Review of the national external quality assessment (EQA) scheme for breast pathology in the UK

Development and Validation of a HER2-Low Focused Immunohistochemical Scoring System With High-Interobserver Concordance: The Australian HER2-Low Breast Cancer Concordance Study

The DESTINY Breast-04 trial revealed survival advantages of trastuzumab deruxtecan for women with metastatic HER2-low breast cancer (1+ or 2+ immunohistochemistry [IHC], without amplification). Although this trial applied the 2018 Americal Society of Clinial Oncology (ASCO)/College of American Pathologists (CAP) HER2 IHC scoring criteria, the subjectivity and imprecision in IHC scoring have raised concerns that patients' treatment may be misaligned. Our group of 9 experienced breast pathologists collated a deidentified set of 60 breast cancer core biopsies from 3 laboratories, evaluated with the Ventana 4B5 HER2 assay and mostly scored locally as HER2 0 or 1+. Based on ASCO/CAP 2018 criteria and our extensive experience of reporting HER2 IHC, we specified scoring conventions for cancers with low levels of HER2 protein expression, articulating specific scoring pitfalls. Each pathologist then reviewed digitized whole slide images of the IHC slides and scored the HER2 expression for each case. At a subsequent consensus workshop, we reviewed the cases jointly to establish consensus scores for each case and determine the percentage of HER2 expressing tumor cells. Consensus was reached on all cases, with 40 classified as 1+ and 3 as 2+ (not amplified), totaling 43 (71.7%) HER2-low cancers. The remaining cases were HER2 0. In 93.3% of cases (56/60), the consensus score matched with the majority opinion of pathologists' independent scores. Seven (41.2%) of the 17 cases reported locally as HER2 0 were classified as HER2 low. Conversely, among 32 cases with local scores of 1+, 7 (21.8%) were reclassified as ultralow or null. Individual pathologists' accuracy in matching the consensus scores ranged from 73.3% to 91.67% (mean, 80.74%). Among HER2-low cancers those in which <20% of the tumor cells expressed HER2 had the lowest concordance levels. Observers Cohen's κ coefficients for concordance were excellent for 4, good in 1, and moderate in the 4 observers. This reference set of cases with expert consensus HER2 scores will be invaluable for peer training and development of our national external quality assurance program for HER2-low cancers. For assessing breast cancers at the low end of HER2 protein expression, our targeted scoring criteria and explicit instruction on pitfalls improved pathologists' accuracy and concordance.

Changes in breast cancer grade from biopsy to excision following surgery or primary chemotherapy

Objective

To compare histological grade (G) of breast cancer and its components (scores for tubule formation - T, nuclear pleomorphism - P and mitotic counts - M) in core needle biopsies (CNBs) and surgical excision specimens (EXC) in patients treated with primary surgery (CHIR) or primary chemotherapy (PST).

Methods

Grade of matched pairs of carcinomas in CNB and EXC was assessed according to the Nottingham grading system.

Results

PST cases tended to have higher pretreatment G. Concordance rates in the CHIR (n = 760) and PST (n = 148) groups for T, P, M and G were 79%, 70%, 75%, 71% and 77%, 70%, 50%, 62%, respectively; differences in concordance rates were significant in M (p < 0.0001) and G (p = 0.024). For discordant cases in the CHIR group, CNBs tended to overestimate T and underestimate P, M and G, whereas in the PST group, the same trends were identified for T and P, but there was a significant tendency for M and G to be lower in EXC specimens.

Conclusions

The reversal of M and G underestimation in CNB to "overestimation" in the PST group can only be explained with the effect of mitosis reduction following chemotherapy. Whether the posttreatment decrease in G reflects any prognostic value remains to be elucidated.

Proficiency testing of diagnosis in histopathology and immunohistochemistry of breast pathology in China: results from a pilot work of National Single Disease Quality Control Program for breast cancer

AIM

Pathologists are currently supposed to be aware of both domestic and international guidelines for breast cancer diagnosis, but it is unclear how successfully these guidelines have been integrated into routine clinical practice in China. Thus, this national proficiency testing (PT) scheme for breast pathology was set up to conduct a baseline assessment of the diagnostic capability of pathologists in China.

METHODS

This national PT plan is designed and implemented according to the "Conformity assessment-General requirements for proficiency testing" (GB/T27043-2012/ISO/IEC 17043:2010). Five cases of breast cancer with six key items, including histologic type, grade, ER, PR, HER2, and Ki67, were selected for testing among 96 participants. The final PT results were published on the website of the National Quality Control Center for Cancer ( http://117.133.40.88:3927/cn/col22/362 ).

RESULTS

Our study demonstrated that the median PT score was 89.5 (54-100). Two institutions with scores < 67 were deemed unacceptable. The accuracy of histologic type, ER, PR, HER2, and Ki67 was satisfactory (all > 86%). However, the histologic grade showed low accuracy (74.0%). The unacceptable results mainly included incorrect evaluation of histologic grade (36.7%), inaccurate evaluation of ER/PR/HER2/Ki67 (28.2%), incorrect identification of C-AD as IBC-NST (15.7%), inappropriate use of 1+/2+/3+ rather than staining percentage for ER/PR (6.1%), misclassification of ER/PR < 1% weak expression as positive staining (1.4%), and no evaluation of histologic grade in ILC, MC, and IMC (5.8%).

CONCLUSIONS

our nationwide PT program exhibited a satisfactory baseline assessment of the diagnostic capability of pathologists in China. More importantly, we identify some areas for further improvement.

Second opinion (external specialist referral) practice of breast pathology: the Nottingham experience

AIMS

Breast pathology is a challenging field, and discrepancies in diagnoses exist and can affect patient management. This study aims to review a breast referral practice and assess the pattern and frequency of breast lesions sent for an external expert review and evaluate potential impacts on patients' care.

