Multimodality Imaging Review of HER2-positive Breast Cancer and Response to Neoadjuvant Chemotherapy.

Human epidermal growth factor receptor 2 (HER2/neu or ErbB2)-positive breast cancers comprise 15%-20% of all breast cancers. The most common manifestation of HER2-positive breast cancer at mammography or US is an irregular mass with spiculated margins that often contains calcifications; at MRI, HER2-positive breast cancer may appear as a mass or as nonmass enhancement. HER2-positive breast cancers are often of intermediate to high nuclear grade at histopathologic analysis, with increased risk of local recurrence and metastases and poorer overall prognosis. However, treatment with targeted monoclonal antibody therapies such as trastuzumab and pertuzumab provides better local-regional control and leads to improved survival outcome. With neoadjuvant treatments, including monoclonal antibodies, taxanes, and anthracyclines, women are now potentially able to undergo breast conservation therapy and sentinel lymph node biopsy versus mastectomy and axillary lymph node dissection. Thus, the radiologist's role in assessing the extent of local-regional disease and response to neoadjuvant treatment at imaging is important to inform surgical planning and adjuvant treatment. However, assessment of treatment response remains difficult, with the potential for different imaging modalities to result in underestimation or overestimation of disease to varying degrees when compared with surgical pathologic analysis. In particular, the presence of calcifications at mammography is especially difficult to correlate with the results of pathologic analysis after chemotherapy. Breast MRI findings remain the best predictor of pathologic response. The authors review the initial manifestations of HER2-positive tumors, the varied responses to neoadjuvant chemotherapy, and the challenges in assessing residual cancer burden through a multimodality imaging review with pathologic correlation. © RSNA, 2023 Quiz questions for this article are available through the Online Learning Center.

Prioritizing Patient Safety and Minimizing Waste: Institutional Review of Cases and a Proposed Process for Designing a Surgical Pathology Gross-Only Examination Policy.

OBJECTIVES: Gross-only examination policies vary widely across pathology departments. Several studies-particularly a College of American Pathologists' Q-Probes study-have looked at the variations in gross-only policies, and even more studies have addressed the (in)appropriateness of certain specimen types for gross-only examination. Few, if any, studies have tackled the important task of how to revise and safely implement a new gross-only examination protocol, especially in collaboration with clinical colleagues. METHODS: We reviewed the grossing protocols from three anatomic pathology centers to identify common gross-only specimen types. We compiled an inclusive list of any specimen types that appeared on one or more centers' lists. We performed a retrospective review of the gross and microscopic diagnoses for those specimen types to determine if any diagnoses of significance would have been missed had that specimen been processed as a gross-only. RESULTS: We reviewed 940 cases among 13 specimen types. For 7 specimen types, the gross diagnoses provided equivalent information to the microscopic diagnoses. For 6 specimen types, microscopic diagnoses provided clinically meaningful information beyond what was captured in the gross diagnoses. CONCLUSIONS: To improve the value of care provided, pathology departments should conduct internal reviews and consider transitioning specimen types to gross-only when safe.

Mucin Neovascularization as a Diagnostic Aid to Distinguish Mucinous Carcinomas From Mucocele-like Lesions in Breast Core Needle Biopsies.

The distinction between mucinous carcinomas (MCs) and mucocele-like lesions (MLLs), particularly those containing detached epithelial fragments, can be problematic in the limited samples afforded by breast core needle biopsies (CNBs). Neovascularization of mucin has been proposed as a criterion to distinguish MC from MLL, but its value in helping to categorize mucin-producing breast lesions in CNB has not been previously investigated. To address this, we evaluated mucin neovascularization on hematoxylin and eosin (H&E)-stained sections of 140 CNB containing mucin-producing breast lesions including 52 MC, 17 mucin-producing ductal carcinoma in situ (mDCIS), and 71 MLL. In 116 cases with sufficient remaining material (42 MC, 16 mDCIS, and 58 MLL), we also assessed mucin neovascularization on CD31 immunostains. On H&E-stained sections, neovascularization of mucin, defined as delicate, thin-walled microvessels in mucin, and unassociated with fibrous septae, was identified significantly more frequently in MC than in MLL (69.2% vs. 14.1%; P=0.0001). The difference in the frequency of mucin neovascularization between MC and MLL was even greater on CD31 immunostains (97.6% vs. 13.8%, P<0.00001). The sensitivity, specificity, positive predictive value, and negative predictive value of mucin neovascularization for categorizing a lesion as MC were 69.2%, 85.8%, 78.3%, and 79.2%, respectively, for H&E-stained sections and 97.6%, 86.2%, 83.7%, and 98.0%, respectively, for CD31 immunostains. We conclude that mucin neovascularization is significantly more common in MC than in MLL in breast CNB on H&E-stained sections and particularly on CD31 immunostains and may be a valuable adjunct in distinguishing between MC and MLL in problematic cases.

