Development of PainFace software to simplify, standardize, and scale up mouse grimace analyses.

ABSTRACT: Facial grimacing is used to quantify spontaneous pain in mice and other mammals, but scoring relies on humans with different levels of proficiency. Here, we developed a cloud-based software platform called PainFace (http://painface.net) that uses machine learning to detect 4 facial action units of the mouse grimace scale (orbitals, nose, ears, whiskers) and score facial grimaces of black-coated C57BL/6 male and female mice on a 0 to 8 scale. Platform accuracy was validated in 2 different laboratories, with 3 conditions that evoke grimacing-laparotomy surgery, bilateral hindpaw injection of carrageenan, and intraplantar injection of formalin. PainFace can generate up to 1 grimace score per second from a standard 30 frames/s video, making it possible to quantify facial grimacing over time, and operates at a speed that scales with computing power. By analyzing the frequency distribution of grimace scores, we found that mice spent 7x more time in a "high grimace" state following laparotomy surgery relative to sham surgery controls. Our study shows that PainFace reproducibly quantifies facial grimaces indicative of nonevoked spontaneous pain and enables laboratories to standardize and scale-up facial grimace analyses.

The interaction effects of age, APOE and common environmental risk factors on human brain structure.

Mounting evidence suggests considerable diversity in brain aging trajectories, primarily arising from the complex interplay between age, genetic, and environmental risk factors, leading to distinct patterns of micro- and macro-cerebral aging. The underlying mechanisms of such effects still remain unclear. We conducted a comprehensive association analysis between cerebral structural measures and prevalent risk factors, using data from 36,969 UK Biobank subjects aged 44-81. Participants were assessed for brain volume, white matter diffusivity, Apolipoprotein E (APOE) genotypes, polygenic risk scores, lifestyles, and socioeconomic status. We examined genetic and environmental effects and their interactions with age and sex, and identified 726 signals, with education, alcohol, and smoking affecting most brain regions. Our analysis revealed negative age-APOE-ε4 and positive age-APOE-ε2 interaction effects, respectively, especially in females on the volume of amygdala, positive age-sex-APOE-ε4 interaction on the cerebellar volume, positive age-excessive-alcohol interaction effect on the mean diffusivity of the splenium of the corpus callosum, positive age-healthy-diet interaction effect on the paracentral volume, and negative APOE-ε4-moderate-alcohol interaction effects on the axial diffusivity of the superior fronto-occipital fasciculus. These findings highlight the need of considering age, sex, genetic, and environmental joint effects in elucidating normal or abnormal brain aging.

The roles of selectivity filters in determining aluminum transport by AtNIP1;2.

Aquaporins (AQPs) are channel proteins involved in transporting a variety of substrates. It has been proposed that the constriction regions in the central pores of the AQP channels play a crucial role in determining transport substrates and activities of AQPs. Our previous results suggest that AtNIP1;2, a member of the AQP superfamily in Arabidopsis, facilitates aluminum transport across the plasma membrane. However, the functions of the constriction regions in AtNIP1;2-mediated transport activities are unclear. This study reports that residue substitutions of the constriction regions affect AtNIP1;2-mediated aluminum uptake, demonstrating the critical roles of the constriction regions for transport activities. Furthermore, a constriction region that partially or wholly mimics AtNIP5;1, a demonstrated boric-acid transporter, could not render the boric-acid transport activity to AtNIP1;2. Therefore, besides the constriction regions, other structural features are also involved in determining the nature of AtNIP1;2's transport activities.Abbreviations: AIAR: alanine-isoleucine-alanine-arginine; AIGR: alanine-isoleucine-glycine- arginine; AQP: aquaporin; Al-Mal: aluminum-malate; ar/R: aromatic/arginine; AVAR: alanine-valine-alanine-arginine; CK: control; H: helical domain; ICP-MS: inductively coupled plasma mass spectrometry; LA - LE: inter-helical loops A to E; NIP: nodulin 26-like intrinsic protein; NPA: asparagine-proline-alanine; NPG: asparagine-proline- glycine; NPS: asparagine-proline-Serine; NPV: asparagine-proline-valine; ORF: open reading frame; PIP: plasma membrane intrinsic proteins; SIP: small basic intrinsic proteins; TM: transmembrane helices; WIAR: tryptophan-isoleucine-alanine-arginine; WVAR: tryptophan-valine-alanine-arginine; WVGR: tryptophan-valine-glycine- arginine.

