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Linear tumor size (T-size) estimated with conventional histology informs breast cancer management. Previously we demonstrated significant differences in margin and focality estimates using conventional histology versus digital whole-mount serial sections (WMSS). Using WMSS we can measure T-size or volume. Here, we compare WMSS T-size with volume, and with T-size measured conventionally. We also compare the ellipsoid model for calculating tumor volume to direct, WMSS measurement. Two pathologists contoured regions of invasive carcinoma and measured T-size from both WMSS and (simulated) conventional sections in 55 consecutive lumpectomy specimens. Volume was measured directly from the contours. Measurements were compared using the paired t-test or Spearman’s rank-order correlation. A five-point ‘border index’ was devised and assigned to each case to parametrize tumor shape considering ‘compactness’ or cellularity. Tumor volumes calculated assuming ellipsoid geometry were compared with direct, WMSS measurements. WMSS reported significantly larger T-size than conventional histology in the majority of cases [61.8%, 34/55; means = (2.34 cm; 1.99 cm), p

Background Obtaining precise histopathologic detail for breast lumpectomy specimens is challenging due to extensive sampling and loss of 3-dimensional conformation with conventional methods. Whole-mount (WM) technique is a method of serial pathologic sectioning designed to maximize cross-sectional visualization, and enhance evaluation of margin status. Methods A decision analytic model was used to create a budget impact analysis comparing costs and outcomes for conventional processing and WM technique for breast lumpectomy specimens. Outcomes included additional operations, time required for processing and pathology interpretation, and the number of slides produced. Cost trade-offs were compared using incremental cost-effectiveness ratios, and a 3-year cost forecast was generated to estimate institutional expenditures required for variable adoption of the WM process. Deterministic and probabilistic sensitivity analyses were performed. Costs are reported in Canadian dollars and are 2014 appraisals. Results WM technique has a higher mean cost per patient ($3218) compared to conventional processing ($1414) and generates 19% more operations due to detection of positive margins. The number of pathology slides produced and pathologist hours required for interpretation were reduced with WM technique. WM costs an additional $9495 per extra operation completed but is forecasted to save approximately 1200 pathologist work hours over 3 years. The model was robust to tested ranges and most sensitive to changes in positive margin prevalence. Conclusion The initiation of routine WM processing for breast lumpectomy specimens is costly. However, favourable tradeoffs in diagnostic accuracy and histopathologic efficiency underpin the need to deliberately consider the adoption of WM technique.

In the process of developing a multiplex of 8 common breast cancer biomarkers (Her2/neu, estrogen receptor, progesterone receptor, Ki-67, aldehyde dehydrogenase-1, Na+K+-ATPase, cytokeratin 8/18, and myosin smooth muscle) on a single formalin-fixed paraffin-embedded slide using a sequential staining, imaging, and dye bleaching technology developed by General Electric Company, membranous Ki-67 staining was observed and colocalized with Her2/neu staining. Using immunohistochemistry as gold standards, we discovered that membranous Ki-67 was an artifact caused by the binding of cyanine 5-conjugated rabbit polyclonal Ki-67 antibody to a secondary cyanine 3-conjugated donkey anti-rabbit antibody which was previously applied and bound to rabbit Her2/neu antibody in our multiplexing experiment. After blocking with rabbit serum, a successful protocol for 8 biomarker multiplexing without cross-reactivity of antibodies from the same species was developed.

