Is mammographic density a marker of breast cancer phenotypes?

PURPOSE: To investigate the association between mammographic density (MD) phenotypes and both clinicopathologic features of breast cancer (BC) and tumor location. METHODS: MD was measured for 297 BC-affected females using qualitative (visual method) and quantitative (fully automated area-based method) approaches. Radiologists' description, visible external markers, and surgical scar were used to establish the location of tumors. Binary logistic regression models were used to assess the association between MD phenotypes and BC clinicopathologic features. RESULTS: Categorical and numerical MD measures showed no association with clinicopathologic features of BC (p > 0.05). Participants with higher BI-RADS scores [(51-75% glandular) and (> 75% glandular)] (p < 0.001), and percent density (PD) categories [PD (21-49%) and PD ≥ 50%] (p = 0.01) were more likely to have tumors emanating from dense areas. Additionally, tumors were commonly found in dense regions of the breast among patients with higher medians of PD (p = 0.001), dense area (DA) (p = 0.02), and lower medians of non-dense area (NDA) (p < 0.001). Adjusted logistic regression models showed that high BI-RADS density (> 75% glandular) has an almost fivefold increased odds of tumors developing within dense areas (OR 4.99, 95% CI 0.93-25.9; p = 0.05. PD (OR 1.02, 95% CI 1-1.03, p = 0.002) and NDA (OR 0.99, 95% CI 0.991-0.997, p < 0.001) had very small effect on tumor location. Compared to tumors within non-dense areas, tumors in dense areas tended to exhibit human epidermal growth factor receptor 2 positive (p = 0.05) and carcinoma in situ (p = 0.01) characteristics. CONCLUSION: MD shows no significant association with clinicopathologic features of BC. However, BC was more likely to originate from dense tissue, with tumors in dense regions having human epidermal growth receptor 2 positive and carcinoma in situ characteristics.

Carotid Intima-Media Thickness and Carotid Plaque: A Pilot Study of Risk Factors in an Indigenous Nigerian Population.

BACKGROUND: Risk factors for carotid intima-media thickness (cIMT) and carotid plaque (CP) differ by ethnicity; however, this is not well understood in some ethnic populations. This work examines the risk factors for cIMT and CP in an indigenous Nigerian population. METHODS: We assessed cIMT and CP in 122 participants and then performed biochemical analysis: fasting blood glucose (FBG), hemoglobin A1c, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglyceride (TG), and total cholesterol (TC). The clinical history and anthropometric characteristics of participants were recorded. Linear models were used to assess the factors associated with cIMT and CP, and stepwise multivariate regression analyses were conducted to assess the predictors of cIMT and CP. RESULTS: The cIMT thickness varied from .5 mm to 1.3 mm. Family history of heart disease (FHHDx), physical activity, FBG, HDL-C, TG, TC, body mass index (BMI), systolic pressure, and waist circumference were significantly associated with cIMT (P ≤ .01). High systolic (ß = .008) and diastolic (ß = .17) pressure, FHHDx (ß = .24), age (ß = .004), physical activity (ß = -.09), and waist circumference (ß = -.017) significantly predicted 85% of the variation in cIMT (P < .001 for all). Family history of hypertension (FHH), LDL-C, and high blood pressure were significantly associated with CP (P ≤ .05). The significant predictors of CP were FHH (ß = .145, P = .03), smoking (ß = .167, P = .01), HDL-C (ß = .283, P < .001), weight (ß = .150, P = .04), and BMI (ß = .183, P = .01), explaining most of the 43.2% variation in CP. CONCLUSIONS: Some of the risk factors differ from those of other ethnicities, suggesting a need for population-specific approach to risk assessment and early detection of subclinical disease.

Diagnostic reference levels for common computed tomography (CT) examinations: results from the first Nigerian nationwide dose survey.

