NCCN Guidelines® Insights: Breast Cancer Screening and Diagnosis, Version 1.2023.

The NCCN Guidelines for Breast Cancer Screening and Diagnosis provide health care providers with a practical, consistent framework for screening and evaluating a spectrum of clinical presentations and breast lesions. The NCCN Breast Cancer Screening and Diagnosis Panel is composed of a multidisciplinary team of experts in the field, including representation from medical oncology, gynecologic oncology, surgical oncology, internal medicine, family practice, preventive medicine, pathology, diagnostic and interventional radiology, as well as patient advocacy. The NCCN Breast Cancer Screening and Diagnosis Panel meets at least annually to review emerging data and comments from reviewers within their institutions to guide updates to existing recommendations. These NCCN Guidelines Insights summarize the panel's decision-making and discussion surrounding the most recent updates to the guideline's screening recommendations.

Photoacoustic dual-scan mammoscope: results from 38 patients.

We have developed a photoacoustics-based imaging system, the dual-scan mammoscope (DSM), that combines optical contrasts with acoustic detection, to obtain the angiographic features in human breast. In this study, we investigated whether the system can differentiate malignant tumor and healthy breast. We have imaged 38 patients with various tumor types and compared results of tumor-bearing breast with healthy breast for each patient. We also compared the photoacoustic and ultrasound imaging results with clinical US. Vascular features in and around the tumor mass were visualized. We found that tumor-bearing breast contained vessels of larger caliber and exhibited stronger variations in the background signals than those in the contralateral healthy breasts. Preliminary data on photoacoustic and ultrasound images also indicate that the technique has potential in differentiating different tumor types. Overall, our results indicate that combining photoacoustic and ultrasound images can improve breast cancer screening.

Dual Scan Mammoscope (DSM)-A New Portable Photoacoustic Breast Imaging System With Scanning in Craniocaudal Plane.

OBJECTIVE: We present a new photoacoustic tomography system that provides visualization of angiographic features in a human breast with mammogram-like images. METHODS: The system images a mildly compressed breast, from both top and bottom, using two 128-element, 2.25 MHz linear transducer arrays and line optical fiber bundles. The mild compression is achieved using plastic films, which is a more comfortable experience for the patient compared to rigid metal plates used in a traditional mammogram. RESULTS: We could image a D cup-sized breast of 7 cm thickness within 1 minute and achieve a spatial resolution of around 1 mm in all directions. CONCLUSION: Our system possesses the benefits of portability, speedy scanning, and patient comfort. The craniocaudal-view images can be easily correlated with existing imaging modalities for data interpretation. SIGNIFICANCE: Early cancer detection plays a critical role in overall cancer survival rate. Our system may address the limitations of mammogram and offer a radiation-free screening technique for patients with dense breasts.

Breast Cancer Screening and Diagnosis, Version 3.2018, NCCN Clinical Practice Guidelines in Oncology.

The NCCN Guidelines for Breast Cancer Screening and Diagnosis have been developed to facilitate clinical decision making. This manuscript discusses the diagnostic evaluation of individuals with suspected breast cancer due to either abnormal imaging and/or physical findings. For breast cancer screening recommendations, please see the full guidelines on NCCN.org.

Breast MRI radiomics: comparison of computer- and human-extracted imaging phenotypes.

BACKGROUND: In this study, we sought to investigate if computer-extracted magnetic resonance imaging (MRI) phenotypes of breast cancer could replicate human-extracted size and Breast Imaging-Reporting and Data System (BI-RADS) imaging phenotypes using MRI data from The Cancer Genome Atlas (TCGA) project of the National Cancer Institute. METHODS: Our retrospective interpretation study involved analysis of Health Insurance Portability and Accountability Act-compliant breast MRI data from The Cancer Imaging Archive, an open-source database from the TCGA project. This study was exempt from institutional review board approval at Memorial Sloan Kettering Cancer Center and the need for informed consent was waived. Ninety-one pre-operative breast MRIs with verified invasive breast cancers were analysed. Three fellowship-trained breast radiologists evaluated the index cancer in each case according to size and the BI-RADS lexicon for shape, margin, and enhancement (human-extracted image phenotypes [HEIP]). Human inter-observer agreement was analysed by the intra-class correlation coefficient (ICC) for size and Krippendorff's α for other measurements. Quantitative MRI radiomics of computerised three-dimensional segmentations of each cancer generated computer-extracted image phenotypes (CEIP). Spearman's rank correlation coefficients were used to compare HEIP and CEIP. RESULTS: Inter-observer agreement for HEIP varied, with the highest agreement seen for size (ICC 0.679) and shape (ICC 0.527). The computer-extracted maximum linear size replicated the human measurement with p < 10-12. CEIP of shape, specifically sphericity and irregularity, replicated HEIP with both p values < 0.001. CEIP did not demonstrate agreement with HEIP of tumour margin or internal enhancement. CONCLUSIONS: Quantitative radiomics of breast cancer may replicate human-extracted tumour size and BI-RADS imaging phenotypes, thus enabling precision medicine.

Using computer-extracted image phenotypes from tumors on breast magnetic resonance imaging to predict breast cancer pathologic stage.

