Harnessing imaging tools to guide immunotherapy trials: summary from the National Cancer Institute Cancer Imaging Steering Committee workshop.

As the immuno-oncology field continues the rapid growth witnessed over the past decade, optimising patient outcomes requires an evolution in the current response-assessment guidelines for phase 2 and 3 immunotherapy clinical trials and clinical care. Additionally, investigational tools-including image analysis of standard-of-care scans (such as CT, magnetic resonance, and PET) with analytics, such as radiomics, functional magnetic resonance agents, and novel molecular-imaging PET agents-offer promising advancements for assessment of immunotherapy. To document current challenges and opportunities and identify next steps in immunotherapy diagnostic imaging, the National Cancer Institute Clinical Imaging Steering Committee convened a meeting with diverse representation among imaging experts and oncologists to generate a comprehensive review of the state of the field.

Examination of fully automated mammographic density measures using LIBRA and breast cancer risk in a cohort of 21,000 non-Hispanic white women.

BACKGROUND: Breast density is strongly associated with breast cancer risk. Fully automated quantitative density assessment methods have recently been developed that could facilitate large-scale studies, although data on associations with long-term breast cancer risk are limited. We examined LIBRA assessments and breast cancer risk and compared results to prior assessments using Cumulus, an established computer-assisted method requiring manual thresholding. METHODS: We conducted a cohort study among 21,150 non-Hispanic white female participants of the Research Program in Genes, Environment and Health of Kaiser Permanente Northern California who were 40-74 years at enrollment, followed for up to 10 years, and had archived processed screening mammograms acquired on Hologic or General Electric full-field digital mammography (FFDM) machines and prior Cumulus density assessments available for analysis. Dense area (DA), non-dense area (NDA), and percent density (PD) were assessed using LIBRA software. Cox regression was used to estimate hazard ratios (HRs) for breast cancer associated with DA, NDA and PD modeled continuously in standard deviation (SD) increments, adjusting for age, mammogram year, body mass index, parity, first-degree family history of breast cancer, and menopausal hormone use. We also examined differences by machine type and breast view. RESULTS: The adjusted HRs for breast cancer associated with each SD increment of DA, NDA and PD were 1.36 (95% confidence interval, 1.18-1.57), 0.85 (0.77-0.93) and 1.44 (1.26-1.66) for LIBRA and 1.44 (1.33-1.55), 0.81 (0.74-0.89) and 1.54 (1.34-1.77) for Cumulus, respectively. LIBRA results were generally similar by machine type and breast view, although associations were strongest for Hologic machines and mediolateral oblique views. Results were also similar during the first 2 years, 2-5 years and 5-10 years after the baseline mammogram. CONCLUSION: Associations with breast cancer risk were generally similar for LIBRA and Cumulus density measures and were sustained for up to 10 years. These findings support the suitability of fully automated LIBRA assessments on processed FFDM images for large-scale research on breast density and cancer risk.

Looking at breast cancer through the ethnic and racial lens𠄄One size definitely does not fit all.

LAY SUMMARY: Breast cancer cases are elevated in younger women in minority cohorts in the United States. Much of this is due to their younger age distributions, particularly for Hispanic women, but beyond this there are elevated risks in younger Black and Asian women. Disparities increase further for minority women when being diagnosed with more advanced disease or dying of breast cancer before the age of 50 years is considered. Strategies for culturally appropriate education about breast cancer, better access to screening, and prompt treatment must be implemented.

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

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

Reproductive Factors and Mammographic Density: Associations Among 24,840 Women and Comparison of Studies Using Digitized Film-Screen Mammography and Full-Field Digital Mammography.