PURPOSE: To explore doses from common adult computed tomography (CT) examinations and propose national diagnostic reference levels (nDRLs) for Nigeria. MATERIALS AND METHODS: This retrospective study was approved by the Nnamdi Azikiwe University and University Teaching Hospital Institutional Review Boards (IRB: NAUTH/CS/66/Vol8/84) and involved dose surveys of adult CT examinations across the six geographical regions of Nigeria and Abuja from January 2016 to August 2017. Dose data of adult head, chest and abdomen/pelvis CT examinations were extracted from patient folders. The median, 75th and 25th percentile CT dose index volume (CTDIvol) and dose-length-product (DLP) were computed for each of these procedures. Effective doses (E) for these examinations were estimated using the k conversion factor as described in the ICRP publication 103 (EDLP = k × DLP). RESULTS: The proposed 75th percentile CTDIvol for head, chest, and abdomen/pelvis are 61 mGy, 17 mGy, and 20 mGy, respectively. The corresponding DLPs are 1310 mGy.cm, 735 mGy.cm, and 1486 mGy.cm respectively. The effective doses were 2.75 mSv (head), 10.29 mSv (chest), and 22.29 mSv (abdomen/pelvis). CONCLUSION: Findings demonstrate wide dose variations within and across centres in Nigeria. The results also show CTDIvol comparable to international standards, but considerably higher DLP and effective doses.

Assessment of Interradiologist Agreement Regarding Mammographic Breast Density Classification Using the Fifth Edition of the BI-RADS Atlas.

OBJECTIVE: The objective of the present study was to assess interradiologist agreement regarding mammographic breast density assessment performed using the rating scale outlined in the fifth edition of the BI-RADS atlas of the American College of Radiology. MATERIALS AND METHODS: Breast density assessments of 1000 cases were conducted by five radiologists from the same institution who together had recently undergone retraining in mammographic breast density classification based on the fifth edition of BI-RADS. The readers assigned breast density grades (A-D) on the basis of the BI-RADS classification scheme. Repeat assessment of 100 cases was performed by all readers 1 month after the initial assessment. A weighted kappa was used to calculate intrareader and interreader agreement. RESULTS: Intrareader agreement ranged from a kappa value of 0.86 (95% CI, 0.77-0.93) to 0.89 (95% CI, 0.81-0.95) on a four-category scale (categories A-D) and from 0.89 (95% CI, 0.86-0.92) to 0.94 (95% CI, 0.89-0.97) on a two-category scale (category A-B vs category C-D). Interreader agreement ranged from substantial (κ = 0.76; 95% CI, 0.73-0.78) to almost perfect (κ = 0.87; 95% CI, 0.86-0.89) on a four-category scale, and the overall weighted kappa value was substantial (0.79; 95% CI, 0.78-0.83). Interreader agreement on a two-category scale ranged from a kappa value of 0.85 (95% CI, 0.83-0.86) to 0.91 (95% CI, 0.90-0.92), and the overall weighted kappa was 0.88 (95% CI, 0.87-0.89). CONCLUSION: Overall, with regard to mammographic breast density classification, radiologists had substantial interreader agreement when a four-category scale was used and almost perfect interreader agreement when a dichotomous scale was used.

An Evaluation of Performance Characteristics of Primary Display Devices.

