Using Correlative Properties of Neighboring Pixels to Enhance Contrast-to-Noise Ratio of Abnormal Hippocampus in Patients With Intractable Epilepsy and Mesial Temporal Sclerosis

Delineation of Inner Annulus Fibrosus and Nucleus Pulposus on Routine T2-weighted MR Images

STUDY DESIGN

Retrospective study of 150 IVDs.

OBJECTIVE

Assessment of costume algorithm ability to delineate the IAF and NP on routine T2 images.

SUMMARY OF BACKGROUND DATA

Central hyperintense region on T2-weighted MR images of normal lumbar IVDs represents a combination of IAF and NP. Ability to identify NP as distinct from IAF can help improve our understanding of IVD morphology in-vivo.

METHODS

Sagittal T2-weighted TSE MR images of 150 lumbar IVDs from 25 patients were analyzed. MR images were processed using a custom algorithm that markedly increased the signal intensity of structures with inherent signal intensity within 2 defined intensity thresholds. Signal intensity and contrast-to- noise ratio between outer annulus fibrosus, IAF, and NP were assessed at baseline and after processing. To assess consistency of underlying T2 differences, similar analysis was done on 108 discs from 18 patients in whom additional sagittal T2-weighted STIR images were available.

RESULTS

Following image processing, apparent IAF and NP were rendered visible in 86% and 84.3% IVDs on T2-weighted TSE and STIR images respectively. While signal intensity of these 2 regions was inherently different (P< 0.001) before processing on TSE and STIR images, their visualization was facilitated by a significant increase (P<0.001) in contrast-to-noise ratio after processing. Nonvisualization of NP was associated with disc degeneration (P<0.001).

CONCLUSION

Inherent differences exist in signal intensities of normal NP and IAF on T2-weighted MR images. Accentuating these differences using image postprocessing techniques can render these 2 structures visible.

An image processing algorithm to aid diagnosis of mesial temporal sclerosis in children: a case-control study

BACKGROUND

Mesial temporal sclerosis (MTS) is an important cause of intractable epilepsy. Early and accurate diagnosis of MTS is essential to providing curative and life-changing therapy but can be challenging in children in whom the impact of diagnosis is particularly high. Magnetic resonance imaging (MRI) plays an important role in the diagnosis of MTS, and image processing of MRI is a recently studied strategy to improve its accuracy.

OBJECTIVE

In a retrospective case-control study, we assessed the performance of an image processing algorithm (Correlative Image Enhancement [CIE]) for detecting MTS-related hippocampal signal abnormality in children.

MATERIALS AND METHODS

Twenty-seven pediatric MTS cases (9 males, 18 females; mean age: 16±standard deviation [SD] 6.7 years) were identified from a pathology database of amygdylo-hippocampectomies performed in children with epilepsy. Twenty-seven children with no seizure history (9 males, 18 females; mean age: 13.8±SD 2.8 years), and with normal brain MRI, were identified for the control group. Blinded investigators processed the MRI coronal FLAIR (fluid-attenuated inversion recovery) images with CIE, saved the processed images as a separate series, and made equivalent region of interest measurements on the processed and unprocessed series to calculate contrast-to-noise ratio. Six blinded reviewers then rated the randomized series for hippocampal signal abnormality and MTS disease status.

RESULTS

CIE increased signal intensity and contrast-to-noise ratio in 26/27 hippocampi with pathologically confirmed MTS (96.3%) with the mean (SD) contrast-to-noise ratio of cases increasing from 14.9 (11.1) to 77.7 (58.7) after processing (P<0.001). Contrast-to-noise ratio increased in 1/54 normal control hippocampi (1.9%), with no significant change in the mean contrast-to-noise ratio of the control group after processing (P=0.57). Mean (SD) reader sensitivity for detecting abnormal signal intensity increased from 83.3% (14.2) to 94.8% (3.3) after processing. Mean specificity for abnormal signal intensity increased from 94.4% (7.3) to 96.3% (0). While sensitivity improved after processing for detection of MTS disease status in 4/6 readers, the mean reader sensitivity and specificity for MTS detection increased only minimally after processing, from 79.6% to 80.7% and from 95.7% to 96.3%, respectively.

CONCLUSION

The CIE image processing algorithm selectively increased the contrast-to-noise ratio of hippocampi affected by MTS, improved reader performance in detecting MTS-related hippocampal signal abnormality and could have high impact on pediatric patients undergoing work-up for seizures.

Evaluating the Utility of a Postprocessing Algorithm for MRI Evaluation of Optic Neuritis

BACKGROUND AND PURPOSE

MR imaging is useful for the detection and/or confirmation of optic neuritis. The objective of this study was to determine whether a postprocessing algorithm selectively increases the contrast-to-noise ratio of abnormal optic nerves in optic neuritis, facilitating this diagnosis on MR imaging.

MATERIALS AND METHODS

In this retrospective case-control study, coronal FLAIR images and coronal contrast-enhanced T1WI from 44 patients (31 eyes with clinically confirmed optic neuritis and 28 control eyes) underwent processing using a proprietary postprocessing algorithm designed to detect and visually highlight regions of contiguous increases in signal intensity by increasing the signal intensities of regions that exceed a predetermined threshold. For quantitative evaluation of the effect on image processing, the contrast-to-noise ratio of equivalent ROIs and the contrast-to-noise ratio between optic nerves and normal-appearing white matter were measured on baseline and processed images. The effect of image-processing on diagnostic performance was evaluated by masked reviews of baseline and processed images by 6 readers with varying experience levels.

RESULTS

In abnormal nerves, processing resulted in an increase in the median contrast-to-noise ratio from 17.8 to 85.0 (P < .001) on FLAIR and from 19.4 to 93.7 (P < .001) on contrast-enhanced images. The contrast-to-noise ratio for control optic nerves was not affected by processing (P = 0.13). Image processing had a beneficial effect on radiologists' diagnostic performance, with an improvement in sensitivities for 5/6 readers and relatively unchanged specificities. Interobserver agreement improved following processing.

CONCLUSIONS

Processing resulted in a selective increase in the contrast-to-noise ratio for diseased nerves and corresponding improvement in the detection of optic neuritis on MR imaging by radiologists.

Image Processing to Improve Detection of Mesial Temporal Sclerosis in Adults

In this retrospective case-control study, we investigated whether an image-processing algorithm designed to exaggerate the intensity of diseased hippocampi on FLAIR images can improve the diagnostic accuracy and interobserver reliability of radiologists in detecting mesial temporal sclerosis-related hippocampal signal alteration. Herein, we share the results of this study that showed that the image processing improved the confidence of radiologists in detecting mesial temporal sclerosis-related signal alteration, allowing an improved sensitivity, specificity, and interobserver reliability.