Felipe de Galiza Barbosa1. 1. MD, Radiologist, Subspecialization in Abdominal Imaging and Hybrid Imaging Methods (PET/CT and PET/MR) at Hospital Sírio-Libanês and at Universidade de São Paulo (USP), São Paulo, SP, Brazil. E-mail: felipegaliza@gmail.com .
In recent decades, we have been faced with an increasing number of thoracic computed
tomography (CT) examinations worldwide, an increase that can be partially attributed to
the growing number of lung cancer screening programs. In addition, the development of
scanners with higher spatial resolution has increased the number of solitary pulmonary
nodules (SPNs) diagnosed per day(.
Probabilistic models for predicting cancer in SPNs can be very important to facilitating
patient management and avoiding unnecessary expenses. Studies have shown that
18F-fluorodeoxyglucose positron-emission tomography/computed tomography
(FDG-PET/CT) is another valuable imaging modality for the assessment of indeterminate
SPNs(, improving accuracy in
the differentiation between benign and malignant nodules, as well as informing the
decision-making process related to patient management.In the previous issue of Radiologia Brasileira, Mosmann et al. published the
article "Solitary pulmonary nodule and 18F-FDG PET/CT. Part 1: epidemiology,
morphological evaluation and probability of cancer"(, which provides a very interesting detailed review of SPN
evaluation and FDG-PET/CT. The authors discuss the background of the two components of
this hybrid method (PET and CT) individually. This first part of the article presents a
brief, concise overview regarding the morphologic assessment of SPNs by CT and puts all
of that information into clinical perspective by presenting the current models to
predict malignancy in pulmonary nodules. Other studies in the literature have discussed
the morphological characteristics of SPNs and their unique cancer potential(. Truong et al.(
summarized the CT aspects of SPNs by subtype (solid or part-solid), correlating each
with its own additional tumor risk.In clinical practice, the management of pulmonary nodules can involve a wide variety of
choices, from the imaging method to be employed to the invasive approach used in their
diagnosis and treatment. The implementation of probabilistic models can be helpful in
stratifying patients by cancer risk, consequently playing an important role in the
clinical decision-making process. The Mosmann et al. article provides a comprehensive
explanation of the models currently in clinical use(. Such an approach can have additional value while there is
increasing discussion regarding the funding of health care systems in Western countries,
including Brazil.In addition to evaluating the morphology of SPNs, in recent decades there has been
increasing interest in studying other parameters, such as nodule metabolism (with
FDG-PET) and perfusion (with contrast-enhanced imaging studies), to predict malignancy.
In this "Part 1" article(, Mosmann et
al. conclude by summing up all of the important clinical information about the most
widely used hybrid imaging method for metabolic evaluation, PET/ CT. The literature
corroborates the important role that PET/CT plays in the evaluation of SPNs(, showing it to be superior to contrast-enhanced imaging methods. There
is a very real possibility that PET/CT will become even more relevant with the upcoming
advances in PET digital detector technology, which will provide higher spatial
resolution and improve image quality(, making the PET evaluation of smaller pulmonary nodules more reliable,
with acceptable accuracy.Finally, I would like to congratulate the authors for conducting a comprehensive and
practical review of such a relevant topic, especially for including probabilistic models
to predict cancer in SPNs. In the context of the current discussion of health care
system funding worldwide, realistic approaches to be discussed are always welcome.
Authors: Mylene T Truong; Jane P Ko; Santiago E Rossi; Ignacio Rossi; Chitra Viswanathan; John F Bruzzi; Edith M Marom; Jeremy J Erasmus Journal: Radiographics Date: 2014-10 Impact factor: 5.333
Authors: Ober van Gómez López; Ana María García Vicente; Antonio Francisco Honguero Martínez; Germán Andrés Jiménez Londoño; Carlos Hugo Vega Caicedo; Pablo León Atance; Ángel María Soriano Castrejón Journal: Transl Lung Cancer Res Date: 2015-06
Authors: M Dabrowska; R Krenke; P Korczynski; M Maskey-Warzechowska; M Zukowska; J Kunikowska; T Orłowski; R Chazan Journal: Medicine (Baltimore) Date: 2015-04 Impact factor: 1.889