Familiarity, confidence and preference of artificial intelligence feedback and prompts by Australian breast cancer screening readers.

Objectives This study explored the familiarity, perceptions and confidence of Australian radiology clinicians involved in reading screening mammograms, regarding artificial intelligence (AI) applications in breast cancer detection. Methods Sixty-five radiologists, breast physicians and radiology trainees participated in an online survey that consisted of 23 multiple choice questions asking about their experience and familiarity with AI products. Furthermore, the survey asked about their confidence in using AI outputs and their preference for AI modes applied in a breast screening context. Participants' responses to questions were compared using Pearson's χ 2 test. Bonferroni-adjusted significance tests were used for pairwise comparisons. Results Fifty-five percent of respondents had experience with AI in their workplaces, with automatic density measurement powered by machine learning being the most familiar AI product (69.4%). The top AI outputs with the highest ranks of perceived confidence were 'Displaying suspicious areas on mammograms with the percentage of cancer possibility' (67.8%) and 'Automatic mammogram classification (normal, benign, cancer, uncertain)' (64.6%). Radiology and breast physicians preferred using AI as second-reader mode (75.4% saying 'somewhat happy' to 'extremely happy') over triage (47.7%), pre-screening and first-reader modes (both with 26.2%) (P < 0.001). Conclusion The majority of screen readers expressed increased confidence in utilising AI for highlighting suspicious areas on mammograms and for automatically classifying mammograms. They considered AI as an optimal second-reader mode being the most ideal use in a screening program. The findings provide valuable insights into the familiarities and expectations of radiologists and breast clinicians for the AI products that can enhance the effectiveness of the breast cancer screening programs, benefitting both healthcare professionals and patients alike.

AI for interpreting screening mammograms: implications for missed cancer in double reading practices and challenging-to-locate lesions.

Although the value of adding AI as a surrogate second reader in various scenarios has been investigated, it is unknown whether implementing an AI tool within double reading practice would capture additional subtle cancers missed by both radiologists who independently assessed the mammograms. This paper assesses the effectiveness of two state-of-the-art Artificial Intelligence (AI) models in detecting retrospectively-identified missed cancers within a screening program employing double reading practices. The study also explores the agreement between AI and radiologists in locating the lesions, considering various levels of concordance among the radiologists in locating the lesions. The Globally-aware Multiple Instance Classifier (GMIC) and Global-Local Activation Maps (GLAM) models were fine-tuned for our dataset. We evaluated the sensitivity of both models on missed cancers retrospectively identified by a panel of three radiologists who reviewed prior examinations of 729 cancer cases detected in a screening program with double reading practice. Two of these experts annotated the lesions, and based on their concordance levels, cases were categorized as 'almost perfect,' 'substantial,' 'moderate,' and 'poor.' We employed Similarity or Histogram Intersection (SIM) and Kullback-Leibler Divergence (KLD) metrics to compare saliency maps of malignant cases from the AI model with annotations from radiologists in each category. In total, 24.82% of cancers were labeled as "missed." The performance of GMIC and GLAM on the missed cancer cases was 82.98% and 79.79%, respectively, while for the true screen-detected cancers, the performances were 89.54% and 87.25%, respectively (p-values for the difference in sensitivity < 0.05). As anticipated, SIM and KLD from saliency maps were best in 'almost perfect,' followed by 'substantial,' 'moderate,' and 'poor.' Both GMIC and GLAM (p-values < 0.05) exhibited greater sensitivity at higher concordance. Even in a screening program with independent double reading, adding AI could potentially identify missed cancers. However, the challenging-to-locate lesions for radiologists impose a similar challenge for AI.

Evaluating Recalibrating AI Models for Breast Cancer Diagnosis in a New Context: Insights from Transfer Learning, Image Enhancement and High-Quality Training Data Integration.