The aim of this study was to complete a full evaluation of the new EIZO RX850 liquid crystal display and compare it to two currently used medical displays in Australia (EIZO GS510 and Barco MDCG 5121). The American Association of Physicists in Medicine (AAPM) Task Group 18 Quality Control test pattern was used to assess the performance of three high-resolution primary medical displays: EIZO RX850, EIZO GS510, and Barco MDCG 5121. A Konica Minolta spectroradiometer (CS-2000) was used to assess luminance response, non-uniformity, veiling glare, and color uniformity. Qualitative evaluation of noise was also performed. Seven breast lesions were displayed on each monitor and photographed with a calibrated 5.5-MP Olympus E-1 digital SLR camera. ImageJ software was used to sample pixel information from each lesion and surrounding background to calculate their conspicuity index on each of the displays. All monitor fulfilled all AAPM acceptance criteria. The performance characteristics for EIZO RX850, Barco MDCG 5121, and EIZO GS510 respectively were as follows: maximum luminance (490, 500.5, and 413 cd/m(2)), minimum luminance (0.724, 1.170, and 0.92 cd/m(2)), contrast ratio (675:1, 428:1, 449:1), just-noticeable difference index (635, 622, 609), non-uniformity (20, 5.92, and 8.5 %), veiling glare (GR = 2465.6, 720.4, 1249.8), and color uniformity (Δu'v' = +0.003, +0.002, +0.002). All monitors demonstrated low noise levels. The conspicuity index (χ) of the lesions was slightly higher in the EIZO RX850 display. All medical displays fulfilled AAPM performance criteria, and performance characteristics of EIZO RX850 are equal to or better than those of the Barco MDCG 5121 and EIZO GS510 displays.

Operator eye doses during computed tomography fluoroscopic lung biopsy.

The aim of this work was to examine the peak entrance surface air kerma (peak ESAK) to the eyes during CT fluoroscopy lung biopsy, and the impact of lead glasses, exposure parameters, head rotation, and height on peak ESAK to the eyes. Two phantoms simulating the patient and radiologist were used, and 108 exposures were made using a 16-slice Toshiba Alexion CT scanner (Toshiba Medical Systems, Nasu, Japan). ESAK to the phantom radiologist's right eye was measured using an Unfors Xi dosimeter (RaySafe, Billdal, Sweden) with and without lead glasses at two kilovoltages (120 kVp and 135 kVp) and three milliampere settings (10 mA, 20 mA, and 30 mA. A paired t test was used to compare peak ESAK to the eye at different angles, heights, and kVp and mA with and without lead glasses. Peak ESAK was higher without compared to with lead glasses (p ⩽ 0.001). The peak ESAK to the eyes increased as the phantom radiologist rotated toward the gantry without lead glasses, from 2.42 µGy at 120° to 10.54 µGy at 30° (p = 0.001). No significant difference was noted in peak ESAK with change in phantom radiologist height (p > 0.05). An increase from 120 kVp to 135 kVp resulted in 23% and 26% increases in peak ESAK with and without lead glasses respectively (p = 0.001). An increase of tube current from 10 mA to 20 mA almost doubled peak ESAK (p = 0.005). Findings demonstrate that lead glasses reduce ESAK to the eyes, and that increased kVp, mA, and eye rotation to the gantry increase ESAK to the eyes.

Association between Family History of Breast Cancer and Breast Density in Saudi Premenopausal Women Participating in Mammography Screening.

BACKGROUND: Mammographic density and family history of breast cancer (FHBC) are well-established independent factors affecting breast cancer risk; however, the association between these two risk factors in premenopausal-screened women remains unclear. The aim of this study is to investigate the relationship between mammographic density and FHBC among Saudi premenopausal-screened women. METHODS: A total of 446 eligible participants were included in the study. Mammographic density was assessed qualitatively using the Breast Imaging Reporting and Data System (BIRADS 4th edition). Logistic regression models were built to investigate the relationship between mammographic density and FHBC. RESULTS: Women with a family history of breast cancer demonstrated an 87% greater chance of having dense tissue than women without a family history of breast cancer (95% CI: 1.14-3.08; p = 0.01). Having a positive family history for breast cancer in mothers was significantly associated with dense tissue (adjusted odds ratio (OR): 5.6; 95% CI: 1.3-24.1; p = 0.02). CONCLUSION: Dense breast tissue in Saudi premenopausal women undergoing screening may be linked to FHBC. If this conclusion is replicated in larger studies, then breast cancer risk prediction models must carefully consider these breast cancer risk factors.

