Density Categories Research Articles

COMMUNITY EMPOWERMENT TOWARDS ENERGY SAVING OF SETTLEMENTAT RT.03 / RW.01 KEL. PETUKANGAN UTARA KEC. PESANGGRAHAN JAKARTA SELATAN

Dense settlements in urban areas are one of the problems in DKI Jakarta. RT.03 / RW.01 Kel. Petukangan Utara, Kec. Pesanggrahan Jakarta Selatan is one of the densest settlements in DKI Jakarta which is located side by side with Universitas Budi Luhur. Based on SNI 03-1733-2004, the level of population density in the region is included in the category of High Density. This can be seen from the houses lined up along the road with little provision of Green Open Space. The community develops the need for building area by maximizing the area of land for building. This impacts the lack of air circulation in accordance with SNI-14-1993-03 about the thermal comfort area of buildings which are conditioned for Indonesians, as well as the lack of lighting in accordance with SNI 03-6575-2001 regarding illumination standards for the light of a room.With thermal comfort and illumination that is not in according to standards in the region, a Community Service activity was held by the Faculty of Engineering of the Universitas Budi Luhur to add community knowledge about how to make thermal comfort and illumination in homes using energy efficient. Thermal comfort can be fulfilled by making vertical greening on limited land, While the comfort of illumination can be fulfilled by using LED lights. The activity uses community empowerment methods, so that the community can independently make vertical greening in their respective homes and know the benefits for thermal comfort and can use LED lights in their respective homes and know the benefits to save electricity. The results of the Community Empowerment Towards Energy Saving Settlements at RT.03 / RW.01 Kel Petukangan Utara Kec. Pesanggrahan Jakarta Selatan, is that the region has vertical greening as a natural air conditioning system and uses an LED lighting system as an energy efficient lighting.

COMMUNITY EMPOWERMENT TOWARDS GREEN SETTLEMENT IN RT.03 / RW.01 PETUKANGAN UTARA VILLAGE, PESANGGRAHAN SUB-DISTRICT, SOUTH JAKARTA

Dense settlements in urban areas are one of the problems in DKI Jakarta, due to the discrepancy between the area of land and the population. RT.03/RW.01 Petukangan Utara Village Pesanggrahan Sub-district South Jakarta is one of the densest settlements in DKI Jakarta which is located next to Universitas Budi Luhur. Based on SNI 031733-2004, the population density level in RT.03/RW.01 of North Petukangan Village, Pesanggrahan Subdistrict, South Jakarta is included in the category of High Density. This can be seen in the dense residential row with the lack of Green Area. The community develops houses by using the land for building and pavement. This impacts the lack of healthy air circulation by SNI-14-1993-03 about the thermal comfort area of buildings for Indonesians. With thermal comfort that is not by SNI standards, the Community Service activity was made by the Universitas Budi Luhur Architecture Department to increase public knowledge about thermal comfort in homes with limited land. Thermal comfort can be achieved by creating a vertical garden on less land to produce cool air in residences. The activity uses the method of community empowerment so that the community can independently create a vertical garden in their homes and know its benefits as thermal comfort in the building. The results of the activities of the Community Empowerment Towards a Green Settlement on RT.03/RW.01 North Petukangan Village Pesanggrahan sub-district of South Jakarta is such settlements have a vertical garden as a natural air conditioning system. With the vertical garden as a natural air conditioning system, it can reduce the use of energy for artificial air conditioning, so that it saves energy and produces better air quality.

Evaluation of data augmentation via synthetic images for improved breast mass detection on mammograms using deep learning.

