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Background: Participation of Iranian women with a family history of breast cancer in breast cancer screening programs is low. This study evaluates the compliance of women having a family history of breast cancer with clinical breast exam (CBE) according to the stage of transtheoretical model (TTM) and health belief model (HBM). Materials and Methods: In this cross-sectional study, we used Persian version of champion's HBM scale to collect factors associated with TTM stages applied to screening from women over 20 years and older. The obtained data were analyzed by SPSS, using descriptive statistics, Chi-square test, independent t-test, and analysis of covariance. Results: Final sample size was 162 women. Thirty-three percent were in action/maintenance stage. Older women, family history of breast cancer in first-degree relatives, personal history of breast disease, insurance coverage, and a history of breast self-examination were associated with action/maintenance stage. Furthermore, women in action/maintenance stages had significantly fewer perceived barriers in terms of CBE in comparison to women in other stages (P < 0.05). There was no significant difference in other HBM subscales scores between various stages of CBE screening behavior (P > 0.05). Conclusion: The finding indicates that the rate of women in action/maintenance stage of CBE is low. Moreover, results show a strong association between perceived barriers and having a regular CBE. These clarify the necessity of promoting national target programs for breast cancer screening, which should be considered as the first preference for reducing CBE barriers.

Background: We conducted our study on 1110 patients with breast masses in order to investigate different aspects of power Doppler sonography (PDS) for differentiating between benign and malignant breast lesions and their prognostication. Materials and Methods: This study was conducted on the women who were referred to the sonography units of University Hospitals for breast sonography and had a BIRADS-3 mass or higher in gray scale sonography. Then, PDS was performed for all the patients. Vascularization, number of vessels, resistance index (RI), pulsatility index (PI), and vascularization patterns were evaluated for all the lesions. We compared our radiologic findings concerning different histopathologic and hormonal aspects of the lesions. Results: The differences between mean vascular density in malignant lesions concerning size of the tumor, histological grade, stage, and hormone receptor status were statistically significant. Although, there was an overlap between benign and malignant values. A resistive index (RI) value higher than 0.83 as a sign for malignancy had sensitivity equal to 75% and specificity equal to 97% (P = 0.04 and 0.03, respectively). A PI value higher than 1.6 has a sensitivity and specificity value of 70% and 98%, respectively, as a malignancy sign (P = 0.02 and 0.04, respectively). Conclusion: It seems that while malignant tumors have significantly higher number of vessels in comparison to benign one, since the number of vessels overlap between benign and malignant tumors, this aspect has little clinical usefulness in distinguishing or prognostication of breast masses. In contrast RI, PI, and vascularization pattern have an ability to differentiate and predict the prognosis of breast lesions.

Breast cancer is the most common type of cancer among women, and the second cause of cancer mortality after pulmonary cancer in this gender. Radiotherapy is one of the major treatments, which locally controls the disease and prohibits in recurrency. Radiation pneumonitis is one of the radiotherapy complications, which usually occurs within 1.5-3 months after radiotherapy. As there is no precise estimation concerning this complication in Isfahan, partial frequency of radiation pneumonitis and its association with the energy and treatment technique in patients with breast cancer were evaluated. This was an analytic cross-sectional study performed in 2010 in university referral center. A total of 382 patients with breast cancer, undergone surgery and referred for radiotherapy entered the study. A posterior and anterior and lateral X-Rays were taken as control images before starting radiotherapy and all X-Rays were repeated after 3-4 months post radiotherapy. The occurrence of radiotherapy pneumonitis was evaluated by the same radiologist. Data were analyzed through SPSS version 20. Out of 382 patients undergone breast conservative surgery (BCS) or modified radical mastectomy (MRM), and radiotherapy, 60 patients had pneumonitis of whom 6 patients underwent BCS and were treated by tangential field (three cases by Co 60 and three cases by PH 9). The rest of radiotherapy pneumonitis patients (n = 54) underwent MRM of whom, 42 cases were treated by one-field and 12 by two-field treatment techniques. Incidence of radiotherapy pneumonitis was different with respect to the adopted technique (one-field, two-field and tangential) (P = 0.023), with the highest association with two-field radiotherapy.