METHODS AND RESULTS

Seven hundred and forty cases that were referred to Nottingham City Hospital for a second opinion between 2019 and 2022 which have slides and reports were retrieved and reviewed. Reasons for referral, initial diagnosis, proffered specialist opinion and any discrepancy or potential impacts of management were assessed. The most frequent entities were papillary lesions (19%), fibroepithelial lesions (17%), invasive carcinomas that were sent for confirmation of the invasive diagnosis or subtyping of the invasive tumour (17%), intraductal epithelial proliferation with atypia (9%) and spindle cell lesions (8%). Other entities included biphasic tumours such as adenomyoepithelioma, as well as vascular and nipple lesions. Few cases were sent for prognostic classification or comments on the management, and in occasional cases no initial diagnosis was offered. After reviewing the cases by the expert pathologists, the initial diagnosis was confirmed or one of the suggested diagnoses was preferred in 79% of cases, including 129 cases (17%) in which the opinion resulted minor changes in the management. Significant changes in the classification of lesions were made in 132 cases (18%) which resulted in significant change in the patient management recommendation. In 14 cases (2%) a final classification was not possible, and further specialist opinion was obtained. Comments on the differential diagnosis and advice on further patient management were provided in most cases.

CONCLUSIONS

This study demonstrates the value of external referral of challenging, rare and difficult to classify breast lesions. It also highlights the most common breast lesions that are likely to be challenging, and specialist opinion can refine their classification to improve patient care.

Improving mitotic cell counting accuracy and efficiency using phosphohistone-H3 (PHH3) antibody counterstained with haematoxylin and eosin as part of breast cancer grading

BACKGROUND

Mitotic count in breast cancer is an important prognostic marker. Unfortunately, substantial inter- and intraobserver variation exists when pathologists manually count mitotic figures. To alleviate this problem, we developed a new technique incorporating both haematoxylin and eosin (H&E) and phosphorylated histone H3 (PHH3), a marker highly specific to mitotic figures, and compared it to visual scoring of mitotic figures using H&E only.

METHODS

Two full-face sections from 97 cases were cut, one stained with H&E only, and the other was stained with PHH3 and counterstained with H&E (PHH3-H&E). Counting mitoses using PHH3-H&E was compared to traditional mitoses scoring using H&E in terms of reproducibility, scoring time, and the ability to detect mitosis hotspots. We assessed the agreement between manual and image analysis-assisted scoring of mitotic figures using H&E and PHH3-H&E-stained cells. The diagnostic performance of PHH3 in detecting mitotic figures in terms of sensitivity and specificity was measured. Finally, PHH3 replaced the mitosis score in a multivariate analysis to assess its significance.

RESULTS

Pathologists detected significantly higher mitotic figures using the PHH3-H&E (median ± SD, 20 ± 33) compared with H&E alone (median ± SD, 16 ± 25), P < 0.001. The concordance between pathologists in identifying mitotic figures was highest when using the dual PHH3-H&E technique; in addition, it highlighted mitotic figures at low power, allowing better agreement on choosing the hotspot area (k = 0.842) in comparison with standard H&E (k = 0.625). A better agreement between image analysis-assisted software and the human eye was observed for PHH3-stained mitotic figures. When the mitosis score was replaced with PHH3 in a Cox regression model with other grade components, PHH3 was an independent predictor of survival (hazard ratio [HR] 5.66, 95% confidence interval [CI] 1.92-16.69; P = 0.002), and even showed a more significant association with breast cancer-specific survival (BCSS) than mitosis (HR 3.63, 95% CI 1.49-8.86; P = 0.005) and Ki67 (P = 0.27).

CONCLUSION

Using PHH3-H&E-stained slides can reliably be used in routine scoring of mitotic figures and integrating both techniques will compensate for each other's limitations and improve diagnostic accuracy, quality, and precision.

An update on the pathological classification of breast cancer

Breast cancer (BC) is a heterogeneous disease, encompassing a diverse spectrum of tumours with varying morphological, biological, and clinical phenotypes. Although tumours may show phenotypic overlap, they often display different biological behaviour and response to therapy. Advances in high-throughput molecular techniques and bioinformatics have contributed to improved understanding of BC biology and refinement of molecular taxonomy with the identification of specific molecular subclasses. Although the traditional pathological morphological classification of BC is of paramount importance and provides diagnostic and prognostic information, current interest focusses on the use of a single gene and multigene assays to stratify BC into distinct groups to guide decisions on systemic therapy. This review considers approaches to the classification of BC, including their limitations, and with particular emphasis on the fundamental role of morphology in establishing an accurate diagnosis of primary invasive carcinoma of breast origin. This forms the basis for further morphological characterization and for all other approaches to BC classification that are used to provide prognostic and therapeutic predictive information.

Defining the area of mitoses counting in invasive breast cancer using whole slide image

Although counting mitoses is part of breast cancer grading, concordance studies showed low agreement. Refining the criteria for mitotic counting can improve concordance, particularly when using whole slide images (WSIs). This study aims to refine the methodology for optimal mitoses counting on WSI. Digital images of 595 hematoxylin and eosin stained sections were evaluated. Several morphological criteria were investigated and applied to define mitotic hotspots. Reproducibility, representativeness, time, and association with outcome were the criteria used to evaluate the best area size for mitoses counting. Three approaches for scoring mitoses on WSIs (single and multiple annotated rectangles and multiple digital high-power (×40) screen fields (HPSFs)) were evaluated. The relative increase in tumor cell density was the most significant and easiest parameter for identifying hotspots. Counting mitoses in 3 mm² area was the most representative regarding saturation and concordance levels. Counting in area <2 mm² resulted in a significant reduction in mitotic count (P = 0.02), whereas counting in area ≥4 mm² was time-consuming and did not add a significant rise in overall mitotic count (P = 0.08). Using multiple HPSF, following calibration, provided the most reliable, timesaving, and practical method for mitoses counting on WSI. This study provides evidence-based methodology for defining the area and methodology of visual mitoses counting using WSI. Visual mitoses scoring on WSI can be performed reliably by adjusting the number of monitor screens.