Breast density is a modifiable factor that is strongly associated with breast cancer risk. We sought to understand the influence of newer technologies of full-field digital mammography (FFDM) on breast density research and to determine whether results are comparable across studies using FFDM and previous studies using traditional film-screen mammography. We studied 24,840 screening-age (40-74 years) non-Hispanic white women who were participants in the Research Program on Genes, Environment and Health of Kaiser Permanente Northern California and underwent screening mammography with either Hologic (Hologic, Inc., Marlborough, Massachusetts) or General Electric (General Electric Company, Boston, Massachusetts) FFDM machines between 2003 and 2013. We estimated the associations of parity, age at first birth, age at menarche, and menopausal status with percent density and dense area as measured by a single radiological technologist using Cumulus software (Canto Software, Inc., San Francisco, California). We found that associations between reproductive factors and mammographic density measured using processed FFDM images were generally similar in magnitude and direction to those from prior studies using film mammography. Estimated associations for both types of FFDM machines were in the same direction. There was some evidence of heterogeneity in the magnitude of the effect sizes by machine type, which we accounted for using random-effects meta-analysis when combining results. Our findings demonstrate the robustness of quantitative mammographic density measurements across FFDM and film mammography platforms.

The origins of breast cancer associated with mammographic density: a testable biological hypothesis.

BACKGROUND: Our purpose is to develop a testable biological hypothesis to explain the known increased risk of breast cancer associated with extensive percent mammographic density (PMD), and to reconcile the apparent paradox that although PMD decreases with increasing age, breast cancer incidence increases. METHODS: We used the Moolgavkar model of carcinogenesis as a framework to examine the known biological properties of the breast tissue components associated with PMD that includes epithelium and stroma, in relation to the development of breast cancer. In this model, normal epithelial cells undergo a mutation to become intermediate cells, which, after further mutation, become malignant cells. A clone of such cells grows to become a tumor. The model also incorporates changes with age in the number of susceptible epithelial cells associated with menarche, parity, and menopause. We used measurements of the radiological properties of breast tissue in 4454 healthy subjects aged from 15 to 80+ years to estimate cumulative exposure to PMD (CBD) in the population, and we examined the association of CBD with the age-incidence curve of breast cancer in the population. RESULTS: Extensive PMD is associated with a greater number of breast epithelial cells, lobules, and fibroblasts, and greater amounts of collagen and extracellular matrix. The known biological properties of these tissue components may, singly or in combination, promote the acquisition of mutations by breast epithelial cells specified by the Moolgavkar model, and the subsequent growth of a clone of malignant cells to form a tumor. We also show that estimated CBD in the population from ages 15 to 80+ years is closely associated with the age-incidence curve of breast cancer in the population. CONCLUSIONS: These findings are consistent with the hypothesis that the biological properties of the breast tissue components associated with PMD increase the probability of the transition of normal epithelium to malignant cells, and that the accumulation of mutations with CBD may influence the age-incidence curve of breast cancer. This hypothesis gives rise to several testable predictions.

Case-control study of mammographic density and breast cancer risk using processed digital mammograms.

BACKGROUND: Full-field digital mammography (FFDM) has largely replaced film-screen mammography in the US. Breast density assessed from film mammograms is strongly associated with breast cancer risk, but data are limited for processed FFDM images used for clinical care. METHODS: We conducted a case-control study nested among non-Hispanic white female participants of the Research Program in Genes, Environment and Health of Kaiser Permanente Northern California who were aged 40 to 74 years and had screening mammograms acquired on Hologic FFDM machines. Cases (n = 297) were women with a first invasive breast cancer diagnosed after a screening FFDM. For each case, up to five controls (n = 1149) were selected, matched on age and year of FFDM and image batch number, and who were still under follow-up and without a history of breast cancer at the age of diagnosis of the matched case. Percent density (PD) and dense area (DA) were assessed by a radiological technologist using Cumulus. Conditional logistic regression was used to estimate odds ratios (ORs) for breast cancer associated with PD and DA, modeled continuously in standard deviation (SD) increments and categorically in quintiles, after adjusting for body mass index, parity, first-degree family history of breast cancer, breast area, and menopausal hormone use. RESULTS: Median intra-reader reproducibility was high with a Pearson's r of 0.956 (range 0.902 to 0.983) for replicate PD measurements across 23 image batches. The overall mean was 20.02 (SD, 14.61) for PD and 27.63 cm(2) (18.22 cm(2)) for DA. The adjusted ORs for breast cancer associated with each SD increment were 1.70 (95 % confidence interval, 1.41-2.04) for PD, and 1.54 (1.34-1.77) for DA. The adjusted ORs for each quintile were: 1.00 (ref.), 1.49 (0.91-2.45), 2.57 (1.54-4.30), 3.22 (1.91-5.43), 4.88 (2.78-8.55) for PD, and 1.00 (ref.), 1.43 (0.85-2.40), 2.53 (1.53-4.19), 2.85 (1.73-4.69), 3.48 (2.14-5.65) for DA. CONCLUSIONS: PD and DA measured using Cumulus on processed FFDM images are positively associated with breast cancer risk, with similar magnitudes of association as previously reported for film-screen mammograms. Processed digital mammograms acquired for routine clinical care in a general practice setting are suitable for breast density and cancer research.

