Faculty Bibliography

Computer-aided detection (CADe) of pulmonary nodules from computer tomography (CT) scans is critical for assisting radiologists to identify lung lesions at an early stage. In this paper, we propose a novel approach for CADe of lung nodules using a two-stage vector quantization (VQ) scheme. The first-stage VQ aims to extract lung from the chest volume, while the second-stage VQ is designed to extract initial nodule candidates (INCs) within the lung volume. Then rule-based expert filtering is employed to prune obvious FPs from INCs, and the commonly-used support vector machine (SVM) classifier is adopted to further reduce the FPs. The proposed system was validated on 100 CT scans randomly selected from the 262 scans that have at least one juxta-pleural nodule annotation in the publicly available database Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI). The two-stage VQ only missed 2 out of the 207 nodules at agreement level 1, and the INCs detection for each scan took about 30 seconds in average. Expert filtering reduced FPs more than 18 times, while maintaining a sensitivity of 93.24%. As it is trivial to distinguish INCs attached to pleural wall versus not on wall, we investigated the feasibility of training different SVM classifiers to further reduce FPs from these two kinds of INCs. Experiment results indicated that SVM classification over the entire set of INCs was in favor of, where the optimal operating of our CADe system achieved a sensitivity of 89.4% at a specificity of 86.8%.

Graphene nanoparticle dispersions show immense potential as multifunctional agents for in vivo biomedical applications. Herein, we follow regulatory guidelines for pharmaceuticals that recommend safety pharmacology assessment at least 10-100 times higher than the projected therapeutic dose, and present comprehensive single dose response, expanded acute toxicology, toxicokinetics, and respiratory/cardiovascular safety pharmacology results for intravenously administered dextran-coated graphene oxide nanoplatelet (GNP-Dex) formulations to rats at doses between 1 and 500 mg/kg. Our results indicate that the maximum tolerable dose (MTD) of GNP-Dex is between 50 mg/kg /=250 mg/kg in the heart, liver, lung, spleen, and kidney; we found no changes in the brain and no GNP-Dex related effects in the cardiovascular parameters or hematological factors (blood, lipid, and metabolic panels) at doses < 125 mg/kg. The results open avenues for pivotal preclinical single and repeat dose safety studies following good laboratory practices (GLP) as required by regulatory agencies for investigational new drug (IND) application.

PURPOSE: Repeated computed tomography (CT) scans are required for some clinical applications such as image-guided interventions. To optimize radiation dose utility, a normal-dose scan is often first performed to set up reference, followed by a series of low-dose scans for intervention. One common strategy to achieve the low-dose scan is to lower the x-ray tube current and exposure time (mAs) or tube voltage (kVp) setting in the scanning protocol, but the resulted image quality by the conventional filtered back-projection (FBP) method may be severely degraded due to the excessive noise. Penalized weighted least-squares (PWLS) image reconstruction has shown the potential to significantly improve the image quality from low-mAs acquisitions, where the penalty plays an important role. In this work, the authors' explore an adaptive Markov random field (MRF)-based penalty term by utilizing previous normal-dose scan to improve the subsequent low-dose scans image reconstruction. METHODS: In this work, the authors employ the widely-used quadratic-form MRF as the penalty model and explore a novel idea of using the previous normal-dose scan to obtain the MRF coefficients for adaptive reconstruction of the low-dose images. In the coefficients determination, the authors further explore another novel idea of using the normal-dose scan to obtain a scale map, which describes an optimal neighborhood for the coefficients determination such that a local uniform region has a small spread of frequency spectrum and, therefore, a small MRF window, and vice versa. The proposed penalty term is incorporated into the PWLS image reconstruction framework, and the low-dose images are reconstructed via the PWLS minimization. RESULTS: The presented adaptive MRF based PWLS algorithm was validated by physical phantom and patient data. The experimental results demonstrated that the presented algorithm is superior to the PWLS reconstruction using the conventional Gaussian MRF penalty or the edge-preserving Huber penalty and the conventional FBP method, in terms of image noise reduction and edge/detail/contrast preservation. CONCLUSIONS: This study demonstrated the feasibility and efficacy of the proposed scheme in utilizing previous normal-dose CT scan to improve the subsequent low-dose scans.

