Clinical Breast Cancer Screening Research Articles

Non-invasive screening and subtyping for breast cancer by serum SERS combined with LGB-DNN algorithms

Early detection of breast cancer and its molecular subtyping is crucial for guiding clinical treatment and improving survival rate. Current diagnostic methods for breast cancer are invasive, time consuming and complicated. In this work, an optical detection method integrating surface-enhanced Raman spectroscopy (SERS) technology with feature selection and deep learning algorithm was developed for identifying serum components and building diagnostic model, with the aim of efficient and accurate noninvasive screening of breast cancer. First, the high quality of serum SERS spectra from breast cancer (BC), breast benign disease (BBD) patients and healthy controls (HC) were obtained. Chi-square tests were conducted to exclude confounding factors, enhancing the reliability of the study. Then, LightGBM (LGB) algorithm was used as the base model to retain useful features to significantly improve classification performance. The DNN algorithm was trained through backpropagation, adjusting the weights and biases between neurons to improve the network's predictive ability. In comparison to traditional machine learning algorithms, this method provided more accurate information for breast cancer classification, with classification accuracies of 91.38 % for BC and BBD, and 96.40 % for BC, BBD, and HC. Furthermore, the accuracies of 90.11 % for HR+/HR- and 88.89 % for HER2+/HER2- can be reached when evaluating BC patients' molecular subtypes. These results demonstrate that serum SERS combined with powerful LGB-DNN algorithm would provide a supplementary method for clinical breast cancer screening.

The prevalence and predictors of clinical breast cancer screening in Sub-Saharan African countries: a multilevel analysis of Demographic Health Survey.

Despite a higher rate of breast cancer in sub-Saharan Africa (SSA), efforts to treat the disease through breast cancer screening are suboptimal, resulting in late diagnosis of breast cancer and poor outcomes. Several studies have been conducted in SSA countries about screening uptake, yet they addressed country or sub-country level data and did not consider both individual and beyond-individual factors related to screening. Hence, pooled prevalence as well as multilevel correlates of screening in the region is sparse, which have been addressed by this study using the most recent data among women with SSA. This study was conducted using the Demographic Health Survey data (2013-2022) from six countries, and a total weighted sample of 95,248 women was examined. STATA version 16 was used for the data analysis. Multilevel mixed-effects logistic regression was performed and significant predictors were reported using adjusted odds ratios (aOR) with 95% confidence intervals (95% CI). The overall weighted prevalence of clinical breast cancer screening was 14.23% (95% CI: 13.97-14.75), with Namibia and Tanzania having the highest (24.5%) and lowest (5.19%) screening rates, respectively. Higher breast cancer screening uptake was observed among women of advanced age (35-49) [aOR = 1.78; 95% CI: 1.60, 1.98], had higher educational levels [aOR = 1.84; 95% CI: 1.66, 2.03], cohabited [aOR = 1.37; 95% CI: 1.21, 1.55], in the richest wealth quintile [aOR = 2.27; 95% CI: 1.95, 2.64], urban residents [aOR = 1.21; 95%CI: 1.10, 1.33], multiparous [aOR = 1.47; 95% CI: 1.30, 1.68], visited health facilities [aOR = 1.64; 95% CI: 1.52, 1.76], and read newspapers [aOR = 1.78; 95%CI: 1.60, 2.15]. The prevalence of clinical breast cancer screening was low (14%). Strengthening awareness campaigns, improving healthcare infrastructure, health education, universal health coverage, and screening program access, with a focus on rural areas, women who lack formal education, and low socioeconomic status, are critical to increasing breast cancer screening rates and equity. Scale-up local and regional collaborations and the involvement of media agencies in the implementation of screening programs, advocacy, dissemination of information, and integration of screening programs with their routine care, such as perinatal care, can boost the screening. The existing health service delivery points also need to focus on integrating breast cancer screening services with routine care such as perinatal care.

