A novel bone suppression method that improves lung nodule detection : Suppressing dedicated bone shadows in radiographs while preserving the remaining signal.

PURPOSE: Suppressing thoracic bone shadows in chest radiographs has been previously reported to improve the detection rates for solid lung nodules, however at the cost of increased false detection rates. These bone suppression methods are based on an artificial neural network that was trained using dual-energy subtraction images in order to mimic their appearance. METHOD: Here, a novel approach is followed where all bone shadows crossing the lung field are suppressed sequentially leaving the intercostal space unaffected. Given a contour delineating a bone, its image region is spatially transferred to separate normal image gradient components from tangential component. Smoothing the normal partial gradient along the contour results in a reconstruction of the image representing the bone shadow only, because all other overlaid signals tend to cancel out each other in this representation. RESULTS: The method works even with highly contrasted overlaid objects such as a pacemaker. The approach was validated in a reader study with two experienced chest radiologists, and these images helped improving both the sensitivity and the specificity of the readers for the detection and localization of solid lung nodules. The AUC improved significantly from 0.596 to 0.655 on a basis of 146 images from patients and normals with a total of 123 confirmed lung nodules. CONCLUSION: Subtracting all reconstructed bone shadows from the original image results in a soft image where lung nodules are no longer obscured by bone shadows. Both the sensitivity and the specificity of experienced radiologists increased.

Differences in Regional Brain Volumes Two Months and One Year after Mild Traumatic Brain Injury.

Conventional structural imaging is often normal after mild traumatic brain injury (mTBI). There is a need for structural neuroimaging biomarkers that facilitate detection of milder injuries, allow recovery trajectory monitoring, and identify those at risk for poor functional outcome and disability. We present a novel approach to quantifying volumes of candidate brain regions at risk for injury. Compared to controls, patients with mTBI had significantly smaller volumes in several regions including the caudate, putamen, and thalamus when assessed 2 months after injury. These differences persisted but were reduced in magnitude 1 year after injury, suggesting the possibility of normalization over time in the affected regions. More pronounced differences, however, were found in the amygdala and hippocampus, suggesting the possibility of regionally specific responses to injury.

Construction and comparative evaluation of different activity detection methods in brain FDG-PET.

AIM: We constructed and evaluated reference brain FDG-PET databases for usage by three software programs (Computer-aided diagnosis for dementia (CAD4D), Statistical Parametric Mapping (SPM) and NEUROSTAT), which allow a user-independent detection of dementia-related hypometabolism in patients' brain FDG-PET. METHODS: Thirty-seven healthy volunteers were scanned in order to construct brain FDG reference databases, which reflect the normal, age-dependent glucose consumption in human brain, using either software. Databases were compared to each other to assess the impact of different stereotactic normalization algorithms used by either software package. In addition, performance of the new reference databases in the detection of altered glucose consumption in the brains of patients was evaluated by calculating statistical maps of regional hypometabolism in FDG-PET of 20 patients with confirmed Alzheimer's dementia (AD) and of 10 non-AD patients. Extent (hypometabolic volume referred to as cluster size) and magnitude (peak z-score) of detected hypometabolism was statistically analyzed. RESULTS: Differences between the reference databases built by CAD4D, SPM or NEUROSTAT were observed. Due to the different normalization methods, altered spatial FDG patterns were found. When analyzing patient data with the reference databases created using CAD4D, SPM or NEUROSTAT, similar characteristic clusters of hypometabolism in the same brain regions were found in the AD group with either software. However, larger z-scores were observed with CAD4D and NEUROSTAT than those reported by SPM. Better concordance with CAD4D and NEUROSTAT was achieved using the spatially normalized images of SPM and an independent z-score calculation. The three software packages identified the peak z-scores in the same brain region in 11 of 20 AD cases, and there was concordance between CAD4D and SPM in 16 AD subjects. CONCLUSION: The clinical evaluation of brain FDG-PET of 20 AD patients with either CAD4D-, SPM- or NEUROSTAT-generated databases from an identical reference dataset showed similar patterns of hypometabolism in the brain regions known to be involved in AD. The extent of hypometabolism and peak z-score appeared to be influenced by the calculation method used in each software package rather than by different spatial normalization parameters.

