetics on oral hypoglycaemics should be treated the same as non-diabetic patients for extractions.

Overcoming Nonlinear Partial Volume Effects in Known-Component Reconstruction of Cochlear Implants

Nonlinear partial volume (NLPV) effects can be significant for objects with large attenuation differences and fine detail structures near the spatial resolution limits of a tomographic system. This is particularly true for small metal devices like cochlear implants. While traditional model-based approaches might alleviate these artifacts through very fine sampling of the image volume and subsampling of rays to each detector element, such solutions can be extremely burdensome in terms of memory and computational requirements. The work presented in this paper leverages the model-based approach called "known-component reconstruction" (KCR) where prior knowledge of a surgical device is integrated into the estimation. In KCR, the parameterization of the object separates the volume into an unknown background anatomy and a known component with unknown registration. Thus, one can model projections of an implant at very high spatial resolution while limiting the spatial resolution of the anatomy - in effect, modeling NLPV effects where they are most significant. We present modifications of the KCR approach that can be used to largely eliminate NLPV artifacts, and demonstrate the efficacy of the modified technique (with improved image quality and accurate implant position estimates) for the cochlear implant imaging scenario.

Robust methods for automatic image-to-world registration in cone-beam CT interventional guidance

PURPOSE

Real-time surgical navigation relies on accurate image-to-world registration to align the coordinate systems of the image and patient. Conventional manual registration can present a workflow bottleneck and is prone to manual error and intraoperator variability. This work reports alternative means of automatic image-to-world registration, each method involving an automatic registration marker (ARM) used in conjunction with C-arm cone-beam CT (CBCT). The first involves a Known-Model registration method in which the ARM is a predefined tool, and the second is a Free-Form method in which the ARM is freely configurable.

METHODS

Studies were performed using a prototype C-arm for CBCT and a surgical tracking system. A simple ARM was designed with markers comprising a tungsten sphere within infrared reflectors to permit detection of markers in both x-ray projections and by an infrared tracker. The Known-Model method exercised a predefined specification of the ARM in combination with 3D-2D registration to estimate the transformation that yields the optimal match between forward projection of the ARM and the measured projection images. The Free-Form method localizes markers individually in projection data by a robust Hough transform approach extended from previous work, backprojected to 3D image coordinates based on C-arm geometric calibration. Image-domain point sets were transformed to world coordinates by rigid-body point-based registration. The robustness and registration accuracy of each method was tested in comparison to manual registration across a range of body sites (head, thorax, and abdomen) of interest in CBCT-guided surgery, including cases with interventional tools in the radiographic scene.

RESULTS

The automatic methods exhibited similar target registration error (TRE) and were comparable or superior to manual registration for placement of the ARM within ∼200 mm of C-arm isocenter. Marker localization in projection data was robust across all anatomical sites, including challenging scenarios involving the presence of interventional tools. The reprojection error of marker localization was independent of the distance of the ARM from isocenter, and the overall TRE was dominated by the configuration of individual fiducials and distance from the target as predicted by theory. The median TRE increased with greater ARM-to-isocenter distance (e.g., for the Free-Form method, TRE increasing from 0.78 mm to 2.04 mm at distances of ∼75 mm and 370 mm, respectively). The median TRE within ∼200 mm distance was consistently lower than that of the manual method (TRE = 0.82 mm). Registration performance was independent of anatomical site (head, thorax, and abdomen). The Free-Form method demonstrated a statistically significant improvement (p = 0.0044) in reproducibility compared to manual registration (0.22 mm versus 0.30 mm, respectively).

CONCLUSIONS

Automatic image-to-world registration methods demonstrate the potential for improved accuracy, reproducibility, and workflow in CBCT-guided procedures. A Free-Form method was shown to exhibit robustness against anatomical site, with comparable or improved TRE compared to manual registration. It was also comparable or superior in performance to a Known-Model method in which the ARM configuration is specified as a predefined tool, thereby allowing configuration of fiducials on the fly or attachment to the patient.