Breast mass lesion area detection method based on an improved YOLOv8 model

<p>Breast cancer has a very high incidence rate worldwide, and effective screening and early diagnosis are particularly important. In this paper, two improved You Only Look Once version 8 (YOLOv8) models, the YOLOv8-GHOST and YOLOv8-P2 models, are proposed to address the difficulty of distinguishing lesions from normal tissues in mammography images. The YOLOv8-GHOST model incorporates GHOSTConv and C3GHOST modules into the original YOLOv8 model to capture richer feature information while using only 57% of the number of parameters required by the original model. The YOLOv8-P2 algorithm significantly reduces the number of necessary parameters by streamlining the number of channels in the feature map. This paper proposes the YOLOv8-GHOST-P2 model by combining the above two improvements. Experiments conducted on the MIAS and DDSM datasets show that the new models achieved significantly improved computational efficiency while maintaining high detection accuracy. Compared with the traditional YOLOv8 method, the three new models improved and achieved F1 scores of 98.38%, 98.8%, and 98.57%, while the number of parameters reduced by 42.9%, 46.64%, and 2.8%. These improvements provide a more efficient and accurate tool for clinical breast cancer screening and lay the foundation for subsequent studies. Future work will explore the potential applications of the developed models to other medical image analysis tasks.</p>

Deep learning algorithm using bispectrum analysis energy feature maps based on ultrasound radiofrequency signals to detect breast cancer.

Ultrasonography is an important imaging method for clinical breast cancer screening. As the original echo signals of ultrasonography, ultrasound radiofrequency (RF) signals provide abundant tissue macroscopic and microscopic information and have important development and utilization value in breast cancer detection. In this study, we proposed a deep learning method based on bispectrum analysis feature maps to process RF signals and realize breast cancer detection. The bispectrum analysis energy feature maps with frequency subdivision were first proposed and applied to breast cancer detection in this study. Our deep learning network was based on a weight sharing network framework for the input of multiple feature maps. A feature map attention module was designed for multiple feature maps input of the network to adaptively learn both feature maps and features that were conducive to classification. We also designed a similarity constraint factor, learning the similarity and difference between feature maps by cosine distance. The experiment results showed that the areas under the receiver operating characteristic curves of our proposed method in the validation set and two independent test sets for benign and malignant breast tumor classification were 0.913, 0.900, and 0.885, respectively. The performance of the model combining four ultrasound bispectrum analysis energy feature maps in breast cancer detection was superior to that of the model using an ultrasound grayscale image and the model using a single bispectrum analysis energy feature map in this study. The combination of deep learning technology and our proposed ultrasound bispectrum analysis energy feature maps effectively realized breast cancer detection and was an efficient method of feature extraction and utilization of ultrasound RF signals.

Influence of distance to health facilities on clinical breast cancer screening behaviour among women in five sub-Saharan African countries

BackgroundRegular breast screening is one of the most effective ways to detect early signs of breast cancer but travel distance to cancer-diagnostic facilities can affect breast screening attendance. Yet, limited studies have examined the impact of distance to cancer-diagnostic facilities on clinical breast screening behaviour among women in sub-Saharan Africa (SSA). This study examined the influence of travel distance to a health facility on clinical breast screening behaviour in five SSA countries: Namibia, Burkina Faso, Cote D’Ivoire, Kenya, and Lesotho. The study further assessed variations in clinical breast screening behaviour across diverse socio-demographic characteristics of women.MethodsA sample of 45,945 women was drawn from the most recent Demographic and Health Surveys (DHS) for the included countries. The DHS uses 2-stage stratified cluster sampling to select nationally representative samples of women (15–49) and men (15–64) via a cross-sectional design. Proportions and binary logistic regression were used to examine associations between the women’s socio-demographic characteristics and breast screening attendance.ResultsThe overall proportion of survey participants who underwent clinical breast cancer screening was 16.3%. Travel distance to a health facility had a significant (p < 0.001) impact on clinical breast screening behaviour as 18.5% of participants who self-reported distance as “not a big problem” attended clinical breast screening compared to 10.8% who self-reported distance as “a big problem”. The study further found that various socio-demographic factors were significantly associated with breast cancer screening uptake, including age, education level, media exposure, wealth status, parity, contraceptive use, health insurance coverage, and marital status. The multivariate analysis controlling for other factors confirmed the strong association between distance to health facilities and screening uptake.ConclusionsThe study found that travel distance is a significant factor affecting clinical breast screening attendance among women in the selected SSA countries. Furthermore, the likelihood of breast screening attendance varied depending on different women’s characteristics. It is crucial to prioritise breast screening interventions, particularly among the disadvantaged women identified in this study, to achieve maximum public health benefits.