Exposure index in digital radiography: initial results of awareness and knowledge from Nigerian digital radiography practices.

INTRODUCTION: Exposure Index (EI) is incorporated into Digital Radiography (DR) systems to indicate incorrect exposure to enable matching exposure to the desired speed class of operation. However, knowledge of the utilization of EI by radiographers in a low-income country has not been investigated. METHODS: A pre-tested questionnaire designed using Google forms, with open and close-ended questions was shared online with radiographers working with DR systems in public and private health facilities in some cities located in southern Nigeria. The 32-item questionnaire had two parts: Part A focused on socio-demographic characteristics and Part B focused on the respondents' awareness and knowledge of EI in DR systems. A 5-point Likert scale with 5 test items was used to assess the respondents' knowledge of EI. Statistical analyses were conducted using the Statistical Package for Social Sciences (SPSS) version 21.0. The probability value of p < 0.05 was considered statistically significant. RESULTS: About 8.3% of the respondents had good knowledge of EI in DR systems in spite of the awareness level of 24.7%. The absence of the EI concept in DR curriculum for undergraduates, the lack of EI software in DR systems, and equipment training by the vendor engineers were reasons for the low level of knowledge of EI in DR systems. CONCLUSION: There is low awareness and knowledge of EI by radiographers in this study, which suggests the need to maximize the benefits of EI concepts by ensuring its integration into clinical radiography practice and curriculum for undergraduates program, to improve knowledge, awareness, and practice in DR.

Reliability of radiologists' first impression when interpreting a screening mammogram.

Previous studies showed that radiologists can detect the gist of an abnormality in a mammogram based on a half-second image presentation through global processing of screening mammograms. This study investigated the intra- and inter-observer reliability of the radiologists' initial impressions about the abnormality (or "gist signal"). It also examined if a subset of radiologists produced more reliable and accurate gist signals. Thirty-nine radiologists provided their initial impressions on two separate occasions, viewing each mammogram for half a second each time. The intra-class correlation (ICC) values showed poor to moderate intra-reader reliability. Only 13 radiologists had an ICC of 0.6 or above, which is considered the minimum standard for reliability, and only three radiologists had an ICC exceeding 0.7. The median value for the weighted Cohen's Kappa was 0.478 (interquartile range = 0.419-0.555). The Mann-Whitney U-test showed that the "Gist Experts", defined as those who outperformed others, had significantly higher ICC values (p = 0.002) and weighted Cohen's Kappa scores (p = 0.026). However, even for these experts, the intra-radiologist agreements were not strong, as an ICC of at least 0.75 indicates good reliability and the signal from none of the readers reached this level of reliability as determined by ICC values. The inter-reader reliability of the gist signal was poor, with an ICC score of 0.31 (CI = 0.26-0.37). The Fleiss Kappa score of 0.106 (CI = 0.105-0.106), indicating only slight inter-reader agreement, confirms the findings from the ICC analysis. The intra- and inter-reader reliability analysis showed that the radiologists' initial impressions are not reliable signals. In particular, the absence of an abnormal gist does not reliably signal a normal case, so radiologists should keep searching. This highlights the importance of "discovery scanning," or coarse screening to detect potential targets before ending the visual search.

A machine learning model based on readers' characteristics to predict their performances in reading screening mammograms.

