Stability of white matter changes related to Huntington's disease in the presence of imaging noise: a DTI study.

Movement artifacts and other sources of noise are a matter of concern particularly in the neuroimaging research of movement disorders such as Huntington's disease (HD). Using diffusion weighted imaging (DWI) and fractional anisotropy (FA) as a compound marker of white matter integrity, we investigated the effect of movement on HD specific changes in magnetic resonance imaging (MRI) data and how post hoc compensation for it affects the MRI results. To this end, we studied by 3T MRI: 18 early affected, 22 premanifest gene-positive subjects, 23 healthy controls (50 slices of 2.3 mm thickness per volume, 64 diffusion-weighted directions (b = 1000 s/mm2), 8 minimal diffusion-weighting (b = 100 s/mm2)); and by 1.5 T imaging: 29 premanifest HD, 30 controls (40 axial slices of 2.3 mm thickness per volume, 61 diffusion-weighted directions (b = 1000 s/mm2), minimal diffusion-weighting (b = 100 s/mm2)). An outlier based method was developed to identify movement and other sources of noise by comparing the index DWI direction against a weighted average computed from all other directions of the same subject. No significant differences were observed when separately comparing each group of patients with and without removal of DWI volumes that contained artifacts. In line with previous DWI-based studies, decreased FA in the corpus callosum and increased FA around the basal ganglia were observed when premanifest mutation carriers and early affected patients were compared with healthy controls. These findings demonstrate the robustness of the FA value in the presence of movement and thus encourage multi-center imaging studies in HD

An expression signature of the angiogenic response in gastrointestinal neuroendocrine tumours: correlation with tumour phenotype and survival outcomes.

BACKGROUND: Gastroenteropancreatic neuroendocrine tumours (GEP-NETs) are heterogeneous with respect to biological behaviour and prognosis. As angiogenesis is a renowned pathogenic hallmark as well as a therapeutic target, we aimed to investigate the prognostic and clinico-pathological role of tissue markers of hypoxia and angiogenesis in GEP-NETs. METHODS: Tissue microarray (TMA) blocks were constructed with 86 tumours diagnosed from 1988 to 2010. Tissue microarray sections were immunostained for hypoxia inducible factor 1α (Hif-1α), vascular endothelial growth factor-A (VEGF-A), carbonic anhydrase IX (Ca-IX) and somatostatin receptors (SSTR) 1–5, Ki-67 and CD31. Biomarker expression was correlated with clinico-pathological variables and tested for survival prediction using Kaplan–Meier and Cox regression methods. RESULTS: Eighty-six consecutive cases were included: 51% male, median age 51 (range 16–82), 68% presenting with a pancreatic primary, 95% well differentiated, 51% metastatic. Higher grading (P=0.03), advanced stage (P<0.001), high Hif-1α and low SSTR-2 expression (P=0.03) predicted for shorter overall survival (OS) on univariate analyses. Stage, SSTR-2 and Hif-1α expression were confirmed as multivariate predictors of OS. Median OS for patients with SSTR-2+/Hif-1α-tumours was not reached after median follow up of 8.8 years, whereas SSTR-2-/Hif-1α+ GEP-NETs had a median survival of only 4.2 years (P=0.006). CONCLUSION: We have identified a coherent expression signature by immunohistochemistry that can be used for patient stratification and to optimise treatment decisions in GEP-NETs independently from stage and grading. Tumours with preserved SSTR-2 and low Hif-1α expression have an indolent phenotype and may be offered less aggressive management and less stringent follow up

Exploiting inflammation for therapeutic gain in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy associated with &#60;5% 5-year survival, in which standard chemotherapeutics have limited benefit. The disease is associated with significant intra- and peritumoral inflammation and failure of protective immunosurveillance. Indeed, inflammatory signals are implicated in both tumour initiation and tumour progression. The major pathways regulating PDAC-associated inflammation are now being explored. Activation of leukocytes, and upregulation of cytokine and chemokine signalling pathways, both have been shown to modulate PDAC progression. Therefore, targeting inflammatory pathways may be of benefit as part of a multi-target approach to PDAC therapy. This review explores the pathways known to modulate inflammation at different stages of tumour development, drawing conclusions on their potential as therapeutic targets in PDAC

Peri-ampullary mixed acinar-endocrine carcinoma

Mixed acinar-endocrine carcinomas (MAEC) are rare tumors of the pancreas. We present the case of a patient with periampullary tumor that presented with painless jaundice and after investigation was found to have MAEC. He underwent pancreaticoduo-dunectomy with tumor free margins and negative lymph nodes. The patient presented with local recurrence and liver metastasis after 1 year and is on chemotherapy with stable lesions 30 months after the diagnosis

Precursor lesions of early onset pancreatic cancer

Early onset pancreatic cancer (EOPC) constitutes less than 5% of all newly diagnosed cases of pancreatic cancer (PC). Although histopathological characteristics of EOPC have been described, no detailed reports on precursor lesions of EOPC are available. In the present study, we aimed to describe histopathological picture of extratumoral parenchyma in 23 cases of EOPCs (definition based on the threshold value of 45 years of age) with particular emphasis on two types of precursor lesions of PC: pancreatic intraepithelial neoplasia (PanIN) and intraductal papillary mucinous neoplasms (IPMNs). The types, grades, and densities of precursor lesions of PC were compared in patients with EOPCs, in young patients with neuroendocrine neoplasms (NENs), and in older (at the age of 46 or more) patients with PC. PanINs were found in 95.6% of cases of EOPCs. PanINs-3 were found in 39.1% of EOPC cases. Densities of all PanIN grades in EOPC cases were larger than in young patients with NENs. Density of PanINs-1A in EOPC cases was larger than in older patients with PC, but densities of PanINs of other grades were comparable. IPMN was found only in a single patient with EOPC but in 20% of older patients with PC. PanINs are the most prevalent precursor lesions of EOPC. IPMNs are rarely precursor lesions of EOPC. Relatively high density of low-grade PanINs-1 in extratumoral parenchyma of patients with EOPC may result from unknown multifocal genetic alterations in pancreatic tissue in patients with EOPCs

