Workload Of Pathologists Research Articles

Quantum Cascade Laser Spectral Histopathology: Breast Cancer Diagnostics Using High Throughput Chemical Imaging.

Fourier transform infrared (FT-IR) microscopy coupled with machine learning approaches has been demonstrated to be a powerful technique for identifying abnormalities in human tissue. The ability to objectively identify the prediseased state and diagnose cancer with high levels of accuracy has the potential to revolutionize current histopathological practice. Despite recent technological advances in FT-IR microscopy, sample throughput and speed of acquisition are key barriers to clinical translation. Wide-field quantum cascade laser (QCL) infrared imaging systems with large focal plane array detectors utilizing discrete frequency imaging have demonstrated that large tissue microarrays (TMA) can be imaged in a matter of minutes. However, this ground breaking technology is still in its infancy, and its applicability for routine disease diagnosis is, as yet, unproven. In light of this, we report on a large study utilizing a breast cancer TMA comprised of 207 different patients. We show that by using QCL imaging with continuous spectra acquired between 912 and 1800 cm-1, we can accurately differentiate between 4 different histological classes. We demonstrate that we can discriminate between malignant and nonmalignant stroma spectra with high sensitivity (93.56%) and specificity (85.64%) for an independent test set. Finally, we classify each core in the TMA and achieve high diagnostic accuracy on a patient basis with 100% sensitivity and 86.67% specificity. The absence of false negatives reported here opens up the possibility of utilizing high throughput chemical imaging for cancer screening, thereby reducing pathologist workload and improving patient care.

Comparison of Three Methods for Measuring Workload in Surgical Pathology and Cytopathology

Pathologist workload in the United States has traditionally been measured by relative value units (RVUs), which is often criticized for providing an inaccurate estimate of actual work. This study compares three methods for measuring workload. Surgical pathology and cytopathology workload for 1 representative month at Stanford Health Care was assessed using three different methods: RVUs, Royal College of Pathologists (RCP) point system, and University of Washington-Seattle (UW) slide count method. Pearson linear regression analysis showed a strong positive correlation of RVUs with the RCP (0.93, P < .01) and UW (0.86, P < .01) systems. The correlation between the RCP and UW systems was weaker (0.70, P = .05). The RCP system rated gastrointestinal, genitourinary, and breast workload lower than the RVU system while medical liver/renal and cytology were valued higher. The UW system overvalued breast workload. RCP is the most advanced and well-developed system for evaluating workload. It provides more weight for higher complexity specimens, while RVUs favor specialties with higher volume of small specimens, and slide counts favor specialties with extensively sampled large specimens.

Large scale tissue histopathology image classification, segmentation, and visualization via deep convolutional activation features

BackgroundHistopathology image analysis is a gold standard for cancer recognition and diagnosis. Automatic analysis of histopathology images can help pathologists diagnose tumor and cancer subtypes, alleviating the workload of pathologists. There are two basic types of tasks in digital histopathology image analysis: image classification and image segmentation. Typical problems with histopathology images that hamper automatic analysis include complex clinical representations, limited quantities of training images in a dataset, and the extremely large size of singular images (usually up to gigapixels). The property of extremely large size for a single image also makes a histopathology image dataset be considered large-scale, even if the number of images in the dataset is limited.ResultsIn this paper, we propose leveraging deep convolutional neural network (CNN) activation features to perform classification, segmentation and visualization in large-scale tissue histopathology images. Our framework transfers features extracted from CNNs trained by a large natural image database, ImageNet, to histopathology images. We also explore the characteristics of CNN features by visualizing the response of individual neuron components in the last hidden layer. Some of these characteristics reveal biological insights that have been verified by pathologists. According to our experiments, the framework proposed has shown state-of-the-art performance on a brain tumor dataset from the MICCAI 2014 Brain Tumor Digital Pathology Challenge and a colon cancer histopathology image dataset.ConclusionsThe framework proposed is a simple, efficient and effective system for histopathology image automatic analysis. We successfully transfer ImageNet knowledge as deep convolutional activation features to the classification and segmentation of histopathology images with little training data. CNN features are significantly more powerful than expert-designed features.

Report of the results of the International Clinical Cytometry Society and American Society for Clinical Pathology workload survey of clinical flow cytometry laboratories.