Using Breast Tissue Information and Subject-Specific Finite-Element Models to Optimize Breast Compression Parameters for Digital Mammography

Digital mammography has become a first-line diagnostic tool for clinical breast cancer screening due to its high sensitivity and specificity. Mammographic compression force is closely associated with image quality and patient comfort. Therefore, optimizing breast compression parameters is essential. Subjects were recruited for digital mammography and breast magnetic resonance imaging (MRI) within a month. Breast MRI images were used to calculate breast volume and volumetric breast density (VBD) and construct finite element models. Finite element analysis was performed to simulate breast compression. Simulated compressed breast thickness (CBT) was compared with clinical CBT and the relationships between compression force, CBT, breast volume, and VBD were established. Simulated CBT had a good linear correlation with the clinical CBT (R2 = 0.9433) at the clinical compression force. At 10, 12, 14, and 16 daN, the mean simulated CBT of the breast models was 5.67, 5.13, 4.66, and 4.26 cm, respectively. Simulated CBT was positively correlated with breast volume (r &gt; 0.868) and negatively correlated with VBD (r &lt; –0.338). The results of this study provides a subject-specific and evidence-based suggestion of mammographic compression force for radiographers considering image quality and patient comfort.

Improving access to cancer genetic testing for underserved women in southeast Texas.

6548 Background: Hereditary breast cancer accounts for 5-10% of all cases, but only 20% of eligible women undergo NCCN guideline-concordant screening. We demonstrated previously that our simple genetic risk screening tool (GRST) and telegenetics improved adherence to genetic testing guidelines and increased high-risk cancer surveillance. Our objective was to identify women eligible for genetic testing using breast cancer screening clinics in underserved communities as entry points, reach them with our tailored program, and measure impact. Methods: This is a prospective study in women presenting for breast cancer screening at The Rose, which provides breast imaging to underserved patients in Houston, TX. Women who consented to participate filled out the GRST and provided socio-demographic information. Those at high risk for hereditary cancer after GRST scoring were provided with educational materials and sent a saliva-based genetic testing kit. When results included a pathogenic variant (PV) or variant of uncertain significance (VUS), individuals received telegenetic counseling and risk reduction resources. Others were notified of negative results by phone. The program included education for providers about importance of genetic testing. Socio-demographic characteristics were analyzed using descriptive statistics. All statistical tests were two-sided. Results: 501 women filled out the GRST. Median age was 52. Median annual salary was $45,000 (IQR 21-75K). 151 (36.3%) were uninsured. 252 (50.3%) identified as White, 230 (45.9%) as Hispanic/Latino, and 106 (21.2%) as Black/African American. 150 (33%) were eligible for genetic testing; 100 could be contacted. Of the 100, 41 declined testing, 40 were lost to follow-up, 19 agreed, and 15 (10% of those eligible) returned the kits. Results included 11 negative, 2 VUS, 1 PV (NF1). Among 41 who declined testing, reported reasons included not wanting to know the results or preference to follow-up with their primary care doctor in 11 (26.8%) each, not enough time or prior genetic testing in 6 (14.6%) each, no reason given by five, and perception that testing was unnecessary in two. Completion of genetic testing was not associated with insurance, salary, family history, or race/ethnicity (p &gt; 0. 05). Conclusions: Our study was successful in identifying underserved women at high risk of hereditary cancer who have not previously undergone genetic testing using a simple screening tool. We reduced barriers to genetic testing by working with a trusted community organization and using remote testing and telegenetics. We did not find any factors associated with genetic testing completion, though results are limited by small sample size. Given the low proportion of patients who completed testing, the next project phase will focus on improving convenience for patients and exploring patient and program-related reasons for non-completion of testing and strategies to overcome these.

