Novelties in Imaging of Thoracic Sarcoidosis

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Abstract

Sarcoidosis is a systemic granulomatous disease affecting various organs, and the lungs are the most commonly involved. According to guidelines, diagnosis relies on a consistent clinical picture, histological demonstration of non-caseating granulomas, and exclusion of other diseases with similar histological or clinical picture. Nevertheless, chest imaging plays an important role in both diagnostic assessment, allowing to avoid biopsy in some situations, and prognostic evaluation. Despite the demonstrated lower sensitivity of chest X-ray (CXR) in the evaluation of chest findings compared to high-resolution computed tomography (HRCT), CXR still retains a pivotal role in both diagnostic and prognostic assessment in sarcoidosis. Moreover, despite the huge progress made in the field of radiation dose reduction, chest magnetic resonance (MR), and quantitative imaging, very little research has focused on their application in sarcoidosis. In this review, we aim to describe the latest novelties in diagnostic and prognostic assessment of thoracic sarcoidosis and to identify the fields of research that require investigation.

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Most cited references 43

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Reduced lung-cancer mortality with low-dose computed tomographic screening.

(2011)

The aggressive and heterogeneous nature of lung cancer has thwarted efforts to reduce mortality from this cancer through the use of screening. The advent of low-dose helical computed tomography (CT) altered the landscape of lung-cancer screening, with studies indicating that low-dose CT detects many tumors at early stages. The National Lung Screening Trial (NLST) was conducted to determine whether screening with low-dose CT could reduce mortality from lung cancer. From August 2002 through April 2004, we enrolled 53,454 persons at high risk for lung cancer at 33 U.S. medical centers. Participants were randomly assigned to undergo three annual screenings with either low-dose CT (26,722 participants) or single-view posteroanterior chest radiography (26,732). Data were collected on cases of lung cancer and deaths from lung cancer that occurred through December 31, 2009. The rate of adherence to screening was more than 90%. The rate of positive screening tests was 24.2% with low-dose CT and 6.9% with radiography over all three rounds. A total of 96.4% of the positive screening results in the low-dose CT group and 94.5% in the radiography group were false positive results. The incidence of lung cancer was 645 cases per 100,000 person-years (1060 cancers) in the low-dose CT group, as compared with 572 cases per 100,000 person-years (941 cancers) in the radiography group (rate ratio, 1.13; 95% confidence interval [CI], 1.03 to 1.23). There were 247 deaths from lung cancer per 100,000 person-years in the low-dose CT group and 309 deaths per 100,000 person-years in the radiography group, representing a relative reduction in mortality from lung cancer with low-dose CT screening of 20.0% (95% CI, 6.8 to 26.7; P=0.004). The rate of death from any cause was reduced in the low-dose CT group, as compared with the radiography group, by 6.7% (95% CI, 1.2 to 13.6; P=0.02). Screening with the use of low-dose CT reduces mortality from lung cancer. (Funded by the National Cancer Institute; National Lung Screening Trial ClinicalTrials.gov number, NCT00047385.).

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Radiomics and radiogenomics in lung cancer: A review for the clinician.

Rajat Thawani, Michael McLane, Niha Beig … (2018)

Lung cancer is responsible for a large proportion of cancer-related deaths across the globe, with delayed detection being perhaps the most significant factor for its high mortality rate. Though the National Lung Screening Trial argues for screening of certain at-risk populations, the practical implementation of these screening efforts has not yet been successful and remains in high demand. Radiomics refers to the computerized extraction of data from radiologic images, and provides unique potential for making lung cancer screening more rapid and accurate using machine learning algorithms. The quantitative features analyzed express subvisual characteristics of images which correlate with pathogenesis of diseases. These features are broadly classified into four categories: intensity, structure, texture/gradient, and wavelet, based on the types of image attributes they capture. Many studies have been done to show correlation between these features and the malignant potential of a nodule on a chest CT. In cancer patients, these nodules also have features that can be correlated with prognosis and mutation status. The major limitations of radiomics are the lack of standardization of acquisition parameters, inconsistent radiomic methods, and lack of reproducibility. Researchers are working on overcoming these limitations, which would make radiomics more acceptable in the medical community.

