Mitotic activity: A systematic literature review of the assessment methodology and prognostic value in feline tumors.

Increased proliferation is a driver of tumorigenesis, and quantification of mitotic activity is a standard task for prognostication. This systematic review is an analysis of all available references on mitotic activity in feline tumors to provide an overview of the assessment methods and prognostic value. A systematic literature search in PubMed and Scopus and a nonsystematic search in Google Scholar were conducted. All articles on feline tumors that correlated mitotic activity with patient outcome were identified. Data analysis revealed that of the 42 eligible articles, mitotic count (MC, mitotic figures/tumor area) was evaluated in 39 studies, and mitotic index (MI, mitotic figures/tumor cells) in 3 studies. The risk of bias was considered high for most studies (26/42, 62%) based on small study populations, insufficient details of the MC/MI methods, and lack of statistical measures for diagnostic accuracy or effect on outcome. The MC/MI methods varied between studies. A significant association of MC with survival was determined in 20 of 28 (71%) studies (10 studies evaluated other outcome metrics or provided individual patient data), while 1 study found an inverse effect. Three tumor types had at least 4 studies, and a prognostic association with survival was found in 5 of 6 studies on mast cell tumors, 5 of 5 on mammary tumors, and 3 of 4 on soft-tissue sarcomas. MI was shown to correlate with survival for mammary tumors by 2 research groups; however, comparisons to MC were not conducted. Further studies with standardized mitotic activity methods and appropriate statistical analysis for discriminant ability of patient outcome are needed to infer the prognostic value of MC and MI.

Mitotic activity: A systematic literature review of the assessment methodology and prognostic value in canine tumors.

One of the most relevant prognostic indices for tumors is cellular proliferation, which is most commonly measured by the mitotic activity in routine tumor sections. The goal of this systematic review was to analyze the methods and prognostic relevance of histologically measuring mitotic activity that have been reported for canine tumors in the literature. A total of 137 articles that correlated the mitotic activity in canine tumors with patient outcome were identified through a systematic (PubMed and Scopus) and nonsystematic (Google Scholar) literature search and eligibility screening process. Mitotic activity methods encompassed the mitotic count (MC, number of mitotic figures per tumor area) in 126 studies, presumably the MC (method not specified) in 6 studies, and the mitotic index (MI, number of mitotic figures per number of tumor cells) in 5 studies. A particularly high risk of bias was identified based on the available details of the MC methods and statistical analyses, which often did not quantify the prognostic discriminative ability of the MC and only reported P values. A significant association of the MC with survival was found in 72 of 109 (66%) studies. However, survival was evaluated by at least 3 studies in only 7 tumor types/groups, of which a prognostic relevance is apparent for mast cell tumors of the skin, cutaneous melanoma, and soft tissue tumor of the skin and subcutis. None of the studies using the MI found a prognostic relevance. This review highlights the need for more studies with standardized methods and appropriate analysis of the discriminative ability to prove the prognostic value of the MC and MI in various tumor types. Future studies are needed to evaluate the influence of the performance of individual pathologists on the appropriateness of prognostic thresholds and investigate methods to improve interobserver reproducibility.

Automated diagnosis of 7 canine skin tumors using machine learning on H&E-stained whole slide images.

Microscopic evaluation of hematoxylin and eosin-stained slides is still the diagnostic gold standard for a variety of diseases, including neoplasms. Nevertheless, intra- and interrater variability are well documented among pathologists. So far, computer assistance via automated image analysis has shown potential to support pathologists in improving accuracy and reproducibility of quantitative tasks. In this proof of principle study, we describe a machine-learning-based algorithm for the automated diagnosis of 7 of the most common canine skin tumors: trichoblastoma, squamous cell carcinoma, peripheral nerve sheath tumor, melanoma, histiocytoma, mast cell tumor, and plasmacytoma. We selected, digitized, and annotated 350 hematoxylin and eosin-stained slides (50 per tumor type) to create a database divided into training, n = 245 whole-slide images (WSIs), validation (n = 35 WSIs), and test sets (n = 70 WSIs). Full annotations included the 7 tumor classes and 6 normal skin structures. The data set was used to train a convolutional neural network (CNN) for the automatic segmentation of tumor and nontumor classes. Subsequently, the detected tumor regions were classified patch-wise into 1 of the 7 tumor classes. A majority of patches-approach led to a tumor classification accuracy of the network on the slide-level of 95% (133/140 WSIs), with a patch-level precision of 85%. The same 140 WSIs were provided to 6 experienced pathologists for diagnosis, who achieved a similar slide-level accuracy of 98% (137/140 correct majority votes). Our results highlight the feasibility of artificial intelligence-based methods as a support tool in diagnostic oncologic pathology with future applications in other species and tumor types.