Atypia in breast pathology: what pathologists need to know

Despite the importance of atypia in diagnosing and classifying breast lesions, the definition of atypia varies depending on the context, with a lack of consistent and objective criteria for assessment. Atypia in breast pathology may be cytonuclear and/or architectural with different applications and implications. Cytonuclear atypia is used to assist the distinction of various intraductal epithelial proliferative lesions including usual ductal hyperplasia (UDH) versus atypical ductal hyperplasia (ADH) or ductal carcinoma in situ (DCIS), and to grade DCIS. In invasive carcinoma, nuclear atypia (i.e., nuclear pleomorphism) is a component of the histological grading system. Stromal cell cytonuclear atypia is one of the key features used to distinguish fibroadenoma from phyllodes tumour (PT) and to classify PT as benign, borderline or malignant. Similarly, cytonuclear atypia is used in the evaluation of myoepithelial cell alterations in the breast. Architectural atypia is used to differentiate flat epithelial atypia (FEA) from ADH or DCIS. In addition to the inherent subjectivity in the interpretation of atypia, which presents as a morphological continuum reflecting a biological spectrum, the lack of standardisation in defining atypia augments diagnostic discordance in breast pathology, with potential implications for patient management. Evidence to date suggests that the traditional criteria used to assess atypia may require modification in the era of digital pathology primary diagnosis. This review aims to provide a comprehensive review of atypia in breast pathology with reference to inconsistencies, challenges and limitations.

A pre-operative prognostic model predicting all cause and cause specific mortality for women presenting with invasive breast cancer

PURPOSE

The aim of this study is to develop a pre-operative prognostic model based on known pre-operative factors.

METHODS

A database of ultrasound (US) lesions undergoing biopsy documented US lesion size, stiffness, and patient source prospectively. Women with invasive cancer presenting between 2010 and 2015 were the study group. Breast and axillary core results and ER, PR and HER receptor status were collected prospectively. Assessment of US skin thickening, US distal enhancement and presence of chronic kidney disease (CKD) was performed retrospectively. Patient survival and cause of death were ascertained from computer records. Predictive models for (i) all-cause mortality (ACM) and (ii) breast cancer death (BCD) were built and then validated using bootstrap k-fold cross-validation. A comparison of predictive performance was made between a full cause-specific Cox model, a sub cause-specific Cox model, and a full Fine-Gray sub-distribution hazard model.

RESULTS

1136 patients were included in the study. The median follow-up time was 6.2 years. 125 (11%) women died from breast cancer and 155 (14%) died from other causes. For the prediction of BCD, the cause-specific Cox sub-model performed the best. The time dependent AUC begins above 0.91 in year one to 3 reducing to 0.83 in year 6. The factors included in the Cox sub model were tumour size, skin thickening, source of detection, tumour grade, ER status, pre-operative nodal metastasis and CKD.

CONCLUSION

We have shown that a model based on preoperative factors can predict BCD. Such prediction if externally validated and incorporating treatment data could be useful for treatment planning and patient counselling.

Nuclear morphology in breast lesions: refining its assessment to improve diagnostic concordance

BACKGROUND

Although evaluation of nuclear morphology plays a crucial role in the diagnosis and categorisation of breast lesions, the criteria used to assess nuclear atypia rely on the subjective evaluation of several features that may result in inter- and intra-observer variation. This study aims to refine the definitions of cytonuclear features in various breast lesions.

METHODS

ImageJ was used to assess the nuclear morphological features including nuclear diameter, axis length, perimeter, area, circularity, and roundness in 160 breast lesions comprising ductal carcinoma in situ (DCIS), invasive breast carcinoma of no special type (IBC-NST), tubular carcinoma, usual ductal hyperplasia (UDH), columnar cell change (CCC) and flat epithelial atypia (FEA). Reference cells included normal epithelial cells, red blood cells (RBCs) and lymphocytes.

RESULTS

Reference cells showed size differences not only between normal epithelial cells and RBCs but also between RBCs in varied-sized blood vessels. Nottingham grade nuclear pleomorphism scores 1 and 3 cut-offs in IBC, compared to normal epithelial cells, were <1.2x and >1.4x that of mean maximum Feret's diameter and <1.6x and >2.4x that of mean nuclear area, respectively. Nuclear morphometrics were significantly different in low-grade IBC-NST vs. tubular carcinoma, low-grade DCIS vs. UDH, and in CCC vs. FEA. No differences in the nuclear features between grade matched DCIS and IBC were identified.

CONCLUSION

This study provides a guide for the assessment of nuclear atypia in breast lesions, refines the comparison with reference cells and highlights the potential diagnostic value of image analysis tools in the era of digital pathology.

Assessment of mitotic activity in breast cancer: revisited in the digital pathology era

The assessment of cell proliferation is a key morphological feature for diagnosing various pathological lesions and predicting their clinical behaviour. Visual assessment of mitotic figures in routine histological sections remains the gold-standard method to evaluate the proliferative activity and grading of cancer. Despite the apparent simplicity of such a well-established method, visual assessment of mitotic figures in breast cancer (BC) remains a challenging task with low concordance among pathologists which can lead to under or overestimation of tumour grade and hence affects management. Guideline recommendations for counting mitoses in BC have been published to standardise methodology and improve concordance; however, the results remain less satisfactory. Alternative approaches such as the use of the proliferation marker Ki67 have been recommended but these did not show better performance in terms of concordance or prognostic stratification. The advent of whole slide image technology has brought the issue of mitotic counting in BC into the light again with more challenges to develop objective criteria for identifying and scoring mitotic figures in digitalised images. Using reliable and reproducible morphological criteria can provide the highest degree of concordance among pathologists and could even benefit the further application of artificial intelligence (AI) in breast pathology, and this relies mainly on the explicit description of these figures. In this review, we highlight the morphology of mitotic figures and their mimickers, address the current caveats in counting mitoses in breast pathology and describe how to strictly apply the morphological criteria for accurate and reliable histological grade and AI models.