Voxel-based classification of FDG PET in dementia using inter-scanner normalization.

Statistical mapping of FDG PET brain images has become a common tool in differential diagnosis of patients with dementia. We present a voxel-based classification system of neurodegenerative dementias based on partial least squares (PLS). Such a classifier relies on image databases of normal controls and dementia cases as training data. Variations in PET image characteristics can be expected between databases, for example due to differences in instrumentation, patient preparation, and image reconstruction. This study evaluates (i) the impact of databases from different scanners on classification accuracy and (ii) a method to improve inter-scanner classification. Brain FDG PET databases from three scanners (A, B, C) at two clinical sites were evaluated. Diagnostic categories included normal controls (NC, nA=26, nB=20, nC=24 for each scanner respectively), Alzheimer's disease (AD, nA=44, nB=11, nC=16), and frontotemporal dementia (FTD, nA=13, nB=13, nC=5). Spatially normalized images were classified as NC, AD, or FTD using partial least squares. Supervised learning was employed to determine classifier parameters, whereby available data is sub-divided into training and test sets. Four different database setups were evaluated: (i) "in-scanner": training and test data from the same scanner, (ii) "x-scanner": training and test data from different scanners, (iii) "train other": train on both x-scanners, and (iv) "train all": train on all scanners. In order to moderate the impact of inter-scanner variations on image evaluation, voxel-by-voxel scaling was applied based on "ratio images". Good classification accuracy of on average 94% was achieved for the in-scanner setups. Accuracy deteriorated for setups with mismatched scanners (79-91%). Ratio-image normalization improved all results with mismatched scanners (85-92%). In conclusion, automatic classification of individual FDG PET in differential diagnosis of dementia is feasible. Accuracy can vary with respect to scanner or acquisition characteristics of the training image data. The adopted approach of ratio-image normalization has been demonstrated to effectively moderate these effects.

B-spline-based stereotactical normalization of brain FDG PET scans in suspected neurodegenerative disease: impact on voxel-based statistical single-subject analysis.

A b-spline-based method 'Lobster', originally designed as a general technique for non-linear image registration, was tailored for stereotactical normalization of brain FDG PET scans. Lobster was compared with the normalization methods of SPM2 and Neurostat with respect to the impact on the accuracy of voxel-based statistical analysis. (i) Computer simulation: Seven representative patterns of cortical hypometabolism served as artificial ground truth. They were inserted into 26 normal control scans with different simulated severity levels. After stereotactical normalization and voxel-based testing, statistical maps were compared voxel-by-voxel with the ground truth. This was done at different levels of statistical significance. There was a highly significant effect of the stereotactical normalization method on the area under the resulting ROC curve. Lobster showed the best average performance and was most stable with respect to variation of the severity level. (ii) Clinical evaluation: Statistical maps were obtained for the normal controls as well as patients with Alzheimer's disease (AD, n=44), Lewy-Body disease (LBD, 9), fronto-temporal dementia (FTD, 13), and cortico-basal dementia (CBD, 4). These maps were classified as normal, AD, LBD, FTD, or CBD by two experienced readers. The stereotactical normalization method had no significant effect on classification by of each of the experts, but it appeared to affect agreement between the experts. In conclusion, Lobster is appropriate for use in single-subject analysis of brain FDG PET scans in suspected dementia, both in early diagnosis (mild hypometabolism) and in differential diagnosis in advanced disease stages (moderate to severe hypometabolism). The computer simulation framework developed in the present study appears appropriate for quantitative evaluation of the impact of the different processing steps and their interaction on the performance of voxel-based single-subject analysis.

Association between FDG uptake, CSF biomarkers and cognitive performance in patients with probable Alzheimer's disease.