Aims Technical limitations in conventional pathological evaluation of breast lumpectomy specimens may reduce diagnostic accuracy in the assessment of margin and focality. A novel technique based on whole-mount serial sections enhances sampling while preserving specimen conformation and orientation. The aim of this study was to investigate assessment of focality and margin status by the use of whole-mount serial sections versus simulated conventional sections in lumpectomies. Methods and results Two pathologists interpreted whole-mount serial sections and simulated conventional sections for 58 lumpectomy specimens by reporting the closest margin and focality. Measurements were compared by the use of McNemar's chi-squared test. Statistically significant differences were observed in the assignment of both margin positivity (P = 0.014) and multifocality (P = 0.021). A positive margin or multifocal disease was identified by the use of whole-mount serial sections but missed in the simulated conventional assessment in 10.3% and 17.2% of all cases, respectively. There was no case in which a positive margin was detected only in the simulated conventional assessment. Conclusions The whole-mount technique is more sensitive than conventional assessment for identifying a positive margin or multifocal disease in breast lumpectomy specimens. Undersampling in conventional sections was implicated in almost all cases of discordance. The majority of positive margins or secondary foci identified only in whole-mount serial sections concerned in-situ disease.

Obtaining accurate histopathologic detail for breast lumpectomy specimens is challenging because of sampling and loss of three-dimensional conformational features with conventional processing. The whole-mount (wm) technique is a novel method of serial pathologic sectioning designed to optimize cross-sectional visualization of resected specimens and determination of margin status. Using a Markov chain cohort simulation cost-effectiveness model, we compared conventional processing with wm technique for breast lumpectomies. Cost-effectiveness was evaluated from the perspective of the Canadian health care system and compared using incremental cost-effectiveness ratios (icers) for cost per quality-adjusted life&ndash, year (qaly) over a 10-year time horizon. Deterministic and probabilistic sensitivity analyses were performed to test the robustness of the model with willingness-to-pay (wtp) thresholds of $0&ndash, $100,000. Costs are reported in adjusted 2014 Canadian dollars, discounted at a rate of 3%. Compared with conventional processing, wm processing is more costly ($19,989 vs. $18,427) but generates 0.03 more qalys over 10 years. The icer is $45,414, indicating that this additional amount is required for each additional qaly obtained. The model was robust to all variance in parameters, with the prevalence of positive margins accounting for most of the model&rsquo, s variability. After a wtp threshold of $45,414, wm processing becomes cost-effective and ultimately generates fewer recurrences and marginally more qalys over time. Excellent baseline outcomes for the current treatment of breast cancer mean that incremental differences in survival are small. However, the overall benefit of the wm technique should be considered in the context of achieving improved accuracy and not just enhancements in clinical effectiveness.

Tumour size, most commonly measured by maximum linear extent, remains a strong predictor of survival in breast cancer. Tumour volume, proportional to the number of tumour cells, may be a more accurate surrogate for size. We describe a novel “3D pathology volumetric technique” for lumpectomies and compare it with 2D measurements. Volume renderings and total tumour volume are computed from digitized whole-mount serial sections using custom software tools. Results are presented for two lumpectomy specimens selected for tumour features which may challenge accurate measurement of tumour burden with conventional, sampling-based pathology: (1) an infiltrative pattern admixed with normal breast elements; (2) a localized invasive mass separated from thein situcomponent by benign tissue. Spatial relationships between key features (tumour foci, close or involved margins) are clearly visualized in volume renderings. Invasive tumour burden can be underestimated using conventional pathology, compared to the volumetric technique (infiltrative pattern: 30% underestimation; localized mass: 3% underestimation for invasive tumour, 44% for in situ component). Tumour volume approximated from 2D measurements (i.e., maximum linear extent), assuming elliptical geometry, was seen to overestimate volume compared to the 3D volumetric calculation (by a factor of 7x for the infiltrative pattern; 1.5x for the localized invasive mass).

Conventional histopathological evaluation is performed on breast specimens using a highly limited sampling of tissues visualized in a two-dimensional (2D) manner although important tumor measurements are three-dimensional. Here we describe a ‘3D’ technique for whole-mount, whole-specimen processing which reduces conformational change and dramatically increases specimen coverage, based on digitizing whole-specimen, whole-mount (up to 12.7 cm × 17.8 cm) serial sections. We describe hardware and software tools for acquiring, viewing and processing the large image datasets (up to 400 GB), validation studies investigating the clinical significance of the additional information gleaned from the 3D approach, and application to radiologic-pathologic correlation and biomarker visualization.

