A novel measure of reliability in Diffusion Tensor Imaging after data rejections due to subject motion.

Diffusion Tensor Imaging (DTI) is commonly challenged by subject motion during data acquisition, which often leads to corrupted image data. Currently used procedure in DTI analysis is to correct or completely reject such data before tensor estimations, however assessing the reliability and accuracy of the estimated tensor in such situations has evaded previous studies. This work aims to define the loss of data accuracy with increasing image rejections, and to define a robust method for assessing reliability of the result at voxel level. We carried out simulations of every possible sub-scheme (N=1,073,567,387) of Jones30 gradient scheme, followed by confirming the idea with MRI data from four newborn and three adult subjects. We assessed the relative error of the most commonly used tensor estimates for DTI and tractography studies, fractional anisotropy (FA) and the major orientation vector (V1), respectively. The error was estimated using two measures, the widely used electric potential (EP) criteria as well as the rotationally variant condition number (CN). Our results show that CN and EP are comparable in situations with very few rejections, but CN becomes clearly more sensitive to depicting errors when more gradient vectors and images were rejected. The error in FA and V1 was also found depend on the actual FA level in the given voxel; low actual FA levels were related to high relative errors in the FA and V1 estimates. Finally, the results were confirmed with clinical MRI data. This showed that the errors after rejections are, indeed, inhomogeneous across brain regions. The FA and V1 errors become progressively larger when moving from the thick white matter bundles towards more superficial subcortical structures. Our findings suggest that i) CN is a useful estimator of data reliability at voxel level, and ii) DTI preprocessing with data rejections leads to major challenges when assessing brain tissue with lower FA levels, such as all newborn brain, as well as the adult superficial, subcortical areas commonly traced in precise connectivity analyses between cortical regions.

Effect of varying displays and room illuminance on caries diagnostic accuracy in digital dental radiographs.

In clinical practice, digital radiographs taken for caries diagnostics are viewed on varying types of displays and usually in relatively high ambient lighting (room illuminance) conditions. Our purpose was to assess the effect of room illuminance and varying display types on caries diagnostic accuracy in digital dental radiographs. Previous studies have shown that the diagnostic accuracy of caries detection is significantly better in reduced lighting conditions. Our hypothesis was that higher display luminance could compensate for this in higher ambient lighting conditions. Extracted human teeth with approximal surfaces clinically ranging from sound to demineralized were radiographed and evaluated by 3 observers who detected carious lesions on 3 different types of displays in 3 different room illuminance settings ranging from low illumination, i.e. what is recommended for diagnostic viewing, to higher illumination levels corresponding to those found in an average dental office. Sectioning and microscopy of the teeth validated the presence or absence of a carious lesion. Sensitivity, specificity and accuracy were calculated for each modality and observer. Differences were estimated by analyzing the binary data assuming the added effects of observer and modality in a generalized linear model. The observers obtained higher sensitivities in lower illuminance settings than in higher illuminance settings. However, this was related to a reduction in specificity, which meant that there was no significant difference in overall accuracy. Contrary to our hypothesis, there were no significant differences between the accuracy of different display types. Therefore, different displays and room illuminance levels did not affect the overall accuracy of radiographic caries detection.