Intra-Tumour Heterogeneity Is One of the Main Sources of Inter-Observer Variation in Scoring Stromal Tumour Infiltrating Lymphocytes in Triple Negative Breast Cancer

Stromal tumour infiltrating lymphocytes (sTILs) are a strong prognostic marker in triple negative breast cancer (TNBC). Consistency scoring sTILs is good and was excellent when an internet-based scoring aid developed by the TIL-WG was used to score cases in a reproducibility study. This study aimed to evaluate the reproducibility of sTILs assessment using this scoring aid in cases from routine practice and to explore the potential of the tool to overcome variability in scoring. Twenty-three breast pathologists scored sTILs in digitized slides of 49 TNBC biopsies using the scoring aid. Subsequently, fields of view (FOV) from each case were selected by one pathologist and scored by the group using the tool. Inter-observer agreement was good for absolute sTILs (ICC 0.634, 95% CI 0.539-0.735, p < 0.001) but was poor to fair using binary cutpoints. sTILs heterogeneity was the main contributor to disagreement. When pathologists scored the same FOV from each case, inter-observer agreement was excellent for absolute sTILs (ICC 0.798, 95% CI 0.727-0.864, p < 0.001) and good for the 20% (ICC 0.657, 95% CI 0.561-0.756, p < 0.001) and 40% (ICC 0.644, 95% CI 0.546-0.745, p < 0.001) cutpoints. However, there was a wide range of scores for many cases. Reproducibility scoring sTILs is good when the scoring aid is used. Heterogeneity is the main contributor to variance and will need to be overcome for analytic validity to be achieved.

Low-risk DCIS. What is it? Observe or excise?

The issue of overdiagnosis and overtreatment of lesions detected by breast screening mammography has been debated in both international media and the scientific literature. A proportion of cancers detected by breast screening would never have presented symptomatically or caused harm during the patient's lifetime. The most likely (but not the only) entity which may represent those overdiagnosed and overtreated is low-grade ductal carcinoma in situ (DCIS). In this article, we address what is understood regarding the natural history of DCIS and the diagnosis and prognosis of low-grade DCIS. However, low cytonuclear grade disease may not be the totality of DCIS that can be considered of low clinical risk and we outline the issues regarding active surveillance vs excision of low-risk DCIS and the clinical trials exploring this approach.

Chronological Trends of Breast Ductal Carcinoma In Situ: Clinical, Radiologic, and Pathologic Perspectives

BACKGROUND

Because no prior studies have evaluated the chronological trends of ductal carcinoma in situ (DCIS) despite the increasing number of surgeries performed for DCIS, this study analyzed how the clinical, radiologic, and pathologic characteristics of DCIS changed during a 10-year period.

METHODS

Of 7123 patients who underwent primary breast cancer surgery at a single institution from 2006 to 2015, 792 patients with pure DCIS were included in this study. The chronological trends of age, symptoms, method for detecting either mammography or ultrasonography, tumor size, nuclear grade, comedonecrosis, and molecular markers were calculated using Poisson regression for all patients and asymptomatic patients.

RESULTS

During 10 years, DCIS surgery rates significantly increased (p < 0.001). Despite the high percentage of DCIS detected on mammography, the detection rate for DCIS by mammography significantly decreased (97.3% in 2006 to 67.6% in 2015; p = 0.025), whereas the detection rate by ultrasound significantly increased (2.7% to 31.0%; p < 0.001). Conservation surgery rates (odds ratio [OR], 1.058), low-to-intermediate nuclear grade rates (OR, 1.069), and the absence of comedonecrosis (OR, 1.104) significantly increased over time (all p < 0.05). Estrogen receptor (ER) negativity (OR, 0.935) and human epidermal growth factor receptor 2 (HER2) positivity rates (OR, 0.953) significantly decreased (all p < 0.05). The same trends were observed for the 613 asymptomatic patients.

CONCLUSION

The rate of DCIS detected on ultrasound only significantly increased during 10 years. Low-to-intermediate nuclear grade rates significantly increased, whereas ER negativity and HER2 positivity rates significantly decreased during the same period. These findings suggest that DCIS detected on screening ultrasound is less aggressive than DCIS detected on mammography.

Artificial intelligence grading of breast cancer: a promising method to refine prognostic classification for management precision

AIM

Artificial intelligence (AI)-based breast cancer grading may help to overcome perceived limitations of human assessment. Here, the potential value of AI grade was evaluated at the molecular level and in predicting patient outcome.

METHODS AND RESULTS

A supervised convolutional neural network (CNN) model was trained on images of 612 breast cancers from The Cancer Genome Atlas (TCGA). The test set, obtained from the Cooperative Human Tissue Network (CHTN), comprised 1058 cancers with corresponding survival data. Upon reversal, a CNN was trained from images of 1537 CHTN cancers and tested on 397 TCGA cancers. In TCGA, mRNA models were trained using AI grade and Nottingham grade (NG) as labels. Performance of mRNA models in predicting patient outcome was evaluated using data from 1807 cancers from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort. In selecting images for training, nucleolar prominence determined high- versus low-grade cancer cells. In CHTN, NG corresponded to significant survival stratification in stages 1, 2 and 3 cancers, while AI grade showed significance in stages 1 and 2 and borderline in stage 3 tumours. In METABRIC, the mRNA model trained from AI grade was not significantly different to the NG-based model. The gene which best described AI grade was TRIP13, a gene involved with mitotic spindle assembly.

