Assessment of Machine Learning of Breast Pathology Structures for Automated Differentiation of Breast Cancer and High-Risk Proliferative Lesions.

Importance: Following recent US Food and Drug Administration approval, adoption of whole slide imaging in clinical settings may be imminent, and diagnostic accuracy, particularly among challenging breast biopsy specimens, may benefit from computerized diagnostic support tools. Objective: To develop and evaluate computer vision methods to assist pathologists in diagnosing the full spectrum of breast biopsy samples, from benign to invasive cancer. Design, Setting, and Participants: In this diagnostic study, 240 breast biopsies from Breast Cancer Surveillance Consortium registries that varied by breast density, diagnosis, patient age, and biopsy type were selected, reviewed, and categorized by 3 expert pathologists as benign, atypia, ductal carcinoma in situ (DCIS), and invasive cancer. The atypia and DCIS cases were oversampled to increase statistical power. High-resolution digital slide images were obtained, and 2 automated image features (tissue distribution feature and structure feature) were developed and evaluated according to the consensus diagnosis of the expert panel. The performance of the automated image analysis methods was compared with independent interpretations from 87 practicing US pathologists. Data analysis was performed between February 2017 and February 2019. Main Outcomes and Measures: Diagnostic accuracy defined by consensus reference standard of 3 experienced breast pathologists. Results: The accuracy of machine learning tissue distribution features, structure features, and pathologists for classification of invasive cancer vs noninvasive cancer was 0.94, 0.91, and 0.98, respectively; the accuracy of classification of atypia and DCIS vs benign tissue was 0.70, 0.70, and 0.81, respectively; and the accuracy of classification of DCIS vs atypia was 0.83, 0.85, and 0.80, respectively. The sensitivity of both machine learning features was lower than that of the pathologists for the invasive vs noninvasive classification (tissue distribution feature, 0.70; structure feature, 0.49; pathologists, 0.84) but higher for the classification of atypia and DCIS vs benign cases (tissue distribution feature, 0.79; structure feature, 0.85; pathologists, 0.72) and the classification of DCIS vs atypia (tissue distribution feature, 0.88; structure feature, 0.89; pathologists, 0.70). For the DCIS vs atypia classification, the specificity of the machine learning feature classification was similar to that of the pathologists (tissue distribution feature, 0.78; structure feature, 0.80; pathologists, 0.82). Conclusion and Relevance: The computer-based automated approach to interpreting breast pathology showed promise, especially as a diagnostic aid in differentiating DCIS from atypical hyperplasia.

Second opinion strategies in breast pathology: a decision analysis addressing over-treatment, under-treatment, and care costs.

PURPOSE: To estimate the potential near-term population impact of alternative second opinion breast biopsy pathology interpretation strategies. METHODS: Decision analysis examining 12-month outcomes of breast biopsy for nine breast pathology interpretation strategies in the U.S. health system. Diagnoses of 115 practicing pathologists in the Breast Pathology Study were compared to reference-standard-consensus diagnoses with and without second opinions. Interpretation strategies were defined by whether a second opinion was sought universally or selectively (e.g., 2nd opinion if invasive). Main outcomes were the expected proportion of concordant breast biopsy diagnoses, the proportion involving over- or under-interpretation, and cost of care in U.S. dollars within one-year of biopsy. RESULTS: Without a second opinion, 92.2% of biopsies received a concordant diagnosis. Concordance rates increased under all second opinion strategies, and the rate was highest (95.1%) and under-treatment lowest (2.6%) when all biopsies had second opinions. However, over-treatment was lowest when second opinions were sought selectively for initial diagnoses of invasive cancer, DCIS, or atypia (1.8 vs. 4.7% with no 2nd opinions). This strategy also had the lowest projected 12-month care costs ($5.907 billion vs. $6.049 billion with no 2nd opinions). CONCLUSIONS: Second opinion strategies could lower overall care costs while reducing both over- and under-treatment. The most accurate cost-saving strategy required second opinions for initial diagnoses of invasive cancer, DCIS, or atypia.

Comparative effectiveness of incorporating a hypothetical DCIS prognostic marker into breast cancer screening.

PURPOSE: Due to limitations in the ability to identify non-progressive disease, ductal carcinoma in situ (DCIS) is usually managed similarly to localized invasive breast cancer. We used simulation modeling to evaluate the potential impact of a hypothetical test that identifies non-progressive DCIS. METHODS: A discrete-event model simulated a cohort of U.S. women undergoing digital screening mammography. All women diagnosed with DCIS underwent the hypothetical DCIS prognostic test. Women with test results indicating progressive DCIS received standard breast cancer treatment and a decrement to quality of life corresponding to the treatment. If the DCIS test indicated non-progressive DCIS, no treatment was received and women continued routine annual surveillance mammography. A range of test performance characteristics and prevalence of non-progressive disease were simulated. Analysis compared discounted quality-adjusted life years (QALYs) and costs for test scenarios to base-case scenarios without the test. RESULTS: Compared to the base case, a perfect prognostic test resulted in a 40% decrease in treatment costs, from $13,321 to $8005 USD per DCIS case. A perfect test produced 0.04 additional QALYs (16 days) for women diagnosed with DCIS, added to the base case of 5.88 QALYs per DCIS case. The results were sensitive to the performance characteristics of the prognostic test, the proportion of DCIS cases that were non-progressive in the model, and the frequency of mammography screening in the population. CONCLUSION: A prognostic test that identifies non-progressive DCIS would substantially reduce treatment costs but result in only modest improvements in quality of life when averaged over all DCIS cases.

