Michael J. Pollack

Variability in measurements of pancreatic cyst size among EUS, CT, and magnetic resonance imaging modalities.

BACKGROUND Cyst size is an important factor in the management of pancreatic cysts, both in predicting the need for surgery and the frequency of follow-up. OBJECTIVE To determine agreement and precision of EUS, CT, and magnetic resonance imaging (MRI) modalities in the evaluation of pancreatic cyst diameter. DESIGN Retrospective chart review. SETTING Tertiary-care center, January 2000 to June 2009. PATIENTS This study involved 175 patients presenting for EUS evaluation of pancreatic cysts, with size measured by at least two of the aforementioned imaging studies within a 90-day period. MAIN OUTCOME MEASUREMENTS Largest cyst diameter from EUS, CT, MRI/MRCP, and surgical pathology. RESULTS A total of 175 patients underwent EUS. Seventy-three had CT plus EUS, 33 had MRI/MRCP plus EUS, 23 had MRI/MRCP plus CT, and 15 had all imaging studies, occurring within 90 days of each other. Median size differences between studies: EUS and CT (ie, absolute value of size determined by EUS minus size determined by CT) = 4 mm (range 0-25 mm), EUS and MRI = 4 mm (range 0-17 mm), CT and MRI = 3 mm (range 2-20 mm). Median size differences for surgical pathology specimens compared with results of 12 EUS, 13 CT, and 8 MRI/MRCP studies were as follows: EUS and pathology = 9.5 mm (range 0-20 mm), CT and pathology = 5 mm (range 0-21 mm), MRI and pathology = 5.5 mm (range 2-44 mm). LIMITATIONS Interobserver variability and small sample of surgical pathology cysts. CONCLUSION There is considerable variation in size estimates of pancreatic cysts by different imaging modalities, which practitioners should take into account when making management decisions. Use of a single imaging modality is recommended during follow-up. The precision of imaging studies for measuring pancreatic cysts must be prospectively defined if change in size is to be reliably used for clinical management.

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.

Initial evaluation of a novel, prototype, forward-viewing echoendoscope in a porcine arterial bleeding model (with video)

BACKGROUND Real-time visualization of submucosal arterial flow at the base of an ulcer might improve endoscopic hemostasis by permitting more accurate assessment of the artery, precise targeting of therapy, and confirmation of vessel ablation. OBJECTIVE To evaluate the utility of a novel, forward-viewing echoendoscope in identifying bleeding submucosal arteries, guiding hemostatic therapy, and confirming cessation of flow through treated vessels. DESIGN In 7 pigs, a previously described porcine model for peptic ulcer hemorrhage was created by isolating the gastroepiploic and/or short gastric artery and tunneling it into the subserosal space at laparotomy. SETTING Animal research facility. INTERVENTION The prototype endoscope was used to image submucosal arterial flow. EUS guidance was then used to deliver endoscopic hemostatic therapy and assess treatment adequacy. MAIN OUTCOME MEASUREMENTS Identification of the target submucosal artery and successful delivery of EUS-guided endoscopic therapy, evidenced by cessation of Doppler flow through the target vessel. RESULTS Tunneled arteries were visualized endosonographically in all 7 cases. EUS-guided submucosal injection of epinephrine was successful in 2 of 2 cases. EUS-guided delivery of thermal hemostatic therapy was successful in 2 of 4 cases. Absence of flow through treated vessels was confirmed in cases in which EUS-guided therapy was successfully delivered. LIMITATIONS Acute animal model. CONCLUSION Proof of principle experiments in a porcine peptic ulcer hemorrhage model suggest that real-time sonographic imaging of submucosal arteries is feasible with a forward-viewing echoendoscope, and guided hemostatic therapy can be delivered.

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.