This paper investigates the adaptability of four state-of-the-art artificial intelligence (AI) models to the Australian mammographic context through transfer learning, explores the impact of image enhancement on model performance and analyses the relationship between AI outputs and histopathological features for clinical relevance and accuracy assessment. A total of 1712 screening mammograms (n = 856 cancer cases and n = 856 matched normal cases) were used in this study. The 856 cases with cancer lesions were annotated by two expert radiologists and the level of concordance between their annotations was used to establish two sets: a 'high-concordances subset' with 99% agreement of cancer location and an 'entire dataset' with all cases included. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of Globally aware Multiple Instance Classifier (GMIC), Global-Local Activation Maps (GLAM), I&H and End2End AI models, both in the pretrained and transfer learning modes, with and without applying the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm. The four AI models with and without transfer learning in the high-concordance subset outperformed those in the entire dataset. Applying the CLAHE algorithm to mammograms improved the performance of the AI models. In the high-concordance subset with the transfer learning and CLAHE algorithm applied, the AUC of the GMIC model was highest (0.912), followed by the GLAM model (0.909), I&H (0.893) and End2End (0.875). There were significant differences (p < 0.05) in the performances of the four AI models between the high-concordance subset and the entire dataset. The AI models demonstrated significant differences in malignancy probability concerning different tumour size categories in mammograms. The performance of AI models was affected by several factors such as concordance classification, image enhancement and transfer learning. Mammograms with a strong concordance with radiologists' annotations, applying image enhancement and transfer learning could enhance the accuracy of AI models.

Variations of image interpretations of radiologists from different populations in mammography and tomosynthesis with different levels of breast density.

Purpose: This study aims to investigate the diagnostic performances of Australian and Shanghai-based Chinese radiologists in reading full-field digital mammogram (FFDM) and digital breast tomosynthesis (DBT) with different levels of breast density. Approach: Eighty-two Australian radiologists interpreted a 60-case FFDM set, and 29 radiologists also reported a 35-case DBT set. Sixty Shanghai radiologists read the same FFDM set, and 32 radiologists read the DBT set. The diagnostic performances of Australian and Shanghai radiologists were assessed using truth data (cancer cases were biopsy proven) and compared overall in specificity, case sensitivity, lesion sensitivity, receiver operating characteristics (ROC) area under the curve, and jack-knife free-response receiver operating characteristics (JAFROC) figure of merit, and they were stratified by case characteristics using the Mann-Whitney U test. The Spearman rank test was used to explore the association between radiologists' performances and their work experience in mammogram interpretation. Results: There were significantly higher performances of Australian radiologists compared with Shanghai radiologists in low breast density for case sensitivity, lesion sensitivity, ROC, and JAFROC in the FFDM set ( P < 0.0001 ); in high breast density, Shanghai radiologists' performances in lesion sensitivity and JAFROC were also lower than Australian radiologists ( P < 0.0001 ). In the DBT test set, Australian radiologists performed better than Shanghai radiologists in cancer detection in both low and high breast density. The work experience of Australian radiologists was positively linked to their diagnostic performances, whereas this association was not statistically significant in Shanghai radiologists. Conclusion: There were significant variations in reading performances between Australian and Shanghai radiologists in FFDM and DBT across different levels of breast density, lesion types, and lesion sizes. An effective training initiative tailored to suit local readers is essential to enhancing the diagnostic accuracy of Shanghai radiologists.

The Impact of Prior Mammograms on the Diagnostic Performance of Radiologists in Early Breast Cancer Detection: A Focus on Breast Density, Lesion Features and Vendors Using Wholly Digital Screening Cases.

BACKGROUND: This study aims to investigate the diagnostic efficacy of radiologists when reading screening mammograms in the absence of previous images, and with the presence of prior images from the same and different vendors. METHODS: 612 radiologists' readings across 9 test sets, consisting of 540 screening mammograms (361-normal and 179-cancer) with 245 cases having prior images obtained from same vendor as current images, 129 from a different vendor and 166 cases having no prior images, were retrospectively analysed. True positive (sensitivity), true negative (specificity) and area under ROC curve (AUC) values of radiologists were calculated for three groups of cases (without prior images (NP), with prior images from same vendor (SP), and with prior images from different vendor (DP)). Logistic regression was used to estimate the odds ratio (OR) of true positive, true negative and true cancer localization among case groups with different levels of breast density and lesion characteristics. RESULTS: Radiologists obtained 12.8% and 10.3% higher sensitivity in NP and DP than SP (0.803-and-0.785 vs. 0.712; p < 0.0001). Specificity in NP and DP cases were 4.8% and 2.0% lower than SP cases (0.749 and 0.771 vs. 0.787). The AUC values for NP and DP were significantly higher than SP cases across different levels of breast density (0.814-and-0.820 vs. 0.782; p < 0.0001). The odds ratio (OR) of true positive for NP relative to SP was 1.6 (p < 0.0001) and DP relative to SP was 1.5 (p < 0.0001). Radiologists were more like to detect architectural distortion in DP than SP cases (OR = 3.2; p < 0.0001), whilst the OR for abnormal calcifications was 2.85 (p < 0.0001). CONCLUSIONS: Cases without previous mammograms or with prior mammograms obtained from different vendors were more likely to benefit radiologists in cancer detection, whilst prior mammograms undertaken from the same vendor were more useful for radiologists in evaluating normal cases.

