Interpretive disparity among pathologists in breast sentinel lymph node evaluation

Development of a Colloidal Gold Immunochromatographic Strip for Rapid Detection of Cyfra 21-1 in Lymph Node Metastasis of Thyroid Cancer

Thyroid cancer is the most common endocrine tumor, and the rate of early lymph node metastasis may be as high as 60%. Currently, detection of lymph node metastasis of thyroid cancer during surgery is limited and time-consuming. Elevated levels of Cyfra 21-1, the proteolytic portion of cytokeratin, are associated with the metastasis and progression of thyroid cancer and are an effective biomarker for the prognosis and diagnosis of thyroid cancer. In this study, an immunochromatographic strip test based on colloidal gold nanoparticles was developed to semi-quantitatively detect the levels of Cyfra 21-1 in lymph nodes within 15 min. The standard (calibration) curve equation was Y = 0.003708 × X + 0.1101, and the detection limit was 0.55–1.14 ng mL⁻¹. The strip did not detect other protein markers of epithelial cells at a concentration of 500 ng mL⁻¹, including cytokeratin 8, cytokeratin 18, epithelial membrane antigen, and epidermal surface antigen. The ability of the strip to differentiate positive from negative metastasis in 40 lymph node specimens was 100% concordant with that of immunohistochemical staining for Cyfra 21-1. In an assessment of 20 lymph node specimens that had been determined by postoperative histopathology to be positive for lymph node metastasis and 20 specimens that were negative, the sensitivity and specificity of the strip were 100% and 95%, respectively. The sensitivity of the strip remained stable when stored at room temperature for 6 months. Together, these results indicated that although further testing using a larger sample size will be required, this immunochromatographic strip test may be useful for rapid intraoperative detection of thyroid cancer metastasis to lymph nodes.

Deep Convolutional Neural Network-Based Lymph Node Metastasis Prediction for Colon Cancer Using Histopathological Images

Background

Human evaluation of pathological slides cannot accurately predict lymph node metastasis (LNM), although accurate prediction is essential to determine treatment and follow-up strategies for colon cancer. We aimed to develop accurate histopathological features for LNM in colon cancer.

Methods

We developed a deep convolutional neural network model to distinguish the cancer tissue component of colon cancer using data from the tissue bank of the National Center for Tumor Diseases and the pathology archive at the University Medical Center Mannheim, Germany. This model was applied to whole-slide pathological images of colon cancer patients from The Cancer Genome Atlas (TCGA). The predictive value of the peri-tumoral stroma (PTS) score for LNM was assessed.

Results

A total of 164 patients with stages I, II, and III colon cancer from TCGA were analyzed. The mean PTS score was 0.380 (± SD = 0.285), and significantly higher PTS scores were observed in patients in the LNM-positive group than those in the LNM-negative group (P < 0.001). In the univariate analyses, the PTS scores for the LNM-positive group were significantly higher than those for the LNM-negative group (P < 0.001). Further, the PTS scores in lymphatic invasion and any one of perineural, lymphatic, or venous invasion were significantly increased in the LNM-positive group (P < 0.001 and P < 0.001).

Conclusion

We established the PTS score, a simplified reproducible parameter, for predicting LNM in colon cancer using computer-based analysis that could be used to guide treatment decisions. These findings warrant further confirmation through large-scale prospective clinical trials.

1399 H&E-stained sentinel lymph node sections of breast cancer patients: the CAMELYON dataset

Background

The presence of lymph node metastases is one of the most important factors in breast cancer prognosis. The most common way to assess regional lymph node status is the sentinel lymph node procedure. The sentinel lymph node is the most likely lymph node to contain metastasized cancer cells and is excised, histopathologically processed, and examined by a pathologist. This tedious examination process is time-consuming and can lead to small metastases being missed. However, recent advances in whole-slide imaging and machine learning have opened an avenue for analysis of digitized lymph node sections with computer algorithms. For example, convolutional neural networks, a type of machine-learning algorithm, can be used to automatically detect cancer metastases in lymph nodes with high accuracy. To train machine-learning models, large, well-curated datasets are needed.

Results

We released a dataset of 1,399 annotated whole-slide images (WSIs) of lymph nodes, both with and without metastases, in 3 terabytes of data in the context of the CAMELYON16 and CAMELYON17 Grand Challenges. Slides were collected from five medical centers to cover a broad range of image appearance and staining variations. Each WSI has a slide-level label indicating whether it contains no metastases, macro-metastases, micro-metastases, or isolated tumor cells. Furthermore, for 209 WSIs, detailed hand-drawn contours for all metastases are provided. Last, open-source software tools to visualize and interact with the data have been made available.

Conclusions

A unique dataset of annotated, whole-slide digital histopathology images has been provided with high potential for re-use.