Digital Compared with Screen-Film Mammography: Measures of Diagnostic Accuracy among Women Screened in the Ontario Breast Screening Program.

PURPOSE: To compare measures of diagnostic accuracy between large concurrent cohorts of women screened with digital computed radiography (CR), direct radiography (DR), and screen-film mammography (SFM). MATERIALS AND METHODS: This study was approved by the University of Toronto Research Ethics Board; informed consent was not required. Three concurrent cohorts of women aged 50-74 years who were screened from 2008-2009 in the Ontario Breast Screening Program with SFM (487,334 screening examinations, 403,688 women), DR (254,758 screening examinations, 220,520 women), or CR (74,140 screening examinations, 64,210 women) were followed for 2 years or until breast cancer diagnosis. Breast cancers were classified as screening-detected or interval on the basis of the woman's final screening and assessment results. Interval cancer rate (per 10 000 negative screening examinations), sensitivity, and specificity were compared across the cohorts by using mixed-effects logistic regression analysis. RESULTS: Interval cancer rates were higher, although not significantly so, for CR (15.2 per 10,000; 95% confidence interval [CI]: 12.8, 17.8) and were similar for DR (13.7 per 10,000; 95% CI: 12.4, 15.0) compared with SFM (13.0 per 10,000; 95% CI: 12.1, 13.9). For CR versus SFM, specificity was similar while sensitivity was significantly lower (odds ratio [OR] = 0.62; 95% CI: 0.47, 0.83; P = .001), particularly for invasive cancers detected at a rescreening examination, for women with breast density of less than 75%, for women with no family history, and for postmenopausal women. For DR versus SFM, sensitivity was similar while specificity was lower (OR = 0.92; 95% CI: 0.87, 0.98; P = .01), particularly for rescreening examinations, for women aged 60-74 years, for women with breast density of less than 75%, for women with a family history, and for women who were postmenopausal. CONCLUSION: Given the 38% lower sensitivity of CR imaging systems compared with SFM, programs should assess the continued use of this technology for breast screening.

Whole-mount pathology of breast lumpectomy specimens improves detection of tumour margins and focality.

AIMS: Technical limitations in conventional pathological evaluation of breast lumpectomy specimens may reduce diagnostic accuracy in the assessment of margin and focality. A novel technique based on whole-mount serial sections enhances sampling while preserving specimen conformation and orientation. The aim of this study was to investigate assessment of focality and margin status by the use of whole-mount serial sections versus simulated conventional sections in lumpectomies. METHODS AND RESULTS: Two pathologists interpreted whole-mount serial sections and simulated conventional sections for 58 lumpectomy specimens by reporting the closest margin and focality. Measurements were compared by the use of McNemar's chi-squared test. Statistically significant differences were observed in the assignment of both margin positivity (P = 0.014) and multifocality (P = 0.021). A positive margin or multifocal disease was identified by the use of whole-mount serial sections but missed in the simulated conventional assessment in 10.3% and 17.2% of all cases, respectively. There was no case in which a positive margin was detected only in the simulated conventional assessment. CONCLUSIONS: The whole-mount technique is more sensitive than conventional assessment for identifying a positive margin or multifocal disease in breast lumpectomy specimens. Undersampling in conventional sections was implicated in almost all cases of discordance. The majority of positive margins or secondary foci identified only in whole-mount serial sections concerned in-situ disease.