We evaluated whether using synthetic mammograms for training data augmentation may reduce the effects of overfitting and increase the performance of a deep learning algorithm for breast mass detection. Synthetic mammograms were generated using in silico procedural analytic breast and breast mass modeling algorithms followed by simulated x-ray projections of the breast models into mammographic images. In silico breast phantoms containing masses were modeled across the four BI-RADS breast density categories, and the masses were modeled with different sizes, shapes, and margins. A Monte Carlo-based x-ray transport simulation code, MC-GPU, was used to project the three-dimensional phantoms into realistic synthetic mammograms. 2000 mammograms with 2522 masses were generated to augment a real data set during training. From the Curated Breast Imaging Subset of the Digital Database for Screening Mammography (CBIS-DDSM) data set, we used 1111 mammograms (1198 masses) for training, 120 mammograms (120 masses) for validation, and 361 mammograms (378 masses) for testing. We used faster R-CNN for our deep learning network with pretraining from ImageNet using the Resnet-101 architecture. We compared the detection performance when the network was trained using different percentages of the real CBIS-DDSM training set (100%, 50%, and 25%), and when these subsets of the training set were augmented with 250, 500, 1000, and 2000 synthetic mammograms. Free-response receiver operating characteristic (FROC) analysis was performed to compare performance with and without the synthetic mammograms. We generally observed an improved test FROC curve when training with the synthetic images compared to training without them, and the amount of improvement depended on the number of real and synthetic images used in training. Our study shows that enlarging the training data with synthetic samples can increase the performance of deep learning systems.

Comparison of FlowCAM and microscope biovolume measurements for a diverse freshwater phytoplankton community

Abstract FlowCAM combines flow cytometry and imaging to rapidly enumerate, classify and measure particles. The instrument potentially increases processing speed of phytoplankton samples. FlowCAM, however, requires extensive comparison to microscopy before incorporation into monitoring and research. Past studies have compared FlowCAM and microscopy results for mostly marine rather than freshwater phytoplankton communities. We compared phytoplankton biovolume, density and taxonomic classifications between FlowCAM and microscopy for 113 samples from Lake Champlain, USA—a large freshwater system with diverse phytoplankton. Total biovolume estimates from FlowCAM were higher than microscope biovolumes due to higher individual particle biovolumes. Biovolume relationships, however, were closely correlated between the two methods. Shape-specific biovolumes from FlowCAM images slightly improved estimates compared to area-based biovolumes. Diatoms and filamentous cyanobacteria showed the strongest relationships between FlowCAM and microscope biovolumes. Microscope natural unit counts were generally higher than FlowCAM counts. Genus richness was weakly related between FlowCAM and microscopy, demonstrating a potential tradeoff between finer taxonomic resolutions with a microscope versus the higher number of particles processed with FlowCAM. Both methods produced reproducible biovolumes with replicate samples. We conclude that microscopy is more reliable when fine taxonomic resolution is needed and FlowCAM is suitable for rapid processing of major phytoplankton groups.

Image evaluation and breast density categories as a function of mammary positioning in full-field digital mammography.

Appropriate mammary positioning is an important factor in optimizing image quality in mammography (MMG). To study the correlation of quality criteria and breast density classification proposed by the American College of Radiology (ACR) and European Guidelines and its influence to achieve a proper positioning, therefore an adequate MMG. A total of 128 routine MMG examinations were reviewed for the definition of breast composition parenchyma and assessment of several quality criteria proposed by the ACR and European Guidelines to achieve an adequate MMG. Adequate MMG was defined as a difference between the posterior nipple line (PNL), difference of the mediolateral oblique (MLO) and craniocaudal (CC) incidences > 1 cm. The quality criteria were analyzed as a function of correlation coefficient in order to evaluate the individual impact of each factor and analysis of variance (ANOVA) for all criteria. Receiver operating characteristic (ROC) curves were plotted to evaluate the performance of the criteria on each type of parenchyma. Negative correlation of fatty breasts and visibility of the mammary angle, a greater number of skin folds and PNL > 1 cm (r < 0). Dense MMG presented less visibility of the lateral tissue compared with other categories. Area under the curve of ROC analysis revealed values of 53.1% and 54.7% for the right and left breasts, respectively. Several factors influenced in the MMG process, but we find that breast parenchyma has a substantial role in affecting these criteria and therefore a correct position for diagnosis, which could compromise MMG diagnostic performance.