Clarke G M, Peressotti C, Holloway C M B, Zubovits J T, Liu K & Yaffe M J (2011) Histopathology59, 116–128 Development and evaluation of a robust algorithm for computer-assisted detection of sentinel lymph node micrometastases Aims: Increasing the sectioning rate for breast sentinel lymph nodes can increase the likelihood of detecting micrometastases. To make serial sectioning feasible, we have developed an algorithm for computer-assisted detection (CAD) with digitized lymph node sections. Methods and results: K-means clustering assigned image pixels to one of four areas in a colourspace (representing tumour, unstained background, counterstained background and microtomy artefacts). Four filters then removed ‘false-positive’ pixels from the tumour cluster. A set of 43 sections containing tumour (a total of 259 foci) and 59 sections negative for malignancy was defined by two pathologists, using light microscopy, and CAD was applied. For the clinically relevant task of identifying the largest focus in each section (micrometastasis in 22/43 sections), the sensitivity and specificity were 100%. Isolated tumour cells (ITCs) were identified in one slide initially considered to be negative. Identification of all 259 foci yielded sensitivities of 57.5% for ITCs (

Aims: To develop a method for preparing diagnostic-quality, whole-mount serial sections of breast specimens while preserving 3-D conformation. This required supporting the fresh specimen prior to breadloafing and refining the conventional tissue processing method. The overall goal is to use digital images of whole-specimen histopathology to improve the estimation of extent of disease. Methods and results: To maintain a 3-D conformation, the specimen is suspended in 3.5% agar at 55°C. The block is sliced at 5-mm intervals. Sectioning is performed after extended fixation in 4% formaldehyde from paraformaldehyde in 0.1 m Millonig's buffer, followed by paraffin processing using a non-routine schedule and extended paraffin infiltration. Whole-mount serial breast sections are produced with features of equal or superior quality to that which can be achieved using conventional methods. The method is compatible with some immunohistochemical stains but requires further optimization for others. Conclusions: The technique is currently suitable for research applications. With the reduction in processing time achievable with microwave-assisted processing, there is the potential for its use as a routine clinical method. This tool may improve the accuracy of margin estimates and identification of multifocality in breast cancer; further evaluation is necessary.

Purpose: Pathologists often look at whole slide images (WSIs) at low magnification to find potentially important regions and then zoom in to higher magnification to perform more sophisticated analysis of the tissue structures. Many automated methods of WSI analysis attempt to preprocess the down-sampled image in order to select salient regions which are then further analyzed by a more computationally intensive step at full magnification. Although it can greatly reduce processing times, this process may lead to small potentially important regions being overlooked at low magnification. We propose a texture analysis technique to ease the processing of H&E stained WSIs by triaging clinically important regions. Method: Image patches randomly selected from the whole tissue area were divided into smaller tiles and Gaussian-like texture filters were applied to them. Texture filter responses from each tile were combined together and statistical measures were derived from their histograms of responses. Bag of visual words pipeline was then employed to combine extracted features from tiles to form one histogram of words per every image patch. A support vector machine classifier was trained using the calculated histograms of words to be able to distinguish between clinically relevant and irrelevant patches. Result: Experimental analysis on 5151 image patches from 10 patient cases (65 tissue slides) indicated that our proposed texture technique out-performed two previously proposed colour and intensity based methods with an area under the ROC curve of 0.87. Conclusion: Texture features can be employed to triage clinically important areas within large WSIs.