Mucus clearance, MyD88-dependent and MyD88-independent immunity modulate lung susceptibility to spontaneous bacterial infection and inflammation

It has been postulated that mucus stasis is central to the pathogenesis of obstructive lung diseases. In Scnn1b-transgenic (Scnn1b-Tg⁺ mice, airway-targeted overexpression of the epithelial Na⁺ channel β subunit causes airway surface dehydration, which results in mucus stasis and inflammation. Bronchoalveolar lavage from neonatal Scnn1b-Tg⁺ mice, but not wild-type littermates, contained increased mucus, bacteria, and neutrophils, which declined with age. Scnn1b-Tg⁺ mice lung bacterial flora included environmental and oropharyngeal species, suggesting inhalation and/or aspiration as routes of entry. Genetic deletion of the Toll-interleukin-1 receptor adapter molecule MyD88 in Scnn1b-Tg⁺ mice did not modify airway mucus obstruction, but caused defective neutrophil recruitment and increased bacterial infection, which persisted into adulthood. Scnn1b-Tg⁺ mice derived into germ-free conditions exhibited mucus obstruction similar to conventional Scnn1b-Tg⁺ mice and sterile inflammation. Collectively, these data suggest that dehydration-induced mucus stasis promotes infection, compounds defects in other immune mechanisms, and alone is sufficient to trigger airway inflammation.

Abstract P6-04-10: Genetic Discrimination of Aggressive from Indolent DCIS

Background: Treatment options for DCIS vary from surgical excision with or without radiation and/or chemopreventive therapy, or mastectomy. Intuitively, more aggressive treatment options should lead to improved survival rates, however, studies have shown no difference in breast cancer mortality between women treated with wide excision only versus those with excision plus radiation and treatments can be costly, lengthy and associated with side effects. To avoid over-treating women with indolent disease, while intensively treating women with aggressive disease, new molecular tools must be developed to supplement pathological information to classify DCIS lesions and predict clinical outcome.

Methods: Formalin-fixed paraffin-embedded (FFPE) pure DCIS biopsy specimens were collected from the pathology archives of the Anne Arundel Medical Center. Samples included those with poor prognosis characterized by either recurrence of DCIS or progression to invasive cancer (n=7) and those good prognosis, having ≥5-year disease-free survival (n=10). RNA was isolated after laser-microdissection of pure tumor cells and hybridized to Breast Cancer DSA™ microarrays (Almac Diagnostics). S-way ANOVA was used to account for batch effects and then Support Vector Machine (SVM) was used to identify candidate genes effective at discriminating good from poor prognosis DCIS. Pathway analysis was performed using MetaCore (GeneGeo).

Results: 328 genes were found to be differentially expressed between good and poor prognosis specimens (P<0.01). Preliminary analysis with SVM found that a 70-gene candidate signature from these 328 genes wasoptimal under the tested conditions for discriminating favorable from poor prognosis DCIS. This candidate signature included genes such as MEF2C, PTK2 and ZBTB2. Pathway analysis revealed that genes involved in cytoskeleton modeling, apoptosis and survival, DNA damage repair and cell adhesion are expressed at lower levels in poor prognosis DCIS while those involved in cell cycle, immune response and cell proliferation are expressed at higher levels.

Conclusions: While studies have attempted to identify molecular profiles associated with aggressive DCIS by comparing DCIS co-occurring with invasive disease to pure DCIS, to our knowledge, this is the first study that identified a candidate molecular signature of prognosis in pure DCIS. Although many of the 70 genes found to differ between favorable and poor prognosis DCIS have not been previously associated with breast cancer or have unknown function, MEF2C and PTK2 have been implicated in invasion and migration, while ZBTB2 is a master regulator of p53 and stimulates cellular proliferation. These data demonstrate aggressive DCIS do differ from indolent DCIS at the genetic level and that these differences may be useful in developing molecular tools to classify DCIS lesions and guide appropriate treatment.

Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P6-04-10.

Identification of a globally distributed clinical streptomycin-resistance plasmid and other resistance determinants in a coastal bay of China

AIMS

To study streptomycin-resistant bacteria isolated from Jiaozhou Bay and their molecular determinants of resistance.

METHODS AND RESULTS

Twenty-seven tetracycline-resistant and 49 chloramphenicol-resistant bacterial isolates from surface seawater of Jiaozhou Bay were selected for investigation. More than 88% of these isolates were resistant to streptomycin. Half of the streptomycin-resistant bacteria harboured the strA-strB gene pair, and six isolates carried Tn5393-like transposons by PCR detection. The p9123-related plasmids containing the sul2-strA-strB gene cluster were characterized in two environmental Escherichia coli isolates. Transposon Tn5393 was first identified on a Klebsiella pneumoniae plasmid, which also carried Tn1721, estP and umu genes responsible for antimicrobial and insecticide resistance.

CONCLUSIONS

Coresistance to streptomycin and tetracycline or chloramphenicol was found with high frequency. p9123-related plasmid and Tn5393 transposon may contribute to the wide distribution and spread of the strA-strB gene pair in Jiaozhou Bay. The detection of streptomycin-resistance plasmid pQ1-1 from Jiaozhou Bay seawater bacteria and human bacterial pathogens from USA indicates its global dissemination and transmission, across different components of the microbiota on earth.

