Download Biostatistics for Radiologists: Planning, Performing, and by Francesco Sardanelli, Giovanni Di Leo PDF

By Francesco Sardanelli, Giovanni Di Leo

The goal of this publication is to give statistical difficulties and strategies in a pleasant strategy to radiologists, emphasizing statistical concerns and strategies most often utilized in radiological stories (e.g., nonparametric checks, research of intra- and interobserver reproducibility, comparability of sensitivity and specificity between diversified imaging modality, distinction among scientific and screening software of diagnostic exams, ect.). The checks may be awarded ranging from a radiological "problem" and all examples of statistical tools purposes could be "radiological".

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Extra resources for Biostatistics for Radiologists: Planning, Performing, and Writing a Radiologic Study

Example text

In practice, it is a kind of “mean” between sensitivity and specificity which is weighted for disease prevalence. Dependence on disease prevalence is the feature shared with the predictive values. 1. show the dependence of predictive values and overall accuracy on disease prevalence. 3. Predictive values of clinical and screening mammography. Imagine 10,000 women with a palpable lump are studied (clinical mammography), with 95% sensitivity and 80% specificity. With a disease prevalence of 50%, we would have 4,750 true positives, 4,000 true negatives, 1,000 false positives, and 250 false negatives.

More importantly, we should fully understand what changes when the statistical unit is no longer the patient (or the subject) but each lesion (or finding). Of course, if each patient has no lesions or only one lesion, we have no consequences in statistical calculations. But a patient can have more than one lesion, as typically we find in the study of liver metastases. The same reasoning can be applied to each of the two kidneys, breasts, lungs, or to a single lobe or segment of the brain, liver, lung, prostate, coronary tree, etc.

Cardiac CT for diagnosing coronary stenoses. Let us suppose that 64-row multislice CT scanners have a 95% sensitivity and a 95% specificity for clinically significant (≥ 50% reduction in lumen diameter) coronary stenoses. If we were to perform the examination (with intravenous administration of iodinated contrast medium) on 100,000 subjects with a high pretest probability of significant stenoses (80% disease prevalence), we would negate a therapeutic coronary angiography (with stenting of the stenosis) in all the false negative subjects, equal to 5% (4,000 patients).

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