Reproducibility of the NEPTUNE descriptor-based scoring system on whole-slide images and histologic and ultrastructural digital images

The multicenter Nephrotic Syndrome Study Network (NEPTUNE) digital pathology scoring system employs a novel and comprehensive methodology to document pathologic features from whole-slide images, immunofluorescence and ultrastructural digital images. To estimate inter- and intra-reader concordance of this descriptor-based approach, data from 12 pathologists (eight NEPTUNE and four non-NEPTUNE) with experience from training to 30 years were collected. A descriptor reference manual was generated and a webinar-based protocol for consensus/cross-training implemented. Intra-reader concordance for 51 glomerular descriptors was evaluated on jpeg images by seven NEPTUNE pathologists scoring 131 glomeruli three times (Tests I, II, and III), each test following a consensus webinar review. Inter-reader concordance of glomerular descriptors was evaluated in 315 glomeruli by all pathologists; interstitial fibrosis and tubular atrophy (244 cases, whole-slide images) and four ultrastructural podocyte descriptors (178 cases, jpeg images) were evaluated once by six and five pathologists, respectively. Cohen's kappa for inter-reader concordance for 48/51 glomerular descriptors with sufficient observations was moderate (0.40<kappa≤0.60) for 17 and good (0.60<kappa≤0.80) for 8, for 52% with moderate or better kappas. Clustering of glomerular descriptors based on similar pathologic features improved concordance. Concordance was independent of years of experience, and increased with webinar cross-training. Excellent concordance was achieved for interstitial fibrosis and tubular atrophy. Moderate-to-excellent concordance was achieved for all ultrastructural podocyte descriptors, with good-to-excellent concordance for descriptors commonly used in clinical practice, foot process effacement, and microvillous transformation. NEPTUNE digital pathology scoring system enables novel morphologic profiling of renal structures. For all histologic and ultrastructural descriptors tested with sufficient observations, moderate-to-excellent concordance was seen for 31/54 (57%). Descriptors not sufficiently represented will require further testing. This study proffers the NEPTUNE digital pathology scoring system as a model for standardization of renal biopsy interpretation extendable outside the NEPTUNE consortium, enabling international collaborations.

Stain Specific Standardization of Whole-Slide Histopathological Images

Variations in the color and intensity of hematoxylin and eosin (H&E) stained histological slides can potentially hamper the effectiveness of quantitative image analysis. This paper presents a fully automated algorithm for standardization of whole-slide histopathological images to reduce the effect of these variations. The proposed algorithm, called whole-slide image color standardizer (WSICS), utilizes color and spatial information to classify the image pixels into different stain components. The chromatic and density distributions for each of the stain components in the hue-saturation-density color model are aligned to match the corresponding distributions from a template whole-slide image (WSI). The performance of the WSICS algorithm was evaluated on two datasets. The first originated from 125 H&E stained WSIs of lymph nodes, sampled from 3 patients, and stained in 5 different laboratories on different days of the week. The second comprised 30 H&E stained WSIs of rat liver sections. The result of qualitative and quantitative evaluations using the first dataset demonstrate that the WSICS algorithm outperforms competing methods in terms of achieving color constancy. The WSICS algorithm consistently yields the smallest standard deviation and coefficient of variation of the normalized median intensity measure. Using the second dataset, we evaluated the impact of our algorithm on the performance of an already published necrosis quantification system. The performance of this system was significantly improved by utilizing the WSICS algorithm. The results of the empirical evaluations collectively demonstrate the potential contribution of the proposed standardization algorithm to improved diagnostic accuracy and consistency in computer-aided diagnosis for histopathology data.

An intra-operative RT-LAMP method allows rapid and reliable detection of sentinel lymph node metastasis in breast cancer patients

The rapid determination of metastasis in sentinel lymph nodes (SLNs) of breast cancer patients plays a significant role in the selection of a surgery strategy. Although a previous one-step nucleic acid amplification assay that uses reverse-transcription (RT) loop-mediated isothermal amplification (LAMP) has showed specific advantages over traditional pathological examination, its target marker requires optimisation. In addition to epithelial-specific CK19, the internal control gene PBGD and the breast-specific PIP were included in the new method. After the RT-LAMP primers were designed and verified using a cell line, the performance of our method was evaluated by comparing it with the corresponding result of the Food and Drug Administration approved breast lymph node (BLN) assay and routine pathological examination. One hundred and seventy-four valid SLN samples from 101 patients were collected from five hospitals. The threshold of reaction time for CK19, PIP and PBGD was defined as 16, 20 and 20 min, respectively. Compared with the BLN assay, the concordance rate of our method was 95.4% (166/174). Statistical analysis revealed that the two methods are consistent (kappa = 0.890, P < 0.001). When compared with pathological examination, the performance of our method (sensitivity = 81.3%, specificity = 89.7%, kappa = 0.691, P < 0.001) was similar to that of the BLN assay (sensitivity = 87.5%, specificity = 84.9%, kappa = 0.668, P < 0.001). This result demonstrates the potential usefulness of our method in clinical practice. In conclusion, we preliminarily established an intra-operative diagnostic method that assimilates the merits of previous assays. In contrast with the BLN assay and pathological examination, our method can be completed in 30 min and shows high sensitivity, specificity and consistency, which we consider as promising for clinical application.