OBJECTIVES: Proposing a machine learning model to predict readers' performances, as measured by the area under the receiver operating characteristics curve (AUC) and lesion sensitivity, using the readers' characteristics. METHODS: Data were collected from 905 radiologists and breast physicians who completed at least one case-set of 60 mammographic images containing 40 normal and 20 biopsy-proven cancer cases. Nine different case-sets were available. Using a questionnaire, we collected radiologists' demographic details, such as reading volume and years of experience. These characteristics along with a case set difficulty measure were fed into two ensemble of regression trees to predict the readers' AUCs and lesion sensitivities. We calculated the Pearson correlation coefficient between the predicted values by the model and the actual AUC and lesion sensitivity. The usefulness of the model to categorize readers as low and high performers based on different criteria was also evaluated. The performances of the models were evaluated using leave-one-out cross-validation. RESULTS: The Pearson correlation coefficient between the predicted AUC and actual one was 0.60 (p < 0.001). The model's performance for differentiating the reader in the first and fourth quartile based on the AUC values was 0.86 (95% CI 0.83-0.89). The model reached an AUC of 0.91 (95% CI 0.88-0.93) for distinguishing the readers in the first quartile from the fourth one based on the lesion sensitivity. CONCLUSION: A machine learning model can be used to categorize readers as high- or low-performing. Such model could be useful for screening programs for designing a targeted quality assurance and optimizing the double reading practice.

Clinicopathologic breast cancer characteristics: predictions using global textural features of the ipsilateral breast mammogram.

Radiomic features from mammograms have been shown to predict breast cancer (BC) risk; however, their contribution to BC characteristics has not yet been explored. This study included 184 women with BC between January 2012 and April 2017. A set of 33 global radiomic features were extracted from the ipsilateral breast mammogram. Associations between radiomic features and BC characteristics were investigated by univariate logistic regression analysis, and receiver-operating characteristic curve analysis was employed to evaluate the predictive performance of radiomic features. Histogram-based features (mean, 70th percentile, and 30th percentile) weakly differentiated progesterone status and tumor size (AUC range: 0.627-0.652, p ≤ 0.007). One gray level run length matrix (GLRLM)-based feature achieved an AUC of 0.68 in discriminating lymph-node status, and the fractal dimension achieved an AUC of 0.65 in predicting tumor size. After stratifying by age at BC diagnosis and baseline percent density (PD), the average predictive performance of the abovementioned features improved from 0.652 to 0.707 for baseline PD adjustment, and from 0.652 to 0.674 for age at BC diagnosis. Higher predictive performances were found for GLRLM-based features in predicting lymph-node status among younger women with high baseline PD (AUC range: 0.710-0.863), and for fractal features in predicting tumor size among patients with low PD (AUC: 0.704). Global radiomic features from the ipsilateral breast mammogram can predict lymph-node status and tumor size among certain categories of women and should be considered as a non-invasive tool for clinical decision-making in BC-affected women and for forecasting disease progression.

Mammographic density changes following BC treatment.

BACKGROUND: Mammographic density (MD) reduction is associated with lower risk of breast cancer (BC) recurrence and may be used as a marker of treatment outcome; however, trends in MD following BC therapies and the factors associated with such trends are poorly understood. The aim of this study was to investigate MD changes following BC treatment and the factors associated with these changes. METHODS: A total of 226 BC-affected patients who received BC treatments were examined. MD was assessed by the Laboratory for individualized Radiodensity Assessment (LIBRA) software. A Wilcoxon ranked signed test was used to investigate the differences in MD before and after treatment and median independent test to assess the associated factors. RESULTS: Significant differences in MD between baseline and follow-up mammograms were observed for all MD measures: percent density (p ≤ 0.005), dense area (p ≤ 0.004), and nondense area (p ≤ 0.02). After adjustment, these differences were more pronounced among younger at BC diagnosis (p ≤ 0.001), premenopausal (p ≤ 0.003), and obese women (p ≤ 0.05). Changes in MD were evident regardless of the treatment regimen. MD reduction was observed among patients with high baseline MD (p < 0.001), younger at BC diagnosis (p ≤ 0.04), premenopausal (p < 0.001), and normal body mass index (p = 0.04). Patients who experienced an increase in nondense area had high percent density at baseline (p ≤ 0.001). CONCLUSION: Two different MD changes were observed over time: MD increase and decrease. Baseline MD, menopausal status, age at BC diagnosis, and body mass index influenced these changes.

