Have the 'black clouds' cleared with new residency programme regulations?

For decades, residents believed to work harder have been referred to as having a 'black cloud'. Residency training programmes recently instituted changes to improve physician wellness and achieve comparable clinical workload. All Internal Medicine residents in the internship class of 2014 at Columbia were surveyed to assess for the ongoing presence of 'black cloud' trainees. While some residents are still thought to have this designation, they did not have a greater workload when compared to their peers.

ICRP PUBLICATION 120: Radiological protection in cardiology.

Cardiac nuclear medicine, cardiac computed tomography (CT), interventional cardiology procedures, and electrophysiology procedures are increasing in number and account for an important share of patient radiation exposure in medicine. Complex percutaneous coronary interventions and cardiac electrophysiology procedures are associated with high radiation doses. These procedures can result in patient skin doses that are high enough to cause radiation injury and an increased risk of cancer. Treatment of congenital heart disease in children is of particular concern. Additionally, staff(1) in cardiac catheterisation laboratories may receive high doses of radiation if radiological protection tools are not used properly. The Commission provided recommendations for radiological protection during fluoroscopically guided interventions in Publication 85, for radiological protection in CT in Publications 87 and 102, and for training in radiological protection in Publication 113 (ICRP, 2000b,c, 2007a, 2009). This report is focused specifically on cardiology, and brings together information relevant to cardiology from the Commission's published documents. There is emphasis on those imaging procedures and interventions specific to cardiology. The material and recommendations in the current document have been updated to reflect the most recent recommendations of the Commission. This report provides guidance to assist the cardiologist with justification procedures and optimisation of protection in cardiac CT studies, cardiac nuclear medicine studies, and fluoroscopically guided cardiac interventions. It includes discussions of the biological effects of radiation, principles of radiological protection, protection of staff during fluoroscopically guided interventions, radiological protection training, and establishment of a quality assurance programme for cardiac imaging and intervention. As tissue injury, principally skin injury, is a risk for fluoroscopically guided interventions, particular attention is devoted to clinical examples of radiation-related skin injuries from cardiac interventions, methods to reduce patient radiation dose, training recommendations, and quality assurance programmes for interventional fluoroscopy.

Fractal characterization of chromatin appearance for diagnosis in breast cytology.

This study explores the use of fractal analysis in the numerical description of chromatin appearance in breast cytology. Images of nuclei from fine-needle aspiration biopsies of the breast are characterized in terms of their Minkowski and spectral fractal dimensions, for 19 patients with benign epithelial cell lesions and 22 with invasive ductal carcinomas. Chromatin appearance in breast epithelial cell nuclear images is demonstrated to be fractal, suggesting that the three-dimensional chromatin structure in these cells also has fractal properties. A statistically significant difference between the mean spectral dimensions of the benign and malignant cases is demonstrated. The two fractal dimensions are very weakly correlated. A statistically significant difference between the benign and malignant cases in lacunarity, a fractal property characterizing the size of holes or gaps in a texture, is found over a wide range of scales. These differences are particularly pronounced at the smallest and largest scales, corresponding respectively to fine-scale texture, indicating whether chromatin is clumped or fine, and to large-scale structures like nucleoli. Logistic regression and artificial neural network classification models are developed to classify unknown cases on the basis of fractal measures of chromatin texture. Using leave-one-out cross-validation, the best logistic regression classifier correctly diagnoses 95.1 per cent of the cases. The best neural network model can correctly classify all of the cases, but it is unclear whether this is due to overtraining. Fractal dimensions and lacunarity are useful tools for the quantitative characterization of chromatin appearance, and can potentially be incorporated into image analysis devices to assure the quality and reproducibility of diagnosis by breast fine-needle aspiration biopsy.

Effect of ultrafast Papanicolaou staining on nuclear and textural features in breast cancer cytology.

OBJECTIVE: To compare quantifiable cytologic features of mammary lesions prepared using the Ultrafast Papanicolaou, Diff-Quik and Papanicolaou methods. STUDY DESIGN: Thirteen patients with mammary lesions were studied; the majority had histopathologic diagnoses of infiltrating ductal carcinoma. For each patient, three specimens were prepared, using (1) Diff-Quik staining after air drying, (2) Papanicolaou staining after wet fixation, and (3) the Ultrafast Papanicolaou procedure. Descriptors of nuclear size, shape and texture were computed from an average of 61.9 normalized nuclear images per specimen. Differences between preparation methods were analyzed using two-way analysis of variance. RESULTS: While differences in nuclear size, shape and texture existed between the three cytologic staining methods, only form factor varied significantly between conventional and Ultrafast Papanicolaou stain. Nuclear areas were larger in Ultrafast Papanicolaou specimens than conventional Papanicolaou specimens, but this difference was not statistically significant. CONCLUSION: The Ultrafast Papanicolaou procedure improves on conventional Papanicolaou staining in terms of speed, with no important quantifiable differences in nuclear morphology.