Thorough review of current workload, staffing, and testing practices in clinical laboratories allows for optimization of laboratory efficiency and quality. This information is largely missing with regard to clinical flow cytometry laboratories. The purpose of this survey is to provide comprehensive, current, and accurate data on testing practices and laboratory staffing in clinical laboratories performing flow cytometric studies. Survey data was collected from flow cytometry laboratories through the ASCP website. Data was collected on the workload during a 1-year time period of full-time and part-time technical and professional (M.D./D.O./Ph.D. or equivalent) flow cytometry employees. Workload was examined as number of specimens and tubes per full time equivalent (FTE) technical and professional staff. Test complexity, test result interpretation, and reporting practices were also evaluated. There were 205 respondent laboratories affiliated predominantly with academic and health system institutions. Overall, 1,132 FTE employees were reported with 29% professional FTE employees and 71% technical. Fifty-one percent of the testing performed was considered high complexity and 49% was low complexity. The average number of tubes per FTE technologist was 1,194 per year and the average number of specimens per FTE professional was 1,659 per year. The flow cytometry reports were predominantly written by pathologists (57%) and were typically written as a separate report (58%). This survey evaluates the overall status of the current practice of clinical flow cytometry and provides a comprehensive dataset as a framework to help laboratory departments, directors, and managers make appropriate, cost-effective staffing decisions. © 2016 International Clinical Cytometry Society.

Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis.

Pathologists face a substantial increase in workload and complexity of histopathologic cancer diagnosis due to the advent of personalized medicine. Therefore, diagnostic protocols have to focus equally on efficiency and accuracy. In this paper we introduce ‘deep learning’ as a technique to improve the objectivity and efficiency of histopathologic slide analysis. Through two examples, prostate cancer identification in biopsy specimens and breast cancer metastasis detection in sentinel lymph nodes, we show the potential of this new methodology to reduce the workload for pathologists, while at the same time increasing objectivity of diagnoses. We found that all slides containing prostate cancer and micro- and macro-metastases of breast cancer could be identified automatically while 30–40% of the slides containing benign and normal tissue could be excluded without the use of any additional immunohistochemical markers or human intervention. We conclude that ‘deep learning’ holds great promise to improve the efficacy of prostate cancer diagnosis and breast cancer staging.

Multimodal nonlinear microscopy of head and neck carcinoma - toward surgery assisting frozen section analysis.

Treatment of early cancer stages is deeply connected to a good prognosis, a moderate reduction of the quality of life, and comparably low treatment costs. Head and neck squamous cell carcinomas were investigated using the multimodal combination of coherent anti-Stokes Raman scattering (CARS), two-photon excited fluorescence (TPEF), and second-harmonic generation (SHG) microscopy. An increased median TPEF to CARS contrast was found comparing cancerous and healthy squamous epithelium with a p value of 1.8·10(-10) . A following comprehensive image analysis was able to predict the diagnosis of imaged tissue sections with an overall accuracy of 90% for a 4-class model. Nonlinear multimodal imaging is verified objectively as a valuable diagnostic tool that complements conventional staining protocols and can serve as filter in future clinical routine reducing the pathologist's workload. © 2016 Wiley Periodicals, Inc. Head Neck 38: First-1552, 2016.

Clear Speech: Technologies that Enable the Expression and Reception of Language

Abstract Approximately 10% of North Americans have some communication disorder. These can be physical as in cerebral palsy and Parkinson's disease, cognitive as in Alzheimer's disease and dementia generally, or both physical and cognitive as in stroke. In fact, deteriorations in language are often the early hallmarks of broader diseases associated with older age, which is especially relevant since aging populations across many nations will result in a drastic increase in the prevalence of these types of disorders. A significant change to how healthcare is administered, brought on by these aging populations, will increase the workload of speech-language pathologists, therapists, and caregivers who are often already overloaded. Fortunately, modern speech technology, such as automatic speech recognition, has matured to the point where it can now have a profound positive impact on the lives of millions of people living with various types of disorders. This book serves as a common ground for two communities: c...

Development of a practical spatial-spectral analysis protocol for breast histopathology using Fourier transform infrared spectroscopic imaging.