Mammographic density (MD) is one of the strongest breast cancer risk factors. Its age-related characteristics have been studied in women in western countries, but whether these associations apply to women worldwide is not known. We examined cross-sectional differences in MD by age and menopausal status in over 11,000 breast-cancer-free women aged 35-85 years, from 40 ethnicity- and location-specific population groups across 22 countries in the International Consortium on Mammographic Density (ICMD). MD was read centrally using a quantitative method (Cumulus) and its square-root metrics were analysed using meta-analysis of group-level estimates and linear regression models of pooled data, adjusted for body mass index, reproductive factors, mammogram view, image type, and reader. In all, 4,534 women were premenopausal, and 6,481 postmenopausal, at the time of mammography. A large age-adjusted difference in percent MD (PD) between post- and premenopausal women was apparent (-0.46 cm [95% CI: -0.53, -0.39]) and appeared greater in women with lower breast cancer risk profiles; variation across population groups due to heterogeneity (I2) was 16.5%. Among premenopausal women, the √PD difference per 10-year increase in age was -0.24 cm (95% CI: -0.34, -0.14; I2 = 30%), reflecting a compositional change (lower dense area and higher non-dense area, with no difference in breast area). In postmenopausal women, the corresponding difference in √PD (-0.38 cm [95% CI: -0.44, -0.33]; I2 = 30%) was additionally driven by increasing breast area. The study is limited by different mammography systems and its cross-sectional rather than longitudinal nature. Declines in MD with increasing age are present premenopausally, continue postmenopausally, and are most pronounced over the menopausal transition. These effects were highly consistent across diverse groups of women worldwide, suggesting that they result from an intrinsic biological, likely hormonal, mechanism common to women. If cumulative breast density is a key determinant of breast cancer risk, younger ages may be the more critical periods for lifestyle modifications aimed at breast density and breast cancer risk reduction.

