Two histologic alterations found to be significantly different between the 35 and 39 and greater than 40 age subgroups were fetal vascular malperfusion (11% [7 of 65] versus 42% [43 of 103]; P = .001) and delayed villous maturation (1.5% [1 of 65] versus 13% [13 of 103]; P = .02). The pure AMA subgroup showed no statistically significant differences compared with the overall AMA group. Chronic deciduitis was the only statistically significant difference between the overall AMA group and the non-AMA comparison group (14% [23 of 168] versus 30% [18 of 60]; P = .02). CONCLUSIONS.— Our findings, particularly the high frequency of fetal vascular malperfusion, suggest that AMA should be an independent indication for placental pathologic examination.CONTEXT.— Apixaban causes a false increase in activated protein C resistance (APCR) ratios and possibly protein S activity. OBJECTIVE.— To investigate whether this increase can mask a diagnosis of factor V Leiden (FVL) or protein S deficiency in an actual population of patients undergoing apixaban treatment and hypercoagulation testing. DESIGN.— During a 4.5-year period involving 58 patients, we compared the following 4 groups heterozygous for FVL (FVL-HET)/taking apixaban, wild-type/taking apixaban, heterozygous for FVL/no apixaban, and normal APCR/no apixaban. Patients taking apixaban were also tested for protein S functional activity and free antigen (n = 40). RESULTS.— FVL-HET patients taking apixaban had lower APCR ratios than wild-type patients (P less then .001). Activated protein C resistance in FVL-HET patients taking apixaban fell more than 3 SD below the cutoff of 2.2 at which the laboratory reflexes FVL DNA testing. No cases of FVL were missed despite apixaban. In contrast to rivaroxaban, apixaban did not interfere with the assessment of protein S activity (mean activity 93.9 IU/dL, free antigen 93.1 IU/dL, P = .39). A total 3 of 40 patients (8%) had low free protein S antigen (30, 55, and 57 IU/dL), with correspondingly similar activity results (27, 59, and 52 IU/dL, respectively). Apixaban did not cause a missed diagnosis of protein S deficiency. CONCLUSIONS.— Despite apixaban treatment, APCR testing can distinguish FVL-HET from healthy patients, rendering indiscriminate FVL DNA testing of all patients on apixaban unnecessary. Apixaban did not affect protein S activity.CONTEXT.— Accurate HER2 testing in breast cancer is crucial for appropriate precision therapy. HER2 testing is most commonly accomplished by a combination of immunohistochemistry and in situ hybridization techniques, as gene amplification is closely tied to protein overexpression. During the last 5+ years, brightfield dual in situ hybridization (DISH) has replaced fluorescence methods (fluorescence in situ hybridization [FISH]) in some laboratories. OBJECTIVE.— To analyze routine HER2 DISH performance in the field. DESIGN.— We reviewed our experience with HER2 DISH performed at outside laboratories and referred for patient care. RESULTS.— Of 273 identified retrospective DISH results, 55 had repeated FISH testing at our institution; 7 (13%) were discordant. Additional cases had technical flaws hampering appropriate scoring. In 23 cases (42%), HER2 DISH was performed without immunohistochemistry. Slide review of a prospective cohort of 42 consecutive DISH cases revealed 14 (33%) with technical or interpretative limitations potentially jeopardizing results. Commonly identified problems include lack of or weak signals in most tumor cells, and silver precipitate or red signals outside of nuclei, resulting in false-negative or false-positive interpretations, respectively. Further, 44% (24 of 55) of DISH reports lacked complete data, specifically average HER2 signals/cell. CONCLUSIONS.— While HER2 DISH can be an efficient and effective alternative to FISH, we illustrate pitfalls and reinforce that careful attention to slide quality and technical parameters are critically important. HER2 DISH cotesting with immunohistochemistry could help minimize false-negative or false-positive HER2 results.OBJECTIVE To compare standard specimen mammography (SSM) with remote intraoperative specimen mammography (ISM) assessment in breast conserving-surgery (BCS) based on operative times, intraoperative additional excision (IAE) and re-intervention rates. METHODS AND MATERIALS We retrospectively compared 129 consecutive patients (136 lesions) who had BCS with SSM at our centre between 11/2011 and 02/2013 with 138 consecutive patients (144 lesions) who underwent BCS with ISM between 08/2014 and 02/2015.SSM or ISM were performed to confirm the target lesions within the excised specimen and margin adequacy. The utility of SMM and ISM was evaluated considering pathology as gold-standard, using χ2 or Fisher's exact tests for comparison of categorical variables, and non-parametric Mann-Whitney test for continuous variables. RESULTS The two groups did not statistically differ for age (p = 0.20), lesion size (p = 0.29) and morphology (p = 0.82) or tumor histology type (p = 0.65). Intraoperative time was significantly longer (p less then 0.00001) for SSM (132 ± 43 min) than for ISM (90 ± 42 min). The proportions requiring IAE did not significantly differ between SSM group (39/136 lesions (40%)) and ISM group (52/144 lesions (57%)) (p = 0.19), overall and in stratified analysis by mammographic features. Selleck 3-Amino-9-ethylcarbazole Re-intervention rates were not statistically different between the two groups [SSM19/136 (14%), ISM13/144 (9%); p = 0.27]. CONCLUSION The introduction of ISM in BCS significantly reduced surgical time but did not change IAE and re-intervention rates, highlighting facilitated communication between surgeons and radiologists. ADVANCES IN KNOWLEDGE Compared to standard mammography imaging, the use of ISM significantly reduced surgical time.Historically, medical imaging has been a qualitative or semi-quantitative modality. It is difficult to quantify what can be seen in an image, and to turn it into valuable predictive outcomes. As a result of advances in both computational hardware and machine learning algorithms, computers are making great strides in obtaining quantitative information from imaging and correlating it with outcomes. Radiomics, in its two forms "handcrafted and deep," is an emerging field that translates medical images into quantitative data to yield biological information and enable radiologic phenotypic profiling for diagnosis, theragnosis, decision support, and monitoring. Handcrafted radiomics is a multistage process in which features based on shape, pixel intensities, and texture are extracted from radiographs. Within this review, we describe the steps starting with quantitative imaging data, how it can be extracted, how to correlate it with clinical and biological outcomes, resulting in models that can be used to make predictions, such as survival, or for detection and classification used in diagnostics.