Cytologic scoring of equine exercise-induced pulmonary hemorrhage: Performance of human experts and a deep learning-based algorithm.

Exercise-induced pulmonary hemorrhage (EIPH) is a relevant respiratory disease in sport horses, which can be diagnosed by examination of bronchoalveolar lavage fluid (BALF) cells using the total hemosiderin score (THS). The aim of this study was to evaluate the diagnostic accuracy and reproducibility of annotators and to validate a deep learning-based algorithm for the THS. Digitized cytological specimens stained for iron were prepared from 52 equine BALF samples. Ten annotators produced a THS for each slide according to published methods. The reference methods for comparing annotator's and algorithmic performance included a ground truth dataset, the mean annotators' THSs, and chemical iron measurements. Results of the study showed that annotators had marked interobserver variability of the THS, which was mostly due to a systematic error between annotators in grading the intracytoplasmatic hemosiderin content of individual macrophages. Regarding overall measurement error between the annotators, 87.7% of the variance could be reduced by using standardized grades based on the ground truth. The algorithm was highly consistent with the ground truth in assigning hemosiderin grades. Compared with the ground truth THS, annotators had an accuracy of diagnosing EIPH (THS of < or ≥ 75) of 75.7%, whereas, the algorithm had an accuracy of 92.3% with no relevant differences in correlation with chemical iron measurements. The results show that deep learning-based algorithms are useful for improving reproducibility and routine applicability of the THS. For THS by experts, a diagnostic uncertainty interval of 40 to 110 is proposed. THSs within this interval have insufficient reproducibility regarding the EIPH diagnosis.

Validation of digital microscopy: Review of validation methods and sources of bias.

Digital microscopy (DM) is increasingly replacing traditional light microscopy (LM) for performing routine diagnostic and research work in human and veterinary pathology. The DM workflow encompasses specimen preparation, whole-slide image acquisition, slide retrieval, and the workstation, each of which has the potential (depending on the technical parameters) to introduce limitations and artifacts into microscopic examination by pathologists. Performing validation studies according to guidelines established in human pathology ensures that the best-practice approaches for patient care are not deteriorated by implementing DM. Whereas current publications on validation studies suggest an overall high reliability of DM, each laboratory is encouraged to perform an individual validation study to ensure that the DM workflow performs as expected in the respective clinical or research environment. With the exception of validation guidelines developed by the College of American Pathologists in 2013 and its update in 2021, there is no current review of the application of methods fundamental to validation. We highlight that there is high methodological variation between published validation studies, each having advantages and limitations. The diagnostic concordance rate between DM and LM is the most relevant outcome measure, which is influenced (regardless of the viewing modality used) by different sources of bias including complexity of the cases examined, diagnostic experience of the study pathologists, and case recall. Here, we review 3 general study designs used for previous publications on DM validation as well as different approaches for avoiding bias.

Computer-assisted mitotic count using a deep learning-based algorithm improves interobserver reproducibility and accuracy.

The mitotic count (MC) is an important histological parameter for prognostication of malignant neoplasms. However, it has inter- and intraobserver discrepancies due to difficulties in selecting the region of interest (MC-ROI) and in identifying or classifying mitotic figures (MFs). Recent progress in the field of artificial intelligence has allowed the development of high-performance algorithms that may improve standardization of the MC. As algorithmic predictions are not flawless, computer-assisted review by pathologists may ensure reliability. In the present study, we compared partial (MC-ROI preselection) and full (additional visualization of MF candidates and display of algorithmic confidence values) computer-assisted MC analysis to the routine (unaided) MC analysis by 23 pathologists for whole-slide images of 50 canine cutaneous mast cell tumors (ccMCTs). Algorithmic predictions aimed to assist pathologists in detecting mitotic hotspot locations, reducing omission of MFs, and improving classification against imposters. The interobserver consistency for the MC significantly increased with computer assistance (interobserver correlation coefficient, ICC = 0.92) compared to the unaided approach (ICC = 0.70). Classification into prognostic stratifications had a higher accuracy with computer assistance. The algorithmically preselected hotspot MC-ROIs had a consistently higher MCs than the manually selected MC-ROIs. Compared to a ground truth (developed with immunohistochemistry for phosphohistone H3), pathologist performance in detecting individual MF was augmented when using computer assistance (F1-score of 0.68 increased to 0.79) with a reduction in false negatives by 38%. The results of this study demonstrate that computer assistance may lead to more reproducible and accurate MCs in ccMCTs.