Radiologists' performance in reading digital breast tomosynthesis with and without synthesized views for cancer detection.

OBJECTIVE: The study aims to evaluate the diagnostic efficacy of radiologists and radiology trainees in digital breast tomosynthesis (DBT) alone vs DBT plus synthesized view (SV) for an understanding of the adequacy of DBT images to identify cancer lesions. METHODS: Fifty-five observers (30 radiologists and 25 radiology trainees) participated in reading a set of 35 cases (15 cancer) with 28 readers reading DBT and 27 readers reading DBT plus SV. Two groups of readers had similar experience in interpreting mammograms. The performances of participants in each reading mode were compared with the ground truth and calculated in term of specificity, sensitivity, and ROC AUC. The cancer detection rate in various levels of breast density, lesion types and lesion sizes between 'DBT' and 'DBT + SV' were also analyzed. The difference in diagnostic accuracy of readers between two reading modes was assessed using Man-Whitney U test. p < 0.05 indicated a significant result. RESULTS: There was no significant difference in specificity (0.67-vs-0.65; p = 0.69), sensitivity (0.77-vs-0.71; p = 0.09), ROC AUC (0.77-vs-0.73; p = 0.19) of radiologists reading DBT plus SV compared with radiologists reading DBT. Similar result was found in radiology trainees with no significant difference in specificity (0.70-vs-0.63; p = 0.29), sensitivity (0.44-vs-0.55; p = 0.19), ROC AUC (0.59-vs-0.62; p = 0.60) between two reading modes. Radiologists and trainees obtained similar results in two reading modes for cancer detection rate with different levels of breast density, cancer types and sizes of lesions (p > 0.05). CONCLUSION: Findings show that the diagnostic performances of radiologists and radiology trainees in DBT alone and DBT plus SV were equivalent in identifying cancer and normal cases. ADVANCES IN KNOWLEDGE: DBT alone had equivalent diagnostic accuracy as DBT plus SV which could imply the consideration of using DBT as a sole modality without SV.

Radiologist Self-training: a Study of Cancer Detection when Reading Mammograms at Work Clinics or Workshops.

Provision of online and remote specialist education and general continued professional education in medicine is a growing field. For radiology specifically, the ability to access web-based platforms that house high resolution medical images, and the high fidelity of simulated activities is increasingly growing due to positive changes in technology. This study investigates the differences in providing a self-directed specialist radiology education system in two modes: at clinics and in-person workshops. 335 Australian radiologists completed 562 readings of mammogram test sets through the web-based interactive BREAST platform with 325 at conference workshops and 237 at their workplaces. They engaged with test sets with each comprising of 60 mammogram cases (20 cancer and 40 normal). Radiologists marked the location of any cancers and had their performance measured via 5 metrics of diagnostic accuracy. Results show that the location of engagement with BREAST did not yield any significant difference in the performances of all radiologists and the same radiologists between two reading modes (P > 0.05). Radiologists who read screening mammograms for BreastScreen Australia performed better when they completed the test sets at designated workshops (P < 0.05), as was also the case for radiologists who read > 100 cases per week (P < 0.05). In contrast, radiologists who read less mammograms frequently recorded better performances in specificity and JAFROC at clinics (P < 0.05). Findings show that remotely accessed online education for specialised training and core skills building in radiology can provide a similar learning opportunity for breast radiologists when compared to on-site dedicated workshops at scientific meetings. For readers with high volumes of mammograms, a workshop setting may provide a superior experience while clinic setting is more helpful to less experienced readers.

Use of Full-quality DICOM Images Compared to Minimally Compressed Mammograms in JPEG Format for Radiology Training: A Study From Radiologist and Radiographer Perspectives.