Breast cancer screening provides sensitive tumor identification, but low specificity implies that a vast majority of biopsies are not ultimately diagnosed as cancer. Automated techniques to evaluate biopsies can prevent errors, reduce pathologist workload and provide objective analysis. Fourier transform infrared (FT-IR) spectroscopic imaging provides both molecular signatures and spatial information that may be applicable for pathology. Here, we utilize both the spectral and spatial information to develop a combined classifier that provides rapid tissue assessment. First, we evaluated the potential of IR imaging to provide a diagnosis using spectral data alone. While highly accurate histologic [epithelium, stroma] recognition could be achieved, the same was not possible for disease [cancer, no-cancer] due to the diversity of spectral signals. Hence, we employed spatial data, developing and evaluating increasingly complex models, to detect cancers. Sub-mm tumors could be very confidently predicted as indicated by the quantitative measurement of accuracy via receiver operating characteristic (ROC) curve analyses. The developed protocol was validated with a small set and statistical performance used to develop a model that predicts study design for a large scale, definitive validation. The results of evaluation on different instruments, at higher noise levels, under a coarser spectral resolution and two sampling modes [transmission and transflection], indicate that the protocol is highly accurate under a variety of conditions. The study paves the way to validating IR imaging for rapid breast tumor detection, its statistical validation and potential directions for optimization of the speed and sampling for clinical deployment.

Forensic Pathology Workload and Complexity: Designing a Complexity System that Accurately Represents Workload

For the most part, workload is defined for forensic pathologists in North America by the number of cases per annum, with specific recommendations set out by the National Association of Medical Examiners (NAME) to perform no more than 250 autopsies in a year. However, this definition of workload is somewhat limiting as it doesn't reflect the case to case variability that forensic pathologists encounter. The variability translates into differing amounts of time needed on the part of the pathologist to devote to each case and those differences in time can be substantial. Complexity systems exist in surgical pathology to better reflect the case-to-case variability that surgical pathologists experience. Based on these complexity systems, departments can have a more accurate representation of workload and appropriately allocate resources and plan staffing. Many different complexity systems exist, but all of them, in their own way, attempt to lessen the gap between overvaluing simple specimens and undervaluing complex specimens. No formal system for gauging complexity exists in forensic pathology. The creation of one would provide a more detailed taxonomy to be better able to define forensic pathologists' workload and compare workload between pathologists and institutions.

Individualized medicine and demographic change as determining workload factors in pathology: quo vadis?

The advent of individualized medicine with novel guidelines, extended quality assessment as well as intensified conventional, immunohistochemical, and molecular characterization of diseases has led to a substantial increase of pathologists' workload. Furthermore, in industrialized countries, we are facing the challenges of demographic change with an aging population. This raises the question of how pathology will be affected by these developments in the future. We extracted German population data and data on the number of board-certified physicians and pathologists from official sources. These data were reviewed in the light of data on caseload, case complexity, auxiliary diagnostic procedures, and matching patient data from a large German pathology department serving as a sector independent regional service provider. The refinement of diagnostic procedures over the last decade has resulted in a 60 % increase in slide numbers per case, doubling of immunohistochemistry procedures, and more than tripling of molecular analyses. Correlation of this development to demographics suggests that an aging population will further increase the caseload and case complexity in the coming decades since patient age is tightly linked to both parameters. This development is currently not accompanied by a sufficient increase in the number of pathologists. Our data point toward an imbalance between the increase in pathology workload and the number of pathologists. Extrapolations suggest a further aggravation of this development in the future. Thus, healthcare systems need to address this problem urgently in order to cope with these challenges.

Intraoperative detection of sentinel lymph node metastases inbreast carcinoma by Fourier transform infrared spectroscopy.