Global processing provides malignancy evidence complementary to the information captured by humans or machines following detailed mammogram inspection.

The information captured by the gist signal, which refers to radiologists' first impression arising from an initial global image processing, is poorly understood. We examined whether the gist signal can provide complementary information to data captured by radiologists (experiment 1), or computer algorithms (experiment 2) based on detailed mammogram inspection. In the first experiment, 19 radiologists assessed a case set twice, once based on a half-second image presentation (i.e., gist signal) and once in the usual viewing condition. Their performances in two viewing conditions were compared using repeated measure correlation (rm-corr). The cancer cases (19 cases × 19 readers) exhibited non-significant trend with rm-corr = 0.012 (p = 0.82, CI: -0.09, 0.12). For normal cases (41 cases × 19 readers), a weak correlation of rm-corr = 0.238 (p < 0.001, CI: 0.17, 0.30) was found. In the second experiment, we combined the abnormality score from a state-of-the-art deep learning-based tool (DL) with the radiological gist signal using a support vector machine (SVM). To obtain the gist signal, 53 radiologists assessed images based on half-second image presentation. The SVM performance for each radiologist and an average reader, whose gist responses were the mean abnormality scores given by all 53 readers to each image was assessed using leave-one-out cross-validation. For the average reader, the AUC for gist, DL, and the SVM, were 0.76 (CI: 0.62-0.86), 0.79 (CI: 0.63-0.89), and 0.88 (CI: 0.79-0.94). For all readers with a gist AUC significantly better than chance-level, the SVM outperformed DL. The gist signal provided malignancy evidence with no or weak associations with the information captured by humans in normal radiologic reporting, which involves detailed mammogram inspection. Adding gist signal to a state-of-the-art deep learning-based tool improved its performance for the breast cancer detection.

Value and Diagnostic Efficacy of Fetal Morphology Assessment Using Ultrasound in A Poor-Resource Setting.

BACKGROUND: Ultrasound is operator-dependent, and its value and efficacy in fetal morphology assessment in a low-resource setting is poorly understood. We assessed the value and efficacy of fetal morphology ultrasound assessment in a Nigerian setting. MATERIALS AND METHODS: We surveyed fetal morphology ultrasound performed across five facilities and followed-up each fetus to ascertain the outcome. Fetuses were surveyed in the second trimester (18th-22nd weeks) using the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) guideline. Clinical and surgical reports were used as references to assess the diagnostic efficacy of ultrasound in livebirths, and autopsy reports to confirm anomalies in terminated pregnancies, spontaneous abortions, intrauterine fetal deaths, and still births. We calculated sensitivity, specificity, positive and negative predictive values, Area under the curve (AUC), Youden index, likelihood ratios, and post-test probabilities. RESULTS: In total, 6520 fetuses of women aged 15-46 years (mean = 31.7 years) were surveyed. The overall sensitivity, specificity, and AUC were 77.1 (95% CI: 68-84.6), 99.5 (95% CI: 99.3-99.7), and 88.3 (95% CI: 83.7-92.2), respectively. Other performance metrics were: positive predictive value, 72.4 (95% CI: 64.7-79.0), negative predictive value, 99.6 (95% CI: 99.5-99.7), and Youden index (77.1%). Abnormality prevalence was 1.67% (95% CI: 1.37-2.01), and the positive and negative likelihood ratios were 254 (95% CI: 107.7-221.4) and 0.23 (95% CI: 0.16-0.33), respectively. The post-test probability for positive test was 72% (95% CI: 65-79). CONCLUSION: Fetal morphology assessment is valuable in a poor economics setting, however, the variation in the diagnostic efficacy across facilities and the limitations associated with the detection of circulatory system anomalies need to be addressed.

Transforming Screening Uptake in Low-resource and Underinformed Populations: A Preliminary Study of Factors Influencing Women's Decisions to Uptake Screening.