Purpose: Completely labeled datasets of pathology slides are often difficult and time consuming to obtain. Semi-supervised learning methods are able to learn reliable models from small number of labeled instances and large quantities of unlabeled data. In this paper, we explored the potential of clustering analysis for semi-supervised support vector machine SVM classifier. Method: A clustering analysis method was proposed to find regions of high density prior to finding the decision boundary using a supervised SVM and was compared with another state-of-the-art semi-supervised technique. Different percentages of labeled instances were used to train supervised and semi-supervised SVM learners from an image dataset generated from 50 whole-mount images 8 patients of breast specimen. Their cross-validated classification performances were compared with each other using the area under the ROC curve measure. Result: Our proposed clustering analysis for semi-supervised learning was able to produce a reliable classification model from small amounts of labeled data. Comparing the proposed method in this study with a well-known implementation of semi-supervised SVM, our method performed much faster and produced better results.

Aims Multiplexed immunofluorescence is a powerful tool for validating multigene assays and understanding the complex interplay of proteins implicated in breast cancer within a morphological context. We describe a novel technology for imaging an extended panel of biomarkers on a single, formalin-fixed paraffin-embedded breast sample and evaluating biomarker interaction at a single-cell level, and demonstrate proof-of-concept on a small set of breast tumours, including those which co-express hormone receptors with Her2/neu and Ki-67. Methods and results Using a microfluidic flow cell, reagent exchange was automated and consisted of serial rounds of staining with dye-conjugated antibodies, imaging and chemical deactivation. A two-step antigen retrieval process was developed to satisfy all epitopes simultaneously, and key parameters were optimized. The imaging sequence was applied to seven breast tumours, and compared with conventional immunohistochemistry. Single-cell correlation analysis was performed with automated image processing. Conclusions We have described a novel platform for evaluating biomarker co-localization. Expression in multiplexed images is consistent with conventional immunohistochemistry. Automation reduces inconsistencies in staining and positional shifts, while the fluorescent dye cycling approach dramatically expands the number of biomarkers which can be visualized and quantified on a single tissue section.

To develop and validate improved processing methods for producing diagnostic-quality, whole-mount serial sections for 3-dimensional imaging of wholebreast histopathologic studies, we subjected 4-mm-thick whole-specimen slices to a 38-hour microwave-assisted protocol. Morphologic features, antigenicity, and tissue shrinkage were evaluated. A schedule using the tissue processor was optimized by evaluating the serial section yield for 3 schedules. The microwave-based processing schedule is adequate for producing diagnostic-quality whole-mount breast serial sections of an area up to 6,000 mm 2 and is compatible with a variety of immunohistochemical stains. A mean ± SE total tissue shrinkage of 8.4% ± 0.2% resulted. For the tissue processor, optimal results are obtained using a 59-hour schedule. Total fixation and processing time for wholemount serial breast sections has been reduced from 21 days to 38 hours, with microwave assistance, and to 59 hours without. No adverse effects of microwaves on morphologic features, antigenicity, or gross tissue dimensions were observed. Compared with current sampling techniques used in histopathology, 3-dimensional (3-D) histopathology imaging of whole breast specimens could provide a powerful tool to enable more accurate assessment of surgical accuracy, through evaluation of specimen margins. It can also be used to provide a more complete and true visualization of the 3-D nature of the extent and focality of disease.

Tumour size is an important prognostic indicator in breast cancer. This is typically measured as a simple linear diameter, although tumour volume may be a better surrogate of tumour burden. We have been optimizing techniques for three-dimensional histopathology based on digital scanning light microscopy of whole-mount, whole-specimen serial sections. We apply this to validate tumour volume measurements obtained using specimen cone-beam CT imaging. We demonstrate initial results for this technique using one lumpectomy and then show examples of how this technique can serve as a `gateway' to validating emerging functional and molecular imaging modalities.

