51 research outputs found

    Transitioning between Convolutional and Fully Connected Layers in Neural Networks

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    Digital pathology has advanced substantially over the last decade however tumor localization continues to be a challenging problem due to highly complex patterns and textures in the underlying tissue bed. The use of convolutional neural networks (CNNs) to analyze such complex images has been well adopted in digital pathology. However in recent years, the architecture of CNNs have altered with the introduction of inception modules which have shown great promise for classification tasks. In this paper, we propose a modified "transition" module which learns global average pooling layers from filters of varying sizes to encourage class-specific filters at multiple spatial resolutions. We demonstrate the performance of the transition module in AlexNet and ZFNet, for classifying breast tumors in two independent datasets of scanned histology sections, of which the transition module was superior.Comment: This work is to appear at the 3rd workshop on Deep Learning in Medical Image Analysis (DLMIA), MICCAI 201

    Is Ductal Carcinoma In Situ With “Possible Invasion” More Predictive of Invasive Carcinoma Than Pure Ductal Carcinoma In Situ?

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    AbstractObjectivesTo compare the underestimation of ductal carcinoma in situ (DCIS) vs DCIS with “possible invasion” at breast biopsy and to determine if any factors related to clinical indication, imaging abnormality, biopsy, or DCIS-grade affected the likelihood of underestimation.MethodsOf 3836 consecutive lesions that were biopsied by using a 14-gauge needle, 117 lesions revealed DCIS. Surgical pathology results of invasive carcinoma were compared with needle biopsy results of DCIS or DCIS with possible invasion. Clinical indication, imaging abnormality, biopsy guidance modality, sample number, and histologic grade were recorded. Yates corrected χ2 and Fisher exact tests were used to determine differences between groups.ResultsA total of 101 lesions were DCIS and 16 were DCIS with possible invasion at biopsy. Thirty-six of 117 lesions (31%) revealed invasive carcinoma at resection pathology. Invasive carcinoma was present more often when DCIS with possible invasion was diagnosed compared with pure DCIS (7/16 [44%] vs 29/101 [29%], P = .36). No factor, including clinical indication, imaging abnormality, biopsy guidance method, sample number, or grade, was found to significantly affect the likelihood of underestimation for lesions diagnosed as DCIS vs DCIS with “possible invasion.” The likelihood of pure DCIS underestimation significantly increased when lesions were high grade compared with either intermediate or low grade (18/44 [41%] vs 9/44 [21%] vs 2/10 [20%], P = .03).ConclusionFor lesions biopsied by using a 14-gauge needle, there is a trend towards underestimation of the presence of invasive carcinoma when pathology reveals DCIS with possible invasion compared with pure DCIS. High-grade DCIS was significantly more likely to be underestimated

    Biological Markers Predictive of Invasive Recurrence in DCIS

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    DCIS is a heterogeneous group of non-invasive cancers of the breast characterized by various degrees of differentiation and unpredictable propensity for transformation into invasive carcinoma. We examined the expression and prognostic value of 9 biological markers with a potential role in tumor progression in 133 patients with pure DCIS treated with breast conserving surgery alone, between 1982–2000. Histology was reviewed and immunohistochemical staining was performed. Pearson correlation coefficient was used to determine the associations between markers and histopathological features. Univariate and multivariate analysis examined associations between time to recurrence and clinicopathologic features and biological markers

    Analytical validation of a standardised scoring protocol for Ki67 immunohistochemistry on breast cancer excision whole sections: an international multicentre collaboration

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    Aims The nuclear proliferation marker Ki67 assayed by immunohistochemistry has multiple potential uses in breast cancer, but an unacceptable level of interlaboratory variability has hampered its clinical utility. The International Ki67 in Breast Cancer Working Group has undertaken a systematic programme to determine whether Ki67 measurement can be analytically validated and standardised among laboratories. This study addresses whether acceptable scoring reproducibility can be achieved on excision whole sections. Methods and results Adjacent sections from 30 primary ER+ breast cancers were centrally stained for Ki67 and sections were circulated among 23 pathologists in 12 countries. All pathologists scored Ki67 by two methods: (i) global: four fields of 100 tumour cells each were selected to reflect observed heterogeneity in nuclear staining; (ii) hot-spot: the field with highest apparent Ki67 index was selected and up to 500 cells scored. The intraclass correlation coefficient (ICC) for the global method [confidence interval (CI) = 0.87; 95% CI = 0.799-0.93] marginally met the prespecified success criterion (lower 95% CI >= 0.8), while the ICC for the hot-spot method (0.83; 95% CI = 0.74-0.90) did not. Visually, interobserver concordance in location of selected hot-spots varies between cases. The median times for scoring were 9 and 6 min for global and hot-spot methods, respectively. Conclusions The global scoring method demonstrates adequate reproducibility to warrant next steps towards evaluation for technical and clinical validity in appropriate cohorts of cases. The time taken for scoring by either method is practical using counting software we are making publicly available. Establishment of external quality assessment schemes is likely to improve the reproducibility between laboratories further

    Analytical validation of a standardized scoring protocol for Ki67: phase 3 of an international multicenter collaboration