Retrobulbar Adenocarcinoma with Subconjunctival Extension in a Common Buzzard (Buteo buteo).

A free ranging, fledged common buzzard (Buteo buteo) was found with severe feather damage and left periorbital swelling. Clinical examination revealed a 3.0 × 2.5 × 1.5 cm left medial subconjunctival mass. The abnormal tissue extended over most of the left cornea, severely impairing the bird's vision in that eye. Additionally, the left globe was displaced in a temporal direction. Computed tomography revealed the origin of the mass to be retrobulbar tissue. An ultrasound examination of the mass found cystic areas, and a sanguineous fluid was aspirated. Cytological examination of the aspirated fluid revealed numerous erythrocytes and a few round cells with oval nuclei, single large nucleoli, and abundant foamy cytoplasm. After a poor prognosis for rehabilitation to the wild, the bird was humanely euthanatized. A postmortem examination of the bird confirmed the retrobulbar mass with extension around the bulbus. Histological examination of the mass was consistent with an invasive adenocarcinoma, likely arising from the lacrimal glands. Neoplasia in the orbit has occasionally been described in Psittaciformes, but only rarely in birds of prey such as Accipitriformes.

Internal Tandem Duplication of Exon 8 of c-kit Is Associated With Longer Total Survival in Canine Cutaneous Mast Cell Tumors.

Canine cutaneous mast cell tumors (ccMCTs) have a highly variable biological behavior and accurate prognostication is essential for therapeutic intervention. Internal tandem duplications (ITD) of exon 11 are the most commonly detected c-kit mutation in ccMCTs and are associated with poor prognosis and increased cellular proliferation. The prognostic value of detecting mutations in other exons of c-kit has not been systematically examined. In this study, we analyzed the prognostic value of ITD mutations of exon 8 in c-kit of ccMCTs in comparison to ccMCTs with ITD mutations of exon 11 and ccMCTs without mutations of exon 8 or 11. The mutational status, histological grade, KIT expression pattern, Ki67 index, AgNOR (argyrophilic nucleolar organizing region) score, and Ag67 score were determined in 221 ccMCTs, and outcome was available for 101 dogs. ITD mutations of exon 8 were found in 73/221 (33%), of exon 11 in 100/221 (45%), and none of these mutations in 50/221 (22%) of ccMCTs. None of the dogs with mutations of exon 8 died due to suspected ccMCT-related cause, but 23% dogs with ccMCTs with mutations of exon 11 died due to suspected ccMCT-related cause. Prognostic parameters in ccMCTs with exon 11 mutations were commonly associated with a high proliferative activity and poor prognosis, while prognostic markers in ccMCTs with mutations of exon 8 had lower values similar to those observed in ccMCTs without mutations in exons 8 or 11 of c-kit. This study indicates that screening for ITD mutations in exon 8 in ccMCTs may be helpful to identify less aggressive ccMCTs and may be recommended as a supplementary prognostic test.

Neoplasia and Tumor-Like Lesions in Pet Rabbits (Oryctolagus cuniculus): A Retrospective Analysis of Cases Between 1995 and 2019.