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Effective doses in radiology and diagnostic nuclear medicine: a catalog.

Mahadevappa Mahesh, Bret A Mettler, Walter Huda … (2008)

Medical uses of radiation have grown very rapidly over the past decade, and, as of 2007, medical uses represent the largest source of exposure to the U.S. population. Most physicians have difficulty assessing the magnitude of exposure or potential risk. Effective dose provides an approximate indicator of potential detriment from ionizing radiation and should be used as one parameter in evaluating the appropriateness of examinations involving ionizing radiation. The purpose of this review is to provide a compilation of effective doses for radiologic and nuclear medicine procedures. Standard radiographic examinations have average effective doses that vary by over a factor of 1000 (0.01-10 mSv). Computed tomographic examinations tend to be in a more narrow range but have relatively high average effective doses (approximately 2-20 mSv), and average effective doses for interventional procedures usually range from 5-70 mSv. Average effective dose for most nuclear medicine procedures varies between 0.3 and 20 mSv. These doses can be compared with the average annual effective dose from background radiation of about 3 mSv. (c) RSNA, 2008.

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Author and article information

Contributors

Philippe Guilpain: Role: Academic Editor

Cosima Schiavone: Role: Academic Editor

Journal

Journal ID (nlm-ta): J Clin Med

Journal ID (iso-abbrev): J Clin Med

Journal ID (publisher-id): jcm

Title: Journal of Clinical Medicine

Publisher: MDPI

ISSN (Electronic): 2077-0383

Publication date (Electronic): 21 May 2021

Publication date Collection: June 2021

Volume: 10

Issue: 11

Electronic Location Identifier: 2222

Affiliations

[1 ]Department of Diagnostic Imaging, Oncological Radiotherapy and Hematology, Fondazione Policlinico Universitario “A. Gemelli” IRCCS, 00168 Rome, Italy; lucio.calandriello@ 123456policlinicogemelli.it (L.C.); annemilia.delciello@ 123456policlinicogemelli.it (A.d.C.); alessandra.farchione@ 123456policlinicogemelli.it (A.F.); riccardo.manfredi@ 123456policlinicogemelli.it (R.M.); annarita.larici@ 123456policlinicogemelli.it (A.R.L.)

[2 ]Section of Radiology, Department of Radiological and Hematological Sciences, Università Cattolica del Sacro Cuore, 00168 Rome, Italy; rosadabronzo@ 123456hotmail.it (R.D.); strappacecilia@ 123456gmail.com (C.S.)

[3 ]Pulmonary Medicine Unit, Department of Medical and Surgical Sciences, Fondazione Policlinico Universitario “A. Gemelli” IRCCS, 00168 Rome, Italy; giuliana.pasciuto@ 123456policlinicogemelli.it

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[* ]Correspondence: giuseppe.cicchetti@ 123456guest.policlinicogemelli.it

Author information

Rosa D’Abronzo https://orcid.org/0000-0002-8569-3525

Giuseppe Cicchetti https://orcid.org/0000-0001-8714-3124

Annemilia del Ciello https://orcid.org/0000-0001-7172-7387

Alessandra Farchione https://orcid.org/0000-0002-5504-5340

Cecilia Strappa https://orcid.org/0000-0002-0506-0083

Anna Rita Larici https://orcid.org/0000-0002-1882-6244

Article

Publisher ID: jcm-10-02222

DOI: 10.3390/jcm10112222

PMC ID: 8196662

PubMed ID: 34063811

SO-VID: 846cf238-c8e5-4fb5-a876-e368eb9919e9

License:

Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

Novelties in Imaging of Thoracic Sarcoidosis

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Most cited references 43

Reduced lung-cancer mortality with low-dose computed tomographic screening.

Radiomics and radiogenomics in lung cancer: A review for the clinician.

Effective doses in radiology and diagnostic nuclear medicine: a catalog.

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