Effective x-ray attenuation coefficient measurements from two full field digital mammography systems for data calibration applications

<p>Abstract</p> <p>Background</p> <p>Breast density is a significant breast cancer risk factor. Currently, there is no standard method for measuring this important factor. Work presented here represents an essential component of an ongoing project that seeks to determine the appropriate method for calibrating (standardizing) mammography image data to account for the x-ray image acquisition influences. Longer term goals of this project are to make accurate breast density measurements in support of risk studies.</p> <p>Methods</p> <p>Logarithmic response calibration curves and effective x-ray attenuation coefficients were measured from two full field digital mammography (FFDM) systems with breast tissue equivalent phantom imaging and compared. Normalization methods were studied to assess the possibility of reducing the amount of calibration data collection. The percent glandular calibration map functional form was investigated. Spatial variations in the calibration data were used to assess the uncertainty in the calibration application by applying error propagation analyses.</p> <p>Results</p> <p>Logarithmic response curves are well approximated as linear. Measured effective x-ray attenuation coefficients are characteristic quantities independent of the imaging system and are in agreement with those predicted numerically. Calibration data collection can be reduced by applying a simple normalization technique. The calibration map is well approximated as linear. Intrasystem calibration variation was on the order of four percent, which was approximately half of the intersystem variation.</p> <p>Conclusion</p> <p>FFDM systems provide a quantitative output, and the calibration quantities presented here may be used for data acquired on similar FFDM systems.</p

Effective radiation attenuation calibration for breast density: compression thickness influences and correction

<p>Abstract</p> <p>Background</p> <p>Calibrating mammograms to produce a standardized breast density measurement for breast cancer risk analysis requires an accurate spatial measure of the compressed breast thickness. Thickness inaccuracies due to the nominal system readout value and compression paddle orientation induce unacceptable errors in the calibration.</p> <p>Method</p> <p>A thickness correction was developed and evaluated using a fully specified two-component surrogate breast model. A previously developed calibration approach based on effective radiation attenuation coefficient measurements was used in the analysis. Water and oil were used to construct phantoms to replicate the deformable properties of the breast. Phantoms consisting of measured proportions of water and oil were used to estimate calibration errors without correction, evaluate the thickness correction, and investigate the reproducibility of the various calibration representations under compression thickness variations.</p> <p>Results</p> <p>The average thickness uncertainty due to compression paddle warp was characterized to within 0.5 mm. The relative calibration error was reduced to 7% from 48-68% with the correction. The normalized effective radiation attenuation coefficient (planar) representation was reproducible under intra-sample compression thickness variations compared with calibrated volume measures.</p> <p>Conclusion</p> <p>Incorporating this thickness correction into the rigid breast tissue equivalent calibration method should improve the calibration accuracy of mammograms for risk assessments using the reproducible planar calibration measure.</p

A Global Plate Model Including Lithospheric Deformation Along Major Rifts and Orogens Since the Triassic

Global deep‐time plate motion models have traditionally followed a classical rigid plate approach, even though plate deformation is known to be significant. Here we present a global Mesozoic–Cenozoic deforming plate motion model that captures the progressive extension of all continental margins since the initiation of rifting within Pangea at ~240 Ma. The model also includes major failed continental rifts and compressional deformation along collision zones. The outlines and timing of regional deformation episodes are reconstructed from a wealth of published regional tectonic models and associated geological and geophysical data. We reconstruct absolute plate motions in a mantle reference frame with a joint global inversion using hot spot tracks for the last 80 million years and minimizing global trench migration velocities and net lithospheric rotation. In our optimized model, net rotation is consistently below 0.2°/Myr, and trench migration scatter is substantially reduced. Distributed plate deformation reaches a Mesozoic peak of 30 × 106 km2 in the Late Jurassic (~160–155 Ma), driven by a vast network of rift systems. After a mid‐Cretaceous drop in deformation, it reaches a high of 48 x 106 km2 in the Late Eocene (~35 Ma), driven by the progressive growth of plate collisions and the formation of new rift systems. About a third of the continental crustal area has been deformed since 240 Ma, partitioned roughly into 65% extension and 35% compression. This community plate model provides a framework for building detailed regional deforming plate networks and form a constraint for models of basin evolution and the plate‐mantle system

Normal and abnormal tissue identification system and method for medical images such as digital mammograms

A system and method for analyzing a medical image to determine whether an abnormality is present, for example, in digital mammograms, includes the application of a wavelet expansion to a raw image to obtain subspace images of varying resolution. At least one subspace image is selected that has a resolution commensurate with a desired predetermined detection resolution range. A functional form of a probability distribution function is determined for each selected subspace image, and an optimal statistical normal image region test is determined for each selected subspace image. A threshold level for the probability distribution function is established from the optimal statistical normal image region test for each selected subspace image. A region size comprising at least one sector is defined, and an output image is created that includes a combination of all regions for each selected subspace image. Each region has a first value when the region intensity level is above the threshold and a second value when the region intensity level is below the threshold. This permits the localization of a potential abnormality within the image