Bone mineral density in virologically suppressed people aged 60 years or older with HIV-1 switching from a regimen containing tenofovir disoproxil fumarate to an elvitegravir, cobicistat, emtricitabine, and tenofovir alafenamide single-tablet regimen: a multicentre, open-label, phase 3b, randomised trial

Tenofovir alafenamide is associated with less renal and bone toxicity than tenofovir disoproxil fumarate and might improve the long-term safety of antiretroviral therapy. We aimed to investigate the effect on bone mineral density of switching from a regimen containing tenofovir disoproxil fumarate to one containing tenofovir alafenamide in participants aged 60 years and older. We did a prospective, open-label, multicentre, randomised trial in 36 European centres. Participants were virologically suppressed (HIV-1 RNA <50 copies per mL), aged 60 years or older, on a tenofovir disoproxil fumarate-containing regimen and were randomly assigned (2:1) via an interactive web-response system to open-label elvitegravir (150 mg), cobicistat (150 mg), emtricitabine (200 mg), and tenofovir alafenamide (10 mg) daily or continued therapy containing tenofovir disoproxil fumarate (300 mg). Participants were stratified by spine and hip bone mineral density categories. Primary endpoints were change from baseline to week 48 in spine and hip bone mineral density with a null hypothesis of zero between-group difference tested at a significance level of 0·05. This study was registered with ClinicalTrials.gov, NCT02616783. Between Dec 22, 2015, and March 21, 2018, 167 participants were randomly assigned to elvitegravir, cobicistat, emtricitabine, and tenofovir alafenamide (n=111 [66%]) or tenofovir disoproxil fumarate (n=56 [34%]). One participant in the elvitegravir, cobicistat, emtricitabine, and tenofovir alafenamide group did not receive treatment and was excluded from all analyses. At week 48, the mean percentage change in spine bone mineral density was 2·24% (SD 3·27) in the elvitegravir, cobicistat, emtricitabine, and tenofovir alafenamide group and -0·10% (3·39) in the tenofovir disoproxil fumarate group (between-group difference 2·43% [95% CI 1·34-3·52]; p<0·0001), and mean percentage change in hip bone mineral density was 1·33% (2·20) in the elvitegravir, cobicistat, emtricitabine, and tenofovir alafenamide group and -0·73% (3·21) in the tenofovir disoproxil fumarate group (difference 2·04% [1·17-2·90]; p<0·0001). The most common adverse events were nasopharyngitis (12 [11%]), back pain (nine [8%]), and diarrhoea (eight [7%]) in the elvitegravir, cobicistat, emtricitabine, and tenofovir alafenamide group; and bronchitis (six [11%]), vitamin D deficiency (four [7%]), and arthralgia (four [7%]) in the tenofovir disoproxil fumarate group. 22 (20%) participants in the elvitegravir, cobicistat, emtricitabine, and tenofovir alafenamide group and one (2%) participant in the tenofovir disoproxil fumarate group had an adverse event that was considered to be related to treatment. No treatment-related serious adverse events were observed. The proportions of adverse events leading to premature treatment discontinuation were similar between groups (four [4%] in the elvitegravir, cobicistat, emtricitabine, and tenofovir alafenamide group; and one (2%) in the tenofovir disoproxil fumarate group). The significantly improved bone mineral density, overall safety, and efficacy data show the feasibility of switching from a regimen containing tenofovir disoproxil fumarate to elvitegravir, cobicistat, emtricitabine, and tenofovir alafenamide in virologically suppressed people living with HIV aged 60 years or older. Gilead Sciences.

Pemetaan Area Risiko Sanitasi Sektor Air Limbah Domestik Kota Cimahi

&lt;p class="Abstrak"&gt;Cimahi is one of developing cities in Indonesia that has sanitation condition with low services, especially in domestic wastewater management. In 2016, the coverage of domestic wastewater services in the city only reached 68.17%. In consequences, some communities discharging their wastewater to the stream. This matter could lead to water pollution that would indirectly affecting public health. Based on these problems, this reserach was carried out to calculate the level of risk in each urban village of Cimahi. The risk level is stated in the form of scores (1-4) with a description of 1 is very low risk; 2 is low risk; 3 is high risk; 4 very high risk. The risk calculation considers the determinants (exposure and impact) which consist of percentage of wastewater service, risk index, perceptions of related regional organizations, population, population density, poverty rates, and regional categories. The results obtained from the calculation of the risk of domestic wastewater in Cimahi show that the Pasirkaliki, Cibabat, Citeureup, Cipageran, Baros, and Cibeber have a very low risk; Cimahi and Utama are at low risk; Karangmekar, Cigugur Tengah and Cibeureum are at high risk; Padasuka, Setiamanah, Leuwigajah and Melong have a very high risk.&lt;/p&gt;

Coming changes to mammography standards: With its proposed amendments to update mammography rules, the US Food and Drug Administration hopes to empower patients and health care providers.