Although blockchain technology and smart contracts are garnering attention in various sectors, their applications and familiarity within the realm of radiology remain largely unexplored. Blockchain, a decentralized digital ledger technology, offers secure, transparent, and resilient data management by distributing the verification process across a network of independent entities. This decentralized technology presents a possible solution for a range of healthcare challenges, from secure data transfer to automated verification processes. To address such challenges in the context of medical imaging, blockchain could provide different approaches, including smart contracts, machine learning algorithms, and the secure dissemination of large files among key stakeholders such as patients, healthcare providers, and institutions. This manuscript aims to explore the current attitudes and perspectives of trainees and radiologists to the utilization of blockchain technology and smart contracts in clinical radiology. Additionally, the study provides an in-depth analysis of the potential applications for incorporating blockchain into radiology.INTRODUCTIONAlthough blockchain technology and smart contracts are garnering attention in various sectors, their applications and familiarity within the realm of radiology remain largely unexplored. Blockchain, a decentralized digital ledger technology, offers secure, transparent, and resilient data management by distributing the verification process across a network of independent entities. This decentralized technology presents a possible solution for a range of healthcare challenges, from secure data transfer to automated verification processes. To address such challenges in the context of medical imaging, blockchain could provide different approaches, including smart contracts, machine learning algorithms, and the secure dissemination of large files among key stakeholders such as patients, healthcare providers, and institutions. This manuscript aims to explore the current attitudes and perspectives of trainees and radiologists to the utilization of blockchain technology and smart contracts in clinical radiology. Additionally, the study provides an in-depth analysis of the potential applications for incorporating blockchain into radiology.After obtaining The George Washington University Committee on Human Research Institutional Review Board (IRB) approval, we conducted a 10-question survey among radiologists and trainees at several institutions and private practices. Surveys were created via the Google Forms application and were emailed to potential participants. Participants were asked about their current academic level (medical student, resident/fellow, academic radiologist, private practice radiologist, others), their knowledge level about the field of imaging informatics and blockchain and smart contract technologies, their level of interest in learning more about blockchain and smart contracts, and their opinion about possible applications of blockchain and smart contract in the future of medical imaging.METHODSAfter obtaining The George Washington University Committee on Human Research Institutional Review Board (IRB) approval, we conducted a 10-question survey among radiologists and trainees at several institutions and private practices. Surveys were created via the Google Forms application and were emailed to potential participants. Participants were asked about their current academic level (medical student, resident/fellow, academic radiologist, private practice radiologist, others), their knowledge level about the field of imaging informatics and blockchain and smart contract technologies, their level of interest in learning more about blockchain and smart contracts, and their opinion about possible applications of blockchain and smart contract in the future of medical imaging.A total of 118 survey requests were distributed; 83 were returned, reflecting a 70.3% overall response rate. Of these, 19 were sent to private practices with a 15.8% response rate (3/19), and 99 to academic centers, yielding an 80.8% response rate (80/99). The survey respondents demonstrated a strong interest and need to further understand these technologies among radiologists and trainees. This study focuses on key components of this technology as it relates to healthcare and the practice of radiology, including data storage, patient care, secure communication, and automation, as well as strengths, weaknesses, opportunities, and threats (SWOT) analysis.RESULTSA total of 118 survey requests were distributed; 83 were returned, reflecting a 70.3% overall response rate. Of these, 19 were sent to private practices with a 15.8% response rate (3/19), and 99 to academic centers, yielding an 80.8% response rate (80/99). The survey respondents demonstrated a strong interest and need to further understand these technologies among radiologists and trainees. This study focuses on key components of this technology as it relates to healthcare and the practice of radiology, including data storage, patient care, secure communication, and automation, as well as strengths, weaknesses, opportunities, and threats (SWOT) analysis.To our knowledge, this is the first study to investigate and establish a baseline for the current perspectives on the application of blockchain technology and smart contracts in clinical radiology amongst trainees and radiologists across academic and private settings. Incorporating blockchain and smart contracts technologies into the field of radiology has the potential to achieve greater efficiency, security, and patient empowerment. However, the adoption of this technology comes with challenges, such as infrastructure, interoperability, scalability, and regulatory compliance. Collaboration between radiologists, hospital administration, policymakers, technology developers, and patient advocacy organizations will help guide and advance our understanding of the potential applications of blockchain and smart contracts in radiology and healthcare.DISCUSSIONTo our knowledge, this is the first study to investigate and establish a baseline for the current perspectives on the application of blockchain technology and smart contracts in clinical radiology amongst trainees and radiologists across academic and private settings. Incorporating blockchain and smart contracts technologies into the field of radiology has the potential to achieve greater efficiency, security, and patient empowerment. However, the adoption of this technology comes with challenges, such as infrastructure, interoperability, scalability, and regulatory compliance. Collaboration between radiologists, hospital administration, policymakers, technology developers, and patient advocacy organizations will help guide and advance our understanding of the potential applications of blockchain and smart contracts in radiology and healthcare.