NuMorph: Tools for cortical cellular phenotyping in tissue-cleared whole-brain images.

Tissue-clearing methods allow every cell in the mouse brain to be imaged without physical sectioning. However, the computational tools currently available for cell quantification in cleared tissue images have been limited to counting sparse cell populations in stereotypical mice. Here, we introduce NuMorph, a group of analysis tools to quantify all nuclei and nuclear markers within the mouse cortex after clearing and imaging by light-sheet microscopy. We apply NuMorph to investigate two distinct mouse models: a Topoisomerase 1 (Top1) model with severe neurodegenerative deficits and a Neurofibromin 1 (Nf1) model with a more subtle brain overgrowth phenotype. In each case, we identify differential effects of gene deletion on individual cell-type counts and distribution across cortical regions that manifest as alterations of gross brain morphology. These results underline the value of whole-brain imaging approaches, and the tools are widely applicable for studying brain structure phenotypes at cellular resolution.

Postoperative pain control with continuous paravertebral nerve block and intercostal nerve block after two-port video-assisted thoracic surgery.

INTRODUCTION: Effective pain control after video-assisted thoracic surgery (VATS) is critical because of the correlation between postoperative pain and recovery after surgery. Due to the limitations of traditional analgesic modalities, in this study, we present a method of placing a paravertebral catheter (PVC) or an intercostal catheter (ICC) in the sub-pleural space, followed by continuous ropivacaine injection by an infusion pump after surgery. AIM: To investigate the impact of continuous paravertebral nerve block and intercostal nerve block on postoperative pain control in patients who underwent two-port thoracic surgery. MATERIAL AND METHODS: A total of 269 patients underwent various types of two-port VATS at Hwa Mei Hospital. Among them, we retrospectively compared paravertebral block versus intercostal nerve block to intravenous patient-controlled analgesia after VATS. Data regarding postoperative pain score on postoperative day 0, 1, 2, 3, and discharge day pain score, tramadol requirements, drainage duration, postoperative hospital stay, postoperative complications, and chronic pain 3 months after surgery were collected and analyzed. RESULTS: Compared with the control group, patients who received a continuous nerve block, including the PVC group and ICC group, had a lower postoperative pain score (p < 0.001), shorter drainage duration (4.63 ±2.84 to 5.61 ±2.66 days, p = 0.004), reduced postoperative hospital stay (6.04 ±3.01 to 7.69 ±3.26 days, p < 0.001), and a reduced frequency of tramadol (0.95 ±1.27 1.79 ±2.13 times, p < 0.001). Additionally, there was no significant difference in chronic pain between groups. CONCLUSIONS: In our study, PVC and ICC appeared to be safe and effective analgesic techniques to reduce postoperative pain, thus shortening the duration of postoperative hospital stay and improving the satisfaction of patients.

Ultraviolet photochemistry of ethane: implications for the atmospheric chemistry of the gas giants.

Chemical processing in the stratospheres of the gas giants is driven by incident vacuum ultraviolet (VUV) light. Ethane is an important constituent in the atmospheres of the gas giants in our solar system. The present work describes translational spectroscopy studies of the VUV photochemistry of ethane using tuneable radiation in the wavelength range 112 ≤ λ ≤ 126 nm from a free electron laser and event-triggered, fast-framing, multi-mass imaging detection methods. Contributions from at least five primary photofragmentation pathways yielding CH2, CH3 and/or H atom products are demonstrated and interpreted in terms of unimolecular decay following rapid non-adiabatic coupling to the ground state potential energy surface. These data serve to highlight parallels with methane photochemistry and limitations in contemporary models of the photoinduced stratospheric chemistry of the gas giants. The work identifies additional photochemical reactions that require incorporation into next generation extraterrestrial atmospheric chemistry models which should help rationalise hitherto unexplained aspects of the atmospheric ethane/acetylene ratios revealed by the Cassini-Huygens fly-by of Jupiter.

Melatonin and Rapamycin Attenuate Isoflurane-Induced Cognitive Impairment Through Inhibition of Neuroinflammation by Suppressing the mTOR Signaling in the Hippocampus of Aged Mice.