Discrimination of lymph node metastases using desorption electrospray ionisation-mass spectrometry imaging

Desorption electrospray ionisation mass spectrometry imaging (DESI-MSI) has been used for the identification of cancer within lymph nodes with accurate spatial distribution in comparison to gold standard matched immuno-histopathological images. The metabolic profile of the cancerous lymph nodes was similar to that of the primary tumour site.

Patients' choice on axillary lymph node dissection following sentinel lymph node micrometastasis--first report on prospective use of a nomogram in very low risk patients

The optimal locoregional treatment of patients diagnosed with sentinel node (SN) micrometastasis is controversial. A previously reported and validated nomogram was used to calculate the risk of non-SN metastasis in patients with SN micrometastasis over a period of 2 years. Patients were given detailed information about the risk, consequences and treatment options of non-SN involvement, the risk and potential complications of unnecessary completion axillary lymph node dissection (ALND), the imperfectness of the nomogram, and other factors that may influence their selection of further treatment. They also received a questionnaire to monitor factors influencing their decisions. Of the 25 patients participating in the study, 10 have opted for ALND. The only factor that seemed to influence their choice was fear from disease recurrence. Giving detailed information to SN micrometastatic patients is a patient-centered alternative to current recommendations on performing ALND in all such patients or omitting ALND in all of them.

Relevant impact of central pathology review on nodal classification in individual breast cancer patients

BACKGROUND

In the MIRROR study, pN0(i + ) and pN1mi were associated with reduced 5-year disease-free survival (DFS) compared with pN0. Nodal status (N-status) was assessed after central pathology review and restaging according to the sixth AJCC classification. We addressed the impact of pathology review.

PATIENTS AND METHODS

Early favorable primary breast cancer patients, classified pN0, pN0(i + ), or pN1(mi) by local pathologists after sentinel node procedure, were included. We assessed the impact of pathology review on N-status (n = 2842) and 5-year DFS for those without adjuvant therapy (n = 1712).

RESULTS

In all, 22% of the 1082 original pN0 patients was upstaged. Of the 623 original pN0(i + ) patients, 1% was downstaged, 26% was upstaged. Of 1137 patients staged pN1mi, 15% was downstaged, 11% upstaged. Originally, 5-year DFS was 85% for pN0, 74% for pN0(i + ), and 73% for pN1mi; HR 1.70 [95% confidence interval (CI) 1.27-2.27] and HR 1.57 (95% CI 1.16-2.13), respectively, compared with pN0. By review staging, 5-year DFS was 86% for pN0, 77% for pN0(i + ), 77% for pN1mi, and 74% for pN1 + .

CONCLUSION

Pathology review changed the N-classification in 24%, mainly upstaging, with potentially clinical relevance for individual patients. The association of isolated tumor cells and micrometastases with outcome remained unchanged. Quality control should include nodal breast cancer staging.

Intraoperative qRT-PCR for detection of lymph node metastasis in head and neck cancer

PURPOSE

Sentinel node biopsy (SNB) has been shown to accurately stage the regional lymphatics in oral carcinoma. However, intraoperative pathology is only moderately sensitive and final pathology takes several days to complete. The purpose of this study was to develop a rapid, automated, and quantitative real-time PCR (qRT-PCR) assay that can match final pathology in an intraoperative time frame.

EXPERIMENTAL DESIGN

Four hundred forty-eight grossly tumor-negative lymph nodes were evaluated for expression of 3 markers [PVA (pemphigus vulgaris antigen), PTHrP (parathyroid hormone-related protein), and TACSTD1 (tumor-associated calcium signal transducer 1)]. Conformity of metastasis detection by qRT-PCR was determined using hematoxylin and eosin and immunohistochemistry staining as the gold standard. PVA and TACSTD1 were then multiplexed with β-glucuronidase to develop a rapid, automated single-tube qRT-PCR assay using the Cepheid GeneXpert system. This assay was used to analyze 103 lymph nodes in an intraoperative time frame.

RESULTS

Four hundred forty-two nodes produced an informative result for both qRT-PCR and pathologic examination. Concordance of qRT-PCR for individual markers with final pathology ranged from 93% to 98%. The best marker combination was TACSTD1 and PVA. A rapid, multiplex assay for TACSTD1 and PVA was developed on the Cepheid GeneXpert and demonstrated an excellent reproducibility and linearity. Analysis of 103 lymph nodes demonstrated 94.2% accuracy of this assay for identifying positive and negative nodes. The average time for each assay to yield results was 35 minutes.

CONCLUSIONS

A rapid, automated qRT-PCR assay can detect lymph node metastasis in head and neck cancer with high accuracy compared to pathologic analysis and may be more accurate than intraoperative pathology. Combined, SNB and rapid qRT-PCR could more appropriately guide surgical treatment of patients with head and neck cancer.