Background Elevated mammographic density (MD) for a woman’s age and body mass index (BMI) is an established breast cancer risk factor. The relationship of parity, age at first birth, and breastfeeding with MD is less clear. We examined the associations of these factors with MD within the International Consortium of Mammographic Density (ICMD). Methods ICMD is a consortium of 27 studies with pooled individual-level epidemiological and MD data from 11,755 women without breast cancer aged 35–85 years from 22 countries, capturing 40 country-& ethnicity-specific population groups. MD was measured using the area-based tool Cumulus. Meta-analyses across population groups and pooled analyses were used to examine linear regression associations of square-root (√) transformed MD measures (percent MD (PMD), dense area (DA), and non-dense area (NDA)) with parity, age at first birth, ever/never breastfed and lifetime breastfeeding duration. Models were adjusted for age at mammogram, age at menarche, BMI, menopausal status, use of hormone replacement therapy, calibration method, mammogram view and reader, and parity and age at first birth when not the association of interest. Results Among 10,988 women included in these analyses, 90.1% (n = 9,895) were parous, of whom 13% (n = 1,286) had ≥ five births. The mean age at first birth was 24.3 years (Standard deviation = 5.1). Increasing parity (per birth) was inversely associated with √PMD (β: − 0.05, 95% confidence interval (CI): − 0.07, − 0.03) and √DA (β: − 0.08, 95% CI: − 0.12, − 0.05) with this trend evident until at least nine births. Women who were older at first birth (per five-year increase) had higher √PMD (β:0.06, 95% CI:0.03, 0.10) and √DA (β:0.06, 95% CI:0.02, 0.10), and lower √NDA (β: − 0.06, 95% CI: − 0.11, − 0.01). In stratified analyses, this association was only evident in women who were post-menopausal at MD assessment. Among parous women, no associations were found between ever/never breastfed or lifetime breastfeeding duration (per six-month increase) and √MD. Conclusions Associations with higher parity and older age at first birth with √MD were consistent with the direction of their respective associations with breast cancer risk. Further research is needed to understand reproductive factor-related differences in the composition of breast tissue and their associations with breast cancer risk.

Background Early age at menarche and tall stature are associated with increased breast cancer risk. We examined whether these associations were also positively associated with mammographic density, a strong marker of breast cancer risk. Methods Participants were 10,681 breast-cancer-free women from 22 countries in the International Consortium of Mammographic Density, each with centrally assessed mammographic density and a common set of epidemiologic data. Study periods for the 27 studies ranged from 1987 to 2014. Multi-level linear regression models estimated changes in square-root per cent density (√PD) and dense area (√DA) associated with age at menarche and adult height in pooled analyses and population-specific meta-analyses. Models were adjusted for age at mammogram, body mass index, menopausal status, hormone therapy use, mammography view and type, mammographic density assessor, parity and height/age at menarche. Results In pooled analyses, later age at menarche was associated with higher per cent density ( β √PD  = 0.023 SE = 0.008, P  = 0.003) and larger dense area ( β √DA  = 0.032 SE = 0.010, P  = 0.002). Taller women had larger dense area ( β √DA  = 0.069 SE = 0.028, P  = 0.012) and higher per cent density ( β √PD  = 0.044, SE = 0.023, P  = 0.054), although the observed effect on per cent density depended upon the adjustment used for body size. Similar overall effect estimates were observed in meta-analyses across population groups. Conclusions In one of the largest international studies to date, later age at menarche was positively associated with mammographic density. This is in contrast to its association with breast cancer risk, providing little evidence of mediation. Increased height was also positively associated with mammographic density, particularly dense area. These results suggest a complex relationship between growth and development, mammographic density and breast cancer risk. Future studies should evaluate the potential mediation of the breast cancer effects of taller stature through absolute breast density.

Once inside the respiratory tract, SARS-Cov-2 may gain access to nasopharyngeal, tracheobronchial, and/or alveolar epithelial cells by binding to angiotensin converting enzyme 2 (ACE2) receptors, leading to cytokine-mediated immune response and inflammation.3 The COVID-19 incubation period is up to two weeks. In our experience and as reported in the literature, less common symptoms and presentations include headaches (7-23%), syncope, seizures, altered mental status, chest pain, acute cardiovascular events, abdominal pain, vomiting, and diarrhea (2-14%).4 With regard to liver involvement, up to approximately 50% of COVID19 patients may present with liver dysfunction, evidenced by elevated ALT and AST.5 Most dysfunction is mild, with prevalence varying with severity of COVID-19. Ji et al demonstrated that COVID19 patients with high body mass index and nonalcoholic fatty liver disease (NAFLD) have a greater risk for both progression in liver damage and COVID-19.5 Progression in liver damage related to NAFLD (and potentially other chronic liver disorders) will complicate COVID-19 presentation, clinical course, and the role of imaging, with the potential for hepatic failure, hepatic encephalopathy, and gastrointestinal bleeding.