We examined the effect of lateral spatial resolution and reader specialty on the accuracy of detection of breast cancer. The motivation for this pilot study was the need to acquire and display very large data sets in whole-specimen 3D digital breast histopathology imaging. The ultimate goal is to determine the minimum resolution adequate for detection of malignancy. Twenty-three histologic slides were selected from breast pathology cases and digitized at 2 sampling distances (3.2 and 1.9 microm pixels). Images were viewed by 14 pathologists, of whom 5 had breast pathology as their primary specialty. The readers assessed the likelihood of malignancy on a 5-point Likert scale, and provided a provisional diagnosis. For the detection task, sensitivity, specificity, overall accuracy of detection, and area under the receiver-operator curve were calculated. An overall diagnostic score, and scores grouped by malignancy type, were also computed. Outcome measures were examined for significant resolution and specialty effects. Increasing the lateral resolution significantly improved accuracy in diagnosis (P=.004) but no effect was found for detection. Breast specialists achieved significantly higher scores for all outcome measures except specificity. Differences in performance between the 2 groups of readers tended to be greater for the diagnostic task compared to detection, especially at the higher resolution. However, specimen coverage may also be a significant factor. Factors related to the readers may have also affected performance in this study. Based on these results, a more comprehensive study should examine pixel sizes between 0.7 and 1.9 microm.

We have developed a digital histopathology imaging system capable of producing a three-dimensional (3D) representation of histopathology from an entire lumpectomy specimen. The system has the potential to improve the accuracy of surgical margin assessment in the treatment of breast cancer by providing finer sampling and 3D visualization. A scanning light microscope was modified to allow digital photomicrography of a stack of large (up to 120x170 mm2) histology slides cut serially through the entire specimen. The images are registered and displayed in 2D and 3D. The design of the system, which reduces or eliminates the appearance of 'tiling' and 'seam' artefacts inherent in the scanning method, is described and its resolution, contrast/noise and coverage properties are characterized through measurements of the modulation transfer function (MTF), depth of field (DOF) and signal difference to noise ratio (SDNR). The imaging task requires a lateral resolution of 5 microm, an SDNR of 5 between relevant features, 'tiling artefact' at a level below the detectability threshold of the eye, and 'seam artefact' of less than 5-10 microm. The tests demonstrate that the system is largely adequate for the imaging task, although further optimizations are required to reduce the degradation of coverage incurred by seam artefact.

We have developed a digital histology imaging system that has the potential to improve the accuracy of surgical margin assessment in the treatment of breast cancer by providing finer sampling and 3D visualization. The system is capable of producing a 3D representation of histopathology from an entire lumpectomy specimen. We acquire digital photomicrographs of a stack of large (120 x 170 mm) histology slides cut serially through the entire specimen. The images are then registered and displayed in 2D and 3D. This approach dramatically improves sampling and can improve visualization of tissue structures compared to current, small-format histology. The system consists of a brightfield microscope, adapted with a freeze-frame digital video camera and a large, motorized translation stage. The image of each slide is acquired as a mosaic of adjacent tiles, each tile representing one field-of-view of the microscope, and the mosaic is assembled into a seamless composite image. The assembly is done by a program developed to build image sets at six different levels within a multiresolution pyramid. A database-linked viewing program has been created to efficiently register and display the animated stack of images, which occupies about 80 GB of disk space per lumpectomy at full resolution, on a high-resolution (3840 x 2400 pixels) colour monitor. The scanning or tiling approach to digitization is inherently susceptible to two artefacts which disrupt the composite image, and which impose more stringent requirements on system performance. Although non-uniform illumination across any one isolated tile may not be discernible, the eye readily detects this non-uniformity when the entire assembly of tiles is viewed. The pattern is caused by deficiencies in optical alignment, spectrum of the light source, or camera corrections. The imaging task requires that features as small as 3.2 mm in extent be seamlessly preserved. However, inadequate accuracy in positioning of the translation stage produces visible discontinuities between adjacent features. Both of these effects can distract the viewer from the perception of diagnostically important features. Here we describe the system design and discuss methods for the correction of these artefacts. In addition, we outline our approach to rendering the processing and display of these large images computationally feasible.