BACKGROUND: Running online training in mammography interpretation poses a challenge to radiologists and reporting radiographers due to the large size of digital mammograms in DICOM format and limited bandwidth capabilities of the users for image transmission. This study aims to compare image quality between the full-quality with minimal compressed JPEG and DICOM format of mammograms on a diagnostic monitor through the evaluation of radiologists and radiographers. METHODS: Twelve participants including six radiologists and six radiographers participated as observers in this study. The observers viewed 60 2D digital mammography screening cases (22 cancer and 38 normal cases) in DICOM and minimal compressed JPEG formats on a 5MP diagnostic monitor. A 5-point Likert scale was provided for observers to compare the quality of mammograms between the two formats, with text anchors indicating to one image being significantly better, slightly better or of equal quality in terms of technical and diagnostic aspects. Nonparametric descriptive statistics were used to evaluate the ratings of radiologists and radiographers in different characteristics of mammograms of two image formats. RESULTS: The DICOM and JPEG images were statistically equivalent through ratings from radiographers in brightness, contrast, dynamic range, sharpness, no significant distortion, no significant noise, and background homogeneity in all mammograms. Similarly, most radiologists rated DICOM and JPEG images clinically and statistically equivalent with respect to difficulty of interpretation, brightness, contrast, dynamic range, sharpness, the appearance of Cooper's ligaments, visibility of subtle microcalcifications, visibility of structures at the margins of the breast. Normal cases were marginally favored by radiologists in DICOM format (ranging from 0.4% to 5.3%) while cancer cases in JPEG (ranging from 0.8% to 7.6%) received slightly higher rating. CONCLUSIONS: Findings showed that baseline full-quality with minimal compression JPEG was equivalent to the DICOM format of full-field digital mammograms which suggests that this type of JPEG could be used for online training and education in radiology.

Differences in lesion interpretation between radiologists in two countries: Lessons from a digital breast tomosynthesis training test set.

INTRODUCTION: In many western countries, there is good evidence documenting the performance of radiologists reading digital breast tomosynthesis (DBT) images. However, the diagnostic efficiency of Chinese radiologists using DBT, particularly type of errors being made and type of cancers being missed, is understudied. This study aims to investigate the pattern of diagnostic errors across different lesion types produced by Chinese radiologists diagnosing from DBT images. Australian radiologists will be used as a benchmark. METHODS: Twelve Chinese radiologists read a DBT test set and located each perceived cancer lesion. True positives, false positives (FP), true negatives and false negatives (FN) were generated. The same test set was also read by 14 Australian radiologists. Z-scores and Pearson correlations were used to compare interpretation of lesions and identification of normal appearances between two groups of radiologists. RESULTS: Architectural distortions (p < .001) and stellate masses (p = .02) were more difficult for Chinese radiologists to correctly diagnose compared to their Australian counterparts. Chinese readers categorised more FPs as discrete masses (p < .001) and fewer FPs as architectural distortions (p < .001) comparing with Australian radiologists. The percentages of FN for each cancer case were not correlated (r = 0.37, p = .18) but the percentages of FP for each normal case were moderately correlated (r = 0.52, p = .02) between two groups of readers. CONCLUSIONS: Architectural distortions and stellate masses were challenging to Chinese radiologists when reading DBT. Our findings proposed the need of development of training and education programs focussing on imaging cases tailored for specific groups of readers with certain interpretation patterns.

Look how far we have come: BREAST cancer detection education on the international stage.

The development of screening mammography over 30 years has remarkedly reduced breast cancer-associated mortality by 20%-30% through detection of small cancer lesions at early stages. Yet breast screening programmes may function differently in each nation depending on the incidence rate, national legislation, local health infrastructure and training opportunities including feedback on performance. Mammography has been the frontline breast cancer screening tool for several decades; however, it is estimated that there are 15% to 35% of cancers missed on screening which are owing to perceptual and decision-making errors by radiologists and other readers. Furthermore, mammography screening is not available in all countries and the increased speed in the number of new breast cancer cases among less developed countries exceeds that of the developed world in recent decades. Studies conducted through the BreastScreen Reader Assessment Strategy (BREAST) training tools for breast screening readers have documented benchmarking and significant variation in diagnostic performances in screening mammogram test sets in different countries. The performance of the radiologists from less well-established breast screening countries such as China, Mongolia and Vietnam were significant lower in detecting early-stage cancers than radiologists from developed countries such as Australia, USA, Singapore, Italy. Differences in breast features and cancer presentations, discrepancies in the level of experiences in reading screening mammograms, the availability of high-quality national breast screening program and breast image interpretation training courses between developed and less developed countries are likely to have impact on the variation of readers' performances. Hence dedicated education training programs with the ability to tailor to different reader cohorts and different population presentations are suggested to ameliorate challenges in exposure to a range of cancer cases and improve the interpretation skills of local radiologists. Findings from this review provide a good understanding of the radiologist' performances and their improvement using the education interventions, primarily the BREAST program, which has been deployed in a large range of developing and developed countries in the last decade. Self-testing and immediate feedback loops have been shown to have important implications for benchmarking and improving the diagnostic accuracy in radiology worldwide for better breast cancer control.