Prevalence and age distribution of tumors is largely unknown in pet rabbits. Currently available studies focused on specific organ systems or specific tumor types and never covered a comparative examination of all tumor types. Previous studies on laboratory rabbits suggested a low tumor prevalence but were mostly limited to young adult animals. In the present study, all tumor types and several tumor-like lesions of all organ systems were analyzed retrospectively in archived pet rabbit samples of all ages. Cases included necropsy cases (n = 2,014) or postmortem tissue samples (n = 102) as well as surgical biopsies (n = 854). All lesions suspicious of neoplasia were reevaluated by histopathology and, when indicated, by immunohistochemistry. Necropsy cases had a tumor prevalence of 14.4% in both sexes or 19.8% in female intact rabbits of all age groups, and up to 47.2% or 66.7%, respectively, in rabbits older than 6 years. Overall, the most common tumor types were uterine adenocarcinoma (prevalence in female intact animals: 13.1%), lymphoma (prevalence: 2.8%), and thymoma (prevalence: 2.1%). Lymphoma, the most common tumor of rabbits ≤24 months of age, were of B-cell immunophenotype in 96% of cases and most commonly located in the lymph nodes (57%), gastrointestinal tract (54%), kidneys (48%), spleen (42%), and liver (41%). Tumors accounted for 81.1% of surgical biopsies and mostly comprised cutaneous, mammary, and uterine tumors. In conclusion, tumor types and prevalence varied significantly with respect to age, revealing some differences from previous studies on laboratory rabbits.

Mitotic Figures-Normal, Atypical, and Imposters: A Guide to Identification.

Counting mitotic figures (MF) in hematoxylin and eosin-stained histologic sections is an integral part of the diagnostic pathologist's tumor evaluation. The mitotic count (MC) is used alone or as part of a grading scheme for assessment of prognosis and clinical decisions. Determining MCs is subjective, somewhat laborious, and has interobserver variation. Proposals for standardizing this parameter in the veterinary field are limited to terminology (use of the term MC) and area (MC is counted in an area measuring 2.37 mm2). Digital imaging techniques are now commonplace and widely used among veterinary pathologists, and field of view area can be easily calculated with digital imaging software. In addition to standardizing the methods of counting MF, the morphologic characteristics of MF and distinguishing atypical mitotic figures (AMF) versus mitotic-like figures (MLF) need to be defined. This article provides morphologic criteria for MF identification and for distinguishing normal phases of MF from AMF and MLF. Pertinent features of digital microscopy and application of computational pathology (CPATH) methods are discussed. Correct identification of MF will improve MC consistency, reproducibility, and accuracy obtained from manual (glass slide or whole-slide imaging) and CPATH approaches.

International Guidelines for Veterinary Tumor Pathology: A Call to Action.

Standardization of tumor assessment lays the foundation for validation of grading systems, permits reproducibility of oncologic studies among investigators, and increases confidence in the significance of study results. Currently, there is minimal methodological standardization for assessing tumors in veterinary medicine, with few attempts to validate published protocols and grading schemes. The current article attempts to address these shortcomings by providing standard guidelines for tumor assessment parameters and protocols for evaluating specific tumor types. More detailed information is available in the Supplemental Files, the intention of which is 2-fold: publication as part of this commentary, but more importantly, these will be available as "living documents" on a website (www.vetcancerprotocols.org), which will be updated as new information is presented in the peer-reviewed literature. Our hope is that veterinary pathologists will agree that this initiative is needed, and will contribute to and utilize this information for routine diagnostic work and oncologic studies. Journal editors and reviewers can utilize checklists to ensure publications include sufficient detail and standardized methods of tumor assessment. To maintain the relevance of the guidelines and protocols, it is critical that the information is periodically updated and revised as new studies are published and validated with the intent of providing a repository of this information. Our hope is that this initiative (a continuation of efforts published in this journal in 2011) will facilitate collaboration and reproducibility between pathologists and institutions, increase case numbers, and strengthen clinical research findings, thus ensuring continued progress in veterinary oncologic pathology and improving patient care.

Giant Cell Sarcomas in Domestic Rabbits (Oryctolagus cuniculus).

