Transitioning between Convolutional and Fully Connected Layers in Neural Networks

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?

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

Interobserver Agreement for Endometrial Cancer Characteristics Evaluated on Biopsy Material

A shift toward a disease-based therapy designed according to patterns of failure and likelihood of nodal involvement predicted by pathologic determinants has recently led to considering a selective approach to lymphadenectomy for endometrial cancer. Therefore, it became critical to examine reproducibility of diagnosing the key determinants of risk, on preoperative endometrial tissue samples as well as the concordance between preoperative and postresection specimens. Six gynaecologic pathologists assessed 105 consecutive endometrial biopsies originally reported as positive for endometrial cancer for cell type (endometrioid versus nonendometrioid), tumor grade (FIGO 3-tiered and 2-tiered), nuclear grade, and risk category (low risk defined as endometrioid histology, grade 1 + 2 and nuclear grade <3). Interrater agreement levels were substantial for identification of nonendometrioid histology (κ = 0.63; SE = 0.025), high tumor grade (κ = 0.64; SE = 0.025), and risk category (κ = 0.66; SE = 0.025). The overall agreement was fair for nuclear grade (κ = 0.21; SE = 0.025). There is agreement amongst pathologists in identifying high-risk pathologic determinants on endometrial cancer biopsies, and these highly correlate with postresection specimens. This is ascertainment prerequisite adaptation of the paradigm shift in surgical staging of patients with endometrial cancer

Biological Markers Predictive of Invasive Recurrence in DCIS

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

Advanced papillary serous carcinoma of the uterine cervix: a case with a remarkable response to paclitaxel and carboplatin combination chemotherapy

Papillary serous carcinoma of the uterine cervix (PSCC) is a very rare, recently described variant of cervical adenocarcinoma. This review, describes a case of stage IV PSCC whose main tumor existed in the uterine cervix and invaded one third of the inferior part of the anterior and posterior vaginal walls. Furthermore, it had metastasized from the para-aortic lymph nodes to bilateral neck lymph nodes. Immnoreactivity for CA125 was positive, whereas the staining for p53 and WT-1 were negative in both the original tumor and the metastatic lymph nodes. Six cycles of paclitaxel and carboplatin combination chemotherapy were administered and the PSCC dramatically decreased in size. The main tumor of the uterine cervix showed a complete response by magnetic resonance imaging (MRI), and on rebiopsy, more than 95% of the tumor cells in the cervix had microscopically disapperared. This is the first report of PSCC in which combination chemotherapy was used and showed a remarkable response

Refined estimates of local recurrence risks by DCIS score adjusting for clinicopathological features: a combined analysis of ECOG-ACRIN E5194 and Ontario DCIS cohort studies

Purpose Better tools are needed to estimate local recurrence (LR) risk after breast-conserving surgery (BCS) for DCIS. The DCIS score (DS) was validated as a predictor of LR in E5194 and Ontario DCIS cohort (ODC) after BCS. We combined data from E5194 and ODC adjusting for clinicopathological factors to provide refined estimates of the 10-year risk of LR after treatment by BCS alone. Methods Data from E5194 and ODC were combined. Patients with positive margins or multifocality were excluded. Identical Cox regression models were fit for each study. Patient-specific meta-analysis was used to calculate precision-weighted estimates of 10-year LR risk by DS, age, tumor size and year of diagnosis. Results The combined cohort includes 773 patients. The DS and age at diagnosis, tumor size and year of diagnosis provided independent prognostic information on the 10-year LR risk (p ≤ 0.009). Hazard ratios from E5194 and ODC cohorts were similar for the DS (2.48, 1.95 per 50 units), tumor size ≤ 1 versus > 1–2.5 cm (1.45, 1.47), age ≥ 50 versus 15%) 10-year LR risk after BCS alone compared to utilization of DS alone or clinicopathological factors alone. Conclusions The combined analysis provides refined estimates of 10-year LR risk after BCS for DCIS. Adding information on tumor size and age at diagnosis to the DS adjusting for year of diagnosis provides improved LR risk estimates to guide treatment decision making

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

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