OBJECTIVES: The objective of this study was to assess the factors influencing women's decision to uptake screening mammography in an underinformed population. STUDY DESIGN: The study is a cross-sectional survey of factors influencing screening uptake. METHODS: A modified breast cancer awareness measure was used to assess women's knowledge of breast cancer, mammography, and factors that influence screening uptake. A second questionnaire investigated health professionals' (HPs') attitude to screening and the criteria for screening recommendation. Descriptive statistics were used to assess women's breast cancer awareness, factors that influence screening uptake, and HPs' attitude to breast cancer education and mammography recommendation. We ranked HPs' responses pertaining to criteria for screening recommendation using a Kendall's W test. RESULTS: Sixty-nine percent (n = 180) of women were aware of breast cancer, and half of them had performed breast self-examination (n = 131). About 53% (n = 138) of women were not aware of mammography, and only 15.4% (n = 40) of them have had a screening mammogram. Women's awareness of breast cancer risk factors and symptoms was poor. Many women would consider having a screening mammogram if instructed to do so by their husbands (87.7%; n = 228), HPs (96.2%; n = 250), and if government-funded screening programmes are available (90%; n = 234). Less than 40% (n = 21) of HPs had referred at least one woman for screening mammography within the last 6 months. Family history, age, and reproductive factors ranked as the highest criteria for screening recommendation. CONCLUSIONS: Spouses and HPs may be crucial to changing the current status quo around screening utilisation and government-funded screening programmes may increase screening uptake.

Are mammographic density phenotypes associated with breast cancer treatment response and clinical outcomes? A systematic review and meta-analysis.

Mammographic density (MD) increases breast cancer (BC) risk, however, its association with patient outcomes is unclear. We examined the association of baseline MD (BMD), and MD reduction (MDR) following BC treatment with patient outcomes. Six databases (CINAHL, Scopus, PubMed, Web of Science, MEDLINE, and Embase) were used to identify relevant articles. The PRISMA strategy was used to extract relevant details. Study quality and risk of bias were assessed using the "Quality In Prognosis Studies" (QUIPS) tool. A Meta-analysis and pooled risk estimates were performed. Results showed that BMD is associated with contralateral breast cancer (CBC) risk (HR = 1.9; 95%CI: 1.3-3.0, p = 0.0007), recurrence (HR = 2.0; 95%CI: 1.0-4.0, p = 0.04), and mortality (HR = 1.4; 95%CI: 1.1-1.9, p = 0.003). No association was found between BMD and prognosis (HR = 3.2; 95%CI: 0.9-11.2, p = 0.06). Data on risk estimates (95%CI) from BMD for survival [RR: 1.75; 0.99-3.1 to 2.4; 1.4-4.1], ipsilateral BC [HR: 1; 0.6-1.6 to 3; 1.2-7.5], and treatment response (OR, 1.8; 0.98-3.3) are limited. MDR showed no association with mortality (HR = 0.5; 95%CI: 0.2-1.2, p = 0.13). MDR is associated with a reduced risk of recurrence [HR/RR: 0.35; 0.17-0.68 to 1.33; 0.67-2.65)], however data on MDR and outcomes such as mortality [HR/RR: 0.5; 0.27-0.93 to 0.59; 0.22-0.88], and CBC risk [RR/HR: 0.53; 0.24-0.84 to 1.3; 0.6-2.7] are limited. Evidence, although sparse, demonstrates that high BMD is associated with an increased risk of recurrence, CBC, and mortality. Conversely, MDR is associated with a reduced risk of BC recurrence, CBC, and BC-related mortality.

The associated factors for radiation dose variation in cardiac CT angiography.