CONCLUSION

An AI grade trained from the morphologically distinctive feature of nucleolar prominence could transmit significant patient outcome information across three independent patient cohorts. AI grade shows promise in gene discovery and for second opinions.

Variability in grading of ductal carcinoma in situ among an international group of pathologists

The prognostic value of cytonuclear grade in ductal carcinoma in situ (DCIS) is debated, partly due to high interobserver variability and the use of multiple guidelines. The aim of this study was to evaluate interobserver agreement in grading DCIS between Dutch, British, and American pathologists. Haematoxylin and eosin-stained slides of 425 women with primary DCIS were independently reviewed by nine breast pathologists based in the Netherlands, the UK, and the USA. Chance-corrected kappa (κma ) for association between pathologists was calculated based on a generalised linear mixed model using the ordinal package in R. Overall κma for grade of DCIS (low, intermediate, or high) was estimated to be 0.50 (95% confidence interval [CI] 0.44-0.56), indicating a moderate association between pathologists. When the model was adjusted for national guidelines, the association for grade did not change (κma = 0.53; 95% CI 0.48-0.57); subgroup analysis for pathologists using the UK pathology guidelines only had significantly higher association (κma = 0.58; 95% CI 0.56-0.61). To assess if concordance of grading relates to the expression of the oestrogen receptor (ER) and HER2, archived immunohistochemistry was analysed on a subgroup (n = 106). This showed that non-high grade according to the majority opinion was associated with ER positivity and HER2 negativity (100 and 89% of non-high grade cases, respectively). In conclusion, DCIS grade showed only moderate association using whole slide images scored by nine breast pathologists. As therapeutic decisions and inclusion in ongoing clinical trials are guided by DCIS grade, there is a pressing need to reduce interobserver variability in grading. ER and HER2 might be supportive to prevent the accidental and unwanted inclusion of high-grade DCIS in such trials.

Clinicopathologic features of unexpectedly HER2 positive breast carcinomas: An institutional experience

Human epidermal growth factor receptor 2 (HER2) overexpression occurs in 15-20 % of all breast carcinomas. These tumors are usually high-grade which often correlates with reduced overall survival and increased rates of recurrence. In a retrospective review, we identified 19 cases of unexpectedly HER2 positive (by immunohistochemistry and/or fluorescence in-situ hybridization) invasive breast carcinomas on core needle biopsies from a registry at Northwestern Memorial Hospital. These cases included low-grade tumors, invasive lobular carcinomas, classic type, and invasive carcinomas with special subtype features. Twelve of the tumors were histologic grade 1 and 7 were histologic grade 2. One of the grade 1 tumors had tubular features (8 %), 1 had cribriform features (8 %), 2 had mucinous features (17 %), 2 were invasive lobular carcinomas, classic type (17 %), and the rest were invasive carcinoma, no special type (50 %). The histologic grade 2 tumors included 5 invasive lobular carcinomas, classic type (71 %) and 2 invasive ductal carcinomas with mucinous features (29 %). By immunohistochemistry, 13 (65 %) were HER2 score 3+, 7 were score 2+ (35 %), and reflex fluorescence in-situ hybridization (FISH) testing showed amplification in 6 cases, with 1 equivocal case amplified on excision. Despite the HER2 positive status in the selected cases, no unique morphologic features that would indicate aggressive behavior were identified. In clinical follow up, two patients were found to have recurrences, five had lymph node metastasis, and one had distant metastasis. None of the patients with recurrent disease were treated with trastuzumab, despite their positive HER2 results. These findings support that our population of HER2 positive carcinomas showed a similar rate of lymph node metastases and recurrence as poorly-differentiated tumors, supporting HER2 positivity as a poor prognostic indicator, irrespective of morphologic features. We recommend continuing to test all breast cancers, regardless of grade or special subtype features, to provide the most comprehensive treatment and prognostic information for both clinicians and patients.

Pathological features of 11,337 patients with primary ductal carcinoma in situ (DCIS) and subsequent events: results from the UK Sloane Project

Background

The Sloane audit compares screen-detected ductal carcinoma in situ (DCIS) pathology with subsequent management and outcomes.

Methods

This was a national, prospective cohort study of DCIS diagnosed during 2003–2012.

Results

Among 11,337 patients, 7204 (64%) had high-grade DCIS. Over time, the proportion of high-grade disease increased (from 60 to 65%), low-grade DCIS decreased (from 10 to 6%) and mean size increased (from 21.4 to 24.1 mm). Mastectomy was more common for high-grade (36%) than for low-grade DCIS (15%). Few (6%) patients treated with breast-conserving surgery (BCS) had a surgical margin <1 mm. Of the 9191 women diagnosed in England (median follow-up 9.4 years), 7% developed DCIS or invasive malignancy in the ipsilateral and 5% in the contralateral breast. The commonest ipsilateral event was invasive carcinoma (n = 413), median time 62 months, followed by DCIS (n = 225), at median 37 months. Radiotherapy (RT) was most protective against recurrence for high-grade DCIS (3.2% for high-grade DCIS with RT compared to 6.9% without, compared with 2.3 and 3.0%, respectively, for low/intermediate-grade DCIS). Ipsilateral DCIS events lessened after 5 years, while the risk of ipsilateral invasive cancer remained consistent to beyond 10 years.

Conclusion

DCIS pathology informs patient management and highlights the need for prolonged follow-up of screen-detected DCIS.