Coming changes to mammography standards: With its proposed amendments to update mammography rules, the US Food and Drug Administration hopes to empower patients and health care providers.

Investigating the feasibility of stratified breast cancer screening using a masking risk predictor

BackgroundWomen with dense breasts face a double risk for breast cancer; they are at a higher risk for development of breast cancer than those with less dense breasts, and there is a greater chance that mammography will miss detection of a cancer in dense breasts due to the masking effect of surrounding fibroglandular tissue. These women may be candidates for supplemental screening. In this study, a masking risk model that was previously developed is tested on a cohort of cancer-free women to assess potential efficiency of stratification.MethodsThree masking risk models based on (1) BI-RADS density, (2) volumetric breast density (VBD), and (3) a combination of VBD and detectability were applied to stratify the mammograms of 1897 cancer-free women. The fraction of cancer-free women whose mammograms were deemed by the algorithm to be masked and who would be considered for supplemental imaging was computed as was the corresponding fraction in a screened population of interval (masked) cancers that would be potentially detected by supplemental imaging.ResultsOf the models tested, the combined VBD/detectability model offered the highest efficiency for stratification to supplemental imaging. It predicted that 725 supplemental screens would be performed per interval cancer potentially detected, at an operating point that allowed detection of 64% of the interval cancers. In comparison, stratification based on the upper two BI-RADS density categories required 1117 supplemental screenings per interval cancer detected to capture 64% of interval cancers.ConclusionThe combined VBD/detectability models perform better than BI-RADS and offer a continuum of operating points, suggesting that this model may be effective in guiding a stratified screening environment.

Can AI Help Make Screening Mammography "Lean"?

Can AI Help Make Screening Mammography "Lean"?

Relationship between Mammographic Density and Age in the United Arab Emirates Population

Objective Higher breast density is a strong, independent risk factor for breast cancer. Breast density varies by age, ethnicity, and geographic area although dense breast tissue has been associated with younger age and premenopausal status. The relationship between breast density and age in women in the United Arab Emirates (UAE) has not been determined. This study evaluated breast density in the UAE population and its relationship with age. Methods Women participating in the national cancer screening program from August 2015 to May 2018 who underwent screening mammography were included. Breast parenchymal density was classified according to the American College of Radiology (ACR) Breast Imaging-Reporting and Data System (BI-RADS) from category a (almost entirely fatty) through d (extremely dense). Subjects were divided into six age groups, and the association between age and breast density was evaluated. Results Of the 4911 women included, 1604 (32.7%), 2149 (43.8%), 1055 (21.5%), and 103 (2.1%) were classified as having categories a–d breast density, respectively. A significant negative correlation was observed between age and breast density category (p < 0.001). Women of mean age 44 ± 7 years had the highest breast density, whereas those of mean age 56 ± 14 years had the lowest breast density. Comparisons of Emirati women with Lebanese and Western women showed that breast density was lower in Emirati women than in the other populations. Conclusions To our knowledge, this is the first study to evaluate the relationship between mammographic breast density and age in UAE women. As in other populations, age was inversely related to breast density, but the proportion of Emirati women with dense breasts was lower than in other populations. Because this study lacked demographic, clinical, and histopathological data, further evaluation is required.

Sensitivity of L-band vegetation optical depth to carbon stocks in tropical forests: a comparison to higher frequencies and optical indices

