Breast cancer is the most common type of non-skin cancer in women. 2D mammography is a screening tool to aid in the
early detection of breast cancer, but has diagnostic limitations of overlapping tissues, especially in dense breasts. 3D
mammography has the potential to improve detection outcomes by increasing specificity, and a new 3D screening tool
with a 3D display for mammography aims to improve performance and efficiency as compared to 2D mammography.
An observer study using human studies collected from was performed to compare traditional 2D mammography with
this new 3D mammography technique. A prior study using a mammography phantom revealed no difference in
calcification detection, but improved mass detection in 2D as compared to 3D. There was a significant decrease in
reading time for masses, calcifications, and normals in 3D compared to 2D, however, as well as more favorable
confidence levels in reading normal cases.
Data for this current study is currently being obtained, and a full report should be available in the next few weeks.
Acute Intracranial hemorrhage (AIH) requires urgent diagnosis in the emergency setting to mitigate eventual sequelae.
However, experienced radiologists may not always be available to make a timely diagnosis. This is especially true for
small AIH, defined as lesion smaller than 10 mm in size. A computer-aided detection (CAD) system for the detection of
small AIH would facilitate timely diagnosis. A previously developed 2D algorithm shows high false positive rates in the
evaluation based on LAC/USC cases, due to the limitation of setting up correct coordinate system for the
knowledge-based classification system. To achieve a higher sensitivity and specificity, a new 3D algorithm is developed.
The algorithm utilizes a top-hat transformation and dynamic threshold map to detect small AIH lesions. Several key
structures of brain are detected and are used to set up a 3D anatomical coordinate system. A rule-based classification of
the lesion detected is applied based on the anatomical coordinate system. For convenient evaluation in clinical
environment, the CAD module is integrated with a stand-alone system. The CAD is evaluated by small AIH cases and
matched normal collected in LAC/USC. The result of 3D CAD and the previous 2D CAD has been compared.
Multiple sclerosis (MS) is a demyelinating disease in the central nervous system. Genetics have been
considered as a leading factor in the prevalence and disease course of MS. We have presented an
informatics-based eFolder system for integrating patients' clinical data with MR images and lesion
quantification results. The completed eFolder system has been designed and developed in aiding to evaluate
disease manifestation differences in Hispanic and Caucasian MS patients. MS lesion data, as shown in MRI,
can be extracted by the 3-D automatic lesion detection tool in the eFolder, and data storing and mining
tools in eFolder is able to extract and compare data from individual patients. The computer-aided detection
(CAD) algorithm has been modified and enhanced to include spatial information as detection criteria. For
this study, 36 Caucasian MS patients and 36 matched Hispanic patients have been selected. Most recent
MR images of the patients are collected, and images are evaluated both by the CAD tool in the eFolder and
radiologists. The results are compared between Caucasian and Hispanic patients and statistically evaluated
to see if the two populations have significant difference in lesion presentations. The results can be used to
evaluate differences in the two groups of patients and to evaluate the new CAD algorithm's performance
with radiologists' contours. Significant findings can further evaluate effectiveness of MS eFolder in MS-related
research.
Breast cancer is the most common type of non-skin cancer in women. 2D mammography is a screening tool to aid in the
early detection of breast cancer, but has diagnostic limitations of overlapping tissues, especially in dense breasts. 3D
mammography has the potential to improve detection outcomes by increasing specificity, and a new 3D screening tool
with a 3D display for mammography aims to improve performance and efficiency as compared to 2D mammography.
An observer study using a mammography phantom was performed to compare traditional 2D mammography with this ne
3D mammography technique.
In comparing 3D and 2D mammography there was no difference in calcification detection, and mass detection was better
in 2D as compared to 3D. There was a significant decrease in reading time for masses, calcifications, and normals in 3D
compared to 2D, however, as well as more favorable confidence levels in reading normal cases. Given the limitations of
the mammography phantom used, however, a clearer picture in comparing 3D and 2D mammography may be better
acquired with the incorporation of human studies in the future.
Multiple sclerosis (MS) is a demyelinating disease of the central nervous system. The chronic nature of MS necessitates
multiple MRI studies to track disease progression. We have presented an imaging informatics decision-support system,
called MS eFolder, designed to integrate patient clinical data with MR images and a computer-aided detection (CAD)
component for automatic white matter lesion quantification. The purpose of the MS eFolder is to comprehensively
present MS patient data for clinicians and radiologists, while providing a lesion quantification tool that can be objective
and consistent for MS tracking in longitudinal studies. The MS CAD algorithm is based on the K-nearest neighbor
(KNN) principles and has been integrated within the eFolder system. Currently, the system has been completed and the
CAD algorithm for quantifying MS lesions has undergone the expert evaluation in order to validate system performance
and accuracy. The evaluation methodology has been developed and the data has been collected, including over 100 MS
MRI cases with various age and ethnic backgrounds. The preliminary results of the evaluation are expected to include
sensitivity and specificity of lesion and non-lesion voxels in the white matter, the effectiveness of different probability
thresholds for each voxel, and comparison between CAD quantification results and radiologists' manual readings. The
results aim to show the effectiveness of a MS lesion CAD system to be used in a clinical setting, as well as a step closer
to full clinical implementation of the eFolder system.