Interobserver Variability in Ductal Carcinoma In Situ of the Breast

OBJECTIVES

Since most patients with ductal carcinoma in situ (DCIS) of the breast are treated upon diagnosis, evidence on its natural progression to invasive carcinoma is limited. It is estimated that around half of the screen-detected DCIS lesions would have remained indolent if they had never been detected. Many patients with DCIS are therefore probably overtreated. Four ongoing randomized noninferiority trials explore active surveillance as a treatment option. Eligibility for these trials is mainly based on histopathologic features. Hence, the call for reproducible histopathologic assessment has never sounded louder.

METHODS

Here, the available classification systems for DCIS are discussed in depth.

RESULTS

This comprehensive review illustrates that histopathologic evaluation of DCIS is characterized by significant interobserver variability. Future digitalization of pathology, combined with development of deep learning algorithms or so-called artificial intelligence, may be an innovative solution to tackle this problem. However, implementation of digital pathology is not within reach for each laboratory worldwide. An alternative classification system could reduce the disagreement among histopathologists who use "conventional" light microscopy: the introduction of dichotomous histopathologic assessment is likely to increase interobserver concordance.

CONCLUSIONS

Reproducible histopathologic assessment is a prerequisite for robust risk stratification and adequate clinical decision-making. Two-tier histopathologic assessment might enhance the quality of care.

Visual histological assessment of morphological features reflects the underlying molecular profile in invasive breast cancer: a morphomolecular study

AIMS

Tumour genotype and phenotype are related and can predict outcome. In this study, we hypothesised that the visual assessment of breast cancer (BC) morphological features can provide valuable insight into underlying molecular profiles.

METHODS AND RESULTS

The Cancer Genome Atlas (TCGA) BC cohort was used (n = 743) and morphological features, including Nottingham grade and its components and nucleolar prominence, were assessed utilising whole-slide images (WSIs). Two independent scores were assigned, and discordant cases were utilised to represent cases with intermediate morphological features. Differentially expressed genes (DEGs) were identified for each feature, compared among concordant/discordant cases and tested for specific pathways. Concordant grading was observed in 467 of 743 (63%) of cases. Among concordant case groups, eight common DEGs (UGT8, DDC, RGR, RLBP1, SPRR1B, CXorf49B, PSAPL1 and SPRR2G) were associated with overall tumour grade and its components. These genes are related mainly to cellular proliferation, differentiation and metabolism. The number of DEGs in cases with discordant grading was larger than those identified in concordant cases. The largest number of DEGs was observed in discordant grade 1:3 cases (n = 1185). DEGs were identified for each discordant component. Some DEGs were uniquely associated with well-defined specific morphological features, whereas expression/co-expression of other genes was identified across multiple features and underlined intermediate morphological features.

CONCLUSION

Morphological features are probably related to distinct underlying molecular profiles that drive both morphology and behaviour. This study provides further evidence to support the use of image-based analysis of WSIs, including artificial intelligence algorithms, to predict tumour molecular profiles and outcome.

Current and future applications of artificial intelligence in pathology: a clinical perspective

During the last decade, a dramatic rise in the development and application of artificial intelligence (AI) tools for use in pathology services has occurred. This trend is often expected to continue and reshape the field of pathology in the coming years. The deployment of computational pathology and applications of AI tools can be considered as a paradigm shift that will change pathology services, making them more efficient and capable of meeting the needs of this era of precision medicine. Despite the success of AI models, the translational process from discovery to clinical applications has been slow. The gap between self-contained research and clinical environment may be too wide and has been largely neglected. In this review, we cover the current and prospective applications of AI in pathology. We examine its applications in diagnosis and prognosis, and we offer insights for considerations that could improve clinical applicability of these tools. Then, we discuss its potential to improve workflow efficiency, and its benefits in pathologist education. Finally, we review the factors that could influence adoption in clinical practices and the associated regulatory processes.

Prognostic significance of nucleolar assessment in invasive breast cancer

AIMS

Nucleolar morphometric features have a potential role in the assessment of the aggressiveness of many cancers. However, the role of nucleoli in invasive breast cancer (BC) is still unclear. The aims of this study were to investigate the optimal method for scoring nucleoli in IBC and their prognostic significance, and to refine the grading of breast cancer (BC) by incorporating nucleolar score.

METHODS AND RESULTS

Digital images acquired from haematoxylin and eosin-stained sections from a large BC cohort were divided into training (n = 400) and validation (n = 1200) sets for use in this study. Four different assessment methods were evaluated in the training set to identify the optimal method associated with the best performance and significant prognostic value. These were: (i) a modified Helpap method; (ii) counting prominent nucleoli (size ≥2.5 µm) in 10 field views (FVs); (iii) counting prominent nucleoli in five FVs; and (iv) counting prominent nucleoli in one FV. The optimal method was applied to the validation set and to an external validation set, i.e. data from The Cancer Genome Atlas (n = 743). Scoring prominent nucleoli in five FVs showed the highest interobserver concordance rate (intraclass correlation coefficient of 0.8) and a significant association with BC-specific survival (P < 0.0001). A high nucleolar score was associated with younger age, larger tumour size, and higher grade. Incorporation of nucleolar score in the Nottingham grading system resulted in a higher significant association with survival than the conventional grade.

CONCLUSIONS

Quantification of nucleolar prominence in five FVs is a cost-efficient and reproducible morphological feature that can predict BC behaviour and can provide an alternative to pleomorphism to improve BC grading performance.