137P Impact of staffing a breast cancer screening clinic with clinical officers at a public referral center in Western Kenya

Cancer screening relies on effective coordination between specialists and general practitioners; both are in shortage in sub-Saharan Africa. The Academic Model Providing Access to Healthcare Breast and Cervical Cancer Control Program (ABCCCP) addressed this need by training and relying on Clinical Officers (COs) for daily activities. COs are licensed by Kenyan Clinical Officer Council after 3.5 years of training and supplement the provision of primary care. We aimed to understand the impact of three full-time COs who staff a specialty breast cancer screening clinic.

Multi-path synergic fusion deep neural network framework for breast mass classification using digital breast tomosynthesis

Objective. To develop and evaluate a multi-path synergic fusion (MSF) deep neural network model for breast mass classification using digital breast tomosynthesis (DBT). Methods. We retrospectively collected 441 patients who had undergone DBT in which the regions of interest (ROIs) covering the malignant/benign breast mass were extracted for model training and validation. In the proposed MSF framework, three multifaceted representations of the breast mass (gross mass, overview, and mass background) are extracted from the ROIs and independently processed by a multi-scale multi-level features enforced DenseNet (MMFED). The three MMFED sub-models are finally fused at the decision level to generate the final prediction. The advantages of the MMFED over the original DenseNet, as well as different fusion strategies embedded in MSF, were comprehensively compared. Results. The MMFED was observed to be superior to the original DenseNet, and multiple channel fusions in the MSF outperformed the single-channel MMFED and double-channel fusion with the best classification scores of area under the receiver operating characteristic (ROC) curve (87.03%), Accuracy (81.29%), Sensitivity (74.57%), and Specificity (84.53%) via the weighted fusion method embedded in MSF. The decision level fusion-based MSF was significantly better (in terms of the ROC curve) than the feature concatenation-based fusion (p< 0.05), the single MMFED using a fused three-channel image (p< 0.04), and the multiple MMFED end-to-end training (p< 0.004). Conclusions. Integrating multifaceted representations of the breast mass tends to increase benign/malignant mass classification performance and the proposed methodology was verified to be a promising tool to assist in clinical breast cancer screening.

Multimodality Imaging of Ductal Carcinoma In Situ

We aim to review the appearance of ductal carcinoma in situ (DCIS) across the spectrum of imaging modalities used in common clinical practice. Changes in technology and clinical breast cancer screening patterns have impacted the imaging evaluation of DCIS. DCIS classically presents as asymptomatic calcifications in women undergoing screening mammography. The replacement of traditional 2D mammography with digital breast tomosynthesis has changed the typical appearance of screen-detected DCIS. Ultrasound is traditionally utilized to detect DCIS in women with clinical symptoms, but efforts to increase screening ultrasound rates for women with dense breasts makes it more important to identify the appearance of DCIS in asymptomatic women. Improvements in MRI technology have made MRI the most sensitive imaging modality to detect DCIS and define the extent of disease, which is increasingly important given greater utilization of MRI for high-risk screening and determination of extent of known disease. Finally, the emergence of active surveillance, or non-surgical management, for DCIS has increased the focus on presurgical identification of associated invasive cancer, with early results demonstrating promise via computer vision and deep learning approaches for this task. DCIS has a highly variable imaging appearance which is subject to changes in imaging technology and clinical management.