Digital versus screen-film mammography: impact of mammographic density and hormone therapy on breast cancer detection.

Most studies that have examined the effects of mammographic density and hormone therapy use on breast cancer detection have included screen-film mammography. This study further examines this association in post-menopausal women screened by digital mammography. Approved by the University of Toronto Research Ethics Board, this study identified 688,418 women of age 50-74 years screened with digital or screen-film mammography from 2008 to 2009 within the Ontario Breast Screening Program. Of 2993 eligible women with invasive breast cancer, 2450 were contacted and 1421 participated (847 screen-film mammography, 574 digital direct radiography). Mammographic density was measured by study radiologists using the standard BI-RADS classification system and by a computer-assisted method. Information on hormone therapy use was collected by a telephone-administered questionnaire. Logistic regression and two-tailed tests for significance evaluated associations between factors and detection method by mammography type. Women with >75 % radiologist-measured mammographic density compared to those with <25 % were more likely to be diagnosed with an interval than screen-detected cancer, with the difference being greater for those screened with screen-film (OR = 6.40, 95 % CI 2.30-17.85) than digital mammography (OR = 2.41, 95 % CI 0.67-8.58) and aged 50-64 years screened with screen-film mammography (OR = 10.86, 95 % CI 2.96-39.57). Recent former hormone therapy users were also at an increased risk of having an interval cancer with the association being significant for women screened with digital mammography (OR = 2.08, 95 % CI 1.17-3.71). Breast screening using digital mammography lowers the risk of having an interval cancer for post-menopausal women aged 50-64 with greater mammographic density.

Reliability of automated breast density measurements.

PURPOSE: To estimate the reliability of a reference standard two-dimensional area-based method and three automated volumetric breast density measurements by using repeated measures. MATERIALS AND METHODS: Thirty women undergoing screening mammography consented to undergo a repeated left craniocaudal examination performed by a second technologist in this prospective institutional review board-approved HIPAA-compliant study. Breast density was measured by using an area-based method (Cumulus ABD) and three automated volumetric methods (CumulusV [University of Toronto], Volpara [version 1.4.5; Volpara Solutions, Wellington, New Zealand), and Quantra [version 2.0; Hologic, Danbury, Conn]). Discrepancy between the first and second breast density measurements (Δ1-2) was obtained for each algorithm by subtracting the second measurement from the first. The Δ1-2 values of each algorithm were then analyzed with a random-effects model to derive Bland-Altman-type limits of measurement agreement. RESULTS: Variability was higher for Cumulus ABD and CumulusV than for Volpara or Quantra. The within-breast density measurement standard deviations were 3.32% (95% confidence interval [CI]: 2.65, 4.44), 3.59% (95% CI: 2.86, 4.48), 0.99% (95% CI: 0.79, 1.33), and 1.64% (95% CI: 1.31, 1.39) for Cumulus ABD, CumulusV, Volpara, and Quantra, respectively. Although the mean discrepancy between repeat breast density measurements was not significantly different from zero for any of the algorithms, larger absolute breast density discrepancy (Δ1-2) values were associated with larger breast density values for Cumulus ABD and CumulusV but not for Volpara and Quantra. CONCLUSION: Variability in a repeated measurement of breast density is lowest for Volpara and Quantra; these algorithms may be more suited to incorporation into a risk model.

Modelling mammography screening for breast cancer in the Canadian context: Modification and testing of a microsimulation model.

