Acute Obstructive Choledocholithiasis: A Case of Elusive Gallstones on Imaging.

Acute choledocholithiasis results when stones form in the gallbladder and then pass into the common bile duct, where they may become lodged and cause obstruction. To our knowledge, very few cases are reported in which multiple imaging techniques had failed to detect the presence of gallstones, as per current literature review. We report a case of a 73-year-old woman with nausea, vomiting, and jaundice who was found to have choledocholithiasis with negative imaging on abdominal ultrasound (US), CT, and magnetic resonance cholangiopancreatography (MRCP).

Development of the hybrid cells in series model to simulate ammonia nutrient pollutant transport along the Umgeni River.

Discharge of organic waste results in high nutrient pollution of the water bodies which is a major menace to the environment. A high quantity of nutrients such as ammonia causes a reduction in the dissolved oxygen level and induces algal growth in the water bodies. Water quality models have been the tools to evaluate the rate at which streams can disperse the pollutants they receive. Many water quality models are flawed either because of their inadequacy to completely simulate the advection component of the pollutant transport, or because of the limited application of the models, due to inaccurate estimation of model parameters. The hybrid cell in series (HCIS) developed by Ghosh et al. (2004) has been able to overcome such difficulties associated with the mixing cell-based models. Thus, the current study focuses on developing an analytical solution for the pollutant transport of the ammonia concentration through the plug flow, the first and second well-mixed cells of the HCIS model. The HCIS model coupled with the first order kinetic equation for ammonia nutrient was developed to simulate the ammonia pollutant concentration in the water column. The ammonia concentration at various points along the river system was assessed by considering the effects of the transformation of ammonia to nitrite, the uptake of ammonia by the algae, the respiration rate of the algae and the input of benthic source to the ammonia concentration in the water column. The proposed model was tested using synthetic data, and the HCIS-NH3 model simulations for spatial and temporal variation of ammonia pollutant transport were analysed. The simulated results of the HCIS-NH3 model agreed with the Fickian-based advection-dispersion equation (ADE) for simulating ammonia concentration solved using an explicit finite difference scheme. The HCIS-NH3 model also showed a good agreement with the observed data from the Umgeni River, except during rainy periods.

In vivo characterization of pancreatic and lymph node tissue by using EUS spectrum analysis: a validation study.

BACKGROUND: Quantitative spectral analysis of the radiofrequency (RF) signals that underlie grayscale EUS images can be used to provide additional, objective information about tissue state. OBJECTIVE: Our purpose was to validate RF spectral analysis as a method to distinguish between (1) benign and malignant lymph nodes and (2) normal pancreas, chronic pancreatitis, and pancreatic cancer. DESIGN AND SETTING: A prospective validation study of eligible patients was conducted to compare with pilot study RF data. PATIENTS: Forty-three patients underwent EUS of the esophagus, stomach, pancreas, and surrounding intra-abdominal and mediastinal lymph nodes (19 from a previous pilot study and 24 additional patients). MAIN OUTCOME MEASUREMENTS: Midband fit, slope, intercept, and correlation coefficient from a linear regression of the calibrated RF power spectra were determined. RESULTS: Discriminant analysis of mean pilot-study parameters was then performed to classify validation-study parameters. For benign versus malignant lymph nodes, midband fit and intercept (both with t test P < .058) provided classification with 67% accuracy and area under the receiver operating curve (AUC) of 0.86. For diseased versus normal pancreas, midband fit and correlation coefficient (both with analysis of variance P < .001) provided 93% accuracy and an AUC of 0.98. For pancreatic cancer versus chronic pancreatitis, the same parameters provided 77% accuracy and an AUC of 0.89. Results improved further when classification was performed with all data. LIMITATIONS: Moderate sample size and spatial averaging inherent to the technique. CONCLUSIONS: This study confirms that mean spectral parameters provide a noninvasive method to quantitatively discriminate benign and malignant lymph nodes as well as normal and diseased pancreas.