Effect of a breast navigation programme in a teaching hospital in Africa

&lt;strong&gt;Background:&lt;/strong&gt; Breast cancer screening programmes have been developed in few developing countries to aid curb the increasing burden. However, breast cancer is still being detected in late stage, attributed to barriers in health care. Patient navigation programmes have been implemented in developed countries to help patients overcome these barriers, and they have been associated with early detection and timely diagnosis. Despite the consistent positive effects of breast navigation programmes, there are no studies conducted to show its effect in Africa where the needs are enormous.&lt;br /&gt;&lt;strong&gt;Aim:&lt;/strong&gt; To evaluate the effect of patient navigation programme on patient return after an abnormal clinical breast cancer screening examination finding at Aga Khan University Hospital, Nairobi(AKUH-N).&lt;br /&gt;&lt;strong&gt;Setting:&lt;/strong&gt; Women presenting for breast screening.&lt;br /&gt;&lt;strong&gt;Methods:&lt;/strong&gt; This was a before-and-after study conducted on 76 patients before and after the implementation of the navigation programme. They were followed up for 30 days. Measures included proportion of patient return and time to return.&lt;br /&gt;&lt;strong&gt;Results:&lt;/strong&gt; The proportion of return of patients in the navigated and non-navigated group was 57.9% and 23.7%, respectively (odds ratio [OR]: 4.43 [95% confidence interval, CI: 1.54– 12.78]; &lt;em&gt;p&lt;/em&gt; = 0.0026).The proportion of timely return in the navigated group was 90.1% and 77.8% for the non-navigated group (OR: 2.85 [95% CI: 0.34–24.30], &lt;em&gt;p&lt;/em&gt; = 0.34). The mean time to return in the non-navigated and navigated group was 7.33 days and 8.33 days, respectively (&lt;em&gt;p&lt;/em&gt; = 0.67).&lt;br /&gt;&lt;strong&gt;Conclusion:&lt;/strong&gt; There was an increase in the proportion of patients who returned for follow-up following abnormal clinical breast examination finding after implementation of the breast navigation programme at AKUH-N.

Abstract B01: Designing a feasible breast cancer genetics research study: Lessons learned

Abstract Background: The current trend toward personalized medicine in cancer care relies heavily on cancer genetics research (CGR). However, members of diverse populations are significantly less likely than others to participate in CGR. Therefore, CGR results lack generalizability to these groups. This study tests strategies to recruit European American (EA) and African American (AA) women of varied income levels who are at risk of developing breast cancer (BC) to CGR. Design: Recruitment began in January 2015 and ended in May 2015. Study flyers are strategically placed in the BC screening clinics at a National Cancer Institute-designated cancer center. Interested patients call the study coordinator for eligibility screening. To supplement low accrual rates using this method, in June 2015, the investigators began using the EPIC electronic health record to identify BC-screened patients who potentially met study eligibility criteria. EPIC-identified patients are randomly selected in groups of 50 and are sent a letter describing the study; if interested, they then call the study coordinator for eligibility screening. Results: The original recruitment strategy resulted in 11 participants (7 AA, 4 EA) while 21 participants (10 AA, 11 EA) were recruited using the EPIC approach. Discussion: The EPIC recruitment strategy resulted in a higher number of recruited participants than the study flyer strategy. Identifying effective approaches to recruit diverse populations to CGR is critically important. Study results show that using a targeted recruitment approach such as the pre-screening approach in the EPIC strategy can bolster participation of diverse populations in CGR. Citation Format: Colleen Bauza, Marvella E. Fordxs. Designing a feasible breast cancer genetics research study: Lessons learned. [abstract]. In: Proceedings of the Ninth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2016 Sep 25-28; Fort Lauderdale, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(2 Suppl):Abstract nr B01.

Can a lifestyle intervention be offered through NHS breast cancer screening? Challenges and opportunities identified in a qualitative study of women attending screening

BackgroundAround one third of breast cancers in post-menopausal women could be prevented by decreasing body fatness and alcohol intake and increasing physical activity. This study aimed to explore views and attitudes on lifestyle intervention approaches in order to inform the proposed content of a lifestyle intervention programme amongst women attending breast cancer screening.MethodsWomen attending breast cancer screening clinics in Dundee and Glasgow, were invited to participate in focus group discussions (FGD) by clinic staff. The groups were convened out with the clinic setting and moderated by an experienced researcher who attained brief details on socio-demographic background and audio-recorded the discussions. Data analysis was guided by the framework approach. The main topics of enquiry were: Understanding of risk of breast cancer and its prevention, views on engaging with a lifestyle intervention programme offered through breast cancer screening and programme design and content.ResultsThirty one women attended 5 focus groups. Participant ages ranged from 51 to 78 years and 38 % lived in the two most deprived quintiles of residential areas. Women were generally positive about being offered a programme at breast cancer screening but sceptical about lifestyle associated risk, citing genetics, bad luck and knowing women with breast cancer who led healthy lifestyles as reasons to query the importance of lifestyle. Engagement via clinic staff and delivery of the programme by lifestyle coaches out with the screening setting was viewed favourably. The importance of body weight, physical activity and alcohol consumption with disease was widely known although most were surprised at the association with breast cancer. They were particularly surprised about the role of alcohol and resistant to thinking about themselves having a problem. They expressed frustration that lifestyle guidance was often conflicting and divergent over time. The concept of focussing on small lifestyle changes, which were personalised, supported socially and appropriate to age and ability were welcomed.ConclusionsOffering access to a lifestyle programme through breast screening appears acceptable. Explaining the relevance of the target behaviours for breast cancer health, endorsing and utilising consistent messages and identifying personalised, mutually agreed, behaviour change goals provides a framework for programme development.