Previous studies have shown that by minimizing the total variation (TV) of the to-be-estimated image with some data and/or other constraints, a piecewise-smooth X-ray computed tomography image can be reconstructed from sparse-view projection data. However, due to the piecewise constant assumption for the TV model, the reconstructed images are frequently reported to suffer from the blocky or patchy artifacts. To eliminate this drawback, we present a total variation-stokes-projection onto convex sets (TVS-POCS) reconstruction method in this paper. The TVS model is derived by introducing isophote directions for the purpose of recovering possible missing information in the sparse-view data situation. Thus the desired consistencies along both the normal and the tangent directions are preserved in the resulting images. Compared to the previous TV-based image reconstruction algorithms, the preserved consistencies by the TVS-POCS method are expected to generate noticeable gains in terms of eliminating the patchy artifacts and preserving subtle structures. To evaluate the presented TVS-POCS method, both qualitative and quantitative studies were performed using digital phantom, physical phantom and clinical data experiments. The results reveal that the presented method can yield images with several noticeable gains, measured by the universal quality index and the full-width-at-half-maximum merit, as compared to its corresponding TV-based algorithms. In addition, the results further indicate that the TVS-POCS method approaches to the gold standard result of the filtered back-projection reconstruction in the full-view data case as theoretically expected, while most previous iterative methods may fail in the full-view case because of their artificial textures in the results.

Lung tumors represent a major health impact globally. Pulmonary cryoablation treatment as a palliative measure for patients with non-operable pulmonary lesions has gained popularity over the last decade. With increasing case load and patients medical status becoming more complex, preparation for pulmonary cryoablation requires the implementation of an enhanced perioperative anesthetic plan. Current literature as well as our institutional experience shows that this patient population presents with multiple comorbidities raising the challenge of providing anesthetic care. These procedures are done under challenging conditions with limited resources and in remote locations in the hospital. A team approach by the anesthesiologist, thoracic surgeon, and interventional radiologist is critical to the success of this treatment. The present review examines our institution’s anesthetic management of percutaneous cryoablation treatment (PCT) in the treatment of non-operable lung cancer and metastases. The objective of this article is to review the current literature guidelines and to discuss our retrospective institutional experience in anesthesia management of PCT procedures

To distinguish malignant pulmonary nodules from benign ones is of much importance in computer-aided diagnosis of lung diseases. Compared to many previous methods which are based on shape or growth assessing of nodules, this proposed three-dimensional (3D) texture feature based approach extracted fifty kinds of 3D textural features from gray level, gradient and curvature co-occurrence matrix, and more derivatives of the volume data of the nodules. To evaluate the presented approach, the Lung Image Database Consortium public database was downloaded. Each case of the database contains an annotation file, which indicates the diagnosis results from up to four radiologists. In order to relieve partial-volume effect, interpolation process was carried out to those volume data with image slice thickness more than 1mm, and thus we had categorized the downloaded datasets to five groups to validate the proposed approach, one group of thickness less than 1mm, two types of thickness range from 1mm to 1.25mm and greater than 1.25mm (each type contains two groups, one with interpolation and the other without). Since support vector machine is based on statistical learning theory and aims to learn for predicting future data, so it was chosen as the classifier to perform the differentiation task. The measure on the performance was based on the area under the curve (AUC) of Receiver Operating Characteristics. From 284 nodules (122 malignant and 162 benign ones), the validation experiments reported a mean of 0.9051 and standard deviation of 0.0397 for the AUC value on average over 100 randomizations

The intravenous, intramuscular or intraperitoneal administration of water solubilized graphene nanoparticles for biomedical applications will result in their interaction with the hematological components and vasculature. Herein, we have investigated the effects of dextran functionalized graphene nanoplatelets (GNP-Dex) on histamine release, platelet activation, immune activation, blood cell hemolysis in vitro, and vasoactivity in vivo. The results indicate that GNP-Dex formulations prevented histamine release from activated RBL-2H3 rat mast cells, and at concentrations >/= 7 mg/ml, showed a 12-20% increase in levels of complement proteins. Cytokine (TNF-Alpha and IL-10) levels remained within normal range. GNP-Dex formulations did not cause platelet activation or blood cell hemolysis. Using the hamster cheek pouch in vivo model, the initial vasoactivity of GNP-Dex at concentrations (1-50 mg/ml) equivalent to the first pass of a bolus injection was a brief concentration-dependent dilation in arcade and terminal arterioles. However, they did not induce a pro-inflammatory endothelial dysfunction effect.