Monitoring vegetation carbon in tropical regions is essential to the global carbon assessment and to evaluate the actions oriented to the reduction of forest degradation. Mainly, satellite optical vegetation indices and LiDAR data have been used to this purpose. These two techniques are limited by cloud cover and are sensitive only to the top of vegetation. In addition, the vegetation attenuation to the soil microwave emission, represented by the vegetation optical depth (VOD), has been applied for biomass estimation using frequencies ranging from 4 to 30 GHz (C- to K-bands). Atmosphere is transparent to microwaves and their sensitivity to canopy layers depends on the frequency, with lower frequencies having greater penetration depths. In this regard, L-band VOD (1.4 GHz) is expected to enhance the ability to estimate carbon stocks. This study compares the sensitivity of different VOD products (from L, C, and X-bands) and an optical vegetation index (EVI) to the above-ground carbon density (ACD). It quantifies the contribution of ACD and forest cover proportion to the VOD/EVI signals. The study is conducted in Peru, southern Colombia and Panama, where ACD maps have been derived from airborne LiDAR. Results confirm the enhanced sensitivity of L-band VOD to ACD when compared to higher frequency bands, and show that the sensitivity of all VOD bands decreases in the densest forests. ACD explains 34% and forest cover 30% of L-band VOD variance, and these proportions gradually decrease for EVI, C-, and X-band VOD, respectively. Results are consistent through different categories of altitude and carbon density. This pattern is found in most of the studied regions and in flooded forests. Results also show that C-, X-band VOD and EVI provide complementary information to L-band VOD, especially in flooded forests and in mountains, indicating that synergistic approaches could lead to improved retrievals in these regions. Although the assessment of vegetation carbon in the densest forests requires further research, results from this study support the use of new L-band VOD estimates for mapping the carbon of tropical forests.

MRI versus mammography for breast cancer screening in women with familial risk (FaMRIsc): a multicentre, randomised, controlled trial.

Approximately 15% of all breast cancers occur in women with a family history of breast cancer, but for whom no causative hereditary gene mutation has been found. Screening guidelines for women with familial risk of breast cancer differ between countries. We did a randomised controlled trial (FaMRIsc) to compare MRI screening with mammography in women with familial risk. In this multicentre, randomised, controlled trial done in 12 hospitals in the Netherlands, women were eligible to participate if they were aged 30-55 years and had a cumulative lifetime breast cancer risk of at least 20% because of a familial predisposition, but were BRCA1, BRCA2, and TP53 wild-type. Participants who were breast-feeding, pregnant, had a previous breast cancer screen, or had a previous a diagnosis of ductal carcinoma in situ were eligible, but those with a previously diagnosed invasive carcinoma were excluded. Participants were randomly allocated (1:1) to receive either annual MRI and clinical breast examination plus biennial mammography (MRI group) or annual mammography and clinical breast examination (mammography group). Randomisation was done via a web-based system and stratified by centre. Women who did not provide consent for randomisation could give consent for registration if they followed either the mammography group protocol or the MRI group protocol in a joint decision with their physician. Results from the registration group were only used in the analyses stratified by breast density. Primary outcomes were number, size, and nodal status of detected breast cancers. Analyses were done by intention to treat. This trial is registered with the Netherlands Trial Register, number NL2661. Between Jan 1, 2011, and Dec 31, 2017, 1355 women provided consent for randomisation and 231 for registration. 675 of 1355 women were randomly allocated to the MRI group and 680 to the mammography group. 218 of 231 women opting to be in a registration group were in the mammography registration group and 13 were in the MRI registration group. The mean number of screening rounds per woman was 4·3 (SD 1·76). More breast cancers were detected in the MRI group than in the mammography group (40 vs 15; p=0·0017). Invasive cancers (24 in the MRI group and eight in the mammography group) were smaller in the MRI group than in the mammography group (median size 9 mm [5-14] vs 17 mm [13-22]; p=0·010) and less frequently node positive (four [17%] of 24 vs five [63%] of eight; p=0·023). Tumour stages of the cancers detected at incident rounds were significantly earlier in the MRI group (12 [48%] of 25 in the MRI group vs one [7%] of 15 in the mammography group were stage T1a and T1b cancers; one (4%) of 25 in the MRI group and two (13%) of 15 in the mammography group were stage T2 or higher; p=0·035) and node-positive tumours were less frequent (two [11%] of 18 in the MRI group vs five [63%] of eight in the mammography group; p=0·014). All seven tumours stage T2 or higher were in the two highest breast density categories (breast imaging reporting and data system categories C and D; p=0·0077) One patient died from breast cancer during follow-up (mammography registration group). MRI screening detected cancers at an earlier stage than mammography. The lower number of late-stage cancers identified in incident rounds might reduce the use of adjuvant chemotherapy and decrease breast cancer-related mortality. However, the advantages of the MRI screening approach might be at the cost of more false-positive results, especially at high breast density. Dutch Government ZonMw, Dutch Cancer Society, A Sister's Hope, Pink Ribbon, Stichting Coolsingel, J&T Rijke Stichting.