Achieving Consistent, Homogeneous, Dark Fat Suppression on Bilateral Breast MRI at 3.0 Tesla in the Clinical Setting

Purpose: Effective fat suppression is a fundamental aspect of diagnostic quality breast MR for cancer screening but is challenging at 3T due to higher B0 and B1 magnetic field inhomogeneities compared with 1.5T. The purpose of this study is to describe a technique to achieve consistent homogeneous, dark fat suppression for T1 breast MR imaging at 3T for clinical breast cancer screening and evaluation. Methods: This was an IRB approved, HIPAA compliant study. Over 100 clinical breast MRI patients were scanned from May 2010 through October 2010, as part of routine clinical care, on a wide-bore 3T Magnetom Verio (Siemens Medical Solutions), One pre-contrast and two post-contrast axial VIBE scans were acquired for dynamic T1 imaging of the bilateral breasts. A longer TE of 4.9 ms was chosen empirically for optimal fat saturation. Two MQSA-certified breast radiologists, independently reviewed 20 consecutive MR studies. MR images were assessed for homogeneity of fat suppression and degree of fat suppression, both on a 5-point scale. A kappa coefficient was calculated for inter-reader agreement for both homogeneity of fat suppression and degree of fat suppression. Results: Overall, we found minimal unsuppressed fat and overall dark gray fat, indicating a high degree of fat suppression on 3T MR. Readers rated 3T fat suppression homogeneity as having minimal to no inhomogeneity in 80-90% of the examinations, with moderate agreement, (K=0.62, p<0.003), and fat suppression degree was rated having dark to very dark fat for all examinations with perfect agreement (K=1.0, p<0.001). Conclusion: Homogeneous, dark fat suppression on bilateral axial breast MRI can be obtained at 3.0T consistently in the clinical setting with minimal unsuppressed fat.

Awareness of female breast cancer among adult males in Mumbai, India

Background: Breast cancer is a major killer disease in females globally and in developing regions, where the early cancer detection facilities are unavailable, prognosis is even worse. Awareness about this disease can lead to early detection and thereby decrease the morbidity and mortality. Materials and Methods: In a longitudinal prospective survey, 150 adult males were interviewed regarding their awareness about occurrence of breast cancer in females using a self designed and validated questionnaire. A battery of questions aiming to assess the levels of awareness of adult males regarding risk factors, signs and symptoms, importance of early detection, methods of detection, treatment options and importance of exercise were considered. Results: This study presented demographic and qualitative information about the levels of awareness about a disease that is alarmingly increasing in women population in India. The results showed that 18% of the targeted adult male population had good awareness, 45% of males had an average awareness and 37% of adult males had poor awareness about breast cancer in females with respect to the domains considered in the survey questionnaire. Conclusion: Breast cancer awareness is very low among men in a metropolitan city like Mumbai. In the absence of breast cancer screening clinics, there is a dire need to take measures to improve breast cancer awareness in men so that they can play a role in early detection of this disease and thereby improve the outcome in this disease.