Intraoperative assessment of sentinel lymph nodes in breast cancer

Background

Sentinel lymph node biopsy (SLNB) reduces the morbidity of axillary clearance and is the standard of care for patients with clinically node-negative breast cancer. The ability to analyse the sentinel node during surgery enables a decision to be made whether to proceed to full axillary clearance during primary surgery, thus avoiding a second procedure in node-positive patients.

Methods

Current evidence for intraoperative sentinel node analysis following SLNB in breast cancer was reviewed and evaluated, based on articles obtained from a MEDLINE search using the terms ‘sentinel node’, ‘intra-operative’ and ‘breast cancer’.

Results and conclusion

Current methods for evaluating the sentinel node during surgery include cytological and histological techniques. Newer quantitative molecular assays have been the subject of much recent clinical research. Pathological techniques of intraoperative SLNB analysis such as touch imprint cytology and frozen section have a high specificity, but a lower and more variably reported sensitivity. Molecular techniques are potentially able to sample a greater proportion of the sentinel node, and could have higher sensitivity.

Size of sentinel-node metastasis and chances of non-sentinel-node involvement and survival in early stage vulvar cancer: results from GROINSS-V, a multicentre observational study

BACKGROUND

Currently, all patients with vulvar cancer with a positive sentinel node undergo inguinofemoral lymphadenectomy, irrespective of the size of sentinel-node metastases. Our study aimed to assess the association between size of sentinel-node metastasis and risk of metastases in non-sentinel nodes, and risk of disease-specific survival in early stage vulvar cancer.

METHODS

In the GROningen INternational Study on Sentinel nodes in Vulvar cancer (GROINSS-V), sentinel-node detection was done in patients with T1-T2 (<4 cm) squamous-cell vulvar cancer, followed by inguinofemoral lymphadenectomy if metastatic disease was identified in the sentinel node, either by routine examination or pathological ultrastaging. For the present study, sentinel nodes were independently reviewed by two pathologists.

FINDINGS

Metastatic disease was identified in one or more sentinel nodes in 135 (33%) of 403 patients, and 115 (85%) of these patients had inguinofemoral lymphadenectomy. The risk of non-sentinel-node metastases was higher when the sentinel node was found to be positive with routine pathology than with ultrastaging (23 of 85 groins vs three of 56 groins, p=0.001). For this study, 723 sentinel nodes in 260 patients (2.8 sentinel nodes per patient) were reviewed. The proportion of patients with non-sentinel-node metastases increased with size of sentinel-node metastasis: one of 24 patients with individual tumour cells had a non-sentinel-node metastasis; two of 19 with metastases 2 mm or smaller; two of 15 with metastases larger than 2 mm to 5 mm; and ten of 21 with metastases larger than 5 mm. Disease-specific survival for patients with sentinel-node metastases larger than 2 mm was lower than for those with sentinel-node metastases 2 mm or smaller (69.5%vs 94.4%, p=0.001).

INTERPRETATION

Our data show that the risk of non-sentinel-node metastases increases with size of sentinel-node metastasis. No size cutoff seems to exist below which chances of non-sentinel-node metastases are close to zero. Therefore, all patients with sentinel-node metastases should have additional groin treatment. The prognosis for patients with sentinel-node metastasis larger than 2 mm is poor, and novel treatment regimens should be explored for these patients.

Accurate classification of sentinel lymph node metastases in patients with lobular breast carcinoma

Among pathologists there is low reproducibility in classifying small volume metastases in sentinel lymph node particularly in cases of invasive lobular carcinoma. We postulate that strict adherence to American Joint Commission on Cancer (AJCC) 2003 criteria may result in inaccurate staging of lobular carcinoma patients. We reviewed cases of metastatic lobular carcinoma in sentinel lymph node biopsies between 1998 and 2008. All sentinel lymph nodes were reassessed using strict adherence to AJCC 2003 criteria. Subsequent axillary lymph node dissection and clinical follow-up were reviewed. Fifty-one patients met our inclusion criteria and were originally classified by the primary pathologist as follows: 10 isolated tumor cells, 8 micrometastases, 27 macrometastases, and 6 'positive' cases without further classification. Cases were re-classified using strict adherence to AJCC 2003 criteria as follows: 21 isolated tumor cells, 2 micrometastases, and 28 macrometastases. Twelve isolated tumor cells cases underwent full axillary dissection, and 3 (25%) had additional macrometastases. All micrometastatic cases underwent axillary dissection; all were negative. Twenty-two macrometastatic cases underwent full axillary dissection and 16 (73%) had additional macrometastases. Diffuse single cells or small clusters should not be interpreted as isolated tumor cells in invasive lobular carcinoma sentinel lymph nodes. The criteria for assessing small volume metastases in the sentinel lymph node of patients with invasive lobular carcinoma need to be more clearly defined.

Nodal-Stage Classification in Invasive Lobular Breast Carcinoma: Influence of Different Interpretations of the pTNM Classification

Purpose

Application of current nodal status classification is complicated in lobular breast carcinoma metastases. The aim of this study was to define the optimal interpretation of the pTNM classification in sentinel node (SN) –positive patients to select patients with limited or with a high risk of non-SN involvement.

