The value of sputum cytology

microRNAs in exhaled breath condensate for diagnosis of lung cancer in a resource-limited setting: a concise review

Lung cancer is one of the common cancers globally with high mortality and poor prognosis. Most cases of lung cancer are diagnosed at an advanced stage due to limited diagnostic resources. Screening modalities, such as sputum cytology and annual chest radiographs, have not proved sensitive enough to impact mortality. In recent years, annual low-dose computed tomography has emerged as a potential screening tool for early lung cancer detection, but it may not be a feasible option for developing countries. In this context, exhaled breath condensate (EBC) analysis has been evaluated recently as a noninvasive tool for lung cancer diagnosis. The breath biomarkers also have the advantage of differentiating various types and stages of lung cancer. Recent studies have focused more on microRNAs (miRNAs) as they play a key role in tumourigenesis by regulating the cell cycle, metastasis and angiogenesis. In this review, we have consolidated the current published literature suggesting the utility of miRNAs in EBC for the detection of lung cancer.

A Review of Deep Learning Techniques for Lung Cancer Screening and Diagnosis Based on CT Images

One of the most common and deadly diseases in the world is lung cancer. Only early identification of lung cancer can increase a patient's probability of survival. A frequently used modality for the screening and diagnosis of lung cancer is computed tomography (CT) imaging, which provides a detailed scan of the lung. In line with the advancement of computer-assisted systems, deep learning techniques have been extensively explored to help in interpreting the CT images for lung cancer identification. Hence, the goal of this review is to provide a detailed review of the deep learning techniques that were developed for screening and diagnosing lung cancer. This review covers an overview of deep learning (DL) techniques, the suggested DL techniques for lung cancer applications, and the novelties of the reviewed methods. This review focuses on two main methodologies of deep learning in screening and diagnosing lung cancer, which are classification and segmentation methodologies. The advantages and shortcomings of current deep learning models will also be discussed. The resultant analysis demonstrates that there is a significant potential for deep learning methods to provide precise and effective computer-assisted lung cancer screening and diagnosis using CT scans. At the end of this review, a list of potential future works regarding improving the application of deep learning is provided to spearhead the advancement of computer-assisted lung cancer diagnosis systems.

Current and Future Development in Lung Cancer Diagnosis

Lung cancer is the leading cause of cancer-related deaths in North America and other developed countries. One of the reasons lung cancer is at the top of the list is that it is often not diagnosed until the cancer is at an advanced stage. Thus, the earliest diagnosis of lung cancer is crucial, especially in screening high-risk populations, such as smokers, exposure to fumes, oil fields, toxic occupational places, etc. Based on the current knowledge, it looks that there is an urgent need to identify novel biomarkers. The current diagnosis of lung cancer includes different types of imaging complemented with pathological assessment of biopsies, but these techniques can still not detect early lung cancer developments. In this review, we described the advantages and disadvantages of current methods used in diagnosing lung cancer, and we provide an analysis of the potential use of body fluids as carriers of biomarkers as predictors of cancer development and progression.

Exfoliative sputum cytology of cancers metastatic to the lung

Although largely replaced by fine-needle aspiration (FNA) and bronchoscopy, cytological examination of sputum for exfoliated malignant cells still is considered a valuable initial diagnostic test in patients presenting with a lung mass. Thirty-five cases of secondary/metastatic tumors involving the lung and diagnosed on sputum were retrospectively reviewed from our cytopathology files for a period of 22 yr (1980-2001). Clinical history and the relevant histopathological material were examined and correlated with the cytological findings. In all cases, a history of malignancy was known. Cytological diagnoses included colonic adenocarcinoma (7 cases); non-Hodgkin's lymphoma (NHL; 5 cases); malignant melanoma (MM; 5 cases); breast carcinoma (5 cases); Hodgkin's lymphoma (HL; 3 cases); pancreatic adenocarcinoma (2 cases); prostatic adenocarcinoma (2 cases); and 1 case each of urothelial carcinoma, endometrial carcinoma, renal cell carcinoma, hepatic small-cell carcinoma, squamous-cell carcinoma (cervix), and leiomyosarcoma (LMS). Cellular preservation was optimal in all cases. The smear background was relatively clean in 25 (71%) cases and predominantly inflamed and/or necrotic in 10 (29%) cases. In non-lymphoid tumors (27 cases), isolated single malignant cells were seen in 7 (26%) cases (all cases of MM and prostatic adenocarcinoma), whereas 20 (74%) cases displayed fragments with intact tumor architecture. Overall, only 10/35 (29%) cases showed noticeable tumor-cell necrosis. In one case (LMS), cell block sections were used for immunoperoxidase (IPOX) studies with positive staining for desmin and actin. Exfoliation of cancer cells in sputum from secondary tumors in the lung is a rare phenomenon in current-day practice, with metastatic colonic adenocarcinoma seen most commonly. Intact tumor architecture was observed in exfoliated cells in 75% of the cases.

Estimation of performance and sequential selection of diagnostic tests in patients with lung lesions suspicious for cancer

CONTEXT

Measuring variation in clinician test ordering behavior for patients with similar indications is an important focus for quality management and cost containment.

OBJECTIVE

To obtain information from physicians and nonphysicians regarding their test-ordering behavior and their knowledge of test performance characteristics for diagnostic tests used to work up patients with lung lesions suspicious for cancer.

DESIGN

A self-administered, voluntary, anonymous questionnaire was distributed to 452 multiple-specialty physicians and 500 nonphysicians in academic and private practice in Pennsylvania, Iowa, and North Carolina. Respondents indicated their estimates of test sensitivities for multiple tests used in the diagnosis of lung lesions and provided their test selection strategy for case simulations of patients with solitary lung lesions. Data were analyzed using descriptive statistics and the chi(2) test.

RESULTS

The response rate was 11.2%. Both physicians and nonphysicians tended to underestimate the sensitivities of all minimally invasive tests, with the greatest underestimations reported for sputum cytology and transthoracic fine-needle aspiration biopsy. There was marked variation in sequential test selection for all the case simulations and no association between respondent perception of test sensitivity and their selection of first diagnostic test. Overall, the most frequently chosen first diagnostic test was bronchoscopy.

CONCLUSIONS

Physicians and nonphysicians tend to underestimate the performance of diagnostic tests used to evaluate solitary lung lesions. However, their misperceptions do not appear to explain the wide variation in test-ordering behavior for patients with lung lesions suspicious for cancer.

Prevention of lung cancer: the key is to stop smoking

OBJECTIVES

To review current approaches to primary prevention of lung cancer and to screening for precarcinogenic or preclinical asymptomatic disease.

DATA SOURCES

Research studies, review articles, and government reports relating to prevention of lung cancer and strategies for smoking cessation.

CONCLUSIONS

Because almost 90% of lung cancer cases can be attributed to tobacco, reduction of smoking is the appropriate focus of lung cancer prevention efforts. Lung cancer chemoprevention remains an experimental approach and large scale screening for lung cancer is of limited value.

IMPLICATIONS FOR NURSING PRACTICE

Nurses are in a strategic position to prevent smoking initiation and to influence successful smoking cessation through education, information on the multiple modalities to assist behavioral change, and ongoing reinforcement.

Small cell lung cancer. Case report

The selection of appropriate chemotherapeutic and/or radiation therapy for small cell lung cancer should be done after careful diagnosis and staging workup. A patient with small cell lung cancer is presented and explanation given for each step in diagnosis and staging.