Associations of pigmentary and naevus phenotype with melanoma risk in two populations with comparable ancestry but contrasting levels of ambient sun exposure.

BackgroundPeople at high risk of developing melanoma are usually identified by pigmentary and naevus phenotypes.ObjectiveWe examined whether associations of these phenotypes with melanoma risk differed by ambient sun exposure or participant characteristics in two population‐based, case–control studies with comparable ancestry but different ambient sun exposure.MethodsData were analysed from 616 cases and 496 controls from the Australian Melanoma Family Study and 2012 cases and 504 controls from the Leeds (UK) case–control study. Questionnaire, interview and dermatological skin examination data were collected using the same measurement protocols. Relative risks were estimated as odds ratios using unconditional logistic regression, adjusted for potential confounders.ResultsHair and skin colour were the strongest pigmentary phenotype risk factors. All associations of pigmentary phenotype with melanoma risk were similar across countries. The median number of clinically assessed naevi was approximately three times higher in Australia than Leeds, but the relative risks for melanoma associated with each additional common or dysplastic naevus were higher for Leeds than Australia, especially for naevi on the upper and lower limbs. Higher naevus counts on the head and neck were associated with a stronger relative risk for melanoma for women than men. The two countries had similar relative risks for melanoma based on self‐reported naevus density categories, but personal perceptions of naevus number differed by country. There was no consistent evidence of interactions between phenotypes on risk.ConclusionsClassifying people at high risk of melanoma based on their number of naevi should ideally take into account their country of residence, type of counts (clinical or self‐reported), body site on which the naevus counts are measured and sex. The presence of naevi may be a stronger indicator of a genetic predisposition in the UK than in Australia based on less opportunity for sun exposure to influence naevus development.

Breast Density in a Contemporary Cohort of Women With Ductal Carcinoma In Situ (DCIS)

Mammographic breast density (MBD) is an independent risk factor for breast cancer. Information regarding the relationship of MBD and breast cancer biology in women with ductal carcinoma in situ (DCIS) is currently lacking. This study aimed to examine the clinicopathologic characteristics of DCIS in women stratified by MBD. A retrospective review was performed to identify women with pure DCIS who underwent preoperative mammography between 2010 and 2018. Clinicopathologic and demographic data were collected. For the purpose of analysis, MBD was categorized as "non-dense" (Breast Imaging-Reporting and Data System [BI-RADS] density categories A and B) or "dense" (BI-RADS C and D) according to its identification in radiology reports. Of 3227 patients with a breast cancer diagnosis enrolled in the institutional Breast Cancer Database during the study period, 658 (20%) had pure DCIS. Of these 658 patients, 42% had non-dense breasts, and 58% had dense breasts. Most lesions were non-palpable (92%) and detected by mammography (84%). Patients with dense breasts were more likely to be younger at the time of diagnosis (p < 0.001), premenopausal (p < 0.001), and Asian (p = 0.018), and to have higher-grade disease (p = 0.006; Table2). Family history, BRCA status, parity, mammogram frequency, palpability, method of presentation, lesion size, hormone receptor status, comedo histology, and recurrence did not differ significantly between the two groups (Table1). The median follow-up period was 7.1years. Women with pure DCIS and higher MBD are more likely to be younger at the time of diagnosis, premenopausal, and Asian, and to present with higher-grade disease. Further research on the relationship of age, MBD, and tumor biology in DCIS is warranted.

Comparison of Contrast-Enhanced Mammography With Conventional Digital Mammography in Breast Cancer Screening: A Pilot Study