Sentinel lymph node (SLN) biopsy is a routine surgical staging procedure in clinically lymph node-negative breast cancer. Fourier transform infrared (FTIR) spectroscopy, a technique based on the biochemical composition of the tissue, has previously been found to be capable of differentiating between normal and malignant tissue. The aim of the present study was to explore the intraoperative use of FTIR spectroscopy for rapidly identifying metastatic SLNs, and distinguishing between metastatic and non-metastatic tissue. Freshly removed SLNs from patients with breast cancer were analysed. Samples were measured by FTIR spectroscopy before histopathological diagnosis. The FTIR spectrum of each sample identified ten bands from 2000 to 900 cm(-1) . The peak position, intensity and full width at half maximum of each absorbent band were measured, and the relative intensity ratios calculated. Canonical discriminant analysis was performed to discriminate between metastatic and non-metastatic samples. A total of 149 SLNs were removed from 49 patients. Histopathological examination confirmed 38 metastatic and 111 non-metastatic SLNs. Eighteen of 29 parameters were significantly different between the metastatic and non-metastatic SLNs. Five parameters were selected as independent factors to form discriminant functions. The sensitivity, specificity and accuracy of this method were 94·7, 90·1 and 91·3 per cent respectively. The accuracy of histological analysis of frozen sections was 100 per cent. FTIR spectroscopy is a promising technique for the real-time diagnosis of SLN metastasis during breast cancer surgery. Surgical relevance Sentinel lymph node (SLN) biopsy is a highly accurate predictor of overall axillary status and has become the standard in disease staging in clinically node-negative breast cancer. A rapid and accurate intraoperative assessment of metastatic spread to the SLN provides the necessary information for the surgeon to proceed with immediate axillary dissection. The results of this research indicate that Fourier transform infrared (FTIR) spectroscopy is a rapid, accurate, non-destructive and cost-effective molecular method that can be used to detect SLN metastasis during surgery. FTIR analysis could be useful for the intraoperative diagnosis of lymph node metastases at large institutions, thereby reducing the workload of pathologists, as well as in regions lacking pathologists such as in developing countries.

Modeling complexity in pathologist workload measurement: the Automatable Activity-Based Approach to Complexity Unit Scoring (AABACUS)

Pathologists provide diagnoses relevant to the disease state of the patient and identify specific tissue characteristics relevant to response to therapy and prognosis. As personalized medicine evolves, there is a trend for increased demand of tissue-derived parameters. Pathologists perform increasingly complex analyses on the same ‘cases'. Traditional methods of workload assessment and reimbursement, based on number of cases sometimes with a modifier (eg, the relative value unit (RVU) system used in the United States), often grossly underestimate the amount of work needed for complex cases and may overvalue simple, small biopsy cases. We describe a new approach to pathologist workload measurement that aligns with this new practice paradigm. Our multisite institution with geographically diverse partner institutions has developed the Automatable Activity-Based Approach to Complexity Unit Scoring (AABACUS) model that captures pathologists' clinical activities from parameters documented in departmental laboratory information systems (LISs). The model's algorithm includes: ‘capture', ‘export', ‘identify', ‘count', ‘score', ‘attribute', ‘filter', and ‘assess filtered results'. Captured data include specimen acquisition, handling, analysis, and reporting activities. Activities were counted and complexity units (CUs) generated using a complexity factor for each activity. CUs were compared between institutions, practice groups, and practice types and evaluated over a 5-year period (2008–2012). The annual load of a clinical service pathologist, irrespective of subspecialty, was ∼40 000 CUs using relative benchmarking. The model detected changing practice patterns and was appropriate for monitoring clinical workload for anatomical pathology, neuropathology, and hematopathology in academic and community settings, and encompassing subspecialty and generalist practices. AABACUS is objective, can be integrated with an LIS and automated, is reproducible, backwards compatible, and future adaptable. It can be applied as a robust decision support tool for the assessment of overall and targeted staffing needs as well as utilization analyses for resource allocation.

The changing role of the pathologist in the management of Barrett's oesophagus.

Pathological specimens from columnar-lined oesophagus (CLO) comprise a considerable proportion of the workload of gastrointestinal pathologists in Western countries. There remain controversies concerning the diagnostic role of pathology. More recently, in the UK at least, the diagnosis has been regarded as primarily an endoscopic endeavour, with pathology being corroborative and only diagnostic when endoscopic features are equivocal or when there are additional features that make the endoscopic diagnosis unclear. There is also recognition that demonstration of intestinalisation or 'goblet cells' is not paramount, and should not be required for the diagnosis. There have been notable changes in the management of CLO neoplasia: pathologists are centrally involved in its management. Pathological assessment of endoscopic mucosal resection (EMR) specimens provides the most useful means of determining the management of early neoplasia and of determining indications for surgery. This represents an extraordinarily rapid change in management, in that, <10years ago, laborious Seattle-type biopsy protocols were recommended, and high grade dysplasia was an indication for resectional surgery. Now, individual patient management is paramount: multi-professional meetings determine management after biopsy and EMR assessment. One significant change is that major resections are undertaken less often, in Western countries, for CLO neoplasia.