Interobserver variability in upfront dichotomous histopathological assessment of ductal carcinoma in situ of the breast: the DCISion study

Histopathological assessment of ductal carcinoma in situ, a nonobligate precursor of invasive breast cancer, is characterized by considerable interobserver variability. Previously, post hoc dichotomization of multicategorical variables was used to determine the "ideal" cutoffs for dichotomous assessment. The present international multicenter study evaluated interobserver variability among 39 pathologists who performed upfront dichotomous evaluation of 149 consecutive ductal carcinomas in situ. All pathologists independently assessed nuclear atypia, necrosis, solid ductal carcinoma in situ architecture, calcifications, stromal architecture, and lobular cancerization in one digital slide per lesion. Stromal inflammation was assessed semiquantitatively. Tumor-infiltrating lymphocytes were quantified as percentages and dichotomously assessed with a cutoff at 50%. Krippendorff's alpha (KA), Cohen's kappa and intraclass correlation coefficient were calculated for the appropriate variables. Lobular cancerization (KA = 0.396), nuclear atypia (KA = 0.422), and stromal architecture (KA = 0.450) showed the highest interobserver variability. Stromal inflammation (KA = 0.564), dichotomously assessed tumor-infiltrating lymphocytes (KA = 0.520), and comedonecrosis (KA = 0.539) showed slightly lower interobserver disagreement. Solid ductal carcinoma in situ architecture (KA = 0.602) and calcifications (KA = 0.676) presented with the lowest interobserver variability. Semiquantitative assessment of stromal inflammation resulted in a slightly higher interobserver concordance than upfront dichotomous tumor-infiltrating lymphocytes assessment (KA = 0.564 versus KA = 0.520). High stromal inflammation corresponded best with dichotomously assessed tumor-infiltrating lymphocytes when the cutoff was set at 10% (kappa = 0.881). Nevertheless, a post hoc tumor-infiltrating lymphocytes cutoff set at 20% resulted in the highest interobserver agreement (KA = 0.669). Despite upfront dichotomous evaluation, the interobserver variability remains considerable and is at most acceptable, although it varies among the different histopathological features. Future studies should investigate its impact on ductal carcinoma in situ prognostication. Forthcoming machine learning algorithms may be useful to tackle this substantial diagnostic challenge.

Artificial intelligence in digital breast pathology: Techniques and applications

Breast cancer is the most common cancer and second leading cause of cancer-related death worldwide. The mainstay of breast cancer workup is histopathological diagnosis - which guides therapy and prognosis. However, emerging knowledge about the complex nature of cancer and the availability of tailored therapies have exposed opportunities for improvements in diagnostic precision. In parallel, advances in artificial intelligence (AI) along with the growing digitization of pathology slides for the primary diagnosis are a promising approach to meet the demand for more accurate detection, classification and prediction of behaviour of breast tumours. In this article, we cover the current and prospective uses of AI in digital pathology for breast cancer, review the basics of digital pathology and AI, and outline outstanding challenges in the field.

Deep learning assisted mitotic counting for breast cancer

As part of routine histological grading, for every invasive breast cancer the mitotic count is assessed by counting mitoses in the (visually selected) region with the highest proliferative activity. Because this procedure is prone to subjectivity, the present study compares visual mitotic counting with deep learning based automated mitotic counting and fully automated hotspot selection. Two cohorts were used in this study. Cohort A comprised 90 prospectively included tumors which were selected based on the mitotic frequency scores given during routine glass slide diagnostics. This pathologist additionally assessed the mitotic count in these tumors in whole slide images (WSI) within a preselected hotspot. A second observer performed the same procedures on this cohort. The preselected hotspot was generated by a convolutional neural network (CNN) trained to detect all mitotic figures in digitized hematoxylin and eosin (H&E) sections. The second cohort comprised a multicenter, retrospective TNBC cohort (n = 298), of which the mitotic count was assessed by three independent observers on glass slides. The same CNN was applied on this cohort and the absolute number of mitotic figures in the hotspot was compared to the averaged mitotic count of the observers. Baseline interobserver agreement for glass slide assessment in cohort A was good (kappa 0.689; 95% CI 0.580-0.799). Using the CNN generated hotspot in WSI, the agreement score increased to 0.814 (95% CI 0.719-0.909). Automated counting by the CNN in comparison with observers counting in the predefined hotspot region yielded an average kappa of 0.724. We conclude that manual mitotic counting is not affected by assessment modality (glass slides, WSI) and that counting mitotic figures in WSI is feasible. Using a predefined hotspot area considerably improves reproducibility. Also, fully automated assessment of mitotic score appears to be feasible without introducing additional bias or variability.

Management and 5-year outcomes in 9938 women with screen-detected ductal carcinoma in situ: the UK Sloane Project

BACKGROUND

Management of screen-detected ductal carcinoma in situ (DCIS) remains controversial.

METHODS

A prospective cohort of patients with DCIS diagnosed through the UK National Health Service Breast Screening Programme (1st April 2003 to 31st March 2012) was linked to national databases and case note review to analyse patterns of care, recurrence and mortality.

RESULTS

Screen-detected DCIS in 9938 women, with mean age of 60 years (range 46-87), was treated by mastectomy (2931) or breast conserving surgery (BCS) (7007; 70%). At 64 months median follow-up, 697 (6.8%) had further DCIS or invasive breast cancer after BCS (7.8%) or mastectomy (4.5%) (p < 0.001). Breast radiotherapy (RT) after BCS (4363/7007; 62.3%) was associated with a 3.1% absolute reduction in ipsilateral recurrent DCIS or invasive breast cancer (no RT: 7.2% versus RT: 4.1% [p < 0.001]) and a 1.9% absolute reduction for ipsilateral invasive breast recurrence (no RT: 3.8% versus RT: 1.9% [p < 0.001]), independent of the excision margin width or size of DCIS. Women without RT after BCS had more ipsilateral breast recurrences (p < 0.001) when the radial excision margin was <2 mm. Adjuvant endocrine therapy (1208/9938; 12%) was associated with a reduction in any ipsilateral recurrence, whether RT was received (hazard ratio [HR] 0.57; 95% confidence interval [CI] 0.41-0.80) or not (HR 0.68; 95% CI 0.51-0.91) after BCS. Women who developed invasive breast recurrence had a worse survival than those with recurrent DCIS (p < 0.001). Among 321 (3.2%) who died, only 46 deaths were attributed to invasive breast cancer.

