Importância da segunda opinião em patologia cirúrgica mamária e suas implicações terapêuticas

Salles, M; Sanches, Fernanda Squárcio Fernandes; Perez, Amanda Arantes; Gobbi, Helenice

doi:10.1590/s0100-72032008001200003

Cited by 6 publications

(5 citation statements)

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“…Other groups have reported inter-rater kappa statistics of 0.6–0.7 for tumor grade, 18,19 in line with both our inter-pathologist agreement and image analysis vs. pathologist agreement for grade. Elsewhere in the literature lower kappa values around 0.5 have been reported between pathologists for histologic grade.…”

Section: Discussionsupporting

confidence: 90%

Image analysis with deep learning to predict breast cancer grade, ER status, histologic subtype, and intrinsic subtype

et al. 2018

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RNA-based, multi-gene molecular assays are available and widely used for patients with ER-positive/HER2-negative breast cancers. However, RNA-based genomic tests can be costly and are not available in many countries. Methods for inferring molecular subtype from histologic images may identify patients most likely to benefit from further genomic testing. To identify patients who could benefit from molecular testing based on H&E stained histologic images, we developed an image analysis approach using deep learning. A training set of 571 breast tumors was used to create image-based classifiers for tumor grade, ER status, PAM50 intrinsic subtype, histologic subtype, and risk of recurrence score (ROR-PT). The resulting classifiers were applied to an independent test set (n = 288), and accuracy, sensitivity, and specificity of each was assessed on the test set. Histologic image analysis with deep learning distinguished low-intermediate vs. high tumor grade (82% accuracy), ER status (84% accuracy), Basal-like vs. non-Basal-like (77% accuracy), Ductal vs. Lobular (94% accuracy), and high vs. low-medium ROR-PT score (75% accuracy). Sampling considerations in the training set minimized bias in the test set. Incorrect classification of ER status was significantly more common for Luminal B tumors. These data provide proof of principle that molecular marker status, including a critical clinical biomarker (i.e., ER status), can be predicted with accuracy >75% based on H&E features. Image-based methods could be promising for identifying patients with a greater need for further genomic testing, or in place of classically scored variables typically accomplished using human-based scoring.

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Section: Discussionsupporting

confidence: 90%

Image analysis with deep learning to predict breast cancer grade, ER status, histologic subtype, and intrinsic subtype

et al. 2018

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“…evaluated the inter-observer variability among six pathologists who assessed 125 cases of DCIS and observed a better diagnostic agreement for high-grade DCIS [33,34]. The nuclear grade of DCIS is an important factor when determining the therapeutic approach because high nuclear-grade lesions are associated with a poor prognosis and are often associated with local recurrence and/or progression into invasive lesions, a greater chance of metastasis, and greater required care during local surgical procedures [4,28]. …”

Section: Discussionmentioning

confidence: 99%

“…Only 4.1% of cases were sent for consultation by pathologists. We believe that formal requests for second opinions regarding precursor and borderline breast lesions should be encouraged, especially amongst general pathologists, with the aim of reducing errors in diagnosis and thereby assuring appropriate therapeutic conduct and guaranteeing patient safety [4,5]. …”

Section: Discussionmentioning

confidence: 99%

“…Studies conducted by our group have revealed significant inter-observer variability between the diagnoses made by general pathologists and those made by breast pathology experts in the diagnosis for DCIS and ADH; this discrepancy could have significant therapeutic implications [4,5]. Although there have been various studies on the diagnostic agreement considering DCIS, few studies have analysed the diagnostic agreement considering LN and CCL [6,7].…”

Section: Introductionmentioning

confidence: 99%

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Inter-observer variability between general pathologists and a specialist in breast pathology in the diagnosis of lobular neoplasia, columnar cell lesions, atypical ductal hyperplasia and ductal carcinoma in situ of the breast

