Peripheral neuropathy in chronic obstructive pulmonary disease (COPD) has received scanty attention. The purpose of this study was to evaluate objectively the functional changes in the peripheral nervous system in COPD by different electrophysiological parameters and to determine the frequencies of these changes in patients with COPD. Aim of the study is assessment of peripheral nerve conduction by evaluation of the motor and sensory nerve conduction (SNC) in COPD patients.

Peripheral neuropathy in chronic obstructive pulmonary disease (COPD) has received scanty attention. The purpose of this study was to evaluate objectively the functional changes in the peripheral nervous system in COPD by different electrophysiological parameters and to determine the frequencies of these changes in patients with COPD. Aim of the study is assessment of peripheral nerve conduction by evaluation of the motor and sensory nerve conduction (SNC) in COPD patients.

Chronic obstructive pulmonary disease (COPD) is an increasingly common disease among older adults that has been linked to other comorbid conditions with serious morbidity and mortality, including cognition impairment. However, it remains poorly understood in COPD. The aim of this study is to evaluate cognitive dysfunction in COPD and to relate it to the severity obtained from spirometric and gasometric evaluation of COPD patients.

Chronic obstructive pulmonary disease (COPD) is an increasingly common disease among older adults that has been linked to other comorbid conditions with serious morbidity and mortality, including cognition impairment. However, it remains poorly understood in COPD. The aim of this study is to evaluate cognitive dysfunction in COPD and to relate it to the severity obtained from spirometric and gasometric evaluation of COPD patients.

Chronic obstructive pulmonary disease (COPD) is an increasingly common disease among older adults that has been linked to other comorbid conditions with serious morbidity and mortality, including cognition impairment. However, it remains poorly understood in COPD. The aim of this study is to evaluate cognitive dysfunction in COPD and to relate it to the severity obtained from spirometric and gasometric evaluation of COPD patients.

Chronic obstructive pulmonary disease (COPD) is an increasingly common disease among older adults that has been linked to other comorbid conditions with serious morbidity and mortality, including cognition impairment. However, it remains poorly understood in COPD. The aim of this study is to evaluate cognitive dysfunction in COPD and to relate it to the severity obtained from spirometric and gasometric evaluation of COPD patients.

Chronic obstructive pulmonary disease (COPD) is an increasingly common disease among older adults that has been linked to other comorbid conditions with serious morbidity and mortality, including cognition impairment. However, it remains poorly understood in COPD. The aim of this study is to evaluate cognitive dysfunction in COPD and to relate it to the severity obtained from spirometric and gasometric evaluation of COPD patients.

Methods: 21 patients with histopathological confirmed glioma were included. Imaging was achieved on a 1.5T MRI scanner. Dynamic susceptibility contrast (DSC) MRI was performed using T2* weighted gradient echo-planner imaging (EPI). A series of 50 dynamic scans were acquired at 1.9 seconds intervals after intravenous bolus injection of 10 mmol/kg Gd- DTPA. Multiple ROIs have been drawn in the hot spots of both intra-tumoral and peri-tumoral regions, corresponding the colour maps. The highest ROI has been selected to represent the rCBV of each intra-tumoral and peri-tumoral regions. Tumors were subdivided into low grades and high grade on the basis of histopathology. Receiver operating characteristic analysis of rCBV, of both intra-tumoral and peri-tumoral regions, was performed to find cutoff values between high and low grade tumors. The resulting sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated. Results: Based on the histopathology, high grade glioma (HGG) represented 71.4% whereas low grade glioma (LGG) represented 28.8%. Both intra-tumoral and peri-tumoral rCBV of HGG were significantly higher than those of LGG. The cut-off value = 2.9 for intratumoral rCBV provided sensitivity, specificity, positive predictive values, negative predictive values, and accuracy of 80%, 100%, 100%, 66.7% and 85.7% respectively to differentiate between HGG and LGG. Additionally, the cut-off value = 0.7 for peri-tumoral rCBV provided sensitivity, specificity, positive predictive values, negative predictive values, and accuracy of 100%, 66.6%, 88.2%, 100%, and 90.5% respectively to differentiate between HGG and LGG. Conclusion: ROI of the highest rCBV is significantly reliable for the preoperative distinction between HGG and LGG. Combined intra-tumoral and peri-tumoral rCBV provides overall better diagnostic accuracy and helps to decrease the invasive intervention for non-surgical candidates.