PURPOSE: Brain imaging of FDG uptake and cerebrospinal fluid (CSF) concentration of amyloid-beta 1-42 (Abeta(1-42)) or tau proteins are promising biomarkers in the diagnosis of Alzheimer's disease (AD). There is still uncertainty regarding any association between decreased FDG uptake and alterations in CSF markers. METHODS: The relationship between FDG uptake, CSF Abeta(1-42) and total tau (T-tau), as well as the Mini-Mental State Examination (MMSE) score was investigated in 34 subjects with probable AD using step-wise linear regression. FDG uptake was scaled to the pons. RESULTS: Scaled FDG uptake was significantly reduced in the probable AD subjects compared to 17 controls bilaterally in the precuneus/posterior cingulate area, angular gyrus/inferior parietal cortex, inferior temporal/midtemporal cortex, midfrontal cortex, and left caudate. Voxel-based single-subject analysis of the probable AD subjects at p < 0.001 (uncorrected) revealed a total volume of significant hypometabolism ranging from 0 to 452 ml (median 70 ml). The total hypometabolic volume was negatively correlated with the MMSE score, but it was not correlated with the CSF measures. VOI-based step-wise linear regression revealed that scaled FDG uptake in the precuneus/posterior cingulate was negatively correlated with CSF Abeta(1-42). Scaled FDG uptake in the caudate was positively correlated with CSF T-tau. CONCLUSION: The extent and local severity of the reduction in FDG uptake in probable AD subjects are associated with cognitive impairment. In addition, there appears to be a relationship between local FDG uptake and CSF biomarkers which differs between different brain regions.

Volumetric spinal canal intrusion: a comparison between thoracic pedicle screws and thoracic hooks.

STUDY DESIGN: A computer-aided design analysis. OBJECTIVES: To introduce the concept of volumetric spinal canal intrusion and report the relative intrusion volumes for thoracic pedicle screws compared to thoracic laminar and pedicle hooks. SUMMARY OF BACKGROUND DATA: Thoracic pedicle screws are being used more frequently; however, there is concern about neurologic risk from medial misplacement. The accepted alternative to screws is hooks. Laminar and pedicle hooks also have significant obligatory spinal canal intrusion. To date, there have been no comparison studies. METHODS: Volumetric analysis of canal intrusion of pedicle screws and hooks was performed by computer-aided design CAM. All implants were of a single product line by a single manufacturer (CD Horizon M8, Medtronic Sofamor Danek). Intrusion of pedicle screws with medial positioning was analyzed in 0.5-mm increments, including a calculation of the "screw shadow," representing additional space not available for the spinal cord between screw threads and lateral to a medially positioned screw with intrusion greater than the screw radius. The length of screw intrusion was determined from postoperative CT scans in patients with thoracic pedicle screw instrumentation. All hook styles were analyzed. The volume of the footplate in line with the dorsal surface of the footplate was considered the intruding volume for laminar hooks, with increasing offset in 0.25-mm increments to represent imperfect fit. Half of the volume of the footplate was considered to be the intruding volume for pedicle hooks since a properly positioned pedicle hook straddles the pedicle. RESULTS: Volumetric intrusion for a 4.5-mm screw ranged from 2.2 mm3 (0.5 mm medial perforation) to 83.4 mm3 (3.0 mm perforation). For a 5.5-mm screw, intrusion volume range was from 1.3 mm3 to 83.2 mm3. Accounting for the "screw shadow," the volumetric intrusion was 9.83 mm3 to 116.3 mm3 and 10.88 mm3 to 134.89 mm3, respectively. Hook volumetric intrusion ranged from 21.15 mm3 for a pediatric narrow-blade ramped pedicle hook to 113.9 mm3 for a wide-blade laminar hook with 1.0 mm of step-off. CONCLUSIONS: A 4.5-mm or 5.5-mm thoracic pedicle screw must have a medial perforation of >or=1.5 mm to have the same volumetric spinal canal intrusion as a pediatric narrow-blade pedicle hook, the smallest hook footplate. Further, the medial violation must be >3 mm to approach the same volumetric intrusion as the largest hook. Accounting for the "screw shadow," a thoracic pedicle screw must have a medial perforation of >2 mm to approach the same intrusion volume as a standard pedicle hook. In the absence of direct neural injury, this explains the clinical finding of medial perforation of up to 4 mm without neurologic compromise.