Can Digital Pathology Result In Cost Savings? A Financial Projection For Digital Pathology Implementation At A Large Integrated Health Care Organization

Background: Digital pathology offers potential improvements in workflow and interpretive accuracy. Although currently digital pathology is commonly used for research and education, its clinical use has been limited to niche applications such as frozen sections and remote second opinion consultations. This is mainly due to regulatory hurdles, but also to a dearth of data supporting a positive economic cost-benefit. Large scale adoption of digital pathology and the integration of digital slides into the routine anatomic/surgical pathology “slide less” clinical workflow will occur only if digital pathology will offer a quantifiable benefit, which could come in the form of more efficient and/or higher quality care. Aim: As a large academic-based health care organization expecting to adopt digital pathology for primary diagnosis upon its regulatory approval, our institution estimated potential operational cost savings offered by the implementation of an enterprise-wide digital pathology system (DPS). Methods: Projected cost savings were calculated for the first 5 years following implementation of a DPS based on operational data collected from the pathology department. Projected savings were based on two factors: (1) Productivity and lab consolidation savings; and (2) avoided treatment costs due to improvements in the accuracy of cancer diagnoses among nonsubspecialty pathologists. Detailed analyses of incremental treatment costs due to interpretive errors, resulting in either a false positive or false negative diagnosis, was performed for melanoma and breast cancer and extrapolated to 10 other common cancers. Results: When phased in over 5-years, total cost savings based on anticipated improvements in pathology productivity and histology lab consolidation were estimated at $12.4 million for an institution with 219,000 annual accessions. The main contributing factors to these savings were gains in pathologist clinical full-time equivalent capacity impacted by improved pathologist productivity and workload distribution. Expanding the current localized specialty sign-out model to an enterprise-wide shared general/subspecialist sign-out model could potentially reduce costs of incorrect treatment by $5.4 million. These calculations were based on annual over and under treatment costs for breast cancer and melanoma estimated to be approximately $26,000 and $ll,000/case, respectively, and extrapolated to $21,500/case for other cancer types. Conclusions: The projected 5-year total cost savings for our large academic-based health care organization upon fully implementing a DPS was approximately $18 million. If the costs of digital pathology acquisition and implementation do not exceed this value, the return on investment becomes attractive to hospital administrators. Furthermore, improved patient outcome enabled by this technology strengthens the argument supporting adoption of an enterprise-wide DPS.

Laboratory demand management of repetitive testing – time for harmonisation and an evidenced based approach

