A novel, rapid, and low cost method for preparing tissues with metallic stents for routine histology.

BACKGROUND: Coronary artery stenting has become a common procedure and cardiovascular pathology specimens containing these metallic stents are accordingly becoming common. Histologic examination of stented vessels is imperative, but special techniques are needed due to the presence of metal within the tissue. We describe a rapid and inexpensive method for preparing stented vascular specimens for routine histology suitable for use in almost any histology laboratory. DESIGN: After formalin fixation and decalcification, stented vascular segments were freeze-embedded and sectioned using a handheld power micro cutoff wheel tool into ~1 mm slices. Sections were allowed to thaw and the strut shards removed with fine forceps. No longer containing metal, the sections were processed for routine paraffin embedding, microtomy and staining. RESULTS: Histologic sections showed only minor tissue disruption around the stent struts. In our experience with 25 stented arteries (mean interval from implantation 5.6 years), the mean subjective section quality score was 4.1 out of 5. The position of each strut could easily be determined, along with neointimal in-stent restenosis and thrombosis. Local reaction to each strut could be surmised even if minor tissue disruption occurred. The entire process was completed in 2-3 days. The incremental cost over that of routine histology is nominal. CONCLUSION: This method for examining stented vascular segments histologically could readily be applied in most pathology laboratories and serves as a highly practical solution to dilemma of examining stents histologically.

Optimizing the Use of Gene Expression Profiling in Early-Stage Breast Cancer.

Purpose Gene expression profiling assays are frequently used to guide adjuvant chemotherapy decisions in hormone receptor-positive, lymph node-negative breast cancer. We hypothesized that the clinical value of these new tools would be more fully realized when appropriately integrated with high-quality clinicopathologic data. Hence, we developed a model that uses routine pathologic parameters to estimate Oncotype DX recurrence score (ODX RS) and independently tested its ability to predict ODX RS in clinical samples. Patients and Methods We retrospectively reviewed ordered ODX RS and pathology reports from five institutions (n = 1,113) between 2006 and 2013. We used locally performed histopathologic markers (estrogen receptor, progesterone receptor, Ki-67, human epidermal growth factor receptor 2, and Elston grade) to develop models that predict RS-based risk categories. Ordering patterns at one site were evaluated under an integrated decision-making model incorporating clinical treatment guidelines, immunohistochemistry markers, and ODX. Final locked models were independently tested (n = 472). Results Distribution of RS was similar across sites and to reported clinical practice experience and stable over time. Histopathologic markers alone determined risk category with > 95% confidence in > 55% (616 of 1,113) of cases. Application of the integrated decision model to one site indicated that the frequency of testing would not have changed overall, although ordering patterns would have changed substantially with less testing of estimated clinical risk-high or clinical risk-low cases and more testing of clinical risk-intermediate cases. In the validation set, the model correctly predicted risk category in 52.5% (248 of 472). Conclusion The proposed model accurately predicts high- and low-risk RS categories (> 25 or ≤ 25) in a majority of cases. Integrating histopathologic and molecular information into the decision-making process allows refocusing the use of new molecular tools to cases with uncertain risk.