PurposeTo perform a pilot evaluation of contrast-enhanced mammography (CEM) for screening to determine whether it can improve accuracy and reader confidence in diagnosis. Methods and MaterialsThis institutional review board–approved reader study was comprised of 64 de-identified CEM cases acquired from December 1, 2014, to June 7, 2016, including 48 negative, 5 biopsy-proven benign, and 11 biopsy-proven malignancies. Negative cases were followed for at least 2 years without evidence of cancer. Ten breast imagers of varying experience first rated the low-energy (LE) mammogram and then the CEM examination using BI-RADS categories and a 5-point Likert scale for confidence in diagnosis. ResultsThere were 635 out a total possible 640 complete reader interpretations included in this analysis. The remaining five incomplete interpretations were excluded. Median sensitivity and specificity improved with the addition of CEM (sensitivity: 0.86 [95% confidence interval {CI}: 0.74-0.95] versus 1 [95% CI: 0.83-1.00], specificity: 0.85 [95% CI: 0.64-0.94] versus 0.88 [95% CI: 0.80-0.92]). Individual receiver operating characteristic curves showed significant improvement with CEM (mean area under the curve increase = 0.056 [95% CI: 0.015-0.097], P = .002). The addition of CEM significantly improved average confidence in 5 of 10 readers when compared with LE (P < .0001) and improved pooled confidence across all tissue density categories, except the almost entirely fatty category. There was a trend toward improved confidence with increasing tissue density with CEM. Degree of background parenchymal enhancement did not affect readers’ level of improvement in confidence when interpreting CEM. SummaryCEM improved reader performance and confidence compared with viewing only LE, suggesting a role for CEM in breast cancer screening for which larger trials are warranted.

Changes in mammographic density over time and the risk of breast cancer: An observational cohort study

BackgroundThe effect of changes in mammographic density over time on the risk of breast cancer remains inconclusive. MethodsWe used information from four centres of the Breast Cancer Screening Program in Spain in the period 1996–2015. We analysed individual level data from 117,388 women first screened age 50–54, with at least two screening examinations. Breast density was determined using the BI-RADS classification (A to D in increasing order) at earliest and latest screening examination. Adjusted Poisson regression models were used to estimate the relative risk (RR) and 95% confidence intervals (95%CI) of the association between changes in mammographic density and breast cancer risk over time. ResultsDuring an average 5.8 years of follow-up, 1592 (1.36%) women had a breast cancer diagnosis. An increase in density category increased breast cancer risk, and a decrease in density decreased the risk, compared with women who remained in the same BI-RADS category. Women whose density category increased from B to C or B to D had a RR of 1.55 (95%CI = 1.24–1.94) and 2.32 (95%CI = 1.48–3.63), respectively. The RR for women whose density increased from C to D was 1.51 (95%CI = 1.03–2.22). Changes in BI-RADS density were similarly associated with the risk for invasive cancer than for ductal carcinoma in situ. ConclusionsAlthough a modest proportion of women changed BI-RADS density category, mammographic density changes modulated the risk of breast cancer and identified women at a differential risk. Using two longitudinal measures of BI-RADS density could help target women for risk-based screening strategies.

A Case-Control Study to Add Volumetric or Clinical Mammographic Density into the Tyrer-Cuzick Breast Cancer Risk Model.

BackgroundAccurate breast cancer risk assessment for women attending routine screening is needed to guide screening and preventive interventions. We evaluated the accuracy of risk predictions from both visual and volumetric mammographic density combined with the Tyrer-Cuzick breast cancer risk model.MethodsA case-control study (474 patient participants and 2243 healthy control participants) of women aged 40–79 years was performed using self-reported classical risk factors. Breast density was measured by using automated volumetric software and Breast Imaging and Reporting Data System (BI-RADS) density categories. Odds ratios (95% CI) were estimated by using logistic regression, adjusted for age, demographic factors, and 10-year risk from the Tyrer-Cuzick model, for a change from the 25th to 75th percentile of the adjusted percent density distribution in control participants (IQ-OR).ResultsAfter adjustment for classical risk factors in the Tyrer-Cuzick model, age, and body mass index (BMI), BI-RADS density had an IQ-OR of 1.55 (95% CI = 1.33 to 1.80) compared with 1.40 (95% CI = 1.21 to 1.60) for volumetric percent density. Fibroglandular volume (IQ-OR = 1.28, 95% CI = 1.12 to 1.47) was a weaker predictor than was BI-RADS density (Pdiff = 0.014) or volumetric percent density (Pdiff = 0.065). In this setting, 4.8% of women were at high risk (8% + 10-year risk), using the Tyrer-Cuzick model without density, and 7.1% (BI-RADS) compared with 6.8% (volumetric) when combined with density.ConclusionThe addition of volumetric and visual mammographic density measures to classical risk factors improves risk stratification. A combined risk could be used to guide precision medicine, through risk-adapted screening and prevention strategies.