SIGNIFICANCE AND IMPACT OF THE STUDY

Streptomycin resistance can be recognized as an important bioindicator of environmental quality, owing to its association with anthropogenic pollution and the multidrug-resistant microbiota.

Modulation of Masseteric Reflexes by Simulated Mastication

It is well-known that limb muscle reflexes are modulated during human movements. However, little is known about the existence of equivalent masticatory muscle reflex modulation. We hypothesized that masticatory reflexes would be modulated during chewing so that smooth masticatory movements occur. To examine this hypothesis, we studied the modulation of inhibitory reflexes evoked by periodontal mechanoreceptor activation and of excitatory reflexes evoked by muscle spindle activation during simulated mastication. In 28 participants, 1- and 2-N mechanical taps were delivered to the incisor. Reflex responses to these taps were examined in the average masseteric electromyogram. To differentiate between periodontal mechanoreceptor- and muscle-spindle-mediated reflex components, we performed experiments prior to, and in the presence of, periodontal anesthesia. Both periodontal mechanoreceptor and muscle spindle reflexes were reduced during simulated masticatory movements.

Epidemiological survey on gastro-intestinal and blood-borne helminths of dogs in north-east Gabon

A survey of helminth parasites was carried out on 198 dogs living in almost complete liberty in villages in the northeast of Gabon. Faeces and blood samples were collected and analysed. Dirofilaria immitis antigen was detected in 13.6% of dogs using the SNAP 3Dx test, a commercially available enzyme-linked immunosorbent assay (ELISA). Faecal examination revealed that 91.4% of dogs were infected by intestinal helminths. Ascarids were found in 58.5% of the samples. Trichuris vulpis was observed in 49.5% of cases, and Uncinaria spp. and Ancylostoma spp. in 34.8%, Spirocerca lupi in 25.3% and Capillaria spp. in 10.6%. Cestode embryophores were found in 8.6% of the samples.

Diversity and spatial distribution of amoA-encoding archaea in the deep-sea sediments of the tropical West Pacific Continental Margin

AIMS

The ecological characteristics of the deep-sea amoA-encoding archaea (AEA) are largely unsolved. Our aim was to study the diversity, structure and distribution of the AEA community in the sediments of the tropical West Pacific Continental Margin, to develop a general view of the AEA biogeography in the deep-sea extreme environment.

METHODS AND RESULTS

Archaeal amoA clone libraries were constructed. Diverse and novel amoA sequences were identified, with the Bohol Sea, Bashi Strait and Sibuyan Sea harbouring the highest and the Bicol Shelf the lowest AEA diversity. Phylogenetic and statistical analyses illustrate a heterogeneous distribution of the AEA community, probably caused by the differential distribution of the terrestrial or estuarine AEA in the various sampling sites.

CONCLUSIONS

The deep-sea sedimentary environments potentially harbour diverse and novel AEA in the tropical West Pacific Continental Margin. The stations in the Philippine inland seas (including station 3043) may represent AEA assemblages with various terrestrial influences and the stations connected directly to the open Philippine Sea may represent marine environment-dominant AEA assemblages.

SIGNIFICANCE AND IMPACT OF STUDY

Our study indicates the potential importance of geological and climatic events in the transport of terrestrial micro-organisms to the deep-sea sedimentary environments, almost totally neglected previously.

The postnatal maternal environment influences diabetes development in nonobese diabetic mice

When nonobese-diabetic (NOD) mouse embryos were implanted into pseudopregnant mothers of a nonautoimmune mouse strain, the progeny had a reduced type 1 diabetes (T1D) incidence, suggesting that transmission of maternal autoantibodies is important for T1D development. Whether eliminating islet autoantibody transmission in utero, or postnatally (through milk), prevented T1D is unknown. Herein, we show that fostering newborn NOD mice on B-cell deficient NOD.Igmu-/- dams does not prevent T1D, demonstrating that postnatally transmitted islet autoantibodies are not required for disease pathogenesis. Additionally, NOD.Igmu-/- mice reared on NOD dams did not develop T1D, indicating that autoantibody transmission to B-cell deficient NOD neonates is insufficient to trigger T1D. Interestingly, newborn NOD mice that were reared by ICR (but not NOD or C57BL/6) dams had reduced T1D incidence, although not as reduced as that reported after embryo transfer to ICR mice, suggesting that both prenatal and postnatal factors contribute to the observed reduction in T1D incidence. Thus, NOD mice have different risks for developing T1D depending on the strain of their foster mother, and both prenatal and postnatal maternal factors, other than islet autoantibodies, influence their T1D incidence. The results may be relevant for understanding the increasing incidence of T1D and designing interventions.