Melatonin exerts neuroprotective effects on isoflurane-induced cognitive impairment. However, the underlying mechanism has yet to be elucidated. The present study sought to determine if melatonin confers its beneficial effects by acting on mammalian target of rapamycin (mTOR) and attenuates the neuroinflammation in the hippocampus of aged mice. A total of 72 male C57BL/6 mice, 16-month-old, were randomly and equally divided into six groups: (1) the control group (CON); (2) the rapamycin group (RAP); (3) the melatonin group (MEL); (4) the isoflurane group (ISO); (5) the rapamycin + isoflurane group (RAP + ISO); and (6) the melatonin + isoflurane group (MEL + ISO). RAP, RAP + ISO, MEL, MEL + ISO groups received 1 mg/kg/day mTOR inhibitor rapamycin solution or 10 mg/kg/day melatonin solution, respectively, intraperitoneally at 5:00 p.m. for 14 days consecutively. Mice in the CON and ISO groups were administered an equivalent volume of saline. Subsequently, ISO, RAP + ISO, and MEL + ISO groups were exposed to inhale 2% isoflurane for 4 h; the CON, RAP, and MEL mice received only the vehicle gas. Then, the memory function and spatial learning of the mice were examined via the Morris water maze (MWM) test. mTOR expression was detected via Western blot, whereas the concentration of inflammatory cytokines tumor necrosis factor (TNF)-α, interleukin (IL)-1ß, IL-6 and that of melatonin was quantified with enzyme-linked immunosorbent assay (ELISA). Melatonin and rapamycin significantly ameliorated the isoflurane-induced cognitive impairment and also led to a decrease in the melatonin levels as well as the expression levels of TNF-α, IL-1ß, IL-6, and p-mTOR in the hippocampus. In conclusion, these results showed that melatonin and rapamycin attenuates mTOR expression while affecting the downstream proinflammatory cytokines. Thus, these molecular findings could be associated with an improved cognitive function in mice exposed to isoflurane.

Serum Phosphorylated Neurofilament Heavy Subunit-H, a Potential Predictive Biomarker for Postoperative Cognitive Dysfunction in Elderly Subjects Undergoing Hip Joint Arthroplasty.

BACKGROUND: Postoperative cognitive dysfunction (POCD), which refers to a cognitive impairment subsequent to surgical procedures, is a common complication in the elderly subjects. This study aimed to investigate potential risk factors for POCD in elderly subjects undergoing hip joint arthroplasty. METHODS: Consecutive elderly osteoarthritis patients who were scheduled to undergo hip arthroplasty under epidural anesthesia were enrolled into this single-center, prospective observational study. Serum phosphorylated neurofilament heavy subunit-H (pNF-H) was measured by the enzyme-linked immunosorbent assay method. A level of >70.5 pg/mL was accepted as pNF-H positivity. Neuropsychological assessment at baseline (1 day before the surgery) and postoperative day 7 was conducted. POCD was defined according to the calculated Z scores. Risk factors for POCD were evaluated by univariate and multivariate logistic regression analyses. RESULTS: In final, 287 patients were enrolled, and 55 had suffered POCD within postoperative 7 days with an incidence of 19.2%. The final multiple logistic regression analysis revealed a higher pNF-H positivity was the only independent risk factor for POCD (odds ratio: 2.03, 95% confidence interval: 1.21-3.29, P = .012). CONCLUSIONS: Our results revealed an increased preoperative serum pNF-H expression was an independent risk factor for POCD development in elderly subjects undergoing hip joint arthroplasty, suggesting the close association between anatomical damage in central nervous system and POCD.

Preoperative Albumin Level Serves as a Predictor for Postoperative Pulmonary Complications Following Elective Laparoscopic Gastrectomy.

