Physiological characterization of skin lesion using non-linear random forest regression model.

The current diagnostic technique for melanoma solely relies on the surface level of skin and under-skin information is neglected. Since physiological features of skin such as melanin are closely related to development of melanoma, the non-linear physiological feature extraction model based on random forest regression is proposed. The proposed model characterizes the concentration of eumelanin and pheomelanin from standard camera images or dermoscopic images, which are conventionally used for diagnosis of melanoma. For the validation, the phantom study and the separability test using clinical images were conducted and compared against the state-of-the art non-linear and linear feature extraction models. The results showed that the proposed model outperformed other comparing models in phantom and clinical experiments. Promising results show that the quantitative characterization of skin features, which is provided by the proposed method, can allow dermatologists and clinicians to make a more accurate and improved diagnosis of melanoma.

Multi-penalty conditional random field approach to super-resolved reconstruction of optical coherence tomography images.

Improving the spatial resolution of Optical Coherence Tomography (OCT) images is important for the visualization and analysis of small morphological features in biological tissue such as blood vessels, membranes, cellular layers, etc. In this paper, we propose a novel reconstruction approach to obtaining super-resolved OCT tomograms from multiple lower resolution images. The proposed Multi-Penalty Conditional Random Field (MPCRF) method combines four different penalty factors (spatial proximity, first and second order intensity variations, as well as a spline-based smoothness of fit) into the prior model within a Maximum A Posteriori (MAP) estimation framework. Test carried out in retinal OCT images illustrate the effectiveness of the proposed MPCRF reconstruction approach in terms of spatial resolution enhancement, as compared to previously published super resolved image reconstruction methods. Visual assessment of the MPCRF results demonstrate the potential of this method in better preservation of fine details and structures of the imaged sample, as well as retaining the sharpness of biological tissue boundaries while reducing the effects of speckle noise inherent to OCT. Quantitative evaluation using imaging metrics such as Signal-to-Noise Ratio (SNR), Contrast to Noise Ratio (CNR), Equivalent Number of Looks (ENL), and Edge Preservation Parameter show significant visual quality improvement with the MPCRF approach. Therefore, the proposed MPCRF reconstruction approach is an effective tool for enhancing the spatial resolution of OCT images without the necessity for significant imaging hardware modifications.

Low-dose computed tomography via spatially adaptive Monte-Carlo reconstruction.

Low-dose computed tomography (CT) reduces radiation exposure but decreases signal-to-noise ratio (SNR) and diagnostic capabilities. Noise compensation can improve SNR so low-dose CT can provide valuable information for diagnosis without risking patient radiation exposure. In this study, a novel noise-compensated CT reconstruction method that uses spatially adaptive Monte-Carlo sampling to produce noise-compensated reconstructions is investigated. By adapting to local noise statistics, a non-parametric estimation of the noise-free image is computed that successfully handles non-stationary noise found in low-dose CT images. Using phantom and real low-dose CT images, effective noise suppression is shown to be accomplished while maintaining structures and details.

Predicting target vessel location on robot-assisted coronary artery bypass graft using CT to ultrasound registration.

PURPOSE: Although robot-assisted coronary artery bypass grafting (RA-CABG) has gained more acceptance worldwide, its success still depends on the surgeon's experience and expertise, and the conversion rate to full sternotomy is in the order of 15%-25%. One of the reasons for conversion is poor pre-operative planning, which is based solely on pre-operative computed tomography (CT) images. In this paper, the authors propose a technique to estimate the global peri-operative displacement of the heart and to predict the intra-operative target vessel location, validated via both an in vitro and a clinical study. METHODS: As the peri-operative heart migration during RA-CABG has never been reported in the literatures, a simple in vitro validation study was conducted using a heart phantom. To mimic the clinical workflow, a pre-operative CT as well as peri-operative ultrasound images at three different stages in the procedure (Stage(0)-following intubation; Stage(1)-following lung deflation; and Stage(2)-following thoracic insufflation) were acquired during the experiment. Following image acquisition, a rigid-body registration using iterative closest point algorithm with the robust estimator was employed to map the pre-operative stage to each of the peri-operative ones, to estimate the heart migration and predict the peri-operative target vessel location. Moreover, a clinical validation of this technique was conducted using offline patient data, where a Monte Carlo simulation was used to overcome the limitations arising due to the invisibility of the target vessel in the peri-operative ultrasound images. RESULTS: For the in vitro study, the computed target registration error (TRE) at Stage(0), Stage(1), and Stage(2) was 2.1, 3.3, and 2.6 mm, respectively. According to the offline clinical validation study, the maximum TRE at the left anterior descending (LAD) coronary artery was 4.1 mm at Stage(0), 5.1 mm at Stage(1), and 3.4 mm at Stage(2). CONCLUSIONS: The authors proposed a method to measure and validate peri-operative shifts of the heart during RA-CABG. In vitro and clinical validation studies were conducted and yielded a TRE in the order of 5 mm for all cases. As the desired clinical accuracy imposed by this procedure is on the order of one intercostal space (10-15 mm), our technique suits the clinical requirements. The authors therefore believe this technique has the potential to improve the pre-operative planning by updating peri-operative migration patterns of the heart and, consequently, will lead to reduced conversion to conventional open thoracic procedures.

Accuracy considerations in image-guided cardiac interventions: experience and lessons learned.