Acute intra-cranial hemorrhage (AIH) may result from traumatic brain injury (TBI). Successful management of AIH
depends heavily on the speed and accuracy of diagnosis. Timely diagnosis in emergency environments in both civilian
and military settings is difficult primarily due to severe time restraints and lack of resources. Often, diagnosis is
performed by emergency physicians rather than trained radiologists. As a result, added support in the form of computer-aided
detection (CAD) would greatly enhance the decision-making process and help in providing faster and more
accurate diagnosis of AIH. This paper discusses the implementation of a CAD system in an emergency environment, and
its efficacy in aiding in the detection of AIH.
Multiple sclerosis (MS) is a demyelinating disease of the central nervous system. The chronic nature of MS necessitates
multiple MRI studies to track disease progression. Currently, MRI assessment of multiple sclerosis requires manual
lesion measurement and yields an estimate of lesion volume and change that is highly variable and user-dependent. In
the setting of a longitudinal study, disease trends and changes become difficult to extrapolate from the lesions. In
addition, it is difficult to establish a correlation between these imaged lesions and clinical factors such as treatment
course. To address these clinical needs, an MS specific e-Folder for decision support in the evaluation and assessment of
MS has been developed. An e-Folder is a disease-centric electronic medical record in contrast to a patient-centric electronic health record. Along with an MS lesion computer aided detection (CAD) package for lesion load, location,
and volume, clinical parameters such as patient demographics, disease history, clinical course, and treatment history are
incorporated to make the e-Folder comprehensive. With the integration of MRI studies together with related clinical data
and informatics tools designed for monitoring multiple sclerosis, it provides a platform to improve the detection of
treatment response in patients with MS. The design and deployment of MS e-Folder aims to standardize MS lesion data
and disease progression to aid in decision making and MS-related research.
Timely detection of Acute Intra-cranial Hemorrhage (AIH) in an emergency environment is essential for the triage of
patients suffering from Traumatic Brain Injury. Moreover, the small size of lesions and lack of experience on the
reader's part could lead to difficulties in the detection of AIH. A CT based CAD algorithm for the detection of AIH has
been developed in order to improve upon the current standard of identification and treatment of AIH. A retrospective
analysis of the algorithm has already been carried out with 135 AIH CT studies with 135 matched normal head CT
studies from the Los Angeles County General Hospital/ University of Southern California Hospital System (LAC/USC).
In the next step, AIH studies have been collected from Walter Reed Army Medical Center, and are currently being processed using the AIH CAD system as part of implementing a multi-site assessment and evaluation of the performance of the algorithm. The sensitivity and specificity numbers from the Walter Reed study will be compared with the numbers from the LAC/USC study to determine if there are differences in the presentation and detection due to the difference in the nature of trauma between the two sites. Simultaneously, a stand-alone system with a user friendly GUI has been developed to facilitate implementation in a clinical setting.
KEYWORDS: Bone, Statistical analysis, Radiography, Digital imaging, Image processing, Picture Archiving and Communication System, Radiology, Medicine, Diagnostics, Data processing
Bone age assessment is most commonly performed with the use of the Greulich and Pyle (G&P)
book atlas, which was developed in the 1950s. The population of theUnited States is not as
homogenous as the Caucasian population in the Greulich and Pyle in the 1950s, especially in the
Los Angeles, California area. A digital hand atlas (DHA) based on 1,390 hand images of children
of different racial backgrounds (Caucasian, African American, Hispanic, and Asian) aged 0-18
years was collected from Children's Hospital Los Angeles. Statistical analysis discovered
significant discrepancies exist between Hispanic and the G&P atlas standard. To validate the usage
of DHA as a clinical standard, diagnostic radiologists performed reads on Hispanic pediatric hand
and wrist computed radiography images using either the G&P pediatric radiographic atlas or the
Children's Hospital Los Angeles Digital Hand Atlas (DHA) as reference. The order in which the
atlas is used (G&P followed by DHA or vice versa) for each image was prepared before actual
reading begins. Statistical analysis of the results was then performed to determine if a discrepancy
exists between the two readings.
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