Combined molecular and histologic end points inform cancer risk estimates for thyroid nodules classified as atypia of undetermined significance.

BACKGROUND: Thyroid nodules classified as atypia of uncertain significance (AUS) on fine-needle aspiration cytology are heterogeneous. Prior studies reported a higher risk of noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP)/cancer among AUS nodules that had cytologic (AUS-C) versus architectural (AUS-A) atypia; however, such studies were generally confined to resected cohorts, introducing bias into risk calculations. The authors hypothesized that combined histologic and molecular end points would permit clinically meaningful calculations of NIFTP/malignancy risk among AUS nodules. METHODS: The study consisted of 279 thyroid nodules classified as AUS on initial fine-needle aspiration and tested by the Afirma Gene Expression Classifier (GEC) between June 2013 and October 2017. Results of GEC testing and histopathologic diagnoses were stratified by AUS classifiers. The AUS-A category was further subclassified as 1) hypocellular microfollicular or 2) cellular with mixed but predominantly microfollicular architecture. NIFTP/cancer risk was calculated for each subgroup, with the inclusion of unresected nodules that had benign GEC results as low-risk end points comparable to histologically benign nodules. RESULTS: When only histologic end points were considered, there was no difference in NIFTP/cancer risk (25% vs 23%; P = .82). By using molecular and histologic end points, AUS cases with cytologic atypia trended toward higher NIFTP/cancer risk than AUS-A cases (14% vs 6%; P = .06). Furthermore, AUS-A cases showed a trend toward lower NIFTP/cancer risk for hypocellular microfollicular aspirates (3%) compared with cellular samples that had mixed/predominantly microfollicular architecture (13%; P = .18). CONCLUSIONS: The inclusion of unresected benign GEC nodules in risk-of-malignancy calculations provides more accurate results, which may be helpful for informing patient management as well as quality improvement in the cytopathology laboratory.

Critical values in cytology.

The timely reporting of critical values, or values that may be life-threatening if immediate action is not taken, is essential to patient care and safety. Although some guidelines exist for critical diagnoses in cytology, not all laboratories have a specific list of diagnoses that should be considered critical, and the very existence of cytology "critical values" has been called into question. Here we propose a pragmatic system for determining cytology critical values and report our laboratory's critical value list, formulated based on a review of the medical literature regarding clinical urgency and other institutions' cytology critical value lists.

Automated Quantitative Measures of Terminal Duct Lobular Unit Involution and Breast Cancer Risk.

BACKGROUND: Manual qualitative and quantitative measures of terminal duct lobular unit (TDLU) involution were previously reported to be inversely associated with breast cancer risk. We developed and applied a deep learning method to yield quantitative measures of TDLU involution in normal breast tissue. We assessed the associations of these automated measures with breast cancer risk factors and risk. METHODS: We obtained eight quantitative measures from whole slide images from a benign breast disease (BBD) nested case-control study within the Nurses' Health Studies (287 breast cancer cases and 1,083 controls). Qualitative assessments of TDLU involution were available for 177 cases and 857 controls. The associations between risk factors and quantitative measures among controls were assessed using analysis of covariance adjusting for age. The relationship between each measure and risk was evaluated using unconditional logistic regression, adjusting for the matching factors, BBD subtypes, parity, and menopausal status. Qualitative measures and breast cancer risk were evaluated accounting for matching factors and BBD subtypes. RESULTS: Menopausal status and parity were significantly associated with all eight measures; select TDLU measures were associated with BBD histologic subtype, body mass index, and birth index (P < 0.05). No measure was correlated with body size at ages 5-10 years, age at menarche, age at first birth, or breastfeeding history (P > 0.05). Neither quantitative nor qualitative measures were associated with breast cancer risk. CONCLUSIONS: Among Nurses' Health Studies women diagnosed with BBD, TDLU involution is not a biomarker of subsequent breast cancer. IMPACT: TDLU involution may not impact breast cancer risk as previously thought.