OBJECTIVE: Postoperative Pulmonary Complications (PPCs) can contribute to increased mortality and prolonged hospital stay in surgical patients with Gastric Cancer (GC). This study aimed to investigate potential risk factors for PPCs in elderly GC patients following elective laparoscopic gastrectomy. METHODS: Eligible consecutive elderly GC patients (aged over 65 years) who were scheduled to undergo elective laparoscopic gastrectomy were enrolled in this study. The demographic, clinicopathological characteristics and laboratory variables were compared in patients with or without PPCs within postoperative 30 days. Risk factors for PPCs were analyzed by multiple logistic regression analysis and receiver operating characteristic (ROC) curve analysis. RESULTS: 35 of all the 262 enrolled patients have developed PPCs with an incidence of 13.4%. Age, chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), forced expiratory volume in one second/ forced vital capacity (FEV1/FVC) ratio, duration of operation, hemoglobin, albumin and C-reactive protein (CRP) were potential risk factors for PPCs by univariate analysis. The preoperative albumin level was the only independent risk factor for PPCs (OR: 1.15, 95%CI: 1.06-1.28, P=0.011) by multiple logistic regression analysis. Preoperative albumin level was a predictor for PPCs with an area under the curve (AUC) of 0.728 and a cut-off value of 33.8 mg/dl (specificity: 54.19%, sensitivity: 77.14%, P<0.001). CONCLUSIONS: Preoperative albumin level was an independent risk factor for PPCs in elderly GC patients after elective laparoscopic gastrectomy.

Dual-core steered non-rigid registration for multi-modal images via bi-directional image synthesis.

In prostate cancer radiotherapy, computed tomography (CT) is widely used for dose planning purposes. However, because CT has low soft tissue contrast, it makes manual contouring difficult for major pelvic organs. In contrast, magnetic resonance imaging (MRI) provides high soft tissue contrast, which makes it ideal for accurate manual contouring. Therefore, the contouring accuracy on CT can be significantly improved if the contours in MRI can be mapped to CT domain by registering MRI with CT of the same subject, which would eventually lead to high treatment efficacy. In this paper, we propose a bi-directional image synthesis based approach for MRI-to-CT pelvic image registration. First, we use patch-wise random forest with auto-context model to learn the appearance mapping from CT to MRI domain, and then vice versa. Consequently, we can synthesize a pseudo-MRI whose anatomical structures are exactly same with CT but with MRI-like appearance, and a pseudo-CT as well. Then, our MRI-to-CT registration can be steered in a dual manner, by simultaneously estimating two deformation pathways: 1) one from the pseudo-CT to the actual CT and 2) another from actual MRI to the pseudo-MRI. Next, a dual-core deformation fusion framework is developed to iteratively and effectively combine these two registration pathways by using complementary information from both modalities. Experiments on a dataset with real pelvic CT and MRI have shown improved registration performance of the proposed method by comparing it to the conventional registration methods, thus indicating its high potential of translation to the routine radiation therapy.

Automatic Cystocele Severity Grading in Ultrasound by Spatio-Temporal Regression.

Cystocele is a common disease in woman. Accurate assessment of cystocele severity is very important for treatment options. The transperineal ultrasound (US) has recently emerged as an alternative tool for cystocele grading. The cystocele severity is usually evaluated with the manual measurement of the maximal descent of the bladder (MDB) relative to the symphysis pubis (SP) during Valsalva maneuver. However, this process is time-consuming and operator-dependent. In this study, we propose an automatic scheme for csystocele grading from transperineal US video. A two-layer spatio-temporal regression model is proposed to identify the middle axis and lower tip of the SP, and segment the bladder, which are essential tasks for the measurement of the MDB. Both appearance and context features are extracted in the spatio-temporal domain to help the anatomy detection. Experimental results on 85 transperineal US videos show that our method significantly outperforms the state-of-the-art regression method.

Learning-Based Multimodal Image Registration for Prostate Cancer Radiation Therapy.

Computed tomography (CT) is widely used for dose planning in the radiotherapy of prostate cancer. However, CT has low tissue contrast, thus making manual contouring difficult. In contrast, magnetic resonance (MR) image provides high tissue contrast and is thus ideal for manual contouring. If MR image can be registered to CT image of the same patient, the contouring accuracy of CT could be substantially improved, which could eventually lead to high treatment efficacy. In this paper, we propose a learning-based approach for multimodal image registration. First, to fill the appearance gap between modalities, a structured random forest with auto-context model is learnt to synthesize MRI from CT and vice versa. Then, MRI-to-CT registration is steered in a dual manner of registering images with same appearances, i.e., (1) registering the synthesized CT with CT, and (2) also registering MRI with the synthesized MRI. Next, a dual-core deformation fusion framework is developed to iteratively and effectively combine these two registration results. Experiments on pelvic CT and MR images have shown the improved registration performance by our proposed method, compared with the existing non-learning based registration methods.

Variable lung protective mechanical ventilation decreases incidence of postoperative delirium and cognitive dysfunction during open abdominal surgery.