Improving radiologist's ability in identifying particular abnormal lesions on mammograms through training test set with immediate feedback.

It has been shown that there are differences in diagnostic accuracy of cancer detection on mammograms, from below 50% in developing countries to over 80% in developed world. One previous study reported that radiologists from a population in Asia displayed a low mammographic cancer detection of 48% compared with over 80% in developed countries, and more importantly, that most lesions missed by these radiologists were spiculated masses or stellate lesions. The aim of this study was to explore the performance of radiologists after undertaking a training test set which had been designed to improve the capability in detecting a specific type of cancers on mammograms. Twenty-five radiologists read two sets of 60 mammograms in a standardized mammogram reading room. The first test set focused on stellate or spiculated masses. When radiologists completed the first set, the system displayed immediate feedback to the readers comparing their performances in each case with the truth of cancer cases and cancer types so that the readers could identify individual-based errors. Later radiologists were asked to read the second set of mammograms which contained different types of cancers including stellate/spiculated masses, asymmetric density, calcification, discrete mass and architectural distortion. Case sensitivity, lesion sensitivity, specificity, receiver operating characteristics (ROC) and Jackknife alternative free-response receiver operating characteristics (JAFROC) were calculated for each participant and their diagnostic accuracy was compared between two sessions. Results showed significant improvement among radiologists in case sensitivity (+ 11.4%; P < 0.05), lesion sensitivity (+ 18.7%; P < 0.01) and JAFROC (+ 11%; P < 0.01) in the second set compared with the first set. The increase in diagnostic accuracy was also recorded in the detection of stellate/spiculated mass (+ 20.6%; P < 0.05). This indicated that the performance of radiologists in detecting malignant lesions on mammograms can be improved if an appropriate training intervention is applied after the readers' weakness and strength are identified.

Mammographic interpretation in Vietnam: Tailored educational strategies are needed to increase clinicians' expertise.

AIM: Breast cancer incidence is rapidly increasing throughout South East Asia, highlighting the need for high-quality early diagnosis and treatment. This study aims to investigate the efficacy of mammography detection in Hanoi and Ho Chi Minh City (HCMC), Vietnam, using data from Australian radiologists as a benchmark; factors that influence performance will be highlighted. METHODS: A total of 53, 35 and 52 clinicians from Australia, HCMC and Hanoi, respectively, examined and diagnosed a test set of 60 mammograms, 20 of which contained cancers. Each clinician completed an accompanying questionnaire establishing demographic and experiential characteristics. The performance metrics of specificity, sensitivity, area under the receiver operating characteristic curve (AUC), location sensitivity and Jackknife free-response ROC (JAFROC) figure of merit were used to evaluate clinicians performance. Mann-Whitney and Kruskal-Wallis statistical methods were employed to establish significance. RESULTS: Vietnamese radiologists demonstrated significantly lower sensitivity, AUC, lesion sensitivity and JAFROC scores compared to Australian radiologists. There was no difference in performance between clinicians from Hanoi and HCMC. However, certain performance features (older and more experienced clinicians compared with their younger, less experienced counterparts, readers who read more compared with fewer mammograms per week, clinicians with greater radiological experience and clinicians that completed a fellowship) demonstrated significantly better performances. CONCLUSIONS: The significant difference in diagnostic efficacy of mammograms between Vietnam and Australia identifies the need for improvements in breast radiology training, management and practice. Cost-effective solutions are available that can improve the reading efficacy of clinicians, and consequently health outcomes for Vietnamese women.