Patients and Methods

SN metastases of 392 patients with lobular breast carcinoma were reclassified according to interpretations of the European Working Group for Breast Screening Pathology (EWGBSP) and guidelines by Turner et al, and the predictive power for non-SN involvement was assessed.

Results

Reclassification according to definitions of EWGBSP and Turner et al resulted in different pN classification in 73 patients (19%). The rate of non-SN involvement in the 40 patients with isolated tumor cells according to Turner et al and with micrometastases according to EWGBSP was 20%, which is comparable to the established rate for micrometastases. The rate of non-SN involvement in the 29 patients with micrometastases according to Turner et al and with macrometastases according to EWGBSP was 48%, which is comparable to the established rate for macrometastases. Therefore, the EWGBSP method to classify SN tumor load better reflected the risk of non-SN involvement than the Turner et al system.

Conclusion

Compared with the guidelines by Turner et al, the EWGBSP definitions better reflect SN metastatic tumor load and allow better differentiation between patients with lobular breast carcinoma who have a limited or a high risk of non-SN metastases. Therefore, we suggest using the EWGBSP definitions in these patients to select high-risk patients who may benefit from additional local and/or systemic therapy.

A quantitative reverse transcription-PCR assay for rapid, automated analysis of breast cancer sentinel lymph nodes

We have previously reported that a quantitative reverse transcription (QRT)-PCR assay accurately analyzes sentinel lymph nodes (SLNs) from breast cancer patients. The aim of this study was to assess a completely automated, cartridge-based version of the assay for accuracy, predictive value, and reproducibility. The triplex (two markers + control) QRT-PCR assay was incorporated into a single-use cartridge for point-of-care use on the GeneXpert system. Three academic centers participated equally. Twenty-nine positive lymph nodes and 30 negative lymph nodes were analyzed to establish classification rules. SLNs from 120 patients were subsequently analyzed by QRT-PCR and histology (including immunohistochemistry), and the predetermined decision rules were used to classify the SLNs; 112 SLN specimens produced an informative result by both QRT-PCR and histology. By histological analysis, 21 SLNs were positive and 91 SLNs were negative for metastasis. QRT-PCR characterization produced a classification with 100% sensitivity, 97.8% specificity, and 98.2% accuracy compared with histology (91.3% positive predictive value and 100% negative predictive value). Interlaboratory reproducibility analyses demonstrated that a 95% prediction interval for a new measurement (DeltaCt) ranged between 0.403 and 0.956. This fully automated QRT-PCR assay accurately characterizes breast cancer SLNs for the presence of metastasis. Furthermore, the assay is not dependent on subjective interpretation, is reproducible across three clinical environments, and is rapid enough to allow intraoperative decision making.

Identification and biologic significance of micrometastases in axillary lymph nodes in patients with invasive breast cancer

CONTEXT

The presence or absence of metastases in axillary lymph nodes is one of the most important prognostic factors for patients with breast cancer. During the past decade sentinel lymph node (SLN) biopsy has been increasingly adopted as a minimally invasive staging alternative to complete axillary node dissection.

OBJECTIVE

Sentinel lymph nodes are more likely to contain metastases than non-SLNs. In routine clinical practice SLNs are assessed by diverse methodologies including multiple sectioning, immunohistochemical staining, and molecular diagnostic tests. Despite the lack of standard histopathologic protocols during the years detailed evaluation of SLNs has resulted in an increased detection of small (micro) metastases.

DATA SOURCES

Breast cancer with micrometastases constitutes a heterogenous group of tumors with variable clinical outcome regarding the risk of additional metastases in the remaining axillary lymph nodes and to patients' survival.

CONCLUSION

The clinical significance of micrometastases has been subject to great controversy in patients with breast cancer. In this review we highlight controversies regarding micrometastases especially in relation to SLNs.

Novel intraoperative molecular test for sentinel lymph node metastases in patients with early-stage breast cancer

PURPOSE

An accurate, intraoperative sentinel lymph node (SLN) test could decrease delayed axillary dissections. Molecular tests may be more sensitive than current intraoperative tests but historically have not been rapid enough and have not been properly validated. We present the results from a large, prospective evaluation of the first rapid molecular SLN test, the Breast Lymph Node (BLN) Assay.

METHODS

A beta trial (n = 304) to determine the threshold levels of mammaglobin and cytokeratin 19 correlating with metastasis greater than 0.2 mm and a validation trial (n = 416) to validate the threshold cutoffs were conducted. Alternating portions from each SLN were processed for histology and the BLN Assay.

RESULTS

BLN Assay performance against extensive permanent-section histology verified by central pathology review was similar to that expected of standard permanent-section histology: sensitivity, 87.6%; specificity, 94.2%; positive predictive value, 86.2%; and negative predictive value (NPV), 94.9%. In 319 patients with both frozen-section hematoxylin and eosin results and BLN Assay results, the BLN Assay had higher sensitivity (95.6%) and NPV (98.2%) than frozen section (sensitivity, 85.6%; NPV, 94.5%). The assay can be performed in approximately 36 to 46 minutes for one to three nodes.

