38 research outputs found
Potentials of Plasma NGAL and MIC-1 as Biomarker(s) in the Diagnosis of Lethal Pancreatic Cancer
Pancreatic cancer (PC) is lethal malignancy with very high mortality rate. Absence of sensitive and specific marker(s) is one of the major factors for poor prognosis of PC patients. In pilot studies using small set of patients, secreted acute phase proteins neutrophil gelatinase associated lipocalin (NGAL) and TGF-β family member macrophage inhibitory cytokine-1 (MIC-1) are proposed as most potential biomarkers specifically elevated in the blood of PC patients. However, their performance as diagnostic markers for PC, particularly in pre-treatment patients, remains unknown. In order to evaluate the diagnostic efficacy of NGAL and MIC-1, their levels were measured in plasma samples from patients with pre-treatment PC patients (n = 91) and compared it with those in healthy control (HC) individuals (n = 24) and patients with chronic pancreatitis (CP, n = 23). The diagnostic performance of these two proteins was further compared with that of CA19-9, a tumor marker commonly used to follow PC progression. The levels of all three biomarkers were significantly higher in PC compared to HCs. The mean (± standard deviation, SD) plasma NGAL, CA19-9 and MIC-1 levels in PC patients was 111.1 ng/mL (2.2), 219.2 U/mL (7.8) and 4.5 ng/mL (4.1), respectively. In comparing resectable PC to healthy patients, all three biomarkers were found to have comparable sensitivities (between 64%-81%) but CA19-9 and NGAL had a higher specificity (92% and 88%, respectively). For distinguishing resectable PC from CP patients, CA19-9 and MIC-1 were most specific (74% and 78% respectively). CA19-9 at an optimal cut-off of 54.1 U/ml is highly specific in differentiating resectable (stage 1/2) pancreatic cancer patients from controls in comparison to its clinical cut-off (37.1 U/ml). Notably, the addition of MIC-1 to CA19-9 significantly improved the ability to distinguish resectable PC cases from CP (p = 0.029). Overall, MIC-1 in combination with CA19-9 improved the diagnostic accuracy of differentiating PC from CP and HCs
Quantitative Computed Tomography in COPD: Possibilities and Limitations
Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease that is characterized by chronic airflow limitation. Unraveling of this heterogeneity is challenging but important, because it might enable more accurate diagnosis and treatment. Because spirometry cannot distinguish between the different contributing pathways of airflow limitation, and visual scoring is time-consuming and prone to observer variability, other techniques are sought to start this phenotyping process. Quantitative computed tomography (CT) is a promising technique, because current CT technology is able to quantify emphysema, air trapping, and large airway wall dimensions. This review focuses on CT quantification techniques of COPD disease components and their current status and role in phenotyping COPD
AAR‐LN‐DQ: Automatic anatomy recognition based disease quantification in thoracic lymph node zones via FDG PET/CT images without Nodal Delineation
A new dimension of FDG-PET interpretation: assessment of tumor biology.
(18)F-Fluoro-2-deoxy-D-glucose (FDG) positron emission tomography (PET) is increasingly being used for the evaluation of several malignancies. Key to the correct interpretation of oncological FDG-PET studies is awareness of the concept that the degree of FDG uptake reflects the biology of the tumor in many cancers. More specifically, cancers with high FDG uptake are often histologically and clinically more aggressive than those with low or no FDG uptake. Therefore, although a negative FDG-PET scan in a patient with a cancer that has a size above the spatial resolution of PET may be interpreted as false-negative in terms of tumor detectability, it should in fact be regarded as true-negative from the view-point of tumor biology. This nonsystematic review will give examples of several major cancers in which the relationship between FDG avidity and tumor biology is applicable, and emphasizes the need to reconsider the definition of a "false-negative" FDG-PET scan in clinical oncology