Interpretative characteristics and case features associated with the performances of radiologists in reading mammograms: A study from a non-screening population in Asia.

AIMS: To explore radiologist characteristics and case features associated with diagnostic performances in cancer detection on mammograms in a South East Asian population. METHODS: Fifty-three radiologists reported 60 mammographic examinations which consisted of 40 normal and 20 cancer-containing cases at the BREAST workshops. Radiologists were asked to examine each mammogram using the BIRADS on diagnostic monitors. Differences in reader characteristics and case features between correct and incorrect decisions were assessed separately for cancer and normal cases. Univariate and multivariate logistic regressions were applied to generate odds ratios (OR) for significant factors related to correct decisions. RESULTS: Radiologists who spent ≥10 hours/week reporting mammograms had a higher possibility of detecting cancer lesions (OR = 1.6; P = 0.01). A higher rate of accuracy in reporting negative cases was associated with female radiologists (OR = 1.4; P = 0.002), radiologists who read ≤20 mammograms per week (OR = 1.5; P < 0.0001), had completed training course (OR = 1.7; P < 0.0001) or wore eyeglasses (OR = 1.4; P = 0.01). Cancer cases with breast density >50% (OR = 2.1; P < 0.0001), having abnormal lesions ≥9 mm (OR = 1.8; P < 0.0001), or displaying calcifications, a discrete mass or nonspecific density (OR = 1.6; P < 0.0001) were recorded with a higher detection rate by radiologists than other cases. Lesions located on the right breasts (OR = 1.8; P < 0.0001) or found in the lower inner, upper outer or mixed locations (OR = 2.7; P < 0.0001) were also recorded with a better diagnostic possibility compared with other lesions. CONCLUSION: This work identified key features related to diagnostic accuracy of breast cancer on mammograms in a nonscreening population, which is helpful for developing appropriate strategies to improve breast cancer detectability of radiologists.

Reading High Breast Density Mammograms: Differences in Diagnostic Performance between Radiologists from Hong Kong SAR/Guangdong Province in China and Australia.

BACKGROUND: Variations in the performance of radiologists reading mammographic images are well reported, but key parameters explaining such variations in different countries are not fully explored. The main aim of this study is to investigate performances of Chinese (Hong Kong SAR and Guangdong Province) and Australian radiologists in interpreting dense breast mammographic images. METHODS: A test set, contained 60 mammographic examinations with high breast density, was used to assess radiologists' performance. Twelve Chinese and thirteen Australian radiologists read all the cases independently and were asked to identify all lesions and provide a grade from 1 to 5 to each lesion. Case sensitivity, specificity, lesion sensitivity, AUC and JAFROC were used to assess radiologists' performances. Demographic information and reading experience were also collected from the readers. Performance scores were compared between the two populations and the relationships between performance scores and their reading experience were discovered. RESULTS: For radiologists who were less than 40-year-old, lesion sensitivity, AUC and JAFROC were significantly lower in Chinese radiologists than those in Australian (52.10% vs 71.45%, p=0.043; 0.76 vs 0.84, p=0.031; 0.59 vs 0.72, p=0.045; respectively). Australian radiologists with less than 10 years of reading experience had higher AUC and JAFROC scores compared with their Chinese counterparts (0.83 vs 0.76, p=0.039; 0.70 vs 0.56, p=0.020, respectively). CONCLUSIONS: We found that younger Australian radiologists performed better at reading dense breast cases which is likely to be linked to intensive fellowship training, immersion in a screening program and exposure to the benefits of a performance-measuring education tool.

Reader characteristics and mammogram features associated with breast imaging reporting scores.