CONCLUSION

The BLN Assay allows a rapid evaluation of 50% of each SLN. Comparison with permanent-section histology on adjacent node pieces evaluated by expert pathologists indicated that the BLN Assay was more sensitive than current intraoperative techniques while maintaining high specificity. These data indicate that the assay may be clinically useful for intraoperative or postoperative axillary lymph node dissection decisions.

Nodal Stage Classification for Breast Carcinoma: Improving Interobserver Reproducibility Through Standardized Histologic Criteria and Image-Based Training

Purpose

Reliable pathologic stage classification of axillary lymph nodes is an important determinant of prognosis and therapeutic decision making for patients with invasive breast cancer. Pathologists' distinction between micrometastasis (pN1mi) and isolated tumor cells [ITC; pN0(i+)] is variable using the American Joint Committee on Cancer (AJCC) Staging Manual (Sixth Edition). We sought to determine whether a set of clearly defined histologic criteria could lead to reproducible nodal classification by pathologists.

Patients and Methods

Digital images of sentinel lymph node biopsies from 56 patients with small-volume nodal metastases were examined by six experienced breast pathologists (MDs), first as a pre-test, and again as a post-test after studying a training program that outlined and illustrated the classification criteria.

Results

Post-test results, after study of the training program, were significantly improved. Compared with the reference MD, agreement improved from 76.2% (pre-test κ = 0.575; standard deviation [SD], 0.25) to 97.3% (post-test κ = 0.947; SD, 0.049). Multirater analysis of agreement among the six MDs improved from 71.5% (pre-test κ = 0.487; ASE, 0.039) to 95.7% (post-test κ = 0.915; ASE, 0.037). Agreement on lobular carcinoma metastasis classification improved from 55% (23 of 42; pre-test) to 100% (42 of 42; post-test) (P < .001), and agreement on ITC classification in nodal parenchyma improved from 67.6% (69 of 102; pre-test) to 98.0% (100 of 102; post-test; P < .001).

Conclusion

Application of current definitions for classification of small-volume nodal metastases are inconsistent, leading to variable classification of ITC and micrometastases. Reproducibility of pathologic nodal stage classification is achievable through study of a training set to clarify the AJCC criteria.

What is a positive sentinel lymph node in a breast cancer patient? A practical approach

Sentinel lymph node (SN) biopsy has become increasingly used for the staging of breast carcinoma, resulting in the upstaging of this disease, and this has led to concerns with regard to what should be considered a positive SN. Factors influencing the positive staging of an SN include metastasis size, the method used for metastasis detection, the definition of metastasis and the individual pathologist. Until evidence to the contrary emerges, an SN should be considered positive if metastases (nodal involvement >0.2mm in the largest dimension) are detected in it by histology. A target size should be identified, and SNs, as the most likely sites of nodal metastases, should be searched systematically to find (nearly) all of the targeted metastases. The European guidelines for SN assessment have set two such target sizes: as a minimum, all metastases >2mm should be identified, and optimally all micrometastases should also be sought.

A combination of molecular markers accurately detects lymph node metastasis in non-small cell lung cancer patients

Occult lymph node metastasis (micrometastasis) is a good prognostic indicator in non-small cell lung cancer (NSCLC) and could be used to direct adjuvant chemotherapy in stage I patients. This study was designed to evaluate molecular markers for detection of occult lymph node metastasis in NSCLC, define the best marker or marker combination to distinguish positive from benign lymph nodes, and evaluate these markers in lymph nodes from pathologically node-negative (pN(0)) NSCLC patients. Potential markers were identified through literature and database searches and all markers were analyzed by quantitative reverse transcription-PCR in a primary screen of six NSCLC specimens and 10 benign nodes. Selected markers were further evaluated on 21 primary NSCLC specimens, 21 positive nodes, and 21 benign nodes, and the best individual markers and combinations were identified. A combination of three markers was further validated on an independent set of 32 benign lymph nodes, 38 histologically positive lymph nodes, and 462 lymph nodes from 68 pN(0) NSCLC patients. Forty-two markers were evaluated in the primary screen and eight promising markers were selected for further analysis. A combination of three markers (SFTPB, TACSTD1, and PVA) was identified that provided perfect classification of benign and positive nodes in all sample sets. PVA and SFTPB are particularly powerful in tumors of squamous and adenocarcinoma histologies, respectively, whereas TACSTD1 is a good general marker for NSCLC metastasis. The combination of these genes identified 32 of 462 (7%) lymph nodes from 20 of 68 (29%) patients as potentially positive for occult metastasis. Long-term follow-up will determine the clinical relevance of these findings.

Large-scale computations on histology images reveal grade-differentiating parameters for breast cancer

BACKGROUND

Tumor classification is inexact and largely dependent on the qualitative pathological examination of the images of the tumor tissue slides. In this study, our aim was to develop an automated computational method to classify Hematoxylin and Eosin (H&E) stained tissue sections based on cancer tissue texture features.