BACKGROUND: Postoperative cognitive dysfunction (POCD) is a subtle impairment of cognitive abilities and can manifest on different neuropsychological features in the early postoperative period. It has been proved that the use of mechanical ventilation (MV) increased the development of delirium and POCD. However, the impact of variable and conventional lung protective mechanical ventilation on the incidence of POCD still remains unknown, which was the aim of this study. METHODS: 162 patients scheduled to undergo elective gastrointestinal tumor resection via laparotomy in Ningbo No. 2 hospital with expected duration >2 h from June, 2013 to June, 2015 were enrolled in this study. Patients included were divided into two groups according to the scheme of lung protective MV, variable ventilation group (VV group, n=79) and conventional ventilation group (CV group, n=83) by randomization performed by random block randomization. The plasma levels of inflammatory cytokines, characteristics of the surgical procedure, incidence of delirium and POCD were collected and compared. RESULTS: Postoperative delirium was detected in 36 of 162 patients (22.2%) and 12 patients of these (16.5%) belonged to the VV group while 24 patients (28.9%) were in the CV group (P=0.036). POCD on the seventh postoperative day in CV group (26/83, 31.3%) was increased in comparison with the VV group (14/79, 17.7%) with significant statistical difference (P=0.045). The levels of inflammatory cytokines were all significantly higher in CV group than those in VV group on the 1st postoperative day (P<0.05). On 7th postoperative day, the levels of IL-6 and TNF-α in CV group remained much higher compared with VV group (P<0.05). CONCLUSIONS: Variable vs conventional lung protective MV decreased the incidence of postoperative delirium and POCD by reducing the systemic proinflammatory response.

Internal conversion versus intersystem crossing: what drives the gas phase dynamics of cyclic α,ß-enones?

We investigate the competition between intersystem crossing (ISC) and internal conversion (IC) as nonradiative relaxation pathways in cyclic α,ß-unsaturated enones following excitation to their lowest lying (1)ππ* state, by means of time-resolved photoelectron spectroscopy and ab initio computation. Upon excitation, the (1)ππ* state of 2-cyclopentenone decays to the lowest lying (1)nπ* state within 120 ± 20 fs. Within 1.2 ± 0.2 ps, the molecule subsequently decays to the triplet manifold and the singlet ground state, with quantum yields of 0.35 and 0.65, respectively. The corresponding dynamics in modified derivatives, obtained by selective methylation, show a decrease in both IC and ISC rates, with the quantum yields of ISC varying between 0.35 and 0.08. The rapid rates of ISC are explained by a large spin orbit coupling of 45-60 cm(-1) over an extended region of near degeneracy between the singlet and triplet state. Furthermore, the rate of IC is depressed by the existence of a well-defined minimum on the (1)nπ* potential energy surface. The nonadiabatic pathways evinced by the present results highlight the fact that these molecular systems conceptually represent "intermediate cases" between ultrafast dynamics mediated by vibrational motions at conical intersections versus those by statistical decay mechanisms.

Resolution enhancement of lung 4D-CT via group-sparsity.

PURPOSE: 4D-CT typically delivers more accurate information about anatomical structures in the lung, over 3D-CT, due to its ability to capture visual information of the lung motion across different respiratory phases. This helps to better determine the dose during radiation therapy for lung cancer. However, a critical concern with 4D-CT that substantially compromises this advantage is the low superior-inferior resolution due to less number of acquired slices, in order to control the CT radiation dose. To address this limitation, the authors propose an approach to reconstruct missing intermediate slices, so as to improve the superior-inferior resolution. METHODS: In this method the authors exploit the observation that sampling information across respiratory phases in 4D-CT can be complimentary due to lung motion. The authors' approach uses this locally complimentary information across phases in a patch-based sparse-representation framework. Moreover, unlike some recent approaches that treat local patches independently, the authors' approach employs the group-sparsity framework that imposes neighborhood and similarity constraints between patches. This helps in mitigating the trade-off between noise robustness and structure preservation, which is an important consideration in resolution enhancement. The authors discuss the regularizing ability of group-sparsity, which helps in reducing the effect of noise and enables better structural localization and enhancement. RESULTS: The authors perform extensive experiments on the publicly available DIR-Lab Lung 4D-CT dataset [R. Castillo, E. Castillo, R. Guerra, V. Johnson, T. McPhail, A. Garg, and T. Guerrero, "A framework for evaluation of deformable image registration spatial accuracy using large landmark point sets," Phys. Med. Biol. 54, 1849-1870 (2009)]. First, the authors carry out empirical parametric analysis of some important parameters in their approach. The authors then demonstrate, qualitatively as well as quantitatively, the ability of their approach to achieve more accurate and better localized results over bicubic interpolation as well as a related state-of-the-art approach. The authors also show results on some datasets with tumor, to further emphasize the clinical importance of their method. CONCLUSIONS: The authors have proposed to improve the superior-inferior resolution of 4D-CT by estimating intermediate slices. The authors' approach exploits neighboring constraints in the group-sparsity framework, toward the goal of achieving better localization and noise robustness. The authors' results are encouraging, and positively demonstrate the role of group-sparsity for 4D-CT resolution enhancement.