MOTIVATION: Medical imaging and its application in interventional guidance has revolutionized the development of minimally invasive surgical procedures leading to reduced patient trauma, fewer risks, and shorter recovery times. However, a frequently posed question with regard to an image guidance system is "how accurate is it?" On one hand, the accuracy challenge can be posed in terms of the tolerable clinical error associated with the procedure; on the other hand, accuracy is bound by the limitations of the system's components, including modeling, patient registration, and surgical instrument tracking, all of which ultimately impact the overall targeting capabilities of the system. METHODS: While these processes are not unique to any interventional specialty, this paper discusses them in the context of two different cardiac image guidance platforms: a model-enhanced ultrasound platform for intracardiac interventions and a prototype system for advanced visualization in image-guided cardiac ablation therapy. RESULTS: Pre-operative modeling techniques involving manual, semi-automatic and registration-based segmentation are discussed. The performance and limitations of clinically feasible approaches for patient registration evaluated both in the laboratory and in the operating room are presented. Our experience with two different magnetic tracking systems for instrument and ultrasound transducer localization is reported. Ultimately, the overall accuracy of the systems is discussed based on both in vitro and preliminary in vivo experience. CONCLUSION: While clinical accuracy is specific to a particular patient and procedure and vastly dependent on the surgeon's experience, the system's engineering limitations are critical to determine whether the clinical requirements can be met.

Investigating perioperative heart migration during robot-assisted coronary artery bypass grafting interventions.

OBJECTIVE: : For robot-assisted coronary artery bypass graft interventions, surgeons typically use a preoperative thoracic computed tomography scan of the patient to plan the procedure. However, the cardiac anatomy is prone to changes induced perioperatively in the effort to access the heart and surgical targets, which, in turn, may invalidate the initial plan. This article presents a method to estimate the perioperative heart migration, information which can be further exploited to refine the preoperative surgical plan. METHODS: : Tracked transesophageal ultrasound images of four patients' hearts were acquired at each stage in the procedure: before lung deflation, after lung deflation, and after both lung deflation and CO2 thoracic insufflation. Anatomic features of interest-the mitral and aortic valves-were identified from each dataset, and their movement between the different procedure stages was recorded and used to estimate the global heart displacement. Moreover, the local morphology of the features of interest was investigated to provide insight on the extent of the deformation the heart has undergone during the workflow. RESULTS: : The study suggested that the heart does undergo substantial displacement-on the order of 10 to 15 mm in each direction (axial, coronal, and sagittal) after lung deflation and CO2 thoracic insufflation. However, no significant differences (P > 0.1) were observed in the morphologic characteristics of the features of interest across the multiple workflow stages, suggesting that local deformations occur at a much smaller scale compared with the global migration. CONCLUSIONS: : The quantification of the perioperatively induced changes is critical to track the displacement of the heart and surgical targets. The recorded migration patterns should not be ignored but rather be used to update the surgical plan to better suit the intraoperative environment.

Predicting target vessel location for improved planning of robot-assisted CABG procedures.

Prior to performing a robot-assisted coronary artery bypass grafting procedure, a pre-operative computed tomography scan is used to assess patient candidacy and to identify the location of the target vessel. The surgeon then determines the optimal port locations to ensure proper reach to the target with the robotic instruments, while assuming that the heart does not undergo any significant changes between the pre- and intra-operative stages. However, the peri-operative workflow itself leads to changes in heart position and consequently the intra-operative target vessel location. As such, the pre-operative plan must be adequately updated to adjust the target vessel location to better suit the intraoperative condition. Here we propose a technique to predict the position of the peri-operative target vessel location with approximately 3.5 mm RMS accuracy. We believe this technique will potentially reduce the rate of conversion of robot-assisted procedures to traditional open-chest surgery due to poor planning.

Sanguinarine suppresses prostate tumor growth and inhibits survivin expression.

Prostate cancer is a frequently occurring disease and is the second leading cause of cancer-related deaths of men in the United States. Current treatments have proved inadequate in curing or controlling prostate cancer, and a search for agents for the management of this disease is urgently needed. Survivin plays an important role in both progression of castration-resistant prostate cancer and resistance to chemotherapy. Altered expression of survivin in prostate cancer cells is associated with cancer progression, drug/radiation resistance, poor prognosis, and short patient survival. In the present study, the authors performed a cell-based rapid screen of the Prestwick Chemical Library consisting of 1120 Food and Drug Administration-approved compounds with known safety and bioavailability in humans to identify potential inhibitors of survivin and anticancer agents for prostate cancer. Sanguinarine, a benzophenanthridine alkaloid derived primarily from the bloodroot plant, was identified as a novel inhibitor of survivin that selectively kills prostate cancer cells over "normal" prostate epithelial cells. The authors found that sanguinarine inhibits survivin protein expression through protein degradation via the ubiquitin-proteasome system. Sanguinarine induces apoptosis and inhibits growth of human prostate cancer cells and in vivo tumor formation. Administration of sanguinarine, beginning 3 days after ectopic implantation of DU145 human prostate cancer cells, reduces both tumor weight and volume. In addition, sanguinarine sensitized paclitaxel-mediated growth inhibition and apoptosis, offering a potential therapeutic strategy for overcoming taxol resistance. These results suggest that sanguinarine may be developed as an agent either alone or in combination with taxol for treatment of prostate cancer overexpressing survivin.