PurposeTo evaluate precision of a software-based liver surface nodularity (LSN) score derived from CT images.MethodsAn anthropomorphic CT phantom was constructed with simulated liver containing smooth and nodular segments at the surface and simulated visceral and subcutaneous fat components. The phantom was scanned multiple times on a single CT scanner with adjustment of image acquisition and reconstruction parameters (N = 34) and on 22 different CT scanners from 4 manufacturers at 12 imaging centers. LSN scores were obtained using a software-based method. Repeatability and reproducibility were evaluated by intraclass correlation (ICC) and coefficient of variation. Using abdominal CT images from 68 patients with various stages of chronic liver disease, inter-observer agreement and test–retest repeatability among 12 readers assessing LSN by software- vs. visual-based scoring methods were evaluated by ICC.ResultsThere was excellent repeatability of LSN scores (ICC:0.79-0.99) using the CT phantom and routine image acquisition and reconstruction parameters (kVp 100–140, mA 200–400, and auto-mA, section thickness 1.25–5.0 mm, field of view 35–50 cm, and smooth or standard kernels). There was excellent reproducibility (smooth ICC: 0.97; 95% CI 0.95, 0.99; CV: 7%; nodular ICC: 0.94; 95% CI 0.89, 0.97; CV: 8%) for LSN scores derived from CT images from 22 different scanners. Inter-observer agreement for the software-based LSN scoring method was excellent (ICC: 0.84; 95% CI 0.79, 0.88; CV: 28%) vs. good for the visual-based method (ICC: 0.61; 95% CI 0.51, 0.69; CV: 43%). Test–retest repeatability for the software-based LSN scoring method was excellent (ICC: 0.82; 95% CI 0.79, 0.84; CV: 12%).ConclusionThe software-based LSN score is a quantitative CT imaging biomarker with excellent repeatability, reproducibility, inter-observer agreement, and test–retest repeatability.

Background Inter-women and intra-women comparisons of mammographic density (MD) are needed in research, clinical and screening applications; however, MD measurements are influenced by mammography modality (screen film/digital) and digital image format (raw/processed). We aimed to examine differences in MD assessed on these image types. Methods We obtained 1294 pairs of images saved in both raw and processed formats from Hologic and General Electric (GE) direct digital systems and a Fuji computed radiography (CR) system, and 128 screen-film and processed CR-digital pairs from consecutive screening rounds. Four readers performed Cumulus-based MD measurements ( n  = 3441), with each image pair read by the same reader. Multi-level models of square-root percent MD were fitted, with a random intercept for woman, to estimate processed–raw MD differences. Results Breast area did not differ in processed images compared with that in raw images, but the percent MD was higher, due to a larger dense area (median 28.5 and 25.4 cm 2 respectively, mean √dense area difference 0.44 cm (95% CI: 0.36, 0.52)). This difference in √dense area was significant for direct digital systems (Hologic 0.50 cm (95% CI: 0.39, 0.61), GE 0.56 cm (95% CI: 0.42, 0.69)) but not for Fuji CR (0.06 cm (95% CI: −0.10, 0.23)). Additionally, within each system, reader-specific differences varied in magnitude and direction ( p  < 0.001). Conversion equations revealed differences converged to zero with increasing dense area. MD differences between screen-film and processed digital on the subsequent screening round were consistent with expected time-related MD declines. Conclusions MD was slightly higher when measured on processed than on raw direct digital mammograms. Comparisons of MD on these image formats should ideally control for this non-constant and reader-specific difference.