Breast cancer risk scores in a standard screening population

SUMMARY Aim: Information regarding the characteristics and breast cancer risk factors of British women in the standard population attending breast cancer screening is limited. Such information could be useful in personalizing screening and care, and informing and educating women about their risk. Materials &amp; methods: Information about various breast cancer risk factors was obtained from 355 women aged between 46 and 74 years at a UK inner-city breast cancer screening clinic using questionnaires. The risk of breast cancer was calculated using the modified Gail model and analyzed using descriptive and regression statistics. Results: There were 26 women recalled for further assessment and two cases confirmed as invasive breast cancer. Forty-seven women reported first-degree relatives with breast cancer. A total of 58% of our sample was overweight or obese, although 84% reported meeting the recommended target of ≥150 min of exercise per week. A total of 44% were smokers and 23% reported consuming alcohol on a regular basis. The mean lifetime risk score was 9.0% and the mean 5-year risk score was 1.5%. Various non-Gail model risk factors were found to be correlated with risk scores, but the only factor that was significantly different between women recalled for further assessment and those who were not was age of menarche. Conclusion: The results suggest that determining risk factor data in a standard screening population could be useful both to the women, who may have modifiable lifestyle factors that can be changed to improve their risk, and to the clinics, which can identify women at a higher risk who may be unaware and not present themselves as candidates for risk assessment.

Technical and clinical breast cancer screening performance indicators for computed radiography versus direct digital radiography

To compare technical and clinical screening performance parameters between computed radiography (CR) and direct digital radiography (DR) systems. The number of women screened with CR was 73,008 and with DR 116,945. Technical and patient dose survey data of 25 CR and 37 DR systems were available. Technical performance was expressed by threshold thickness values at the mean glandular dose (MGD) level of routine practice. Clinical indicators included recall rate (RR), cancer detection rate (CDR), percentage of ductal carcinoma in situ (DCIS), percentage of cancers with T-scores smaller than 1 cm and positive predictive value (PPV). Contrast threshold values for the 0.1-mm gold disk were 1.44 μm (SD 0.13 μm) for CR and 1.20 μm (SD 0.13 μm for DR). MGD was 2.16 mGy (SD 0.36 mGy) and 1.35 mGy (SD 0.32 mGy) for CR and DR respectively. We obtained for CR, respectively DR, the following results: RR in the first round of 5.48 % versus 5.61 %; RR in subsequent rounds of 2.52 % versus 2.65 %; CDR of 0.52 % versus 0.53 %; DCIS of 0.08 % versus 0.11 %; a rate of cancers with T-scores smaller than 1 cm of 0.11 % versus 0.11 %; PPV of 18.45 % versus 18.64 %; none of them was significantly different. Our screening indicators are reassuring for the use of CR and DR, with CR operating at 60 % higher MGD. • Breast cancer screening can employ both computed (CR) and direct digital radiography (DR). • Screening performance parameters for CR and DR technology are not significantly different. • Screening parameters are in accordance with European Guidelines. • Radiation doses employed for CR are generally 60 % greater than for DR.

Ten Years after Human Genome Sequencing: Is Personalized Breast Screening and Prevention Reality?

To the Editor, In the May issue of the World Journal of Surgery, Bennett and colleagues reported the results of multimodality breast screening for women at high risk of developing breast cancer. Are we able—nearly a decade since the completion of the draft sequence of the human genome—to translate the major advances in biotechnology, DNA sequence, and basic sciences to stratify women in the general population according to their breast-cancer risk for personalized screening and individualized primary prevention? In 1999, Bennett et al. [1], recognizing the need for personalized screening, established a Familial Breast Cancer Screening Clinic (FBCSC) program for women with breast cancer family history and increased risk of breast cancer. Since its inception, a total of 2,440 women have participated in the FBCSC clinical breast examination, breast ultrasound, and mammography. The authors conclude that multimodality screening for these women was effective and appropriate. During the past decade, rapid advances have been made in screening and primary prevention of women at risk of hereditary breast ovarian cancer (HBOC) syndrome. Genetic testing for identifying carriers of mutations in BRCA1 and BRCA2 (BRCA1/2) genes has been available, and breast magnetic resonance imaging has been recommended by recent guidelines for women at increased risk of breast cancer. However, several questions grow the uncertainty. Do women with positive BRCA1/2 testing benefit more from prophylactic bilateral mastectomy, bilateral salpingo-oophorectomy, or intensified surveillance? What is the optimal screening for women with family history but BRCA1/2-negative testing? Given that these heritable BRCA mutations with large effect on breast-cancer risk are very rare in the general population, what is the management of the vast majority of women in the general population without family history? The landmark achievement of the completion of the draft sequence of the human genome a decade ago raised excitement that would lead to a new era of molecular medicine and new ways to prevent, diagnose, treat, and cure complex diseases as cancer. However, despite research and technology rapid advances in the past decade, has human health truly benefited from the sequencing of the human genome? The leaders of the public and private efforts for the completion of human genome sequencing, Francis Collins and Craig Venter, both say ‘‘not much’’ [2, 3]. Indeed, a large-scale study based on newly discovered genetic variants provided negative results. In this study published in the New England Journal of Medicine, the addition of ten SNPs in standard breast cancer risk factors was not associated with a significant increase in the prediction risk of women who participated in this study [4]. In a recent editorial in the journal Nature for the first postgenomic decade era, it is emphasized that the astounding technological and intellectual advances should include equally astounding applications to human health in the next decade [5]. But because of the high complexity and heterogeneity of breast cancer, it is unknown whether primary prevention of women in the general population and cure of patients with breast cancer can be achieved within the next C. Katsios Department of Surgery, University of Ioannina, School of Medicine, Ioannina 451 10, Greece e-mail: chkatsios@gmail.com