In a time when laboratories are struggling to cope with increasing pressures on their services, and shrinking budgets demand management tools and strategies provide potential solutions. There are a number of areas where the laboratory is being squeezed including increasing workloads, increased costs, reduced revenue, inappropriate tests and changes in how their services are commissioned and delivered. The pathology workload in the UK alone is increasing by an average of 10% every year and must be delivered despite a 20% reduction in pathology funding [ 1 ]. Workload has been increasing due to both increases in appropriate and inappropriate tests. Advances in laboratory technology have allowed multiple testing, more rapid turnaround times and more choice. With the advent of the worldwide web, patients are better informed and become advocates for their own investigations. The population is also getting older with more patients having chronic diseases, which require effective long-term management. Requestors are also more defensive in the way they request for fear of missing a test or a medico-legal consequence. Identifying the appropriate and inappropriate test is a challenge for the laboratory, but this in itself depends upon the perspective of the individual. A standardised approach and definition of an appropriate or inappropriate test is required to allow the laboratories to effectively manage each. In Australia, the National Coalition of Public Pathology Report (2012) presents a matrix that can be used to ascertain whether a request is appropriate or inappropriate, thereby bringing some standardisation to this difficult area [ 2 ]. Therefore, the laboratory must be proactive in effectively managing its workload in order to provide the best service for the patient within the defined constraints. The ideal demand management strategy ensures that the right test is done on the right patient at the right time. It also provides an opportunity to harmonise processes and remove unnecessary waste thereby saving money. A number of demand management solutions are available, which can assist the laboratory and can be grouped into five areas: education, rules aimed at restricting test requests, redesign of request forms, computerised physician order entry (CPOE) and reimbursement models [ 2 ]. Fryer and Smellie have recently published a demand management toolbox to assist laboratories in achieving effective workload management [ 3 ]. One solution that has already showed promise and sustainability are rules aimed at restricting tests based on time between repetitive tests [ 4 , 5 ]. In this issue of the Clinical Chemistry and Laboratory Medicine , Janssens and Wasser discuss an example of this type of intervention, calculating the financial savings realised [ 6 ]. In partnership with hospital physicians “ spare periods ” (periods during which tests were barred) were produced and implemented through the laboratory information and management system (LIMS). Although the savings in this example were relatively low in proportion to their own pathology budget and previously published figures, they indicated that it should still be continued due to the minimum effort required to sustain it. A key step in such a solution is the partnership between the laboratory and the clinician using the service as demonstrated in this paper. What is sometimes lacking is the evidence to support an intervention particularly when barring tests, which from a user ’ s perspective may be thought to be necessary. The provision of and availability of individual tests may differ between laboratories with different demand management rules in place based on local practice and rarely published evidence or practice. To address some of the variance in practice and lack of evidence base, the Clinical Practice Section of the Association for Clinical Biochemistry (ACB) prepared a set of consensus/evidence based recommendations on when a test should be repeated [ 7 ]. The National Minimum Retesting Interval Project used a “ state of the art ” approach to prepare over 100 recommendations in a number of clinical areas [ 8 ]. Invited members working in small groups prepared recommendations, which when complete were then assessed by an independent reviewer before review by a panel of regional representatives. Where evidence

Better retrieval of lymph nodes in colorectal resection specimens by pathologists’ assistants

BackgroundErrors in surgical pathology are partly due to the increasing workload of pathologists. To reduce this workload, ‘pathologists’ assistants’ (PAs) have been trained to take over some of the pathologists’...

Efficacy of intraoperative GeneSearch Breast Lymph Node (BLN) Assay for breast cancer metastasis detection in sentinel lymph node in Chinese patients

Although intraoperative assessment of the sentinel lymph node (SLN) is useful, it has not gained popularity in China as it involves a heavy workload for pathologists. We conducted a prospective clinical feasibility study of the GeneSearch Breast Lymph Node (BLN) Assay performed in 158 SLNs from 97 patients by comparison with postoperative permanent section histopathology, to validate its potential usefulness in China. Every SLN was cut into alternating 1.5 to 3.0 mm slabs. The BLN assay processed 50% of the fresh alternating slabs to detect the presence of cytokeratin 19 and mammaglobin mRNA. Assay results were compared with those for permanent section histopathology and intraoperative imprint cytology. Slides for imprint cytology were prepared from the BLN assay node tissue before it was processed. Full axillary lymph node (ALN) dissections were performed on some patients after a SLN biopsy. The BLN assay was successfully performed on 158 SLNs from 97 patients. Overall performance of the BLN assay compared with permanent section histopathology was sensitivity 83.9% (26/31), specificity 95.5% (63/66), positive predictive value 89.7% (26/29), negative predictive value 92.6% (63/68), and overall agreement 91.8% (89/97). The BLN assay detected about 25% more metastases than imprint cytology. Moreover, the BLN assay correctly identified most of the additional non-sentinel ALNs metastases (P = 0.005). Our results from a large series of Chinese patients with breast cancer indicate that the BLN assay may be a viable alternative for the standard intraoperative procedures used for metastases detection, especially in early stage breast cancer patients. Name of the trial register: GeneSearch Breast Lymph Node (BLN) Assay China Registration Study. NCT00869674.

