MATERIALS AND METHODS: We retrospectively assessed 107 cadavers that had undergone conventional autopsy and PMCT. We made 5 measurements from the PMCT that included cervical length (CL), thoracic length (TL), lumbosacral length (LS), total column length of the spine, excluding the sacrum and coccyx (TCL), and ellipse line measurement of the whole spine, excluding the sacrum and coccyx (EL). We compared these anthropometric PMCT measurements with AL and correlated them using linear regression analysis.
RESULTS: The results showed a significant linear relationship existed between TL and LS with AL, which was higher in comparison with the other parameters than the rest of the spine parameters. The linear regression formula derived was: 48.163 + 2.458 (TL) + 2.246 (LS).
CONCLUSIONS: The linear regression formula derived from PMCT spine length parameters particularly thoracic and lumbar spine gave a finer correlation with autopsy body length and can be used for accurate estimation of cadaveric height. To the best of our knowledge, this is the first ever linear regression formula for cadaveric height assessment using only post mortem CT spine length measurements.
METHODS: Positron emission tomography (PET) and computed tomography (CT) image data from 97 patients with LC and 77 patients with TB nodules were collected. One hundred radiomic features were extracted from both PET and CT imaging using the pyradiomics platform, and 2048 deep learning features were obtained through a residual neural network approach. Four models included traditional machine learning model with radiomic features as input (traditional radiomics), a deep learning model with separate input of image features (deep convolutional neural networks [DCNN]), a deep learning model with two inputs of radiomic features and deep learning features (radiomics-DCNN) and a deep learning model with inputs of radiomic features and deep learning features and clinical information (integrated model). The models were evaluated using area under the curve (AUC), sensitivity, accuracy, specificity, and F1-score metrics.
RESULTS: The results of the classification of TB nodules and LC showed that the integrated model achieved an AUC of 0.84 (0.82-0.88), sensitivity of 0.85 (0.80-0.88), and specificity of 0.84 (0.83-0.87), performing better than the other models.
CONCLUSION: The integrated model was found to be the best classification model in the diagnosis of TB nodules and solid LC.
OBJECTIVE: The current review was aimed to present a comprehensive overview and critical appraisal of majorly employed neuroimaging techniques for rational diagnosis and effective monitoring of effectiveness of employed therapeutic intervention for NPH. Moreover, a critical overview of recent developments and utilization of pharmacological agents for treatment of hydrocephalus has also been appraised.
RESULTS: Considering the complications associated with the shunt-based surgical operations, consistent monitoring of shunting via neuroimaging techniques hold greater clinical significance. Despite having extensive applicability of MRI and CT scan, these conventional neuroimaging techniques are associated with misdiagnosis or several health risks to patients. Recent advances in MRI (i.e., Sagittal-MRI, coronal-MRI, Time-SLIP (time-spatial-labeling-inversion-pulse), PC-MRI and diffusion-tensor-imaging (DTI)) have shown promising applicability in diagnosis of NPH. Having associated with several adverse effects with surgical interventions, non-invasive approaches (pharmacological agents) have earned greater interest of scientists, medical professional, and healthcare providers. Amongst pharmacological agents, diuretics, isosorbide, osmotic agents, carbonic anhydrase inhibitors, glucocorticoids, NSAIDs, digoxin, and gold-198 have been employed for management of NPH and prevention of secondary sensory/intellectual complications.
CONCLUSION: Employment of rational diagnostic tool and therapeutic modalities avoids misleading diagnosis and sophisticated management of hydrocephalus by efficient reduction of cerebrospinal fluid (CSF) production, reduction of fibrotic and inflammatory cascades secondary to meningitis and hemorrhage, and protection of brain from further deterioration.
METHODS: Sociometric data on networks on people who inject drugs from Hartford, CT, which were collected in 2012-2013, provided assessment of risk behaviors among 1574 injection network members, including participation in OAT and SSP. Subject's network characteristics were examined in relation to retention in OAT, as well as secondary syringe exchange using exponential random graph model (ERGM) and regression.
RESULTS: Based on the analysis, we found that probability of individuals being retained in OAT was positively associated with the OAT retention status of their peers within the network. Using simulations, we found that higher levels of positive correlation of OAT retention among network members can result in reduced risk of transmission of HIV to network partners on OAT. In addition, we found that secondary syringe exchange engagement was associated with higher probability of sharing of paraphernalia and unsterile needles at the network level.
CONCLUSIONS: Understanding how networks mediate risk behaviors is crucial for making progress toward ending the HIV epidemic.