OBJECTIVE:: This study aimed to examine the associated factors for dose variation and influence cardiac CT angiography (CCTA) dose benchmarks in current CT imaging centres. METHODS:: A questionnaire was distributed to CT centres across Australia and Saudi Arabia. All participating centres collected data for adults who underwent a CCTA procedure. The questionnaire gathered information about the examination protocol, scanning parameters, patient parameters, and volume CT dose index (CTDI vol) and dose-length product (DLP). A stepwise regression analysis was performed to assess the contribution of tube voltage (kV), padding time technique, cross-sectional area (CSA) of chest and weight to DLP. RESULTS:: A total of 17 CT centres provided data for 423 CCTA examinations. The median CTDIvol, DLP and effective dose were 18 mGy, 256 mGy.cm and 5.2 mSv respectively. There was a statistically significant difference in DLP between retrospective and prospective ECG-gating modes (p = 0.001). Median DLP from CCTA using padding technique was 61% higher than CCTA without padding (p = 0.001). The stepwise regression showed that kV was the most significant predictor of DLP followed by padding technique then CSA while patient weight did not statistically significantly predict DLP. Correlation analysis showed a strong positive correlation between weight and CSA (r = 0.78), and there was a moderate positive correlation between weight and DLP (r = 0.42), as well as CSA and DLP (r = 0.48). CONCLUSION:: Findings show radiation dose variations for CCTA. The associated factors for dose variation found in this study are scanning mode, kV, padding time technique and CSA of the chest. This results support the need to include CSA measurements in future dose survey and for setting DRLs. ADVANCES IN KNOWLEDGE:: The study provides baseline information that helps to understand the associated factors for dose variations and high doses within and between centres performing CCTA.

DIAGNOSTIC REFERENCE LEVELS FOR CARDIAC CT ANGIOGRAPHY IN AUSTRALIA.

This study aims to assess patient radiation dose from cardiac computed tomography angiography (CCTA) with the aim of proposing a national diagnostic reference levels (NDRLs) for CCTA procedures in Australia. A questionnaire was used to retrospectively gather baseline information related to CCTA scanning and patient parameters in CT centres across the country. The 75th percentile of both volumetric CT dose index (CTDIvol) and dose length-product (DLP) was used as DRL values for CCTA. A DRL for CT calcium scoring test was also determined. NDRLs were compared with international published data. Data sets of 338 patients from nine CT centres were used for analysis. The CCTA DRL for the CTDIvol and the DLP were 22 mGy and 268 mGy cm, respectively. The CT calcium scoring test DRL for DLP was 137 mGy cm. The DRL values for CCTA in Australia have been recommended for the first time. DRLs are lower than those in most published studies due to the implementation of dose-saving technologies such as prospective ECG-gated mode and iterative reconstruction algorithms. Considerable variations remain in patient doses between hospitals for the most frequently used CCTA protocols, indicating the potential for DRLs to prompt dose optimisation strategies in CT facilities.

Radiologists can detect the 'gist' of breast cancer before any overt signs of cancer appear.

Radiologists can detect abnormality in mammograms at above-chance levels after a momentary glimpse of an image. The study investigated this instantaneous perception of an abnormality, known as a "gist" response, when 23 radiologists viewed prior mammograms of women that were reported as normal, but later diagnosed with breast cancer at subsequent screening. Five categories of cases were included: current cancer-containing mammograms, current mammograms of the normal breast contralateral to the cancer, prior mammograms of normal cases, prior mammograms with visible cancer signs in a breast from women who were initially reported as normal, but later diagnosed with breast cancer at subsequent screening in the same breast, and prior mammograms without any visible cancer signs from women labelled as initially normal but subsequently diagnosed with cancer. Our findings suggest that readers can distinguish patients who were diagnosed with cancer, from individuals without breast cancer (normal category), at above-chance levels based on a half-second glimpse of the mammogram even before any lesion becomes visible on the mammogram. Although 20 of the 23 radiologists demonstrated this ability, radiologists' abilities for perceiving the gist of the abnormal varied between the readers and appeared to be linked to expertise. These results could have implications for identifying women of higher than average risk of a future malignancy event, thus impacting upon tailored screening strategies.