METHODS

Image processing of histology slide images was used to detect and identify adipose tissue, extracellular matrix, morphologically distinct cell nuclei types, and the tubular architecture. The texture parameters derived from image analysis were then applied to classify images in a supervised classification scheme using histologic grade of a testing set as guidance.

RESULTS

The histologic grade assigned by pathologists to invasive breast carcinoma images strongly correlated with both the presence and extent of cell nuclei with dispersed chromatin and the architecture, specifically the extent of presence of tubular cross sections. The two parameters that differentiated tumor grade found in this study were (1) the number density of cell nuclei with dispersed chromatin and (2) the number density of tubular cross sections identified through image processing as white blobs that were surrounded by a continuous string of cell nuclei. Classification based on subdivisions of a whole slide image containing a high concentration of cancer cell nuclei consistently agreed with the grade classification of the entire slide.

CONCLUSION

The automated image analysis and classification presented in this study demonstrate the feasibility of developing clinically relevant classification of histology images based on micro- texture. This method provides pathologists an invaluable quantitative tool for evaluation of the components of the Nottingham system for breast tumor grading and avoid intra-observer variability thus increasing the consistency of the decision-making process.

Comprehensive examination of sentinel lymph node in breast cancer: a solution without a problem?

Although several methods have been devised to examine sentinel lymph node (SLN) specimens in breast cancer, the extent of examination and whether it should routinely include multilevel sectioning to detect micrometastases (MM) (<2.0 mm) is still debated. In this study all "positive'' SLN biopsies from 67 consecutive patients with breast carcinoma and evaluated by means of an extended protocol were reviewed. Abnormal findings included micrometastases (MM) between 0.2 and 1.0 mm (14 cases), (MM) between 1.0 and 2.0 mm (8 cases), metastases>2.0 mm (22 cases), and isolated tumor cells (ITCs) (23 cases). The likelihood of finding metastatic deposits was comparable if sections were carried out at 100-, 150-, 200-, 250-, and 500-microm intervals. No metastatic foci>2.0 mm would have been missed. 1 MM (1.1 mm focus) was missed within the 250- and 500-microm levels on hematoxylin-eosin, but not complementary cytokeratin staining. Our data show that SLN step sectioning does not add significant yield if compared to standard examination carried on initial levels, if the minimal target of 1.0 mm micrometastatic deposit is sought.

A rapid, fully automated, molecular-based assay accurately analyzes sentinel lymph nodes for the presence of metastatic breast cancer

OBJECTIVE

To develop a fully automated, rapid, molecular-based assay that accurately and objectively evaluates sentinel lymph nodes (SLN) from breast cancer patients.

SUMMARY BACKGROUND DATA

Intraoperative analysis for the presence of metastatic cancer in SLNs from breast cancer patients lacks sensitivity. Even with immunohistochemical staining (IHC) and time-consuming review, alarming discordance in the interpretation of SLN has been observed.

METHOD

A total of 43 potential markers were evaluated for the ability to accurately characterize lymph node specimens from breast cancer patients as compared with complete histologic analysis including IHC. Selected markers then underwent external validation on 90 independent SLN specimens using rapid, multiplex quantitative reverse transcription-polymerase chain reaction (QRT-PCR) assays. Finally, 18 SLNs were analyzed using a completely automated RNA isolation, reverse transcription, and quantitative PCR instrument (GeneXpert).

RESULTS

: Following analysis of potential markers, promising markers were evaluated to establish relative level of expression cutoff values that maximized classification accuracy. A validation set of 90 SLNs from breast cancer patients was prospectively characterized using 4 markers individually or in combinations, and the results compared with histologic analysis. A 2-marker assay was found to be 97.8% accurate (94% sensitive, 100% specific) compared with histologic analysis. The fully automated GeneXpert instrument produced comparable and reproducible results in less than 35 minutes.

CONCLUSIONS

A rapid, fully automated QRT-PCR assay definitively characterizes breast cancer SLN with accuracy equal to conventional pathology. This approach is superior to intraoperative SLN analysis and can provide standardized, objective results to assist in pathologic diagnosis.

The value of immunohistochemistry in sentinel lymph node histopathology in breast cancer

The optimal protocol for the histopathological examination of sentinel lymph nodes (SLNs) in breast cancer has not been determined. The value of more detailed examination using immunohistochemistry (IHC) is controversial. A total of 476 SLNs from 216 patients were reviewed. Sentinel lymph nodes were sectioned at three levels at 100 μm intervals and stained with haematoxylin and eosin (H&E). If the H&E sections showed no evidence of metastasis, then the three serial sections were stained with a murine monoclonal anti-cytokeratin antibody (CAM 5.2). Metastatic deposits were classified as macrometastasis (>2.0 mm), micrometastasis (0.2–2.0 mm) or isolated tumour cells (ITC, <0.2 mm). Of the 216 patients, 56 (26%) had metastasis as identified by H&E. Immunohistochemistry detected metastatic deposits in a further nine patients (4%), of whom four (2%) had micrometastasis and five (2%) had ITC only. Those cases with micrometastases were all, on review, visible on the H&E sections. Immunohistochemistry detects only a small proportion of metastasis in SLNs. All metastatic deposits identified by IHC were either micrometastasis or ITC. Until the prognostic significance of these deposits has been determined, IHC may be of limited value in the histopathological examination of SLNs.