OBJECTIVES: This study aims to explore the reading performances of radiologists in detecting cancers on mammograms using Tabar Breast Imaging Reporting and Data System (BIRADS) classification and identify factors related to breast imaging reporting scores. METHODS: 117 readings of five different mammogram test sets with each set containing 20 cancer and 40 normal cases were performed by Australian radiologists. Each radiologist evaluated the mammograms using the BIRADS lexicon with category 1 - negative, category 2 - benign findings, category 3 - equivocal findings (Recall), category 4 - suspicious findings (Recall), and category 5 - highly suggestive of malignant findings (Recall). Performance metrics (true positive, false positive, true negative, and false negative) were calculated for each radiologist and the distribution of reporting categories was analyzed in reader-based and case-based groups. The association of reader characteristics and case features among categories was examined using Mann-Whitney U and Kruskal-Wallis tests. RESULTS: 38% of cancer-containing mammograms were reported with category 3 which decreased to 32.3% with category 4 and 16.2% with category 5 while 16.6 and 10.3% of cancer cases were marked with categories 1 and 2. Female readers had less false-negative rates when using categories 1 and 2 for cancer cases than male readers (p < 0.01). A similar pattern as gender category was also found in Breast Screen readers and readers completed breast reading fellowships compared with non-Breast Screen and non-fellowship readers (p < 0.05). Radiologists with low number of cases read per week were more likely to record the cancer cases with category 4 while the ones with high number of cases were with category 3 (p < 0.01). Discrete mass and asymmetric density were the two types of abnormalities reported mostly as equivocal findings with category 3 (47-50%; p = 0.005) while spiculated mass or stellate lesions were mostly selected as highly suggestive of malignancy with category 5 (26%, p = 0.001). CONCLUSIONS: Most radiologists used category 3 when reporting cancer mammograms. Gender, working for BreastScreen, fellowship completion, and number of cases read per week were factors associated with scoring selection. Radiologists reported higher Tabar BIRADS category for specific types of abnormalities on mammograms than others. ADVANCES IN KNOWLEDGE: The study identified factors associated with the decision of radiologists in assigning a BIRADS Tabar score for mammograms with abnormality. These findings will be useful for individual training programs to improve the confidence of radiologists in recognizing abnormal lesions on screening mammograms.

Breast Cancer Diagnostic Efficacy in a Developing South-East Asian Country

Background: Breast cancer, is increasing in prevalence amongst South East (SE) Asian women, highlighting the need for high quality, early diagnoses. This study investigated radiologists' detection efficacy in a developing (DC) and developed (DDC) SE Asian country, as compared to Australian radiologists. Methods: Using a test-set of 60 mammographic cases, 20 containing cancer, JAFROC figures of merit (FOM) and ROC area under the curves (AUC) were calculated as well as location sensitivity, sensitivity and specificity. The test set was examined by 35, 15, and 53 radiologists from DC, a DDC and Australia, respectively. Results: DC radiologists, compared to both groups of counterparts, demonstrated significantly lower JAFROC FOM, ROC AUC and specificity scores. DC radiologists had a significantly lower location sensitivity than Australian radiologists. DC radiologists also demonstrated significantly lower values for age, hours of reading per week, and years of mammography experience when compared with other radiologists. Conclusion: Significant differences in breast cancer detection parameters can be attributed to the experience of DC radiologists. The development of inexpensive, innovative, interactive training programs are discussed. This nonuniform level of breast cancer detection between countries must be addressed to achieve the World Health Organisation goal of health equity.

Improvement of Cancer Detection on Mammograms via BREAST Test Sets.

BACKGROUND: Breast Screen Reader Assessment Strategy (BREAST) is an innovative training and research program for radiologists in Australia and New Zealand. The aim of this study is to evaluate the efficacy of BREAST test sets in improving readers' performance in detecting cancers on mammograms. MATERIALS AND METHODS: Between 2011 and 2018, 50 radiologists (40 fellows, 10 registrars) completed three BREAST test sets and 17 radiologists completed four test sets. Each test set contained 20 biopsy-proven cancer and 40 normal cases. Immediate image-based feedback was available to readers after they completed each test set which allowed the comparison of their selections with the truth. Case specificity, case sensitivity, lesion sensitivity, the Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) and Jackknife Free-Response Receiver Operating Characteristic (JAFROC) Figure of Merit (FOM) were calculated for each reader. Kruskal-Wallis test was utilized to compare scores of the radiologist and registrars across all test-sets whilst Wilcoxon signed rank test was to compare the scores between pairs of test sets. RESULTS: Significant improvements in lesion sensitivity ranging from 21% to 31% were found in radiologists completing later test sets compared to first test set (p ≤ 0.01). Eighty three percent of radiologists achieved higher performance in lesion sensitivity after they completed the first read. Registrars had significantly better scores in the third test set compared to the first set with mean increases of 79% in lesion sensitivity (p = 0.005) and 37% in JAFROC (p = 0.02). Sixty percent and 100% of registrars increased their scores in lesion sensitivity in the second and third reads compared to the first read while the percentage of registrars with higher scores in JAFROC was 80%. CONCLUSION: Introduction of BREAST into national training programs appears to have an important impact in promoting diagnostic efficacy amongst radiologists and radiology registrars undergoing mammographic readings.