Multinucleated giant cells (MGCs) are a prominent histological feature of various mesenchymal neoplasms and are often considered a criterion of malignancy. Mesenchymal neoplasms with MGCs for which the cell lineage is unclear generally are referred to as giant cell sarcomas. Here we characterize the gross, histologic, and immunohistochemical features of 90 giant cell sarcomas in domestic pet rabbits. Based on the anatomic location and histologic and immunohistochemical findings, 18 cases were classified as histiocytic sarcomas (HS) and 72 cases as anaplastic sarcomas (AS). At postmortem examination, HS was either localized HS (n = 7) always affecting the lungs, or disseminated HS (n = 10) that affected the lungs (n = 10), liver (n = 6), kidneys (n = 4), pleura (n = 2), mediastinum (n = 2), heart (n = 4), skeletal muscle (n = 1), adipose tissue (n = 1), and lymph node (n = 1). Additionally, one cecal biopsy was consistent with HS. Microscopically, HS were characterized by sheets of neoplastic polygonal to round cells that contained single to several, often greatly enlarged nuclei as well as abundant cytoplasm. HS were always positive for CD204 and always negative for SMA and desmin. In contrast, AS arose most commonly from the skin or subcutis (n = 62) and rarely the skeletal muscle (n = 8) or abdominal organs (n = 2). In 29% of extra-abdominal AS, the tumor deeply invaded into surrounding connective tissue, skeletal muscle, tendons, and bone causing pathological fractures. Five of 9 postmortem cases metastasized to various organs often including the lungs. Microscopically, AS were characterized by sheets of spindle or pleomorphic cells admixed with variable numbers of MGCs. Immunohistochemically, AS were always negative for CD204 and often (71%) positive for SMA and/or desmin.

Computerized Calculation of Mitotic Count Distribution in Canine Cutaneous Mast Cell Tumor Sections: Mitotic Count Is Area Dependent.

Mitotic count (MC) is an important element for grading canine cutaneous mast cell tumors (ccMCTs) and is determined in 10 consecutive high-power fields with the highest mitotic activity. However, there is variability in area selection between pathologists. In this study, the MC distribution and the effect of area selection on the MC were analyzed in ccMCTs. Two pathologists independently annotated all mitotic figures in whole-slide images of 28 ccMCTs (ground truth). Automated image analysis was used to examine the ground truth distribution of the MC throughout the tumor section area, which was compared with the manual MCs of 11 pathologists. Computerized analysis demonstrated high variability of the MC within different tumor areas. There were 6 MCTs with consistently low MCs (MC<7 in all tumor areas), 13 cases with mostly high MCs (MC ≥7 in ≥75% of 10 high-power field areas), and 9 borderline cases with variable MCs around 7, which is a cutoff value for ccMCT grading. There was inconsistency among pathologists in identifying the areas with the highest density of mitotic figures throughout the 3 ccMCT groups; only 51.9% of the counts were consistent with the highest 25% of the ground truth MC distribution. Regardless, there was substantial agreement between pathologists in detecting tumors with MC ≥7. Falsely low MCs below 7 mainly occurred in 4 of 9 borderline cases that had very few ground truth areas with MC ≥7. The findings of this study highlight the need to further standardize how to select the region of the tumor in which to determine the MC.

Pseudodiverticula of the Small Intestine Associated With Idiopathic Smooth Muscle Hypertrophy in Domestic Rabbits ( Oryctolagus cuniculus).

Acquired outpouches of the intestinal tract are referred to as pseudodiverticula or false pulsion diverticula. In contrast to true diverticula, in which the wall contains all layers of the intestinal tract, the wall of pseudodiverticula lacks the tunica muscularis. Smooth muscle hypertrophy of the small intestine is commonly considered a cause of pseudodiverticulosis in animals due to increased intraluminal pressure. This study reports pseudodiverticula associated with idiopathic smooth muscle hypertrophy of the small intestine in lagomorphs. Four domestic rabbits had single or multiple (up to 200) pseudodiverticula of various size in the small intestine. In all cases the tunica muscularis was diffusely thickened, significantly exceeding reference thickness of 14 rabbits (mean, 112.3 µm; range, 26.3-389.0 µm). Clinical signs were considered to be caused by severe necrosis and inflammation of the wall of large pseudodiverticula, leading to perforation with subsequent peritonitis and mesenteric and omental abscess formation in 2 cases.

Validation of Digital Microscopy Compared With Light Microscopy for the Diagnosis of Canine Cutaneous Tumors.