Natural Resources Research Institute Technical Report

The original physical report contained a CD in the back with files on it for Appendices B-F, as well as a set of Figures and a set of Plates. The report describes the content of these files in more detail. Each set of files (individual Appendices, Figures, and Plates) has been zipped and uploaded as a separate folder attached to this record. This is an account of the number and types of files uploaded, as well as any file format conversions that took place. Appendix B contains 2 .xls (Microsoft Excel 97-2003) files; these were converted to .csv (Comma-Separated Values) to improve accessibility and .xlsx (Microsoft Excel 2016) to retain formulas that were lost in the .csv files. All 3 versions (6 files total) were uploaded. Appendix C contains 26 .jpg (JPEG) files, which were uploaded as is. Appendix D contains 6 .pdf (Portable Document Format) files, which had OCR (Optical Character Recognition) applied and were converted to the archival form of PDF files, PDF/A, before being uploaded. Appendix E contains 1 .xls file; this was converted to .xlsx, and each individual sheet was also converted to a separate .csv file. All 3 versions (7 files total) were uploaded. Appendix F contains 2 .doc (Microsoft Word 97-2003) files and 5 subfolders. The .doc files were converted to PDF/A files and both versions were uploaded. The subfolders contain a total of 6 sub-subfolders; all of these together originally contained a total of 504 files (.bak, .jpg, .hpf, .rtf, and .xrdml). The .bak, .jpg, .hpf, and .xrdml files were uploaded as is, because the file format is supported (.jpg), acceptably open (.xrdml), or too specific to have a better option to convert to (.bak and .hpf). The .rtf (Rich Text Format) files were converted to PDF/A files and both versions were uploaded. A total of 590 files were uploaded in Appendix F. Figures originally contained 73 files, 46 .jpg and 27 .rtf. The .jpg files were uploaded as is; the .rtf files were converted to PDF/A files and both versions were uploaded. A total of 100 files were uploaded in Figures. Plates contains 37 .pdf files, which were converted to PDF/A files before being uploaded.The taconite mines on the Mesabi Iron Range of northeastern Minnesota generate millions of tons of mined waste rock annually that could potentially be used as aggregate material in road building projects. Paramount to defining potential aggregate horizons within the mined ironformation is an understanding of the stratigraphy as it relates to mined ore units and waste units at each of the respective taconite mines. However, each mine uses a different submember terminology to designate the various ore and waste horizons. The major emphasis of this investigation was to produce a stratigraphic “Rosetta Stone” of the Biwabik Iron Formation that ties the stratigraphy and differing submember terminology of one mine to all of the other mines on the Mesabi Iron Range. Toward that end, the Natural Resources Research Institute (NRRI) looked at core from over 380 drill holes, and some mine exposures, in the central and western Mesabi Iron Range (Biwabik to Coleraine, MN area) to develop a stratigraphic system that links all of the mined ore and waste submembers. The methodology used in this investigation was to log multitudinous deep drill holes from a single mine, hang all of the drill holes on a common datum (bottom of the Lower Slaty member), and then correlate all of the submembers, as used by that particular mine, making note of bedding features and other unique features that define a particular submember. This same system of “logging, hanging, and correlating” was done at each of the taconite mines (seven different mines/areas along the Mesabi Iron Range) to better understand each mine’s submember terminology. The hung stratigraphic-sections from each mine were then used to collectively make generalized stratigraphic columns for each of the mines. These stratigraphic columns were then added to the “Rosetta Stone” (Plate II of this report) that is used to illustrate how the submembers at one mine correlate with similar submembers at all of the other mines. In the end, this investigation identified 25 major “Rosetta” units that define the stratigraphy of the Biwabik Iron Formation that can be used to link together all of the differing submember nomenclatures from the various taconite mines. This division of the iron-formation into 25 major units, based primarily on their overall bedding characteristics, is applicable to only the central and western Mesabi Iron Range and does not include the more highly metamorphosed iron-formation of the eastern Mesabi Iron Range, e.g., to the east of Aurora, MN

Statistical learning methods as a preprocessing step for survival analysis: evaluation of concept using lung cancer data

