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author:("schuller, Beth A.")
1.  A Novel Automated Mammographic Density Measure and Breast 
Cancer Risk 
Background Mammographic breast density is a strong breast cancer risk factor but is not used in the clinical setting, partly because of a lack of standardization and automation. We developed an automated and objective measurement of the grayscale value variation within a mammogram, evaluated its association with breast cancer, and compared its performance with that of percent density (PD).
Methods Three clinic-based studies were included: a case–cohort study of 217 breast cancer case subjects and 2094 non-case subjects and two case–control studies comprising 928 case subjects and 1039 control subjects and 246 case subjects and 516 control subjects, respectively. Percent density was estimated from digitized mammograms using the computer-assisted Cumulus thresholding program, and variation was estimated from an automated algorithm. We estimated hazards ratios (HRs), odds ratios (ORs), the area under the receiver operating characteristic curve (AUC), and 95% confidence intervals (CIs) using Cox proportional hazards models for the cohort and logistic regression for case–control studies, with adjustment for age and body mass index. We performed a meta-analysis using random study effects to obtain pooled estimates of the associations between the two mammographic measures and breast cancer. All statistical tests were two-sided.
Results The variation measure was statistically significantly associated with the risk of breast cancer in all three studies (highest vs lowest quartile: HR = 7.0 [95% CI = 4.6 to 10.4]; OR = 10.7 [95% CI = 7.5 to 15.3]; OR = 2.6 [95% CI = 1.6 to 4.2]; all P trend < .001). In two studies, the risk estimates and AUCs for the variation measure were greater than those for percent density (AUCs for variation = 0.71 and 0.76; AUCs for percent density = 0.65 and 0.65), whereas in the third study, these estimates were similar (AUC for variation = 0.60 and AUC for percent density = 0.61). A meta-analysis of the three studies demonstrated a stronger association between variation and breast cancer (highest vs lowest quartile: RR = 3.6, 95% CI = 1.9 to 7.0) than between percent density and breast cancer (highest vs lowest quartile: RR = 2.3, 95% CI = 1.9 to 2.9).
Conclusion The association between the automated variation measure and the risk of breast cancer is at least as strong as that for percent density. Efforts to further evaluate and translate the variation measure to the clinical setting are warranted.
doi:10.1093/jnci/djs254
PMCID: PMC3634551  PMID: 22761274
2.  The influence of mammogram acquisition on the mammographic density and breast cancer association in the mayo mammography health study cohort 
Breast Cancer Research : BCR  2012;14(6):R147.
Introduction
Mammographic density is a strong risk factor for breast cancer. Image acquisition technique varies across mammograms to limit radiation and produce a clinically useful image. We examined whether acquisition technique parameters at the time of mammography were associated with mammographic density and whether the acquisition parameters confounded the density and breast cancer association.
Methods
We examined this question within the Mayo Mammography Health Study (MMHS) cohort, comprised of 19,924 women (51.2% of eligible) seen in the Mayo Clinic mammography screening practice from 2003 to 2006. A case-cohort design, comprising 318 incident breast cancers diagnosed through December 2009 and a random subcohort of 2,259, was used to examine potential confounding of mammogram acquisition technique parameters (x-ray tube voltage peak (kVp), milliampere-seconds (mAs), thickness and compression force) on the density and breast cancer association. The Breast Imaging Reporting and Data System four-category tissue composition measure (BI-RADS) and percent density (PD) (Cumulus program) were estimated from screen-film mammograms at time of enrollment. Spearman correlation coefficients (r) and means (standard deviations) were used to examine the relationship of density measures with acquisition parameters. Hazard ratios (HR) and C-statistics were estimated using Cox proportional hazards regression, adjusting for age, menopausal status, body mass index and postmenopausal hormones. A change in the HR of at least 15% indicated confounding.
Results
Adjusted PD and BI-RADS density were associated with breast cancer (p-trends < 0.001), with a 3 to 4-fold increased risk in the extremely dense vs. fatty BI-RADS categories (HR: 3.0, 95% CI, 1.7 - 5.1) and the ≥ 25% vs. ≤ 5% PD categories (HR: 3.8, 95% CI, 2.5 - 5.9). Of the acquisition parameters, kVp was not correlated with PD (r = 0.04, p = 0.07). Although thickness (r = -0.27, p < 0.001), compression force (r = -0.16, p < 0.001), and mAs (r = -0.06, p = 0.008) were inversely correlated with PD, they did not confound the PD or BI-RADS associations with breast cancer and their inclusion did not improve discriminatory accuracy. Results were similar for associations of dense and non-dense area with breast cancer.
Conclusions
We confirmed a strong association between mammographic density and breast cancer risk that was not confounded by mammogram acquisition technique.
doi:10.1186/bcr3357
PMCID: PMC3701143  PMID: 23152984
3.  Automatic Monitoring of Localized Skin Dose with Fluoroscopic and Interventional Procedures 
Journal of Digital Imaging  2010;24(4):626-639.
