Biostatistics for Radiologists: Planning, Performing, and by Francesco Sardanelli MD, Giovanni Di Leo Dr.Sci. (auth.)

By Francesco Sardanelli MD, Giovanni Di Leo Dr.Sci. (auth.)

Many radiological manuscripts are pressured through barriers on the subject of research layout, definition of enrollment standards and traditional of reference, loss of initial estimation of pattern dimension, and wrong use of statistical exams. those boundaries occasionally oblige the reviewer to suggest rejection of a manuscript extra often than may be the case if rejection have been established exclusively on inherent blunders in technical functionality or interpretation of imaging modalities.

An underlying target of this publication is to facilitate the interplay among radiologists and statisticians by way of explaining the fundamentals of statistical tools as utilized to scientific imaging. The goal is to aid advance a fashion of considering past purely find out how to practice calculations and get p values. therefore, radiologists could be capable of resolve small statistical difficulties and, extra importantly, to imagine the precise point of view throughout the the most important part while a research is deliberate and undertaken.

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Additional info for Biostatistics for Radiologists: Planning, Performing, and Writing a Radiologic Study

Sample text

Sensitivity and specificity should be used to refer to the intrinsic diagnostic performance of a given examination while predictive values enable us to evaluate the reliability of the results of the same examination once it is permormed. It should be borne in mind that these are not the same thing, as we will explain by demonstrating the influence of disease prevalence on predictive values. 5). ) to perform the examination, and on the radiologist’s skill in interpreting the examination. Sensitivity and specificity are not influenced by the disease prevalence in the study population (they are instead influenced by the degree, the stage of the disease, as we will demonstrate in the next section).

For instance, if we state that computed tomography (CT) is highly “specific” for the diagnosis of intracranial hemorrhage, we would mean that this imaging modality can reliably identify a hyperattenuation on nonenhanced scans as a hemorrhage. However, this statement has two different meanings: if really there is an intracranial hemorrhage, it is highly probable that CT can detect it; a CT diagnosis of intracranial hemorrhage is rarely a false positive. Using correct scientific terminology, these two sentences are the same as saying that CT has both high sensitivity and high positive predictive value for intracranial hemorrhage.

Throughout the book the reader will find several mathematical formulas. These have been included in their entirety for the readers willing to understand the mechanism of computing. However, a thorough understanding of the formulas is by no means required to grasp the general sense of the concepts and their practical use. Introduction 15 It is far from our intention to educate radiologists so that they can replace statisticians, as this appears neither possible nor useful. Instead it is our aim educate radiologists so that they may interact with statisticians with proficiency and critical judgment.

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