Resolution enhancement of lung 4D-CT data using multiscale interphase iterative nonlocal means.

PURPOSE: Four-dimensional computer tomography (4D-CT) has been widely used in lung cancer radiotherapy due to its capability in providing important tumor motion information. However, the prolonged scanning duration required by 4D-CT causes considerable increase in radiation dose. To minimize the radiation-related health risk, radiation dose is often reduced at the expense of interslice spatial resolution. However, inadequate resolution in 4D-CT causes artifacts and increases uncertainty in tumor localization, which eventually results in extra damages of healthy tissues during radiotherapy. In this paper, the authors propose a novel postprocessing algorithm to enhance the resolution of lung 4D-CT data. METHODS: The authors' premise is that anatomical information missing in one phase can be recovered from the complementary information embedded in other phases. The authors employ a patch-based mechanism to propagate information across phases for the reconstruction of intermediate slices in the longitudinal direction, where resolution is normally the lowest. Specifically, the structurally matching and spatially nearby patches are combined for reconstruction of each patch. For greater sensitivity to anatomical details, the authors employ a quad-tree technique to adaptively partition the image for more fine-grained refinement. The authors further devise an iterative strategy for significant enhancement of anatomical details. RESULTS: The authors evaluated their algorithm using a publicly available lung data that consist of 10 4D-CT cases. The authors' algorithm gives very promising results with significantly enhanced image structures and much less artifacts. Quantitative analysis shows that the authors' algorithm increases peak signal-to-noise ratio by 3-4 dB and the structural similarity index by 3%-5% when compared with the standard interpolation-based algorithms. CONCLUSIONS: The authors have developed a new algorithm to improve the resolution of 4D-CT. It outperforms the conventional interpolation-based approaches by producing images with the markedly improved structural clarity and greatly reduced artifacts.

Estimating the 4D respiratory lung motion by spatiotemporal registration and super-resolution image reconstruction.

PURPOSE: One of the main challenges in lung cancer radiation therapy is how to reduce the treatment margin but accommodate the geometric uncertainty of moving tumor. 4D-CT is able to provide the full range of motion information for the lung and tumor. However, accurate estimation of lung motion with respect to the respiratory phase is difficult due to various challenges in image registration, e.g., motion artifacts and large interslice thickness in 4D-CT. Meanwhile, the temporal coherence across respiration phases is usually not guaranteed in the conventional registration methods which consider each phase image in 4D-CT independently. To address these challenges, the authors present a unified approach to estimate the respiratory lung motion with two iterative steps. METHODS: First, the authors propose a novel spatiotemporal registration algorithm to align all phase images of 4D-CT (in low-resolution) to a high-resolution group-mean image in the common space. The temporal coherence of registration is maintained by a set of temporal fibers that delineate temporal correspondences across different respiratory phases. Second, a super-resolution technique is utilized to build the high-resolution group-mean image with more anatomical details than any individual phase image, thus largely alleviating the registration uncertainty especially in correspondence detection. In particular, the authors use the concept of sparse representation to keep the group-mean image as sharp as possible. RESULTS: The performance of our 4D motion estimation method has been extensively evaluated on both the simulated datasets and real lung 4D-CT datasets. In all experiments, our method achieves more accurate and consistent results in lung motion estimation than all other state-of-the-art approaches under comparison. CONCLUSIONS: The authors have proposed a novel spatiotemporal registration method to estimate the lung motion in 4D-CT. Promising results have been obtained, which indicates the high applicability of our method in clinical lung cancer radiation therapy.