The prevalence of non-sentinel node metastases in breast cancer patients with sentinel node micrometastases

AIMS

The aim of the study was to estimate the prevalence of and risk factors for non-sentinel node (NSN) involvement in breast cancer patients with sentinel node (SN) micrometastases.

METHODS

Eighty-four patients with SN micrometastases were included. Both the SN and NSN were examined using serial sectioning and immunohistohemistry. Various indices were evaluated as possible risk factors for NSN involvement.

RESULTS

NSN involvement was found in 22/84 patients. The median size of the NSN metastases was 1.25 mm (0.01-12 mm). The NSN metastases were larger than 2 mm in 8 patients and smaller than 0.2 mm in 6 patients. NSN involvement was observed in 14/35 patients with metastatic findings in all removed SN. Three of the 23 patients with 2 or 3 tumour negative SN had NSN metastases. None of the 12 patients with 4 or more uninvolved SN had NSN metastases. NSN involvement could not excluded by other patient, tumour or sentinel node related factors.

CONCLUSIONS

Every fourth patient will have residual disease in the axilla, 10% even large metastases, if axillary clearance is omitted in patients with SN micrometastases. The risk of NSN involvement seems negligible in patients with a single SN micrometastasis and four or more healthy SN harvested.

Molecular Staging of Lymph Nodes from Patients with Esophageal Adenocarcinoma

Purpose: This study was designed to evaluate molecular markers for the detection of micrometastasis in esophageal adenocarcinoma, define algorithms to distinguish positive from benign lymph nodes and to validate these findings in an independent tissue set and in patients with pN0 esophageal adenocarcinoma.

Experimental Design: Potential markers were identified through literature and database searches. All markers were analyzed by quantitative reverse transcription (QRT)-PCR on a limited set of primary tumors and benign lymph nodes. Selected markers were further evaluated on a larger tissue set and classification algorithms were generated for individual markers and combinations. Algorithms were statistically validated internally as well as externally on an independent set of lymph nodes. Selected markers were then used to identify occult disease in lymph nodes from 34 patients with pN0 esophageal adenocarcinoma.

Results: Thirty-nine markers were evaluated, six underwent further analysis and five were analyzed in the external validation study. Two markers provided perfect classification in both the screening and validation sets, although parametric bootstrap analysis estimated 2% to 3% optimism in the observed classification accuracy. Several marker combinations also gave perfect classification in the observed data sets, and estimates of optimism were lower, implying more robust classification than with individual markers alone. Five of thirty-four patients with esophageal adenocarcinoma had positive nodes by multimarker QRT-PCR analysis and disease-free survival was significantly worse in these patients (P = 0.0023).

Conclusions: We have identified novel QRT-PCR markers for the detection of occult lymph node disease in patients with esophageal adenocarcinoma. The objective nature of QRT-PCR results, and the ability to detect occult metastases, make this an attractive alternative to routine pathology.

Improving the reproducibility of diagnosing micrometastases and isolated tumor cells

BACKGROUND

The latest edition of the tumor-lymph node-metastasis (TNM) classification of malignant tumors distinguishes between isolated tumor cells (pN0) and micrometastases (pN1mi). The reproducibility of these categories has not been assessed previously.

METHODS

Digital images from 50 cases with low-volume lymph node involvement from axillary sentinel lymph nodes were circulated twice for evaluation (Evaluation Rounds 1 and 2) among the members of the European Working Group for Breast Screening Pathology, and the members were asked to categorize lesions as micrometastasis, isolated tumor cells, or something else and to classify each case into a pathologic lymph node (pN) category of the pathologic TNM system. Methods for improving the low reproducibility of the categorizations were discussed between the two evaluation rounds. kappa Statistics were used for the assessment of interobserver variability.

RESULTS

The kappa value for the consistency of categorizing low-volume lymph node load into micrometastasis, isolated tumor cells, or neither of those changed from 0.39 to 0.49 between Evaluation Rounds 1 and 2, but it was slightly lower for the pN categories (0.35 and 0.44, respectively). Interpretation of the definitions of isolated tumor cells (especially with respect to their localization within the lymph node), lack of guidance on how to measure them if they were multiple, and lack of any definitions for multiple simultaneous foci of lymph node involvement were listed among the causes of discordant diagnoses.

CONCLUSIONS

The results of the current study indicated that the definitions available have minor contradictions and do not permit a reproducible distinction between micrometastases and isolated tumor cells. Refinement of these definitions, therefore, is required. One refinement that may improve reproducibility is suggested in this report.