CONCLUSION

Recurrent DCIS or invasive cancer is uncommon after screen-detected DCIS. Both RT and endocrine therapy were associated with a reduction in further events but not with breast cancer mortality within 5 years of diagnosis. Further research to identify biomarkers of recurrence risk, particularly as invasive disease, is indicated.

Diagnostic concordance of reporting lymphovascular invasion in breast cancer

AIMS

This study aims to assess the diagnostic agreement of lymphovascular invasion (LVI) in invasive breast cancer (BC).

METHODS

Data on LVI were collected from the UK National Health Service Breast Screening Programme pathology external quality assurance scheme database. 101 BCs assessed over a 10-year period (2004-2014) were included. Cases were scored by an average of 600 pathologists. Three H&E stained slides from each case were reviewed by three pathologists and additional variables were evaluated.

RESULTS

In the whole series, the overall κ value was 0.4 (range 0.26-0.53). On review, LVI was detected in all three slides in 20 cases (20%), in two slides in 12 cases and in one of the three slides in 9 cases and was not seen in 60 cases. For concordance analysis, the first and last groups were used to represent cases with definite (LVI+) and absent LVI (LVI-), respectively. In the LVI+group (n=20), the level of agreement ranged from 0.54 to 0.99 (median 0.86). In the LVI- group (n=60), the level of agreement ranged from 0.52 to 1.00 (median 0.93), with 44% of cases showing interobserver concordance of >95%. There was a correlation between increasing number of involved lymphovascular spaces in the section and higher LVI reporting concordance. Some degree of retraction/fixation artefacts was observed in 35% of cases; this was associated with a lower concordance rate.

CONCLUSIONS

The concordance of reporting LVI is variable. Cases without LVI and those with multiple involved vessels are likely to have the highest concordance and the highest detection rates.

Breast cancer histologic grading using digital microscopy: concordance and outcome association

Aims

Virtual microscopy utilising digital whole slide imaging (WSI) is increasingly used in breast pathology. Histologic grade is one of the strongest prognostic factors in breast cancer (BC). This study aims at investigating the agreement between BC grading using traditional light microscopy (LM) and digital WSI with consideration of reproducibility and impact on outcome prediction.

Methods

A large (n=1675) well-characterised cohort of BC originally graded by LM was re-graded using WSI. Two separate virtual-based grading sessions (V1 and V2) were performed with a 3-month washout period. Outcome was assessed using BC-specific and distant metastasis-free survival.

Results

The concordance between LM grading and WSI was strong (LM/WSI Cramer’s V: V1=0.576, and V2=0.579). The agreement regarding grade components was as follows: tubule formation=0.538, pleomorphism=0.422 and mitosis=0.514. Greatest discordance was observed between adjacent grades, whereas high/low grade discordance was uncommon (1.5%). The intraobserver agreement for the two WSI sessions was substantial for grade (V1/V2 Cramer’s V=0.676; kappa=0.648) and grade components (Cramer’s V T=0.628, p=0.573 and M=0.580). Grading using both platforms showed strong association with outcome (all p values <0.001). Although mitotic scores assessed using both platforms were strongly associated with outcome, WSI tends to underestimate mitotic counts.

Conclusions

Virtual microscopy is a reliable and reproducible method for assessing BC histologic grade. Regardless of the observer or assessment platform, histologic grade is a significant predictor of outcome. Continuing advances in imaging technology could potentially provide improved performance of WSI BC grading and in particular mitotic count assessment.

The BIG 2.04 MRC/EORTC SUPREMO Trial: pathology quality assurance of a large phase 3 randomised international clinical trial of postmastectomy radiotherapy in intermediate-risk breast cancer

Introduction

SUPREMO is a phase 3 randomised trial evaluating radiotherapy post-mastectomy for intermediate-risk breast cancer. 1688 patients were enrolled from 16 countries between 2006 and 2013. We report the results of central pathology review carried out for quality assurance.

Patients and methods

A single recut haematoxylin and eosin (H&E) tumour section was assessed by one of two reviewing pathologists, blinded to the originally reported pathology and patient data. Tumour type, grade and lymphovascular invasion were reviewed to assess if they met the inclusion criteria. Slides from potentially ineligible patients on central review were scanned and reviewed online together by the two pathologists and a consensus reached. A subset of 25 of these cases was double-reported independently by the pathologists prior to the online assessment.

Results

The major contributors to the trial were the UK (75%) and the Netherlands (10%). There is a striking difference in lymphovascular invasion (LVi) rates (41.6 vs. 15.1% (UK); p = <0.0001) and proportions of grade 3 carcinomas (54.0 vs. 42.0% (UK); p = <0.0001) on comparing local reporting with central review. There was no difference in the locally reported frequency of LVi rates in node-positive (N+) and node-negative (N−) subgroups (40.3 vs. 38.0%; p = 0.40) but a significant difference in the reviewed frequency (16.9 vs. 9.9%; p = 0.004). Of the N− cases, 104 (25.1%) would have been ineligible by initial central review by virtue of grade and/or lymphovascular invasion status. Following online consensus review, this fell to 70 cases (16.3% of N− cases, 4.1% of all cases).

Conclusions

These data have important implications for the design, powering and interpretation of outcomes from this and future clinical trials. If critical pathology criteria are determinants for trial entry, serious consideration should be given to up-front central pathology review.

Electronic supplementary material

The online version of this article (doi:10.1007/s10549-017-4145-4) contains supplementary material, which is available to authorized users.