Outcomes of Multimodality Breast Screening for Women at Increased Risk of Familial Breast Cancer

While population-based breast screening for women over the age of 50 years is a generally accepted and proven health strategy, the role of breast screening specifically among women at high risk of familial breast cancer has remained controversial. Indeed, there are very few services specifically offering a breast-screening program for women at high risk of familial breast cancer. In 1999 a Familial Breast Cancer Screening Clinic (FBCSC) was established at the North Brisbane BreastScreen Queensland Service to provide a regular multimodality screening program utilizing clinical breast examination, breast ultrasound, and mammography for women at higher risk of hereditary breast cancer and with entry into the program commencing from the age of 30 years. Since its inception, a total of 2440 women have participated in the FBCSC. A total 7051 breast-screening examinations have been performed on these participants, with 53 breast cancers being diagnosed, including 8 in situ ductal carcinomas, 38 invasive ductal carcinomas, and 7 invasive lobular carcinomas. The mean size of the cancers was 16 mm (range = 1-45 mm), and of the 45 invasive cancers, 60% were less than or equal to 15 mm in size. The overall axillary node positive rate was 24.5% (13/53). The invasive cancer detection rate for first-round screening was 8.3 cancers per 1000 women screened, with 5.2 cancers per 1000 women detected on subsequent round screening. The results from this service demonstrate that multimodality screening for women at high risk of familial breast cancer and including women of younger age is effective and appropriate, with very acceptable cancer detection rates and pathological cancer characteristics being observed consistent with early-stage detection. The colocated siting of this service within a BreastScreen Queensland facility has proven to be efficient and cost effective.

Measuring the psychological consequences of breast cancer screening: a confirmatory factor analysis of the Psychological Consequences Questionnaire

To use confirmatory factor analysis (CFA) to test the proposed factor structure of the Psychological Consequences Questionnaire (PCQ), a measure of the psychological impact of breast cancer screening. A further aim was to examine the robustness of the proposed factor structure across key demographic and clinical variables. Following visits to breast cancer screening clinics, women who received a false-positive diagnosis and a matched sample of women who had received all-clear diagnoses were sent a questionnaire package containing the PCQ and a demographics measure. A total of 220 women returned completed questionnaires. CFA was used to test the factor structure and multiple indicator-multiple cause (MIMIC) models were used to test the robustness of the factor structure across the test result group, age, and family history of breast cancer diagnosis. The CFA results suggested support for both a three- and a one-factor model; a one-factor model was preferred, however, due to the very high covariance between the three latent factors in the three-factor model. A CFA MIMIC model suggested that the test result impacted on the latent factor: women who initially received a false-positive diagnosis showed significantly higher levels of psychological dysfunction after screening. The PCQ appears to be a promising tool for assessing psychological dysfunction after breast cancer screening; however, a one-factor model received more support than the initially proposed three-factor model. There was little evidence of differential item functioning across key demographic and clinical variables for the PCQ.