A huge intraductal papillary mucinous carcinoma of the bile duct treated by right trisectionectomy with caudate lobectomy

<p>Abstract</p> <p>Background</p> <p>Because intraductal papillary mucinous neoplasm of the bile duct (IPMN-B) is believed to show a better clinical course than non-papillary biliary neoplasms, it is important to make a precise diagnosis and to perform complete surgical resection.</p> <p>Case presentation</p> <p>We herein report a case of malignant IPMN-B treated by right trisectionectomy with caudate lobectomy and extrahepatic bile duct resection. Radiologic images showed marked dilatation of the left medial sectional bile duct (B4) resulting in a bulky cystic mass with multiple internal papillary projections. Duodenal endoscopic examination demonstrated very patulous ampullary orifice with mucin expulsion and endoscopic retrograde cholangiogram confirmed marked cystic dilatation of B4 with luminal filling defects. These findings suggested IPMN-B with malignancy potential. The functional volume of the left lateral section was estimated to be 45%. A planned extensive surgery was successfully performed. The remnant bile ducts were also dilated but had no macroscopic intraluminal tumorous lesion. The histopathological examination yielded the diagnosis of mucin-producing oncocytic intraductal papillary carcinoma of the bile duct with poorly differentiated carcinomas showing neuroendocrine differentiation. The tumor was 14.0 × 13.0 cm-sized and revealed no stromal invasiveness. Resection margins of the proximal bile duct and hepatic parenchyma were free of tumor cell. The patient showed no postoperative complication and was discharged on 10^thpostoperative date. He has been regularly followed at outpatient department with no evidence of recurrence.</p> <p>Conclusion</p> <p>Considering a favorable prognosis of IPMN-B compared to non-papillary biliary neoplasms, this tumor can be a good indication for aggressive surgical resection regardless of its tumor size.</p

Composition of human islet cell preparations for transplantation

To study the cellular composition of human islet cell isolates for transplantation, formalin-fixed and paraffin-embedded cell pellets were stained by the immunoperoxidase method with a panel of antibodies characterising endocrine, epithelial, soft tissue and haematolymphoid components. Immediately after separation, the isolates contained 30-80% islet cells, differing mainly in the content of islet and acinar cells, whereas the soft tissue, ductal/ductular and haematolymphoid elements comprised a relatively constant 10-20%. After 1 week in culture the islet cell content of less highly purified isolates (30-40% islets) dropped dramatically to 5%. The highly purified isolates (70-80% islets) showed only a minimal change in cellular composition; however, approximately two-thirds of islet cells were degranulated and did not stain for insulin. Haematolymphoid components were still present in all cultured isolates. We conclude that primarily mechanical purification methods and short-term culture are not sufficient to eliminate highly immunogenic cells. In addition, short-term culture is deleterious to the isolate if a significant number of acinar cells is still present after enrichment. © 1992 Springer-Verlag

The Marker State Space (MSS) Method for Classifying Clinical Samples

The development of accurate clinical biomarkers has been challenging in part due to the diversity between patients and diseases. One approach to account for the diversity is to use multiple markers to classify patients, based on the concept that each individual marker contributes information from its respective subclass of patients. Here we present a new strategy for developing biomarker panels that accounts for completely distinct patient subclasses. Marker State Space (MSS) defines "marker states" based on all possible patterns of high and low values among a panel of markers. Each marker state is defined as either a case state or a control state, and a sample is classified as case or control based on the state it occupies. MSS was used to define multi-marker panels that were robust in cross validation and training-set/test-set analyses and that yielded similar classification accuracy to several other classification algorithms. A three-marker panel for discriminating pancreatic cancer patients from control subjects revealed subclasses of patients based on distinct marker states. MSS provides a straightforward approach for modeling highly divergent subclasses of patients, which may be adaptable for diverse applications. © 2013 Fallon et al

Comparison of artificial neural network and logistic regression models for prediction of mortality in head trauma based on initial clinical data

BACKGROUND: In recent years, outcome prediction models using artificial neural network and multivariable logistic regression analysis have been developed in many areas of health care research. Both these methods have advantages and disadvantages. In this study we have compared the performance of artificial neural network and multivariable logistic regression models, in prediction of outcomes in head trauma and studied the reproducibility of the findings. METHODS: 1000 Logistic regression and ANN models based on initial clinical data related to the GCS, tracheal intubation status, age, systolic blood pressure, respiratory rate, pulse rate, injury severity score and the outcome of 1271 mainly head injured patients were compared in this study. For each of one thousand pairs of ANN and logistic models, the area under the receiver operating characteristic (ROC) curves, Hosmer-Lemeshow (HL) statistics and accuracy rate were calculated and compared using paired T-tests. RESULTS: ANN significantly outperformed logistic models in both fields of discrimination and calibration but under performed in accuracy. In 77.8% of cases the area under the ROC curves and in 56.4% of cases the HL statistics for the neural network model were superior to that for the logistic model. In 68% of cases the accuracy of the logistic model was superior to the neural network model. CONCLUSIONS: ANN significantly outperformed the logistic models in both fields of discrimination and calibration but lagged behind in accuracy. This study clearly showed that any single comparison between these two models might not reliably represent the true end results. External validation of the designed models, using larger databases with different rates of outcomes is necessary to get an accurate measure of performance outside the development population