Impact of Different Sectioning of Excision Biopsies of the Cervical Transformation Zone for Detection of Invasive Cervical Cancer in 2 European Centers Related to National Cervical Screening Programs

The impact of the number of sections used in cervical excision biopsies of transformation zone on sensitivity of histological detection of cervical cancer is poorly documented. To assess whether different techniques of sectioning cervical excision biopsies in 2 European laboratories influence the finding of cervical cancer by histopathological examination. The routine assessment at the Department of Histopathology and Cytology, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK (Sheffield), encompassed sectioning a cone in 3-mm tissue blocks and cutting 3 levels per block. At the Institute of Pathology, Faculty of Medicine, University of Ljubljana, Slovenia (Ljubljana), cones were cut in a 3- to 4-mm-thick tissue block, and 10 levels were cut per block, spaced every 100 microm. The number of blocks and levels per block were assessed for each cone. Histopathological detection of cervical carcinoma between the laboratories was compared. Among 820 cones in the Sheffield laboratory, we detected 35 invasive carcinomas, whereas 6 invasive carcinomas were detected among 94 cones in the Ljubljana laboratory. Although the Slovenian laboratory examined a significantly larger number of levels per cone biopsy (64 vs 24 in Sheffield), this was not associated with a larger proportion of invasive cervical carcinoma, especially foci of stage IA1 or high-grade cervical intraepithelial neoplasia diagnosed on excision biopsies: 6.4% of invasive cervical carcinomas (5 [83.3%] of stage IA1) in Ljubljana and 4.3% (30 [85.7%] of stage IA1) in Sheffield laboratory (P > 0.05); 71.2% of high-grade cervical intraepithelial neoplasia in Ljubljana and 75.5% in Sheffield (P > 0.05). Our assessment showed that a method with a large number of levels per cervical cone or large loop excision of the transformation zone biopsy did not increase sensitivity for the detection of cervical cancer. However, extensive sectioning substantially affects the pathologist's workload, and this may need to be reconsidered.

Pathology as the cornerstone of human tissue banking: European consensus expert group report.

Aside from ethical considerations, the primary requirement for usage of human tissues in basic or translational research is the thorough characterization of tissues. The second, but equally essential, requirement is that tissues be collected, processed, annotated, and preserved in optimal conditions. These requirements put the pathologist at the center of tissue banking activities and of research aimed at discovering new biomarkers. Pathologists not only provide information identifying the specimen but also make decisions on what materials should be biobanked, on the preservation conditions, and on the timeline of events that precede preservation and storage. This central position calls for increased recognition of the role of the pathologist by the biomolecular community and places new demands on the pathologist's workload and scope of scientific activities. These questions were addressed by an Expert Group Meeting of the European Biological and Biomolecular Research Infrastructure (BBMRI). While detailed recommendations are published elsewhere (Bevilacqua et al., Virchows Archivs, 2010, in press), this article outlines the strategic and technological issues identified by the Expert Group and identifies ways forward for better integration of pathology in the current thrust for development of biomarker-based "personalized medicine."

The Effects of Additional Tumor Cavity Sampling at the Time of Breast-Conserving Surgery on Final Margin Status, Volume of Resection, and Pathologist Workload

Margin status is an important prognostic factor for local recurrence after breast-conserving surgery (BCS) in patients with breast malignancy. It is unclear whether the removal of additional tumor cavity margins reduces the reoperation rate and is cosmetically acceptable. This study compares the reoperation rates, volume of breast excised in cm(3), and number of pathology slides examined in two groups of patients who underwent BCS with or without four or five additional margins (BCS + M). We retrospectively analyzed 320 patients who underwent BCS or BCS + M for stage 0-I-II breast cancer from 2004 to 2007. We classified the margins as negative (>or=1 mm), close (<1 mm), or positive based on the distance from the tumor to the margin of resection. Of 320 cases analyzed, 199 (62.2%) underwent BCS and 121 (37.8%) had BCS + M. Overall, patients with BCS + M had a higher negative margins rate (85.1% vs. 57.2%, P < 0.05) and a lower reoperation rate. However, when ductal carcinoma in situ (DCIS) and infiltrating ductal carcinoma (IDC) were analyzed separately, only patients with IDC showed a higher negative margin rate (91% vs. 62.1%, P < 0.001) and a lower volume of breast tissue excised (205.63 vs. 392.27, P = 0.03). There was no significant increase in pathology workload in both groups. Resection of four to five additional margins during BCS for early-stage invasive breast cancer results in a higher rate of negative microscopic margins, lower volume of breast excised, and subsequently, a lower reoperation rate. The advantages of this approach include improved patient satisfaction and decreased cost.