Inconsistencies of Breast Cancer Risk Factors between the Northern and Southern Regions of Vietnam

Background: In recent decades the amount of new breast cancer cases in the southern region has been reported to increase more rapidly than in the northernVietnam. The aim of this study is to compare breast cancer risk factors between the two regions and establish if westernized influences have an impact on any reported differences. Method: Data was collected from the two largest oncology hospitals in the north and the south of Vietnam in 2015. Breast density, demographic, reproductive and lifestyle data of 127 cases and 269 controls were collected in the north and 141 cases and 250 controls were gathered from the south. Baseline differences in factors between cases and age-matched controls in each region were assessed using chi-square tests and independent t-tests. Odds ratios (OR) for independent risk factors for breast cancer were obtained from conditional logistic regression. Results: In northern Vietnam significantly increased risks in developing breast cancer were observed for women with age at first menstrual period less than 14 years old (OR=2.1; P<0.05), post-menopausal status (OR=2.6; P<0.0001), having less than 2 babies (OR=2.1; P<0.05). Southern Vietnamese women having a breast density of more than 75% (OR=2.1; P<0.01), experiencing post-menopause (OR=1.6; P<0.05), having a history of less than 3 pregnancies (OR=2.6; P<0.0001) and drinking more than a cup of coffee per day (OR=1.9; P<0.05) were more likely to be diagnosed with breast cancer. Conclusion: We found that women living in the south had some breast cancer associations, such as increased mammographic density and coffee consumption, which are closer to the risks in westernized populations than women in the north.

Risk Factors of Female Breast Cancer in Vietnam: A Case-Control Study.

PURPOSE: Rates of women with breast cancer have increased rapidly in recent years in Vietnam, with over 10,000 new patients contracting the disease every year. This study was conducted to identify demographic, reproductive and lifestyle risk factors for breast cancer in Vietnam. MATERIALS AND METHODS: Breast density, demographic, reproductive and lifestyle data of 269 women with breast cancer and 519 age-matched controls were collected in the two largest oncology hospitals in Vietnam (one in the north and one in the south). Baseline differences between cases and controls in all women, premenopausal and postmenopausal women were assessed using chi-squared tests and independent t tests. Conditional logistic regression was used to derive odds ratios (OR) for factors that had statistically significant associations with breast cancer. RESULTS: Vietnamese women with breast cancer were significantly more likely to have a breast density > 75% (OR, 1.7), be younger than 14 years at first menstrual period (OR, 2.2), be postmenopausal (OR, 2.0), have less than three pregnancies (OR, 2.1), and have less than two babies (OR, 1.7). High breast density (OR, 1.6), early age at first menstrual period (OR, 2.6), low number of pregnancies (OR, 2.3), hormone use (OR, 1.8), and no physical activities (OR, 2.2) were significantly associated with breast cancer among premenopausal women, while breast density (OR, 2.0), age at first menstrual period (OR, 1.8), number of pregnancies (OR, 2.3), and number of live births (OR, 2.4) were the risk factors for postmenopausal women. CONCLUSION: Breast density, age at first menarche, menopause status, number of pregnancies, number of babies born, hormone use and physical activities were significantly associated with breast cancer in Vietnamese women.

Female breast cancer in Vietnam: a comparison across Asian specific regions.

Breast cancer is one of the most commonly diagnosed malignancies and the leading cause of cancer death of women over the world. A large number of females with breast cancer in Vietnam and other Southeast Asian (SEA) countries present at an early age with more aggressive tumors compared with women in Australia. Despite experiencing a low incidence rate, the increasing incidence rate among SEA countries exceeds that of the Westernized world. Changes in reproductive factors, environmental exposures, and lifestyle are the possible causes of this trend. However, limited evidence shows that these factors are associated with breast cancer in the Vietnamese population. Breast cancer incidence rates within Vietnam are not uniform and appear to be dependent on geographic location. Findings from this review have important implications for breast cancer control and treatment in Vietnam. A good understanding of the morphology of the breast and the type and nature of breast cancers presenting in Vietnam is required to facilitate the introduction of an effective national breast screening program.