PURPOSE: This study aimed to assess the imaging findings in patients with pathologically proven carcinoid tumors and determine if SUV can help to differentiate typical from atypical (more aggressive) pulmonary carcinoid tumors. PATIENTS AND METHODS: A retrospective review of patients with a biopsy-proven diagnosis of a pulmonary carcinoid tumor at our institution from 2002 to 2010 that had a preoperative PET scan was performed after institutional review board approval was obtained. PET results, including SUV uptake and location, were recorded as well as all data from pathology reports. Carcinoids were considered to be more aggressive if they showed pathological diagnosis consistent with atypical carcinoid, lymph node invasion, poor histological grade (poorly differentiated), or evidence of systemic metastases. Atypical carcinoid pathology consisted of focal necrosis or a higher mitotic index (2-10 per square millimeter) with features of nests, trabeculae, pleomorphic cells, or dense hyperchromasia. SUV uptake was then evaluated and compared between the typical and atypical carcinoid groups using nonparametric statistical methods. RESULTS: We identified 29 patients from 2002 to 2010 at our institution with a pathological diagnosis of pulmonary carcinoid. Twenty-three were histopathologically typical, and the other 6 showed atypia. Mean (SD) nodule size was 2.4 (1.3) cm in the typical group versus 5.0 (3.2) cm in the atypical group (P = 0.065). Mean (SD) SUV uptake in the typical carcinoid group was 2.7 (1.6) and in the atypical group the SUV was 8.1 (4.1) (P < 0.01). A cutoff SUV of 6 or greater is predictive of malignancy (odds ratio, 23.6; P < 0.01), as well as a nodule size of 3.5 cm or greater (odds ratio, 5.1; P = 0.024). CONCLUSIONS: Preoperative PET imaging result is frequently positive in carcinoid tumors, and the biological behavior correlates well with SUV; however, size is not as strong of a predictor of malignancy. Size of 3.5 cm or greater and SUV of 6 or greater have a predictive value of greater than 95% for malignant histology.

BACKGROUND: Non-small cell lung cancer (NSCLC) has a predilection to occur in emphysematous lungs. The relation between the regional severity of emphysema and the location of NSCLC as well as long-term survival has been poorly studied. METHODS: Computed tomography (CT) scans of 153 patients with biopsy-proven stage I NSCLC diagnosed between 2001 and 2006 were assigned an emphysema severity score in four regions of the lung. The location of the cancer was compared with the severity of emphysema in that region. Survival was also analyzed. RESULTS: Thirty-nine patients had no emphysema documented on CT scan and 114 did. The most common location of cancer was the right upper quadrant with 37% of cancers, followed by the left upper quadrant with 23% of cancers. Twenty-two percent of the cancers occurred in the right lower quadrant, and only 12% were in the left lower quadrant. There is a strong association for cancer being located in the area with the highest degree of emphysema (P < 0.001). Emphysema severity score was also associated with long-term survival (log-rank P = 0.03). CONCLUSIONS: The regional severity of emphysema assessed via a visual scale using CT appears to be associated with the location of lung cancer and is an independent predictor of long-term survival.

We report the synthesis and characterization of a novel carbon nanostructure-based magnetic resonance imaging contrast agent (MRI CA); graphene nanoplatelets intercalated with manganese (Mn(2+)) ions, functionalized with dextran (GNP-Dex); and the in vitro assessment of its essential preclinical physicochemical properties: osmolality, viscosity, partition coefficient, protein binding, thermostability, histamine release, and relaxivity. The results indicate that, at concentrations between 0.1 and 100.0 mg/mL, the GNP-Dex formulations are hydrophilic, highly soluble, and stable in deionized water, as well as iso-osmolar (upon addition of mannitol) and iso-viscous to blood. At potential steady-state equilibrium concentrations in blood (0.1-10.0 mg/mL), the thermostability, protein-binding, and histamine-release studies indicate that the GNP-Dex formulations are thermally stable (with no Mn(2+) ion dissociation), do not allow non-specific protein adsorption, and elicit negligible allergic response. The r 1 relaxivity of GNP-Dex was 92 mM(-1)s(-1) (per-Mn(2+) ion, 22 MHz proton Larmor frequency); ~20- to 30-fold greater than that of clinical gadolinium (Gd(3+))- and Mn(2+)-based MRI CAs. The results open avenues for preclinical in vivo safety and efficacy studies with GNP-Dex toward its development as a clinical MRI CA.