Characterization of pancreatic cancer and intra-abdominal lymph node malignancy using spectrum analysis of endoscopic ultrasound imaging.

This study assessed the ability of spectral analysis of endoscopic ultrasound (EUS) RF signals acquired in humans in vivo to distinguish between (1) benign and malignant intraabdominal and mediastinal lymph nodes and (2) pancreatic cancer, chronic pancreatitis, and normal pancreas. Mean midband fit, slope, intercept, and correlation coefficient from a linear regression of the calibrated RF power spectra were computed over regions of interest defined by the endoscopist. Linear discriminant analysis was then performed to develop a classification of the resulting spectral parameters. For lymph nodes, classification based on the midband fit and intercept provided 67% sensitivity, 82% specificity, and 73% accuracy for malignant vs. benign nodes. For pancreas, classification based on midband fit and correlation coefficient provided 95% sensitivity, 93% specificity, and 93% accuracy for diseased vs. normal pancreas and 85% sensitivity, 71% specificity, and 85% accuracy for pancreatic cancer vs. chronic pancreatitis. These promising results suggest that mean spectral parameters can provide a non-invasive method to quantitatively characterize pancreatic cancer and lymph malignancy in vivo.

Automated quantification of colonic crypt morphology using integrated microscopy and optical coherence tomography.

Colonic crypt morphological patterns have shown a close correlation with histopathological diagnosis. Imaging technologies such as high-magnification chromoendoscopy and endoscopic optical coherence tomography (OCT) are capable of visualizing crypt morphology in vivo. We have imaged colonic tissue in vitro to simulate high-magnification chromoendoscopy and endoscopic OCT and demonstrate quantification of morphological features of colonic crypts using automated image analysis. 2-D microscopic images with methylene blue staining and correlated 3-D OCT volumes were segmented using marker-based watershed segmentation. 2-D and 3-D crypt morphological features were quantified. The accuracy of segmentation was validated, and measured features are in agreement with known crypt morphology. This work can enable studies to determine the clinical utility of high-magnification chromoendoscopy and endoscopic OCT, as well as studies to evaluate crypt morphology as a biomarker for colonic disease progression.

EUS spectrum analysis for in vivo characterization of pancreatic and lymph node tissue: a pilot study.

BACKGROUND: EUS is limited by variability in the examiner's subjective interpretation of B-scan images to differentiate among normal, inflammatory, and malignant tissue. By using information otherwise discarded by conventional EUS systems, quantitative spectral analysis of the raw radiofrequency (RF) signals underlying EUS images enables tissue to be characterized more objectively. OBJECTIVE: Our purpose was to determine the feasibility of using spectral analysis of EUS data for characterization of pancreatic tissue and lymph nodes. DESIGN AND SETTING: A pilot study of eligible patients was conducted to analyze the RF data obtained during EUS by using spectral parameters. PATIENTS: Twenty-one subjects who underwent EUS of the esophagus, stomach, pancreas, and surrounding intra-abdominal and mediastinal lymph nodes. MAIN OUTCOME MEASUREMENTS: Linear regression parameters of calibrated power spectra of the RF signals were tested to differentiate normal pancreas from chronic pancreatitis and from pancreatic cancer as well as benign from malignant-appearing lymph nodes. RESULTS: The mean intercept, slope, and midband fit of the spectra differed significantly among normal pancreas, adenocarcinoma, and chronic pancreatitis when all were compared with each other (P < .01). On direct comparison, mean midband fit for adenocarcinoma differed significantly from that for chronic pancreatitis (P < .05). For lymph nodes, mean midband fit and intercept differed significantly between benign- and malignant-appearing lymph nodes (P < .01 and P < .05, respectively). LIMITATIONS: Small sample population and spatial averaging inherent to this technique. CONCLUSIONS: Mean spectral parameters in EUS imaging can provide a noninvasive method to discriminate normal from diseased pancreas and lymph nodes.