BACKGROUND: Modelling is a flexible and efficient approach to gaining insight into the trade-offs surrounding a complex process like breast screening, which involves more variables than can be controlled in an experimental study. DATA AND METHODS: The University of Wisconsin Cancer Intervention and Surveillance Modeling Network (CISNET) breast cancer microsimulation model was adapted to simulate breast cancer incidence and screening performance in Canada. The model considered effects of breast density on the sensitivity and specificity of screening. The model's ability to predict age-specific incidence of breast cancer was assessed. RESULTS: Predictions of age-adjusted incidence over calendar years and age-specific incidence of breast cancer in Canadian women are presented. Based on standard screening strategies, ratios of in situ to invasive disease and stage distribution of disease at diagnosis are compared with data from the British Columbia provincial screening program. INTERPRETATION: The adapted model performs well in predicting age-specific incidence and cross-sectional incidence in the absence of screening. The ratios of detection of in situ to invasive cancers and the overall stage distribution of detected cancers are in reasonable agreement with empirical data from British Columbia.

Clinical outcomes of modelling mammography screening strategies.

BACKGROUND: A validated breast cancer model can be used to compare health outcomes associated with different screening strategies. DATA AND METHODS: The University of Wisconsin Cancer Intervention and Surveillance Modeling Network (CISNET) breast cancer microsimulation model was adapted to simulate breast cancer incidence, screening performance and delivery of optimal therapies in Canada. The model considered effects of breast density on incidence and screening performance. Model predictions of incidence, mortality and life-years (LY) gained for a 1960 birth cohort of women for No Screening were compared with 11 digital mammography screening strategies that varied by starting and stopping age and frequency. RESULTS: In the absence of screening, the estimate of LYs lost from breast cancer was 360.1 per 1,000 women, and each woman diagnosed with breast cancer after age 40 who dies of breast cancer would lose an average of 19.1 years. Biennial screening at ages 50 to 74 resulted in 116.3 LYs saved. Annual screening at ages 40 to 49, followed by biennial screening to age 74, resulted in 170.3 LY saved. Screening annually at ages 40 to 74 recovered the most: 214 LY saved. Annual screening at age 40 resulted in 54 LY gained per 1,000 women. More frequent screening was associated with an increased ratio of detection of ductal in situ to invasive cancers, more abnormal recalls and more negative biopsies, but a reduction in the number of women required to be screened per life saved or per LY saved. INTERPRETATION: In general, mortality reduction was found to be associated with the total number of lifetime screens for breast cancer. However, for the same number of screens, more frequent screening after age 50 appeared to have a greater impact than beginning screening earlier. When the number of LYs saved by screening was considered, a greater impact was achieved by screening women in their 40s than by reducing the interval between screens.

Total cost-effectiveness of mammography screening strategies.

BACKGROUND: Breast cancer screening technology and treatment have improved over the past decade. This analysis evaluates the total cost-effectiveness of various breast cancer screening strategies in Canada. DATA AND METHODS: Using the Wisconsin Cancer Intervention and Surveillance Monitoring Network (CISNET) breast cancer simulation model adapted to the Canadian context, costs and quality-adjusted life years (QALY) were evaluated for 11 mammography screening strategies that varied by start/stop age and screening frequency for the general population. Incremental cost-effectiveness ratios are presented, and sensitivity analyses are used to assess the robustness of model conclusions. RESULTS: Incremental cost-effectiveness analysis showed that triennial screening at ages 50 to 69 was the most cost-effective at $94,762 per QALY. Biennial ($97,006 per QALY) and annual ($226,278 per QALY) strategies had higher incremental ratios. INTERPRETATION: The benefits and costs of screening rise with the number of screens per woman. Decisions about screening strategies may be influenced by willingness to pay and the rate of recall for further examination after positive screens.

Mammographic features associated with interval breast cancers in screening programs.