Improving image-guided radiation therapy of lung cancer by reconstructing 4D-CT from a single free-breathing 3D-CT on the treatment day.

PURPOSE: One of the major challenges of lung cancer radiation therapy is how to reduce the margin of treatment field but also manage geometric uncertainty from respiratory motion. To this end, 4D-CT imaging has been widely used for treatment planning by providing a full range of respiratory motion for both tumor and normal structures. However, due to the considerable radiation dose and the limit of resource and time, typically only a free-breathing 3D-CT image is acquired on the treatment day for image-guided patient setup, which is often determined by the image fusion of the free-breathing treatment and planning day 3D-CT images. Since individual slices of two free breathing 3D-CTs are possibly acquired at different phases, two 3D-CTs often look different, which makes the image registration very challenging. This uncertainty of pretreatment patient setup requires a generous margin of radiation field in order to cover the tumor sufficiently during the treatment. In order to solve this problem, our main idea is to reconstruct the 4D-CT (with full range of tumor motion) from a single free-breathing 3D-CT acquired on the treatment day. METHODS: We first build a super-resolution 4D-CT model from a low-resolution 4D-CT on the planning day, with the temporal correspondences also established across respiratory phases. Next, we propose a 4D-to-3D image registration method to warp the 4D-CT model to the treatment day 3D-CT while also accommodating the new motion detected on the treatment day 3D-CT. In this way, we can more precisely localize the moving tumor on the treatment day. Specifically, since the free-breathing 3D-CT is actually the mixed-phase image where different slices are often acquired at different respiratory phases, we first determine the optimal phase for each local image patch in the free-breathing 3D-CT to obtain a sequence of partial 3D-CT images (with incomplete image data at each phase) for the treatment day. Then we reconstruct a new 4D-CT for the treatment day by registering the 4D-CT of the planning day (with complete information) to the sequence of partial 3D-CT images of the treatment day, under the guidance of the 4D-CT model built on the planning day. RESULTS: We first evaluated the accuracy of our 4D-CT model on a set of lung 4D-CT images with manually labeled landmarks, where the maximum error in respiratory motion estimation can be reduced from 6.08 mm by diffeomorphic Demons to 3.67 mm by our method. Next, we evaluated our proposed 4D-CT reconstruction algorithm on both simulated and real free-breathing images. The reconstructed 4D-CT using our algorithm shows clinically acceptable accuracy and could be used to guide a more accurate patient setup than the conventional method. CONCLUSIONS: We have proposed a novel two-step method to reconstruct a new 4D-CT from a single free-breathing 3D-CT on the treatment day. Promising reconstruction results imply the possible application of this new algorithm in the image guided radiation therapy of lung cancer.

Hierarchical patch-based sparse representation--a new approach for resolution enhancement of 4D-CT lung data.

4D-CT plays an important role in lung cancer treatment because of its capability in providing a comprehensive characterization of respiratory motion for high-precision radiation therapy. However, due to the inherent high-dose exposure associated with CT, dense sampling along superior-inferior direction is often not practical, thus resulting in an inter-slice thickness that is much greater than in-plane voxel resolutions. As a consequence, artifacts such as lung vessel discontinuity and partial volume effects are often observed in 4D-CT images, which may mislead dose administration in radiation therapy. In this paper, we present a novel patch-based technique for resolution enhancement of 4D-CT images along the superior-inferior direction. Our working premise is that anatomical information that is missing in one particular phase can be recovered from other phases. Based on this assumption, we employ a hierarchical patch-based sparse representation mechanism to enhance the superior-inferior resolution of 4D-CT by reconstructing additional intermediate CT slices. Specifically, for each spatial location on an intermediate CT slice that we intend to reconstruct, we first agglomerate a dictionary of patches from images of all other phases in the 4D-CT. We then employ a sparse combination of patches from this dictionary, with guidance from neighboring (upper and lower) slices, to reconstruct a series of patches, which we progressively refine in a hierarchical fashion to reconstruct the final intermediate slices with significantly enhanced anatomical details. Our method was extensively evaluated using a public dataset. In all experiments, our method outperforms the conventional linear and cubic-spline interpolation methods in preserving image details and also in suppressing misleading artifacts, indicating that our proposed method can potentially be applied to better image-guided radiation therapy of lung cancer in the future.