<p>Abstract</p> <p>Background</p> <p>Statistical learning (SL) techniques can address non-linear relationships and small datasets but do not provide an output that has an epidemiologic interpretation.</p> <p>Methods</p> <p>A small set of clinical variables (CVs) for stage-1 non-small cell lung cancer patients was used to evaluate an approach for using SL methods as a preprocessing step for survival analysis. A stochastic method of training a probabilistic neural network (PNN) was used with differential evolution (DE) optimization. Survival scores were derived stochastically by combining CVs with the PNN. Patients (n = 151) were dichotomized into favorable (n = 92) and unfavorable (n = 59) survival outcome groups. These PNN derived scores were used with logistic regression (LR) modeling to predict favorable survival outcome and were integrated into the survival analysis (i.e. Kaplan-Meier analysis and Cox regression). The hybrid modeling was compared with the respective modeling using raw CVs. The area under the receiver operating characteristic curve (Az) was used to compare model predictive capability. Odds ratios (ORs) and hazard ratios (HRs) were used to compare disease associations with 95% confidence intervals (CIs).</p> <p>Results</p> <p>The LR model with the best predictive capability gave Az = 0.703. While controlling for gender and tumor grade, the OR = 0.63 (CI: 0.43, 0.91) per standard deviation (SD) increase in age indicates increasing age confers unfavorable outcome. The hybrid LR model gave Az = 0.778 by combining age and tumor grade with the PNN and controlling for gender. The PNN score and age translate inversely with respect to risk. The OR = 0.27 (CI: 0.14, 0.53) per SD increase in PNN score indicates those patients with decreased score confer unfavorable outcome. The tumor grade adjusted hazard for patients above the median age compared with those below the median was HR = 1.78 (CI: 1.06, 3.02), whereas the hazard for those patients below the median PNN score compared to those above the median was HR = 4.0 (CI: 2.13, 7.14).</p> <p>Conclusion</p> <p>We have provided preliminary evidence showing that the SL preprocessing may provide benefits in comparison with accepted approaches. The work will require further evaluation with varying datasets to confirm these findings.</p

Natural Resources Research Institute Technical Report

The eight data files (seven spreadsheets and one zipped folder) mentioned in the report (Appendices B, C, E, and F) are attached to this record along with the PDF file of the report. The zipped folder contains hundreds of .jpg, .las, .pdf, .tfd, and .xls files, totaling 3.24GB of data

A global plate model including lithospheric deformation along major rifts and orogens since the Triassic

Global deep‐time plate motion models have traditionally followed a classical rigid plate approach, even though plate deformation is known to be significant. Here we present a global Mesozoic–Cenozoic deforming plate motion model that captures the progressive extension of all continental margins since the initiation of rifting within Pangea at ~240 Ma. The model also includes major failed continental rifts and compressional deformation along collision zones. The outlines and timing of regional deformation episodes are reconstructed from a wealth of published regional tectonic models and associated geological and geophysical data. We reconstruct absolute plate motions in a mantle reference frame with a joint global inversion using hot spot tracks for the last 80 million years and minimizing global trench migration velocities and net lithospheric rotation. In our optimized model, net rotation is consistently below 0.2°/Myr, and trench migration scatter is substantially reduced. Distributed plate deformation reaches a Mesozoic peak of 30 × 10^6 km^2 in the Late Jurassic (~160–155 Ma), driven by a vast network of rift systems. After a mid‐Cretaceous drop in deformation, it reaches a high of 48 x 10^6 km^2 in the Late Eocene (~35 Ma), driven by the progressive growth of plate collisions and the formation of new rift systems. About a third of the continental crustal area has been deformed since 240 Ma, partitioned roughly into 65% extension and 35% compression. This community plate model provides a framework for building detailed regional deforming plate networks and form a constraint for models of basin evolution and the plate‐mantle system

A global plate model including lithospheric deformation along major rifts and orogens since the Triassic

Global deep‐time plate motion models have traditionally followed a classical rigid plate approach, even though plate deformation is known to be significant. Here we present a global Mesozoic–Cenozoic deforming plate motion model that captures the progressive extension of all continental margins since the initiation of rifting within Pangea at ~240 Ma. The model also includes major failed continental rifts and compressional deformation along collision zones. The outlines and timing of regional deformation episodes are reconstructed from a wealth of published regional tectonic models and associated geological and geophysical data. We reconstruct absolute plate motions in a mantle reference frame with a joint global inversion using hot spot tracks for the last 80 million years and minimizing global trench migration velocities and net lithospheric rotation. In our optimized model, net rotation is consistently below 0.2°/Myr, and trench migration scatter is substantially reduced. Distributed plate deformation reaches a Mesozoic peak of 30 × 10^6 km^2 in the Late Jurassic (~160–155 Ma), driven by a vast network of rift systems. After a mid‐Cretaceous drop in deformation, it reaches a high of 48 x 10^6 km^2 in the Late Eocene (~35 Ma), driven by the progressive growth of plate collisions and the formation of new rift systems. About a third of the continental crustal area has been deformed since 240 Ma, partitioned roughly into 65% extension and 35% compression. This community plate model provides a framework for building detailed regional deforming plate networks and form a constraint for models of basin evolution and the plate‐mantle system