This software tool locates and computes the intensity of radiation skin dose resulting from fluoroscopically guided interventional procedures. It is comprised of multiple modules. Using standardized body specific geometric values, a software module defines a set of male and female patients arbitarily positioned on a fluoroscopy table. Simulated X-ray angiographic (XA) equipment includes XRII and digital detectors with or without bi-plane configurations and left and right facing tables. Skin dose estimates are localized by computing the exposure to each 0.01 × 0.01 m2 on the surface of a patient irradiated by the X-ray beam. Digital Imaging and Communications in Medicine (DICOM) Structured Report Dose data sent to a modular dosimetry database automatically extracts the 11 XA tags necessary for peak skin dose computation. Skin dose calculation software uses these tags (gantry angles, air kerma at the patient entrance reference point, etc.) and applies appropriate corrections of exposure and beam location based on each irradiation event (fluoroscopy and acquistions). A physicist screen records the initial validation of the accuracy, patient and equipment geometry, DICOM compliance, exposure output calibration, backscatter factor, and table and pad attenuation once per system. A technologist screen specifies patient positioning, patient height and weight, and physician user. Peak skin dose is computed and localized; additionally, fluoroscopy duration and kerma area product values are electronically recorded and sent to the XA database. This approach fully addresses current limitations in meeting accreditation criteria, eliminates the need for paper logs at a XA console, and provides a method where automated ALARA montoring is possible including email and pager alerts.
doi:10.1007/s10278-010-9320-7
PMCID: PMC3138926  PMID: 20706859
Peak skin dose; sentinal event; DICOM structured report dose; patient entrance reference point; fluoroscopy; interventional radiology; Joint Commission (JC); radiation dose; Digital Imaging and Communications in Medicine (DICOM)
4.  An Automated DICOM Database Capable of Arbitrary Data Mining (Including Radiation Dose Indicators) for Quality Monitoring 
Journal of Digital Imaging  2010;24(2):223-233.
The U.S. National Press has brought to full public discussion concerns regarding the use of medical radiation, specifically x-ray computed tomography (CT), in diagnosis. A need exists for developing methods whereby assurance is given that all diagnostic medical radiation use is properly prescribed, and all patients’ radiation exposure is monitored. The “DICOM Index Tracker©” (DIT) transparently captures desired digital imaging and communications in medicine (DICOM) tags from CT, nuclear imaging equipment, and other DICOM devices across an enterprise. Its initial use is recording, monitoring, and providing automatic alerts to medical professionals of excursions beyond internally determined trigger action levels of radiation. A flexible knowledge base, aware of equipment in use, enables automatic alerts to system administrators of newly identified equipment models or software versions so that DIT can be adapted to the new equipment or software. A dosimetry module accepts mammography breast organ dose, skin air kerma values from XA modalities, exposure indices from computed radiography, etc. upon receipt. The American Association of Physicists in Medicine recommended a methodology for effective dose calculations which are performed with CT units having DICOM structured dose reports. Web interface reporting is provided for accessing the database in real-time. DIT is DICOM-compliant and, thus, is standardized for international comparisons. Automatic alerts currently in use include: email, cell phone text message, and internal pager text messaging. This system extends the utility of DICOM for standardizing the capturing and computing of radiation dose as well as other quality measures.
doi:10.1007/s10278-010-9329-y
PMCID: PMC3056966  PMID: 20824303
Data extraction; medical informatics applications; radiation dose; database management systems; knowledge base
5.  Diagnostic Ionizing Radiation Exposure in a Population-Based Cohort of Patients with Inflammatory Bowel Disease 
Objective
For diagnosis, assessing disease activity, complications and extraintestinal manifestations, and monitoring response to therapy, patients with inflammatory bowel disease undergo many radiological studies employing ionizing radiation. However, the extent of radiation exposure in these patients is unknown.
Methods
A population-based inception cohort of 215 patients with inflammatory bowel disease from Olmsted County, Minnesota, diagnosed between 1990 and 2001, was identified. The total effective dose of diagnostic ionizing radiation was estimated for each patient. Linear regression was used to assess the median total effective dose since symptom onset.
Results
The number of patients with Crohn's disease and ulcerative colitis was 103 and 112, with a mean age at diagnosis of 38.6 and 39.4 yr, respectively. Mean follow-up was 8.9 yr for Crohn's disease and 9.0 yr for ulcerative colitis. Median total effective dose for Crohn's disease was 26.6 millisieverts (mSv) (range, 0–279) versus 10.5 mSv (range, 0–251) for ulcerative colitis (P < 0.001). Computed tomography accounted for 51% and 40% of total effective dose, respectively. Patients with Crohn's disease had 2.46 times higher total effective dose than ulcerative colitis patients (P = 0.001), adjusting for duration of disease.
Conclusions
Annualizing our data, the radiation exposure in the inflammatory bowel disease population was equivalent to the average annual background radiation dose from naturally occurring sources in the U.S. (3.0 mSv). However, a subset of patients had substantially higher doses. The development of imaging management guidelines to minimize radiation dose, dose-reduction techniques in computed tomography, and faster, more robust magnetic resonance techniques are warranted.
doi:10.1111/j.1572-0241.2008.01920.x
PMCID: PMC2831296  PMID: 18564113
7.  Digital practice planning/DICOM structured reporting digital radiology equipment acquisition and installation procedures: A team approach at mayo clinic, Rochester, MN 
Journal of Digital Imaging  2001;14(Suppl 1):3-5.
Digital imaging system integration is a complex process. A project team and a defined process for system planning, evaluation, and implementation can improve the chance for success. In this presentation, our project team relates their experiences.
doi:10.1007/BF03190284
PMCID: PMC3452722  PMID: 11442115

Résultats 1-7 (7)