Unifying screening processes within the PROSPR consortium: a conceptual model for breast, cervical, and colorectal cancer screening.

General frameworks of the cancer screening process are available, but none directly compare the process in detail across different organ sites. This limits the ability of medical and public health professionals to develop and evaluate coordinated screening programs that apply resources and population management strategies available for one cancer site to other sites. We present a trans-organ conceptual model that incorporates a single screening episode for breast, cervical, and colorectal cancers into a unified framework based on clinical guidelines and protocols; the model concepts could be expanded to other organ sites. The model covers four types of care in the screening process: risk assessment, detection, diagnosis, and treatment. Interfaces between different provider teams (eg, primary care and specialty care), including communication and transfer of responsibility, may occur when transitioning between types of care. Our model highlights across each organ site similarities and differences in steps, interfaces, and transitions in the screening process and documents the conclusion of a screening episode. This model was developed within the National Cancer Institute-funded consortium Population-based Research Optimizing Screening through Personalized Regimens (PROSPR). PROSPR aims to optimize the screening process for breast, cervical, and colorectal cancer and includes seven research centers and a statistical coordinating center. Given current health care reform initiatives in the United States, this conceptual model can facilitate the development of comprehensive quality metrics for cancer screening and promote trans-organ comparative cancer screening research. PROSPR findings will support the design of interventions that improve screening outcomes across multiple cancer sites.

Second opinion in breast pathology: policy, practice and perception.

AIMS: To assess the laboratory policies, pathologists' clinical practice and perceptions about the value of second opinions for breast pathology cases among pathologists practising in the USA. METHODS: Cross-sectional data were collected from 252 pathologists who interpret breast specimens in eight states using a web-based survey. Descriptive statistics were used to characterise findings. RESULTS: Most participants had >10 years of experience interpreting breast specimens (64%), were not affiliated with academic centres (73%) and were not considered experts by their peers (79%). Laboratory policies mandating second opinions varied by diagnosis: invasive cancer 65%; ductal carcinoma in situ (DCIS) 56%; atypical ductal hyperplasia 36% and other benign cases 33%. 81% obtained second opinions in the absence of policies. Participants believed they improve diagnostic accuracy (96%) and protect from malpractice suits (83%), and were easy to obtain, did not take too much time and did not make them look less adequate. The most common (60%) approach to resolving differences between the first and second opinion is to ask for a third opinion, followed by reaching a consensus. CONCLUSIONS: Laboratory-based second opinion policies vary for breast pathology but are most common for invasive cancer and DCIS cases. Pathologists have favourable attitudes towards second opinions, adhere to policies and obtain them even when policies are absent. Those without a formal policy may benefit from supportive clinical practices and systems that help obtain second opinions.

Strategies for expanding colorectal cancer screening at community health centers.

Community health centers are uniquely positioned to address disparities in colorectal cancer (CRC) screening as they have addressed other disparities. In 2012, the federal Health Resources and Services Administration, which is the funding agency for the health center program, added a requirement that health centers report CRC screening rates as a standard performance measure. These annually reported, publically available data are a major strategic opportunity to improve screening rates for CRC. The Patient Protection and Affordable Care Act enacted provisions to expand the capacity of the federal health center program. The recent report of the Institute of Medicine on integrating public health and primary care included an entire section devoted to CRC screening as a target for joint work. These developments make this the ideal time to integrate lifesaving CRC screening into the preventive care already offered by health centers. This article offers 5 strategies that address the challenges health centers face in increasing CRC screening rates. The first 2 strategies focus on improving the processes of primary care. The third emphasizes working productively with other medical providers and institutions. The fourth strategy is about aligning leadership. The final strategy is focused on using tools that have been derived from models that work.

Pathological and molecular assessment of sentinel lymph nodes in solid tumors.

Sentinel nodes (SNs) are the first set of nodes to receive drainage and cancer cells from a primary tumor. While there may be a single SN, frequently there are one to three or more SNs. The development of sentinel node surgery over the last decade has led to dramatic changes in the surgical approach to regional nodes draining solid tumors. The surgeon can now identify, to a level of accuracy previously impossible, the regional nodes most likely to be involved with cancer in any individual patient. This new capability comes at a cost; the principles guiding the extent of nodal surgery must be completely re-examined. The extent of surgical resection required to achieve each of the goals of regional node surgery-(1) establishing prognosis, (2) obtaining regional control, and (3) improving overall survival-may no longer be simply the default "regional node resection" and may vary depending on the clinical goals. Inseparable from this new surgical technology is the methodology employed for pathologic evaluation of SNs. It is critical that pathologists and clinicians conduct definitive clinical research directed toward defining the role and impact that SN surgery has on each of these surgical goals.