INTRODUCTION: Percent mammographic density (PMD) is associated with an increased risk of interval breast cancer in screening programs, as are younger age, pre-menopausal status, lower body mass index and hormone therapy. These factors are also associated with variations in PMD. We have examined whether these variables influence the relative frequency of interval and screen-detected breast cancer, independently or through their associations with PMD. We also examined the association of tumor size with PMD and dense and non-dense areas in screen-detected and interval breast cancers. METHODS: We used data from three case-control studies nested in screened populations. Interval breast cancer was defined as invasive breast cancer detected within 12 months of a negative mammogram. We used a computer-assisted method of measuring the dense and total areas of breast tissue in the first (baseline) mammogram taken at entry to screening programs and calculated the non-dense area and PMD. We compared these mammographic features, and other risk factors at baseline, in women with screen-detected (n = 718) and interval breast cancer (n = 125). RESULTS: In multi-variable analysis, the baseline characteristics of younger age, greater dense area and smaller non-dense mammographic area were significantly associated with interval breast cancer compared to screen-detected breast cancer. Compared to screen-detected breast cancers, interval cancers had a larger maximum tumor diameter within each mammographic measure. CONCLUSIONS: Age and the dense and non-dense areas in the baseline mammogram were independently associated with interval breast cancers in screening programs. These results suggest that decreased detection of cancers caused by the area of dense tissue, and more rapid growth associated with a smaller non-dense area, may both contribute to risk of interval breast cancer. Tailoring screening to individual mammographic characteristics at baseline may reduce the number of interval cancers.

Methods for assessing and representing mammographic density: an analysis of 4 case-control studies.

To maximize statistical power in studies of mammographic density and breast cancer, it is advantageous to combine data from several studies, but standardization of the density assessment is desirable. Using data from 4 case-control studies, we describe the process of reassessment and the resulting correlation between values, identify predictors of differences in density readings, and evaluate the strength of the association between mammographic density and breast cancer risk using different representations of density values. The pooled analysis included 1,699 cases and 2,422 controls from California (1990-1998), Hawaii (1996-2003), Minnesota (1992-2001), and Japan (1999-2003). In 2010, a single reader reassessed all images for mammographic density using Cumulus software (Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada). The mean difference between original and reassessed percent density values was -0.7% (95% confidence interval: -1.1, -0.3), with a correlation of 0.82 that varied by location (r = 0.80-0.89). Case status, weight status, age, parity, density assessment method, mammogram view, and race/ethnicity were significant determinants of the difference between original and reassessed values; in combination, these factors explained 9.2% of the variation. The associations of mammographic density with breast cancer and the model fits were similar using the original values and the reassessed values but were slightly strengthened when a calibrated value based on 100 reassessed radiographs was used.

Digital compared to screen-film mammography: breast cancer prognostic features in an organized screening program.

Our previous study found cancer detection rates were equivalent for direct radiography compared to screen-film mammography, while rates for computed radiography were significantly lower. This study compares prognostic features of invasive breast cancers by type of mammography. Approved by the University of Toronto Research Ethics Board, this study identified invasive breast cancers diagnosed among concurrent cohorts of women aged 50-74 screened by direct radiography, computed radiography, or screen-film mammography from January 1, 2008 to December 31, 2009. During the study period, 816,232 mammograms were performed on 668,418 women, and 3,323 invasive breast cancers were diagnosed. Of 2,642 eligible women contacted, 2,041 participated (77.3 %). The final sample size for analysis included 1,405 screen-detected and 418 interval cancers (diagnosed within 24 months of a negative screening mammogram). Polytomous logistic regression was performed to evaluate the association between tumour characteristics and type of mammography, and between tumour characteristics and detection method. Odds ratios (OR) and 95 % confidence intervals (CI) were recorded. Cancers detected by computed radiography compared to screen-film mammography were significantly more likely to be lymph node positive (OR 1.94, 95 %CI 1.01-3.73) and have higher stage (II:I, OR 2.14, 95 %CI 1.11-4.13 and III/IV:I, OR 2.97, 95 %CI 1.02-8.59). Compared to screen-film mammography, significantly more cancers detected by direct radiography (OR 1.64, 95 %CI 1.12-2.38) were lymph node positive. Interval cancers had worse prognostic features compared to screen-detected cancers, irrespective of mammography type. Screening with computed radiography may lead to the detection of cancers with a less favourable stage distribution compared to screen-film mammography that may reflect a delayed diagnosis. Screening programs should re-evaluate their use of computed radiography for breast screening.