et al. 2014

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BackgroundThis study aimed to assess inter-observer variability between the original diagnostic reports and later review by a specialist in breast pathology considering lobular neoplasias (LN), columnar cell lesions (CCL), atypical ductal hyperplasia (ADH), and ductal carcinoma in situ (DCIS) of the breast.MethodsA retrospective, observational, cross-sectional study was conducted. A total of 610 breast specimens that had been formally sent for consultation and/or second opinions to the Breast Pathology Laboratory of Federal University of Minas Gerais were analysed between January 2005 and December 2010. The inter-observer variability between the original report and later review was compared regarding the diagnoses of LN, CCL, ADH, and DCIS. Statistical analyses were conducted using the Kappa index.ResultsWeak correlations were observed for the diagnoses of columnar cell change (CCC; Kappa = 0.38), columnar cell hyperplasia (CCH; Kappa = 0.32), while a moderate agreement (Kappa = 0.47) was observed for the diagnoses of flat epithelial atypia (FEA). Good agreement was observed in the diagnoses of atypical lobular hyperplasia (ALH; Kappa = 0.62) and lobular carcinoma in situ (LCIS; Kappa = 0.66). However, poor agreement was observed for the diagnoses of pleomorphic LCIS (Kappa = 0.22). Moderate agreement was observed for the diagnoses of ADH (Kappa = 0.44), low-grade DCIS (Kappa = 0.47), intermediate-grade DCIS (Kappa = 0.45), and DCIS with microinvasion (Kappa = 0.56). Good agreement was observed between the diagnoses of high-grade DCIS (Kappa = 0.68).ConclusionsAccording to our data, the best diagnostic agreements were observed for high-grade DCIS, ALH, and LCIS. CCL without atypia and pleomorphic LCIS had the worst agreement indices.Virtual SlidesThe virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1640072350119725.

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“…We used well-defined diagnostic criteria per Schnitt and Vincent-Salomon and noted fewer cases of CCC and CCH with atypia than what has been reported [10,11,33]. We believe that in many series and cases in our Breast Consulting Laboratory, FEA is being overdiagnosed, which could lead to the implementation of more aggressive treatments [34]. …”

Section: Discussionmentioning

confidence: 99%

Lobular neoplasia: frequency and association with other breast lesions

et al. 2011

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BackgroundUsing new molecular biology techniques, recent studies have implicated a common evolutionary pathway between lobular neoplasia, lobular carcinomas, and columnar cell lesions. Our aims were to assess the frequency of lobular neoplasia in a series of breast biopsies that were performed and examined in the same institution and to analyze the association between subtypes of lobular neoplasia and benign and malignant breast lesions.MethodsCases were selected after reviewing archived pathological reports in the Breast Pathology Laboratory, School of Medicine of Federal University of Minas Gerais (1999-2008). Cases of lobular neoplasia were reviewed and classified as atypical lobular hyperplasia, ductal involvement by cells of atypical lobular hyperplasia, lobular carcinoma in situ, and pleomorphic lobular carcinoma in situ. Coexistence of lobular neoplasia with other breast lesions, including columnar cell lesions, invasive ductal carcinoma and invasive lobular carcinoma, was evaluated. The association between lobular neoplasia and breast lesions was analyzed by Fisher's exact test and chi-square test for linear trend.ResultsWe analyzed 5650 breast specimens, selecting 135 breast specimens (2.4%) that had a diagnosis of lobular neoplasia, corresponding to 106 patients. Hematoxylin and eosin-stained slides were available for 84 cases, 5 of which were excluded because they contained only "indeterminate" in situ lesions. Of the 79 remaining cases, columnar cell lesions were present in 78.5%, primarily with columnar cell changes without atypia (67.7%). Invasive carcinoma was present in 45.6% of cases of lobular neoplasia--a similar frequency (47.2%) as invasive ductal carcinoma and invasive lobular carcinoma. We noted a significant linear trend (p < 0.03) of a higher frequency of invasive carcinomas that were concomitant with lobular carcinoma in situ compared with atypical lobular hyperplasia. Invasive lobular carcinomas were associated with lobular carcinoma in situ in 33% of cases, compared with 2.8% of atypical lobular hyperplasia cases.ConclusionsOur findings confirm a frequent association between lobular neoplasia and columnar cell lesions, the majority of which lacked atypia. We also observed a greater frequency of invasive carcinoma, more commonly invasive lobular carcinoma, associated with more developed forms of lobular neoplasia (lobular carcinoma in situ).

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Importância da segunda opinião em patologia cirúrgica mamária e suas implicações terapêuticas

Cited by 6 publications

References 0 publications

Image analysis with deep learning to predict breast cancer grade, ER status, histologic subtype, and intrinsic subtype

Image analysis with deep learning to predict breast cancer grade, ER status, histologic subtype, and intrinsic subtype

Inter-observer variability between general pathologists and a specialist in breast pathology in the diagnosis of lobular neoplasia, columnar cell lesions, atypical ductal hyperplasia and ductal carcinoma in situ of the breast

Lobular neoplasia: frequency and association with other breast lesions

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