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Algorithmic Approach

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David P. Naidich – One of the best experts on this subject based on the ideXlab platform.

  • an Algorithmic Approach to the interpretation of diffuse lung disease on chest ct imaging a theory of almost everything
    Chest, 2020
    Co-Authors: James F Gruden, David P. Naidich, Francis Girvin, Stephen Machnicki, Stuart L Cohen, Suhail Raoof

    Abstract:

    We propose an Algorithmic Approach to the interpretation of diffuse lung disease on high-resolution CT. Following an initial review of pertinent lung anatomy, the following steps are included. Step 1: a preliminary review of available chest radiographs, including the “scanogram” obtained at the time of the CT examination. Step 2: a review of optimal methods of data acquisition and reconstruction, emphasizing the need for contiguous high-resolution images throughout the entire thorax. Step 3: initial uninterrupted scrolling of contiguous high-resolution images throughout the chest to establish the quality of examination as well as an overview of the presence and extent of disease. Step 4: determination of one of three predominant categories – primarily reticular disease, nodular disease, or diseases associated with diffuse alteration in lung density. Based on this determination, one of the three following Steps are followed: Step 5: evaluation of cases primarily involving diffuse lung reticulation; Step 6: evaluation of cases primarily resulting in diffuse lung nodules; and Step 7: evaluation of cases with diffuse alterations in lung density including those with diffusely diminished lung density vs those with heterogenous or diffusely increased lung density, respectively. It is anticipated that this Algorithmic Approach will substantially enhance initial interpretations of a wide range of pulmonary disease.

  • Lung Hyperlucency: A Clinical-Radiologic Algorithmic Approach to Diagnosis.
    Chest, 2019
    Co-Authors: Sujith V. Cherian, David P. Naidich, Jay H. Ryu, Francis Girvin, Nishant Gupta, Stephen Machnicki, Kevin K. Brown, Vishisht Mehta, Rosa M. Estrada Y Martin, Mangala Narasimhan

    Abstract:

    Areas of diminished lung density are frequently identified both on routine chest radiographs and chest CT examinations. Colloquially referred to as hyperlucent foci of lung, a broad range of underlying pathophysiologic mechanisms and differential diagnoses account for these changes. Despite this, the spectrum of etiologies can be categorized into underlying parenchymal, airway, and vascular-related entities. The purpose of this review is to provide a practical diagnostic Algorithmic Approach to pulmonary hyperlucencies incorporating clinical history and characteristic imaging patterns to narrow the differential.

  • Cavitary Lung Diseases: A Clinical-Radiologic Algorithmic Approach
    Chest, 2018
    Co-Authors: Khalid Gafoor, David P. Naidich, Shalin Patel, Francis Girvin, Nishant Gupta, Stephen Machnicki, Kevin K. Brown, Atul C. Mehta, Bryan Husta, Jay H. Ryu

    Abstract:

    Cavities occasionally are encountered on thoracic images. Their differential diagnosis is large and includes, among others, various infections, autoimmune conditions, and primary and metastatic malignancies. We offer an Algorithmic Approach to their evaluation by initially excluding mimics of cavities and then broadly classifying them according to the duration of clinical symptoms and radiographic abnormalities. An acute or subacute process (

Suhail Raoof – One of the best experts on this subject based on the ideXlab platform.

  • an Algorithmic Approach to the interpretation of diffuse lung disease on chest ct imaging a theory of almost everything
    Chest, 2020
    Co-Authors: James F Gruden, David P. Naidich, Francis Girvin, Stephen Machnicki, Stuart L Cohen, Suhail Raoof

    Abstract:

    We propose an Algorithmic Approach to the interpretation of diffuse lung disease on high-resolution CT. Following an initial review of pertinent lung anatomy, the following steps are included. Step 1: a preliminary review of available chest radiographs, including the “scanogram” obtained at the time of the CT examination. Step 2: a review of optimal methods of data acquisition and reconstruction, emphasizing the need for contiguous high-resolution images throughout the entire thorax. Step 3: initial uninterrupted scrolling of contiguous high-resolution images throughout the chest to establish the quality of examination as well as an overview of the presence and extent of disease. Step 4: determination of one of three predominant categories – primarily reticular disease, nodular disease, or diseases associated with diffuse alteration in lung density. Based on this determination, one of the three following Steps are followed: Step 5: evaluation of cases primarily involving diffuse lung reticulation; Step 6: evaluation of cases primarily resulting in diffuse lung nodules; and Step 7: evaluation of cases with diffuse alterations in lung density including those with diffusely diminished lung density vs those with heterogenous or diffusely increased lung density, respectively. It is anticipated that this Algorithmic Approach will substantially enhance initial interpretations of a wide range of pulmonary disease.

  • A practical Algorithmic Approach to the diagnosis and management of solitary pulmonary nodules: Part 2: Pretest probability and algorithm
    Chest, 2013
    Co-Authors: Vishal K. Patel, Sagar K. Naik, David P. Naidich, William D Travis, Jeremy A Weingarten, Richard Lazzaro, David D. Gutterman, Catherine Wentowski, Horiana B. Grosu, Suhail Raoof

    Abstract:

    In this second part of a two-part series, we describe an Algorithmic Approach to the diagnosis of the solitary pulmonary nodule (SPN). An essential aspect of the evaluation of SPN is determining the pretest probability of malignancy, taking into account the significant medical history and social habits of the individual patient, as well as morphologic characteristics of the nodule. Because pretest probability plays an important role in determining the next step in the evaluation, we describe various methods the physician may use to make this determination. Subsequently, we outline a simple yet comprehensive algorithm for diagnosing a SPN, with distinct pathways for the solid and subsolid SPN.

Edieal J. Pinker – One of the best experts on this subject based on the ideXlab platform.

  • Introduction to the OR Forum Article: “An Algorithmic Approach to Linear Regression”.
    Operations Research, 2016
    Co-Authors: Edieal J. Pinker

    Abstract:

    Comment on “An Algorithmic Approach to Linear Regression” by Dimitris Bertsimas and Angela King.