The relationships among performance measures in the selection of diagnostic tests.

Diagnostic tests are typically evaluated using performance measures, such as sensitivity, specificity, positive and negative predictive values, accuracy, and likelihood ratios. Numerous criteria have been suggested as to the types of diagnostic scenarios for which each of these measures is most important. Reports in the medical literature will often characterize a test by the values of some, but not all, of these performance measures. At times the unreported measures can be of interest in evaluating whether to use a test. A set of formulas is presented which, in many cases, enables one to determine unreported measures from those provided, for example, accuracy from sensitivity, specificity, and positive predictive value. The relationships between the measures of diagnostic test effectiveness and the prevalence of disease are discussed. An application to the diagnosis of acute myocardial infarction with new biochemical markers is used to illustrate these relationships.

Reproducibility and accuracy of interactive segmentation procedures for image analysis in cytology.

The segmentation of nuclear images is a crucial step in the development of procedures using image analysis for the cytological diagnosis of cancer. The purpose of this study is to evaluate the reproducibility and accuracy of several interactive segmentation methods which can be used in this context. Four methods were studied: a thresholding-based method enabling selection of intensity histogram contrast and brightness, manual tracing with a stylus, and arc- and ellipse-fitting routines. Features of nuclear size and shape were derived from nuclei segmented on repeated occasions by several individuals. Variance component models provided a statistical framework for evaluating the intraobserver and interobserver variability of these measurements in terms of their intraclass correlation coefficients. Of the methods tested, the arc-fitting segmentation method gave the most reproducible results, and thresholding the least. Reproducibility was generally very high both between individuals and for repeated segmentations by a single individual. Accuracies of area measurements for the various methods, as determined with respect to point counting, paralleled the reproducibilities of the methods. Sample size requirements were observed to be more dependent on the biological variability of the tissue sampled than on the particular segmentation method or on the number of individuals performing segmentation.

Ovarian dysplasia in epithelial inclusion cysts. A morphometric approach using neural networks.

BACKGROUND: Ovarian dysplasia has been described in the ovarian surface epithelium by histologic and morphometric studies. This study evaluates ovarian dysplasia in epithelial inclusion cysts adjacent to overt carcinoma and also incidentally found in ovaries removed for nonneoplastic diseases, including oophorectomies for family history of ovarian cancer, using an artificial neural network. METHODS: Histologic sections from 37 ovaries of which 26 were diagnosed with dysplasia in epithelial inclusion cysts (10 adjacent to carcinoma and 16 incidental) and 11 with benign epithelial inclusion cysts were evaluated by tracing nuclear profiles and assessing measures of nuclear area, shape, and texture. These sections were analyzed using artificial neural networks and also statistically using the Kruskal-Wallis test with the Dunn procedure to compare the morphologic similarity of dysplasia found incidentally in inclusion cysts unrelated to carcinoma from that in inclusion cysts adjacent to carcinoma. RESULTS: Neither statistical nor artificial neural network analysis was able to distinguish between incidental and adjacent dysplasia. Both types differed significantly from the control cases. CONCLUSIONS: Neural networks are powerful classification tools when applied to multiple variables extracted from individual cases. In this study, they helped to substantiate the similarity between dysplasia found incidentally and that adjacent to ovarian carcinoma. Because dysplasia represents a potential precancerous lesion, its incidental finding may help identify patients at risk for developing ovarian carcinoma.

Nuclear diffuseness as a measure of texture: definition and application to the computer-assisted diagnosis of parathyroid adenoma and carcinoma.

A measure of texture, the nuclear diffuseness, was formulated for use in biological classification, and specifically to characterize quantitatively chromatin texture. Nuclear diffuseness corresponds to the amount of local intensity variation in the digitized image of a nuclear profile. As a setting in which to test the efficacy of nuclear diffuseness as a diagnostic tool, the identification of parathyroid adenoma and carcinoma was considered. Digitized images of sections of parathyroid chief cell nuclei were obtained from 16 biopsies, and the nuclear diffuseness, as well as other morphometric descriptors, were computed. With just the average nuclear diffuseness and average nuclear profile area, jackknife (leave-one-out) classification using an artificial neural network was able to diagnose correctly and unambiguously the condition (normal, parathyroid adenoma, or parathyroid carcinoma) in 15 of 16 cases. In one case, the neural network assigned a higher weight to the correct diagnosis, but was unable to distinguish between normal and adenoma conclusively.