Integration of new technologies, such as digital microscopy, into a highly standardized laboratory routine requires the validation of its performance in terms of reliability, specificity, and sensitivity. However, a validation study of digital microscopy is currently lacking in veterinary pathology. The aim of the current study was to validate the usability of digital microscopy in terms of diagnostic accuracy, speed, and confidence for diagnosing and differentiating common canine cutaneous tumor types and to compare it to classical light microscopy. Therefore, 80 histologic sections including 17 different skin tumor types were examined twice as glass slides and twice as digital whole-slide images by 6 pathologists with different levels of experience at 4 time points. Comparison of both methods found digital microscopy to be noninferior for differentiating individual tumor types within the category epithelial and mesenchymal tumors, but diagnostic concordance was slightly lower for differentiating individual round cell tumor types by digital microscopy. In addition, digital microscopy was associated with significantly shorter diagnostic time, but diagnostic confidence was lower and technical quality was considered inferior for whole-slide images compared with glass slides. Of note, diagnostic performance for whole-slide images scanned at 200× magnification was noninferior in diagnostic performance for slides scanned at 400×. In conclusion, digital microscopy differs only minimally from light microscopy in few aspects of diagnostic performance and overall appears adequate for the diagnosis of individual canine cutaneous tumors with minor limitations for differentiating individual round cell tumor types and grading of mast cell tumors.

Virtual Microscopy in Histopathology Training: Changing Student Attitudes in 3 Successive Academic Years.

Several veterinary faculties have integrated virtual microscopy into their curricula in recent years to improve and refine their teaching techniques. The many advantages of this recent technology are described in the literature, including remote access and an equal and constant slide quality for all students. However, no study has analyzed the change of perception toward virtual microscopy at different time points of students' academic educations. In the present study, veterinary students in 3 academic years were asked for their perspectives and attitudes toward virtual microscopy and conventional light microscopy. Third-, fourth-, and fifth-year veterinary students filled out a questionnaire with 12 questions. The answers revealed that virtual microscopy was overall well accepted by students of all academic years. Most students even suggested that virtual microscopy be implemented more extensively as the modality for final histopathology examinations. Nevertheless, training in the use of light microscopy and associated skills was surprisingly well appreciated. Regardless of their academic year, most students considered these skills important and necessary, and they felt that light microscopy should not be completely replaced. The reasons for this view differed depending on academic year, as the perceived main disadvantage of virtual microscopy varied. Third-year students feared that they would not acquire sufficient light microscopy skills. Fifth-year students considered technical difficulties (i.e., insufficient transmission speed) to be the main disadvantage of this newer teaching modality.

The Pathologist 2.0: An Update on Digital Pathology in Veterinary Medicine.

Using light microscopy to describe the microarchitecture of normal and diseased tissues has changed very little since the middle of the 19th century. While the premise of histologic analysis remains intact, our relationship with the microscope is changing dramatically. Digital pathology offers new forms of visualization, and delivery of images is facilitated in unprecedented ways. This new technology can untether us entirely from our light microscopes, with many pathologists already performing their jobs using virtual microscopy. Several veterinary colleges have integrated virtual microscopy in their curriculum, and some diagnostic histopathology labs are switching to virtual microscopy as their main tool for the assessment of histologic specimens. Considering recent technical advancements of slide scanner and viewing software, digital pathology should now be considered a serious alternative to traditional light microscopy. This review therefore intends to give an overview of the current digital pathology technologies and their potential in all fields of veterinary pathology (ie, research, diagnostic service, and education). A future integration of digital pathology in the veterinary pathologist's workflow seems to be inevitable, and therefore it is proposed that trainees should be taught in digital pathology to keep up with the unavoidable digitization of the profession.

Synovial myxoma or myxosarcoma? Lymph node metastasis in 2 dogs.

Synovial myxoma, a rare joint tumor in dogs, has traditionally been considered benign, acknowledging that local invasion into regional tissues including bone may be present. Given the diagnostic challenges in distinguishing synovial myxoma from other joint lesions through clinical features and diagnostic imaging, definitive diagnosis relies on characteristic gross and histologic features. Within the inner surface of the joint capsule, synovial myxomas form nodules of stellate-to-spindle cells within abundant myxomatous matrix. We present here 2 cases of synovial myxoma with metastasis to regional lymph nodes and compare these 2 cases to 3 cases without evidence of lymph node metastasis. Aside from lymphovascular invasion in one case with metastasis, there were no overt histologic features of the primary tumor to suggest aggressive biologic behavior. The finding of lymph node metastasis warrants reconsideration of the term "synovial myxoma" for this neoplasm. We suggest the term "synovial myxosarcoma," considering that histologic features of the primary tumor do not predict biologic behavior. Our case series highlights the importance of lymph node sampling in suspected synovial myxosarcoma cases as well as thorough histologic examination, emphasizing careful evaluation for lymphovascular invasion.