The underlying factor structure of National Institutes of Health Stroke scale: an exploratory factor analysis.

The underlying structure of National Institutes of Health Stroke Scale (NIHSS) as the most widely used scale in clinical trials has been the focus of little attention. The aim of the current study was to elucidate the clustering pattern of NIHSS items in ischemic stroke patients. A series of 152 consecutive patients with first-ever ischemic strokes admitted to a university affiliated hospital were enrolled. NIHSS score was estimated on admission and correlation coefficients between its items were calculated. Further, exploratory factor analysis was used to study the clustering pattern of NIHSS items. Extinction neglect, visual field, and facial palsy were weakly associated with other NIHSS items. Factor analysis led to a four-factor structure. Factors 1 and 3 were determined by left brain function as items of right arm and leg motor, language and dysarthria loaded on both of them. By contrast, factor 2 reflected right brain involvement. Since visual field and ataxia loaded on factor 4, this factor was primarily associated with posterior strokes. Our study shows that a four-factor structure model is plausible for NIHSS. Further, for the first time, a single distinct factor is identified for posterior strokes.

Prediction of lymphovascular space invasion in cervical carcinoma using diffusion kurtosis imaging.

BACKGROUND: This study aimed to investigate the potential relationship between diffusion kurtosis imaging (DKI)- derived parameters and lymphovascular space invasion (LVSI) in patients with cervical carcinoma. PATIENTS AND METHODS: This prospective study included 30 patients with cervical carcinoma. The patients underwent MRI, diffusion-weighted imaging (DWI), and DKI prior to surgery. The surgical pathology results were accepted as the reference standard for determining the LVSI status. The DKI-derived parameters, including mean diffusivity (MD) and mean kurtosis (MK), were measured. The apparent diffusion coefficient (ADC) value was also assessed. RESULTS: The MD value of LVSI positive cervical carcinomas was significantly lower than LVSI negative carcinomas (p-value = 0.01). MK value was significantly higher in LVSI positive tumors (p-value = 0.01). However, the ADC value did not show a significant difference between LVSI positive and LVSI negative tumors (p-value = 0.2). MD and MK parameters showed similar diagnostic accuracy in identifying the LVSI status, with the area under the curve of 0.77 and 0.78, respectively. CONCLUSION: In this study, DKI-derived parameters were associated with the LVSI status in cervical carcinomas. Further studies with larger sample size are required to confirm these results.

Improved Diagnostic Accuracy in Characterization of Adnexal Masses by Detection of Choline Peak Using 1H MR Spectroscopy in Comparison to Internal Reference at 3 Tesla.

BACKGROUND: The aim of this study was to assess the role of the presence of a choline peak in 3 Tesla 1H magnetic resonance spectroscopy (MRS) for differentiating benign from malignant adnexal masses. MATERIALS AND METHODS: A total of 46 adnexal masses (23 malignant and 23 benign) underwent 1H MRS study prior to surgery to assess the presence of choline peak. RESULTS: A choline peak was detected in 16 malignant masses (69.5%) and was absent in the other 7 (30.5%). A choline peak was only detected in 6 (26%) of the benign adnexal masses. The presence of an MRS choline peak had a sensitivity of 69.5%, a specificity of 74%, a positive predictive value (PPV) of 72.7%, and a negative predictive value (NPV) of 71% for diagnosing malignant adnexal masses. A significant difference between the frequency of mean choline peaks in benign and malignant adnexal masses was observed (P value<0.01). CONCLUSIONS: A 1H MRS choline peak is seen in malignant adnexal masses more frequently than the benign masses, and may be helpful for diagnosing malignant adnexal masses.

Differentiation of benign from malignant adnexal masses by functional 3 tesla MRI techniques: diffusion-weighted imaging and time-intensity curves of dynamic contrast-enhanced MRI.

BACKGROUND: The aim of this study was to evaluate and compare the accuracy of diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) value, and time-intensity curve (TIC) type analysis derived from dynamic contrast-enhanced MR imaging (DCE-MRI) in differentiating benign from malignant adnexal masses. MATERIALS AND METHODS: 47 patients with 56 adnexal masses (27 malignant and 29 benign) underwent DWI and DCE-MRI examinations, prior to surgery. DWI signal intensity, mean ADC value, and TIC type were determined for all the masses. RESULTS: High signal intensity on DWI and type 3 TIC were helpful in differentiating benign from malignant adnexal masses (p<0.001). The mean ADC value was significantly lower in malignant adnexal masses (p<0.001). An ADC value<1.20?10-3 mm2/s may be the optimal cutoff for differentiating between benign and malignant tumors. The negative predictive value for low signal intensity on DWI, and type 1 TIC were 100%. The pairwise comparison among the receiver operating characteristic (ROC) curves showed that the area under the curve (AUC) of TIC was significantly larger than the AUCs of DWI and ADC (p<0.001 for comparison of TIC and DWI, p<0.02 for comparison of TIC and ADC value). CONCLUSIONS: DWI, ADC value and TIC type derived from DCE-MRI are all sensitive and relatively specific methods for differentiating benign from malignant adnexal masses. By comparing these functional MR techniques, TIC was found to be more accurate than DWI and ADC.

A simple risk score for early ischemic stroke mortality derived from National Institutes of Health Stroke Scale: a discriminant analysis.

OBJECTIVES: The aim of the current study was to design a new simpler form of National Institutes of Health Stroke Scale (NIHSS) for use in emergency settings, and compare its predictive ability with original NIHSS score for mortality. METHODS: A total of 152 consecutive patients with first ever ischemic stroke admitted to a university affiliated hospital were recruited. NIHSS score on admission was estimated and the predictive ability of NIHSS items for mortality at 28 days was evaluated by logistic regression. Stepwise discriminant analysis was performed on NIHSS items to obtain a discriminant function with the best discriminative ability for mortality. Further, receiver operating characteristics (ROC) curves were depicted to compare the new determined discriminant function with the original NIHSS score. RESULTS: Cumulative rate of mortality was 11.8% for 28-day follow-up period. Among NIHSS items, scores of visual field, limb ataxia and extinction neglect were not associated with mortality (P>0.05). On the contrary, level of consciousness-commands, language and gaze were determined as independent indicators of mortality (P<0.05), and their coefficients on discriminant function were equal to 0.65, 0.44 and 0.30, respectively. In addition, area under the ROC curve of the calculated discriminant function was not statistically different from NIHSS score (P>0.05). CONCLUSIONS: The suggested discriminant function, comprising NIHSS items of level of consciousness-commands, language and gaze, can predict 28-day mortality after ischemic stroke in a similar way to the original NIHSS score and can provide a baseline for stroke severity in emergency settings.