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    Pathological analysis of the nuclear proliferation biomarker Ki67 has multiple potential roles in breast and other cancers. However, clinical utility of the immunohistochemical (IHC) assay for Ki67 immunohistochemistry has been hampered by unacceptable between-laboratory analytical variability. The International Ki67 Working Group has conducted a series of studies aiming to decrease this variability and improve the evaluation of Ki67. This study tries to assess whether acceptable performance can be achieved on prestained core-cut biopsies using a standardized scoring method. Sections from 30 primary ER+ breast cancer core biopsies were centrally stained for Ki67 and circulated among 22 laboratories in 11 countries. Each laboratory scored Ki67 using three methods: (1) global (4 fields of 100 cells each); (2) weighted global (same as global but weighted by estimated percentages of total area); and (3) hot-spot (single field of 500 cells). The intraclass correlation coefficient (ICC), a measure of interlaboratory agreement, for the unweighted global method (0.87; 95% credible interval (CI): 0.81–0.93) met the prespecified success criterion for scoring reproducibility, whereas that for the weighted global (0.87; 95% CI: 0.7999–0.93) and hot-spot methods (0.84; 95% CI: 0.77–0.92) marginally failed to do so. The unweighted global assessment of Ki67 IHC analysis on core biopsies met the prespecified criterion of success for scoring reproducibility. A few cases still showed large scoring discrepancies. Establishment of external quality assessment schemes is likely to improve the agreement between laboratories further. Additional evaluations are needed to assess staining variability and clinical validity in appropriate cohorts of samples

    EMT in Breast Carcinoma—A Review

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    The epithelial to mesenchymal transition (EMT) is a cellular program that is involved in embryonic development; wound healing, but also in tumorigenesis. Breast carcinoma (BC) is the most common cancer in women worldwide, and the majority of deaths (90%) are caused by invasion and metastasis. The EMT plays an important role in invasion and subsequent metastasis. Several distinct biological events integrate a cascade that leads not only to a change from an epithelial to mesenchymal phenotype, but allows for detachment, migration, invasion and ultimately, colonization of a second site. Understanding the biological intricacies of the EMT may provide important insights that lead to the development of therapeutic targets in pre-invasive and invasive breast cancer, and could be used as biomarkers identifying tumor subsets with greater chances of recurrence, metastasis and therapeutic resistance leading to death

    Automatic cellularity assessment from post-treated breast surgical specimens

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    Neoadjuvant treatment (NAT) of breast cancer (BCa) is an option for patients with the locally advanced disease. It has been compared with standard adjuvant therapy with the aim of improving prognosis and surgical outcome. Moreover, the response of the tumor to the therapy provides useful information for patient management. The pathological examination of the tissue sections after surgery is the gold-standard to estimate the residual tumor and the assessment of cellularity is an important component of tumor burden assessment. In the current clinical practice, tumor cellularity is manually estimated by pathologists on hematoxylin and eosin (H&E) stained slides, the quality, and reliability of which might be impaired by inter-observer variability which potentially affects prognostic power assessment in NAT trials. This procedure is also qualitative and time-consuming. In this paper, we describe a method of automatically assessing cellularity. A pipeline to automatically segment nuclei figures and estimate residual cancer cellularity from within patches and whole slide images (WSIs) of BCa was developed. We have compared the performance of our proposed pipeline in estimating residual cancer cellularity with that of two expert pathologists. We found an intra-class agreement coefficient (ICC) of 0.89 (95% CI of [0.70, 0.95]) between pathologists, 0.74 (95% CI of [0.70, 0.77]) between pathologist #1 and proposed method, and 0.75 (95% CI of [0.71, 0.79]) between pathologist #2 and proposed method. We have also successfully applied our proposed technique on a WSI to locate areas with high concentration of residual cancer. The main advantage of our approach is that it is fully automatic and can be used to find areas with high cellularity in WSIs. This provides a first step in developing an automatic technique for post-NAT tumor response assessment from pathology slides. © 2017 International Society for Advancement of Cytometry.Canadian Cancer Society (grant # 703006); National Institutes of Health (grant number U24CA199374-01)

    Retroperitoneal Extraovarian Fibrothecoma Mimicking a Malignant Epithelial Ovarian Carcinoma

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    Background. Fibrothecomas are benign sex cord-stromal tumors which rarely originate outside of the ovary. To date, two such cases have been reported in the literature. We report the third case of an extraovarian fibrothecoma and the first presenting similarly to a metastatic epithelial ovarian cancer. Clinical History. We describe a 62-year-old woman with history, physical examination, and imaging suggestive of metastatic ovarian cancer. CA-125 was elevated at 1291 U/mL. Paracenteses were negative for malignant cells and core biopsy showed spindle cell proliferation. A primary debulking surgery for a presumed ovarian cancer was planned. Method and Results. At surgery, 6 liters of ascites were drained. The uterus, ovaries, peritoneum, and omentum were normal. An 18×11×7 cm retroperitoneal mass was found between the left ureter and the sigmoid mesocolon, wrapped with sigmoid colon. Fallopian tubes and ovaries were normal. The mass was resected en bloc with the sigmoid colon, uterus, ovaries, and omentum. Microscopically, there was spindle cell proliferation typical of fibrothecoma. No ovarian tissue was identified in association with the tumor. Conclusion. This third case of extraovarian fibrothecoma highlights the importance of obtaining histologic evidence of malignancy prior to initiating neoadjuvant chemotherapy for a presumed ovarian cancer.Peer Reviewe
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