Methods: 21 patients with histopathological confirmed glioma were included. Imaging was achieved on a 1.5T MRI scanner. Dynamic susceptibility contrast (DSC) MRI was performed using T2* weighted gradient echo-planner imaging (EPI). A series of 50 dynamic scans were acquired at 1.9 seconds intervals after intravenous bolus injection of 10 mmol/kg Gd- DTPA. Multiple ROIs have been drawn in the hot spots of both intra-tumoral and peri-tumoral regions, corresponding the colour maps. The highest ROI has been selected to represent the rCBV of each intra-tumoral and peri-tumoral regions. Tumors were subdivided into low grades and high grade on the basis of histopathology. Receiver operating characteristic analysis of rCBV, of both intra-tumoral and peri-tumoral regions, was performed to find cutoff values between high and low grade tumors. The resulting sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated. Results: Based on the histopathology, high grade glioma (HGG) represented 71.4% whereas low grade glioma (LGG) represented 28.8%. Both intra-tumoral and peri-tumoral rCBV of HGG were significantly higher than those of LGG. The cut-off value = 2.9 for intratumoral rCBV provided sensitivity, specificity, positive predictive values, negative predictive values, and accuracy of 80%, 100%, 100%, 66.7% and 85.7% respectively to differentiate between HGG and LGG. Additionally, the cut-off value = 0.7 for peri-tumoral rCBV provided sensitivity, specificity, positive predictive values, negative predictive values, and accuracy of 100%, 66.6%, 88.2%, 100%, and 90.5% respectively to differentiate between HGG and LGG. Conclusion: ROI of the highest rCBV is significantly reliable for the preoperative distinction between HGG and LGG. Combined intra-tumoral and peri-tumoral rCBV provides overall better diagnostic accuracy and helps to decrease the invasive intervention for non-surgical candidates.

Methods: 21 patients with histopathological confirmed glioma were included. Imaging was achieved on a 1.5T MRI scanner. Dynamic susceptibility contrast (DSC) MRI was performed using T2* weighted gradient echo-planner imaging (EPI). A series of 50 dynamic scans were acquired at 1.9 seconds intervals after intravenous bolus injection of 10 mmol/kg Gd- DTPA. Multiple ROIs have been drawn in the hot spots of both intra-tumoral and peri-tumoral regions, corresponding the colour maps. The highest ROI has been selected to represent the rCBV of each intra-tumoral and peri-tumoral regions. Tumors were subdivided into low grades and high grade on the basis of histopathology. Receiver operating characteristic analysis of rCBV, of both intra-tumoral and peri-tumoral regions, was performed to find cutoff values between high and low grade tumors. The resulting sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated. Results: Based on the histopathology, high grade glioma (HGG) represented 71.4% whereas low grade glioma (LGG) represented 28.8%. Both intra-tumoral and peri-tumoral rCBV of HGG were significantly higher than those of LGG. The cut-off value = 2.9 for intratumoral rCBV provided sensitivity, specificity, positive predictive values, negative predictive values, and accuracy of 80%, 100%, 100%, 66.7% and 85.7% respectively to differentiate between HGG and LGG. Additionally, the cut-off value = 0.7 for peri-tumoral rCBV provided sensitivity, specificity, positive predictive values, negative predictive values, and accuracy of 100%, 66.6%, 88.2%, 100%, and 90.5% respectively to differentiate between HGG and LGG. Conclusion: ROI of the highest rCBV is significantly reliable for the preoperative distinction between HGG and LGG. Combined intra-tumoral and peri-tumoral rCBV provides overall better diagnostic accuracy and helps to decrease the invasive intervention for non-surgical candidates.