Examining urban and rural bicycling in the United States: Early findings from the 2017 National Household Travel Survey

IntroductionBicycling has personal and population health benefits. While bicycle research has focused primarily on the urban context, the rural context is equally important. There are documented disparities in health behaviors and health outcomes in rural areas compared to urban areas. It is unknown whether bicycling is one of these health behavior disparities. MethodsThis study addresses two questions: 1) what is the prevalence of bicycling behaviors by urbanicity (urban/rural and population density category), and 2) what are the characteristics that best categorize individuals as cyclists versus non-cyclists, overall and for rural populations. We used the 2017 National Household Travel Survey, a nationally representative sample of the US non-institutionalized population (age ≥5 years). Bicycling was defined as any bicycling, bicycling for exercise, bicycle commuting, and bike share program use. Analyses used complex survey procedures to estimate unadjusted and adjusted prevalence; and, random forest to rank characteristics that best categorize respondents as bicyclists. ResultsThe unadjusted prevalence of any reported bicycling was higher in high-density urban areas (≥10,000 persons per square mile (ppsm)), 14.7% (95% CI: 13.4%–16.0%), than very low-density rural areas (<500 ppsm), 11.8% (10.4%–13.2%). However, when adjusting for covariates, the prevalence was comparable: high-density urban: 14.4% (12.9%–16.0%); very low-density rural: 12.2% (10.8%–13.7%). Unadjusted prevalence of bicycling for exercise were also similar (high-density urban: 8.2% (7.0%–9.3%); very low-density rural: 7.0% (6.1%–7.9%)). We also found that characteristics that best categorize bicyclists from the overall sample were different from the rural only sample. ConclusionsThis research suggests that bicycling prevalence overall and for exercise are similar between urban and rural areas across population densities. It also suggests that characteristics that were important for rural bicyclists were different from urban bicyclists. Urban-focused bicycle research may need modification to fit the rural context to promote bicycling and physical activity.

Effect of Mammographic Screening Modality on Breast Density Assessment: Digital Mammography versus Digital Breast Tomosynthesis.

Background Breast Imaging Reporting and Data System (BI-RADS) breast density categories assigned by interpreting radiologists often influence decisions surrounding supplemental breast cancer screening and risk assessment. The landscape of mammographic screening continuously evolves, and different mammographic screening modalities may result in different perception of density, reflected in different assignment of BI-RADS density categories. Purpose To investigate the effect of screening mammography modality on BI-RADS breast density assessments. Materials and Methods Data were retrospectively analyzed from 24 736 individual women (42.3% [10 455 of 24 736] white women, 57.7% [14 281 of 24 736] black women; mean age, 56.3 years; age range, 40.0-74.9 years) who underwent from one to seven mammographic screening examinations from September 2010 through February 2017 (60 766 examinations). Three screening modalities were used: digital mammography alone (8935 examinations); digital mammography with digital breast tomosynthesis (DBT; 30 779 examinations); and synthetic mammography with DBT (21 052 examinations). Random-effects logistic regression analysis was performed to estimate the likelihood of assignment to high versus low BI-RADS density category according to each modality, adjusted for ethnicity, age, body mass index (BMI), and radiologist. The interactions of modality with ethnicity and BMI on density categorization were also tested with the model. Results Women screened with DBT versus digital mammography alone had lower likelihood regarding categorization of high density breasts (digital mammography and DBT vs digital mammography: odds ratio, 0.69 [95% confidence interval: 0.61, 0.80], P < .001; synthetic mammography and DBT vs digital mammography: odds ratio, 0.43 [95% confidence interval: 0.37, 0.50], P < .001). Lower likelihood of high density was also observed at synthetic mammography and DBT compared with digital mammography and DBT (odds ratio, 0.62; 95% confidence interval: 0.56, 0.69; P < .001). There were interactions of modality with ethnicity (P = .007) and BMI (P = .003) on breast density assessment, with greater differences in density categorization according to modality observed for black women than for white women and groups with higher BMI. Conclusion Breast density categorization may vary by screening mammographic modality, and this effect appears to vary by ethnicity and body mass index. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Philpotts in this issue.