BACKGROUND: The objective of this study was to demonstrate that computer-extracted image phenotypes (CEIPs) of biopsy-proven breast cancer on magnetic resonance imaging (MRI) can accurately predict pathologic stage. METHODS: The authors used a data set of deidentified breast MRIs organized by the National Cancer Institute in The Cancer Imaging Archive. In total, 91 biopsy-proven breast cancers were analyzed from patients who had information available on pathologic stage (stage I, n = 22; stage II, n = 58; stage III, n = 11) and surgically verified lymph node status (negative lymph nodes, n = 46; ≥ 1 positive lymph node, n = 44; no lymph nodes examined, n = 1). Tumors were characterized according to 1) radiologist-measured size and 2) CEIP. Then, models were built that combined 2 CEIPs to predict tumor pathologic stage and lymph node involvement, and the models were evaluated in a leave-1-out, cross-validation analysis with the area under the receiver operating characteristic curve (AUC) as the value of interest. RESULTS: Tumor size was the most powerful predictor of pathologic stage, but CEIPs that captured biologic behavior also emerged as predictive (eg, stage I and II vs stage III demonstrated an AUC of 0.83). No size measure was successful in the prediction of positive lymph nodes, but adding a CEIP that described tumor "homogeneity" significantly improved discrimination (AUC = 0.62; P = .003) compared with chance. CONCLUSIONS: The current results indicate that MRI phenotypes have promise for predicting breast cancer pathologic stage and lymph node status. Cancer 2016;122:748-757. © 2015 American Cancer Society.

Breast cancer center: improving access to patient care.

To improve access for patients to the Breast Cancer Center at Roswell Park Cancer Institute, the Opportunities for Improvement Project team defined 3 goals: reduce the delay to initial appointment, reduce delays in treatment at the Breast Cancer Center, and reduce delays in the start of endocrine therapy. The team developed a set of tools using Lean methodology that helped to address variables contributing to inefficiencies that result in delays. The idea behind these tools was to integrate all the business variables, such as volume, clinical space, physician availability, services offered in the Breast Program, and patient types, to produce a system or schedule that is more predictable. A new schedule for physicians, independent mid-level clinics, a survivorship program, a primary nursing model, and new roles and responsibilities were defined and implemented. Mean scores in a Press Ganey survey for wait-time questions improved by 10 points, and patient complaints decreased by almost 40%. The team concluded that delays in the Breast Program were symptoms of a larger dysfunction in systems. Fixing the problems required a comprehensive approach to review all the variables that resulted in delays.

Full-field digital mammography on LCD versus CRT monitors.

OBJECTIVE: Our purpose was to determine if the display of full-field digital mammograms on a 5-megapixel liquid crystal display (LCD) monitor is at least equivalent to the display of the same on a 5-megapixel cathode ray tube (CRT) monitor. MATERIALS AND METHODS: Five radiologists evaluated normal anatomy and features of 61 abnormalities in 48 full-field digital mammograms. A 9-point Likert scale was used to compare images on two identical soft-copy review workstations, one equipped with two 5-megapixel CRTs and the other with two 5-megapixel LCDs. Outcomes were evaluated using a random-effects analysis of variance model. Means and SEs were reported. Ninety-five percent confidence intervals and p values were calculated. RESULTS: The two systems were equivalent for most features. The LCDs were rated better for the sharpness of mass margins (p = 0.011) and mass conspicuity (p = 0.050). For calcium features, the LCDs were rated better than the CRTs for lesion conspicuity (p = 0.010) and number of calcifications (p = 0.043). For architectural distortions, there was no statistically significant difference between the monitors in any of the features evaluated. For display characteristics, the LCDs were better for luminance (p = 0.021). The CRTs were significantly better for image noise (p = 0.001). In the overall ratings, there was no statistically significant difference between the two displays. CONCLUSION: The 5-megapixel monochrome active-matrix LCD is equivalent to and in some respects better than the 5-megapixel CRT display for full-field digital mammograms over a range of normal and abnormal findings.

Can computer-aided detection with double reading of screening mammograms help decrease the false-negative rate? Initial experience.

PURPOSE: To retrospectively evaluate the role of computer-aided detection (CAD) in reducing the rate of false-negative (FN) findings on screening mammograms considered normal at initial double reading. MATERIALS AND METHODS: At the authors' institution, independent prospective double readings in which the second reader is not blinded to results of the first reading are performed routinely for all mammograms. When cancer is diagnosed, prior mammograms also are reviewed with double reading to determine cancer visibility. Findings are categorized as (a) no evidence of cancer on any prior screening mammogram and patient presents more than 1 year after prior screening, (b) no evidence of cancer on any prior screening mammogram and patient presents with symptoms within 1 year after prior screening (year-interval occult false-negative), or (c) cancer visible. The clinical director separately evaluates each case in the same way. In 2000, 519 histologically proved breast cancers were diagnosed, including 132 for which patients sought a second opinion and FN findings were not tracked. Prior screening mammograms were available in 318 of the other 387 cases. Five radiologists in two reading sessions independently reviewed current and prior mammograms to categorize visible cancers as either threshold or actionable FN findings. Visible cancers deemed actionable by at least three of five readers were analyzed with a commercially available CAD system. FN rates were calculated prior to and after CAD analysis. RESULTS: Twenty-seven occult and 71 visible cancers were found (total FN findings, 98). Three of five readers considered 52 (73%) of 71 visible cancers actionable. The CAD system correctly marked 37 (71%) of these 52 on prior screening mammograms (19 [65%] of 29 masses, seven [88%] of eight microcalcifications, seven [78%] of nine architectural distortions, and four [67%] of six masses with microcalcifications). The FN rate was 98 (31%) of 318 before CAD and 61 (19%) of 318 after CAD. CONCLUSION: In this retrospective review of this small subset of cancers, it appears that CAD has the potential to decrease the FN rate at double reading by more than one-third (from 31% to 19%). The CAD system correctly marked 37 (71%) of 52 actionable findings read as negative in previous screening years.