Deep learning assessment of breast terminal duct lobular unit involution: Towards automated prediction of breast cancer risk.

Terminal duct lobular unit (TDLU) involution is the regression of milk-producing structures in the breast. Women with less TDLU involution are more likely to develop breast cancer. A major bottleneck in studying TDLU involution in large cohort studies is the need for labor-intensive manual assessment of TDLUs. We developed a computational pathology solution to automatically capture TDLU involution measures. Whole slide images (WSIs) of benign breast biopsies were obtained from the Nurses' Health Study. A set of 92 WSIs was annotated for acini, TDLUs and adipose tissue to train deep convolutional neural network (CNN) models for detection of acini, and segmentation of TDLUs and adipose tissue. These networks were integrated into a single computational method to capture TDLU involution measures including number of TDLUs per tissue area, median TDLU span and median number of acini per TDLU. We validated our method on 40 additional WSIs by comparing with manually acquired measures. Our CNN models detected acini with an F1 score of 0.73±0.07, and segmented TDLUs and adipose tissue with Dice scores of 0.84±0.13 and 0.87±0.04, respectively. The inter-observer ICC scores for manual assessments on 40 WSIs of number of TDLUs per tissue area, median TDLU span, and median acini count per TDLU were 0.71, 0.81 and 0.73, respectively. Intra-observer reliability was evaluated on 10/40 WSIs with ICC scores of >0.8. Inter-observer ICC scores between automated results and the mean of the two observers were: 0.80 for number of TDLUs per tissue area, 0.57 for median TDLU span, and 0.80 for median acini count per TDLU. TDLU involution measures evaluated by manual and automated assessment were inversely associated with age and menopausal status. We developed a computational pathology method to measure TDLU involution. This technology eliminates the labor-intensiveness and subjectivity of manual TDLU assessment, and can be applied to future breast cancer risk studies.

Preoperative bronchial cytology for the assessment of tumor spread through air spaces in lung adenocarcinoma resection specimens.

BACKGROUND: Tumor spread through air spaces (STAS), a significant prognostic indicator, has been described recently as a pattern of invasion in pulmonary carcinomas. However, questions remain regarding preoperative identification of STAS and whether it represents an in vivo phenomenon versus an ex vivo artifact. METHODS: We retrospectively reviewed 67 paired preoperative bronchoalveolar lavage (BAL) or bronchial washing (BW) cytology specimens with the subsequent lung adenocarcinoma surgical resection specimen to determine whether preoperative cytology could predict STAS. Other clinical, radiologic, and pathologic features of the resected lesions were also correlated with preoperative bronchial cytology results. RESULTS: Positive bronchial cytology was observed in 28 cases (41.8%), 24 of which had STAS (85.7%); however, negative BAL/BW cytology was observed in 39 cases (58.2%), 29 of which had STAS (74.4%) (x2  = 1.27, P = .26, not significant). High-STAS burden was observed in 44 cases (83.0%), 21 (47.7%) with negative BAL/BW and 23 (52.3%) with positive BAL/BW. Low-STAS burden was observed in 9 cases (17.0%), 8 (88.9%) with negative BAL/BW and only 1 (11.1%) with positive BAL/BW (x2  = 5.11, P = .024, significant). For tumors with STAS, a statistically significant difference was identified in the maximal STAS distance from the main tumor edge between BAL/BW-positive and BAL/BW-negative groups (P = .007). Of the remaining clinicopathologic and radiologic features, only visceral pleural invasion was significantly associated with BAL/BW positivity. CONCLUSION: Presurgical bronchial cytology alone cannot adequately predict tumor STAS; however, it may provide useful information regarding the extent and overall burden of STAS on the subsequent resection specimen.